Metallic glasses (MGs) have attracted extensive attention in the past decades due to their
unique chemical, physical and mechanical properties promising for a wide range of …

A molecular dynamics study was performed on the mechanical response of thermal-
pressure rejuvenated CuxZr100− x metallic glasses. The effect of temperature (50, 300, 600 …

In this work, a machine learning (ML) model, optimized by genetic algorithm, was
established to predict and characterize the tribological behavior of CuZr metallic glasses …

In the present work, a novel micromechanical data-driven Machine Learning (ML) framework
was proposed to characterize material parameters in bulk metallic glasses (BMGs) using …

The development and implementation of the methods for designing amorphous metal alloys
with desired mechanical properties is one of the most promising areas of modern materials …

This study examines the mechanical performance of various lattice structures, highlighting
the roles of geometric configurations, material properties, and processing conditions …

Utilization of small molecules as passivation materials for perovskite solar cells (PSCs) has
gained significant attention recently, with hundreds of small molecules demonstrating …

Abstract Superelasticity of Ni x Ti 100− x B2 shape memory alloys (SMAs) with different
atomic compositions and void defects are investigated using molecular dynamics …

The field of metallic glasses has been an active area of research owing to the complex
structure–property correlations and intricacies surrounding glass formation and relaxation …

This article introduces an innovative approach that utilizes machine learning (ML) to address
the computational challenges of accurate atomistic simulations in materials science …