78 citations · 192 across the 5 of their papers we have counts for
5 papers
PiNNAcLe: Adaptive Learn-On-The-Fly Algorithm for Machine-Learning Potential
Yunqi Shao, Chao Zhang
PiNNAcLe is an implementation of our adaptive learn-on-the-fly algorithm for running machine-learning potential (MLP)-based molecular dynamics (MD) simulations -- an emerging appro…
Transference number in polymer electrolytes: mind the reference-frame gap
Yunqi Shao, Harish Gudla, Daniel Brandell +1
The transport coefficients, in particular the transference number, of electrolyte solutions are important design parameters for electrochemical energy storage devices. Recent obser…
Importance of the ion-pair lifetime in polymer electrolytes
Harish Gudla, Yunqi Shao, Supho Phunnarungsi +2
Ion-pairing is commonly considered as a culprit for the reduced ionic conductivity in polymer electrolyte systems. However, this simple thermodynamic picture should not be taken li…
Temperature effects on the ionic conductivity in concentrated alkaline electrolyte solutions
Yunqi Shao, Matti Hellström, Are Yllö +4
Alkaline electrolyte solutions are important components in rechargeable batteries and alkaline fuel cells. As the ionic conductivity is thought to be a limiting factor in the perfo…
PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials
Yunqi Shao, Matti Hellström, Pavlin D. Mitev +2
Atomic neural networks (ANNs) constitute a class of machine learning methods for predicting potential energy surfaces and physico-chemical properties of molecules and materials. De…