Materials Science
Universal machine-learning interatomic potentials (uMLIPs) have become powerful tools for accelerating computational materials discovery by replacing expensive first-principles calculations in crystal structure prediction (CSP). However,…
Electron chirality has been proposed as a microscopic quantity that characterizes electronic handedness, yet its underlying control parameter has not been clearly identified. Furthermore, its applicability is limited to systems with…
Lateral heterostructures of 2D transition metal dichalcogenide offer a powerful platform to investigate photonic and electronic phenomena at atomically sharp interfaces. However, their controlled engineering, including tuning lateral domain…
The coupling of atomic vibrations to electronic excitations - traditionally understood to be a source of energy loss in semiconductors - has recently been explored in photosynthetic light harvesting as a means to circumvent dissipation by…
Over the past few decades, thin-film optoelectronic devices have shown significant advancements. Light-emitting diodes (LEDs) based on organic materials, polymers, quantum dots, as well as metal halide perovskites have achieved remarkable…
Magnetoelastic coupling in van der Waals (vdW) magnetic materials enables a unique interplay between the spin and lattice degrees of freedom. Characterizing the elastic responses with atomic and femtosecond resolution across the magnetic…
Topological kagome magnets offer a rich landscape for exploring the intricate interplay of quantum interactions among geometry, topology, spin, and correlation. GdTi3Bi4 crystallizes in layered Ti based kagome nets intertwined with zigzag…
Understanding electrical resistivity in metals remains a central challenge in quantifying charge transport at finite temperature. Current first-principles calculations based on the Boltzmann transport equation often match experiments, yet…
Phase-change materials (PCMs) based on group IV, V, and VI elements, such as Ge, Sb, and Te, exhibit distinctive liquid-state features, including thermodynamic anomalies and unusual dynamical properties, which are believed to play a key…
Kagome metals are an intriguing class of quantum materials as the presence of both flat bands and Dirac points provides access to functional properties present in strongly correlated and topological materials. To fully harness these…
Ferroelectricity in perovskites is known to be suppressed by a moderate hydrostatic pressure. The notion that a polar instability should reappear in a higher pressure regime is well accepted theoretically but experiments have failed so far…
Ensuring the trustworthiness and robustness of deep learning models remains a fundamental challenge, particularly in high-stakes scientific applications. In this study, we present a framework called attention-guided training that combines…
Disorder significantly impacts the electronic properties of conducting quantum materials by inducing electron localization and thus altering the local density of states and electric transport. In insulating quantum magnetic materials, the…
Altermagnets, combining zero net magnetization with intrinsic spin splitting, demonstrate unique quantum phenomena crucial for spintronic applications. KV$_2$Se$_2$O is proven to be a d-wave altermagnet with phase transition from a…
Time-resolved photoconductivity is widely used to characterize non-equilibrium charge-carrier lifetime, impurity content, and solar cell efficiency in a broad range of semiconductors. Most measurements are limited to the detection of…
Grain boundary (GB) migration governs microstructure evolution and can mediate plastic deformation through sliding or shear coupling. Numerous experimental and numerical studies have reported a wide range of behaviors associated with…
Spin defects in two-dimensional materials hold significant potential for quantum information technologies and sensing applications. The negatively charged boron vacancy (VB-) in hexagonal boron nitride (hBN) has attracted considerable…
Machine learned interatomic potentials (MLIPs) are becoming a standard method for DFT-level accurate molecular dynamics simulation and large-scale studies of crystal energetics. Increasingly popular are universal pre-trained potentials,…
Central to interatomic potential efficiency is the radial envelope function that enables linear scaling with computational cost by defining a local neighborhood of atoms. This has enabled MLIPs to revolutionize materials science over the…
Engineering optical properties, such as luminescence purity and charge transfer, is crucial for harnessing the application potential of atomically thin transition metal dichalcogenides (TMDCs). While electrostatic gating is widely applied…