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Tailoring the performance of next-generation high entropy materials requires a deep understanding of the competition between entropy-driven random solid solution and enthalpy-driven chemical ordering. Investigating such order and disorder…

Materials Science · Physics 2026-03-24 Fanli Zhou , Hao Chen , Pengxiang Xu , Kai Yang , Zongrui Pei , Xianglin Liu

We propose a computationally lean, two-stage approach that reliably predicts self-assembly behavior of complex charged molecules on a metallic surfaces under electrochemical conditions. Stage one uses ab initio simulations to provide…

Computational Physics · Physics 2020-07-15 Benedikt Hartl , Shubham Sharma , Oliver Brügner , Stijn F. L. Mertens , Michael Walter , Gerhard Kahl

Reduced-order models (ROMs) can efficiently simulate high-dimensional physical systems but lack robust uncertainty quantification methods. Existing approaches are frequently architecture- or training-specific, which limits flexibility and…

Machine Learning · Computer Science 2025-11-18 Jonas E. Katona , Emily K. de Jong , Nipun Gunawardena

Molecular building blocks interacting at the nanoscale organize spontaneously into stable mono- layers that display intriguing long-range ordering motifs on the surface of atomic substrates. The patterning process, if appropriately…

Mesoscale and Nanoscale Physics · Physics 2011-02-18 Marta Balbás Gambra , Carsten Rohr , Kathrin Gruber , Bianca Hermann , Thomas Franosch

We report molecular dynamics calculations on two-component, cold (1.2 > T > 0.56 in natural units), three-dimensional Lennard-Jones fluids. Our system was small (7813 A, 7812 B particles), dense (N/V = 1.30), and distinctly finite (L \times…

Soft Condensed Matter · Physics 2009-11-11 Paul C. Whitford , George D. J. Phillies

Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of…

Chemical Physics · Physics 2020-12-09 Félix Musil , Michele Ceriotti

We introduce a simple, fast, and easy to implement unsupervised learning algorithm for detecting different local environments on a single-particle level in colloidal systems. In this algorithm, we use a vector of standard bond-orientational…

Soft Condensed Matter · Physics 2020-01-08 Emanuele Boattini , Marjolein Dijkstra , Laura Filion

A comprehensive framework of characterizing complex self-assembled structures with a set of orientational order parameters is presented. It is especially relevant in the context of using anisotropic building blocks with various symmetries.…

Soft Condensed Matter · Physics 2022-02-23 Jack A. Logan , Srinivas Mushnoori , Meenakshi Dutt , Alexei V. Tkachenko

We apply reduced-order modeling (ROM) techniques to single-phase flow in faulted porous media, accounting for changing rock properties and fault geometry variations using a radial basis function mesh deformation method. This approach…

Numerical Analysis · Mathematics 2024-03-07 Enrico Ballini , Luca Formaggia , Alessio Fumagalli , Anna Scotti , Paolo Zunino

Phases with distinct thermodynamic properties must differ in their underlying distributions of microscopic structures. While ordered phases are readily distinguished by unit cells and space groups, the local structural basis differentiating…

We study the classic $k$-median and $k$-means clustering objectives in the beyond-worst-case scenario. We consider three well-studied notions of structured data that aim at characterizing real-world inputs: Distribution Stability…

Data Structures and Algorithms · Computer Science 2017-08-11 Vincent Cohen-Addad , Chris Schwiegelshohn

It is shown that the Mott insulating and superfluid phases of bosons in an optical lattice may be distinguished by a non-local 'parity order parameter' which is directly accessible via single site resolution imaging. In one dimension, the…

Quantum Gases · Physics 2013-05-03 Steffen Patrick Rath , Wolfgang Simeth , Manuel Endres , Wilhelm Zwerger

Data within a specific context gains deeper significance beyond its isolated interpretation. In distributed systems, interdependent data sources reveal hidden relationships and latent structures, representing valuable information for many…

Machine Learning · Computer Science 2025-12-30 Mario Colosi , Reza Farahani , Maria Fazio , Radu Prodan , Massimo Villari

Due to rapid advancements in technology, datasets are available from various domains. In order to carry out more relevant and appropriate analysis, it is often necessary to project the dataset into a higher or lower dimensional space based…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Sourav Ghosh , Chayan Maitra , Rajat K. De

It is argued that the (traditional) global level statistics which determines localization and coherent transport properties of disordered systems at zero temperature (e.g. the Anderson model) becomes inappropriate when it comes to…

Disordered Systems and Neural Networks · Physics 2015-06-25 A. V. Malyshev

The supercritical state is currently viewed as uniform on the pressure-temperature phase diagram. Supercritical fluids have the dynamic motions of a gas but are able to dissolve materials like a liquid. They have started to be deployed in…

Statistical Mechanics · Physics 2014-05-30 Dima Bolmatov , D. Zav'yalov , M. Zhernenkov

A simulation study demonstrates that localization can arise as the result of the breakdown of stable quasi-crystal-like atomic configurations. Samples produced at elevated quench rates and via more energetic processes contain a lower…

Materials Science · Physics 2007-05-23 Yunfeng Shi , Michael L. Falk

Self-organized monolayers of highly flexible \Frechet dendrons were deposited on graphite surfaces by solution casting. Scanning tunneling microscopy (STM) reveals an unprecedented variety of patterns with up to seven stable hierarchical…

Mesoscale and Nanoscale Physics · Physics 2011-02-18 B. A. Hermann , C. Rohr , M. Balbás Gambra , A. Malecki , M. S. Malarek , E. Frey , T. Franosch

We consider a model of bosons on a regular lattice with a kinetic energy due to hopping among sites and a potential energy due to strong on site interaction. A superfluid phase is expected when the ground state of the local energy is doubly…

Statistical Mechanics · Physics 2007-05-23 F. de Pasquale , S. M. Giampaolo

Out-of-Time-Order-Correlator (OTOC) and Loschmidt Echo (LE) are commonly regarded as diagnostic tools for chaos, although they may yield misleading results because of various other factors. Previous studies have concluded that OTOC shows…

Quantum Physics · Physics 2025-07-01 Pranaya Pratik Das , Biplab Ganguli