We present LayerPCM, an extension of the polarizable-continuum model coupled to real-time time-dependent density-functional theory for an efficient and accurate description of the electrostatic interactions between molecules and multilayered dielectric substrates on which they are physisorbed. The former are modelled quantum-mechanically, while the latter are treated as polarizable continua characterized by their dielectric constants. The proposed approach is purposely designed to simulate complex hybrid heterostructures, with nano-engineered substrates including a stack of anisotropic layers. LayerPCM is suitable to describe the polarization-induced renormalization of frontier energy levels of the adsorbates in the static regime. Moreover, it can be reliably applied to simulating laser-induced ultrafast dynamics of the molecules through the inclusion of electric fields generated by Fresnel-reflection at the substrate. Depending on the complexity of the underlying layer structure, such reflected fields can assume non-trivial shapes and profoundly affect the dynamics of the photo-excited charge carriers in the molecule. In particular, the interaction with the substrate can give rise to strong delayed fields which lead to interference effects resembling those of multi-pulse-based spectroscopy. The robustness of the implementation and the above-mentioned features are demonstrated with a number of examples, ranging from intuitive models to realistic systems.
Angularly Selective Enhanced Vortex Screening in Extremely Layered Superconductors with Tilted Columnar Defects
Low Temperatures Lab, Centro Atómico Bariloche, CNEA（低温实验室，巴里洛切原子中心，国家原子能委员会）；Instituto de Nanociencia y Nanotecnología, CONICET-CNEA, Nodo Bariloche（纳米科学与技术研究所，CONICET-CNEA，巴里洛切节点）；Instituto Balseiro, CNEA and Universidad Nacional de Cuyo（巴尔塞罗研究所，国家原子能委员会和库约国立大学）；Neutrons Beam National Lab, CNEA（中子束国家实验室，国家原子能委员会）；Vmnetic SAS；Laboratoire des Solides Irradiés, CEA/DRF/IRAMIS, École Polytechnique, CNRS, Institut Polytechnique de Paris（辐照固体实验室，CEA/DRF/IRAMIS，巴黎综合理工学院，CNRS，巴黎理工学院）
Impressive computational acceleration by using machine learning for 2-dimensional super-lubricant materials discovery
University of Technology Sydney（悉尼科技大学）；University of North Carolina（北卡罗来纳大学）；Commonwealth Scientific and Industrial Research Organization（澳大利亚联邦科学与工业研究组织）；Monash University（莫纳什大学）；La Trobe University（拉筹伯大学）；The University of Nottingham（诺丁汉大学）；The University of Queensland（昆士兰大学）；Flinders University（弗林德斯大学）
