cp2k: atomistic simulations of condensed matter systems
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 …
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
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 …
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 …
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
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 …
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
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 …
perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is …
Generalized neural-network representation of high-dimensional potential-energy surfaces
The accurate description of chemical processes often requires the use of computationally
demanding methods like density-functional theory (DFT), making long simulations of large …
demanding methods like density-functional theory (DFT), making long simulations of large …
Reducing the stochasticity of crystal nucleation to enable subnanosecond memory writing
Operation speed is a key challenge in phase-change random-access memory (PCRAM)
technology, especially for achieving subnanosecond high-speed cache memory …
technology, especially for achieving subnanosecond high-speed cache memory …
Machine learning interatomic potentials as emerging tools for materials science
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 …
but they are still fundamentally limited by the large computational cost of explicit electronic …
Machine learning based interatomic potential for amorphous carbon
We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid
and amorphous elemental carbon. Based on a machine learning representation of the …
and amorphous elemental carbon. Based on a machine learning representation of the …
[HTML][HTML] Perspective: How good is DFT for water?
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 …
tool for investigating aqueous systems of all kinds, including those important in chemistry …