Aggregating structure in coal water slurry studied by eDLVO theory and fractal dimension

Abstract

Coal water slurry gasification is a main source of hydrogen in the developing hydrogen economy. Moreover, biomass and waste can be added, making gasification process greener. To expand the application of coal water slurry and gasification process, it is necessary to understand the micro-structure in this large particle suspension system. In this paper, the micro-structure in coal water slurry was studied by extended DLVO (eDLVO) theory and fractal dimension, which is used to explain the mechanism of stability in large particle suspension systems. The interaction between two coal particles was characterized from the interparticle potential and energy barrier based on the eDLVO theory. The rheology and stability between different types of coals are measured and explained by the aggregating structure and fractal dimension in coal water slurry. The results indicated that there would be an aggregating structure in high rank coals, due to the interparticle potential caused by the surface properties, but probably not in low rank coals. This aggregating structure can be described and characterized by fractal dimension. The aggregation of particles is the source of the stability for high rank coals, as the close-packed 3D network structure in large particle suspension can support coal particles from settling down. The results have demonstrated that the combination of the eDLVO theory and rheological measurement is an effective way to investigate the stability of large particle suspension systems.

Graphical abstract

Keywords

coal water slurry / extended DLVO (eDLVO) / fractal dimension / stability

1 Introduction

Coal water slurry (CWS), a kind of coal-based liquid fuel, which has the fluidity and stability similar to oil, can be easily pumped, transported and stored, mainly used for gasification and combustion [1,2]. In the 1970s, due to the world oil crisis, OECD countries such as the US, Canada, Sweden, Japan, and Germany conducted a lot of studies in coal water slurry preparation, long-distance pipeline transportation, and large-scale power plants burning [3]. Nowadays in China, since coal is the major energy source, the consumption of coal water slurry for gasification has exceeded 200 million t/a, with 30 million t/a for combustion (total ca. 100 million tons oil equivalent, or 700 million barrels of oil equivalent) [4], in industries such as electricity, petroleum, chemical industry, building materials, etc. Recently, biomass and waste with a relative low calorie are added into coal water slurry to gasify and generate hydrogen to make the gasification process greener. In the developing hydrogen economy, gasification is a main source for hydrogen, which can be used as a low carbon fuel, not only for chemical products and heat, but also for hydrogen vehicles, energy storage, and long-distance transport of energy. Coal water slurry gasification has the characteristics such as operation convenience, feeding flexibility, and low investment, which is suitable for large scale hydrogen production [5,6]. However, the stability of coal water slurry is always a problem which confines the application of coal water slurry in the place of the gasification plant. Moreover, adding biomass and wastes will significantly influence the stability of coal water slurry [7–11]. Therefore, it is necessary to understand the mechanism of stability of coal water slurry.

Coal water slurry is thermodynamically unstable and will inevitably settle down because of gravity, as most of the particles are larger than 1 μm [12–14]. To make a stable suspension with large particles (>1 mm), extra forces are needed to support particles against gravity [15,16]. The electrical double layer repulsive force and the van der Waals attractive force, referred to as the DLVO (Derjaguin-Landau-Verwey-Overbeek) theory, are the forces usually discussed in the colloidal suspension system to quantitatively explain the aggregation of dispersion [17,18]. In 1969, Laskowski and Kitchener [19] found that besides the traditional DLVO force, there are other attractions between bubbles and hydrophobic solid particles in the phenomena of instability of water film on the surface of methyl silica. In 1972, Israelachvili and Pashley [20] used surface force apparatus (SFA) for the first time to directly measure the additional long-range attraction between solid surfaces in addition to the traditional DLVO force, giving direct evidence of the existence of hydrophobic forces. By considering the effects of hydrophobic forces into the DLVO theory, the extend DLVO (eDLVO) theory was developed [20–23].

The DLVO and the eDLVO theory are usually applied in the colloidal system, such as tailing water treatment and flotation [24–27]. In the coal field, the eDLVO theory is applied in the area of coal-bubble interaction and coal-mineral interaction [28–30]. However, few of the studies focus the application of eDVLO theory in large particle suspension, as the particles will naturally settle down. Moreover, the influence of micro-forces (electrical double layer force and van der Waals force) on the stability of large particle suspension is rarely studied.

The rheology of coal water slurry has long been studied, especially on the influence of dispersant and stabilizer [12,31,32]. The coal water slurry can be shear thinning, shear thickening, or Newtonian flow, with or without yield stress. More studies are focused on increasing the concentration of coal water slurry with different additives, others are focused on the stability, while still others are focused on the micro-structure and particle-particle interaction in the slurry. The interparticle interaction and micro-structure are one of the basic factors influencing the rheology in colloidal suspension [33]. In coal tailing treatment, it is found that coal particles can be aggregated as flocs and characterized by fractal analysis [34]. However, for coal water slurry with a high concentration, it is unclear whether coal particles are aggregated in slurry. The coal water slurry at a high concentration is opaque and closer to a gel state, making it hard to directly characterize the aggregating structure. The influences of aggregation on the rheology and stability of coal water slurry are still less reported.

The fractal concept has been applied for the quantification of aggregating structure through fractal dimension in the colloidal system, though some challenges still remain in the accurate and efficient measurement of fractal dimension. Fractal dimension is a ratio, which provides a statistical index of complexity and reflects the validity of space occupied by complex bodies [35]. Generally, when the fractal dimension is large, the aggregation network is more compact. Small angle light scattering, qualitative image analysis, confocal scanning laser microscopy, light obscuration measurement, and sedimentation measurement are the main application for the determination of mass fractal dimension of aggregates [36,37]. However, for the coal water slurry with a high solid concentration, the aforementioned methods are not applicable or not proper to determine the fractal dimension, as the opaque and dense slurry is not suitable for optical and laser measurements and difficult to be sampled without changing the original structure. Therefore, the fractal data and micro structure of coal water slurry are less reported. To overcome these barriers, a method related to yield stress and fractal dimension of aggregating structure will be employed.

In this paper, the interparticle potential between two coal particles in large particle suspension is calculated based on the eDLVO theory using the data of surface properties of different coal samples. Besides, the relation between interparticle potential and the stability of coal water slurry is quantitatively studied by using the eDLVO theory and conducting rheological experiments. Moreover, the three-dimension structure of coal aggregation, caused by interparticle potential, in coal water slurry is implied by fractal dimension from rheological measurement. Furthermore, the mechanism of the stability of large particle suspension is explained by interparticle interaction and aggregating structure.

2 Experimental

2.1 Materials

Four coal samples are used in the experiments: WCW (Wucaiwan) coal from Zhundong area in Xinjiang Uygur Autonomous Region, China; HLR coal from Hailar district in Inner Mongolia Autonomous Region, China; SHH coal, a mixed coal, used in Shenhua Sanhe Power Plant in Hebei province, China; BD coal, from Boundary Dam, Canada. Part of the data of BD coal is cited from Ref. [16] for the comparison in this paper. The proximate and ultimate analysis data of coal samples are listed in Table 1.

2.2 Diffuse reflectance infrared fourier transform spectroscopy (DRIFTS)

The spectra of dry coal samples from 400 cm^–1 to 4000 cm^–1 at a 4 cm^–1 resolution were obtained by using the Nicolet FTIR spectrometer with a diffuse reflection accessory (Thermo scientific). A high temperature reaction chamber was attached into the diffuse reflection accessory for the in-situ measurement. About 5 mg coal sample and 50 mg analytical pure KBr powder were mixed and then loaded into the reaction chamber. The sample was heated up to 100°C with an equilibrium time of 5 min. The dry KBr spectrum at 100°C was used as the background spectrum. The FTIR spectra of the samples were obtained by deducting the background spectrum with baseline correction.

2.3 Contact angle

The contact angle of coals was measured by using the sessile drop method on a pressed fine coal disc with a drop shape analyzer (DSA, Krüss, Germany) equipped with an optical microscope and illumination system. The coal disc was prepared by pressing 400 mg of dry coal sample (mean particle size smaller than 100 mm) at 30 MPa for 2 min followed by polishing with 1200 grits silicon carbide abrasive papers. The contact angle measured by using this method is influenced by the porosity, compressing pressure, and its own heterogeneity of coal disc. The real contact angle, excluding the effect of porosity, can be gained by the correction of the Cassie-Baxter equation [38].

2.4 Zeta potential

A suspension containing 0.1 wt.% to 0.5 wt.% coal sample was prepared at its nature pH (7.2–8.2) with 1 mmol/L KCl background electrolyte. The suspension was allowed to settle for 5 h and the supernatant was used for zeta potential measurements by Zetasizer Nano ZS (Malvern Instruments, UK) at room temperature.

2.5 Rheology

The coal water slurries were mixed by deionized water and coal samples according to the desired concentration. No apparent sedimentation was visualized for all the slurries prepared for 1 h. Twenty minutes of mechanical mixing was applied in order to generate the homogeneous dispersions before measurement.

A coaxial cylinder rheometer (Rheolab QC, Anton Paar, Austria) equipped with a temperature-controlled water bath was used to measure the rheological behaviors of coal water slurries. Prior to measurement, sixty seconds of pre-shear at 200 s^–1 followed by a 30 s equilibrium time was applied to remove the shear history. The steady state shear sweep method was applied to measure the viscosity of coal water slurry. The proper shear rate range was selected for specific samples to ensure the laminar flow. An equilibrium time of 10 s was used for each shear rate to ensure that the steady state was reached before each measurement. All the experiments were conducted at (20±0.1)°C.

2.6 Stability measurement

The glass rod penetration test was employed to evaluate the stability of CWS by measuring the variation of penetration ratio (%) with storage time (h) as described in Refs. [16,39]. The CWS after preparation was stored in a glass cylinder (calibration from 0 to 100 mL) at room temperature for 7 days to test the stability. A schematic graph of coal water slurry in cylinder after storage is shown in Fig. 1. A glass rod (5.3 mm in diameter and 62.4 g in weight) was dropped down from the CWS surface perpendicularly to the bottom of the cylinder. The glass rod stopped when the tip went through the loose layer and contacted with the hard sediment. The penetration ratio was calculated as

(1)\mathrm{Penetration}\mathrm{\hspace{0.17em}}\mathrm{ratio}(\%)={\displaystyle \frac{d_{\mathrm{p}}}{d_{\mathrm{t}}}}\times \mathrm{100},

where d_p is the distance the glass rod traveled (cm) and d_t is the height of the total slurry in cylinder.

The mud line is a line between the supernatant layer and the dark slurry layer. The separation ratio was calculated as

(2)\mathrm{Separation}\mathrm{\hspace{0.17em}}\mathrm{ratio}(\%)={\displaystyle \frac{d_{\mathrm{s}}}{d_{\mathrm{t}}}}\times \mathrm{100},

where d_s is the length of the supernatant above the mud line.

3 Results and discussion

3.1 Interparticle interaction characterized by eDLVO from coal surface properties

The aggregation or separation between two identical and spherical coal particles can be predicted by their interparticle potential. The interparticle potential can be calculated by applying the extended DLVO (eDLVO) model with the data of surface property.

Figure 2 depicts the infrared spectra of the HLR, WCW, and SHH coals. The broad peak strength between 3100–3600 cm^–1 in Fig. 2 represents the amount of water and –OH functional groups on the surface of coal samples while the narrow peak strength between 1550–1700 cm^–1 represents the number of C=O and carboxyl groups on the surface of coal samples [40]. Therefore, the number of oxygen functional groups on the surface of different coals has the following trends: WCW>HLR>SHH.

The contact angles of different coal samples are directly measured by experiments, as demonstrated in Fig. 3. The value of contact angles from coal sample is SHH (84°), HLR (69°)>WCW (66°)>BD (58°). The values of contact angles from coal samples are consistent with the number of oxygen functional groups on the surface of coal samples. The contact angles of BD, HLR, and WCW are close, which is much smaller than that of SHH.

Figure 4 illustrates the zeta potential of coal samples. The absolute value of zeta potential from coal samples is BD (–57 mV)>WCW (–35mV)>HLR (–32 mV)>SHH (–27 mV). The trend of Zeta potential is consistent with the data of oxygen functional groups on the surface of coal samples, but the difference of zeta potential between BD coal and other coal samples is large.

The DVLO theory mainly considers the electric double layer force/potential (V_E) and the van der Waals force/potential (V_D) between particles, which can be used to quantitatively describe colloidal stability. The hydrophobic force between hydrophobic surfaces has a long range of action, which makes hydrophobic particles tend to associate with each other [12,41,42]. The extended eDLVO theory considers the effect of hydrophobic force/potential (V_H) based on the DLVO theory and the specific expression of the total potential energy (V_T) between particles is expressed in Eq. (3) [43].

(3)V_{\mathrm{T}}=V_{\mathrm{E}}+V_{\mathrm{D}}+V_{\mathrm{H}}.

The van der Waals force between two identical coal particles is always attractive [44]. When the distance between particles is very small, it promotes particle aggregation. For two identical coal particle spheres with diameter a, which has a distance H, when a>H, the effect of the van der Waals potential can be expressed as [43,44]

(4)V_{\mathrm{D}}=-{\displaystyle \frac{A_{\mathrm{121}}a}{\mathrm{12}H}},

where A₁₂₁ is the Hamaker constant of material 1 in medium 2 with material 1.

In coal water slurry, part of the dissolved metal cation adsorbs on the coal surface, forming a double electric layer structure. The concentration of ions in solution has a great influence on the electric potential of particle surface. With the increase of ion concentration in the solution, the diffusion layer becomes thinner and reduces the value of electrical double layer potential. For two spherical particles with surface potential ({\psi }_{\mathrm{\delta }}), the value of electrical double layer potential can be expressed as [45]

(5)V_{\mathrm{E}}=\mathrm{2}\mathrm{\pi }\epsilon a{\psi }_{\mathit{\delta }}^{\mathrm{2}}\ln [\mathrm{1}+\exp (-\kappa H)],

where ε is the dielectric constant, {\kappa }^{-\mathrm{1}} is the Debye screening length, and {\psi }_{\mathit{\delta }} is the Stern potential (Zeta potential is used for calculation instead.).

Although the origin of hydrophobic forces is still being debated, there is overwhelming evidence for its existence, as stated in Introduction. The hydrophobic force may also be described in the form of the van der Waals equation. For two identical spherical particles, when a>H, the hydrophobic effect can be calculated with a similar form of the van der Waals potential by [29,30]

(6)V_{\mathrm{H}}=-{\displaystyle \frac{K_{\mathrm{121}}a}{\mathrm{12}H}},

where K₁₂₁ is the hydrophobic constant of material 1 in medium 2 with material 1, which can be calculated as [42]

(7)K_{\mathrm{121}}=A\exp (b_k\theta ),

where b_k is constant, when q<86.89°, A=\mathrm{2.732}\times {\mathrm{10}}^{-\mathrm{21}}, b_k = 0.04136 [46].

By substituting Eqs. (4)–(6) into Eq. (3), the equation for calculating the potential between two identical spherical coal particles can be obtained by

(8)V_{\mathrm{T}}=\mathrm{2}\mathrm{\pi }\epsilon a{\psi }_{\mathit{\delta }}^{\mathrm{2}}\ln [\mathrm{1}+\exp (-\kappa H)]-{\displaystyle \frac{A_{\mathrm{121}}a}{\mathrm{12}H}}-{\displaystyle \frac{K_{\mathrm{121}}a}{\mathrm{12}H}}.

Table 2 tabulates the values of parameters for calculation in Eq. (8) by using the eDLVO model. The potential between two identical spherical coal particles calculated from Eq. (8) is exhibited in Fig. 5. It should be pointed out that some assumptions are made in the derivation of Eq. (8) and the systematic inaccuracy may be accrued during the measurement of the values of parameters, which are two major factors influencing the results in Fig. 5. In the derivation of Eq. (8), it is mainly assumed that two coal particles are identical and spherical; the diameter of coal particle is much larger than the distance between two particles, namely a>>H; the surface of coal particle is homogeneous, including surface charges etc.; and the equation used for calculating hydrophobic effect and subsequent equations are empirical formulas. The deviation induced in the calculation process are as follows: Zeta potential is used as Stern potential in the calculation of Eq. (5); systematic errors in measurement of contact angle and Zeta potential are inevitable; interpolation calculations and assumptions are made for the values of Hamaker constant and {\kappa }^{-\mathrm{1}}.

As shown in Fig. 5, for different types of coals, the potentials between two coal particles are quite different. The main difference is the change of energy barrier between particles. For BD coal, a lignite with very low degree of coalification, there is a significant energy barrier, which prevents coal particles from further approaching and aggregating. For SHH coal, a coal with a higher degree of coalification, the energy barrier disappears and coal particles have a natural agglomeration. WCW and HLR coal are between the two. WCW coal has an energy barrier smaller than BD coal, but larger than HLR, which is still larger enough to prevent two coal particles from getting close to each other. However, the energy barrier of HLR coal is small enough, which can be overcome by the Brownian motion and the small hydrodynamic force of particles. In this way, Fig. 5 theoretically predicts the possibility of the aggregation of particles by the calculation of interparticle potential from the eDLVO model.

3.2 Interparticle interaction indicated from rheological measurement

The interaction potential between coal particles can be indicated through the rheological measurement of coal water slurry. The rheological experimental data points and fitting curve of coal water slurry made from SHH and WCW coal is displayed in Fig. 6. Generally, all the samples of coal water slurry present the shear-thinning behavior with a yield stress. The yield stress usually exhibits in flocculated suspensions, which is related to the strength of the network structure generated by the aggregation of particles, as the force per unit area required to breakdown the structure [48]. Therefore, the yield stress shows the interparticle forces in the macro scale.

With the increase of shear rate, the shear stress of CWS changes accordingly, which can be fitted by the Herschel–Bulkley (H-B) model. H-B model is a power-law function with yield stress term. It is widely used to simulate the fluid with a yield stress and pseudoplastic behavior [49],

(9)\sigma ={\sigma }_{\mathrm{0}}+K{\dot{\gamma }}^n,

where σ and σ₀ are shear stress and yield stress (Pa), \dot{\gamma } is shear rate (s^–1), and n is rheological index (dimensionless). When n=1, the slurry is Newtonian fluid; n>1, it is dilatant fluid; when n<1, it is pseudoplastic fluid. K is consistency coefficient (Pa⋅sⁿ), and as the K value increases, the slurry thickens, and the apparent viscosity increases, too.

The lines in Fig. 6 are the fitting curves after power law fitting of data points using the H–B model with a good match with the data points. Table 3 lists the fitting parameters. From Fig. 6 and the rheological index (n) in Table 3, it can be seen that the coal water slurry made from SHH and WCW coals exhibits shear thinning characteristics (n<1). With the increase of slurry concentration, the value of n decreases and the pseudoplastic property increases, which indicates that the slurry with a low concentration is close to the Newtonian fluid. However, with the increase of concentration, it is closer to the pseudoplastic fluid. The shear thinning behavior is probably caused by the break of the microstructure of the aggregation of particles [50,51]. When increasing the solid loading of the slurries made by SHH coal, the yield stress increases, which is similar to the slurries made by WCW coal. In Table 3, for the samples with a similar viscosity (different solid loading), the yield stress of the slurries made by SHH is systematically higher than that of WCW. It can be seen that the slurries made by SHH coal have a stronger network structure generated by particle aggregation, which is predicted by the interparticle potential in Fig. 5.

It is supposed that the network structure can prevent coal particles from settling down, i.e., the aggregation of particles predicted by interparticle potential can render the large particle system stability. To verify this, the stability of coal water slurry is tested and the network structure of coal water slurry is implied by rheological measurements.

3.3 Aggregating structure in coal water slurry

The homogeneous coal water slurries, stored in the cylinder after 7 days, is separated into three layers: supernatant, soft sediment and hard sediment (from top to bottom), as demonstrated in Fig. 7. The detailed data of the variation of the stability classified by the separation ratio and the penetration ratio with the storage time are shown in Fig. 8. As shown in Fig. 8(a), the separation ratio of coal water slurry of different coal types and concentrations increase with stationary time, which means the supernatant layer is generated/separated and increases with the storage time. The separation ratio increases rapidly with time, then decreases gradually, and finally stabilizes after 168 h (a week). The separation ratio at 168 h is presented in Table 4, with the calculation of concentrations of the slurries below the supernatant. It can be seen that the separation ratio decreases with the increase of coal water slurry concentration for each type of coals. It is noteworthy that for the same type of coal, although the original concentration of coal water slurry is different, the solid loading of the coal water slurry layer below the supernatant is almost the same after a week of storage. Moreover, the solid loading in Table 4 is in accordance with the maximum solid loading of each type of coal (data not shown in this paper).

Figure 8(b) is the penetration ratio of coal water slurry of different coal types and concentrations. The penetration ratio means the volume percentage of the coal water slurry that can be retrieved from the original coal water slurry after a certain period of storage by simple stir. The penetration ratio can also be used as the stable ratio of coal water slurry, if neglecting the supernatant after storage. Except for the coal water slurry made from WCW coal, other coal water slurries are relatively stable, only a slight precipitation in the first 24 h, and then tending to be stable with a penetration ratio or stable ratio more than 95%. For coal water slurries made from WCW and BD coal, hard sediment of the slurries increases fast at the beginning of storage to 100 h. As the concentration decreases, the stability decreases.

Figures 2 to 5 indicate that different types of coals have different surface properties, which in turn affect the interparticle potential. For SHH and HLR coal, there is no energy barrier or very small barrier between the two particles, which makes coal particles spontaneously aggregate together in aqueous solution to form a three-dimensional structure as demonstrated in Fig. 9. For WCW coal and BD coal, there is an energy barrier between coal particles to prevent coal particles from gathering together. From Table 4 and Fig. 8, it can be seen that the coal water slurry with particle aggregation has a better stability. The stability of coal water slurries can probably be explained by the network structure generated by the interparticle potential that prevents coal particles from settling into closed packing (hard sediment).

To verify the assumption above, it is necessary to characterize the network structure to bridge between stability and interparticle potential. The yield stress is used to show the strength of the network structure above, while in this part the fractal dimension is used to characterize the three-dimension structure of the network.

The fractal concept has been applied for the quantification of aggregating structure through fractal dimension in the colloidal suspension system, which can also be used in the large particle (D₅₀>0.2 mm) suspension system. Fractal dimension is a ratio, which provides a statistical index of complexity and reflects the validity of the space occupied by complex bodies [35]. Generally, the aggregation network is more compact with a larger fractal dimension. The simulated images of aggregating structure of the identical and spherical coal particles with different fractal dimensions are demonstrated in Fig. 9, which is simulated by MATLAB, assuming that coal particles are rigid after sticking to each other. With the increase of fractal dimension, the aggregating structure becomes more compact as the validity of space is occupied by more particles. Meanwhile, more and more particles are aggregated together to form a complex structure, rather than suspending freely in the slurry.

As mentioned above, due to the opacity and high solid loading of the slurry, most of the measurements of the fractal dimension are not applicable or not accurate for coal water slurry without changing its micro structure. To overcome these barriers, a method connecting the yield stress and the fractal dimension of the aggregating structure is employed. The fractal dimension of the coal particle aggregation structure is calculated by using the exponential relationship between the yield stress and the volume fraction proposed by Dorget et al. [52].

(10){\sigma }_{\mathrm{0}}\approx \beta {\displaystyle \frac{kTR}{a^{\mathrm{4}}}}{({\varphi }_{\mathrm{v}})}^{\frac{\mathrm{4}}{\mathrm{3}-D}},

where σ₀ is the yield stress, {\varphi }_{\mathrm{v}} is the volume fraction of particles, D is the fractal dimension of aggregation structure, k is the Boltzmann constant, T is the temperature, a is the diameter of particles, R is the radius of agglomeration structure, and β is the structural coefficient. This equation is originally used in the colloidal system. As the assumption of this equation is similar, it is also employed in this paper. When the volume fraction is close to the solid-gel transition point, the fractal dimension can be seen as a constant. Meanwhile, the yield stress and the volume fraction have a local approximate power law relation [53–55], as shown in

(11){\sigma }_{\mathrm{0}}\propto {({\varphi }_{\mathrm{v}})}^{\frac{\mathrm{4}}{\mathrm{3}-D}}.

This means that in logarithmic coordinates, lgσ₀ and lg {\varphi }_{\mathrm{v}} are linear near the solid-gel transition point, thus the fractal dimension D can be calculated from coefficients. Figure 10 shows the relationship between the yield stress and the volume fraction of coal water slurry at the same temperature and particle size distribution. The data points are linearly distributed in logarithmic coordinates, and the fitted index (4/(3–D)) is 7.04. Therefore, the fractal dimension of the aggregation structure of the coal water slurry prepared from SHH coal is 2.43. This result is close to the fractal dimension range (2.27–2.66) measured by Liao et al. [36]. By measuring the fractal dimension, the micro structure of coal particles in the slurry is characterized.

4 Conclusions

In this study, the micro-structure in coal water slurry is by eDLVO theory and fractal dimension. The interaction between two coal particles was characterized from the interparticle potential and energy barrier based on the eDLVO theory. The rheology and stability between different types of coals were measured and explained by the aggregating structure and fractal dimension in coal water slurry. The mechanism of the stability of coal water slurry was investigated by applying the eDLVO theory and rheological measurements. The results demonstrated that the combination of the eDLVO theory with rheological measurement is an effective way to investigate the stability of large particle suspension systems.

The main results obtained are summarized as follows:

(1) The aggregation or separation of large particles (coal particles) can be predicted from the interparticle potential and energy barrier, which can be calculated by eDLVO theory using the data of surface properties of different coal samples.

(2) There is an aggregating structure in high rank coals, due to the interparticle potential resulted from their surface properties and calculated from eDLVO equations, but probably not in low rank coals.

(3) The aggregation of particles is the source of the stability for high rank coals, as the close-packed 3D network structure in large particle suspension can prevent coal particles from settling down.

(4) The 3D structure of the aggregation in coal water slurry was implied and quantified through rheological measurements and fractal dimension.

This paper provides some basic information and methods for future investigation of coal water slurry with the addition of biomass and wastes.

References

[1] Li Q, Zhang J. Coal gasification. In: Cheng Y, Jin Y, eds. Multiphase Reactor Engineering for Clean and Low-Carbon Energy Applications. Wiley, 2017

[2] Strizhak P A, Vershinina K Y. Maximum combustion temperature for coal-water slurry containing petrochemicals. Energy, 2017, 120: 34–46

[3] Papachristodoulou G, Trass O. Coal slurry fuel technology. Canadian Journal of Chemical Engineering, 1987, 65(2): 177–201

[4] Duan Q, Zhang S, Duan J. Development outlook and preparation and application technology of coal water mixture. Coal Science and Technology, 2017, 45: 205–213 (in Chinese)

[5] Wan W, Dai Z, Li C, Innovative concept for gasification for hydrogen based on the heat integration between water gas shift unit and coal–water–slurry gasification unit. International Journal of Hydrogen Energy, 2014, 39(15): 7811–7818

[6] Shim H, Jung S, Wang H Y, The comparison study on the operating condition of gasification power plant with various feedstocks. Korean Journal of Chemical Engineering, 2009, 26(2): 324–331

[7] Zhang Y, Xu Z, Tu Y, Study on properties of coal-sludge-slurry prepared by sludge from coal chemical industry. Powder Technology, 2020, 366: 552–559

[8] Yi S, Hao L, Li S, The influence of water content in rice husk bio-oil on the rheological properties of coal bio-oil slurries. Energy, 2019, 189: 116307

[9] Wang C, Zhao H, Dai Z, The effect of inorganic salt in wastewater on the viscosity of coal water slurry. Environmental Science and Pollution Research International, 2019, 26(14): 14171–14177

[10] Liu P, Zhu M, Zhang Z, Rheological behaviour and stability characteristics of biochar-water slurry fuels: effect of biochar particle size and size distribution. Fuel Processing Technology, 2017, 156: 27–32

[11] Li W, Li W, Liu H, Influence of sewage sludge on the slurry ability of coal–water slurry. Fuel, 2009, 88(11): 2241–2246

[12] Botsaris G D, Glazman Y M. Stability and rheology of coal slurries. In: Botsaris G D, Glazman Y M, eds. Interfacial Phenomena in Coal Technology. New York: Marcel Dekker Inc., 1989

[13] Usui H, Saeki T, Hayashi K, Sedimentation stability and rheology of coal water slurries. Coal Preparation, 1997, 18(3–4): 201–214

[14] Dinçer H, Boylu F, Sirkeci A A, The effect of chemicals on the viscosity and stability of coal water slurries. International Journal of Mineral Processing, 2003, 70(1–4): 41–51

[15] Laskowski J. Coal Flotation and Fine Coal Utilization. Houston: Gulf Professional Publishing, 2001

[16] Li Q, Yang D, Liu Q, Hydrothermal dewatering of lignite water slurries: part 2 surface properties and stability. Canadian Journal of Chemical Engineering, 2019, 97(1): 133–139

[17] Derjaguin B V, Churaev N V, Muller V M. The Derjaguin–Landau–Verwey–Overbeek (DLVO) theory of stability of lyophobic colloids. In: Surface Forces. Springer, 1987

[18] Chaturvedi T, Schembre J M, Kovscek A R. Spontaneous imbibition and wettability characteristics of Powder River Basin coal. International Journal of Coal Geology, 2009, 77(1–2): 34–42

[19] Laskowski J, Kitchener J A. The hydrophilic—hydrophobic transition on silica. Journal of Colloid and Interface Science, 1969, 29(4): 670–679

[20] Israelachvili J, Pashley R. The hydrophobic interaction is long range, decaying exponentially with distance. Nature, 1982, 300(5890): 341–342

[21] Yotsumoto H, Yoon R H. Application of extended DLVO theory: I. stability of rutile suspensions. Journal of Colloid and Interface Science, 1993, 157(2): 426–433

[22] Yotsumoto H, Yoon R H. Application of extended DLVO theory: II. stability of silica suspensions. Journal of Colloid and Interface Science, 1993, 157(2): 434–441

[23] Boinovich L. DLVO forces in thin liquid films beyond the conventional DLVO theory. Current Opinion in Colloid & Interface Science, 2010, 15(5): 297–302

[24] Yu Y, Ma L, Xu H, DLVO theoretical analyses between montmorillonite and fine coal under different pH and divalent cations. Powder Technology, 2018, 330: 147–151

[25] Wang C, Harbottle D, Liu Q, Current state of fine mineral tailings treatment: a critical review on theory and practice. Minerals Engineering, 2014, 58: 113–131

[26] Deng M, Xu Z, Liu Q. Impact of gypsum supersaturated process water on the interactions between silica and zinc sulphide minerals. Minerals Engineering, 2014, 55: 172–180

[27] Tao D. Role of bubble size in flotation of coarse and fine particles—a review. Separation Science and Technology, 2005, 39(4): 741–760

[28] Zhang M, Liu Q, Liu J. Extended DLVO theory applied to coal slime-water suspensions. Journal of Central South University, 2012, 19(12): 3558–3563

[29] Piñeres J, Barraza J. Energy barrier of aggregates coal particle–bubble through the extended DLVO theory. International Journal of Mineral Processing, 2011, 100(1–2): 14–20

[30] Yoon R, Mao L. Application of extended DLVO theory, IV: derivation of flotation rate equation from first principles. Journal of Colloid and Interface Science, 1996, 181(2): 613–626

[31] Kaji R, Muranaka Y, Miyadera H, Effect of electrolyte on the rheological properties of coal-water mixtures. AIChE Journal, 1987, 33(1): 11–18

[32] Roh N S, Shin D H, Kim D C, Rheological behaviour of coal-water mixtures. 1. Effects of coal type, loading and particle size. Fuel, 1995, 74(8): 1220–1225

[33] Mewis J, Wagner N J. Colloidal Suspension Rheology. Cambridge: Cambridge University Press, 2012

[34] Ofori P, Nguyen A V, Firth B, Shear-induced floc structure changes for enhanced dewatering of coal preparation plant tailings. Chemical Engineering Journal, 2011, 172(2–3): 914–923

[35] Bushell G C, Yan Y D, Woodfield D, On techniques for the measurement of the mass fractal dimension of aggregates. Advances in Colloid and Interface Science, 2002, 95(1): 1–50

[36] Liao J Y H, Selomulya C, Bushell G, On different approaches to estimate the mass fractal dimension of coal aggregates. Particle & Particle Systems Characterization, 2005, 22(5): 299–309

[37] Bushell G C, Yan Y D, Woodfield D, On techniques for the measurement of the mass fractal dimension of aggregates. Advances in Colloid and Interface Science, 2002, 95(1): 1–50

[38] He Y B, Laskowski J S. Contact angle measurements on discs compressed from fine coal. Coal Preparation, 1992, 10(1–4): 19–36

[39] Qiu X, Zhou M, Yang D, Evaluation of sulphonated acetone–formaldehyde (SAF) used in coal water slurries prepared from different coals. Fuel, 2007, 86(10–11): 1439–1445

[40] Georgakopoulos A. Study of low rank Greek coals using FTIR spectroscopy. Energy Sources, 2003, 25(10): 995–1005

[41] Yoon R, Flinn D H, Rabinovich Y I. Hydrophobic interactions between dissimilar surfaces. Journal of Colloid and Interface Science, 1997, 185(2): 363–370

[42] Pazhianur R, Yoon R. Model for the origin of hydrophobic force. Mining, Metallurgy & Exploration, 2003, 20(4): 178–184

[43] Xu Z, Yoon R H. The role of hydrophobia interactions in coagulation. Journal of Colloid and Interface Science, 1989, 132(2): 532–541

[44] Israelachvili J N. Chapter 13–van der Waals forces between particles and surfaces. In: Intermolecular & Surface Forces. Academic Press, 2011, 253–289

[45] Quemada D, Berli C. Energy of interaction in colloids and its implications in rheological modeling. Advances in Colloid and Interface Science, 2002, 98(1): 51–85

[46] Soni G. Development and validation of a simulator based on a first-principle flotation model. Dissertation for the Doctoral Degree. Blacksburg, US: Virginia Polytechnic Institute and State University, 2013

[47] Biletskyy V, Sergeyev P, Krut O. Fundamentals of highly loaded coal-water slurries. In: Mining of Mineral Deposits. Boca Raton: CRC Press, 2013

[48] Dzuy N Q, Boger D V. Yield stress measurement for concentrated suspensions. Journal of Rheology (New York, N.Y.), 1983, 27(4): 321–349

[49] Herschel W H, Bulkley R. Measurement of rubber-benzole solutions. Colloid & Polymer Science, 1926, 39: 291–300 (in German)

[50] Mishra S K, Senapati P K, Panda D. Rheological behavior of coal-water slurry. Energy Sources, 2002, 24(2): 159–167

[51] Swain P, Panda D. Rheqlogy of coal-water mixtures. Fuel Science & Technology International, 1996,14: 1237–1251

[52] Dorget M. Rheological properties of silica-silicone compounds. Dissertation for the Doctoral Degree. Grenoble, France: Institute National Polytechnique, 1995 (in French)

[53] Pignon F, Piau J, Magnin A. Structure and pertinent length scale of a discotic clay gel. Physical Review Letters, 1996, 76(25): 4857–4860

[54] Pignon F, Magnin A, Piau J, Yield stress thixotropic clay suspension: investigations of structure by light, neutron, and X-ray scattering. Physical Review. E, 1997, 56(3): 3281–3289

[55] Piau J M, Dorget M, Palierne J F, Shear elasticity and yield stress of silica-silicone physical gels: fractal approach. Journal of Rheology (New York, N.Y.), 1999, 43(2): 305–314

RIGHTS & PERMISSIONS

Higher Education Press