Pore Structure Characterization in Carbon Materials

Pore structure in carbon materials underpins performance across catalysis, energy storage and environmental remediation. Carbonaceous substrates, ranging from activated carbons to graphene derivatives, exhibit a hierarchical network of micropores, mesopores and macropores whose dimensions and connectivity govern adsorption capacity, mass transport and surface reactivity. Characterisation techniques have evolved from traditional gas adsorption isotherms, mercury intrusion porosimetry and electron microscopy towards advanced methods such as in situ small-angle scattering, high-resolution adsorption measurements and tomographic imaging. These approaches yield pore size distributions, surface area, pore volume and internal topology. Modelling frameworks based on density functional theory and Monte Carlo simulation translate adsorption data into quantitative metrics, while geometric algorithms—including Voronoi tessellation—provide rigorous definitions of pore geometry. The integration of experimental and computational methods has opened pathways to tailor pore structure for specific applications, such as selective gas capture, supercapacitor electrodes and pollutant removal, with an emphasis on reproducibility and standardisation of measurement protocols.

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Pore Structure Characterization in Carbon Materials publication trend

The graph below shows the total number of articles in pore structure characterization in carbon materials across all publications each year (not limited to Nature Index journals).

Technical terms

Micropore: Pore of width less than 2 nm, crucial for high adsorption capacity.

Mesopore: Pore of width between 2 nm and 50 nm, important for diffusion and transport.

Pore Size Distribution: Quantitative profile of pore volume as a function of pore width.

Density Functional Theory: Modelling approach that interprets adsorption isotherms via statistical mechanics of fluid–solid interactions.

Voronoi tessellation: Spatial partitioning method that calculates pore regions around points to define pore geometry.

References

1. Generalized geometric pore size distribution code GPSD-3D for periodic systems composed of monodisperse spheres. Computer Physics Communications (2024).
2. Voronoi tessellation-based algorithm for determining rigorously defined classical and generalized geometric pore size distributions. Physical Review E (2023).
3. A Grand Canonical Monte Carlo Simulation for the Evaluation of Pore Size Distribution of Nuclear-Grade Graphite from Kr Adsorption Isotherms. C – Journal of Carbon Research (2023).