In Silico Demonstration of Fast Anhydrous Proton Conduction on Graphanol.

ABSTRACT: Development of new materials capable of conducting protons in the absence of water is crucial for improving the performance, reducing the cost, and extending the operating conditions for proton exchange membrane fuel cells. We present detailed atomistic simulations showing that graphanol (hydroxylated graphane) will conduct protons anhydrously with very low diffusion barriers. We developed a deep learning potential (DP) for graphanol that has near-density functional theory accuracy but requires a very small fraction of the computational cost. We used our DP to calculate proton self-diffusion coefficients as a function of temperature, to estimate the overall barrier to proton diffusion, and to characterize the impact of thermal fluctuations as a function of system size. We propose and test

SUBMITTER: Achar SK 

PROVIDER: S-EPMC10236431 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature