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

超润滑，一种超低摩擦的状态，将有助于显著减少与摩擦相关的能量损失和任何移动机械设备的设备故障。考虑到这类设备小型化的趋势，在原子尺度上研究机械性能变得越来越重要。开发具有超润滑性的纳米级器件需要详细了解原子尺度上控制动态滑动摩擦的基本原理。在这个尺度上，特别是在原子光滑的表面上，摩擦是由电子和声子激发控制的，这可以看作是调节摩擦的杠杆。这个项目的中心目标是通过计算研究动力摩擦的机制。明确地模拟与界面剪切相关的动态摩擦系数需要开发新的原子模拟工具，其中包括声子和电子摩擦耗散机制。使用这些方法，我们将研究在定义良好的系统中摩擦能量耗散的基本机制。这将提供新的见解，哪些摩擦效应占主导地位的系统和在哪些实验可控的环境条件下。我们的见解和模拟方法将为开发允许切换摩擦“打开”和“关闭”的新系统奠定基础。主持人是计算固态物理、表面化学、电子摩擦建模和机器学习方法方面的专家，这与本提案的研究目标非常吻合。该研究员将把他的研究范围扩展到表面动态过程的模拟，包括非绝热模拟在内的MD模拟和能量耗散。他将进一步了解动态机器学习方法的发展。这将提升他未来塑造原子界面工程领域的能力。

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.