Processing‐Dependent Performance of the LiNiO 2 Cathode in Lithium‐Ion Batteries

For enhanced energy and power density, most of the commercially available lithium ion batteries use LiNixMnyCo(1-x-y)O2 (where, x and y are some fraction between 0.0 and 1.0) based active materials in the cathode side[1]. Synthesis of these cathode active materials are conducted through the calcination of transition metal hydroxide (NixMnyCo(1-x-y)(OH)2) precursors with lithium hydroxides or carbonates[2]. Size, shape and internal porosity of the cathode active particles significantly impact the overall performance and cycle life experienced by the lithium ion cell[3]. Morphology of the cathode active particle is usually determined by the size and shape of the transition metal hydroxide precursors[4]. Hence, appropriate understanding of the synthesis mechanism of the hydroxide precursors (NixMnyCo(1-x-y)(OH)2) is necessary for developing better quality cathode active particles for usage in the next generation lithium ion batteries. Coprecipitation reaction at constant pH in continuous stirred tank reactors (CSTR) is the most commonly used technique for developing battery grade transition metal hydroxide precursors in a large scale[2, 4-6]. Focused ion beam scanning electron microscopy (FIB-SEM) images of the cathode active materials clearly reveals the presence of sub-micron sized primary crystalline particles, which aggregates to form micron sized secondary particles[3]. Morphology of these primary and secondary particles are determined during the coprecipitation process, which depends on the solution pH, ammonia content and stirring speed maintained within the reactor[4, 5]. A computational methodology has been developed as part of the present research effort, which successfully captures the nucleation, growth and aggregation of the crystalline primary particles observed during the coprecipitation process within the chemical reactor. Evolution of the primary particle nucleus density occurs according to the magnitude of super-saturation ratio[7]. Growth of the crystalline primary particles happen in a rate limited fashion, which leads to a linear increase in the primary particle diameter with time. Agglomeration of these primary particles lead to the formation of secondary particles[4, 5], which has been simulated using an energy minimization technique. Presence of ammonia within the reactor increases the solubility of the transition metal hydroxides through the formation of metal ammonia complexes[5]. As described by van Bommel and Dahn[5], primary particle growth and aggregation happens through a dissolution-recrystallization mechanism via formation of this metal-ammonia complex. Concentration of this complex depends on the pH and ammonia content of the solution, which has been determined by solving appropriate mass balance equations and equilibrium relations for transition metal ions and ammonia, maintained under constant pH conditions[5, 6]. Figure 1 (black solid line) demonstrates the computationally predicted secondary particle size with respect to the magnitude of solution pH. The particle size distribution is shown by the error-bars, which indicates the first standard deviation. Ammonia content have been kept constant at 1.6M for this particular simulation. Good correlation between the experimentally obtained secondary particle sizes (denoted by red squares in Figure 1)[4] and that predicted by the computational results clearly demonstrates the capability of the developed methodology to capture the real physical phenomena with reasonable accuracy. All the particle sizes and size-distributions reported here have been obtained at the end of the coprecipitation process. Dependence of the particle morphology (such as, size and shape) on the reaction parameters (such as, solution pH, ammonia content) will be elucidated in this study. References Thackeray, M.M., et al., Advances in manganese-oxide 'composite' electrodes for lithium-ion batteries. Journal of Materials Chemistry, 2005. 15(23): p. 2257-2267.Lee, M.H., et al., Synthetic optimization of Li[Ni1/3Co1/3Mn1/3]O-2 via co-precipitation. Electrochimica Acta, 2004. 50(4): p. 939-948.Gilbert, J.A., I.A. Shkrob, and D.P. Abraham, Transition Metal Dissolution, Ion Migration, Electrocatalytic Reduction and Capacity Loss in Lithium-Ion Full Cells. Journal of the Electrochemical Society, 2017. 164(2): p. A389-A399.Noh, M. and J. Cho, Optimized Synthetic Conditions of LiNi0.5Co0.2Mn0.3O2 Cathode Materials for High Rate Lithium Batteries via Co-Precipitation Method. Journal of the Electrochemical Society, 2013. 160(1): p. A105-A111.van Bommel, A. and J.R. Dahn, Analysis of the Growth Mechanism of Coprecipitated Spherical and Dense Nickel, Manganese, and Cobalt-Containing Hydroxides in the Presence of Aqueous Ammonia. Chemistry of Materials, 2009. 21(8): p. 1500-1503.Wang, D.P., et al., Growth mechanism of Ni0.3Mn0.7CO3 precursor for high capacity Li-ion battery cathodes. Journal of Materials Chemistry, 2011. 21(25): p. 9290-9295.Karthika, S., T.K. Radhakrishnan, and P. Kalaichelvi, A Review of Classical and Nonclassical Nucleation Theories. Crystal Growth & Design, 2016. 16(11): p. 6663-6681. Figure 1

Lithium metal for the battery industry

Influence of different lithium sources on the morphology, structure and electrochemical performances of lithium-rich layered oxides

Abstract. It is important to understand the relative contribution of primary and secondary particles to regional and global aerosol so that models can attribute aerosol radiative forcing to different sources. In large-scale models, there is considerable uncertainty associated with treatments of particle formation (nucleation) in the boundary layer (BL) and in the size distribution of emitted primary particles, leading to uncertainties in predicted cloud condensation nuclei (CCN) concentrations. Here we quantify how primary particle emissions and secondary particle formation influence size-resolved particle number concentrations in the BL using a global aerosol microphysics model and aircraft and ground site observations made during the May 2008 campaign of the European Integrated Project on Aerosol Cloud Climate Air Quality Interactions (EUCAARI). We tested four different parameterisations for BL nucleation and two assumptions for the emission size distribution of anthropogenic and wildfire carbonaceous particles. When we emit carbonaceous particles at small sizes (as recommended by the Aerosol Intercomparison project, AEROCOM), the spatial distributions of campaign-mean number concentrations of particles with diameter >50 nm (N50) and >100 nm (N100) were well captured by the model (R2≥0.8) and the normalised mean bias (NMB) was also small (−18% for N50 and −1% for N100). Emission of carbonaceous particles at larger sizes, which we consider to be more realistic for low spatial resolution global models, results in equally good correlation but larger bias (R2≥0.8, NMB = −52% and −29%), which could be partly but not entirely compensated by BL nucleation. Within the uncertainty of the observations and accounting for the uncertainty in the size of emitted primary particles, BL nucleation makes a statistically significant contribution to CCN-sized particles at less than a quarter of the ground sites. Our results show that a major source of uncertainty in CCN-sized particles in polluted European air is the emitted size of primary carbonaceous particles. New information is required not just from direct observations, but also to determine the "effective emission size" and composition of primary particles appropriate for different resolution models.

Most of the existing data on the effective particle size characteristics of fluvial suspended sediment derive from instantaneous sampling methods that may not be representative of the overall suspended sediment loads. This presents difficulties when there is a need to incorporate effective particle size data into numerical models of floodplain sedimentation and sediment‐associated contaminant transfer. We have used a field‐based water elutriation apparatus (WEA) to assemble a large (36 flood) database on the time‐integrated nature of the effective and absolute particle size characteristics of suspended sediment in four subcatchments of the River Exe basin of southwest England. These catchments encompass a wide range of terrains and fluvial environments that are broadly representative of much of the UK and temperate, low relief northwest Europe. The WEA provides important data on the physical characteristics of composite particles that are not attainable using other methods. This dataset has allowed, for the first time, detailed interbasin comparisons of the time‐integrated particle size characteristics of suspended sediment and reliable estimates of the contribution of five effective size classes to the mean annual suspended sediment load of the study catchments. The suspended sediment load of each river is dominated by composite rather than primary particles, with, for example, almost 60% (by mass) of the sediment load of the River Exe at Thorverton transported as composite particles > 16 µm in size. All the effective size classes contain significant clay components. A key outcome of this study is the recognition that each catchment has a distinctive time‐integrated effective particle size signature. In addition, the time‐integrated effective particle size characteristics of the suspended loads in each of the catchments display much greater spatial variability than the equivalent absolute particle size distributions. This indicates that the processes producing composite particles vary significantly between these catchments, and this has important implications for our understanding of the dynamics of suspended sediment properties. Copyright © 2007 John Wiley & Sons, Ltd.

An electrochemical impedance spectroscopy (EIS) has been applied to the investigation of the electrochemical properties of LIB because the time constant related to the electrode/solution interface can be discriminated in impedance spectrum. In the present study, the effect of particle size of the cathode active material on the electrochemical properties of LIB was investigated by in-situ EIS2). The in-situ EIS2) allows for the impedance measurement of the positive electrode, negative electrode, and cell of LIB simultaneously without stopping the measurement of the charge/discharge curve. A three-electrode cell was used for the impedance measurement. An active material of positive electrode was LiCoO2 (LCO) with particle size of 5 μm, 10 μm and 20 μm. The conductive additive and binder of positive electrode were acetylene black (AB) and polyvinylidene fluoride (PVDF), respectively. The positive electrode was fabricated by hand-screen printing. An Al sheet was used as the current collector. In the present study, the theoretical capacity of the positive electrode was calculated from the capacity density of LCO, whose value was defined as 1C-rate. The C-rate denotes the charge/discharge rate, and the 1 C indicates the charge/discharge rate that can fill/empty the total capacity of a battery in an hour. An active material and a current collector of negative electrode were natural spherical graphite and Cu sheet, respectively. A lithium ring was used as the reference electrode (RE), and a mixture of an ethylene carbonate (EC) and an ethyl methyl carbonate (EMC) (3:7 by volume) containing 1 M LiPF6 were used as the electrolyte. After the charge/discharge curve measurement using potentio-galvanostat (sp-50, Bio-Logic), the impedance measurement of the positive electrode during charge/discharge was measured at 1 C by in-situ EIS. The impedance measurement was carried out in the frequency range of 100 mHz to 100 kHz at 5 frequencies per decade with AC amplitude of 10 mV. An electrochemical measurement system (HZ-7000, Hokuto Denko) was used for the measurement. After the charge/discharge curve measurement at 0.3 C, the charge transfer resistance R ct was estimated from the curve fitting of the impedance spectra of the positive electrode during charge/discharge at 1 C using an equivalent circuit. It was confirmed that the R ct value decreased with increasing SOC at each particle size. Comparing the R ct values at each SOC, the R ct values at discharge were larger than that at the charge. This indicates that R ct is varied depending on the direction of current. Furthermore, the R ct values at each particle size during charge and discharge were decreased with decreasing the particle size, demonstrating the increase of the reaction surface area on the cathode active material. On the basis of these results, the diffusion distance of Li ions in the solid phase during charge/discharge was discussed.

Variations of Li chemical diffusion coefficient () with voltage in a series of Co-free Li1+x(Ni0.5Mn0.5)1−xO2, 0 ≤ x ≤ 0.12, materials were systematically investigated using the recently developed “Atlung Method for Intercalant Diffusion”. The effects of primary and secondary particle sizes, excess Li content, heating temperature, and synthesis atmospheres on were measured. Li-ion kinetics can be enhanced by an order of magnitude by lowering the amount of Ni atoms in the Li layers (cation mixing) from 10% to 4%. Decreasing cation mixing can be accomplished by either increasing the excess Li content or heating temperature. When cycled to 4.6 V, higher specific capacities were obtained, but with a penalty to due to transition metal migration to the Li layers. The primary particles control the Li diffusion length in these materials, regardless of the secondary particle size indicating that grain boundary diffusion must be very rapid. The general trends observed in this work are of great value for the development of higher Mn-containing, Co-free materials. It should be possible to increase energy/power density by making large secondary particles, composed of small primary particles to minimize the solid-state diffusion length while maximizing grain boundary diffusion.

Mechanical degradation is one of the most significant mechanisms that affect the cycle life of lithium-ion batteries. Cracks and fractures have been observed in both cathode and anode active material particles, which lead to isolation of active materials, disruption of the electrically conductive network and exposure of fresh surfaces that cause side reactions. These effects significantly reduce the battery capacity and increase the internal resistance. Modeling and simulation are essential to study the generation and effects of stress inside batteries. Treating the intercalation-induced stress analogously to thermal stress, a model has been developed to study the stress and concentration inside a particle. 1 This model has been extended to study various problems at both particle and cell levels. Nevertheless, this model and its extensions are based on the assumption of solid particles. This assumption does not apply for active materials with an agglomerate structure, such as LiNi0.8Co0.15Al0.05O2 (NCA). 2 In these materials, many nanometer-scale primary particles agglomerate to a micrometer-scale secondary particle by the adhesion of binder. The secondary particle is porous rather than a compact solid, as the electrolyte is found to be soaked into the agglomerate. 2 Therefore, charge transfer reactions are expected to occur between the primary particle surface and the electrolyte inside a secondary particle. Although electrochemical models have been developed to investigate the characteristic of an agglomerate accounting for the effects of its internal structure, 3 no mechanical model has been developed to study the stress in agglomerates for lithium-ion batteries. Meanwhile, multiple experiments have reported observations of fracture of agglomerates after cycling, which is a major mechanism of capacity degradation. This calls for a fully understanding of the mechanical behaviors at the agglomerate level. This work presents a coupled mechanical and electrochemical model to predict the intercalation-induced stress in a secondary particle with an agglomerate structure, as shown in Fig. 1. In this model, the electrochemical and transport processes are accounted for at both the secondary and primary particle levels. The porous electrode theory is applied at the secondary particle level, and the solid diffusion is incorporated at the primary particle level. Simulation results from the electrochemical model revealed that a major concentration gradient exists along the radius of the secondary particle, while the concentration is fairly uniform in each primary particle. Based on this finding, the mechanical model focused on the stress generation at the secondary particle level. The secondary particle is assumed to be mechanically homogeneous with effective properties, which can be calculated from the porosity and properties of bulk materials. Because the primary particle is much smaller than the secondary particle, the secondary particle is regarded as a continuum. Each spatial point in the secondary particle is composed of many primary particles at that location. Therefore the stress at each spatial point represents the loading stress exerted on the primary particles at that location. This loading stress is important to know since it is the cause of separation of primary particles, i.e. fracture in the secondary particle. The intercalation-induced stress is calculated using the analogy to thermal stress. The developed model has been applied to investigate factors affecting the stress generation behaviors. The results are summarized as follows: 1) A strong dependence of OCP on the solid lithium concentration leads to a more uniform current density in the secondary particle, which reduces the stress level. 2) A large magnitude of over-potential at the secondary particle surface causes severely non-uniform current density, and thus larger stresses. 3) The primary particle size shows a significant effect on the current density, concentration and stress profiles. A larger primary particle size results in a smaller active surface area per volume, which reduces the impact of non-uniform current density and thus reduces the stress level in the secondary particle. However, the concentration gradient inside the primary particle becomes pronounced with the increase of the primary particle size, which may generate stress inside the primary particle. 4) The comparison between a porous secondary particle and a solid particle of the same size shows that the stress is greatly alleviated in the porous secondary particle. This is attributed to the lower Young’s modulus of the porous particle, and more importantly, to the smaller concentration gradient in the porous secondary particle.

In this work, the influences of the particle size and morphology of raw materials on the formation of MoSi2 by self-propagating high-temperature synthesis (SHS) were investigated. A series of Si powders with different particle sizes and Mo powders with different morphologies were obtained by grinding for 1, 5 and 10 hours, respectively. X-ray diffraction pattern characterization (XRD) and scanning electron microscopy (SEM) were used to characterize the samples. It was found that, the phase compositions and morphologies of the combustion products depended on the particle size and morphology of the raw materials. The particle sizes of Si powders decreased with increasing the grinding time, and a secondary phase of Mo5Si3 was detected in the obtained MoSi2 powders when the smallest particle size of Si powders was about 1μm. While, the particle sizes of Mo powders increased with increasing the grinding times, and the obtained MoSi2 showed massive flaky structures, which were similar to the morphologies of Mo particles.

One way to obtain higher energy densities in lithium-ion batteries is to increase the nickel content in lithium nickel-cobalt-manganese oxide (NCM) cathode active materials (CAMs), ultimately approaching LiNiO2 (LNO). At the same time, a higher nickel content and specific capacity comes with more severe degradation of the CAM during battery cycling. Doping of the CAM with additional elements is a common approach to increase structural stability. For any CAM, comparisons of different dopants with each other and with undoped references are therefore commonly found in the literature.[1,2] In some cases, the effect of different dopants on the CAM particle morphology is also reported.[3,4] However, the influence of the process route of dopant introduction is rarely discussed. The most common ways are either the co-calcination of dopant source, lithium source and CAM precursor (pCAM), or the co-precipitation of dopant ions during pCAM precipitation. Impregnating the pCAM surface with a suspension of smaller dopant particles or a dopant solution, followed by solvent removal, can provide better dopant distribution in case of low dopant ion mobility or phase separation tendencies during calcination.Building on the previous finding that the primary particle morphology is the determining factor of LNO performance,[5,6] in this work, the primary particle morphology, but also dopant distribution in a series of 0.25 mol% Zr-doped LNO obtained from the three different process routes co-calcination, impregnation and co-precipitation, is investigated. This low dopant concentration is common in commercial CAM, as thus the content of redox-active transition metal content remains high to provide maximal energy density. Zr also tends to phase separate in the form of Li2ZrO3 at high concentrations, which is this way avoided as much as possible, since the chosen concentration is below the solubility limit of Zr in the LNO bulk. In this comparison, it is found that not the dopant itself, but the process route of its introduction affects the primary particle morphology of LNO, likely explained by the initial dopant localization early in the calcination.Differences in electrochemical performance, both in coin cells and long-term cycled pouch cells, as well as in specific capacitance and gas evolution are then also found to be due not to the dopant, as one would initially assume in comparisons of doped and undoped materials, but to the effect of the process route on LNO primary particle morphology.

In recent years, solid waste backfill mining has developed rapidly and widely used to control surface subsidence and reduce accumulation of solid waste. As crushed materials are used to backfill goafs, the particle size of backfill materials becomes a key factor influencing the control of surface subsidence. To analyse the influences of particle size of backfill materials on surface subsidence, the compaction properties of crushed gangue backfill materials (CGBM) with different particle sizes were tested by using the YAS5000 testing machine and a self-made compacting device. Moreover, based on the strain hardening behaviour of CGBM in the process of compaction, a method of simulating CGBM using double-yield model was put forward. By employing this method in simulation, the influence of particle size of CGBM on surface subsidence was studied. The research results are demonstrated as follows: with the increase in particle size of the backfill materials, these maximum values such as the maximum surface subsidence, horizontal movement, inclination, curvature, and horizontal deformation increased gradually. Little difference was found in the surface subsidence and movement while using CGBM with particle sizes in the ranges of 2.5–16 and 2.5–50 mm with uniform gradation. However, both values were obviously smaller than those using CGBM with particle sizes of 20–31.5 and 31.5–50 mm. In terms of samples with particle sizes of 2.5–50 mm, the gradation of particles was uniform. By using large particles to form frame structures and small particles to fill fractures, such structures with strong anti-deformation abilities produced a small amount of deformation under the load from overlying strata. Therefore, this structure exerted a good controlling effect on surface deformation.

Lithium- and Manganese-rich (LMR) cathode-oxides are an important class of materials that hold promise for decreasing dependance on critical elements. However, these materials suffer from low solid-phase transport of Li-ions, thereby requiring careful control of synthesis and processing for targeted microstructural design of particles. Synthesis methodology (such as coprecipitation in batch or continuous mode), synthesis conditions (such as precursor chemistry, pH, temperature, stirring rate), calcination conditions (such as temperature, time, atmosphere), and post-synthesis treatments (such as acid leaching, coatings) act in a correlated fashion to determine the primary and secondary particle size, porosity, and microstructure of cathode particles. These morphological features critically impact lithium transport, reaction kinetics, mechanical integrity, and overall electrochemical performance.Computational modeling has proven to be an essential tool for experimentalists in optimizing electrode designs; however conventional battery models do not adequately account for the microstructure of secondary particles or the associated electrolyte diffusion pathways within agglomerate pores. In this regard, an agglomerate model has been developed to address this gap by capturing multiscale lithium diffusion within both electrode pores and primary particles in the agglomerates, allowing accurate estimation of actual battery capacity as a function of important metrics such as discharge rate. Importantly, the agglomerate model acts as a forward model, simulating how combinations of particle sizes and porosity distributions affect the electrochemical performance of cathode materials. For example, an increase in battery capacity is observed for a specific solid fraction distribution, as shown in the abstract figure.In this presentation, optimization techniques will be discussed to show how the energy density of LMRs can be maximized. By identifying the optimal particle size and porosity distributions, the agglomerate model allows performance to be mapped back to specific synthesis conditions using the existing process-morphology-performance learnings. This direct feedback loop allows researchers to go from simulation to synthesis by replacing trial-and-error with logical, performance-driven cathode material design. Figure 1

Evolution of nickel, manganese, and cobalt hydroxide precursor, Ni1/3Mn1/3Co1/3(OH)2, in typical co-precipitation reactions is investigated at different pH levels (i.e. 10.6 and 11.4). The growth of the Ni1/3Mn1/3Co1/3(OH)2 primary and secondary particle is monitored and their particle size distribution revealed different numbers of growth stages for samples prepared at pH 10.6 and pH 11.4. Experimental The experiment is carried out in a 1L CSTR with water bath jacket (60 oC) to synthesize Ni1/3Mn1/3Co1/3(OH)2. The reaction proceeds with the addition of 5.0 M NH3(aq) at 15 mL/h and 2.0 M MSO4 (M = Ni, Co, and/or Mn in desired ratios) at 20 mL/h.(1) A pH meter with feedback to the pump is used to monitor the pH value, and 4.0 M NaOH solution is automatically added to the reaction contents by the pump to maintain the desired pH. Samples are prepared with two solution pH levels of 10.6 and 11.4. An overhead rotator is used to stir the solution, and nitrogen gas continuously bubbled into the solution throughout the synthesis. Sample synthesized in the pH 10.6 solution is referred as sample A, while the one synthesized at the high pH level of 11.4 is referred as sample B. The total reaction time is 3 hrs. Ex-situ samples are drawn from the reactor with pipette during the reaction at certain timer intervals. These samples are immediately diluted in vials to avoid further co-precipitation reaction before characterizing their particle size distribution using particle size analyzer (Cilas 1190LD, Cilas Particle Size). Results and Discussion Our analysis focuses on the growth kinetics of the hydroxide primary and secondary particles. Figure 1 (black-square line) shows the change in the median particle size of sample A as a function of reaction time. The secondary particle grows from 1.5 to 16 µm in 3 hours. Three stages of particle growth could be observed: (I) growth and agglomeration of primary particles (before 45 mins); (II) mixed stage (45~100 mins); and (III) surface smoothing of secondary particles (after 100 mins). In stage I, primary particles are formed through instant nucleation, growth, and agglomeration after the addition of transition metal sources. The growth rate is as high as 11.0 µm/h, which is due to the immediate agglomeration of newly formed primary particles, decreasing their surface energy. In contrast, the growth rate of the particles dropped significantly to 0.9 µm/h in stage III. During this stage, the newly added transition metal ions form smooth layers in the void space of the secondary particles surfaces, which consists of disordered nanoplates. This could be proven by the SEM images (not shown here). In stage II, the growth rate of the secondary particles is about 3.2 µm/h, representing a mixed effect of stage I and stage III. This suggests that the growth and agglomeration of the primary particles as well as the surface smoothing of the secondary particles occur at the same time. The change in the growth mechanism is directly related to the concentration of total transition metal ions and hydroxide in the reactor. A quick calculation shows the concentration of transition metal is 0.05 M and 0.1 M at the first turning point (1 hour) and second turning point (2 hour), respectively. Also shown in Figure 1 (red-circle line) is the change in the secondary particle size as a function of reaction time for sample B synthesized at pH 11.4. In this case, the secondary particles grow from 1.5 to 8 µm in 3 hours. Unlike sample A, only two stages of particle growth can be observed: (I) growth and agglomeration of primary particle at 5.1 µm/h for reaction time smaller than 40 mins; and (II) surface smoothing of the secondary particles at 0.9 µm/h for longer reaction time. The lack of the mixed stage in sample B indicates the primary particle agglomeration is not taking place on the formed secondary particles after 40 mins. This observation is also supported by the SEM images.. The concentration of transition metal in the reactor at the turning point (i.e. 40 mins) is about 0.03 M. A. van Bommel and J. R. Dahn, Chem Mater, 21, 1500 (2009). Figure 1

Experimental research on particle aggregation behavior in nanorefrigerant–oil mixture

The process of reactive granulation is considered. Sodium carbonate primary particles react with dodecyl‐benzenesulfonic acid droplets to form granules where the active component is an anionic surfactant formed by the reaction. The effect of primary particle size on the maximum binder/solids ratio was systematically investigated and found to be directly proportional to the specific surface area of the primary particles regardless of how this surface area was achieved—whether by monodisperse powders or bimodal powder mixtures. The effect of binder viscosity on the maximum binder capacity has shown a nontrivial behavior: while the maximum binder content increased with increasing binder viscosity for fine primary particles, the opposite trend was observed in the case of coarse primary particles. This behavior was explained by detailed studies of primary particle wetting and binder penetration into particle beds, as well as by microtomography analysis of the internal granule structure. © 2014 American Institute of Chemical Engineers AIChE J, 61: 395–406, 2015