Issue 24, 2022

Water on porous, nitrogen-containing layered carbon materials: the performance of computational model chemistries

Abstract

Porous, layered materials containing sp2-hybridized carbon and nitrogen atoms, offer through their tunable properties, a versatile route towards tailormade catalysts for electrochemistry and photochemistry. A key molecule interacting with these quasi two-dimensional materials (2DM) is water, and a photo(electro)chemical key reaction catalyzed by them, is water splitting into H2 and O2, with the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) as half reactions. The complexity of some C/N-based 2DM in contact with water raises special needs for their theoretical modelling, which in turn is needed for rational design of C/N-based catalysts. In this work, three classes of C/N-containing porous 2DM with varying pore sizes and C/N ratios, namely graphitic carbon nitride (g-C3N4), C2N, and poly(heptazine imides) (PHI), are studied with various computational methods. We elucidate the performance of different models and model chemistries (the combination of electronic structure method and basis set) for water and water fragment adsorption in the low-coverage regime. Further, properties related to the photo(electro)chemical activity like electrochemical overpotentials, band gaps, and optical excitation energies are in our focus. Specifically, periodic models will be tested vs. cluster models, and density functional theory (DFT) vs. wavefunction theory (WFT). This work serves as a basis for a systematic study of trends for the photo(electro)chemical activity of C/N-containing layered materials as a function of water content, pore size and density.

Graphical abstract: Water on porous, nitrogen-containing layered carbon materials: the performance of computational model chemistries

Article information

Article type
Paper
Submitted
09 2 2022
Accepted
27 4 2022
First published
29 4 2022

Phys. Chem. Chem. Phys., 2022,24, 14709-14726

Water on porous, nitrogen-containing layered carbon materials: the performance of computational model chemistries

C. Penschke, R. E. von Zander, A. Beqiraj, A. Zehle, N. Jahn, R. Neumann and P. Saalfrank, Phys. Chem. Chem. Phys., 2022, 24, 14709 DOI: 10.1039/D2CP00657J

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