Graphite is the most widely used anode material in lithium-ion batteries because of its stability, conductivity, and ability to reversibly store lithium ions. However, graphite performance can vary significantly depending on particle morphology, surface area, density, porosity, and crystal structure. These differences directly influence critical battery characteristics including irreversible capacity loss, cycling stability, volumetric energy density, slurry processing behavior, and fast-charging capability.
As battery manufacturers continue to optimize materials for electric vehicles and next-generation energy storage systems, accurately characterizing graphite materials has become increasingly important. Single analytical techniques alone are often insufficient to fully understand graphite behavior, particularly when subtle surface and structural differences can strongly affect electrochemical performance.
This application note demonstrates how orthogonal analytical methodologies can be combined to provide a more complete understanding of graphite anode materials. Using complementary techniques including particle sizing, automated imaging, gas adsorption, density analysis, and X-ray diffraction, two natural graphite samples were evaluated and compared.
The study highlights how spheroidized graphite materials can exhibit smoother particle morphology, lower surface area, higher packing density, and more ordered crystal structures, all of which may contribute to improved cycling durability and higher volumetric energy density. In contrast, graphite materials with smaller particles, rougher surfaces, and higher defect concentrations may offer different performance advantages such as improved lithium-ion diffusion and fast-charging behavior, while also increasing the likelihood of side reactions with electrolytes.
By correlating particle size distribution, morphology, BET surface area, TAP density, adsorption energy, and crystallographic phase information, researchers can develop a multidimensional understanding of graphite suitability for different battery applications. This approach also supports material qualification, process optimization, and quality control workflows across battery R&D and manufacturing environments.
The analytical workflow presented in this study combines technologies including the Mastersizer 3000+, Morphologi 4, TriStar, GeoPyc, AccuPyc, and Aeris XRD to build a comprehensive graphite characterization strategy for lithium-ion battery research.
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Graphite has long been the dominant anode material in commercial lithium-ion batteries due to its favorable electrochemical stability, layered structure, and ability to intercalate lithium ions reversibly. However, the suitability of graphite as an anode depends on a range of structural, chemical, and electrochemical characteristics that can vary significantly with synthesis methods, precursor materials, and processing conditions. Quantifying these characteristics requires analytical approaches that capture different and complementary aspects of graphite performance. Quantifying graphite suitability as an anode material through orthogonal methodologies provides a more rigorous alternative, moving beyond singular data points to a multidimensional validation strategy.
In this case study, we demonstrate that by integrating independent, orthogonal technologies, such as pairing X-ray diffraction with gas adsorption, particle size and shape, and density measurements, researchers can unlock a robust framework for assessing graphite quality and predicting its behavior in battery systems. By integrating multiple independent metrics, this approach enables a more comprehensive evaluation of graphite’s suitability as an anode material, reducing bias from single-method assessments and improving the reliability of material selection for high-performance energy storage applications.
In this case study, two graphite samples were analyzed: a spheroidized natural graphite sample, Gr_Smp1, and a non-spheroidized natural graphite sample, Gr_Smp2.
The particle size distribution of these samples, measured with the Mastersizer 3000+ laser diffraction system, is shown in Figure 1. D50 in Gr_Smp1 is 17.6 µm compared to 4.61 µm in Gr_Smp2.
| Sample name | Dx (10) (µm) | Dx (50) (µm) | Dx (90) (µm) |
|---|---|---|---|
| Gr_Smp1 | 10.6 | 17.6 | 29.1 |
| Gr_Smp2 | 1.97 | 4.61 | 9.12 |
The density of these samples was measured using an AccuPyc gas pycnometer. The surface area, Sp, contributed by particle size distribution alone, was estimated from particle size distribution and material density.
| Sample name | Density (g/cc) | Sp (m²/g) |
|---|---|---|
| Gr_Smp1 | 2.229 | 0.16 |
| Gr_Smp2 | 2.309 | 0.78 |
Due to the small particle size, the surface area in Gr_Smp2 is much larger. Surface area is a parameter of high interest in electrode materials. On one hand, it facilitates Li ion flow; on the other, it can contribute to material degradation through reaction with the electrolyte. In addition to particle size and shape, two more factors contribute to the surface area: porosity and surface roughness.
TriStar is a high-end instrument that can measure not only the total surface area, but also the presence of pores in the range 0.3 nm to 300 nm, using multiple gas adsorption isotherms. 3Flex takes this performance to the next level due to the availability of low-pressure ports down to 10-9 bar. The N2 adsorption and desorption isotherms measured on the two graphite samples are shown in Figure 2.
These isotherms reveal the absence of micro- and meso-pores in these materials. However, St, the total BET surface area, is vastly different in the two materials.
| Sample name | Sp (m²/g), MS3000+ and AccuPyc | St (m²/g), TriStar/3Flex | Porosity, TriStar/3Flex + AutoPore |
|---|---|---|---|
| Gr_Smp1 | 0.16 | 1.98 | Non-porous |
| Gr_Smp2 | 0.78 | 12.96 | Non-porous |
As the particles are non-porous, the difference between the total surface area and the surface area from particle size alone is due to either irregular particle shape or surface roughness. There is a direct correlation between BET surface area and irreversible capacity loss upon the first cycle. The low value in Gr_Smp1 indicates much lower irreversible capacity loss.
Optical imaging using Morphologi 4 provides a fast and straightforward way of measuring particle shape irregularity. The measured particle images and calculated HS circularity of the two samples are shown in Figure 3.
The mean HS circularity in Gr_Smp1 is 0.91, and in Gr_Smp2 it is 0.86, where an HS circularity of 1 means a perfect sphere. High HS circularity (≥ 0.9) in Gr_Smp1 would mean better tap density and lower viscosity in electrode slurries, allowing for more consistent coatings.
For 3D particles, HS circularity is a close approximation for sphericity. Thus, the surface area of irregular particle shape can be estimated by dividing the surface area of spherical particles, estimated with Mastersizer 3000+ and AccuPyc, by the mean HS circularity. The corresponding surface area for the two samples is 0.18 m²/g and 0.91 m²/g. Therefore, the total surface area measured with gas adsorption cannot be explained by particle size and shape alone. In the absence of porosity, a significant contribution to surface area should come from surface roughness.
Graphite primary particles have flake-like morphology, and spheroidized secondary particles may inherit roughness caused by agglomeration. Data from automated imaging using Morphologi 4 can also be analyzed to measure particle solidity, a parameter that closely describes surface roughness. A solidity value of 1 means a smooth spherical particle, and lower values correspond to surface roughness and irregularities. Measured solidity in Gr_Smp2 was lower compared to Gr_Smp1, meaning Gr_Smp2 has higher surface roughness.
Another parameter that bears the combined effect of particle size, shape, and roughness is tap density. More circular and larger particles usually lead to higher tap density, which also results in higher energy density. Tap density measurements were carried out using GeoPyc.
| Sample name | D50 (µm), Mastersizer 3000+ | HS circularity, Morphologi 4 | Solidity, Morphologi 4 | Tap density (g/cc), GeoPyc |
|---|---|---|---|---|
| Gr_Smp1 | 17.6 | 0.91 | 0.980 | 1.1628 |
| Gr_Smp2 | 4.61 | 0.86 | 0.965 | 0.4000 |
Crystal phase purity and crystal plane orientation often play an important role in battery cell performance. To investigate the crystal phases, these samples were measured on an Aeris compact XRD system. Both samples showed the presence of both 2H and 3R crystal modifications. As shown in Figure 4, Rietveld refinement reveals a low 3R phase (10.5%) in Gr_Smp1 and a high 3R phase (45%) in Gr_Smp2.
The presence of 3R phases in these samples shows that they are natural graphite, as synthetic graphite usually contains only the 2H phase. High 3R content in Gr_Smp2 is typical of milled and disordered crystalline material.
Good graphite anode materials for lithium-ion batteries are optimized by balancing basal planes, which are low reactivity and stable, and prismatic edge planes, which are high reactivity and support fast lithium diffusion, to maximize capacity and minimize irreversible capacity loss. High-performance graphite tends to have a higher proportion of basal plane surfaces to limit edge-initiated side reactions, with the ratio of basal to edge planes typically favoring the basal plane heavily. Likewise, graphite anodes with significant disorder or amorphous regions have numerous defects that are more susceptible to interaction with the electrolyte, leading to faster degradation. Therefore, low BET surface area is important, but having a high basal-to-prismatic plane ratio and low surface defects is even more important.
XRD can also be used to investigate crystal plane orientation. However, XRD is a bulk technique and is not sensitive to the surface. In this case study, surface adsorption energy was used to differentiate crystal plane orientation. The known typical adsorption energies are:
The adsorption energy plot shows that the surface of Gr_Smp1 mainly consists of basal planes, whereas prismatic planes and defects constitute the surface of Gr_Smp2.
| Parameter | Instrument used | Gr_Smp1 | Gr_Smp2 | Comment |
|---|---|---|---|---|
| Particle size (D50 µm) | Mastersizer 3000+ | 17.6 | 4.61 | Gr_Smp1 has smoother and spheroidized particles, which are good for dispersion, coating, and cycling stability. |
| HS circularity | Morphologi 4 | 0.91 | 0.86 | Higher circularity in Gr_Smp1 supports better tap density and coating consistency. |
| Solidity | Morphologi 4 | 0.980 | 0.965 | Lower solidity in Gr_Smp2 indicates higher roughness and irregularity. |
| Density (g/cc) | AccuPyc | 2.229 | 2.309 | True density supports surface area and material characterization calculations. |
| Surface area (m²/g) combining particle size, shape, and density | Mastersizer 3000+, Morphologi 4, AccuPyc | 0.18 | 0.91 | Gr_Smp1 would have lower irreversible capacity loss due to low surface area. |
| BET total surface area (m²/g) | TriStar | 1.98 | 12.96 | Higher BET surface area in Gr_Smp2 suggests greater reactivity with electrolyte. |
| Tap density (g/cc) | GeoPyc | 1.163 | 0.40 | High tap density in Gr_Smp1 leads to high volumetric energy density. |
| Crystal phases | Aeris XRD | 3R 10.5%; 2H 89.5% | 3R 45%; 2H 55% | The 3R phase is higher when the sample is milled and disordered. |
| Crystal plane on particle surface | TriStar | Mainly basal | Mainly prismatic and defects | Basal planes improve cycling durability by reducing electrolyte erosion. |
These investigations show that Gr_Smp1 has spheroidized large particles with low surface area, predominantly 2H crystal phase, and basal planes on the particle surface. Low surface area and basal surface planes make this material robust against electrolyte degradation. This anode material is suitable for high-energy-density battery applications, such as electric vehicles. Gr_Smp2, on the other hand, has small particles with a higher surface area and a significant 3R crystal phase. A small particle size makes it suitable for applications where rapid charging is a key requirement, at the expense of long-term cycling durability.
Particle size, particle morphology such as circularity and roughness, crystalline phase, true and tap density, surface area, and surface structure play an important role in qualifying graphite anode materials for manufacturing high-performance batteries. Malvern Panalytical offers interconnected orthogonal analytical solutions that can be used at both R&D and quality control scales for the in-depth investigation of these materials to evaluate their suitability for making high-quality electrodes for lithium-ion batteries.