Borophene, a monolayer of boron, has risen as a new exciting two-dimensional (2D)
material having extraordinary properties, including anisotropic metallic behavior and flexible …

Wearable sensors in healthcare monitoring have recently found widespread applications in
biomedical fields for their non-or minimal-invasive, user-friendly and easy-accessible …

Borophene stands out uniquely among Xenes with its metallic character, Dirac nature,
exceptional electron mobility, thermal conductivity, and Young's moduli—surpassing …

Poor selectivity is a common problem faced by gas sensors. In particular, the contribution of
each gas cannot be reasonably distributed when a binary mixture gas is co-adsorbed. In this …

Since the birth of the concept of machine learning interatomic potentials (MLIPs) in 2007, a
growing interest has been developed in the replacement of empirical interatomic potentials …

With the growing interest in the field of artificial materials, more advanced and sophisticated
functionalities are required from phononic crystals and acoustic metamaterials. This implies …

Abstract Machine learning (ML) exhibits substantial potential for predicting the properties of
solid‐state electrolytes (SSEs). By integrating experimental or/and simulation data within ML …

The prediction of optical properties dominated by light scattering in particulate media
composed of high-concentration and polydisperse particles is greatly important in various …

Machine learning interatomic potentials (MLIPs) are one of the main techniques in the
materials science toolbox, able to bridge ab initio accuracy with the computational efficiency …

The inherent discontinuity and unique dimensional attributes of nanomaterial surfaces and
interfaces bestow them with various exceptional properties. These properties, however, also …