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Metallic glasses possess outstanding mechanical and physical properties, making them promising candidates for advanced structural and functional applications; however, the lack of understanding and control over their glass transition and…

Soft Condensed Matter · Physics 2025-06-04 Wei Chu , Zheng Wang , Christopher Ness , Konrad Samwer , Alessio Zaccone , Lina Hu

Inferring geometrically consistent dense 3D scenes across a tuple of temporally consecutive images remains challenging for self-supervised monocular depth prediction pipelines. This paper explores how the increasingly popular transformer…

Computer Vision and Pattern Recognition · Computer Science 2021-10-18 Patrick Ruhkamp , Daoyi Gao , Hanzhi Chen , Nassir Navab , Benjamin Busam

The prediction of crystal properties is essential for understanding structure-property relationships and accelerating the discovery of functional materials. However, conventional approaches relying on experimental measurements or density…

Materials Science · Physics 2025-06-24 Changwen Xu , Shang Zhu , Venkatasubramanian Viswanathan

Crystallization represents a fundamental process engendering solidification of a material and determines its microstructure. Driven by complex phenomena at the atomic scale, its understanding for alloys still remains elusive. The present…

Materials Science · Physics 2022-10-06 Sébastien Becker , Emilie Devijver , Rémi Molinier , Noël Jakse

Our understanding of supercooled liquids and glasses has lagged significantly behind that of simple liquids and crystalline solids. This is in part due to the many possibly relevant degrees of freedom that are present due to the disorder…

Machine Learning · Statistics 2018-08-01 Samuel S. Schoenholz

Topological defects are singularities within a field that cannot be removed by continuous transformations. The definition of these irregularities requires an ordered reference configuration, calling into question whether they exist in…

Soft Condensed Matter · Physics 2025-01-06 Vinay Vaibhav , Arabinda Bera , Amelia C. Y. Liu , Matteo Baggioli , Peter Keim , Alessio Zaccone

Recent advances in computational materials science present novel opportunities for structure discovery and optimization, including uncovering of unsuspected compounds and metastable structures, electronic structure, surface, and…

Using molecular dynamics simulations, with a realistic many-body embedded-atom potential, and a novel method to characterize local order, we study the structure of pure nickel during the rapid quench of the liquid and in the resulting…

Disordered Systems and Neural Networks · Physics 2016-08-15 Oscar Rodríguez de la Fuente , José M. Soler

Identifying single phase, high-entropy systems has been a prominent research focus of materials engineering over the past decade. The considerable effort in computational modeling and experimental verification has yielded several methods…

Materials Science · Physics 2024-09-02 Kevin Kaufmann , Haoren Wang , Jaskaran Saini , Kenneth S. Vecchio

The time-honored Allen-Feldman theory of heat transport in glasses is generally assumed to predict a finite value for the thermal conductivity, even if it neglects the anharmonic broadening of vibrational normal modes. We demonstrate that…

Disordered Systems and Neural Networks · Physics 2023-07-19 Alfredo Fiorentino , Enrico Drigo , Stefano Baroni , Paolo Pegolo

The analytical model of a glass-forming system is formulated within the formalism analogous to gauge theory constructions in quantum field theory. This work explores the scope of the proposed approach and investigates the equilibrium…

Statistical Mechanics · Physics 2025-07-15 Son L. D. , Vasin M. G

The design of next-generation alloys through the Integrated Computational Materials Engineering (ICME) approach relies on multi-scale computer simulations to provide thermodynamic properties when experiments are difficult to conduct.…

Glass formation is one of the most interesting phenomena in the condensed matter field. Considerable effort has gone into understanding and predicting the glass formability. However, the previous prediction requires the glass first made…

Materials Science · Physics 2019-02-12 R. Dai , R. Ashcraft , A. K. Gangopadhyay , K. F. Kelton

The term "fragility" describes the rate at which viscosity grows when a supercooled liquid approaches its putative glass transition temperature. The field of glassy materials is actively searching for a structural origin that governs this…

Soft Condensed Matter · Physics 2021-08-06 Indrajit Tah , Smarajit Karmakar

We review a theoretical perspective of the dynamics of glass forming liquids and the glass transition. It is a perspective we have developed with our collaborators during this decade. It is based upon the structure of trajectory space. This…

Soft Condensed Matter · Physics 2010-04-20 David Chandler , Juan P. Garrahan

The phase-field model for the description of the solidification processes with the glass-crystal competition is suggested. The model combines the first-order phase transition model in the phase-field formalism and gauge-field theory of…

Materials Science · Physics 2024-08-07 M. G. Vasin , V. Ankudinov

Dynamic heterogeneity is now recognised as a central aspect of structural relaxation in disordered materials with slow dynamics, and was the focus of intense research in the last decade. Here we describe how initial, indirect observations…

Statistical Mechanics · Physics 2010-09-28 Ludovic Berthier , Giulio Biroli , Jean-Philippe Bouchaud , Robert L Jack

The formation of clusters in supercooled liquids close to the glass transition temperature is described by rate equations in which the coefficients are determined on physical grounds rather than in terms of thermodynamic quantities such as…

Disordered Systems and Neural Networks · Physics 2007-05-23 V. Halpern

We utilize the generalized entropy theory (GET) of glass formation to address one of the most singular and least understood properties of polymer glass-forming liquids in comparison to atomic and small molecule liquids -- the often…

Soft Condensed Matter · Physics 2024-12-30 Xiaolei Xu , Jack F. Douglas , Wen-Sheng Xu

We present an image processing algorithm developed for quantitative analysis of directional solidification of metal alloys in thin cells using X-ray imaging. Our methodology allows to identify the fluid volume, fluid channels and cavities,…

Materials Science · Physics 2023-08-02 Mihails Birjukovs , Natalia Shevchenko , Sven Eckert