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Optimization of coal water slurry properties through fine coal particle addition

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Green Processing and Synthesis
From the journal Green Processing and Synthesis Volume 15 Issue 1

Abstract

For lowering energy consumption of low-concentration coal water slurry (CWS), this study investigates enhancing CWS performance through incorporation of micronized particles of coal as into the gasification raw material. Experimental results reveal that ultrafine particles of coal possess good physicochemical properties including low inherent moisture content, large specific surface area, and higher zeta potential. With the incorporation of 15 % fine coal particles, the concentration of CWS increased by 3 percentage points to 63.5 %, while the fractal dimension rose from 2.231 to 2.412, indicating improved packing efficiency of coal particles. Additionally, spread area per unit mass was increased by 21.2 %, and water separation rate was reduced by more than 50.3 %, depicting enhanced slurry stability. Further investigation indicated that fine particles lowered interparticle distance and increased ζ by 40.8 %, enhancing spatial resistance and electrostatic repulsion. The dynamic study indicated that incorporation of fine particles lowered activation energy by 1.42 %, the mean reaction rate (K mean) is increased by 188 %, and resulted in a forward shift in temperature of reaction. These observations reveal that incorporation of fine particles can be a means to enhance rheological and gasification properties of CWS and therefore improve energy efficiency in fuel applications on the basis of coal.

Keywords: coal water slurry; fine coal particles; gasification reaction; fractal dimension; packing efficiency

1 Introduction

The principal energy source in Chinese energy composition, efficient utilization of coal is of strategic importance to national energy security and socio-economic progress [1], 2]. Coal water slurry (CWS) gasification as a major part of clean coal technology is of vital importance with technical advantages.

CWS production utilizes premium low-sulfur, low-ash coals to effectively mitigate pollutants at the source, reducing particulate matter and SO2 emissions by over 50 % compared to conventional coal combustion [3], with atomized combustion achieving over 99 % efficiency and significant NOx reduction [4], 5]. As a high-efficiency fuel substitute, CWS enables a 2:1 mass replacement of fuel oil in industrial applications, reducing fossil fuel dependency [6], 7]. Its gasification-derived syngas (CO + H2) integrates seamlessly with advanced systems like IGCC, elevating energy efficiency to 45–50 % – a 10–15 % improvement over traditional coal systems – while supporting global clean energy goals [8], [9], [10]. Gasification fine slag (≤30 % moisture) containing 20 %–50 % residual carbon serves as supplementary fuel for slurry plants [11], [12], [13]. Blending sewage sludge with coal enhances slurry fuel production, where sonication improves homogeneity, and increasing sludge ratios (10–30 %) reduce viscosity via thixotropy and hydrogen-bond-mediated particle dispersion [14], 15]. Thermogravimetric analysis reveals sludge-modified samples exhibit lower combustion temperatures, while BDO tar addition reduces activation energy through Na+ catalytic effects in residues [16], 17]. Coking wastewater elevates CWS concentration to 62.16 % (vs. 61.36 % conventional), enhancing combustion efficiency through phenolic compounds’ competitive adsorption, though Ca2+, NH4 +, and Na+ ions compromise slurry stability via surface charge interactions [18], [19], [20].

In CWS waste co-processing, careful control of parameters like calorific value, ash fusion temperature, and sulfur content is crucial for gasifier stability [21], [22], [23]. Limiting chlorine prevents corrosion, and heavy metals necessitate flue gas cleaning, enabling over 20 waste streams to achieve waste reduction and fuel conservation [24], 25]. Challenges include high-sulfur/ash coals causing slagging and blockages [26], slurry concentrations <62 % reducing efficiency, and >35 % water content inducing 5–8 % combustion heat loss [27], [28], [29]. While coal blending improves flexibility, it risks temperature instability [30], 31]. Composite additives boost slurry concentration by 1–3 % via enhanced particle dispersion [32], 33], and optimized coal particle sizing increases concentration without quality compromise.

Current research on particle size gradation in CWS focuses on optimizing distribution to enhance slurry concentration, stability, and rheological performance. Studies demonstrate that tailored particle size distributions, such as bimodal or continuous gradation, improve slurry properties: coarse particles increase concentration, while fine particles enhance flowability and stability by filling pore structures and releasing bound water [34], [35], [36]. Advanced computational models, including BP neural networks, accurately predict relationships between bimodal parameters and slurry concentration, enabling a 4 % increase in low-rank coal slurry concentration [35]. The integration of physics-based approaches, such as the compartment packing model, with optimization algorithms like particle swarm optimization, further refines particle gradation design. This hybrid framework maximizes packing efficiency, reduces viscosity, and generates ideal unimodal, bimodal, or trimodal distributions to enhance structural compactness [37], 38]. Additionally, rheological analyses highlight pseudoplastic behavior influenced by temperature and ash content, with Herschel-Bulkley models validated by ANN for precise predictions [39], 40]. Collectively, these advancements underscore the shift from empirical methods to data-driven, systematic gradation strategies, emphasizing packing efficiency and computational modeling to achieve energy-efficient, high-performance CWS formulations.

This study aims to elucidate how fine coal particles regulate critical performance characteristics of CWS, specifically addressing concentration limitations, rheological properties, and gasification reactivity. Through spread-area fluidity measurements and particle size distribution analysis, we systematically investigated the dual role of fine particles in stabilizing slurry microstructure via electrostatic repulsion mechanisms while simultaneously enhancing gasification performance. The findings establish fundamental principles for designing optimized particle gradation strategies to improve both the processing efficiency and thermochemical conversion potential of CWS systems.

2 Methods

2.1 Coal sample

The Shendong mining field (LGH coal) was employed to pick a test coal sample. Proximate analysis of the test coal was conducted in accordance with “Proximate analysis of coal – Instrumental method” (GB/T 30732-2014). The test results of this quality of coal are outlined in Table 1.

Table 1:

Proximate analysis results of coal sample.

Sample Proximate analysis wt/% Ultimate analysis wt/% Q b,ad/MJ kg−1
M ad A ad V ad FCad C ad H ad O ad N ad S t,ad
LGH 9.61 6.76 29.97 53.66 66.74 3.44 12.39 0.61 0.45 26.62

The lump coal was fed into a hammer mill for rapid grinding to produce coal powder with 100 % particle size <2 mm. This size-fractionated sample was designated as the coarse fraction. The remaining material was then ground in a planetary ball mill for 1, 3, 5, and 20 min, respectively, to obtain coal samples with different particle size distributions. Particle size distribution of pulverized coal collected during different stages of grinding was analyzed using a laser particle size analyzer (BT-2003, Laser Particle Size Analyzer, Dandong Baite Instrument Co., Ltd). Analytical results are illustrated in Figure 1.

Figure 1: Particle size distribution of coal samples at different grinding times.
Figure 1:

Particle size distribution of coal samples at different grinding times.

1 g of coal was put in a special sample tube and was subjected to vacuum degassing pretreatment to desorb adsorbed impurities. High-grade nitrogen gas was introduced to make it possible to do multilayer adsorption experiments and to precisely determine the surface characteristics of the sample. Specific surface area (SSA) was calculated using the Brunauer-Emmett-Teller (BET) equation based on measurement of nitrogen adsorption isotherms. Analysis was done using NOVA 1000e Specific Surface Area and Pore Size Analyzer (Quantachrome, USA) to precisely measure the surface characteristics of the coal.

1 g of coal was ultrasonically dispersed in deionized water with a mass of 50 g to create a homogeneous suspension to ensure uniform particle distribution. An aliquot of 0.5 mL was transferred precisely into an electrophoresis cell for measurement. Zeta potential (ζ) of coal particles was calculated by calculating their electrophoretic mobility under a direct current (DC) electric field to reveal information on electrostatic stability of the system of coal and water. Measurement was done using the JS94H Microelectrophoresis Instrument (Shanghai Zhongchen Digital Technology Equipment Co., Ltd).

The experimental data (Figures 1 and 2) reveal that there is a reverse proportionality between grinding time and coal particle median diameter (D 50). Extension of milling time to 10 min makes it possible to obtain ultrafine coal powder with D 50 ≈ 10 μm. Parallel measurements reveal that there is a progressive reduction in air-dried moisture content (Mad) with increased duration of grinding as a consequence of breakdown of pore structure and release of adsorbed water under stress.

Figure 2: Mad, SSA, and ζ with different coal particle sizes.
Figure 2:

Mad, SSA, and ζ with different coal particle sizes.

In particular, SSA grows exponentially with growing particle refinement to exhibit a significant increase in reactive surface availability. Refinement is also accompanied by a 29 % increase in absolute ζ to represent enhanced electrostatic charge resulting in improved dispersion and slurry stability. These results confirm the key role played by mechanical grinding to modify electrochemical properties of coal surfaces.

2.2 Performance evaluation of CWS

Rheological measurements were performed utilizing a rotational viscometer (NXS-4C, CWS viscosity meter, Chengdu Instrument Factory) under precise temperature control (25 ± 0.1 °C). The shear stress-viscosity relationship of CWS was characterized through controlled shear rate sweeps ranging from 10 s−1 to 100 s−1. The viscosity value at a shear rate of 100 s−1 was designated as the apparent viscosity.

The characterization of flow behavior involves pouring the CWS from a 250 mL beaker at a constant velocity and observing the resulting flow pattern. The flow patterns are classified as follows: Grade A indicates continuous flow, Grade B denotes intermittent flow, and Grade C represents clustered flow.

The spread area per unit mass of CWS (SACWS) was assessed through an image-based metrology protocol. A precise measurement of 3 g of CWS (±0.1 mg) was obtained using an electronic balance, and the sample was subsequently placed on a glass plate measuring 10 cm × 10 cm. The dynamics of the spreading process were recorded using a CMOS camera (DS-UVC-U168R, HIKVISION) under controlled illumination conditions, specifically utilizing a D65 standard light source.

At t = 30 ± 0.5 s, the percentage of pixels within the diffusion area relative to the total number of pixels in the shooting area (100 cm2) can be determined as follows:

(1) SAR = N spread / N total × 100   cm 2

Where N spread represents the pixels in the exhibition area and N total represent the pixels in the 100 cm2 area.

Sample mass to ascertain the spread area per unit mass can be normalized as follows:

(2) SA CWS = SAR / m cws   cm 2   g − 1

Where m cws represents the quality of transferred CWS.

The schematic representation of the experimental setup is depicted in Figure 3.

Figure 3: Experimental setup for measuring spread area of CWS.
Figure 3:

Experimental setup for measuring spread area of CWS.

The CWS water separation rate (WSR) can be measured by filling a test tube with CWS to a two-thirds height and allowing it to stand for 24 h. The test tube is subsequently closed. WSR is measured as a ratio of the height of the supernatant to total liquid in a test tube [41].

2.3 Gasification reactivity of CWS

Thermogravimetric analysis (TGA) of CWS was performed using a NETZSCH STA 449 F3 simultaneous thermal analyzer under rigorously controlled conditions. Approximately 30.0 ± 0.2 mg of a homogeneous sample was accurately weighed and placed in a corundum crucible. The experiment was conducted in a gas atmosphere comprising nitrogen (N2) at a flow rate of 50 mL min−1 and carbon dioxide (CO2) at a flow rate of 50 mL min−1, with a programmed heating rate of 15 °C min−1, ranging from 30 °C to 1,400 °C.

3 Results and discussion

3.1 Effect of fine particles on concentration of CWS

In CWS, there are interstitial voids with inherent irregular-shaped packing of particles. Fine particles of coal (∼10 μm size) were introduced to the raw coal with mass fractions of 5 %, 10 %, 15 %, and 20 % based on particle grading optimization principles to improve filling efficiency between coarse particles. This was to improve packing by providing controlled particle-to-particle contact between coarse and fine particles. Rheological properties and apparent viscosities of CWS are outlined in Table 2.

Table 2:

Performance of CWS with different fine coal particle proportions.

Proportion of fine particles/% Concentration/% Fluidity Apparent viscosity/mPa· s
0 60.5 B 552.3
0 61.0 C 603.2
5 61.0 A 658.0
5 61.5 B 701.8
5 62.0 B 912.8
10 62.0 A 860.0
10 62.5 B 922.5
10 63.0 B 985.7
15 63.0 A 939.8
15 63.5 B 993.0
15 64.0 B 1,265.8
20 63.0 B 990.0
20 63.5 B 1,249.2

Apparent viscosity and flowability are important performance criteria for CWS in industrial applications as they affect directly processability, transportation efficiency, storage stability, and combustion or gasification efficiency. Industrial practice typically demands that CWS with apparent viscosity greater than 1,200 mPa s or with flowability rating of Class C will be considered unsuitable for industrial operations.

In Table 2, the key constraint to having CWS with high concentration has a dramatic transition from poor flowability to excessive apparent viscosity with increased proportion of fine particles. Solid concentration has a clear parabolic trend to a maximum of 63.5 wt% for a content of fine particles of 15 wt%. Beyond this optimal limit, while the slurry still maintains acceptable flow properties, apparent viscosity increases to levels greater than 1,200 mPa s. This results in a reverse proportionality between fine particle loading of coal and resulting concentration.

In Figure 1, the Mad decrease the content of adsorbed water in CWS on addition. This increases free water content in CWS and increases its flow. Apart from this, these fine particles occupy interparticle pores between large particles, and this increases packing efficiency (PE) of the coal and increases concentration of CWS. Cumulative distribution curves for CWS having concentration of 60.5 % and 63.5 % are presented in Figure 4.

Figure 4: Cumulative particle size distribution curves of CWS samples.
Figure 4:

Cumulative particle size distribution curves of CWS samples.

The fractal dimension (Eq. (3)) is employed to characterize the spatial distribution and structural complexity of coal particles within the slurry [42]. A lower fractal dimension suggests greater particle agglomeration, typically resulting in increased viscosity and reduced flowability. Conversely, a higher fractal dimension indicates a more homogeneous particle dispersion, contributing to improved slurry stability and combustion efficiency. Furthermore, when considering surface fractal dimension, it quantifies the irregularity of coal particle surfaces, which directly impacts additive adsorption behavior and the overall rheological properties of the slurry [43].

(3) y r = N 0 K r V 0 2 − D r 3 − D

(4) 3   ln y r = b   ln   r + C

(5) D = 3 − b

r: particle size;y (r): number of coal powder particles with size less than r;N 0: total number of particles in the coal powder system;K r: shape factor of coal powder particles;V 0: total volume of the coal powder particle system;D: fractal dimension.

Assuming the right-hand side of Eq. (3) (N 0 K r/[V 0 (2 − D)]) is a constant term, let b = 3 − D. Taking the logarithm of both sides in Eq. (3) yields Eq. (4), where C is a constant. If ln y(r) − ln r exhibits a linear relationship in double logarithmic coordinates, it indicates that the particle size distribution possesses fractal characteristics. Based on the linear slope b, the fractal dimension of the coal powder system can be calculated through Eq. (5).

Based on the particle size distribution of coal-water slurry in Figure 4, nine characteristic distribution parameters were selected for data fitting (D 6, D 10, D 16, D 25, D 50, D 75, D 84, D 90, D 97). Taking D 50 as an example, r represents the maximum particle size when the cumulative distribution reaches 50 %, and y(r) corresponds to 50 % (0.5). After calculating and taking the logarithm of different characteristic parameters, a linear fitting was performed to obtain Figure 5.

Figure 5: Vairation in fractal dimension of CWS.
Figure 5:

Vairation in fractal dimension of CWS.

As the CWS concentration increased from 60.5 % to 63.5 %, the fractal dimension rose from 2.231 to 2.412, corresponding to an approximate increase of 8.1 %. This increase indicates that the incorporation of fine coal particles, along with the higher slurry concentration, enhanced particle packing density, reduced interparticle spacing, and facilitated the formation of a more compact network structure. The elevated fractal dimension thus reflects a significant improvement in the packing efficiency of coal particles.

The apparent viscosity of CWS mixed with 20 % fine particles increases with increasing concentration through two synergistic mechanisms. Firstly, decreased volume of freely mobile water reduces interparticle distance and increases viscous resistance through increased packing of particles; Secondly, the naturally large SSA of fine particles outgrows the wetting capability of available CWS additives at constant dosage levels and leads to incomplete dispersion. Both effects (i.e., geometric limitations resulting from reduced volume of water and surface chemistry limitations) contribute to increased apparent viscosity in high concentration CWS with fine particles.

3.2 Effect of fine coal particles on flowability of CWS

In CWS, particles and water and dispersants constitute a metastable network-like structure. Free water molecules that are not adsorbed on particle surfaces or engaged in forming compact hydration layers are present in interstitial pores of this three-dimensional structure. This structure is rheologically shear-sensitive; on application of shear stress, progressive disruption of this microstructure results in liberation of entrapped free water and concomitant lowering of viscosity. Shear-thinning behavior and reverse shear rate/shear stress classification position CWS in the category of shear-thinning pseudoplastic fluids.

The rheology characterization in this work employed a power-law model (Eq. (6)) to account for CWS flow behavior. Shear stress (τ) and shear rate (γ) relations for various CWS formulations are illustrated in Figure 3 and thus show the characteristic pseudoplastic behavior of these materials.

(6) τ = τ 0 + K γ n

Where τ represents the shear stress (Pa); τ 0 represents yield stress (Pa); K represents the consistency coefficient (Pa s); γ represents the shear rate (s−1); and n represents the flow behavior index (dimensionless). The pseudoplastic (shear-thinning) behavior intensifies with decreasing n values.

Figure 6 depicts a linear relationship between γ and τ for the CWS, with correlation coefficients (R 2) exceeding 0.99, thereby indicating a strong degree of linearity. The parameters obtained from the linear fitting are summarized in Table 3.

Figure 6: Relationship between γ and τ of CWS.
Figure 6:

Relationship between γ and τ of CWS.

Table 3:

Fitted power-law rheological parameters of CWS.

Proportion of fine particles/% Concentration/% K n R 2
0 60.5 0.52 0.99 0.99
5 62.0 1.15 0.93 0.99
10 63.0 1.39 0.89 0.99
15 63.5 2.81 0.78 0.99
20 63.0 2.60 0.79 0.99

The consistency coefficient (K) increases with increasing proportion of fine particles to a maximum with a 15 % addition and then decreases. Flow behavior index (n) has a reverse trend. This is a clear indication that addition of fine particles of coal not only increases concentration and apparent viscosity of slurry but more importantly improves its pseudoplastic character. This improvement is accountable for storage stability and pumpability of CWS.

In measurement of CWS flow development, SACWS was used as a standardized flow measurement in mm2 g−1. Figure 7 illustrates a comparison of SSA for various CWS in test conditions for controlled spreading.

Figure 7: Comparison of SACWS across different CWS.
Figure 7:

Comparison of SACWS across different CWS.

Based on the data in Table 2 and the standardized measurements of spread area, the CWS demonstrates a three-tier classification system for flowability: Grade A (≥1,102 mm2 g−1), Grade B (802–987 mm2 g−1), and Grade C (≤661 mm2 g−1). This quantitative assessment method objectively correlates spread area with fundamental rheological parameters, thereby minimizing the potential for subjective judgment errors.

In the absence of fine coal particles, the maximum concentration of the prepared CWS was recorded at 60.5 %, accompanied by a SACWS of only 802 mm2 g−1 and a flowability grade classified as B. However, upon the incorporation of varying proportions of fine coal particles, the maximum concentration of the slurry continued to exhibit a B-grade flowability while demonstrating a substantial increase in SACWS of at least 17.8 %. Notably, with the addition of 15 % fine coal particles, the slurry attained its peak concentration of 63.5 % and a SACWS of 972 mm2 g−1, reflecting a 21.2 % enhancement compared to the maximum concentration slurry devoid of fine coal particles, along with significantly improved flowability.

3.3 Effect of fine coal particles on spatial structure of CWS

The WSR is a key parameter for gauging CWS stability since it directly affects both quality and combustion efficiency. Based on the results, the addition of fine coal powder with a particle size of approximately 10 μm can dramatically reduce the D50 of slurry. This adjustment not only optimizes particle size distribution of CWS but also reconstructs three-dimensional spatial structure of CWS and thereby improves system stability. Variation patterns of WSRs for CWS made with different proportions of fine particles are depicted in Figure 8.

Figure 8: WSR of CWS.
Figure 8:

WSR of CWS.

In Figure 8, CWS has a “V-shaped” trend in WSR with increasing content of fine particles. The WSR is initially reduced before increasing later on. Significantly, addition of fine particles causes a decline in WSR by more than 50.3 % in CWS and therefore to a significant enhancement of stability. With a content of 15 % of fine particles, CWS (63.5 wt%) has the lowest WSR of 3.57 %. This is accompanied by clear three-dimensional structural changes compared to the unmodified slurry as evident through spatial granularity distribution in Figure 7.

Figure 9(a) illustrates a different stratification of particle sizes for untreated CWS. There is a trimodal distribution with peaks of 0.7 μm, 18 μm, and 147 μm for the top layer and a monomodal distribution with a peak of 179 μm for the middle and bottom layers. This phase separation means that fine particles of coal are concentrated in the upper layer while coarse particles of coal are found in the lower layers. For the modified CWS (Figure 9(b)), there is excellent vertical homogeneity with stable trimodal distributions (0.7 μm, 18 μm, and 145 μm) for all layers, thereby establishing improved structural stability.

Figure 9: Spatial particle size distribution of CWS. (a) CWS without fine coal particle blending. (b) CWS with 15 % fine coal particle blending.
Figure 9:

Spatial particle size distribution of CWS. (a) CWS without fine coal particle blending. (b) CWS with 15 % fine coal particle blending.

The ζ of coal particles that is responsible for controlling slurry stability by governing interactive forces based on DLVO theory has a direct inverse relation with particle size. This size-induced increase in charge is a result of higher surface charge density with decreasing particle size due to increased SSA.

Figure 10 depicts a 40.8 % increase in ζ for CWS with 15 % fine particles relative to CWS without fine particles. CWS without fine particles has a large vertical potential gradient with top layer measurement of −47 mV, middle layer measurement of −37 mV, and bottom layer measurement of −36 mV. This is because of restricted accumulation of fine particles in top layers with interparticle spacing greater than the electric double layer. Therefore, Derjaguin–Landau–Verwey–Overbeek (DLVO) energy barrier is not potent enough to overcome settling by gravity. Incorporation of 15 % fine particles results in: (1) reduction in mean interparticle spacing that enhances steric hindrance and (2) formation of overlapping electric double layers by high-charge-density fines to form three-dimensional electrostatic barriers. Spatial variation in potential is thus reduced to less than 2 % across the slurry column and thereby achieves complete anti-sedimentation stability.

Figure 10: Spatial ζ distribution of CWS.
Figure 10:

Spatial ζ distribution of CWS.

3.4 Effect of fine coal particles on gasification reaction characteristics of CWS

The incorporation of fine particles of coal results in multi-dimensional enhancement of CWS systems including a 3 % increase in solid concentration, a 21.2 % improvement in fluidity, and improved stability as indicated by a reduction in WSR to 3.57 %. TG and derivative thermogravimetry (DTG) of CWS with concentration of 60.5 % (unblended with fine particles of coal) and CWS with concentration of 63.5 % (blended with 15 % fine particles of coal) are presented in Figure 11.

Figure 11: Comparative gasification reactivity of CWS.
Figure 11:

Comparative gasification reactivity of CWS.

In the dehydration stage (Figure 11), there is a higher rate of water loss in the slurry of coal mixed with ultrafine particles. This is due to the action of grinding that ruptures certain pores in the coal and decreases the volume of adsorbed water in such pores [44]. Therefore, there is increased free water content in the slurry and this results in increased dehydration rate. Additionally, particle size reduction and increased SSA enhance liberation of volatiles. Reduced particle size of the coal at the third peak of weight loss results in decreased difference in the Gibbs free energy for chemical reaction and increased tendency for combustion and pyrolysis of particles. This subsequently results in decreased pyrolysis and ignition temperatures.

The kinetic parameters for gasification of coal-water slurry were determined by using integral equation of Coats and Redfern as follows:

(7) ln − ln 1 − α T 2 = ln k 0 R β E − E R T

(8) ln 1 − 1 − α 1 − n T 2 1 − n = ln k 0 R β E − E R T

Where k 0 represents the frequency factor (min−1); E represents the activation energy (kJ mol−1); R represents the universal gas constant (8.314 J (mol K)−1); T represents the reaction temperature (K); n represents the reaction order; α represents the coal conversion rate (%); and β represents the heating rate (K min−1).

Let X = 1 T , Y = ln − ln 1 − α T 2 or Y = ln 1 − 1 − α 1 − n T 2 1 − n , a = − E R , b = ln k 0 R β E . Therefore, Eqs. (7) and (8) can be converted to Eq. (9) as follows:

(9) Y = a X + b

Where Y is calculated through a plot is made against X. By fitting the curve, intercept and slope are further determined to obtain k 0 and E. The kinetic parameters for the coal water slurry gasification reaction are presented in Table 4.

Table 4:

Kinetic parameters of gasification reaction for CWS.

Samples T s/°C T max/°C T e/°C K mean/%·min−1 K max/%·min−1 k 0/min−1 E/kJ ·mol−1
CWS-60.5 % 923.2 1,061.0 1,124.1 0.18 4.12 6.7 × 103 85.91
CWS-63.5 % 922.5 1,048.2 1,118.1 0.52 4.15 7.4 × 103 84.84

The experimental data reveal that CWS with a concentration of 63.5 % and 15 % fine particles has significantly improved gasification efficiency compared to that with a concentration of 60.5 %. In particular, maximum reaction temperature (T max) and end temperature (T e) are reduced by 12.8 °C and 6 °C, respectively, and move the reaction window forward. Additionally, the mean reaction rate (K mean) is increased by 188 %, which indicates that fine particles in CWS enhance gas-solid mass transfer efficiency by increased SSA. Kinetic study also reveals that there is a 10 % increase in frequency factor and a reduction of E by 1.25 % for the higher concentration sample. This is in accordance with the effect of fine coal addition to decrease energy barrier for the reaction and enhance collision frequency. Such properties provide dual benefit of improved low-temperature efficiency and reactivity in industrial gasification. Further improvement of gasification rate can decrease gasification cycles and reduce residual carbon formation.

3.5 Effect of fine coal particles on performance of CWS

During pulverization of coal, there is destruction of partial pore structures that leads to a decrease in bound water content of the matrix of coal. This effect leads to a higher proportion of free water in CWS system and thereby increases fluidity with addition of fine particles of coal. By optimizing the particle size distribution of coal in CWS through adding fine coal particles into the gaps between large coal particles, the packing density is increased. This forms a compact packing structure and enhances the steric hindrance effect. Additionally, the higher zeta potential of fine particles strengthens electrostatic repulsion between particles. The combined effect of these factors synergistically improves both the concentration and stability of the CWS significantly. Along with this, higher SSA of fine particles provides large numbers of active sites for gasification reactions that reduce E significantly and thus enhance gasification reactivity of CWS. However, the addition of excessive fine particles leads to aggregation through lack of dispersion. Synergistic action of van der Waals forces and liquid bridging between particles leads to viscous dominance that causes a dramatic increase in apparent viscosity that finally restricts maximum possible solid content. The conceptual model of the influence of fine coal particles on the performance of coal water slurry is shown in Figure 12.

Figure 12: Conceptual model of fine coal particle effects on performance of CWS.
Figure 12:

Conceptual model of fine coal particle effects on performance of CWS.

4 Conclusions

  1. The addition of 15 % fine particles of coal (D50 ≈ 10 μm) has a significant impact on CWS performance. This change increases CWS concentration to 63.5 % from 60.5 % and the fractal dimension to 2.412 from 2.231. Further, fine particles enhance the pseudoplastic character of slurry and fluidity. This is evident through a rise of 21.2 % in the spreading area per unit mass, which indicates enhanced processability and transportability of CWS.

  2. The incorporation of fine particles also aids with greater electrostatic stability. CWS has a rise in ζ of 40.8 %, with reduced interparticle distance and greater steric hindrance effects. Over and above this, electric double layers of charged fine particles overlapping with each other form a three-dimensional electrostatic barrier that reduces potential fluctuations to less than 2 % in all layers. This structural support leads to overall anti-sedimentation stability and long-term homogeneity in the slurry.

  3. The gasification efficiency of CWS is significantly improved with fine particles of coal. Compared with CWS without fine particles of coal, the modified slurry is characterized by a forward shift of the reaction window with a decrease in both T max and T e. Additionally, there is an increase in K mean by 188 %, enhancement in k 0 by 10 %, and decrease in E by 1.25 %. These results confirm that addition of fine particles of coal lowers the energy barrier of the reaction and enhances collision frequencies of molecules and thereby enhances low temperature efficiency and high reactivity of CWS in industrial gasification processes.

Corresponding author: Ming Liu, Anhui Provincial Institute of Modern Coal Processing Technology, Anhui University of Science and Technology, Huainan, China; and School of Chemical and Blasting Engineering, Anhui University of Science and Technology, Huainan, China, E-mail:

Funding source: Open Research Fund Program of Anhui Provincial Institute of Modern Coal Processing Technology

Award Identifier / Grant number: MTY202308, MTY202203

Funding source: University-level key projects of Anhui University of Science and Technology

Award Identifier / Grant number: xjyb2020-05

  1. Funding information: The work was supported by the Open Research Fund Program of Anhui Provincial Institute of Modern Coal Processing Technology, Anhui University of Science and Technology (Grant No. MTY202308, MTY202203), University-level key projects of Anhui University of Science and Technology (Grant No.xjyb2020-05).

  2. Author contribution: Ming Liu: data analysis, writing – original draft, writing – review & editing, funding acquisition. Han-xu Li: conceptualization and supervision. Ye Zhang: investigation, funding acquisition.

  3. Conflict of interest: The authors state no conflicts of interest.

  4. Data availability: All data generated or analysed during this study are included in this published article.

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Received: 2025-08-14
Accepted: 2025-12-07
Published Online: 2026-01-21

© 2026 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/gps-2025-0133
Keywords for this article
coal water slurry; fine coal particles; gasification reaction; fractal dimension; packing efficiency
Creative Commons
BY 4.0

Articles in the same Issue

  1. Research Articles
  2. Green processing of industrial waste and obtaining adsorbent for purification of sulfur dioxide
  3. Eco-sustainable synthesis of chromium oxide (Cr2O3) nanoparticles via pomegranate husk extract: calcination-driven control of structure and properties
  4. Effect of starch modification on the mechanical, thermal, morphological, and biodegradability properties of Nylon 6-based nanocomposites
  5. Optimization of coal water slurry properties through fine coal particle addition
  6. Biosynthesis of TiO2 nanoparticles via Pleurotus florida as a green nanotechnology-based strategy for multifunctional therapeutic applications
  7. Human health risk due to polycyclic aromatic hydrocarbons in PM10 and PM2.5: a case study at two selected Kindergartens in Hanoi, Vietnam
  8. Hierarchical microporous miscanthus-derived activated carbon enables entropy-driven high-efficiency dye removal
  9. Graphite, graphene oxide, and reduced graphene oxide: comparative characterization of optical, morphological, structural and electric relaxation properties
  10. Solvent-free ionic gelation of carvacrol-loaded chitosan nanoparticles: fractional factorial optimization and pH-responsive release
  11. Erratum
  12. Erratum to: Optimizing ultrasound-assisted extraction process of anti-inflammatory ingredients from Launaea sarmentosa: a novel approach
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