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High-performance graphical processing units (GPU) are used for the repeated parallelised propagation of non-linear partial differential equations on large spatio-temporal grids. The main challenge results as a combination of the requirement…

Multiscale modeling is essential for understanding the complex behavior of materials. However, accurately transferring all relevant information from one scale to another has remained an outstanding challenge. Neural operators,…

Materials Science · Physics 2026-05-12 Kaushik Bhattacharya

This study focuses on solving the numerical challenges of imposing absorbing boundary conditions for dynamic simulations in the material point method (MPM). To attenuate elastic waves leaving the computational domain, the current work…

Geophysics · Physics 2025-01-24 Jun Kurima , Bodhinanda Chandra , Kenichi Soga

High-fidelity numerical methods that model the physical layout of a device are essential for the design of many technologies. For methods that characterize electromagnetic effects, these numerical methods are referred to as computational…

With the rise of deep learning, there has been renewed interest within the process industries to utilize data on large-scale nonlinear sensing and control problems. We identify key statistical and machine learning techniques that have seen…

Atomistic simulations provide insights into structure-property relations on an atomic size and length scale, that are complementary to the macroscopic observables that can be obtained from experiments. Quantitative predictions, however, are…

Materials Science · Physics 2021-04-14 Nataliya Lopanitsyna , Chiheb Ben Mahmoud , Michele Ceriotti

In this study we explore the optimization of laser pulse duration to obtain the shortest possible pulse. We do this by employing a feedback loop between a pulse shaper and pulse duration measurements. We apply to this problem several…

Computational Physics · Physics 2023-04-26 Francesco Capuano , Davorin Peceli , Gabriele Tiboni , Alexandr Špaček , Bedřic Rus

Simulation offers a simple and flexible way to estimate the power of a clinical trial when analytic formulae are not available. The computational burden of using simulation has, however, restricted its application to only the simplest of…

In this paper, we investigate the use of variational quantum algorithms for simulating the thermodynamic properties of dinuclear metal complexes. Our study highlights the potential of quantum computing to transform advanced simulations and…

Quantum Physics · Physics 2024-10-28 Ana Clara das Neves Silva , Clebson Cruz

This paper describes a 2D and 3D simulation engine that quantitatively models the statics, dynamics, and non-linear deformation of heterogeneous soft bodies in a computationally efficient manner. There is a large body of work simulating…

Graphics · Computer Science 2012-12-13 Jonathan Hiller , Hod Lipson

This paper addresses the numerical simulation of self-piercing rivetting processes to join fibre reinforced polymers and sheet metals. Special emphasis is placed on the modelling of the deformation and failure behaviour of the composite…

When they are damaged or injured, soft biological tissues are able to self-repair and heal. Mechanics is critical during the healing process, as the damaged extracellular matrix (ECM) tends to be replaced with a new undamaged ECM supporting…

Computational Engineering, Finance, and Science · Computer Science 2021-12-08 Di Zuo , Yiqian He , Stéphane Avril , Haitian Yang , Klaus Hackl

The physical processes at the interface of a low-temperature plasma and a solid are extremely complex. They involve a huge number of elementary processes in the plasma, in the solid as well as charge, momentum and energy transfer across the…

Plasma Physics · Physics 2018-09-10 M. Bonitz , A. Filinov , J. W. Abraham , D. Loffhagen

Supported nanoparticle catalysts are widely used in the chemical industry. Computational modeling of supported nanoparticles based on density functional theory (DFT) often involves structural searches of stable local minimum energy…

Materials Science · Physics 2026-03-26 Jiayan Xu , Abhirup Patra , Amar Deep Pathak , Sharan Shetty , Detlef Hohl , Roberto Car

Machine learning techniques are powerful tools for construction of emulators for complex systems. We explore different machine learning methods and conceptual methodologies, ranging from functional approximations to dynamical…

Dynamical Systems · Mathematics 2021-01-01 Hannah Lu , Dinara Ermakova , Haruko Murakami Wainwright , Liange Zheng , Daniel M. Tartakovsky

The liquidus temperature is an important parameter in understanding the crystalline behavior of materials and in the operation of blast furnaces. Its modeling can be carried out by linear and nonlinear methods through data, considering the…

Materials Science · Physics 2023-07-24 Patrick dos Anjos , Lucas A. Quaresma , Marcelo L. P. Machado

Microscale additive manufacturing of reflective copper is becoming increasingly important for microelectronics and microcomputers, due to its excellent electrical and thermal conductivity. Yet, it remains challenging for state-of-the-art…

Optics · Physics 2025-12-30 Youwen Liang , Bo Shen , Wan Shou

Selective thin-film removal is needed in many microfabrication processes such as 3-D patterning of optoelectronic devices and localized repairing of integrated circuits. Various wet or dry etching methods are available, but laser machining…

Revealing possible long-living coherence in ultrafast processes allows detecting genuine quantum mechanical effects in molecules. To investigate such effects from a quantum chemistry perspective, we have developed a method for simulating…

Chemical Physics · Physics 2018-07-04 Emanuele Coccia , Filippo Troiani , Stefano Corni
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