Hydrogen peroxide is widely used in everyday life, from disinfectants and medical sterilization to environmental cleanup and manufacturing. Despite its importance, most hydrogen peroxide is still produced using large-scale industrial processes that require considerable energy. So researchers are looking for cleaner alternatives.
A team of researchers has made a breakthrough in this regard, developing a new computational framework to help identify effective catalysts for producing hydrogen peroxide directly from water and electricity. This study focuses on two-electron hydroxylation reactions, an electrochemical process that can produce hydrogen peroxide in a more localized and potentially sustainable way.
As the study's lead author Hao Li outlines, this was no walk in the park. “Designing a catalyst for this reaction has been difficult because catalysts come in many different forms, including metal alloys, metal oxides, and single-atomic materials. Each type has a different atomic structure, making it difficult to compare or predict their performance using a single method.”
To address this problem, Lee and his team developed a new method to describe catalytic active sites at the atomic level. This approach, called a weighted atom-centered symmetry function, captures both the geometric arrangement of atoms and their chemical properties in a unified form. These descriptors were combined with machine learning models and reaction modeling to predict how well different materials would perform.
Using this framework, the team was able to predict key reaction properties across a wide range of catalyst types. This prediction is in close agreement with the results of detailed quantum mechanical calculations and with previously reported experimental data, indicating that this approach can be applied to a variety of materials.
The researchers then used this model to rapidly screen potential catalysts and identified lithium scandium oxide (LiScO₂) as a promising candidate. Experiments confirmed that the material can produce hydrogen peroxide with approximately 90% efficiency and remains stable for nearly a week of continuous operation.
“This framework allows us to directly link atomic-scale information to measurable performance,” Li adds. “It helps reduce trial and error in catalyst development and makes the exploration process more systematic.”
The framework is implemented as follows. Digital catalyst platform (the largest experimental + computational catalyst database to date with a digital platform for users, developed by Hao Li Lab) can be used to efficiently predict reaction properties. The method processes different types of materials in a consistent manner and can be extended beyond the production of hydrogen peroxide.
The researchers expect this approach to support the design of catalysts for other important electrochemical reactions and contribute to cleaner chemical production and energy technologies in the future.
- Publication details:
title: A universal catalyst design framework for electrochemical hydrogen peroxide synthesis facilitated by local atomic environmental descriptors
author: Zhijian Liu, Yan Liu, Yuqi Zhang, Yeyu Deng, Zhong Zheng, Ruth Knibbe, Tianxiang Gao, Mingzhe Li, Ziye Wang, Bingqian Zhang, Xue Jia, Di Zhang, Heng Liu, Xuqiang Shao, Zhengyang Gao, Li Wei, Hao Li, and Weijie Yang.
journal: Angewante Chemie International Edition
Doi: 10.1002/anie.202518027
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