Process Development Strategies for

Energetic Materials

P. Dube, M. Jorgensen, S. Lenahan, L.J. Ping and J. S. SalanNalas Engineering Services, Incorporated, Centerbrook, CT

860-861-3691

1

What do we do?

• Transition chemical processes to the plant environment– Identify engineering challenges including heat transfer, mass transfer, and kinetics

– Evaluate chemistry in the laboratory using in situtools (IR, Raman, FBRM, PVM, heat flow)

• Evaluate pilot and production equipment. Validate processes through scale-down experiments.

• Develop low-cost chemical processes

2

Our Model

3

Process Development

Engineering

ChemistryAnalytical

• process understanding

• Scale-up support

• process modeling

• predictive experimentation

• scale-up assessments

• in-situ monitoring

• low-cost processes

• screening guidance/support

• bond forming steps

• transfer best technology available

• analytical support for reactions

• isolated intermediate and API

characterization

• in-situ support for process

monitoring and understanding

• Teamwork

• understand goals

• understand and accept

responsibilities of each group

Energetic Materials

Simply Special Chemicals

• Explosives, propellants, pyrotechnics,

reactive materials, related chemicals and

fuels, and their application in propulsion

systems and ordnance

4

Explosives

• Stimuli that can make materials react

– Impact

– Friction

– Electrostatic discharge

– Thermal

• In-situ monitoring makes sense

– Heat flow

– Spectroscopy

– Particle size analysis

– Gas evolution

5

Bond Forming Steps

Oxidations

6

Intermediates in the oxidation of an amine to the nitro

N

N N

NH2NH2

CH3

N

N N

NH2NO2

CH3

DAMT

N

N N

O2N NO2

CH3

DNMT

NAMT

Selectivity

Tailored Reactivity

Selectivity

We love nitro compounds

Selectivity

• Your toolbox…

• Kinetics

– DynoChem

• Mass Transfer

– VisiMix

• Heat Transfer

– Mettler Toledo AutoChem

7

N

N N

NH2NH2

CH3

N

N N

NH2NO2

CH3

DAMT

N

N N

O2N NO2

CH3

DNMT

NAMT

N

N N

NH2NH

CH3

OH

N

N N

NH2N

CH3

O

N

N N

NH NO2

CH3

OH

N

N N

NNO2

CH3

O

N

N N

NH2N

CH3

N

NN

NH2N

CH3

N

N N

NH2N

+

CH3

N

NN

NH2N

CH3

O-

Process Details

• Add hydrogen peroxide

• Add DAMT-HNO3

• Add sodium tungstate dihydrate

• Ramp to T=80°C over 2 hours

• Hold for 4 hours

• Notes:

– No control of pH

– All ingredients in the reactor prior to heat ramp8

Heat Flow• Potential challenges

– Hydrogen peroxide’s stability is influenced primarily by temperature, pH and impurities.

– The existing process calls for the addition of all reagents at low temperature…1. Hydrogen peroxide

2. DAMT-NO3

3. Catalyst (sodium tungstate)

Followed by a temperature ramp to T=80°C

– Having all ingredients in the reactor presents a dangerous situation; the reaction has the potential to release all heat associated with the reaction(s) at one time

– PLUS hydrogen peroxide stability is questionable9

Heat Flow • How do we typically control heat generated from a reaction?

– Dose reagent or substrate to control conversion as well as accumulation (unreacted) of starting materials

– Elevate the temperature (activation energy) to assist in getting the reagents to react faster and minimize accumulation

– Avoid temperature ramps without knowing

1. exactly how much unreacted material remains prior to ramp

2. how much heat will be generated when it is converted at the ramped temperatures (know your side reactions!)

3. Can your system handle it?

10

11

(Francis Stoessel, Thermal Safety of Chemical Processes, Risk Assessment and

Process Design. 2008, Weinheim: Wiley-VCH. ISBN: 978-3-527-31712-7)

Dec. 23, 1969. Year of Woodstock!

Increased demand for blue jeans.

12

(Francis Stoessel, Thermal Safety of Chemical Processes, Risk Assessment and

Process Design. 2008, Weinheim: Wiley-VCH. ISBN: 978-3-527-31712-7)

Reactor afterwards. The lid was 700 meter away from the site. Five fatalities, 31

injured. There was a lot of pride in the city of Bassel because of the chemical

industry doing so well. There was consequences to people being killed and injured.

Heat Flow Summary

13

Qflow: heat flow through the reactor wall U: overall heat transfer coefficient of the reactor wall W/(m2 K)A: heat exchange area (wetted area) m2Tr: temperature of the reactor contents °CTj: temperature of the jacket °C

Qaccu: heat storage (accumulation) by the reaction mass Mr reaction mass (sum of all additions and dosings) gCpr specific heat capacity of the reaction mass J/(g K)dTr/dt current change in the temperature of the reaction mass K/s

Qdos: heat input due to dosing dMr/dt mass flow of all added substances g/sCp dos specific heat capacity of the added substances J/(g K)Tr current temperature of the reaction mass °CTdos temperature of the added substances °C

Qreaction =Qflow + Qaccumulation + Qdosing

Qr = U A . (Tr - Tj) + Mr . Cpr . dTr/dt + dMr/dt . Cpdos . (Tr - Tdos)

Tdos

Qdos

Qaccu

QflowTj

Tr

Calibration Calculated Enter value

Heat of reaction calculation (Qr) based on heat flow balance:

Heat Flow Summary w pH

14

Heat Flow Summary w pH

15

• Hydrogen Peroxide (35%)

Heat Flow Summary w pH

16

• Hydrogen Peroxide +

• DAMT-NO3 Salt– Slurry

• Mass transfer…what happens when things go into solution?

Heat Flow Summary w pH

17

• Hydrogen Peroxide (35%) +

• DAMT-NO3 salt +

• Sodium Tungstate

Heat Flow Summary w pH

18

• Temperature Ramp, Tr~30°C

• Solution-note heat output

FBRM

• FBRM probe optics are rotated

at a controlled high speed, and

the focused laser beams scan

across the particle system in a

circular path19

Introduce FBRM

• FBRM great way to nail down exactly when crystallization events occur.

20

Black line = FBRM counts

Heat Flow Summary

21precipitation

• As ramp progresses, gas

evolves

• Solids form

dissolution ?

N

N N

NH2NH2

CH3

N

N N

NH2NO2

CH3

DAMT

N

N N

O2N NO2

CH3

DNMT

NAMT

Selectivity

Tailored Reactivity

Selectivity

Black line = FBRM counts

Decomposition?

• Shortly after solids form, gas evolution is noticed (T~63°C)

• Gas evolution continues as ramp progresses producing a large foam cap over time.

• Notes– Gas evolution significantly influences heat flow and subsequent calculations

– Decomposition reactions generate heat. This is not produced from your desired reaction. It is very important to know which reactions contribute heat and quantify these contributions.

22

Dissolution Again!

• ~25 minutes after ramp complete, T=80°C.

• Whatever intermediate that is forming is soluble in the reaction mixture.

• Finally, solids precipitate again but are not pure. Solids are a mixture with primary component desired product. Big ‘gumball’ forms.

23

Heat Flow

• Customer: Going to the 200-gallon scale

• How much heat can the reactor remove?

24

Black line = FBRM counts

What is safe?

25

Data source: Pilot Plant Real Book

Good rule of thumb is 50-60 Watts/liter

Watts/Liter f(t)

• l

26

W/l

∆∆∆∆Tadiabatic = 278 K!

Temperature Ramp

• In the laboratory the surface area to reaction volume is high. Very easy to remove heat through jacket wall.

• In the plant, the surface area to reaction volume is low. Very difficult to remove heat through jacket wall.

• Quantifying (RC1) the heat AND profile are key to determining scaleable process.

• Suggestion: Eliminate the temperature ramp through controlled dose of hydrogen peroxide.

27

Reactions

• Desired-

• Undesired-

• Undesired-28

N

N N

NH2NH2

CH3

N

N N

NH2NO2

CH3

DAMT

N

N N

O2N NO2

CH3

DNMT

NAMT

Selectivity

Tailored Reactivity

Selectivity

2 H2O2 → 2 H2O + O2

2 H2O2 + catalyst → 2 H2O + O2 + catalyst

Hydrogen Peroxide

29

Hydrogen Peroxide

+ Catalyst

30

Emergency program initiated

Overlay Heat

• Competitive reactions, little control during scale-up

31

Reaction

Hydrogen Peroxide

Hydrogen Peroxide

& Catalyst

• As temperature rises, kinetics faster

• As temperature rises, hydrogen

peroxide consumed!

Pics Hydrogen Peroxide

+ Catalyst

• As the temperature progresses more gas is generated until finally the material ejects from the reactor.

32

Video Hydrogen Peroxide

+ Catalyst

33

SummaryMto this point

• Reaction is highly exothermic and includes temperature ramp

• The 200-gallon Pfaudler will not adequately remove heat generated from this reaction.

• Decomposition of hydrogen peroxide is contributing to some degree. Catalyst exasperates the decomposition.

• The degree of decomposition depends on ramp rate and kinetics of reactions– As hydrogen peroxide is consumed to produce intermediates, products and impurities, it is no longer available to participate in decomposition reaction

– For this reason, the amount of heat generated from decomposition is highly dependent on temperature ramp rate (temperature) and kinetics.

• Scaleable?34

Analogous System

C C

N

O

N

N N+

CC

N

O

N

NN

H

H H

H

O

C C

N

O

N

N NO2

H

H

C C

N

O

N

N N

H

H H

H

C C

N

O

N

N NHOH

H

H

C C

N

O

N

N N O

H

H

C C

N

O

N

N N

CC

N

O

N

NN

H

H H

H

3,4 diaminofurazan 3-amino,4-nitrosofurazan3-amino-4-(hydroxyamino)furazan

diaminoazoxyfurazan

aminonitrofurazan

diaminoazofurazan

DAAzF

DAF ANF

DAAF

35

EasyMax Screening Results

pH Lot Number

Area Percent (Isolated Solids)

DAF ANF DAAF DAAzF16.03

min

16.51

min

Isolated

Yield

DSC

Onset

(°C)

Varies BATCH 1.52 0.13 94.89 0.44 1.23 0.96 N/A 253.34

6 NAL-02-111 1.40 0.06 91.25 1.17 3.50 2.63 82.76% 250.19

6.5 NAL-02-114 1.28 0.08 93.58 1.20 2.13 1.73 80.88% 252.19

6.8 NAL-02-134 1.25 0.08 95.51 0.42 1.37 0.99 75.41% 254.47

7 NAL-02-110 1.23 0.08 95.77 1.05 0.95 0.92 57.16% 254.48

Thermal stability increases with increasing pH

Yield decreases with increasing pH

36

N+

N NO

NH2N

NO

NH2

N

N+

N N

O

N

O- O

-

N

N NO

NH2N

+

NO

NH2

N

N+

N N

O

N

O-

O-

Batch Experiments• Challenge: charge reagents as fast as possible while maintaining pH.

• Approach: Using pH control feedback loop, charge oxidizer quickly. Quench ENTIRE reaction at different time points. Dilute entire reaction mixture as ‘sample’ for HPLC analysis. Repeat as necessary.

• Results: Input concentration profiles to DynoChem for fitting.

Solution.DAAzF (Exp) (mol)

Solution.DAAF (Exp) (mol)

Solution.ANF (Exp) (mol)

Solution.DAF (Exp) (mol)

Solution.DAAzF (mol)

Solution.ANF (mol)

Solution.DAAF (mol)

Solution.DAF (mol)

easymax eight reactions at pH6.5 25C

Time (min)

Pro

ce

ss p

rofil

e (

se

e le

ge

nd)

0.0 30.0 60.0 90.0 120.0 150.00.0

0.0012

0.0024

0.0036

0.0048

0.006

37

About Mixing

• Mixing is often neglected until there is a problem at the plant scale. Why?

• Mixing DOES NOT SCALE

38

Round bottom flask

About Mixing

• Round bottom flask-choice of chemist

• OptiMax-choice for process development

• Batch Plant Reactor-choice for manufacturing

• What ties this equipment together during scale-up?

39

Round bottom flask

Batch OxoneTM Process

• Charge water to reactor

• Charge 3,4 diaminofurazan to reactor

• Charge sodium bicarbonate to reactor

• Charge oxidizer slowly to reactor (gas generation)

• 2nd charge sodium bicarbonate to reactor (adjust pH)

• 2nd charge oxidizer to reactor

• Filter solids

• Good stuff!

40

Nalas developed a continuous process and demonstrated

it in the laboratory producing 300-grams high quality product

Proof of Concept

• Produced over 300-grams

– 2-liter and 10-liter in series

• Particle size distribution controlled with continuous process

41

2-liter

10-liter

Filtration

1. DAF solution

2. Oxone Solution

3. Sodium Carbonate

Solution

1 2 3

Aft

er

2nd

Do

se

Oxo

ne

ho

ld p

eri

od

Results, 2-liter/10-liter

Batch

Continuous

2-liter to 10-liter run

In-situ PVM images

Design of 50-liter CSTR

Reactor 4100

Reactor 4200

ph1

ph2

Scale 1/DAF

Scale 2/oxone

Scale 3/sodium

carbonate

Pump 3

VFD: 3

Pump 1

VFD: 6

Pump 2

VFD: 5

Pump 5/DAAF slurry

Duplex Head

VFD: 4

DAAF Slurry

E-33Scale 4/sodium

carbonate (Optional)

Pump 4

No VFD

VFD: 1

VFD: 2 Buchner Filter

Process Water Drum

Diaphragm

Pump

43

MIXING MODEL NOT COMPLETE AT THIS TIME

Schedule = Go Go Go!!!!!

Pilot Scale-Two 50-liter CSTRs in Series

44

• Operated from control room

• Minimal operator ‘hands-on’ requirements

• Product had impurity that influenced thermal

stability including initial melt.

• What is the best pH?

Particle Comparison

45

1st 50-liter continuous campaign

“spherical DAAF”

2-liter to 10-liter run

Reactor Design

• Kinetic Model

– Used DynoChem

– Levenspiel plots

– Validation

• Mixing Model

– VisiMix

– Validation

46

Precipitation and Solids Dispersion

• Product is not soluble in water (solvent)

• Precipitation occurs immediately upon formation of product

• If crystals are present, growth and/or agglomeration may

dominate over nucleation

• Poor dispersion may lead

to some particles residence

time being longer than others

47

Solid-Liquid Mixing

• Dispersion of solids-physical process where solid particles or aggregates are suspended and dispersed by the action of the agitator in a fluid to achieve a uniform suspension or slurry.

• What about a continuous process?– Batch vs. continuous crystallization

– Scale-up

48What does our system look like?

poor better Ideal!

Scale-down Experiments

• Mixing parameters can be matched between EasyMax, OptiMax,

RC1, lab-scale equipment, pilot-scale equipment and production

equipment

• Mixing challenges can be identified and resolved early in

development

• It is pointless to generate data in the lab that is not representative

of data that will be generated in the plant. A mixing sensitivity

can make lab data useless and any resulting kinetic model

generated from lab data.

Reactor Geometry

• Mixing does not scale

• Use VisiMix to model conditions in the plant environment

• Use VisiMix to match these conditions in the laboratory

• Gain confidence in your process!

50

VisiMix Model

• Identify methods to control morphology and particle size

51

rpm

impeller

Definitions

• Maximum degree of non-uniformity (axial, radial)– This parameter characterizes the maximum deviation in local concentrations of the solid phase

from the average concentration in the tank. Complete uniformity of the solid phase distribution is

not always necessary. However, if actual non-uniformity is higher than 25-30%, partial settling or

flotation may occur.

• Average concentration of solid phase in continuous flow– This parameter is related to continuous flow processes. The concentration of the suspension in

the outlet point is assumed to be equal to the concentration in the feed flow. The difference

between the actual average concentration in the tank and the concentration in the flow depends on

the degree of uniformity of axial and radial distributions and on the outlet position.

• Relative residence time of solid phase– This parameter is related to continuous flow processes, and is estimated as a relation of the mean

residence time of the solid phase to the mean residence time of the suspension. Mean residence

time of the solid phase depends on the relation of local concentration in the outlet point to the

average concentration of the solid in the tank. The higher is the degree of uniformity of

distribution, the smaller is the difference in the residence times for the solid and liquid phases.

This difference can also be reduced by a correct choice of the outlet position.

52

Turbulence Parameters150 rpms 230 rpms

Energy dissipation-maximum value (W/kg) 12.7 45.8

Energy dissipation-average value (W/kg) 0.182 0.655

Characteristic time of micromixing (s) 4.00 2.11

150 rpms 230 rpms

Maximum degree of non-uniformity-axial, % 298 166

Maximum degree of non-uniformity - radial, % 13.6 10.5

Average concentration of solid phase in continuous flow (kg/m3) 4.44 6.31

Relative residence time of solid phase (ratio) 1.80 1.27

Solid-Liquid Mixing Parameters

Average concentration of solid phase in continuous

flow approaches ideality (8.0 kg/m3)

rpm

Single paddle

impeller 230 rpms

Single pitched

impeller 230 rpms

Dual pitched

impeller 230 rpms

Max degree of non-

uniformity –axial, %

35.4 39.0 97.0

Average concentration of

solid phase in continuous

flow (kg/m3)

6.32 6.08 6.86

Relative residence time

(ratio)

1.27 1.32 1.17

Characteristic time of

micro-mixing (sec)

4.63 3.79 2.79

54Best for pH control

impeller

Flow Patterns• Dual impeller-second impeller actually interferes with flow pattern, resulting in higher degree of non-uniformity

55

39% non-uniformity

97% non-uniformity2nd impeller causes local

high degree of non-uniformity

Comparison

56

2-liter/10-liter Setup Initial 50-liter setup Revised 50-liter setup

poor better Ideal!

You can always lower your dip tube!

Cost Avoidance?• Producing the material initially included the following estimated costs:– Labor ~$60K (processing, drying, packaging)

– Materials ~$50K (DAF starting material alone at $1,000/kg plus 8 week lead time)

• Not only as the material expensive but will set the project timeline further to the right due to long lead times

• Some pharma raw ingredients can cost 10Xs as much

– Analytical ~$35K

– Subtotal ~$145K (one step)

– Remember, this is ONE synthetic step! (i.e. 10 steps ~$1.5M)

• Modeling effort cost~$30K– Model reactors/process (dimensions, material properties)

– Scale-down experiments

– Analytical

– Report

• Modeling effort schedule~2 weeks total

57

Scale up Thoughts

• Producing chemistry is a challenge all by itself. Pharma targets can have 10-15 steps in Phases I/II.

• Modeling allows the user to quickly and efficiently (low cost!) evaluate how your process will run in the exact equipment to which you scale.

• Synthesis Workstations (EasyMax/OptiMax) provide a consistent and affordable solution for model validations (scale-down experiments)

58

Scale up Thoughts• Utilizing the proper tools (models and automated reactors) allows the chemical engineer to reduce risk upon scale up, provide the project a higher chance of success with fastest possible path to market.

• Chemical Engineering is not magic! It is a science that assists the team in producing processes that work in the equipment to which you will produce your product.

59

Final Summary• VisiMix allows for quick and efficient investigations related to mixing that minimize risk upon scale-up

• VisiMix allowed us to evaluate a specific reactor configuration, make appropriate changes and produce quantities of high quality material for our customer

• New focus is on reducing cost of starting material (DAF)

• Optimizing equipment trains for commercial manufacturer of product (DAAF)

• Having and knowing how to use the right tools makes the difference between SUCCESS and FAILURE

• Modeling is proven to save development time and MONEY

60