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Atomic-scale design of superlubricity of carbon nanostructures on metallic substrates

Atomic-scale design of superlubricity of carbon nanostructures on metallic substrates
金属基底上碳纳米结构超润滑性的原子尺度设计
批准号:
EP/Y024923/1
负责人:
Reinhard J. Maurer
金额:
$23.84万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
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英文摘要
Superlubricity, a state of ultra-low friction, will facilitate a significant reduction of friction-related energy loss and device failure of any moving mechanical device. Given the trend towards miniaturisation of such devices, studies of mechanical properties at atomic scales become ever more important. Developing nanoscale devices exhibiting superlubricity requires a detailed understanding of the fundamental principles governing dynamic sliding friction at an atomic scale. At this scale, particularly at atomically smooth surfaces, friction is governed by electronic and phononic excitations, which may be seen as levers to regulate friction. The central aim of this project is to computationally investigate the mechanisms of dynamic friction. Explicitly simulating the dynamic friction coefficient associated with interfacial shear requires the development of new atomistic simulation tools that incorporate phononic and electronic frictional dissipation mechanisms. Using these methods, we will study the fundamental mechanisms of frictional energy dissipation in well-defined systems. This will provide new insights into which frictional effects dominate for which system and under which experimentally controllable environment conditions. Our insights and simulation methods will build the groundwork to develop new systems that allow switching friction "on" and "off". The host is an expert on computational solid-state physics, surface chemistry, modelling of electronic friction and machine learning methods, which ideally aligns with the research goals of this proposal. The researcher will extend his research portfolio to the simulation of dynamic processes at surfaces, MD simulation including non-adiabatic simulations, and energy dissipation. He will further his knowledge on the development of ML methods for dynamics. This will boost his future ability to shape the field of atomistic interface engineering.
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