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Neural network (NN) interatomic potentials provide fast prediction of potential energy surfaces, closely matching the accuracy of the electronic structure methods used to produce the training data. However, NN predictions are only reliable…

Machine Learning · Computer Science 2021-08-31 Daniel Schwalbe-Koda , Aik Rui Tan , Rafael Gómez-Bombarelli

Soft particles such as microgels and core-shell particles can undergo significant and anisotropic deformations when adsorbed to a liquid interface. This, in turn, leads to a complex phase behavior upon compression. Here we develop a…

Controllable diffusion methods have substantially expanded the practical utility of diffusion models, but they are typically developed as isolated, backbone-specific systems with incompatible training pipelines, parameter formats, and…

Machine Learning · Computer Science 2026-04-28 Zhongjie Duan , Hong Zhang , Yingda Chen

To facilitate the transition of quantum effects from the controlled laboratory environment to practical real-world applications, there is a pressing need for scalable platforms. One promising strategy involves integrating thermal vapors…

Atomic Physics · Physics 2024-01-18 Hadiseh Alaeian , Artur Skljarow , Stefan Scheel , Tilman Pfau , Robert Löw

Pre-trained Language Models have emerged as promising tools for predicting molecular properties, yet their development is in its early stages, necessitating further research to enhance their efficacy and address challenges such as…

Machine Learning · Computer Science 2023-10-24 Eduardo Soares , Akihiro Kishimoto , Emilio Vital Brazil , Seiji Takeda , Hiroshi Kajino , Renato Cerqueira

The process of homogeneous crystal nucleation has been considered in a model liquid, where the interparticle interaction is described by a short-range spherical oscillatory potential. Mechanisms of initiating structural ordering in the…

Materials Science · Physics 2018-12-18 Bulat N. Galimzyanov , Dinar T. Yarullin , Anatolii V. Mokshin

A general Landau's free energy functional is used to study the dynamics of crystallization during liquid-solid Spinodal Decomposition (SD). The strong length scale selectivity imposed during the early stage of SD induces the appearance of…

Statistical Mechanics · Physics 2015-05-20 Leopoldo R. Gomez , Daniel A. Vega

Generative AI models, such as score-based diffusion models, have recently advanced the field of computational materials science by enabling the generation of new materials with desired properties. In addition, these models could also be…

Materials Science · Physics 2026-01-06 Timo Reents , Arianna Cantarella , Marnik Bercx , Pietro Bonfà , Giovanni Pizzi

We investigate crystal nucleation in supersaturated colloid suspensions using enhanced molecular dynamics simulations augmented with machine learning techniques. The simulations reveal that crystallization in the model colloidal system…

Soft Condensed Matter · Physics 2024-04-30 Vanessa J. Meraz , Ziyue Zou , Pratyush Tiwary

Pure phase and mixed phase TiO$_2$ nanoparticles have been produced using a pyrolytic method from a non-aqueous carboxylate precursor. The precursor was prepared by a multiphase cation exchange using pentanoic acid (C$_4$H$_9$COOH). The…

Materials Science · Physics 2021-02-08 Dmitry Zablotsky , Mikhail M. Maiorov , Aija Krumina , Marina Romanova , Elmars Blums

In order to optimize a self-assembly reaction, it is essential to understand the factors that govern its pathway. Here, we examine the influence of nucleation pathways in a model system for addressable, multicomponent self-assembly based on…

Soft Condensed Matter · Physics 2018-08-01 Martin Sajfutdinow , William M. Jacobs , Aleks Reinhardt , Christoph Schneider , David M. Smith

The atomic-scale response of inhomogeneous fluids at interfaces and surrounding solute particles plays a critical role in governing chemical, electrochemical and biological processes at such interfaces. Classical molecular dynamics…

Materials Science · Physics 2023-11-28 Kamron Fazel , Nima Karimitari , Tanooj Shah , Christopher Sutton , Ravishankar Sundararaman

Reduction of information entropy along with ever-increasing complexity are among the key signatures of living matter. Understanding the onset of such behavior in early prebiotic world is essential for solving the problem of origins of life.…

Populations and Evolution · Quantitative Biology 2018-10-17 Alexei V. Tkachenko , Sergei Maslov

We study induced nucleation by considering the accumulation rate of shrinking subcritical bubbles. We derive the probability for a collection of subcritical bubbles to form a critical bubble, and argue that this mechanism could well play a…

High Energy Physics - Phenomenology · Physics 2009-09-25 K. Enqvist , I. Vilja

Mixing of two fluids can lead to the formation of a precipitate. If one of the fluids is injected into a confined space filled with the other, a created precipitate disrupts the flow locally and forms complex spatiotemporal patterns. The…

Soft Condensed Matter · Physics 2023-12-12 Shunsuke Tanaka , Kojiro Otoguro , Miyuki Kunihiro , Hiroki Ishikawa , Yutaka Sumino

This paper presents a homogenisation-based constitutive model to describe the effective tran- sient diffusion behaviour in heterogeneous media in which there is a large contrast between the phase diffusivities. In this case mobile species…

Computational Physics · Physics 2019-03-19 Laurence Brassart , Laurent Stainier

Understanding the driving forces behind the nucleation of different polymorphs is of great importance for material sciences and the pharmaceutical industry. This includes understanding the reaction coordinate that governs the nucleation…

Soft Condensed Matter · Physics 2021-08-25 Ziyue Zou , Sun-Ting Tsai , Pratyush Tiwary

We introduce structural heterogeneity, a new topological characteristic for semi-ordered materials that captures their degree of organisation at a mesoscopic level and tracks their time-evolution, ultimately detecting the order-disorder…

Accurate segmentation and classification of nuclei in histology images is critical but challenging due to nuclei heterogeneity, staining variations, and tissue complexity. Existing methods often struggle with limited dataset variability,…

Image and Video Processing · Electrical Eng. & Systems 2025-01-22 Wenhua Zhang , Sen Yang , Meiwei Luo , Chuan He , Yuchen Li , Jun Zhang , Xiyue Wang , Fang Wang

In molecular dynamics simulations, nanochannel flows are usually driven by a constant force, that aims to represent a pressure difference between inlet and outlet, and periodic boundary conditions are applied in the streamwise direction…

Fluid Dynamics · Physics 2018-01-17 Vicente Bitrián , Javier Principe