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Charge transfer plays a crucial role in many processes of interest in physics, chemistry, and bio-chemistry. In many applications the size of the systems involved calls for time-dependent density functional theory (TDDFT) to be used in…

Chemical Physics · Physics 2017-10-11 Neepa T. Maitra

Materials design has traditionally evolved through trial-error approaches, mainly due to the non-local relationship between microstructures and properties such as strength and toughness. We propose 'alloy informatics' as a machine learning…

Materials Science · Physics 2025-04-08 Dario Massa , Efthimios Kaxiras , Stefanos Papanikolaou

We present a plane-wave basis set implementation of charge constrained density functional molecular dynamics (CDFT-MD) for simulation of electron transfer reactions in condensed phase systems. Following earlier work of Wu et al. Phys. Rev.…

Chemical Physics · Physics 2015-05-13 H. Oberhofer , J. Blumberger

Defect segmentation is central to computer vision based inspection of infrastructure assets during both construction and operation. However, deployment remains limited due to scarce pixel-level labels and domain shift across environments.…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Babak Asadi , Peiyang Wu , Mani Golparvar-Fard , Ramez Hajj

Electronic structure is ubiquitously obtained via density functional theory (DFT), where the charge density plays a central role. This work presents EdenGNN (Equivariant Density Graph Neural Network), a machine learning (ML) charge density…

Materials Science · Physics 2026-03-16 Xiwen Li , Zaizhou Xin , Hongyu Yu , Yang Zhong , Xingao Gong , Hongjun Xiang

Predicting low-energy molecular conformations given a molecular graph is an important but challenging task in computational drug discovery. Existing state-of-the-art approaches either resort to large scale transformer-based models that…

Quantitative Methods · Quantitative Biology 2024-10-31 Majdi Hassan , Nikhil Shenoy , Jungyoon Lee , Hannes Stark , Stephan Thaler , Dominique Beaini

Density functional theory (DFT) is a fundamental method for simulating quantum chemical properties, but it remains expensive due to the iterative self-consistent field (SCF) process required to solve the Kohn-Sham equations. Recently, deep…

Computational Physics · Physics 2025-10-23 Seongsu Kim , Nayoung Kim , Dongwoo Kim , Sungsoo Ahn

The structure of dilute electrolyte solutions close to a surface carrying a spatially inhomogeneous surface charge distribution is investigated by means of classical density functional theory (DFT) within the approach of fundamental measure…

Soft Condensed Matter · Physics 2020-06-23 Maximilian Mußotter , Markus Bier , S. Dietrich

Constrained density functional theory (CDFT) is used to evaluate the energy level alignment of a benzene molecule as it approaches a graphene sheet. Within CDFT the problem is conveniently mapped onto evaluating total energy differences…

Mesoscale and Nanoscale Physics · Physics 2016-01-27 Subhayan Roychoudhury , Carlo Motta , Stefano Sanvito

Density functional theory (DFT) is used to rationalize magnetic parameters of hydrated electron trapped in alkaline glasses as observed using Electron Paramagnetic Resonance (EPR) and Electron Spin Echo Envelope Modulation (ESEEM)…

General Physics · Physics 2016-09-28 I. A. Shkrob

A conformal field theory (CFT) in dimension $d\geq 3$ coupled to a planar, two-dimensional, conformal defect is characterized in part by a "central charge" $b$ that multiplies the Euler density in the defect's Weyl anomaly. For defect…

High Energy Physics - Theory · Physics 2016-03-09 Kristan Jensen , Andy O'Bannon

Discovering heterogeneous catalysts tailored for specific reaction intermediates remains a fundamental bottleneck in materials science. While traditional trial-and-error methods and recent generative models have shown promise, they struggle…

Materials Science · Physics 2026-05-19 Minkyu Kim , Nayoung Kim , Honghui Kim , Sungsoo Ahn

Heterogeneous interfaces are central to many energy-related applications in the nanoscale. From the first-principles electronic structure perspective, one of the outstanding problems is accurately and efficiently calculating how the…

Materials Science · Physics 2023-08-29 Zhen-Fei Liu

We present an accurate local density-functional for electronic-structure calculations within the density functional theory (DFT). The functional is derived by analyzing the structure of the standard perturbative expansion of the correlation…

Materials Science · Physics 2024-11-28 Mario Benites , Angel Rosado , Efstratios Manousakis

A simplified density functional theory (DFT) method for charged adsorbates on an ultrathin, insulating film supported by a metal substrate is developed and presented. This new method is based on a previous DFT development that uses a…

Materials Science · Physics 2017-03-27 Ivan Scivetti , Mats Persson

We investigate the coupled dynamics of concentration and charge in asymmetric 1:1 electrolytes, focusing on the interplay between diffusion asymmetry and external electric fields. Using Brownian dynamics simulations and linearized…

Soft Condensed Matter · Physics 2026-01-22 Thê Hoang Ngoc Minh , Sleeba Varghese , Benjamin Rotenberg

The accuracy of density-functional theory (DFT) is determined by the quality of the approximate functionals, such as exchange-correlation in electronic DFT and the excess functional in the classical DFT formalism of fluids. The exact…

Electrostatics govern charge transfer and reactivity in materials. Yet, most foundation potentials (FPs) either do not explicitly model such interactions or pay a prohibitive scaling penalty to do so. Here, we introduce charge-equilibrated…

Materials Science · Physics 2025-11-12 Tsz Wai Ko , Runze Liu , Adesh Rohan Mishra , Zihan Yu , Ji Qi , Shyue Ping Ong

Approximate density functional theory (DFT) suffers from many-electron self- interaction error, otherwise known as delocalization error, that may be diagnosed and then corrected through elimination of the deviation from exact piecewise…

Materials Science · Physics 2016-11-08 Terry Z. H. Gani , Heather J. Kulik

Denoising Diffusion Probabilistic Models (DDPMs) have established a new state-of-the-art in generative image synthesis, yet their deployment is hindered by significant computational overhead during inference, often requiring up to 1,000…

Machine Learning · Computer Science 2025-11-25 Srishti Gupta , Yashasvee Taiwade