This article presents an end-to-end functional bidirectional deep-learning (DL) model for three-dimensional chiral metamaterial design and optimization. This ML model utilizes multitask joint learning features to recognize, generalize, and explore in detail the nontrivial relationship between the metamaterials’ geometry and their chiroptical response, eliminating the need for auxiliary networks or equivalent approaches to stabilize the physically relevant output. This model efficiently realizes both forward and inverse retrieval tasks with great precision, offering a promising tool for iterative computational design tasks in complex physical systems. Other potential applications include photodetectors, polarization-resolved imaging, and circular dichroism (CD) spectroscopy.

Article develops a planar model for an artificially structured boundary that may provide magnetic confinement of nonmagnetically trapped plasma particles.

This article is a response to a comment on the authors' original article "Disentangling Orbital and Valley Hall Effects in Bilayers of Transition Metal Dichalcogenides." The authors' response concludes that they do not believe the main points of the original Letter are affected by the Comment.

Article describes how continuum solvation models are becoming increasingly relevant in condensed matter simulations, allowing to characterize materials interfaces in the presence of wet electrified environments at a reduced computational cost with respect to all atomistic simulations. However, some challenges with the implementation of these models in plane-wave simulation packages still persists, and to address these challenges, the authors present the implementation of a double-cell formalism, in which the simulation cell used for the continuum environment is uncoupled from the one used for the electronic-structure simulation of the quantum-mechanical system.