activity
20002024
most citedPredicting electronic structures at any length scale with machine learning

73 citations · 234 across the 8 of their papers we have counts for

collaborators

8 papers

cond-mat.mtrl-sci2024

Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations

Attila Cangi, Lenz Fiedler, Bartosz Brzoza +11

We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for…

cond-mat.mtrl-sci2023★ 6 cited

Machine learning the electronic structure of matter across temperatures

Lenz Fiedler, Normand A. Modine, Kyle D. Miller +1

We introduce machine learning (ML) models that predict the electronic structure of materials across a wide temperature range. Our models employ neural networks and are trained on d…

cond-mat.mtrl-sci2022★ 73 cited

Predicting electronic structures at any length scale with machine learning

Lenz Fiedler, Normand A. Modine, Steve Schmerler +5

The properties of electrons in matter are of fundamental importance. They give rise to virtually all molecular and material properties and determine the physics at play in objects…

cond-mat.mtrl-sci2022

Electron dynamics in extended systems within real-time time-dependent density functional theory

Alina Kononov, Cheng-Wei Lee, Tatiane Pereira dos Santos +10

Due to a beneficial balance of computational cost and accuracy, real-time time-dependent density functional theory has emerged as a promising first-principles framework to describe…

cond-mat.mtrl-sci2020★ 67 cited

Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks

J. Austin Ellis, Lenz Fiedler, Gabriel A. Popoola +5

We present a numerical modeling workflow based on machine learning (ML) which reproduces the the total energies produced by Kohn-Sham density functional theory (DFT) at finite elec…

cond-mat.mtrl-sci2018★ 50 cited

Kinetics-Controlled Degradation Reactions at Crystalline LiPON/Li(x)CoO(2) and Crystalline LiPON/Li-metal Interfaces

Kevin Leung, Alexander J. Pearse, A. Alec Talin +3

Detailed understanding of solid-solid interface structure-function relations is critical for the improvement and wide deployment of all solid-state batteries. The interfaces betwee…

cond-mat.mtrl-sci2015★ 2 cited

Graphene/MoS2 van der Waals Bilayer as the Anode Material for Next Generation Li-ion Battery: A First-Principles Investigation

Towfiq Ahmed, N. A. Modine, Jian-Xin Zhu

We performed density functional theory (DFT) calculations for a bi-layered heterostructure combining a graphene layer with a MoS2 layer with and without intercalated Li atoms. Our…

cond-mat.mtrl-sci2000★ 36 cited

HARES: an efficient method for first-principles electronic structure calculations of complex systems

U. V. Waghmare, Hanchul Kim, I. J. Park +3

We discuss our new implementation of the Real-space Electronic Structure method for studying the atomic and electronic structure of infinite periodic as well as finite systems, bas…