E L 3 E V I E R PII: S0016-2361(97)00065-3

Fuel Vol. 76, No. 13, pp. 1241-1248, 1997 © 1997 Elsevier Science Ltd. All rights reserved

Printed in Great Britain 0016-2361/97 $17.00+0.00

Unbiased methods for the morphological description of char structures

Diego Alvarez, Angeles G. Borrego and Rosa Menendez Instituto Nacional del Carb6n, CSIC, Apartado 73, 33080 Oviedo, Spain (Received 22 October 1996; revised 17 February 1997)

This paper shows how the most relevant morphological parameters of chars can be accurately measured with the aid of standard image analysis techniques. The descriptions of char particles thus obtained allow a more precise application of most of the classification schemes in use to date, or the production of useful data for the modelling of p.f. combustion. The application of these techniques is illustrated with a simplified scheme for the classification of char structures, with emphasis on the discrimination of the main structural types considered in current classification systems. Data obtained from the application of the proposed techniques to char samples from three coals of different rank and maceral composition clearly reflect the differences that could be expected from the plastic properties of the parent coals. The accuracy and objectivity of the measurements by these techniques make them a valuable tool for improving the repeatability and reproducibility of char petrographic analyses. © 1997 Elsevier Science Ltd.

(Keywords: chars; morphology; classification)

There is considerable evidence that the accessibility of oxygen to the carbonaceous material which forms char particles governs the gasification process under the con- ditions typical of p.f. combustion r-3. Numerous research groups have attempted a microscopic description of the

4 8 different structural types of char particles - . In most cases, the aim of the studies has been to create a classification system which enables an operator to describe char samples in terms of the relative populations of different struc- tural types. The existence of certain well-defined structural types has been acknowledged by most of these authors. Thus, very swollen structures with a large devolatilization hole are commonly referred to as cenospheres, while particles having a number of degassing vesicles with regular sizes homogeneously distributed across their volume are usually called networks; finally, solid structures with very low porosities are also taken into account in the various classification systems. The wall thickness of char structures is also commonly regarded as a key parameter in describing their compactness.

Image analysis has also been widely used for the structural characterization of chars and different methods have been developed for this purpose, their main advantages being the avoidance of subjectivity in the analysis and increased accuracy of the measurements. Thus a computer

9 simulation of char combustion has been proposed and frequently used 1°-12 as a straightforward way of estimating the accessibility of oxygen to the char material. This procedure is able to measure the relative amounts of carbonaceous matter at any depth from the outer and pore surfaces of the char material, thus providing valuable information not only about the structure of pyrolysis chars but also about its variation during combustion, provided that

the reaction occurs according to the proposed model, i.e. continuously progressing inwards from the outer and pore edges of the char material and at the same rate regardless of the size of these pores. This method describes char samples as a whole rather than as the sum of individual particles, and thus the possibility that certain char types could be particularly prone to incomplete burnout is difficult to assess. To the present authors' knowledge, only one attempt has been made to describe individual particles through image analysis 13. These workers collected binary images of selected char particles from different samples, classified them according to a system derived from Bailey et al. 8 and then measured some of their most relevant structural parameters using image analysis techniques. Considerable overlap was found to exist between the porosities of thin-walled cenospheres and networks, and the same was observed with thick-walled structures. On the other hand, the authors succeeded in discriminating thick- and thin-walled structures using the Euclidean distance transform, but no actual measurements of wall thickness were made.

In any case, both the manual and the image analysis approaches have had only limited success in correlating the microscopic structure of chars and the characteristics of the parent coals or their combustion performance. It is believed that this situation could be improved if the subjectivity implicit in the description of char types in manual classification systems could be suppressed and accurate measurements could be obtained of the structural parameters needed for their application (porosity, wall thickness, distribution of carbonaceous matter across the char sections, etc.).

In this paper, improved methods of char characterization

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Morpho/ogica/ description of char structures: D. A/varez et al.

based on image analysis techniques are proposed, their main advantages being the accuracy with which structural parameters are measured and the absolute objectivity in the classification of char structures.

EXPERIMENTAL

Char preparation Three coals were selected for this study: E1 Cerrejon

(Colombia), Van Dykes Drift (South Africa) and Taft Merthyr (UK). El Cerrejon and Van Dykes Drift are high- volatile bituminous coals with different inertinite contents (17.8 and 67.6 vol.% respectively), whereas Taft Merthyr is a semi-anthracite with a moderate to low inertinite content (23.3 vol.%). The chemical and petrographic characteristics of these coals are shown in Table 1. The coals were ground and sieved to a size fraction of 36-75/~m, which was fed to a drop-tube furnace (DTF) to obtain the corresponding chars. The pyrolysis tests were carded out at 1000°C in N2 atmosphere. The coal feed rate was estimated to be - 3 g h -1 and the residence time - 1 s. The char particles left the reactor through a water-cooled probe and were collected in a cyclone.

Image analysis The chars were embedded in epoxy resin and polished

surfaces were prepared for examination under a microscope (50 × oil immersion objective) attached to a standard CCD camera, the latter being connected to an image analysis system (VIDAS, Rel 2.1, developed by Kontron Elektronik GmbH) for the display, processing and analysis of images from cross-sections of selected char particles.

A conventional point-counting procedure was used to obtain representative sets of particles from the char samples. 250, 363 and 352 particle cross-sections were selected from Taft Merthyr, E1 Cerrejon and Van Dykes Drift chars respectively. At each location, if the reference point impinged on the carbonaceous material of a char particle, the entire image was digitized and stored for further measurements. This procedure ensured that the sets of particles obtained were a representation of the total volume of char material, as opposed to the alternative procedure of selecting a particle when the crosswire landed on either a pore or the carbonaceous matter, in which case the collective obtained would be a representation of the total volume of char particles. The main advantage of the criterion chosen here is that the sets of particles thus obtained are a close representation of a mass of char. In fact, if all the char material in the sample had the same true density (a reasonable assumption), exact mass percentages would be obtained.

Once the particle selection was finished, binary images of the isolated cross-sections were obtained using a sequence of standard image processing operations. In these images,

the char material is represented in white (phase) pixels and the pores and resin in black (background) pixels.

Parameter calculation Porosity. The fractional porosity of a particle was

calculated as the complement of the quotient of the area of the char material and the area of the image repre senting char material plus porosity, obtained by 'filling' the pores.

Wall thickness. Image analysis offers a number of possibilities for the measurement of wall breadths 14. Thus the lengths of the intercepts between the objects studied and a grid of parallel lines are often used as an estimate of the wall breadth distribution. Several approximations which make use of correlations between wall breadths and particle area, perimeter, porosity and/or diameter have also been proposed. However, none of these gave a satisfactory result for the highly heterogeneous and asymmetric samples considered in this study. A sequence of standard image analysis operations, which makes extensive use of the ero- sion and dilation operations, was therefore specially designed as an alternative route to obtain the real wall dimensions, within the experimental error intrinsic to any measurement on microscope images. This method is sum- marized in Figure 1:

(1) The images shown in the top row are obtained through successive erosion of the original image until total con- sumption of the char material.

(2) These are then partly restored (bottom row) by submit- ting them to as many dilations as the number of erosions needed to generate them.

(3) The thickness of the walls suppressed after each cycle (erosion + dilation) is equal to twice the depth of ero- sion. The darker the grey level of phase pixels in the discriminated image (right), the thicker the wall they belong to.

Radial mass distribution (RMD). The method devised here for the mathematical description of the distribution of carbonaceous matter across the char particles was also designed ad hoc in this study, and makes use of standard image analysis operations, thus allowing its implementation in any image analysis software package. The aim of the method was to give an unbiased estimation of the propensity of a coal to form cenospheres during pyrolysis. Also it was intended to discriminate these structural types from the rest of the highly porous structures (networks) commonly found in chars. In this procedure, a Euclidean distance transform is performed on the binary image from the filled cross- section of each particle studied, and then the grey-scale image obtained is multiplied pixel-wise by the binary image containing the original particle cross-section. This sequence of operations is illustrated in Figure 2. In the image thus obtained, every phase pixel is displayed in a

Table 1 Petrographic and chemical composition of coals

go (%)

Vitrinite Liptinite Inertinite Ash VM

(vol.%) (wt% db) (wt% daf)

C H N Song Odiff

(wt% daf)

El Cerrejon 0.63 78.3 3.9 17.8 6.8 39.4 80.4 Van Dykes Drift 0.73 27.4 5.0 67.6 14.1 29.1 77.0 Taft Merthyr 1.82 76.7 0.0 23.3 5.2 13.6 90.8

5.4 1.6 0.5 12.1 3.9 1.7 0.3 17.1 4.1 1.3 0.7 3.1

1242 Fuel 1997 Volume 76 Number 13

Morphological description of char structures: D. Alvarez et al.

ORIGINAL IMAGE

Figure 1

2nderosion ~k ~,~ 3rderosion ~i ~ , ) • )

lb.

One Two Three dilation dilations dilations

DISCRIMINATED IMAGE

.. II

SUCCESSIVE SUMMATIONS + NORMALIZATION

Operational sequence used for the measurement of wall thicknesses

ORIGINAL IMAGE FILLED IMAGE EUCLIDEAN DIST. MAP DISCRIMINATED IMAGE

Figure 2 Successive transformations needed to obtain the RMD of a char particle. The grey level of the phase pixels in the discriminated image is proportional to their distance to the edge of the particle (right)

grey level equal to its shortest distance to the edge of the particle cross-section, and the grey-level histogram of this image contains, already supported by numerical data, all the information required to describe the radial distribution of the char material in the particle. A very flexible parametric equation was found which is able to reduce the raw data obtained from every particle cross-section to just two numbers. This equation is: V c = [ 1 - (1-Ra)a']¢where Vc is the fractional cumulative volume of carbonaceous matter from the edge of a particle to a given radial distance, Ra is the dimensionless radius corresponding to that parti- cular distance, and ~b and ~a are the fitting parameters which contain all the information regarding the radial mass distri- bution of every char particle. It has to be stressed that this equation lacks any physical meaning and its use is only aimed at the compression and ease of handling of the RMD data. Figure 3 shows binary images from three dif- ferent char structures, together with their RMD profiles and best-fit curves. The sharp differences existing between the

RMD profiles of the cenosphere and the two other char types shown can be used to distinguish that particular struc- tural type. On the other hand, network and solid chars show very similar RMD profiles, as might be expected, bearing in mind that this method considered only the way in which the carbonaceous matter was distributed radially in the cross-sections, and thus all the particles in which pores do not manifest any preference for specific radial positions will have similar RMD profiles, regardless of their porosity values. However, the distinction between network and solid chars is a straightforward task if a certain porosity value is selected as a threshold to separate these two struc- tural types.

THE CLASSIFICATION SCHEME

At this stage, it is possible to quantify accurately the most relevant structural data--porosity, wall thickness and R M D - - o f char particles and place them in specific

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Morphological description of char structures: D. Alvarez et al.

positions in the continuum of possible structures adopted by char particles. All that remains is to divide that continuum reasonably into classes, by means of the appropriate threshold values for each parameter. The thresholds selected here represent an attempt to approach as nearly as possible to the decisions that a human operator would make to discriminate the main structural types considered in currently used methods. The discrimination between cenospheres and networks is made on the basis of the RMD data: if > 10% of the char material is confined in an inner core of half the particle radius, the structure is classified as network, otherwise it is considered as a cenosphere. This is schematically shown in Figure 4. The examples shown feature the most common characteristics which particles within each group should share and also represent the main structural types considered in most char classification schemes 4-8'12. Nevertheless, it has to be borne in mind that char particles are formed under extreme conditions and from a very heterogeneous material. Hence it is to be expected not that their structures could follow a limited set of patterns, but rather that they will display a continuum of possible structures. However, this does not nullify the convenience of reducing the whole variety of char morphologies to a number of discrete situations.

RESULTS AND DISCUSSION

It is generally accepted that, except for operational and particle size conditions (which were the same throughout this work), coal rank and maceral composition are the two main factors affecting char morphology. Therefore, three coals showing very different petrographic characteristics were selected to test the ability of the above procedures to characterize and clearly distinguish the pyrolysis chars. E1 Cerrejon was taken as a 'baseline' coal having a low inertinite content (17.8 vol.%) and a relatively low rank (Ro = 0.63%). Taft Merthyr has a similar inertinite content (23.3 vol.%) to El Cerrejon but a much higher rank (Ro = 1.82%). Finally, Van Dykes Drift is very similar in rank (Ro = 0.73%) to E1 Cerrejon but its inertinite content is as high as 67.6 vol.% (see Table 1). Given the large variation in maceral composition between these three coals, vitrinite reflectance was regarded in this study as the most reliable rank parameter, as any other bulk chemical parameter would be affected by the differences in chemical composition of the various macerals. For instance, the difference in volatile matter between Van Dykes Drift (29.1 wt%) and E1 Cerrejon (39.4 wt%) could be attributed to the greater maturity of the former, but their vitrinite reflectances reveal that Van Dykes Drift is only slightly more mature than E1 Cerrejon, the observed difference in volatile matter being

100

8O

- / • 40 >

m 20

E

0 0,00

S = 8.40

9=1.15 i I ~ I

0.20 0.40 0.80 0.80

Dimensionless Radius

l

1.00

tO0

80

0

~ 6o

_~ 2 0

E 0 (..) 0.00

~i¢, (p = 0.68 I I I I I

0 . 2 0 0 . 4 0 0 . 6 0 0 . 8 0 1 . 0 0

Dimensionless Radius

Figure 3

100 A

~8o E "~ 60 ) .~ 40,

20. E 0.00

, , , 0.98 ,

0.20 0.40 0.60 0.80 1.00 Dimensionless Radius

Three typical char structures and their corresponding RMD and best-fit curves

1244 Fuel 1997 Volume 76 Number 13

Morphological description of char structures: D. Alvarez et al.

I < 3 3 %

I > 500 ~tm 2

POROSITY I I

> 3 3 %

WALLS > 10 p.m

I >50%

I >10%

I WALLS>5 Pml

I I >50% <50%

I

MIXED

CROSS SECTION ]

I <50%

RMD I I

< 1 0 %

IWALLS>5 aml

I >50%

I < 500 p_m 2

I <50%

! FRAGMENT

Figure 4

t SOLID

THICK WALLED

NETWORK

THIN WALLED

NETWORK

<2 THICK

WALLED CENOSPHERE

THIN WALLED

CENOSPHERE

Classification scheme based on measurements of cross-sectional area, porosity, wall thickness and RMD

actually due to the lower volatile yield of inertinites compared with vitrinites.

Coal plasticity is a most relevant characteristic for the understanding of behaviour in a p.f. boiler, and multiple tests (Audibert-Arnu, Gieseler, etc.) exist for quantifying related properties such as swelling or fluidity. However, the temperatures and heating rates used in these tests have been chosen to closely resemble those in a coke oven and are thus very different from the conditions prevailing during p.f. combustion. Furthermore, none of them is sensitive enough to detect the relatively small differences existing between the plastic properties of the non-coking coals. Of the coals used in this study, Taft Merthyr and Van Dykes Drift are too high in rank and inertinite content respectively to allow any useful data to be obtained from these tests. It was therefore decided to look for the indirect information regarding coal plasticity provided by the morphology of char particles, especially their tendency to generate cenospheres and thin- walled structures.

The porosity distributions of char particles from the samples studied are shown in Figure 5. E1 Cerrejon produced the most porous char, with a mean porosity of 64%, while Van Dykes Drift and Taft Merthyr yielded much denser chars with mean porosities of 40 and 44% respectively. On the other hand, the porosity distribution of E1 Cerrejon char shows a sharp peak at -75%, suggesting that this is a rather homogeneous material. The distribution spreads over the entire range for Van Dykes Drift but also shows a maximum at a porosity of -45%. However, the porosity distribution in Taft Merthyr char is quite irregular, with a high percentage ( -15%) of non-porous structures and the rest of the particles displaying a widespread distribution of porosities peaking at -60%. The distribu- tions of wall thicknesses, shown in Figure 6, also differ widely in the chars studied. Thus El Cerrejon char seems again to be the most homogeneous material, displaying a very narrow distribution, with thicknesses almost exclu- sively < 5 #m. Van Dykes Drift also tends to form

Fuel 1997 Volume 76 Number 13 1245

Morphological description of char structures: D. Alvarez et al.

30

25

20

15

10

5

0

0 0 0 0 0 0 0 0 0 0

3° t 25

20

15

10

VAN DYKES DRIFT

0 0 0 0 0 0 0 0 0 0

Figure 5

30

25

20

15

10

5

0

o d d d d d o o d d

Porosity distributions in the chars studied

30 ~D

25

2o

s

0

Figure 6

,zr ,~ - - ¢=-.. CERREJON

,," "4 ~ VAN DYKES DRIFT

• & ~ / ~ t ~ . _ . - - o - . . TAFF MERTHYR

. . . .

0 2 4 6 8

Wall breadth (microns)

Distribution of wall thicknesses in the chars studied

thin-walled char, although in this char the distribution is highly skewed towards thicker walls compared with those of El Cerrejon. Finally, Taft Merthyr generates mainly thick-walled chars, with most of the material forming walls > 5/~m.

To gain further insight into the structural changes undergone by coal particles during the pyrolysis stage, a more detailed description of the individual particles that compose each sample has to be considered. Table 2 lists

the percentages of the different structural types found in the char samples using the above procedures. These results are in good agreement with the predictions based on the characteristics of the parent coals. Thus E1 Cerrejon yields the most porous char, with only 2.5 vol.% solid structures. Van Dykes Drift, with a similar rank to E1 Cerrejon but a much higher inertinite content, generates the highest proportion of solid structures (32.7 vol.%) during pyrolysis. Finally, the proportion of dense structures found in Taft Merthyr char (22.8 vol.%) is much higher than that in E1 Cerrejon, but still lower than that in Van Dykes Drift char.

The formation of cenospheric char during pyrolysis was also found to depend on both coal rank and maceral composition. Thus the tendency to form cenospheres dramatically decreases from E1 Cerrejon (39.2 vol.%) to Van Dykes Drift (12.5 vol.%). On the other hand, the influence of coal rank on the formation of cenospheric char, though remarkable, is not as pronounced as that of inertinite. Thus Taft Merthyr, with a much higher rank than E1 Cerrejon or Van Dykes Drift, still generates 24.1 vol.% of cenospheres, twice as much as E1 Cerrejon. However, 75 vol.% of the cenospheres generated by Taft Merthyr is classified as thick-walled, whereas those from El Cerrejon are almost exclusively thin-walled. Finally, the cenospheres formed from Van Dykes Drift are also mainly thin-walled (68 vol.%).

The population of network chars was observed to vary very little among the samples studied, being only slightly lower for Taft Merthyr char. Again, the main differences are found in the relative proportions of thin- and thick-walled structures, with 96 vol.% of the networks from E1 Cerrejon being classified as thin-walled, compared with 74 vol.% from Van Dykes Drift and only 19vo1.% from Taft Merthyr.

Significant amounts of mixed structures were found only in Taft Merthyr char (5.4 vol.%). This is a positive feature as far as the characterization of char structures is concerned, since most of the structures found in the samples studied have been given a very specific description, as opposed to the rather vague definition of mixed structures.

Finally, very similar percentages of particle cross- sections < 500 #m 2 were found in the three chars studied. This suggests that they might be the statistical result of the random sectioning of particles; hence it is not likely that the sets of particle cross-sections found in these samples had been biased by imposing this size threshold.

A comparison of the data obtained for E1 Cerrejon and Taft Merthyr chars illustrates the changes that take place in the structure of chars with increasing coal rank, and is in good agreement with previously reported resultsS'lS:

(1) The population of cenospheric char decreases with increasing rank, though this effect is not especially pronounced. Thus, the ratio of cenospheres to cenospheres plus networks is 0.45 for El Cerrejon and 0.38 for Taft Merthyr. This difference is not too large, bearing in mind that E1 Cerrejon is a high- volatile bituminous coal while Taft Merthyr is a semi- anthracite.

(2) Much thicker walls were encountered in the char from Taft Merthyr than from El Cerrejon. As mentioned above, both cenospheres and networks were mainly thick-walled in Taft Merthyr, whereas < 2% of the char particles from E1 Cerrejon were classified as thick-walled.

1246 Fuel 1997 Volume 76 Number 13

Morphological description of char structures: D. Alvarez et al.

Table 2 Morphology of pyrolysis chars (vol.%)

El Cerrejon Van Dykes Drift Taft Merthyr

Cenosphere Thin-walled 38.6 8.5 6.1 Thick-walled 0.6 4.0 18.0 Total 39.2 12.5 24.1

Network Thin-walled 46.5 34.9 7.4 Thick-walled 1.9 12.2 31.9 Total 48.4 47.1 39.3

Solid 2.5 32.7 22.8 Mixed 0.0 0.3 4.5 Fragment 9.9 7.4 9.3 Total thin-walled 85.1 43.4 13.5

Total thick-walled 2.5 16.2 49.9

(3) The increase in the proportion of solid structures from E1 Cerrejon to Taft Merthyr could be due to variations in the size of the inertinite domains in these coals. E1 Cerrejon coal has a high proportion of detrital macerals and its inertinite must be more loosely dispersed in the vitrinite matrix than it is in Taft Merthyr. Also, the existence of very thick-walled structures, derived from vitrinite macerals but having very low porosities, might be responsible of the high proportion of solid structures found in Taft Merthyr.

(4) In any case, the most striking changes in char morphol- ogy attributable to the increase in coal rank have been found in the thickness of char walls, rather than in var- iations in the percentages of the structural types consid- ered in this study.

Similarly, when comparing the morphologies of E1 Cerrejon and Van Dykes Drift chars, the following effects

16 18 attributable to coal inertinite content were observed - :

(1) In general, inertinites underwent much less porosity development than vitrinites, and this is reflected in the high percentage of solid structures found in Van Dykes Drift compared with El Cerrejon char. This increase occurred mainly at the expense of cenospheres.

(2) The ratio of thin- to thick-walled chars was lower in Van Dykes Drift, probably due to the generation of some highly fused structures (cenospheres and net- works) from the least-altered inertinites. The fact that both chars have the same proportions of networks, and that these are still mostly thin-walled in Van Dykes Drift, suggests that those inertinites which passed through a somewhat plastic stage could have generated mainly thin-walled networks. However, the inertinites which had not undergone any porosity development, but still had some inherent porosity, could have been regarded as networks by this method.

(3) The strongest change in char morphology attributable to the increase in inertinite content is the drastic reduction observed in the percentage of cenospheres.

Summarizing, the influence of coal rank on the plastic properties shown by the carbonaceous material during pyrolysis manifests itself as the effect of a gradual variation within the total volume of the vitrinites, and this is why the strongest variations in char morphology from a low- to a high-rank coal consisted precisely in an increase in wall

thickness, which indicates a higher viscosity of the whole mass of carbonaceous matter during pyrolysis. Conversely, the variations with the increase in inertinite content are mainly reflected in how the carbonaceous matter is arranged in the particle cross-sections, i.e. the observed reduction in the percentage of cenospheres. This is in agreement with the fact that differences in the maceral composition of coals represent only variations in the relative proportions of basically two components: the vitrinite macerals, which achieve (at certain ranks) good plastic properties during pyrolysis, and the inertinite macerals, which have generally poor to very poor plasticities. As a result, the structure of char particles mainly depends on the individual maceral compositions of the parent coal particles 17A9.

These observations relate to the experimental conditions under which the pyrolysis tests were carried out, different trends being possible at higher temperatures t9, but these could in any case be quantifiable using the methods proposed in this study.

ACKNOWLEDGEMENTS

This work was funded by the EU through the Joule Programme (Project JOUF-0050-C). Diego Alvarez and Angeles G. Borrego thank the Spanish Ministry for Education and the EU TMR Programme, respectively, for postdoctoral fellowships. Special thanks go to Dr Jim Williamson for his advice on the development of this paper and careful editing of the manuscript.

REFERENCES

1 Mulcahy, M. F. R. and Smith, I. W., Reviews of Pure and Applied Chemistry, 1969, 19, 81.

2 Smith, I. W., in Nineteenth Symposium (International) on Combustion. The Combustion Institute, Pittsburgh, 1982, pp. 1045-1065.

3 Walker, P. L. Jr, Fuel, 1981, 60, 801. 4 Lightman, P. and Street, P. J., Fuel, 1968, 47, 7. 5 Jones, R. B., McCourt, C. B,, Morley, C. and King, K., Fuel,

1985, 64, 1460. 6 Shibaoka, M., Fuel, 1985, 64, 263. 7 Diessel, C. F. K. and Wolff-Fischer, E. M., Proposal for a

classification of combustion residues. Communication to the International Committee for Coal and Organic Petrology (ICCP) Meeting, Beijing, 1987.

Fuel 1997 Volume 76 Number 13 1247

Morphological description of char structures: D. Alvarez et al.

8 Bailey, J. G., Tate, A., Diessel, C. F. K. and Wall, T. F., Fuel, 1990, 69, 225.

9 Zygourakis, K. and Sandman, V. W. Jr, AIChE Journal, 1988, 34, 2030.

10 Zygourakis, K., Energy and Fuels, 1993, 7, 33. 11 Lester, E., Cloke, M., Gibb, W. H. and Miles, N. J., in

Proceedings of the International Conference on Coal Science, Banff, Vol. II. 1993, p. 117.

12 Alvarez, D., Men~ndez, R., Fuente, E. and Vleeskens, J. M., in Proceedings of the International Conference on Coal Science, Banff, Vol. I. 1993, p. 77.

13 Lester, E., Cloke, M. and Allen, M., Energy and Fuels, 1996, 10, 696.

14 Russ, J. C. The Image Processing Handbook, 2nd edn. CRC Press, Boca Raton, FL, 1995, pp. 463-469.

15 Bend, S. L., Edwards, I. A. S. and Marsh, H., Fuel, 1992, 71, 493.

16 Thomas, C. G., Gosnell, M. E., Gawronski, E., Phong-anant, D. and Shibaoka, M., Organic Geochemistry, 1993, 20, 779.

17 Thomas, C. G., Shibaoka, M., Gawronski, E., Gosnell, M. E. and Phong-anant, D. D., Fuel, 1993, 72, 913.

18 Borrego, A. G., Alvarez, D. and Menendez, R., Energy and Fuels (in press).

19 Rosenberg, P., Petersen, H. I. and Thomsen, E., Fuel, 1996, 75, 1071.

1248 Fuel 1997 Vo lume 76 Number 13