IN DEGREE PROJECT MATERIALS SCIENCE AND ENGINEERING,SECOND CYCLE, 30 CREDITS

, STOCKHOLM SWEDEN 2020

Inoculant measurement with thermal analysis

CHRISTOPHER ARMSTRONG

KTH ROYAL INSTITUTE OF TECHNOLOGYSCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT

Abstract Over time the level of inoculant will decrease due to fading and this needs to be compensated by

more additions of inoculant. When casting CGI400 at Scania a one-step method is used, and the

inoculant additions are based on the last ladle from the previous oven. Longer stops in production

will result in the previous oven not being representable and more inoculant should be added. A

method to establish the inoculation level of the base iron in the oven would make it easier to control

the process.

This study was about inoculation measurements with the help of thermo- analysis of the melt in the

oven to get a better understanding how it fluctuates between ovens and changes over time. The

study is also about how to implement this tool into production in a foundry.

With the help of thermo- analytic measurements, the inoculation level of the melt was established,

and the method was also used to see how the level of inoculant changed over. To establish the

inoculation additions needed, the saturation point of inoculant was investigated.

The results from the study shows that the starting level of inoculant is too low in the melt it also

shows that the inoculation level fluctuates over time. The conclusions that can be drawn from this

study is that thermos analysis can be used in production to establish the inoculation level, but more

measurements needs to be conducted to determine its accuracy.

Keywords:

Thermal Analysis, Inoculation, Nucleation, Compacted Graphite Iron, CGI, Cast Iron, Material

Properties

Sammanfattning Över tid så minskar ympnivån i en smälta på grund av fading och detta måste kompenseras med mer

tillsatser av ymp. Vid gjutning av CGI400 på Scania används en en-stegs metod där man baserar

ymptillsatsen i skänken på vad ympnivån var i sista skänken från den tidigare ugnen. Vid längre

produktionsstopp kommer inte ympnivån från ugnen innan vara representativ utan mer ymp måste

tillsättas. En metod för att bestämma ympnivån av basjärnet i ugnen skulle göra det lättare att styra

processen.

Denna studie handlar om ympmätning med hjälp av termisk analys i bas smälta för att få en bättre

förståelse för hur den fluktuerar mellan ugnar och ändras över tid. Studien handlar också om hur

man ska kunna applicera denna mätmetod i produktionen på ett gjuteri.

Med hjälp av termo analytiska mätningar skulle grundnivån av ymp i smältan bestämmas och även

för att se hur nivån ändrades över tiden. För att bestämma tillsatsen av ymp som borde tillföras

undersöktes mättnadspunkten av ymp och hur den kunde tillsättas i skänk.

Resultaten från studien visar att grundnivån av ymp är för låg och resultaten visar också att nivån av

ymp fluktuerar både upp och ner ökar tid vilket inte var vad man hade förväntat sig och även det

finns flera faktorer som kan påverka nivån. Slutsatsen som kan dras är att termisk analys kan

användas i produktion för att bestämma ympnivån, men mer mätningar behövs för att bestämma

dess noggrannhet.

List of abbreviations:

CGI- Compacted graphite Iron

LGI- Lamellar graphite iron

SGI- Spheroidal graphite iron

TEmin- Eutectic minimum temperature

DTEmin- Difference in eutectic minimum temperature

TL- Liquidus temperature

SEM- Scanning electron microscope

LOM- Light optical microscope

CE- Carbon equivalent

CEL- Carbon equivalent liquids

S- Saturation point

wt%- Weight percent

𝜎- Yield stress

d- Diameter

ΔG- Difference in Gibbs energy

MGM- The modification index

MGI- Inoculation index

𝑁𝑓- Grains per area

𝑁𝑤- Grains intersected in sample

𝑁𝑖- Grains inside sample

𝑅2- Coefficient of determination

Table of content

Introduction ..................................................................................................................................... 1

1.1 Ethical, social, and environmental aspect ............................................................................... 1

Theoretical background ................................................................................................................... 3

2.1 CGI ........................................................................................................................................... 4

2.2 Microstructure ......................................................................................................................... 5

2.3 Process ..................................................................................................................................... 5

2.4 Solidification ............................................................................................................................ 7

2.5 Nucleation ............................................................................................................................... 9

2.6 Defects from improper inoculation additions ....................................................................... 13

2.7 Thermal analysis .................................................................................................................... 13

2.8 Sinter cast process ................................................................................................................. 15

2.9 Thermocalc ............................................................................................................................ 16

2.10 Raw material .......................................................................................................................... 17

Experimental procedure ................................................................................................................ 17

3.1 Method .................................................................................................................................. 17

3.2 Average starting value and nucleation fading ....................................................................... 18

3.3 Saturation point ..................................................................................................................... 21

3.4 Minilab-suitcase .................................................................................................................... 21

3.5 Testing of inoculation addition in ladle ................................................................................. 23

3.6 Laboratory preparation ......................................................................................................... 24

3.7 Etching ................................................................................................................................... 25

3.8 Image J ................................................................................................................................... 27

3.9 Grain density ......................................................................................................................... 27

3.10 Grain size ............................................................................................................................... 27

3.11 Additional testing .................................................................................................................. 28

3.12 Chemical analysis................................................................................................................... 28

3.13 Thermocalc ............................................................................................................................ 29

3.14 Comparison of TL for cups ..................................................................................................... 29

Results ........................................................................................................................................... 29

4.1 Level on inoculation in oven .................................................................................................. 29

4.2 Inoculation fading over time ................................................................................................. 30

4.3 Saturation point ..................................................................................................................... 32

4.4 Testing inoculation additions to the ladle ............................................................................. 34

4.5 Grain size and density ........................................................................................................... 35

4.6 Addition of scrap iron ............................................................................................................ 36

4.7 Effects of inoculants used...................................................................................................... 37

4.8 Effects of slagging .................................................................................................................. 37

4.9 Effect of carbon additions to DTEmin ................................................................................... 37

4.10 Increased temperatures effect on DTEmin ........................................................................... 38

4.11 Comparison of nucleation level between ladle and oven ..................................................... 38

4.12 Chemical analysis................................................................................................................... 39

4.13 Charged material ................................................................................................................... 40

4.14 Thermocalc ............................................................................................................................ 40

4.15 Comparison of cups ............................................................................................................... 42

Discussion ...................................................................................................................................... 42

5.1 Average inoculation level ...................................................................................................... 42

5.2 Saturation point ..................................................................................................................... 42

5.3 Testing of inoculant additions to the ladle ............................................................................ 43

5.4 Inoculation fading over time ................................................................................................. 43

5.5 Grain size and density ........................................................................................................... 44

5.6 Addition of scrap iron ............................................................................................................ 44

5.7 Effects of inoculants used...................................................................................................... 44

5.8 Effects of carbon additions .................................................................................................... 45

5.9 Increased temperatures effect on DTEmin ........................................................................... 45

5.10 Comparison of the nucleation level between oven and ladle ............................................... 45

5.11 Chemical analysis................................................................................................................... 45

5.12 Material charged ................................................................................................................... 46

5.13 Thermocalc ............................................................................................................................ 46

5.14 Comparison of cups ............................................................................................................... 47

5.15 Overall discussion .................................................................................................................. 47

Conclusion ..................................................................................................................................... 48

Further research ............................................................................................................................ 49

Sources of error ............................................................................................................................. 49

Acknowledgment ........................................................................................................................... 50

References ................................................................................................................................. 51

1

Introduction When casting metals, the composition of the melt is very important for the finale properties of the

finished product. It is not just the alloying composition that is important also the level of inoculant

present in the melt plays a significant role. These are the starting points for the metals nucleation

and will have a big effect on material properties such as the strength, ductility, and the thermal

conductivity.

When producing cast iron today an analysation of the nucleation level takes place in the ladle at the

foundry at Scania. Additions of inoculant and magnesium (Mg) to alter the graphite precipitation is

added to the ladle before the sample is taken. It takes several minutes for the software to analyse

the sample, valuable processing time and time where the melt in the ladle’s temperature is

constantly dropping. Therefore, the melt is cast before the results of the test is received. Depending

on the results, the base treatment will be altered for the next ladle to reach the required levels of

inoculant and Mg. The first ladles additions are based on the last ladle from the previous oven. This

could cause problems. Even though the alloying composition of the melt is within certain limits for

every compound the level of inoculants will vary depending on heating, stirring, raw material and on

how long the oven has been sitting if there is a stop in production. This could lead to undesirable

material properties and variation between the finished products.

Reduction in discarded products will lead to lower energy consumption and a reduction of material

usage. The steel and Iron industry are one of the heaviest polluters and energy demanding industries

in the world. By becoming more energy and material efficient the carbon footprint from this industry

will be reduced. [1]

Also, by improving strength of the material that they use for casting engine blocks and cylinder

heads, the diesel engine trucks will be able withstand higher combustion pressure and will be able to

get more effect out of their engines. This will lead to heavier loads being possible to haul leading to a

better CO2 to weight ratio [2] [3].

It would be very beneficial if one could know the status of the melt already in the oven in terms of

inoculant level. This would decrease discarded products not meeting the required material

properties. By analysation of the cooling curve the eutectic minimum temperature can be established

which can tell us the level of inoculation by comparing this temperature for a cup with and a without

inoculant additions. The saturation point can then be found which will tell us how much inoculant

should be added to the melt. This will be done by using Heraeus Electro-Nite testing cups and

software to analyse cooling curves of the samples. The microstructure of the samples will also be

analysed to see if there is any correlation between the grainsize and density with the results given by

the cooling curves portrait by the software.

The aim of the project is to test this method of measuring the nucleation level and to see if it will

have a positive impact when incorporated into production.

Ethical, social, and environmental aspect A producer of a product that runs on fossil fuel should try to minimize its carbon footprint, so it is

not just economically viable but also ethical and environmental. The transport sector which

utilizes these products produces a lot of carbon dioxide which contributes to global warming. This

will lead to a changing environment which will have a negative impact with rising sea levels and

drought which will lead to famine. It is in everyone’s interest to try to produce products with

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minimum emissions and produce products that will last a very long time. Also, from an ethical and

social standpoint improved engine performance that results in vehicles travelling further with

heavier loads means communities further from civilization can be reached as well as areas were

fuel is scares. Further development will lead to an increase of trained personal needed which will

benefit the social aspect.

3

Theoretical background Cast iron is a very versatile alloy consisting mainly of iron and carbon with a carbon content

exceeding 2%. Silicon is almost always present in all cast irons due to its graphite stabilizing effect.

Other alloying elements are also added such as silica, manganese, copper to get the required

material properties. The physical and mechanical properties can also be influenced by heat

treatment and by the altering the cooling rate [4].

The iron can either solidify as grey cast iron or as white cast iron. They get their name from the

colour of the surface when the material is fractured. White cast iron is a metastable phase, here the

carbon present in the iron will precipitate as the carbon rich phase cementite (FeC3) during

solidification which reflects a white colour. Here the carbon has not had enough time to migrate to

form the more stable phase, graphite. For grey cast iron which is the more commonly used in

industry the carbon precipitates as graphite flakes which reflects a grey colour when fractured [3] [4].

There exists a variety of different grades of cast iron with different that can be used many different

applications. What gives them their different properties and differentiates them from each other is

the shape of their graphite particles and the eutectic matrix. From earlier categorizing the cast iron

depending on the colour of the fracture they are categorized depending on the shape of the

graphite. Figure 1 shows how the graphite looks in the different grades of cast iron in a SEM [3] [5].

Figure 1: Graphite structure for the three different grades of cast iron seen in SEM. From left to right: Grey-, Compacted graphite- and Ductile iron. [5]

Cast iron consists of several different classes but three of them are more common than the others.

• Lamellar graphite iron (LGI)- It is also known as grey iron or flake graphite iron. The graphite

in the stable matrix is shaped as flakes or lamellas. LGI has very high thermal conductivity,

this due to the three-dimensional graphite network within the material. This is one of the

reasons why the material is often used in the automotive industry when constructing

cylinders heads as an example. The tips of the flakes in the network have sharp points and

create notches where the graphite joins the matrix. At these points, stresses in the material

will concentrate and cracks will form when the stress is to large. This leads to a material that

is brittle. The presence of this flakes leads to the material’s good machinability [3] [4] [5] [6]

[7].

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• Spheroidal graphite iron (SGI)- It is also called ductile or nodular cast iron. Here the graphite

is shaped as nodules/ spheroids. This type of cast iron is stronger and more ductile than LGI

because the graphite does not create sharp notches in the material where stress

concentrates. The spheroid shape of the graphite is created by usually adding magnesium to

the iron. The downside with this cast iron is that its thermal conductivity is quite poor due to

the lack of interconnecting graphite [3] [4] [5] [6] [7].

• Compacted graphite iron (CGI)- this is a cast iron that combines the high conductivity of LGI

with the ductile properties of SGI. The thermal analysis to establish the inoculation will be

done on three different grades of CGI so a more in-depth explanation of CGI will be given [3]

[4] [5] [6] [7].

The mechanical properties for the different grades of cast iron can be seen in table 1. These values

are provided by Sintercast, but other sources claim that the tensile strength for LGI varies from 150-

450, CGI between 250-575 and SGI between 350-900 MPa [8].

Table 1: Mechanical properties for the three different grades of cast iron [9].

Property LGI CGI SGI

Tensile strength [MPa] 250 450 750

Elastic Modulus [GPa] 105 145 750

Elongation [%] 0 1.5 5

Thermal conductivity [W/mK] 46 37 28

Relative damping capacity 1 0.35 0.22

Hardness [HBN 10/3000] 179-202 217-241 217-255

R-B fatigue [MPa] 110 200 250

CGI Compact graphite iron is a material that combines the strength and ductility of SGI and the good

thermal conductivity of LGI. CGI possesses 70% higher tensile strength and 35% higher elastic

modulus and about double the fatigue strength compared to ordinary grey iron. This including its

good thermal conductivity is why it is a widely used product in the automotive industry especially for

engine parts. With the automotive industry being a very development intense industry, looking for a

more environmental approach, a material was needed that could make the engines lighter and with

increased mechanical properties. The engine must be able to withstand the increased combustion

pressure being generated that comes with increasing torque and horsepower [3] [4] [10] [11] [12].

According to ISO, the International Organization for Standards, to be classified as CGI with standard

16122:2006 the microstructure of a two-dimensional polished surface of a CGI sample must contain a

minimum of 80% compacted shape graphite and less than 20% nodularity and have no flake graphite.

ISO 16122 includes five grades of CGI with a tensile strength from 300 MPa to 500 MPa [5]. Zero

percent nodularity is what should be strived for when producing CGI.

5

At Scania three different grades of pearlitic CGI are produced depending the requirements of the

product. They are named in the rapport CGI400 used for product A, CGI425 used for product B and

CGI450 used for product C. The numbers at the end of the name is the tensile strength of the

material in MPa.

Microstructure The graphite particles in CGI has a vermicular shape and at a first glance they seem to be individual

particles not linked to each other. When viewing the material in the SEM as seen in figure 2, one can

see that the particles are linked to each other in an interconnecting web in the eutectic cell.

Figure 2: Microstructure of CGI seen in LOM on the left and SEM on the right [6]

This is the reason for its good thermal conductivity. The graphite particles are like that of lamellar

iron, they are randomly orientated and elongated but the ends are rounded instead of sharp. This

together with the complex graphite morphology results in a strong adhesion between the graphite

and the eutectic cell leading to its superior mechanical properties [3] [5] .

Process CGI is created by adding an element that will alter the graphite morphology to the melt, this could be

titanium, magnesium or rare earth metals such as cerium or lanthanum [12]. At Scania magnesium is

added and will alter the graphite just enough to get round edges on the fingers of the graphite

network which are usually sharp notches. This process is very precise and the window very small

where right amount of Mg additions will result in CGI, see figure 3. If too much is added SGI will be

created instead [13].

6

Figure 3: Mg vs Nodularity [14]

It has been proven that it is not the Mg itself that alters the graphite morphology, but it neutralizes

elements that that has a decreasing effect on the nodularity. Oxygen and sulphur are the two main

components that has this effect, but it is still unclear why they have this effect. Sulphur will also form

iron sulphide in the grain boundaries, which is very undesirable, but with the right amount of

magnesium manganese sulphide will be created which is harmless because it will be formed within

the grain [4] [15]. Titanium is usually also added, it has the opposite effect, it decreases nodularity

creating a larger process window. The downside of this is that titanium carbides are formed which

will lead to decreased machinability [12] [16].

Producing CGI puts a lot of demand and precision on process control. If flake graphite appears the

mechanical properties can be decreased with as much as 25-40%, and this can happen with a change

of active magnesium content of 0.001%. The aim is to get the microstructure inside the red box seen

in figure 4. With increased nodularity the strength and stiffness of the material will invertible

increase on the expense of machinability, thermal conductivity and castability [3] [4][5] [6] [17].

Figure 4: Inoculation vs Mg modification on microstructure [14].

The mechanical properties and especially the strength of the material of CGI can be altered in two

different ways. One is the ratio between perlite and ferrite in the eutectic matrix. The higher the

7

ration between perlite and ferrite the harder and stronger the material is but the toughness

decreases. Copper and tin are two alloying elements that benefits perlite formation that can be

added. Chrome and manganese can also be added but the downside of these alloying elements is

that they are carbide stabilizers and will promote the iron to solidify as white cast iron. The second

option is to alter the morphology as mentioned previously be adding for example Mg [11].

Carbon equivalent

As for all cast irons carbon has a big importance of the mechanical properties. Because of alloying

elements effect on the carbon present in the iron the concept of carbon equivalent (CE) is often

used. The carbon equivalents take into consideration other alloying elements and their effect on the

carbon in melt. When the CE is at 4.3% the composition is eutectic same as when just considering

carbon. By using CE one can treat the multicomponent cast iron as a binary Fe-C alloy instead [18].

There is a direct correlation between the phase change temperature and the composition. This

correlation has been used to map phase diagrams. The liquidus temperature (TL) will give us the %C

of the melt or the carbon equivalent (CE) which as mentioned earlier includes the influence of other

alloying elements on the carbon such as Si, Mn, P, S [18]. CE is expressed by equation 1, some will

only consider C, Si and P because the levels of Mn and S are usually quite low.

𝐶𝐸 = %𝐶 + 0.33%𝑆𝑖 + 0.33%𝑃 − 0.027%𝑀𝑛 + 0.4%𝑆 Equation 1

The solidification of a material is not a process in equilibrium, a theoretical cooling curve will look

different than the actual curve. There will be undercooling, the material will solidify below the

theoretical (equilibrium) liquidus temperature. The non- equilibrium liquids temperature will be

lower than the theoretical one [18].

But due to the difference between the non-equilibrium and equilibrium curve, the CEL carbon

equivalent liquids have been introduced instead. It is based on empirical studies and experiments

with standardized sand cups [18]. CEL is expressed by equation 2.

𝐶𝐸𝐿 = %𝐶 + 0.25%𝑆𝑖 + 0.5%𝑃 Equation 2

This improved definition should be used when calculating the carbon equivalent from the liquidus

temperature when using thermal analysis as measuring tool of the iron [19].

Solidification The right chemical composition is of great importance as just mentioned before solidification starts.

For a material to start to solidify the liquid phase must be undercooled, which means that the

temperature must be below the eutectic temperature [20].When a material solidifies the atoms

changes from being disorderly orientated, having an amorph structure to be rearranged into a

specific lattice structure also called crystal structure. When this occurs the atoms releases energy in

8

the form of heat to its surrounding. Less energy is needed in an ordered structure due to the

decrease of degrees of freedom of movement. Once a nuclease is formed it can continue to grow and

its speed is dependent on how fast the heat can be carried away. This is depends on the heat

generation during the phase change, flow of the melt and the mould material that transports away

the heat [20] [21].

The binary equilibrium phase-diagram Fe-C needs to be studied to get an understanding of the

phases present and the different phase changes that occurs during solidification, see figure 5. When

the iron contains approximately 4.3% C melt is said to have a eutectic composition and no primary

phase will precipitate. The melt will solidify as austenite and depending on the cooling rate the

carbon will either precipitate as cementite or as graphite. When producing CGI, the goal is to get as

close to the eutectic point as possible to get as much carbon as possible to fill out the pores without

getting any cementite or exploded graphite.

Figure 5: Fe-C phase-diagram showing both the stable and metastable phases constructed using Thermo-Calc.

9

If CE is below the value of 4.3% it is considered hypo-eutectic and above hyper-eutectic. A hypo-

eutectic composition is preferable when producing CGI. When you have hypo-eutectic composition

the iron rich phase austenite will form as the primary phase. The austenitic primary phase grows as

thin dendrites and will continue to grow until they collide with a neighbouring dendrite with a

different growth direction. When they collide two grains are created with a grain- boundary dividing

them and the dendrite will start to coarsen instead of growing larger. When the dendrites grow,

being an iron rich phase that only can dissolve approximately 2.08 % carbon, carbon will we be

rejected into the melt. If the rate of solidification is to high the carbon will not have time to diffuse

from the dendrites to the melt creating a concentration gradient in the solidified material. This is

called segregation and it is the last to solidify area that will have the highest concentration of carbon

[3] [4].

In the case of a hyper-eutectic composition the carbon rich phase graphite or cementite will form

before the eutectic transformation. Too high solidification rate which will increase the undercooling

which will lead to a metastable solidification and cementite instead of graphite will be formed which

CGI is susceptible to. This can be seen in the phase diagram seen in figure 5. When the composition

of the melt has reached eutectic, eutectic solidification will be formed. Here the remaining melt will

solidify as austenite and graphite or cementite embedding the already precipitated phase [3] [4].

What also can be seen in the phase diagram is that a solid- state phase transformation will occur at

around 738 °C. Here the austenite will transform and depending on the cooling rate, composition

and initial crystal structure either into pearlite which is a two-phased lamellar structure consisting of

88 wt% ferrite and 12 wt% cementite or ferrite with graphite will be formed. Pearlite is what

normally austenite decomposes to in conventional casting at the eutectoid temperature where the

cooling rate is not too high. Very low cooling rates will lead to a complete ferritic matrix where the

carbon will precipitate on the already precipitated graphite or cementite [3] [4] [22].

The morphology of the graphite precipitated is very much affected by the level of undercooling of

the material which is dependent on the cooling conditions during solidification. With increased

undercooling the nodularity will increase, finer and more disperse graphite particles will be formed.

Lower undercooling leads to coarser and fewer particles. By altering the cooling rate and the Mg

additions all types of morphologies can be formed [4] [15].

Nucleation Nucleation is when a small particle solidifies in the melt and there are three different types of

nucleation: homogenous, heterogeneous, and dynamic. Nucleation is a “platform” where crystal

growth is initiated during cooling. This growth is started when the temperature falls below the

liquidus line or for a eutectic composition the eutectic line. Of the three different types,

heterogenous is the most common. For nucleation sites to be able to support crystal growth it must

exceed a critical size so it will not be re-melted. This is illustrated by figure 6 which shows the Gibbs

free energy in relation to the radius of the nuclei. Once the “hump” on the green line is passed the

nuclei will start to grow spontaneously. The green line is a combination of the volume free energy

which is the driving force towards nucleation and the interfacial energy represented by the blue line

which is always positive and counteracts nucleation. To be able to reach the critical size, the

undercooling which is the driving force for the nucleation must overcome the energy barrier. There

are two different ways nuclei are formed and grows. Either they are developed continuously as the

temperature changes, or instantaneously when a specific temperature is reached [21] [23].

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Figure 6: Critical radius for spontaneous nucleation in terms of Gibbs energy [23].

It is more energy efficient to nucleate on an already existing substrate, this is called heterogeneous

nucleation and austenite almost always nucleate this way. Surfaces support nucleation because of

wetting, angles greater than zero between the two phases will promote nucleation. Wetting is the

degree of which a liquid will spread on a solid when they come in contact with each other, one

measure of this is the contact angle as mentioned should be greater than zero. Homogeneous

nucleation, when you nucleate out of nothing is very rare and needs a lot of energy and are only

possible when the cooling rates are extremely high. Figure 7 shows the difference in energy to reach

the critical radius. The critical radius is the same for both homo- and heterogeneous nucleation but

the critical volume is usually smaller because of wetting [4] [23] [24] [25].

Figure 7: Comparison of critical radius for spontaneous nucleation for heterogeneous and homogenous nucleation in terms of Gibbs energy [23].

Inoculation

These nucleation points can be increased by inoculation additions to the melt and they have a big

effect on the mechanical properties of the material [21].

Most of the inoculants used for cast iron are based on ferrosilicon and additions from group 2 and 3

from the periodic table are most often added such as calcium, barium, strontium, titanium,

zirconium, and rare earth metals. Most ferrosilicon alloys contain between 65-75 % silica, a high

concentration of silica makes the melt exothermal and that it blends well. It is proven that pure

ferro-silica has bad inoculation effect, so that is why the alloying elements mentioned previously are

added. Because of the relative high cost of these elements there is an economical limit how much

should [26].

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The best supported theories of additions to get heterogeneous inoculation is by adding silicon-

dioxide particles or salt-like carbides [27]. These elements will react with the oxygen and sulphur that

is dissolved in the melt to form oxy-sulphide clusters that have crystal structure that resembles that

of graphite. These clusters will benefit graphite nucleation, so it is of great importance that there is

some oxygen and sulphur dissolved in the iron. This might sound strange because it was mentioned

earlier that they had a negative effect on nodularity. The level of sulphur and oxygen in the melt will

alter the amount Mg needed to reach levels enough for the grey cast iron to turn in to CGI. Increased

or decreased levels of oxygen and sulphur will shift the Mg requirement curve left or right with

inoculation of CGI the amount of inoculation additions is critical. Too much will lead to increased

nodularity and the ratio of vermicular graphite will decrease [14] [28].

Effects on material properties

The main purpose of adding inoculation particles is to facilitate the formation of graphite so it can

occur with minimum or no undercooling. Increased formation of graphite will increase the thermal

conductivity of the material. Increased growth of graphite leads to decreased shrinkage propensity as

well, due to the growth of graphite that makes up for the solidification shrinkage in the formation of

austenite. Decrease in undercooling will also avoid cementite formation [18] [26] [29] [30].

Improved inoculation results in more eutectic grains being created during solidification to a certain

extent. Increased nucleation gives the melt more surfaces to homogenously nucleate on, but on the

same time it decreases undercooling. Increased undercooling is reported to give a finer grain

structure with increased grain density and decreased grain size. So, it is a combination of the two

that will give the optimal grain density in terms of mechanical properties [18].

More grains which will give you a harder and stronger material because the dislocations are inhibited

to move as far because the grain-boundaries. The Hall-Patch relation stats that with increased

grainsize the yield stress will be increased as seen in equation 3.

𝜎𝑦 = 𝜎0 + 𝑘𝑦𝑑−1

2⁄ Equation 3

In equation 3 the yield stress is 𝜎𝑦, 𝜎0 and 𝑘𝑦 are material dependent constants and d is the average

grainsize (diameter). This tells us that with an increased grainsize the yield stress will decrease

resulting in better mechanical properties [9].

Superheating as mentioned earlier decreases the liquidus temperature most probably because it

diminishes the nucleation potential of the melt.

Other goals for adding inoculants are to [28]:

• Reduce segregation.

• Increase ductility.

• Give a homogenous structure.

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Fading of nucleation potential

As mentioned previously, fading is an unwanted decrease in nuclei when casting melts. It has been

observed a fading of nucleation potential when a melt has been sitting for a longer period before

being tapped, fading is time dependent. This is because the nucleation particles that differs in their

mass and density from the surrounding melt might react or dissolve into the melt or might

concentrate due to gravitational sedimentation. It has been seen that an increased temperature of

the melt decreases the nucleation potential. This reaction with the melt will lead to a decrease of the

catalytic effect of the nucleation particles and lead to inhomogeneous distribution of the particles in

the melt leading to grain-size variations in the casting. This fading of nucleation particles is also

thought of to be the result of Oswald ripening also known as coalescence. To minimize surface

energy smaller particles gets absorbed by larger particles, this gives the particles a higher volume to

surface area ratio. Particles can also be trapped in the slag or get stuck to the wall of the oven.

Decrease in holding time and a chemistry composition that is adjusted to minimize the loss of active

inoculant will decrease the fading effect [31] [32].

Method of inoculation

When adding inoculant there are three different ways, either into the ladle, additions to the melt

stream when casting or straight into the mould. The inoculant has greatest effect directly when

added and has a fading effect and most inoculants will have lost its effect 10 minutes after it has

been added. So, it is important to do it as close to the time of casting as possible [44].

Adding the inoculant straight into the ladle is the most flexible and the simplest way of adding

inoculants. For best stirring effect and to get a homogenised dispersion of the inoculant it should be

added when the ladle is 1/4 full. For this method there are generally three different ways of adding

the inoculant [28] [33].

• Additions of inoculant to the stream as the melt is poured into the ladle.

• Additions of finer grainsized inoculant to the stream by compressed air.

• Additions by inoculant wire that is added as the ladle is filled.

At Scania for their production of CGI cast irons they add the inoculant into the ladle after the ladle is

filled with a wire were the outer coating is made of a protective sheet of iron to make sure the

inoculant gets further down into the melt.

Adding the inoculant when casting is a method mostly used in foundries where they use mechanical

or automatic casting devices. The upside with this method is that the fading effect is minimized, and

less inoculant is there for needed. On the downside is that the particles might not have time to

dissolve into the melt and the inoculant will not be evenly dispersed.

13

There are as well here three different ways of adding the inoculant;

• Stream of fine inoculants particles by compressed air that is added to the melt stream as the

mould is filled. This is the method of inoculation additions for Scania grey cast iron when

producing their cylinder heads.

• Additions by wire to the melt stream.

• Additions of the inoculant straight into the mould. In this case the inoculant is placed in the

runner or the inlet to the mould. When the melt passes by the inoculant is successively

dispersed into the flowing melt.

One cannot say that one method is more superior as another, it all has to do with what type of

production you are running and at what scale. They all have pros and cons and the best way is to try

to find an option that is best suited for ones needs [28].

Material charged

The starting value of nuclei in the melt comes from the material that is being charged in the oven. Pig

and wrought iron are both claimed to be rich in nuclei compared to returns from in-house production

so a higher percentage of these materials in your charge will give you a higher starting value. This is a

known casting “hack”, to ad pig iron with rust on it to a dead melt to oxidize it and ad nucleation

points to the melt. By using thermal analysation, the level on nucleation additions are adapted to the

level present in the melt, this is called dynamic nucleation and is

Defects from improper inoculation additions If the melt is not properly inoculated could result in a variety of defects on the finished cast goods.

The ones most prominent for CGI are [34]:

• To large amount of additions with a high concentration of calcium will generate slag-like

inclusions.

• To large grainsize or inoculation at low temperatures, below 1300 °C can result in inclusions

which will cause problems when processed.

• Inoculation with high concentration of aluminium can give rise to “pinholes” especially when

casting in sand forms.

• Lack of nucleation points can promote white solidification, which will lead to porosity in the

material. The cementite will not expand as the graphite will.

Thermal analysis Thermal analysis can be used to measure the inoculant level in the melt, but a lot of other

information can be interpreted from the temperature variation over time and its derivative. By using

computer analysation, the alloy composition, grain refining, eutectic morphology, fraction solid,

amount of the phases can be given or predicted. The inoculations effect can be seen by the decrease

in undercooling and this knowledge is used to see how well a melt is inoculated. Thermal analysis is

based on the knowledge that every event that occurs in the solidification of a material leaves its

14

mark on the cooling curve. Phase changes, both solid state and liquid to solid can be seen on the

cooling curve by the latent heat of solidification realised. The cooling curve can be divided up into

four sections to better describe what occurs during solidification, seen in figure 8. In the first section

the metal is present as a melt, called the liquid area. Here stable oxides and sulphides are formed

that will be formed as the temperature decreases and will be very important as nucleation points.

The second section is where the primary phase will solidify. The eutectic temperature is the starting

point of the third section and will continue until the melt is completely solidified. The fourth and final

phase only involves decrease in temperature [18] [21] [28].

Figure 8: The four different regions of solidification [21].

Thermal analysation can be done in different ways but the simplest is by using a thermocouple

inserted into a test mould. The shape of the curve comes from the balance between the heat from

the material realised to the surroundings and the exothermic heat created during the phase change

when the material solidifies. The geometry of the test cups is of most importance for the results

given by the curve and should enable consistent sampling conditions. Other factors that play into

effect is the tapping temperature, level of oxidation and the pouring time. It is proven that

superheating will lower the eutectic temperature, so it is of most importance. If one wants to

examine the level of inoculation of the sample, a smaller test cup is to be preferred [18].

The analysation method provided by Electro-Nite is by using two testing cups, one with and one

without inoculant particles in it. The melt is poured in the two cups and two cooling curves are

established. The difference in the eutectic minimum temperature between the two cups will tell us

the level of inoculant [18] [19].

When carbon that is dissolved in the melt is crystalized and form graphite of different morphologies

latent heat is realised. This heat realised up on solidification is 3600 joules/ gram for graphite,

compared to approximately 210 joules/ gram for austenite. This knowledge can be used to measure

the inoculation levels in the melt. Inoculants are used as nucleation points for the crystallization of

carbon into graphite [34].

Measurements done by [26], a measuring cup that holds 370 grams of melt and the specific heat for

cast iron at the eutectic point is 0.8 J/g/°C. If it is assumed that 1 gram of carbon crystalizes to

graphite the theoretical temperature increase would be 12 °C. The accuracy of the commercial

15

thermal analytic system area gives or take 1.2 °C, which means that it would be able to detect

precipitation of 0.1 gram of graphite. The eutectic graphite on total is about 1.4 % if the cast iron has

a carbon content of 3.4%, which would equal 5.2 grams in the sample cup. The precipitation will then

be roughly two percent. This would be a sufficient mount for the measuring equipment to detect

differences in inoculation levels.

The test cups are usually made either of metal or sand. Metal can give a more precise positioning of

the thermocouples, but the sand cups are cheaper. A test cup that has Tellurium added to it

promotes the metastable white solidification. The high growth rate of the white eutectic close to

eliminates the undercooling. These cups are used to establish the liquidus temperature of the melt.

Not only the cooling curve temperature over time can give us information of the solidification event,

but also the first and second derivate can give us an estimation of the grain refinement and the

propensity to micro shrinkage. If one compares LGI with SGI for example. LGI releases very little

latent heat at the end of solidification, which will give it a large increase in cooling rate. SGI realises

more latent heat and will not have such a large increase in cooling rate [18] [29].

Sinter cast process Sinter cast is a company that provides a thermal analytic tool to measure the level of Mg and

inoculant present in the melt that is used by Scania for their CGI products. Each oven equals to five

ladles that will be casted. The melt in the oven has no additions of Mg in it. Mg has a very high

affinity to air and is therefore very reactive and should be added at the latest stage possible of the

process. Also, the inoculant additions should be done as close in time to casting due to fading. These

additions are made to the melt in ladles just before they are casted. The first ladle gets a base

treatment of Mg and inoculants based on the last ladle from the previous oven’s values. Before a

sample is taken with a sinter cast sampling cup and analysed. It measures the modification index

(MGM) which is the level of Mg, inoculation index (MGI) and the carbon equivalent for the melt

based on thermal analysis. The measured values will be shown on the screen and depending on the

values It will tell if they are acceptable or not. Depending on the values for this ladle alterations in

terms of additions of inoculants and Mg will be made for the next ladle. But the results take several

minutes to get, and the operators will not wait for the results to be able to make alterations for the

ladle are working with [14].

The previous method is used for CGI400, for CGI450 and CGI425 the addition of Mg and inoculant is a

two-step process. First a base treatment is done on the melt, here 90% of the Mg is and 10%

inoculant is added. A sample is taken, and the process is stopped until the results of MGM, MGI and

CE are received. Based on the results received from the test more additions of Mg and inoculants are

made but now usually 90% inoculant and 10% Mg.

The sampling cup is mounted with two thermocouples, one in the centre of the cup and one close to

the bottom this to allow for simulation of Mg-fading. To get optimum measurements the

temperature of the melt should be as close to 1280 °C as possible. Figure 9 shows a Sintercast

sampling cup which looks quite different then a sand cup. The shape of the sampling cup will lead to

no oxidization and fixed volume and mass to get accurate measurements [14] [22].

16

Figure 9: Sample cup for Sintercast measurements [48].

.

Thermocalc Thermocalc can be used for a variety of applications and is a thermodynamic software used for

scientific and research use. In the case for the study of thermal analysis of the inoculation level in a

melt it can be used to compare the results provided by the Electro-Nite. The software is often used in

materials engineering to calculate [35] ;

• Phase diagrams, simulation of phase transformation

• Amounts of different phases and their compositions

• Liquidus and solidus temperatures

• Stable and metastable phase equilibria

• Collect thermal chemical data such as enthalpies, heat capacities and activities to name o

few.

• With the help of the Scheil-Gulliver model solidification of a melt can be simulated.

Normally Thermocalc is used for equilibrium calculations, for these cases it is assumed that the

diffusion between the solid and the liquid is complete. These calculations are very good and useful

for many applications but is proven not to be as accurate for the solidification process, here the

diffusion in the solid state is blocked. The Scheil- Gulliver model is a non- equilibrium calculation that

has been proven to show better results for these calculations and works good for typical cooling

rates seen in foundries. This model assumes infinitely fast diffusion in the liquid phase and no or low

diffusion in the solid phase and that the solid/liquid interface is in thermodynamic equilibrium [36].

The classic model that was mentioned above works very well for many alloys but not for steel and

Iron. Carbon that dissolves interstitially is a very fast diffuser in solid state and is a very important

alloying element for steel and iron. By assuming no diffusion in the solid state will not give an

accurate result. A second form of Scheil- Gulliver model can be used that allows one to pick elements

to be “fast diffusers” in the solid phase and this addresses the problem mentioned earlier [36].

17

Raw material

Inoculant

The inoculation used by Scania for its CGI products is Odermath- wire. The composition can be seen

in table 2. The inoculation that are added to the Electro-Nite sample cups is SMW605, the

composition can be seen in table 3.

Table 2: Odermath-wire composition.

Odermath- wire (9N23) Si [%] Al [%] Ca [%] Zr [%]

Min 72 0.8 1.2 1.2

Max 78 1.8 3 1.8

Aim 72 1.04 1.43 1.53

Table 3: SMW605 composition.

SMW605 %Si %Al %Ca %Bi %SE

Min 62 - 1.8 0.8 0.8

Max 68 1 2.4 1.2 1.2

Charge

For the three different CGI compositions different recipes are used when charging the oven. These

recipes are altered in terms of weight of ingoing material depending on what melt was run in the

oven previously and how much that is left the oven from previous run. If the melt run previously has

to high levels of certain alloying elements that should not be in the following the remaining melt will

be discarded into small ladle to be re-melted later. The charge is made up of four different

components;

1. CGI- chips

2. CGI- returns

3. Pig Iron- low phosphorus

4. Wrought iron- scrap iron

Experimental procedure

Method For each oven of melt which has a weight of approximately ten metric tonne equals five ladles that

will be cast into engine blocks or cylinder heads. The main goal is to establish the level of inoculant in

the oven, so the first ladle will get proper inoculation additions. The second ladle will get inoculation

additions by the Sintercast measurement tool based on the levels from the first ladle.

The level inoculation level will be established using thermal analysis, for these two different sampling

cups are used. One empty sampling cup with a fixed volume and an identical cup but with 0.05 wt%

inoculant added to it. The difference in the eutectic minimum temperature (DTEmin), will tell us the

level of inoculation.

18

All the samples taken during this investigation will be taken on from untreated melts, no magnesium

has been added to the melt to create CGI. The melt will have the morphology and structure of grey

cast iron.

The tests were conducted on all grades of CGI, though most test were done on CGI400 due to its

production volume. The grade of CGI will be mentioned when presenting the results, but due to the

very close composition between the three grades of CGI they are expected to behave the same way

and will be the same type of alloy when analysed unless big differences between them are noted.

Average starting value and nucleation fading First, the average starting level of inoculant should be established for the melt in the oven by taking

several measurements. Simultaneously Inoculation fading will be investigated by conducting tests

over time on ovens that are sitting due to stop in production.

For each measurement taken, three different sampling cups was used. The first cup has an addition

of tellurium in it. This measurement is taken on a different mount connected to a different computer

and software. The volume of the cups contains tellurium is different compared to the other cups. The

cooling curve is calculated by the software and is based on a fixed volume, so changing the cup size

will alter the result. This is used to establish the liquidus temperature for the melt that correlates to

the carbon equivalent, which is an important process parameter.

It is important so that we can tell that we have the right chemistry for the melt. It does not matter

what order you use the cups, but a good idea is to use the cup with tellurium first to see that the

melt have the right chemistry, so time and cups are not wasted.

The chemistry of the melt is checked with a spectrometer, this gives the amount of each component

in the melt. The carbon content observed by the spectrometer is not reliable because some carbon

will be burnt off during the procedure by the spectrometer. Therefore, the tellurium cup is used to

establish the CE and TL. The samples to establish the chemistry and the TL is taken after the melt has

been heated to 1400 °C. The results for the TL just take a few minutes to receive and depending on

the results additions of carbon will be given. The results from the spectrometer takes longer time and

the melt is heated up to 1460 °C and de-slagged while waiting for the results. Depending on the

results from the spectrometer, the chemistry might be adjusted though this is seldom needed after

years of fine tuning.

The second sampling cup which has no additions is taken after the melt has been de-slagged and the

chemistry and TL checks out. Heating of the melt will lead to stirring of the melt due to convection

which will lead to a homogenised melt. The samples are taken a few minutes after to ensure the

movement of the melt has stopped. The first samples taken from an oven after it is de-slagged is

considered as t=0, sample taken at time zero. This is the starting value of the melt.

19

Figure 10: Picture of the set up by the oven.

The testing cups with the melt are left on the mount until the instrument has taken out the eutectic

min and max temperature or when they can be seen on the curve if the instrument as failed to point

them out. The sample is removed from the mount, having a temperature of around 1000-1100°C and

is left to cool down for further investigations. The sample should not be left on the mount longer

then needed so the connectors do not get heated up before and can cool down before the next

measurement is taken.

The third cup with inoculation additions to it is mounted and a new sample is taken and the same

procedure as for the cup with no inoculation is conducted. A measurement takes approximately

maximum 5 minutes for the three cups. The set up by the oven can be seen in figure 10 and picture

of the two cups used for DTEmin measurements can be seen in figure 11.

To get proper measurements it is important that the tapping temperature does not exceed 1370 °C

and that it is at least 20 °C above the TL. The upper limit is not to exceed the range of the

thermocouple, so samples are most often cooled for a few seconds before being poured into the

sampling cup. This goes for all the measurements for all the different cups. The sample is taken from

the top of the melt in the oven using a ceramic dipping cup. When the sample is taken from the oven,

any slag at the surface of the oven is removed, the cup is dipped in the melt once to heat it up a rinse

out any impurities. An additional scoop is taken, some of the melt is poured back to remove any

unwanted slag that might float on the surface.

The cups are mounted on a heat resistant contact block that is connected by a type K extension wire.

The wire conducts the electrical signal from the thermocouple of type K (NiCr-Ni) with a range of 400

- 1370 °C to the Heraeus Electro-Nite Quick-lab-E measurement instrument connected to a computer

where the software Meltcontrol 2020 is installed. The software will display a cooling curve and from

analysing the curve and knowing how different properties of the melt would affect the curve and

what type of sampling cups is being used information can be gathered.

20

For ovens that has been sitting and cooled down, they are heated again to the correct measuring

temperature which is set to between 1400-1460 °C. These ovens are used to take measurements

over time to investigate nucleation fading. This can be done when there is a stop in the production

line.

Figure 11: Picture of the two cups used to measure the DTEmin. The one on the left is the cup with inoculant additions and the cup to the right is empty.

The difference in eutectic minimum temperature (TEmin) for the cup with and without inoculation is

calculated and this determines how well the melt is inoculated. Increased inoculation as mentioned

previously will increase the TEmin temperature, the undercooling will decrease. In figure 12 the two

solidification curves for the two different cups can be seen. It is the temperature difference between

the two when it is at its lowest before the temperature increases due to the exothermal reaction

occurring. These points are marked with a black dot in the image, and it is the temperature

difference between these two points that is donated as DTEmin. Several tests are done, and an

average starting value is calculated.

Figure 12: Cooling curve for cup containing inoculant and cup not containing inoculant. The black points show the eutectic minimum temperature points.

1050

1100

1150

1200

1250

1300

1

16

31

46

61

76

91

10

6

12

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13

6

15

1

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6

18

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19

6

21

1

22

6

24

1

25

6

27

1

28

6

30

1

31

6

33

1

34

6

36

1

37

6

39

1

40

6

42

1

43

6

45

1

46

6

48

1

49

6

Tem

per

atu

re [

°C]

Time [s/10]

without inoculation Inoculated

21

Saturation point A melt has a saturation point for inoculation, after this point the TEmin will not be as large as

previously with additions of inoculants. This point can be seen in figure 13 where S is the saturation

point. After this point the temperature difference between the two cups with different amount of

inoculation will be small, this point is the goal to reach. If you have less, you do not have enough

inoculant additions and past you are spending money on excess additions of inoculation which is not

economical. According to Electro-Nite, the supplier of the measuring equipment the DTEmin should

be less than 2 °C for it to be considered saturated and if the difference is larger than 3 °C more

additions of inoculant is required. The yellow curve in the effect of increased silicon in the melt, the

green the effect of the inoculant which is FeSi and the blue curve is a composition of them both, the

total effect. This will be established by using the Mini-lab suitcase provided by Electro- Nite.

Figure 13: TEmin vs amount of nucleation. Showing the saturation point marked S.

Minilab-suitcase

Procedure

To find the saturation point of the melt, the Minilab- suitcase provided by Electro-Nite was used seen

in figure 14. Each melt will always vary a bit in composition, heating practices, raw material etc. and

this will affect the level on inoculation of the melt. The needed addition of inoculant will be different

to reach the saturation point for each melt. By using additional cups that have stepwise more

additions of inoculation; 0.05%, 0.10% and 0.15% one can find between which cups the difference in

eutectic minimum temperature is below the reference value for the saturation point. When that is

22

found the cup with the lower additions of the inoculant of the two cups compared will tell you how

much inoculant should be added to the melt.

Figure 14: The minilab- suitcase used to fill the testing cups with increasing amount of inoculant.

Equipment

The suitcase contains the tools to be able to prepare empty test cups with inoculants to be able to

conduct the tests described. It has a calibrated spoon that holds 65 milligrams of inoculant, this

equals to 0.05 weight percent of the sample that has a fixed volume and weighs 130 grams. For these

test Scania’s own inoculant 9N23 will be used instead of SMW605 that the pre-filed cups are filed

with. A piece of the inoculant wire used in production was cut off and the inoculants inside the wire

was removed. The size of the inoculant is desired to be in the range between 125 to 355 μm. To get

this size a sieve is used with a top filter with the mesh size of 355 μm and a bottom with a mesh size

of 125 μm. The inoculant is collected from in between these two filters to get desired size.

The test cups to be used for the minilab are the cups called QC4000Cov2T. These cups have two

pieces of tape that covers the inlet hole from both sides, and it is between these two pieces of tape

that the inoculant is contained. This is to simulates the stream inoculation and should give the

inoculation a homogenous dispersion in the melt. The cups that was at disposal for the test was the

QC4000Cov, which is the same type of cup except that it lacks the two, cover tapes. The first test was

done by pouring the inoculant straight in the hole, so it was at the bottom of the cup. To get a set up

closer to the cups with two pieces of tape, for the rest of the tests the inoculant was trapped

between two pieces of tape just above the inlet hole, see figure 15. This also to get a better

dispersion of the particles.

23

Figure 15: Preparation of the cups with increasing inoculation additions.

The spoon is used to scope up the right amount of inoculant and is poured in the funnel to make

filling easy and correct. A metal clip is put on the sample with the sample id and the amount of

inoculant added written on it.

Testing of inoculation addition in ladle When the amount of inoculation is determined with the help of the mini-lab suitcase this will be

tested for inoculation additions to the ladle. Inoculant wire used in the production will be cut in the

required length to get enough inoculant, this will be placed in the ladle. By placing the wire in the

bottom of the ladle will ensure good mixing when the melt is poured on top of it. The samples will

later be taken on the ladle’s way to the casting floor and the same method as previously will be used

to determine the DTEmin, see figure 16.

Figure 16: Pictures how samples are taken from the ladle

24

Laboratory preparation The samples chosen for further investigation of the microstructure must be prepared. Samples with

values ranging from high to low where chosen and it is the samples with no inoculation additions

that are to be analysed because they represent the actual melt in the oven. Some inoculated samples

will also be prepared but just for comparison. The sample is cut just below the thermocouple as seen

in figure 17. The sample is mounted into a Bakelite puck to make handling of the sample easier using

a Struers CitoPress-30. The sample is then grinded using Struers AbraPol-20 and then polished using a

using four different polishing surfaces going from coarse to fine with three different grades of

diamond paste, 6, 3 and 1 my meter. When the samples are finished being polished, they are rinsed

with ethanol, wiped with cotton soaked in ethanol and the rinsed with ethanol again before being

blow-dried with a hairdryer. After this a clean scratch free surface is achieved ready for further

investigation.

Figure 17: Picture of sample with a line demonstrating where the sample is cut for further investigation.

The samples are first investigated using a light optical microscope of type Zeiss Axio Imager.M2m to

look at the microstructure of the sample. When conducting further analysation on the samples only

the samples with no additions will be analysed because these samples represent the melt in the

oven. The programme axiovision is used to be able to analyse the pictures using the microscope on a

HP Z440 compute. With this imaging programme a mosaic picture, an image that is several pictures

put together to create on large image of the surface was used. The software also has a feature that

can determine the area of graphite present in the sample and the nodularity of the graphite.

Nodularity is not of interest, but an increase of inoculation points could lead to an increase in

graphite because it promotes graphite precipitation. The microstructure of the analysed sample is

different than from the finished CGI product. There has been no addition of Mg yet to the melt, so

the sample we look at are not CGI but grey iron. Therefore, the samples contain flake graphite some

nodularity with a ferritic background. The microstructure is analysed to see a difference from the

different samples in terms of primary precipitation of dendrites and graphite formation of the

microstructure, see figure 18. To be able to get a cell count of the image which is how the inoculation

level can be measured the sample has to be etched.

Thermocouple Sample cut

25

Figure 18: Microstructure of sample seen with LOM. The left with 2.5x zoom and the right with 10x.

Etching

Nital- etching

The first sample tested was etched with 2% Nital. The etchant was dropped on the sample and was

left to react with the substrate for 10 seconds. After that, the sample was rinsed with water and then

ethanol before blow-dried. The etchant removed the graphite in the sample and darkened the white

ferrite, but no cells could be detected. The same procedure was done again for an additional 10

seconds. The only difference was that the ferrite got darker, figure 19 shows the result after 20

seconds of Nital etching. You were able to detect small outlines of grain boundaries if you zoomed in

close enough, but not enough to get a good cell count. After some research, the best approach to be

able to see and get a cell count would by the help of colour etching.

Figure 19: Sample after Nital- etching for 20 seconds.

Colour etching preparation

You colour etch your sample to form a thin film on the surface which creates an optical interference

effect. When colour etching the samples to reveal the grain structure and size of the material an

etchant based on picrin- acid was used. This etchant has been proven to be the most effective to

26

reveal the cell structure of the material according to experiments conducted at Scania. In the images

one can tell where the concentration of Si is the highest, it is seen by a range of white to light blue to

dark blue in colour in the images. Si has negative segregation and will segregate to the first solidified

area, revealing which area solidified first. The areas that are browner in colour have less Si and have

probably solidified later. The focus is to reveal the grainsize and grain density of the samples.

500 ml of picrin-acid was measured in a glass vessel and 125 grams of sodium hydroxide weighed and

dissolved in the acid. The reaction is very exothermic so not all the sodium hydroxide was added at

once, but it was added as it was dissolved. The solution is very basic with a pH of around 13. The

solution was heated up to 90 °C with an induction stove using a thermometer to establish the

temperature. The temperature fluctuated between 85-95 °C, because of difficulties to fix the

temperature. A magnetic stirrer in the bottom of the vessel was used so the solution was well mixed

and homogeneous. The sample surface was submerged in the solution and left submerged first for

approximately nine minutes. The sample was rinsed in water, then with ethanol before being dried

with a blow drier. The sample was then investigated with a LOM to see if the sample needed more

etching or if it was sufficient. The etching time needed is very temperature and concentration

dependent. Being hard to get the exact temperature the time needed to etch can vary greatly. The

guidelines given state that for 80 °C 10-25 minutes is needed to get a clear cell structure and less for

higher temperatures. 90 °C was chosen per instruction from a supervisor at STC with long experience

of etching.

After investigating the sample using the LOM it was concluded that the sample was under etched and

is was etched again for three more minutes and then investigated again. This procedure went on

until the sample was properly etched. This time to etch a sample varied between 20-30 minutes

depending on time, temperature and the concentration of the etchant that became less effective

over time making the task a lot more difficult than projected. Figure 20 shows the corner of a sample.

Here both the segregation of Si as well as the grains can be seen after colour etching.

Figure 20: Corner of a sample after colour etching. The blue colour comes from SI segregation to the first to solidify region.

27

Image J An imaging software programme ImageJ is used to enhance the images. The programme has many

usable features such as adjustment of the colour and contrast to easier see the grain-boundaries and

the eutectic cells that we are investigating. By adding a scalebar in the axio-software that is

connected to the microscope. Length measurement can be taken in the image that is needed to

calculate grains per area and the average grain size. Figure 21 shows an enhanced image and an

image where the grain boundaries are filled in with red colour to easier identify the lines.

Grain density A way of determining if there was enough inoculant in the melt and compare the thermal analytic

results with the microstructure of the sample is by investigating the grainsize and the average grains

per area also known as grain density. These two measurements should correlate with each other.

Increased difference in eutectic minimum temperature should give us fewer grains per area and

therefore larger grains. The number of grains per area (Nf) is calculates using equation 4. F is the area

of the rectangle that you are investigating, Ni are the grains inside the rectangle and Nw are the

grains that intersect the sides of the area. The grains that are in the corners are not counted by

themselves but two adds up as one. To easier see the grain boundaries they are filled in with a black

line using windows paint.

𝑁𝐹 =𝑁𝑖 + 0.5𝑁𝑤 + 1

𝐹 Equation 4

Figure 21: Shows how lines are drawn using software paint to easier see the grain boundaries when calculating

size and density.

Grain size The average grain size can be measured by using the mean intercept method. A line is drawn across

the area of investigation and the length of the line is divided by the grain boundaries crossed. Four

lines are drawn, and an average length/ diameter of the grains are established. This method is most

reliable if the size of the grains does not vary too much.

28

Figure 22: How the lines are drawn to calculate the average grain size.

For both above calculations the sample has be colour etched to reveal the grains- boundaries and the

imaging software image J is used to measure and to enhance the images. Two images are taken for

each sample investigated and an average value for each sample is taken from the average of the two

images. A total of 12 samples are etched and examined. An example of this can be seen in figure 22.

Additional testing Other tests were conducted to see how different foundry practices affects the inoculation level of

the melt.

• How carbon and wrought iron additions will affect the levels of inoculant

• How increased oven temperature will affect inoculant fading.

• To ensure good measurement procedures, test how de-slagging will affect the results.

• How the inoculant levels change as the level of melt decreases in the oven. This will be done

both taking samples from the ladle as well as from the oven.

• Testing the difference in DTEmin between the inoculant used in the cups and used in

production.

Chemical analysis For each oven, a chemical analysis is done with a spectroscope. A sample for analysis is first taken in

the oven and then from the first ladle. This is done for every oven, but we selected the following

samples to be able to find some correlation. The composition of the charge for some selected

samples were investigated to see if a correlation between the composition of the charge and

nucleation level could be established.

29

Thermocalc The thermodynamic simulating software Thermocalc is used to create both a metastable phase-

diagram that will simulate what happens in the cup containing tellurium that promotes the formation

of cementite. A stable phase-diagram will also be simulated that should be more accurate for the

melt solidifying in the other cups. The diagrams are binary Fe-C diagrams which do not consider all

the alloying elements, they will only be relative accurate when considering the carbon equivalent

(CE) which takes into consideration P and S.

To consider the alloying elements the Scheil- Gulliver model for solidification will be done using the

Thermocalc software to calculate TL for the melt. This model will also be done but by using the

carbon equivalent for both stable and metastable solidification. Carbon will be picked as a fast

diffuser when running the calculations. An average CE was established from 12 samples of CGI. The

amount P and S present in the melt is very low and the difference between them insignificant so the

CE can be considered the same for both. An average for the alloying elements for the three different

alloys is also taken and used for the calculations.

Comparison of TL for cups To be able to minimise the cup usage, time, and equipment the TL measurement using an ordinary

tellurium cup is compared with the TL registered using the testing cup without inoculant. These two

cups are connected to two different computers that considers the volume of the cup which is

different for the two cups and which is needed to calculate the TL. If a correlation can be derived

how the temperature differs between these two cups, only two instead of three cups needs to be

used for this process.

Results For each test taken only one DTEmin could be established, due to time limitation when taken test in

the production. No standard deviation can therefore be established for the test which limits the

reliability of the tests and sources of error are hard to establish. The point of the results is to show if

this measuring technique is sufficient and the value of the results are less important.

Level on inoculation in oven Table 4 shows the starting average level of inoculation in the oven and the max in min values

registered for the grades of CGI at T=0. The CGI400 average is based on 19 melts, the CGI450 is based

on four samples and CGI425 on five, but due to the very similar chemistry a combined average can be

used. Table shows that CGI425 and 450 have similar values and that CGI400 has a higher average

value.

Table 4: Max, min, median and average DTEmin starting value for CGI400, CGI425, CGI450 and combined.

DTEmin [°C] CGI400 CGI425 CGI450 Combined

Max 12.8 7.4 7.3 12.8

Min 2.1 3.6 1.2 1.2

Median 6.3 5.0 4.7 6.3

Average 6.7 5.0 5.4 6.2

30

Inoculation fading over time Figures 23-27 shows the DTEmin over time also known as the inoculation fading. This was done for

six different ovens for different length of time seen in the graphs. The samples were taken as

mentioned previously in the section about experimental method. The figures show an increase of

fading at first, but after two to three hours most show a decrease in DTEmin.

Figure 23: DTEmin vs time. Illustrates inoculant fading over an eight-hour period.

Figure 24: DTEmin vs time. Illustrates a five-hour test on inoculant fading.

7,37,7 8,6

8,3 8,2

5,5

6,5

5

5,5

6

6,5

7

7,5

8

8,5

9

0 1 2 3 4 5 6 7 8 9

DTE

min

[°C

]

Time [h]

4,3

6,6

5,2

6,3

4,8

4

5

6

7

8

9

10

11

0 1 2 3 4 5 6

DTE

min

[°C

]

Time [h]

31

Figure 25: DTEmin vs time. Illustrates inoculant fading over a four-hour test.

Figure 26: DTEmin vs time. Inoculant fading over a two-hour test.

Figure 27: DTEmin vs time. Inoculant fading over a two-hour test.

5,7

6,6

10,4

4

5

6

7

8

9

10

11

0 0,5 1 1,5 2 2,5 3 3,5 4 4,5

DTE

min

[°C

]

Time [h]

7,1

8

4

5

6

7

8

9

10

11

0 0,5 1 1,5 2 2,5

DTE

min

[°C

]

Time [h]

1,2

6,5

0

1

2

3

4

5

6

7

8

9

10

0 0,5 1 1,5 2

DTE

min

[°C

]

Time [h]

32

Saturation point Figures 28-32 shows the temperature where the eutectic undercooling is reached for the different

levels of inoculation. The samples were taken from the same oven over an eight-hour period. The

lower value of inoculant of the two cups being compared shows the level of inoculation additions

needed. All test conducted shows that when comparing the cup containing 0.05wt% inoculant with

the cup containing 0.1wt% the saturation point is meet which is reached when the difference is less

than 3 °C. This was for the CGI450 composition.

Figure 28: TEmin vs inoculation to find the saturation point, test 1.

Figure 29: TEmin vs inoculation to find the saturation point, test 2.

1140,9

1146,8

1146

1148,1

1140

1141

1142

1143

1144

1145

1146

1147

1148

1149

0 0,05 0,1 0,15 0,2

TEm

in [

°C]

Inoculation [wt%]

1138,2

1144,6

1146

1147,7

1136

1138

1140

1142

1144

1146

1148

1150

0 0,05 0,1 0,15 0,2

TEm

in [

°C]

Inoculation [wt%]

33

Figure 30: TEmin vs inoculation to find the saturation point, test 3.

Figure 31: TEmin vs inoculation to find the saturation point, test 4.

Figure 32: TEmin vs inoculation to find the saturation point, test 5.

1139,2

1142,5

1145,2

1147,1

1138

1139

1140

1141

1142

1143

1144

1145

1146

1147

1148

0 0,05 0,1 0,15 0,2

TEm

in [

°C]

Inoculation [wt%]

1140,8

1144

1146,4 1145,8

1140

1141

1142

1143

1144

1145

1146

1147

0 0,05 0,1 0,15 0,2

TEm

in [

°C]

Inoculation [wt%]

1139,5

1145,21145,8

1147,5

1139

1140

1141

1142

1143

1144

1145

1146

1147

1148

0 0,02 0,04 0,06 0,08 0,1 0,12 0,14 0,16

TEm

in [

°C]

Inoculation [wt%]

34

Testing inoculation additions to the ladle Previous test showed that 0.05wt% inoculant should be added to reach the saturation point. 12

meters of Odermath inoculant wire was cut and placed in the bottom of 8 ladles. Every meter

contains 120 grams of inoculant, 12 meters give you 1440 grams of inoculant. Every ladle contains

1800 kg of melt which means the inoculant additions are 0.078wt%. The inoculant exchange will not

be 100% so a little bit more than 0.05wt% was added as told. These eight tests are conducted on 2

different ovens, three on the first seen in figure 33 on ladle 3-5, where the starting inoculation level

on the oven was recorded. The starting value is denoted as ladle zero in figure 33. Five tests on the

other seen in figure 34 on ladle 1-5. One of the cups had a hole in it so ladle number four is not

shown on the figure 34.

The figures show that changing the order of the cups for the samples had no evident effect on the

result. Figure 33 shows that even with additions of inoculant to the ladle, the DTEmin still increased

for all the ladles tested. The test was conducted on CGI400 and with an average starting value of 6.7

one can assume that the inoculation additions to the ladle seen in figure 34 also had no effect to the

DTEmin.

Figure 33: DTEmin for the five tests taken for the different inoculant additions.

5,3

8,1

8,2

8,1

0

1

2

3

4

5

6

7

8

9

0 1 2 3 4 5

DTE

min

[°C

]

Skänk

35

Figure 34:DTEmin for the five tests taken for the different inoculant additions.

Grain size and density Figure 35 shows how the grainsize changes as the DTEmin for the cup with and without inoculant

additions increases. This value is taken by using the intercept method on images taken from samples

that has been colour etched. Several images are taken from each sample and an average is derived.

Samples are taken with different DTEmin values go generate the plot. The figure shows that an

increase of DTEmin will increase the grainsize.

Figure 35: Grainsize vs DTEmin, how DTEmin effects the size of the grains.

The 𝑅2= value for the exponential fitted curve is 0.9338 and the model is based on equation 5.

Y = 126.83e0.1968x Equation 5

7,6

8 7,7

8,4

0

1

2

3

4

5

6

7

8

9

10

1 2 3 4 5

DTE

min

[°C

]

Skänk

0

200

400

600

800

1000

1200

1400

0 2 4 6 8 10 12

Gra

insi

ze [

µm

]

DTEmin [°C]

36

Figure 36 shows how the grain density changes as the difference in undercooling between the two

samples increases. Equation 5 is used to calculate the grain density and the samples for investigation

have been colour etched to reveal the grains structure as when calculating the grain size. An average

for each sample is taken by investigating several images. The figure shows that with increased

DTEmin the grain density will increase.

Figure 36: Grain density vs DTEmin, how increased DTEmin effects the density of the grains.

The 𝑅2= value for the fitted exponential curve is 0.8545 and the model is based on the equation 6.

y = 56.988e-0.36x Equation 6

Addition of scrap iron The thermal analysis before and after 100 kg of scrap (wrought) iron is added to melt weighing

approximately 10 000 kg that has been sitting for eight hours can be seen in figure 37. The figure

shows that addition of iron will decrease DTEmin excessively.

Figure 37: DTEmin before and after 100 kg of wrought iron additions.

0

5

10

15

20

25

30

35

40

0 2 4 6 8 10 12

Gra

in d

enis

ty [

n/m

m2

]

DTEmin [°C]

6,5

3

2,5

3

3,5

4

4,5

5

5,5

6

6,5

7

0 20 40 60 80 100

DTE

min

[°C

]

Scrap Iron [kg]

37

Effects of inoculants used Difference in the eutectic minimum temperature between the inoculant provided by Electro-Nite and

the inoculant used by Scania for the CGI production line can be seen in table 5. This was done by

comparing the sample cup without inoculant additions with one cup containing 0.05% SMW605 and

one cup containing 0.05% 9N23. It shows that there is a difference in what value of the eutectic

minimum temperature that they portray.

Table 5: Shows the difference in TEmin temperature for the two inoculants used.

SMW605 9N23 DT

1148.2 1146.8 1.4 1146.8 1144.6 2.2 1147.5 1142.5 5.0 1146.3 1144.0 2.3 1146.0 1145.2 0.8

Effects of slagging Figure 38 shows the effect of slagging has on the DTEmin which is important to document too ensure

measurement accuracy. The melt was heated up to 1400 °C and the test was taken the same time as

the operators take the spectrometer sample and the TL for the melt. The second test was taken after

the melt had been heated up additionally to 1460 °C and the slag had been removed. The figure

shows that there is no difference in the DTEmin if the sample is taken before and after de-slagging if

they are taken within in a short time interval.

Figure 38: DTEmin before and after slag is removed from the melts surface in the oven.

Effect of carbon additions to DTEmin Figure 39 shows DTEmin before and after the addition of four cups of carbon addition to lower the TL

that was at 1144 °C. The second sample was taken 15 minutes after the carbon addition. The figure

shows that 15 minutes after carbon has been added it will not have any effect on the DTEmin.

5,2 5,4

0

1

2

3

4

5

6

7

8

9

10

0 1

DTE

min

[°C

]

De-slagging

38

Figure 39: Shows DTEmin before and 15 minutes after carbon additions.

Increased temperatures effect on DTEmin Figure 40 shows the DTEmin before and after the oven has been idling at a temperature of 1570 °C.

The figure shows that an increased temperature of the oven will lead to a rapid decrease of the

inoculant level.

Figure 40: DTEmin vs time. The fading of inoculant over one hour at 1570 °C.

Comparison of nucleation level between ladle and oven Figure 42 shows a comparison of the level of inoculation when taking samples from the oven after

each ladle removed and samples taken from each ladle taken from the oven. The starting value

“zero” is equal to the starting value in the oven when no ladle has been removed which should be

the same value as the first ladle will have. The measurements from the two different lines are not

from the same oven so the value of the numbers should not be compared but the “behaviour/

4,74,5

0

1

2

3

4

5

6

7

8

9

10

0 1

DTE

min

[°C

]

Carbon addition

7,5

20

0

5

10

15

20

25

0 0,2 0,4 0,6 0,8 1

DTE

min

[°C

]

Time [h]

39

tendency” of the level of inoculation should. Both lines in the figure show the same tendency to

increase and decrease of the inoculation level.

Figure 41: DTEmin vs ladles taken from oven. The trend between the test taken from the ladle and the oven.

Chemical analysis Table 6 shows the chemical composition of ten CGI400 batches taken both from the oven and from

the first ladle using a spectroscope. Table 7 shows the chemical composition of five CGI425 ovens

and table 8 the composition for three CGI450 ovens. The average composition for the three different

types of CGI can be seen in table 9. The samples for the spectroscope are taken when the melt has

been heated up to 1400 °C. When comparing the composition for each grade of CGI no correlation

could be seen between amount of each alloying element and DTEmin.

Table 6: CGI400 composition for 10 samples.

C [wt%]

Si [wt%]

Mn [wt%]

P [wt%]

Cr [wt%]

Mo [wt%]

Cu [wt%]

Sn [wt%]

Ti [wt%]

DTEmin [°C]

3.63 2.22 0.343 0.025 0.0245 0.0042 0.864 0.0615 0.00401 12.8

3.71 2.23 0.338 0.028 0.023 0.0037 0.852 0.0614 0.00464 7.1

3.76 2.34 0.348 0.027 0.024 0.0045 0.853 0.0585 0.00547 6.2

3.56 2.18 0.378 0.027 0.039 0.0098 0.851 0.0545 0.00635 2.3

2.68 2.22 0.405 0.028 0.025 0.0033 0.886 0.587 0.00683 5.2

3.61 2.25 0.402 0.029 0.021 0.0031 0.916 0.0655 0.00737 2.1

3.58 2.25 0.434 0.028 0.026 0.0040 0.899 0.0576 0.00868 7.8

3.68 2.26 0.299 0.028 0.024 0.0049 0.885 0.0545 0.00403 4.4

3.62 2.26 0.391 0.247 0.039 0.0097 0.901 0.0545 0.00616 6.7

3.60 2.29 0.399 0.028 0.026 0.0051 0.896 0.0558 0.00696 5.7

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5

DTE

min

[°C

]

Ladles taken from oven

Oven Ladle

40

Table 7: CGI425 composition for 5 samples.

C [wt%]

Si [wt%]

Mn [wt%]

P [wt%]

Cr [wt%]

Mo [wt%]

Cu [wt%]

Sn [wt%]

Ti [wt%]

DTEmin [°C]

3.68 2.21 0.398 0.0266 0.0238 0.00382 0.891 0.0664 0.00588 4.0

3.62 2.21 0.342 0.0255 0.0255 0.0072 0.897 0.0586 0.00427 7.4

3.62 2.20 0.314 0.0273 0.03 0.0106 0.928 0.0693 0.00406 3.6

3.60 2.30 0.327 0.0259 0.0236 0.00226 0.958 0.0744 0.00611 5.2

3.51 2.22 0.269 0.0259 0.0217 0.00291 0.939 0.0704 0.00658 4.7

Table 8: CGI450 composition for 3 samples.

C [wt%]

Si [wt%]

Mn [wt%]

P [wt%]

Cr [wt%]

Mo [wt%]

Cu [wt%]

Sn [wt%]

Ti [wt%]

DTEmin [°C]

3.64 2.30 0.304 0.027 0.0245 0.00653 0.99 0.0854 0.00481 6.3

3.57 2.29 0.336 0.027 0.032 0.00324 0.988 0.0824 0.00652 1.2

3.66 2.37 0.321 0.0258 0.0231 0.00631 0.978 0.0896 0.00623 7.3

Table 9: Average composition for CGI.

Charged material Table 10 shows the average amount of each material that is added to each charge of the different

compositions of CGI. This is based on seven charges of CGI400, three of CGI 425 and four CGI 450. It

shows that CGI450 and 425 have more pig and scrap iron in the charge and a lower DTEmin.

Table 10: Average amount of the ingoing material in a charge for the different CGI compositions and the average DTEmin for the samples used..

Grade of cast iron Pig iron [kg] CGI- returns [kg] Scrap iron [kg] DTEmin [°C]

CGI450 2903 2672 3602 5.4

CGI425 2947 2763 3680 5.2

CGI400 2624 2621 3394 6.8

Thermocalc Figure 42-43 show the stable and the metastable phase diagram for a Fe-C alloy. Table 11 shows the

both liquidus temperature and the temperature when the melt has completely solidified when using

the Scheil- Gulliver model with a CE of 4.23%. It shows the different phases, the difference in

eutectic and eutectoid temperatures and when the two systems are completely solidified. The

metastable solidification which needs increased undercooling has a lower temperature for all the

above.

Average

C [wt%]

Si [wt%]

Mn [wt%]

P [wt%]

Cr [wt%]

Mo [wt%]

Cu [wt%]

Sn [wt%]

Ti [wt%]

CGI400 3.64 2.24 0.37 0.027 0.0027 0.0052 0.88 0.058 0.0060

CGI425 3.61 2.23 0.32 0.027 0.025 0.0054 0.92 0.068 0.0054

CGI450 3.62 2.32 0.32 0.027 0.027 0.0054 0.99 0.86 0.0059

41

Figure 42: The stable Fe-C phase-diagram constructed using Thermocalc.

Figure 43: The metastable phase-diagram constructed using Thermocalc.

Table 11: The liquidus temperature and the temperature when the metal is completely solidified for the stable and metastable system using Thermocalc.

Solidification TL [°C] 100% solidified [°C]

Stable 1165.8 1153.4

Metastable 1165.8 1148.2

42

Comparison of cups Table 12 shows the difference between the TL measurements between the normal testing cup used

to establish the inoculation level and the tellurium cup used in production. Ten samples were used

for the experiment with a combination of the different grades of CGI, for this experiment the grade

does not matter because it is the difference between the values that are of importance.

Table 12: Difference in liquidus temperature for the testing cup with no inoculant additions and the tellurium cup.

TL, testing cup [°C] TL, tellurium [°C] DT [°C] 1139.2 1137 2.2 1137.3 1136 1.3 1140.6 1134 6.6 1139.1 1142 2.9 1140.5 1145 4.5 1140.9 1139 1.9 1141.9 1140 1.9 1141.4 1145 3.6 1140 1140 0 1140.5 1143 2.5

The average temperature difference between the two cups were 2.75 °C.

Discussion

Average inoculation level The average inoculation level was established for all CGI compositions. For CGI400 the average was

6.7 and the median 6.3 when analysing 19 tests at time t=0. For CGI425 and CGI 450 the value was a

bit lower with a median and average of 5.0 for CGI425 and a median value of 4.7 and average of 5.4

for CGI450. The results for CGI450 and CGI425 are only based on nine measurements combined. The

only reason that fewer tests has been done on these compositions is that more CGI400 products are

produced at Scania and there for more ovens are run that test can be conducted on. CGI425 has 25%

lower average and CGI450 20% lower average then CGI400.

A few tests gave very high numbers, the highest being 12.4 and some low, the lowest being 1.2. No

clear explanation can be given to these deviating results. The very low ones could be due to

operators adding carbon just before the test without notifying the tester. This would give a what is

called a “fake” inoculation level. This would only last a few minutes before dropping. One thought

was that perhaps slag had been trapped in the testing cup, but no slag particles could be seen in the

microscope.

For a melt to be considered to have a sufficient level of inoculant the value of DTEmin should at least

be below three and preferable below two. Both the values of 6.7 and 5.2 are far from ideal but the

values were to be expected. The Sintercast ads inoculants to every ladle so it would be concerning if

this was not the case. This is the average starting value in the oven and it is not until the melt has

been poured into the ladle that the level will be adjusted just before being cast.

Saturation point The starting inoculation level for the melt is too low as mentioned previously so the level of

inoculation addition to reach the saturation point is of most interest. The tests conducted shows that

for all tests with DTEmin with starting values ranging from 3.2-6.4 the saturation point could be

found between the cups with 0.05 and 0.1wt% additions as seen in table 13. This shows that an

43

addition of 0.05wt% inoculant is needed to reach the saturation point where DTEmin is less than

three. This also proves that a big difference in DTEmin like three and six is not so big when it is

converted to inoculation additions.

Table 13: DTEmin for the five tests taken for the different inoculant additions. The t denotes hours after the first measurement was taken.

Testing of inoculant additions to the ladle The results from this test was not at all as expected. When conducting test on the first oven the

starting DTEmin for the oven was 5.3, because of technical difficulties the first sample was taken first

on ladle three. Ladle three, four and five all showed similar values but the DTEmin was higher than

the starting value in the oven after inoculation had been added. When samples are taken, the first

cup without inoculation is filled just as the ladle is moving from the oven to the casting floor. The

second sample is taken when the TEmin can be identified by the software and the melt for the cup

with inoculations is taken roughly at the same time as the ladle reaches the cast floor, approximately

1 minute later. One reason could be that perhaps the inoculant had not had time to mix properly

when the first sample was taken, leading to low TEmin values. For the second test the order of how

the samples were taken were switched, now the cup with inoculant was filled first. The result was

the same. When comparing figure 33 and 34 the difference between the lowest and the highest

value is 0.6 which can be neglected as measurement error.

One would assume that the inoculant had enough time to dissolve because when the inoculant is

added in production it is feed quickly into the melt and then casted shortly thereafter. In this case

the melt is poured on top of the inoculant which should lead to good mixing and a homogeneous

melt. One thought is that the inoculant is oxidized too quickly. A little bit of melt is almost always left

in the ladle and when the inoculant is added to the left-over melt fading will start to occur. The time

from when the inoculant is added to when the melt is poured is just a few minutes. One last reason

that perhaps the easiest is when the melt is poured in excess temperature of over 1500 °C the

inoculation fading will be very rapid which is seen in other test conducted. This together with the

other factors mentioned is most likely the reason for the poor inoculant exchange to the melt.

When comparing the inoculation index on the Sintercast software, no increase could be detected on

the ladles that were treated with additional inoculation compared to the ladles that was not. This

tells us as well that this way of adding inoculant is not working.

The test shows that this is not a sufficient way of adding inoculants to a melt.

Inoculation fading over time When analysing the results of how the DTEmin changes over time some trends can be noticed. For

the first two hours for all the test conducted there is an increase in DTEmin, the level of inoculant has

decreased, fading has occurred. Up to three hours fading has occurred in most of the test, but after

four hours after first seeing a fading of inoculation a decrease of DTEmin can be seen in all tests. This

was not expected. If we look at the eight-hour test conducted seen in figure 23 a steep increase in

DTEmin can be noticed up to 2.5 hours from T=0. Between 2.5- 6 hours a small decrease can be seen.

Inoculant additions t=0, DTEmin [°C] t=2.5, DTEmin [°C] t=4, DTEmin [°C] t=7, DTEmin [°C] t=8, DTEmin [°C]

0-0.05 5.9 6.4 3.3 3.2 5.7

0.05-0.1 0.8 1.4 2.7 2.4 0.6

0.1-0.15 2.1 1.7 1.9 0.6 1.7

44

This small difference could be due to measurement error, but after six hours a large decrease can be

seen that cannot regarded as a measurement error.

One possibility why there is a decrease in DTEmin after a period could be because of the erosion of

the lining in the oven. The lining used in the ovens are provided by Calderys and is of the type SILICA

MIX Q 16. This ceramic as the name entails is based on Si which can also be found in the inoculation

agent. It is a known fact that the lining of the oven will erode over time and high temperature,

stirring and long exposure to high temperature will increase erosion. This lining is changed every six

weeks as an average and if the weight of lining that is eroded is divided by the ovens run

approximately 1.1-1.2 kg of the ceramic is goes into the melt. This would amount to 0.012wt% of the

melt. So, one thought is that when the oven has been sitting for a long period of time, the melt has

cooled down, reheated for a longer period Si from the lining will be realised to the melt.

Other reasons could be that over time the melt at the surface start to oxides increasing the

nucleation points, especially after the slag is removed that protects the melt. Another is that slag

particles dissolve in the melt, but this has not been seen in the samples viewed in the LOM.

The increase in DTEmin if comparing the starting value with the highest is not that big. A bigger

difference was expected, the largest difference seen was 5.3 and for that test the starting value was

very low, below the saturation point.

Grain size and density When investigating the microstructure of twelve different samples with a DTEmin ranging from high

to low, one can clearly see the correlation. With increased difference in eutectic minimum

temperature between the two cups means less inoculation particles in the melt, which leads to fewer

nucleation points. Fewer nucleation points will lead to fewer grains that will have space to grow

larger. That is what the figure 35 and 36 shows us. Increased grain size should lead to a decrease in

grain density, which the figures show. The line fitted for the data points in figure 35 has an R2 value

of 0.9338 which is very high. The R2 tells us how well a model fits the data points. This means that

there is a 93% chance that by using this model that other points would be on that line. Using

equation 5 given an x value it will give a y value, so the point ends up on the line. This equation for

the model is exponentially growing, which means that the grainsize will grow exponentially with

increasing DTEmin. The line shown figure 36 has an R2 of 0.8545 which is also high and is also

exponentially fitted curve. No previous compression between DTEmin and grain size and density has

not been found to compare with.

Addition of scrap iron The addition of scrap iron is for ovens that have been sitting, idling for a longer period. This is done

to replenish the Si that has burnt off without altering the composition. Figure 37 shows that by

adding wrought iron you will decrease the DTEmin for the melt. By this addition you create

movement, this from the temperature difference between the melt and the iron. This will create

convection stirring which will homogenise the melt and the Si will work as nucleation points.

Effects of inoculants used When comparing the DTEmin for the two different inoculants a difference can be seen in the results.

The difference is rather small and could have to do with the accuracy of the measurement

equipment. The test was the difference is 5 °C cannot on the other hand be blamed on that. For best

accuracy, the inoculant used in production should be used. Different inoculants will have different

saturation points so the one used in production should be used to be able to establish inoculation

additions.

45

Effects of carbon additions As mentioned previously additions of carbon can give a fake nucleation level but it is presumed to be

short lived. During other test when measuring the DTEmin operators added carbon without notifying

the tester and it was noted that after the addition DTEmin would decrease. When adding the carbon

to the oven it is done by throwing granulated carbon on the surface of the melt in the oven and

increasing the temperature of the oven to stir the melt with help of convection. The carbon yield is

very poor and a lot of it gets stuck to the slag at the surface, this will lead to the fake nucleation level

when taking the sample from the top of the oven. But as the test showed, 15 minutes after stirring is

enough time for the level to even out. The dangers of this is that when the thermal analysis is done

on the casting floor from the ladle and there is fake nucleation level an insufficient amount of

inoculation will be added to melt.

Increased temperatures effect on DTEmin It is a known fact that increased temperature and time have a negative effect on the inoculation

level. As can be seen in figure 40 the DTEmin increased a lot faster and higher than had been seen

when the oven was left at 1400-1460 °C. The DTEmin went from 7.5- 20, stating the fact that the

fading of the nucleation level is very temperature dependent.

Comparison of the nucleation level between oven and ladle Only two tests have been done and they show the same trend seen in figure 41, but the increase and

decrease does not occur after the same ladle removed. The highest value can be seen in what is left

in the oven, that is poured in the last ladle to be discarded. The decrease of DTEmin can probably be

explained by fading over time, the increase is harder to explain. It could perhaps have to do with the

increased stirring after the oven has been tilted back and forth and the extra space in the oven leads

to more movement of the melt. Also, the reasons presented previously about erosion of the lining is

valid here. When comparing the samples taken from the oven and from the ladle itself, the same

tendencies can be seen, and these are taken from two separate ovens. The time factor for moving

the equipment from the oven to the casting floor limited the possibility of taken these

measurements from the same oven. The samples from the ladle are taken before any inoculation

additions.

If the inoculation level changes between each ladle, the one-step Sintercast method is not very

reliable. If each level has changing levels of inoculant you cannot base the additions on

measurements done on the previous ladle for the next. You can end up with a melt that does not

have enough inoculant which will decrease the mechanical properties of the material.

Chemical analysis When comparing the chemical analysis for the selected samples no correlation can be seen between

the samples in terms of variation of chemical composition and the DTEmin. The variation between

the samples are relatively small due to strict min and max levels set for each element that this small

variation should not influence the DTEmin sufficiently. The elements that was analysed was the

elements that have a min and max value set by Scania. Other trace elements were detected by the

spectrometer, but due to their small percentage they were neglected.

46

Material charged When no correlation could be seen by DTEmin and the chemical composition an idea came that

perhaps it could have something to do with the charge. Of the ingoing materials is known that scrap

(wrought) iron and pig iron have a positive effect on the inoculation level. An interesting observation

was made when comparing the different CGI compositions. On an average over 10% more pig iron

and 5% more wrought iron goes into CGI425 and CGI450 compared to CGI400 when comparing what

the weight of the ingoing materials. But when dividing the CGI returns on the total amount of weight

of a charge for the different compositions there was only roughly a 1% difference between CGI425

and CGI450 compared to CGI400. CGI400 having 1% lower amount of scrap and pig iron in the

charge, which should even if it is a very small difference contribute to the improved inoculation level.

Wrought Iron shows in our test conducted that it has a positive effect on the inoculation level and

though not tested in this project it a well-known fact that adding pig iron will increase the inoculation

level. It is an old foundry trick, that one ads pig iron to a melt that is “dead”. When looking at the

average inoculation level for the two, CGI425 has a 28% lower average value and CGI450 has 20%

lower. These higher starting values of inoculation probably comes from the higher amount of pig and

wrought iron being used.

The recipe for each melt is altered depending on what is left in the oven and what composition it

had. The software used to calculate amount of the different materials in the charge takes this into

account and alters the amount of each material going into the charge to ensure each meets the

standard requirement set by Scania. This makes it hard to compare different ovens. When analysing

these four main components making up the charge does not take into consideration the alloying

elements effect on the DTEmin.

Thermocalc When the liquidus temperature is taken in production to establish carbon content, tellurium cups are

used as mentioned previously which promotes metastable solidification. The eutectic temperature as

can be seen in figure 43 is 1148 °C. This is at equilibrium and, but it is not a process in equilibrium. To

get a solidification process started there must be undercooling, the temperature must be below the

solidification point. The temperature therefore where the melt starts to solidify is below the liquidus

temperature or the eutectic temperature for a eutectic melt. A system is in equilibrium when the

Gibbs free energy is equal to zero, then it is the most stable state. This is not on the phase changing

boundary, here there is great potential for a decrease in Gibbs energy which means that the system

is not in equilibrium.

The stable phase diagram is what should be seen in the other cups not containing tellurium. As seen

in the samples taken graphite particles can be seen and not cementite. Samples containing tellurium

was attempted to be cut in half, but due the hardness of the cementite it was not successful.

When producing CGI products, the TL should be in the range of 1140- 1145°C, for the samples that

was used to get an average CE for the Thermocalc measurements the average TL was 1143°C. This is

lower than the temperature both seen in the phase-diagram at a CE of 4.23 and in table 11 showing

the TL using the Scheil-Gulliver model. The same TL was derived both for the single point equilibrium

calculations and the non-equilibrium Scheil-Gulliver model.

The phase diagram can be explained as mentioned that even though this is the starting temperature

of solidification, the melt will not have completely solidified until a below this temperature where

the undercooling is greater. When the CE is so close to the eutectic point, the liquidus temperature

47

and the eutectic temperature will almost have the same value. This would in that case correlate well

with a TL of 1143°C.

Thermocalc is a very good for thermodynamic calculations and they have very good databases that

are based on empirical data and research. It is a good tool, but these are just predictions and not

reality and other thermodynamic simulation software will get other results depending on their

databases.

Comparison of cups When looking at the comparison of the TL for the two cups, the difference is not very large. The

average difference 2.74, the problem is that there are some samples were the difference is quite

large, 6.6. This would not be tolerated when there is only a 5 degrees interval. The software that

calculates the TL using the cups uses an equation that considers the volume of the cup, which is

different for the two cups. That together with the tellurium additions is what sets the cups apart.

Perhaps with more testing a correlation can be established between the cups but for the most

accurate reading of the TL the cups with tellurium should be used hence that is what they are

designed for.

Overall discussion When analysing the results gathered from all the different test conducted, is this a good method to

establish the inoculation level in the melt? I would say yes. The microstructure analysis shows that an

increase in DTEmin will have a negative effect on the grain size and density which will have a

negative effect on the mechanical properties of the finished product. If the result would not show

this there would be something wrong. The R2 is very high which increases the credibility of the

model used for the grain size and density.

A correlation can be suspected between the saturation model and the grain size model. The

saturation model has a logarithmic appearance, which is the invers of the exponentially fitted curve

for grain size. After the saturation point has been meet in a melt the TEmin difference between the

two testing cups are low, it reaches a minimum. The same can be seen for the grain density, it first

has a sharp decrease in grain density that later slows down not unlike the saturation of a melt but its

invers. A saturated melt will lead to an increase in grain density, which means a decrease in grain

size.

The starting level of inoculation is to low, which was no surprise. I gather that there are three

different alternatives to increase the level. Either a base inoculant treatment should be given straight

into the oven before being poured into the ladle. The benefits of this is that it is simple and easy to

do. The downside of it is that it must be mixed into the melt and due to fading time will be a factor

and should be poured into a ladle and cast right away.

The second approach would be to ad inoculant into the first ladle poured. This way one will get good

mixing of the inoculant when the melt is poured into the ladle with the inoculant additions, and

fading will not be an issue because it will be cast right away. The only problem with this method is

that the inoculant additions for the next ladle is based on the previous one. If the first ladle has high

inoculant values the next ladle will not get enough. The Sintercast system would have to be adjusted

for this.

The test conducted when adding inoculant to the ladle was not successful and why is unclear. Adding

inoculant to the ladle or straight in the mould is a proven technique that is used in industry. The

inoculant used in the test was probably not designed for this method of additions and other factors

mentioned earlier also contributed.

48

The third approach would be to be able to connect the results given by the testing cups with the

Sintercast system if that is possible. The results so far show that 0.05wt% inoculant is sufficient to

reach the saturation point. If this information could be relayed to the Sintercast system for the first

ladle, this would solve the problem. The other ladles can then be based on the test results provided

by the Sintercast system. as mentioned previously though is the issue with alternating inoculation

levels in the ladles taken from the oven. This is problematic if the treatment for the next ladle is

based on the previous, though when conducting tests 0.05wt% was enough to inoculate DTEmin

from a range of over 6 to 3. Still, it should be mentioned.

The test has proven when the samples should be taken and what effect material additions will have

on the melt both short and long term. Pig iron is known to increase the inoculant level though not

tested for this report. Scrap iron was proven to increase the inoculant level in the test conducted. Pig

iron is expensive compared to other resources and wrought iron comes from in-house returns and

not in great volume. Another cheap way of introducing inoculant should be investigated.

The main issue will be how to incorporate this into production. This will mean extra work and

knowledge required by the operators and will add some more time to the process. Minimize the

number of cups needed for the different measurements have been tested and should be further

investigated if it is possible. Even though this extra time and money for the extra equipment, it

cannot compare to the savings it can lead to with a decrease in discarded products.

Conclusion Thru out this project the main goal was to test how well thermal analysis works on establishing the

inoculant level and if it can be used in production. Now the inoculant level is measured in the ladle

but with the help of thermal analysis the hope was to retrieve this information already in the oven.

The conclusion that can be drawn from this project is the following:

• The DTEmin is above 3 which means that the starting level of inoculant is too low in the

oven.

• 0.05wt% inoculant additions should be added to reach the saturation point.

• The tests showed that an increase in DTEmin will decrease the grain density and increase the

grain size.

• Fading of inoculant occurred when the oven was sitting idling for the first 2-4 hours.

• Increased temperature increased the rate of inoculation fading.

• Carbon additions temporarily gave a false inoculation level that was dispersed 15 minutes

after.

• Additions of scrap iron in the charge will increased the inoculant level.

Before this tool is used in further research should be done how it can best be implemented into

production.

49

Further research As mentioned in the discussion further research should be conducted to see what the best way of is

increasing the nucleation level. We have the three options mentioned, either in the oven, ladle or

that the Sintercast system accounts for the low value for the first ladle. Other options are probably

available that have not been mentioned in this report.

Further investigations should be done in how the charge material can be best altered to get a better

inoculant level in the melt. Pig iron is proven to have this desired effect, but it is not very cost

effective. Is there any other in-house discarded material that can be used?

One result that was surprising when measuring the fading effect over time is that the inoculant level

increased after a certain period. On possibility of this was the deuteriation of the lining of the oven,

but more research should be put into this matter.

As mentioned earlier is that the goal of this report was to conclude if thermal analysis could be used

sufficiently to measure the inoculation level and an answer to that has been given. Further research

must be done on the accuracy of the tests. Several samples should be taken at the same time or right

after each other to see what the standard deviation is between the results. How accurate are they

and what is the source of error? This is hard to do when working and testing in production, but by

testing this in lab one limits the variables you cannot control and that why area able to just alter one

thing and see what affect it gives.

Sources of error When filling the sand- cups there might be some unwanted factors that might affect the results.

There might some variations in the fill volume which is used for the calculations and the tap

temperature that can affect the results. The sand cups geometry will alter, first the sand will absorb

the heat which will lead to the binder to soften which will change the geometry. Also the pour-in

filling technique will introduce impurities as the metal oxidizes when in contact with air and air

entrainment when filling is also of concern [38].

When collecting samples from the oven communication is key between the one taking the samples

and the operators. It happens that there are some miscommunications that can lead to unwanted

results. Such as carbon is added before the two samples are needed to compare the results. This can

almost always be detected in the results or it is noticed just as it happens. There is still a small chance

that something like this has gone undetected.

50

Acknowledgment I would like to give a special thanks with a deep sense of gratitude to the individuals that made it

possible for me to conduct and finish my master thesis.

Isak Hollinger and Jessica Elfsberg that gave me the opportunity to do my master thesis at Scania.

My supervisors at Scania: Mitra Basirat Engström PhD, Mostafa Payendeh PhD and David Lindström

PhD who guided me and made sure I could conduct all the test necessary to finish my thesis even

though times very tough.

Fareed Khan at STC, Scania who showed me how to colour etch and analyse my samples.

To all the operators and engineers at the foundry that showed me around an helped me with my

experiments. Without you it would not have been possible.

To my supervisor at KTH Björn Glaser who helped me with my report and made sure everything was

going well.

51

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