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

• Published in: Advanced materials (Weinheim) 2024-01, Vol.36 (2), p.e2304269-n/a
• Main Authors: Bai, Yang, Khoo, Zi Hui Jonathan, I Made, Riko, Xie, Huiqing, Lim, Carina Yi Jing, Handoko, Albertus Denny, Chellappan, Vijila, Cheng, Jianwei Jayce, Wei, Fengxia, Lim, Yee‐Fun, Hippalgaonkar, Kedar
• Format: Article
• Language: English
• Subjects: Composition; Copper; Electromagnetic absorption; high‐throughput experiments; Hydrogen evolution; Machine learning; Optimization; Optimization models; Photoelectric effect; Photoelectric emission; photo‐electrochemical water splitting; Random sampling; Sulfides; Tin dioxide; Water splitting; Workflow
• ISSN: 0935-9648; 1521-4095
• DOI: 10.1002/adma.202304269

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. A closed‐loop workflow combining synthesis, deposition, characterization is used to explore Cu–Sb–S oxide films for efficient water reduction. The workflow narrows down optimal conditions for high photo‐electrocatalytic activity by optimizing for proxy objectives, including bandgap, Cu1+/Cu ratio, and film uniformity. This results in the successful identification of an optimal material composition through multi‐objective constrained optimization techniques.