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应助: 0 (幼儿园)
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虫号: 3876134

[交流] 德国柏林亥姆霍兹能源研究中心招收2025年CSC奖学金博士，方向/电催化/XAS/OER

【项目概况】
课题：AI-aided design of operando X-ray absorption studies 或者Benchmarking of electrocatalysts at high current density 二选一
主题：Energy electrocatalysis。
联系方式：Marcel Risch, marcel.risch@helmholtz-berlin.de
套瓷材料要求：个人简历、成绩单、雅思/托福成绩单、研究计划（不强求，有最好）。

老师人很好，学术氛围也非常浓厚，欢迎有相关研究背景的同学申请

Topic 1: AI-aided design of operando X-ray absorption studies
Chemical processes such as electrocatalysis depend on many correlated materials properties, which hampers comprehensive insight and the development of predictive models. X-ray absorption spectroscopy (XAS) is a powerful method to elucidate the electronic structure of electrocatalysts but requires access to synchrotrons, which limits the available experimental time. Consequently, the vast majority of all previous XAS studies have varied no more than one variable of a usually very complex multivariate parameter space of electrocatalytic reactions. This may have led to identification of local rather than global maxima of the performance parameters (activity, stability, selectivity, etc.) of the reaction. In this project, we propose a disruptive approach to improve upon this shortcoming, namely AI-guided Bayesian optimization to treat electrocatalysis as a truly multivariate problem while keeping the needed number of experiments low so that they can be performed during a typical beamtime. The project will focus on the environmental parameters during oxygen electrocatalysis (oxygen evolution and/or oxygen reduction) on state-of-the-art row transition metal electrocatalysts such as NiFe oxides and Pt-based alloys. There will be the opportunity to collaborate on XAS experiments with leading groups.

Requirement:
Background in electrocatalysis, preferably in oxygen electrocatalysis, demonstrated by successful completion of lectures, research stays on these topics and publications in scientific journals
• Background in X-ray spectroscopy, preferably X-ray absorption spectroscopy, demonstrated by successful completion of lectures, research stays on these topics and publications in scientific journals
• Previous experience with Bayesian optimization, other theoretical methods or modelling is a bonus
• Openness to work in an international, interdisciplinary and diverse working environment

TOPIC 2 :Benchmarking of electrocatalysts at high current density
The oxygen evolution reaction (OER) is a key enabler of sustainable chemical energy storage, yet research progress in the past decades is unclear because electrocatalysts were tested by incompatible protocols and at too low current density. In this PhD topic, transition metals will be electrodeposited onto steel mesh as a platform to investigate their electrocatalytic activity for the OER and optionally other oxidizing reactions. In contrast to current literature data, the experiments will be performed in a single cell alkaline electrolyzer. Benchmarking will be facilitated using our NOMAD database and its functions to explore the stored data along defined criteria and metrics for stability and activity. The database also enables AI-guided optimization of the electrodeposition and optimization of the operating conditions. It is expected that the database produced during this PhD project will have high impact on industrial and academic reaserch.

Requirement:
Background in electrocatalysis, preferably in oxygen electrocatalysis, demonstrated by successful completion of lectures, research stays on these topics and publications in scientific journals
• Experience with materials synthesis and materials characterization using electron microscopy, XPS, XRD or spectroscopic methods
• Openness to work in an international, interdisciplinary and diverse working environment

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