基于数据驱动的钙钛矿光催化材料设计
21世纪，日益增长的能源需求和随之而来的环境污染是全球面临的两大关键挑战。为应对能源危机并保护地球，太阳能因其丰富性、可再生性和可持续性，成为极具吸引力的解决方案。利用光催化反应将太阳能转化为化学能是一种前景广阔的方法，可用于生产氢气或一氧化碳等清洁燃料、通过光降解污染物实现水净化、杀灭细菌以及绿色合成关键工业前体化合物等。钙钛矿材料因其多样的组成和结构特性，在光催化领域展现出巨大潜力。然而，其工业应用常受限于较低的量子效率和稳定性。为了克服这些挑战，迫切需要开发高效、稳定、适用于工业应用的钙钛矿基光催化剂。
本博士项目旨在通过整合机器学习与实验技术，开发新型钙钛矿光催化材料。研究生将在计算化学和机器学习模型的辅助下，通过实验调控钙钛矿材料的化学组成和形貌，以提升特定光催化性能。这一研究方法将加深对结构和元素改性如何影响光催化性能的理解，为钙钛矿基催化材料的发展提供重要的科学依据。
Data-Driven Design of Perovskites for Photocatalytic Applications
The growing demand for energy and the accompanying environmental pollution are two critical challenges we face in the 21st century. To address the energy crisis while protecting the planet, solar energy offers a compelling solution due to its abundance, renewability, and sustainability. One promising approach to harness solar energy is through photocatalytic reactions, which convert sunlight into chemical energy for various applications, such as producing hydrogen or carbon monoxide as clean fuels, purifying water through photodegradation of pollutants, inactivating bacteria, and enabling green synthesis of critical industrial precursors. Perovskites, with their versatile compositions and structural diversity, have shown great potential in photocatalysis. However, their industrial application is often hindered by low quantum efficiency and instability. To overcome these challenges, the development and optimization of highly efficient and stable perovskite-based photocatalysts tailored for industrial applications are urgently needed.
This PhD project aims to develop novel perovskite-based photocatalysts by integrating machine learning and experimental techniques. The student will carry out experiments to tune the chemical composition and morphology of perovskite materials to enhance specific photocatalytic activities, assisted by computational chemistry and machine learning models. This approach will deepen our understanding of how structural and elemental modifications influence photocatalytic performance, providing valuable insights for advancing perovskite-based catalysis.
Dr Haoxin Mai: Haoxin Mai received his MSc degree in Information Technology and Computer Science from the University of Technology Sydney, and PhD degree in Materials Chemistry from the Research School of Chemistry at the Australian National University in 2020. He has worked at the Royal Melbourne Institute of Technology (RMIT) University as a research fellow from 2020. His research interests include perovskite photocatalysis and photoluminescence, ferroelectric thin films, controllable synthesis of inorganic colloid nanocrystals and computational modelling. His research is highly interdisciplinary, combining materials chemistry, nanotechnology, surface/interface science with computation chemistry and machine learning techniques to solve photocataltyic and optoelectronic problems. Dr. Mai has published 20 lead-authored papers in prestigious journals such as Chem. Rev., Chem. Soc. Rev.,J. Am. Chem. Soc., Angew. Chem., Mater. Today, and Adv. Sci., with >5600 citations. He also serves as a regular reviewer for leading journals, including Angew. Chem., Nat. Comm., Nat. Chem., and Adv. Funct. Mater..
Prof. Rachel Caruso: Rachel Caruso is a materials chemist and has expertise in advanced porous materials. She has led teams of scientists at the Max Planck Institute of Colloids and Interfaces, The University of Melbourne, the Commonwealth Scientific and Industrial Research Organisation and RMIT University. Her research interests include materials such as porous oxides, perovskites and carbon materials for energy and environmental applications. She is currently the Director of the Advanced Materials Enabling Capability Platform at RMIT University. Her research has resulted in 177 peer-reviewed publications and five book chapters. According to SciVal, 31% of her publications in the period 2014-2023 appear in the top 10% most cited publications worldwide and 82% appear in the top 10% ranking journals in their field. Her publications have received over 17,900 citations, with 38 manuscripts receiving over 100 citations each. She has an h-index of 62, which attests to the high impact of the body of research and its acceptance by experts in the field.
The deadline for submitting an application that would guarantee full consideration is Dec. 1st, 2025. Applicants should have earned a B.S. or M.S degree upon chemistry. The PhD candidate should have a strong interest in materials chemistry, good understanding of crystal structure, as well as wet-laboratory skills. Candidates having knowledge about theoretical computations and modelling will be highly preferred. All PhD students will receive full financial aid including tuition, competitive stipend, and benefits. Interested students please apply to the graduate school directly (https://www.rmit.edu.au/study-with-us/levels-of-study/research-programs/phd/phd-applied-chemistry-dr229). Inquiries should be addressed to Haoxin Mai (haoxin.mai@rmit.edu.au).
请有意申请的同学将个人简历发送至haoxin.mai@rmit.edu.au
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