Mesopore-dominant nitrogen-doped carbon with a large defect degree and high conductivity via inherent hydroxyapatite-induced self-activation for lithium-ion batteries

Biomass derived hierarchical porous carbon for high-performance O2/N2 adsorption; a new green self-activation approach

Biomass-derived porous carbons are the most common adsorbent materials for O₂/N₂ adsorption because of their excellent textural properties, high surface area, and low expense. A new synthesis method based on a self-activation technique was developed for a new green porous carbon adsorbent. This ecofriendly system was used for the synthesis of hierarchical porous carbons from walnut-shell precursors. The sorbent was successfully synthesized by facile one-step carbonization, with the activating reagents being gases released during the activation. The sample morphology and structure were characterized by field emission scanning electron microscopy, high-resolution transmission electron microscopy, Raman, Fourier transform infrared spectra, X-ray photoelectron spectroscopy, X-ray powder diffraction, thermogravimetric, and differential thermal analysis. The optimal porous carbons were synthesized at 1000 °C, providing a surface area as high as 2042.4 (m² g⁻¹) and micropore volume of about 0.499 (m³ g⁻¹). At 298 °K under 9.5 bar pressure, the potential for O₂/N₂ separation using porous carbon samples was studied, and the sips isotherms with the highest adsorption potential were determined to be 2.94 (mmol g⁻¹) and 2.67 (mmol g⁻¹), respectively. The sample exhibited stable O₂/N₂ separation over ten cycles, showing high reusability for air separation. Finally, the technology described presents a promising strategy for producing eco-friendly porous carbon from a variety of biomass on an industrial scale.

Green porous carbon was synthesized by self-activation methodology with facile one-step carbonization from a walnut-shell precursor for air separation. The adsorption process behavior was surveyed using isotherm, kinetic and thermodynamic models.