A neural network-based approach to predicting absorption in nanostructured, disordered photoelectrodes

by Coridan, Robert H.

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Disordered nanostructures in photoelectrodes can increase light absorption in photoelectrochemical system designs. Predicting their optical properties is an elusive task due to the immensity of unique configurations and the intrinsic variance of each. A neural network trained from a small subset of simulations can emulate the complex absorption properties of the entire configuration space for a model disordered system with quantifiable accuracy and computational efficiency.

Journal
Chemical Communications
Volume
56
Issue
72
Year
2020
Start Page
10473
ISBN/ISSN
1359-7345; 1364-548X
PMID
32756676
DOI
10.1039/d0cc04229c