Machine learning has demonstrated superior performance in predicting vast materials properties. However, predicting a spectral-like continuous material property such as phonon density of states (DOS) is more challenging for machine learning. In this work, ...
Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift toward ...
Carbon nano-onions are a class of nanomaterials that can exhibit long electron spin relaxation times at room temperature and thus hold promise as potential building blocks for spintronics and quantum information processing devices. Despite first being synt ...
Motivated by the presence of Ising transitions that take place entirely in the singlet sector of frustrated spin-1/2 ladders and spin-1 chains, we study two types of effective dimer models on ladders, a quantum dimer model and a quantum loop model. Buildin ...
Silicon and oxygen are potential light elements in Earth's core because their stronger affinity to metal observed with increasing temperature posits that significant amounts of both can be incorporated into the core. It was proposed that an Fe-Si-O liquid ...
Developing a high-performance catalyst and establishing a catalytic mechanism for understanding the catalytic activity are crucial to new generation photovoltaic technology. In this work, we present a feasible and general route to synthesize a bio-based po ...
The vibrational properties of vitreous GeSe2 are studied within the Becke-Lee-Yang-Parr (BLYP) generalized gradient approximation to density functional theory. For this purpose, we consider two models. The first one is derived from a chemically ordered net ...
