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澳大利亚墨尔本皇家理工大学Rachel Caruso组招 光催化方向 全额奖学金 博士研究生
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water splitting photocatalysts ╟ where machine learning meets experiment our ever-increasing need for energy and its associated environmental pollution are two pressing problems that we face as our population and industrialization increase in the 21st century. to circumvent an energy crisis and maintain an inhabitable planet, solar energy is deemed to be an attractive solution because the sun provides free, renewable, abundant and sustainable energy. a feasible way to transfer solar energy to chemical energy is through photocatalytic reactions, producing hydrogen or carbon monoxide as clean chemical fuels from water or co2 by sunlight, as well as purifying water via photodegradation of pollutants and inactivating bacteria. since the discovery of the photocatalytic properties of tio2 in 1972, more than 140 types of inorganic photocatalysts have been discovered. however, most have low quantum efficiency due to large bandgaps, poor matching of the redox potentials and fast electron-hole recombination. therefore, more effective photocatalysts are required to make solar fuel production and photodegradation commercially viable. conventionally, significant time is required to develop new photocatalysts, including material design, experimental parameter optimization and performance evaluation. with the assistance of materials informatics and artificial intelligence, useful patterns and knowledge can be extracted from the literature and research databases, accelerating the discovery and optimization of new photocatalysts, and allowing experimental resources to be focused on the most promising materials. this phd project will focus on developing and optimizing new photocatalytic materials via machine learning and experimental methods. to conduct this project, the student will learn a range of machine learning modelling skills, along with laboratory-based synthesis and characterization including electron microscopy, x-ray diffraction analysis and gas sorption studies. the student will also work with prof. domen (japan) to test the water splitting quantum efficiency of the photocatalysts. rachel caruso组具有多元化的学术背景, 与众多国际合作者开展多项高质量的科研工作, 截止2021年12月，prof. Rachel Caruso的 谷歌学术总引用次数达 20342，h-index达到63. 根据你博士期间的科研成果,你将会得到机器学习专家david winkler教授指导,或者和光催化专家Kazunari Domen教授合作 联系方式： 请有意者将以下申请材料以pdf格式发送到 dehong.chen@rmit.edu.au 或 haoxin.mai@rmit.edu.au： （1）个人陈述；（2）cv；（3）成绩单 |
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