相关论文: Synthesizability, hardness, and stacking order in …

Machine learning has emerged as a novel tool for the efficient prediction of materials properties, and claims have been made that machine-learned models for the formation energy of compounds can approach the accuracy of Density Functional…

MAB phases (MABs) are atomically-thin laminates of ceramic/metallic-like layers, having made a breakthrough in the development of 2D materials. Though theoretically offering a vast chemical and phase space, relatively few MABs have yet been…

Intercalation and stacking order modulation are two active ways in manipulating the interlayer interaction of transition metal dichalcogenides (TMDCs), which lead to a variety of emergent phases and allow for engineering material…

Even though thermodynamic energy-based crystal structure prediction (CSP) has revolutionized materials discovery, the energy-driven CSP approaches often struggle to identify experimentally realizable metastable materials synthesized through…

Though offering unprecedented pathways to molecular dynamics (MD) simulations of technologically-relevant materials and conditions, machine-learning interatomic potentials (MLIPs) are typically trained for ``simple'' materials and…

The vastness of the space of possible multicomponent metal alloys is hoped to provide improved structural materials but also challenges traditional, low-throughput materials design efforts. Computational screening could narrow this search…

Newly designed Li-ion battery cathode materials with high capacity and greater flexibility in chemical composition will be critical for the growing electric vehicles market. Cathode structures with cation disorder were once considered…

We present a systematic benchmark of MACE potentials for iron-nickel alloys, focusing on structural, elastic, magnetic, and finite-temperature properties relevant to phase stability. The reference dataset comprises spin-polarized PBE…

Two-dimensional (2D) transition metal carbides and nitrides, known as MXenes, possess unique physical and chemical properties, enabling diverse applications in fields ranging from energy storage to communication, catalysis, sensing,…

Ultra-high temperature ceramics (UHTCs) represent a class of crystalline materials for extreme environments. They can withstand extremely high temperatures but are mechanically difficult to work with due to their inherent brittleness.…

In this paper we develop the stability rules for NASICON structured materials, as an example of compounds with complex bond topology and composition. By applying machine learning to the ab-initio computed phase stability of 3881 potential…

The lithium-carbon binary system possesses a broad range of chemical compounds, which exhibit fascinating chemical bonding characteristics that give rise diverse and technologically important properties. While lithium carbides with various…

The practically unlimited high-dimensional composition space of high-entropy materials (HEMs) has emerged as an exciting platform for functional materials design and discovery. However, the identification of stable and synthesizable HEMs…

We propose an efficient computational methodology for predicting the synthesizability of high entropy oxides (HEOs) in a large space of possible candidate compounds. HEOs are a growing field with an enormous potential chemical composition…

Predicting solid-solid phase transitions remains a long-standing challenge in materials science. Solid-solid transformations underpin a wide range of functional properties critical to energy conversion, information storage, and thermal…

We employ a descriptor based machine-learning approach to assess the effect of chemical alloying on formation-enthalpy of rare-earth intermetallics. Application of machine-learning approaches in rare-earth intermetallic design have been…

The discovery of intrinsic magnetic topological order in $\rm MnBi_2Te_4$ has invigorated the search for materials with coexisting magnetic and topological phases. These multi-order quantum materials are expected to exhibit new topological…

In the present work we detail how the many-body potential energy landscape of interatomic potentials for carbon can be explored by utilising the nested sampling algorithm, allowing the calculation of their pressure-temperature phase diagram…

Layered, hexagonal crystal structures, like zeta and eta phases, play an important role in ultra-high temperature ceramics, often significantly increasing toughness of carbide composites. Despite their importance open questions remain about…

We have systematically studied the mechanical stability of all noble metal carbides with the rock-salt structure by calculating their elastic constants within the density function theory scheme. It was found that only four carbides (RuC,…