cp2k: atomistic simulations of condensed matter systems

J Hutter, M Iannuzzi, F Schiffmann… - Wiley Interdisciplinary …, 2014 - Wiley Online Library
cp2k has become a versatile open‐source tool for the simulation of complex systems on the
nanometer scale. It allows for sampling and exploring potential energy surfaces that can be …

Designing crystallization in phase-change materials for universal memory and neuro-inspired computing

W Zhang, R Mazzarello, M Wuttig, E Ma - Nature Reviews Materials, 2019 - nature.com
The global demand for data storage and processing has increased exponentially in recent
decades. To respond to this demand, research efforts have been devoted to the …

Insights into the activity of single-atom Fe-NC catalysts for oxygen reduction reaction

K Liu, J Fu, Y Lin, T Luo, G Ni, H Li, Z Lin… - Nature …, 2022 - nature.com
Single-atom Fe-NC catalysts has attracted widespread attentions in the oxygen reduction
reaction (ORR). However, the origin of ORR activity on Fe-NC catalysts is still unclear, which …

Visualizing interfacial collective reaction behaviour of Li–S batteries

S Zhou, J Shi, S Liu, G Li, F Pei, Y Chen, J Deng… - Nature, 2023 - nature.com
Benefiting from high energy density (2,600 Wh kg− 1) and low cost, lithium–sulfur (Li–S)
batteries are considered promising candidates for advanced energy-storage systems …

[HTML][HTML] CP2K: An electronic structure and molecular dynamics software package-Quickstep: Efficient and accurate electronic structure calculations

TD Kühne, M Iannuzzi, M Del Ben, VV Rybkin… - The Journal of …, 2020 - pubs.aip.org
CP2K is an open source electronic structure and molecular dynamics software package to
perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is …

Generalized neural-network representation of high-dimensional potential-energy surfaces

J Behler, M Parrinello - Physical review letters, 2007 - APS
The accurate description of chemical processes often requires the use of computationally
demanding methods like density-functional theory (DFT), making long simulations of large …

Reducing the stochasticity of crystal nucleation to enable subnanosecond memory writing

F Rao, K Ding, Y Zhou, Y Zheng, M **a, S Lv, Z Song… - Science, 2017 - science.org
Operation speed is a key challenge in phase-change random-access memory (PCRAM)
technology, especially for achieving subnanosecond high-speed cache memory …

Machine learning interatomic potentials as emerging tools for materials science

VL Deringer, MA Caro, G Csányi - Advanced Materials, 2019 - Wiley Online Library
Atomic‐scale modeling and understanding of materials have made remarkable progress,
but they are still fundamentally limited by the large computational cost of explicit electronic …

Machine learning based interatomic potential for amorphous carbon

VL Deringer, G Csányi - Physical Review B, 2017 - APS
We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid
and amorphous elemental carbon. Based on a machine learning representation of the …

[HTML][HTML] Perspective: How good is DFT for water?

MJ Gillan, D Alfe, A Michaelides - The Journal of chemical physics, 2016 - pubs.aip.org
Kohn-Sham density functional theory (DFT) has become established as an indispensable
tool for investigating aqueous systems of all kinds, including those important in chemistry …