The Phase Diagram of the Electron Liquid
Most of the properties of materials, from their strength and hardness to their conductivity and colour, are determined by the ...
Using Machine Learning to uncover the Unique Properties of Nanoconfined Water
Water – the molecule of life – is an intriguing substance to study. The properties of water, already unique at the macroscale, ...
Multiscale Modelling of Electronic and Defect Properties of Cerium Oxides
A new theoretical framework was developed to investigate the electronic and defect properties of ceria (CeO2) by integrating ...
Mechanism of dielectric breakdown in oxide films
Gate dielectrics breakdown (BD) is one of the most challenging areas in the field of semiconductor device reliability. Despite massive ...
Improving Pd-based alloy catalysts for CO2 hydrogenation with Density Functional Theory and Artificial Intelligence
The global annual production of methanol is ~100 million tonnes, predominately from oil-derived sources using heterogeneous catalysts. ...
Accelerated Materials Discovery for Solid State Hydrogen Storage Applications Using Machine Learning and Density Functional Theory Simulations
We demonstrate how the integration of machine learning (ML) and density functional theory (DFT) approaches accelerates the discovery ...
Defect chemistry of the layered lithium-ion cathode material LiNiO₂
The layered lithium-ion cathode material LiNiO₂ (LNO) has attracted significant attention due to its high energy density, yet ...
Simulation-led discovery of porous non-metal organic frameworks for energy applications
Designing crystalline solids with specific functionalities is a challenge due to the complexity of predicting how molecules will ...
Thermoelectric transport in molecular crystals driven by gradients of thermal electronic disorder
In this work, MCC researchers develop a quantum dynamical simulation approach revealing in atomistic detail how the charge carrier ...