Closed‐Loop Multi‐Objective Optimization for Cu–Sb–S Photo‐Electrocatalytic Materials’ Discovery

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Closed‐Loop Multi‐Objective Optimization for Cu–Sb–S Photo‐Electrocatalytic Materials’ Discovery
Title:
Closed‐Loop Multi‐Objective Optimization for Cu–Sb–S Photo‐Electrocatalytic Materials’ Discovery
Journal Title:
Advanced Materials
Publication Date:
10 September 2023
Citation:
Bai, Y., Khoo, Z. H. J., I Made, R., Xie, H., Lim, C. Y. J., Handoko, A. D., Chellappan, V., Cheng, J. J., Wei, F., Lim, Y., & Hippalgaonkar, K. (2023). Closed‐Loop Multi‐Objective Optimization for Cu–Sb–S Photo‐Electrocatalytic Materials’ Discovery. Advanced Materials, 36(2). Portico. https://doi.org/10.1002/adma.202304269
Abstract:
Copper antimony sulfides are regarded as promising catalysts for photo‐electrochemical water splitting because of their earth abundance and broad light absorption. The unique photoactivity of copper antimony sulfides is dependent on their various crystalline structures and atomic compositions. Here, a closed‐loop workflow is built, which explores Cu–Sb–S compositional space to optimize its photo‐electrocatalytic hydrogen evolution from water, by integrating a high‐throughput robotic platform, characterization techniques, and machine learning (ML) optimization workflow. The multi‐objective optimization model discovers optimum experimental conditions after only nine cycles of integrated experiments–machine learning loop. Photocurrent testing at 0 V versus reversible hydrogen electrode (RHE) confirms the expected correlation between the materials’ properties and photocurrent. An optimum photocurrent of −186 µA cm−2 is observed on Cu–Sb–S in the ratio of 9:45:46 in the form of single‐layer coating on F‐doped SnO2 (FTO) glass with a corresponding bandgap of 1.85 eV and 63.2% Cu1+/Cu species content. The targeted intelligent search reveals a nonobvious CuSbS composition that exhibits 2.3 times greater activity than baseline results from random sampling.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the Agency for Science, Technology and Research - Advanced Manufacturing and Engineering Programmatic Fund, Accelerated Materials Development for Manufacturing Program
Grant Reference no. : A1898b0043

This research / project is supported by the Agency for Science, Technology and Research - Advanced Manufacturing and Engineering Industry Alignment Fund - Pre-Positioning
Grant Reference no. : A19E9a0103
Description:
ISSN:
0935-9648
1521-4095
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