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Distribution of Relaxation Times Based on Lasso Regression: A Tool for High-Resolution Analysis of IMPS Data in Photoelectrochemical Systems.

Authors :
Piccioni A
Vecchi P
Vecchi L
Grandi S
Caramori S
Mazzaro R
Pasquini L
Source :
The journal of physical chemistry. C, Nanomaterials and interfaces [J Phys Chem C Nanomater Interfaces] 2023 Apr 20; Vol. 127 (17), pp. 7957-7964. Date of Electronic Publication: 2023 Apr 20 (Print Publication: 2023).
Publication Year :
2023

Abstract

Intensity-modulated photocurrent spectroscopy (IMPS) has been largely employed in semiconductor characterization for solar energy conversion devices to probe the operando behavior with widely available facilities. However, the implementation of IMPS data analysis to complex structures, whether based on the physical rate constant model (RCM) or the assumption-free distribution of relaxation times (DRT), is generally limited to a semi-quantitative description of the charge carrier kinetics of the system. In this study, a new algorithm for the analysis of IMPS data is developed, providing unprecedented time resolution to the investigation of μs to s charge carrier dynamics in semiconductor-based systems used in photoelectrochemistry and photovoltaics. The algorithm, based on the previously developed DRT analysis, is herein modified with a Lasso regression method and available to the reader free of charge. A validation of this new algorithm is performed on a α-Fe <subscript>2</subscript> O <subscript>3</subscript> photoanode for photoelectrochemical water splitting, identified as a standard platform in the field, highlighting multiple potential-dependent charge transfer paths, otherwise hidden in the conventional IMPS data analysis.<br />Competing Interests: The authors declare no competing financial interest.<br /> (© 2023 The Authors. Published by American Chemical Society.)

Details

Language :
English
ISSN :
1932-7447
Volume :
127
Issue :
17
Database :
MEDLINE
Journal :
The journal of physical chemistry. C, Nanomaterials and interfaces
Publication Type :
Academic Journal
Accession number :
37181327
Full Text :
https://doi.org/10.1021/acs.jpcc.3c00770