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In this study, we present a graph neural network-based learning approach using an autoencoder setup to derive low-dimensional variables from features observed in experimental crystal structures. These variables are then biased in enhanced…

Statistical Mechanics · Physics 2023-10-13 Ziyue Zou , Pratyush Tiwary

The quasiparticle method, which has achieved a great success in solid state electronics and crystal lattice vibration, is adopted to study the solid state ion transport. A general recipe is put forward to map the classical solid state ion…

Materials Science · Physics 2024-02-13 Jiaming Hu

Node-link diagrams are a popular method for representing graphs that capture relationships between individuals, businesses, proteins, and telecommunication endpoints. However, node-link diagrams may fail to convey insights regarding graph…

Social and Information Networks · Computer Science 2023-09-20 Paul Rosen , Mustafa Hajij , Bei Wang

Many processes in chemistry, physics, and biology involve rare events in which the system escapes from a metastable state by surmounting an activation barrier. Examples range from chemical reactions, protein folding, and nucleation events…

Chemical Physics · Physics 2020-10-07 Niels Zijlstra , Daniel Nettels , Rohit Satija , Dmitrii E. Makarov , Benjamin Schuler

Crystal structures are characterized by atomic bases within a primitive unit cell that repeats along a regular lattice throughout 3D space. The periodic and infinite nature of crystals poses unique challenges for geometric graph…

Machine Learning · Computer Science 2024-03-19 Keqiang Yan , Cong Fu , Xiaofeng Qian , Xiaoning Qian , Shuiwang Ji

This work presents a fast and scalable approach for predicting surface stability and equilibrium crystal morphology in ionic materials using electrostatic analysis. The method constructs stoichiometric slab terminations and evaluates their…

Materials Science · Physics 2026-04-30 Sourav Baiju , Payam Kaghazchi

Trapped atomic ions have become one of the most promising architectures for a quantum computer, and current effort is now devoted to the transport of trapped ions through complex segmented ion trap structures in order to scale up to much…

Quantum Physics · Physics 2008-02-20 D. Hucul , M. Yeo , W. K. Hensinger , J. Rabchuk , S. Olmschenk , C. Monroe

Graph filters are a staple tool for processing signals over graphs in a multitude of downstream tasks. However, they are commonly designed for graphs with a fixed number of nodes, despite real-world networks typically grow over time. This…

Machine Learning · Computer Science 2024-09-12 Bishwadeep Das , Elvin Isufi

Dielectric microstructures have been reported to have negative influences on perm-selective ion transportation because ions do not migrate in areas where the structures are located. However, the structure can promote the transportation if…

Applied Physics · Physics 2019-11-05 Keon Huh , So-Yoon Yang , Jae Suk Park , Jung A Lee , Hyomin Lee , Sung Jae Kim

Understanding mechanisms of ion transport in bulk materials is central to designing next-generation ion conductors for energy storage devices, yet studies employing all-atom molecular dynamics (MD) have largely been limited to reporting…

Materials Science · Physics 2026-02-19 KyuJung Jun , Pablo A. Leon , Jurğis Ruža , Juno Nam , Rafael Gómez-Bombarelli

We present a novel framework based on optimal transport for the challenging problem of comparing graphs. Specifically, we exploit the probabilistic distribution of smooth graph signals defined with respect to the graph topology. This allows…

Machine Learning · Computer Science 2019-12-09 Hermina Petric Maretic , Mireille EL Gheche , Giovanni Chierchia , Pascal Frossard

Many network analysis and graph learning techniques are based on models of random walks which require to infer transition matrices that formalize the underlying stochastic process in an observed graph. For weighted graphs, it is common to…

Methodology · Statistics 2022-10-28 Vincenzo Perri , Luka V. Petrović , Ingo Scholtes

We provide a data structure for maintaining an embedding of a graph on a surface (represented combinatorially by a permutation of edges around each vertex) and computing generators of the fundamental group of the surface, in amortized time…

Data Structures and Algorithms · Computer Science 2007-05-23 David Eppstein

There has been a recent surge of interest in using machine learning to approximate density functional theory (DFT) in materials science. However, many of the most performant models are evaluated on large databases of computed properties of,…

Materials Science · Physics 2021-07-02 Filip Ekström , Rickard Armiento , Fredrik Lindsten

We simulate structure in the vicinity of different size nanovoids using a new variant of the Molecular Statics, wherein atomic structure in the vicinity of nanovoids and the parameters that define the displacements of atoms placed in…

Materials Science · Physics 2022-02-02 A. V. Nazarov , A. P. Melnikov , A. A. Mikheev , I. V. Ershova

We study the urban-scale macroscopic traffic flow in city networks. Star graph is considered as traffic network. Star graphs with controlled traffic flow are transformed to various cell-transmission graphs by using the cell transmission…

Adaptation and Self-Organizing Systems · Physics 2019-12-10 Takashi Nagatani

Drag and diffusion of mobile ions in solids are of interest for both purely theoretical and applied scientific communities. This article proposes a theoretical description of ion drag in solids that can be used to estimate ionic…

Mesoscale and Nanoscale Physics · Physics 2022-06-24 Aleksandr Rodin , Keian Noori , Alexandra Carvalho , Antonio Helio Castro Neto

When ions move through solids, they interact with the solid's constituent atoms and cause them to vibrate around their equilibrium points. This vibration, in turn, modifies the potential landscape through which the mobile ions travel.…

Materials Science · Physics 2024-07-03 A. Rodin , B. A. Olsen , A. Ustyuzhanin , A. Maevskiy , K. Noori

Introduction: molecular geometry, the three-dimensional arrangement of atoms within a molecule, is fundamental to understanding chemical reactivity, physical properties, and biological activity. The prevailing models used to describe…

General Physics · Physics 2026-05-12 Sebastian Ali Sacasa-Cespedes

Graphs are widely used for modeling various types of interactions, such as email communications and online discussions. Many of such real-world graphs are temporal, and specifically, they grow over time with new nodes and edges. Counting…

Social and Information Networks · Computer Science 2023-01-04 Deukryeol Yoon , Dongjin Lee , Minyoung Choe , Kijung Shin