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The optimization of properties of perovskite oxides has drawn interest on account of their diverse areas of application. In this work, the hierarchical clustering technique is used to reduce the multi-collinearity among selected features…

Materials Science · Physics 2022-03-01 George Stephen Thoppil , Alankar Alankar

Predicting residual stresses has always been a topic of significance due to its implications in the development of enhanced materials and better processing conditions. In this work, an analytical model for prediction of residual stresses is…

Materials Science · Physics 2024-03-28 Rachit Dhar , Ankur Krishna , Bilal Muhammed

Microstructural heterogeneity affects the macro-scale behavior of materials. Conversely, load distribution at the macro-scale changes the microstructural response. These up-scaling and down-scaling relations are often modeled using…

Materials Science · Physics 2023-06-13 Ashwini Gupta , Anindya Bhaduri , Lori Graham-Brady

We analyze a mesoscopic model of a shear stress material with a three dimensional slab geometry, under an external quasistatic deformation of a simple shear type. Relaxation is introduced in the model as a mechanism by which an unperturbed…

Soft Condensed Matter · Physics 2023-04-27 E. A. Jagla

Evaluating the mechanical response of fiber-reinforced composites can be extremely time consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input-output pairs and…

Materials Science · Physics 2024-10-03 Yixuan Sun , Imad Hanhan , Michael D. Sangid , Guang Lin

The onset of nonlinear effects in metals, such as plasticity and damage, is strongly influenced by the heterogeneous stress distribution at the grain level. This work is devoted to studying the local stress distribution of shear stresses…

Materials Science · Physics 2022-07-26 Flavia Gehrig , Daniel Wicht , Maximilian Krause , Thomas Böhlke

Crystal plasticity theory is often employed to predict the mesoscopic states of polycrystalline metals, and is well-known to be costly to simulate. Using a neural network with convolutional layers encoding correlations in time and space, we…

Computational Physics · Physics 2019-10-09 Ari Frankel , Kousuke Tachida , Reese Jones

This short paper presents the potential of using machine learning to predict materials behaviour in the context of hydrogen interaction with steel. Effort has been made to understand the quality, and amount of data needed to get improved…

Materials Science · Physics 2021-10-22 M. Amir Siddiq

Stress-strain relations for random packings of entangling chains under triaxial compression can exhibit strain stiffening and sustain stresses several orders-of-magnitude beyond typical granular materials. X-ray tomography reveals the…

Soft Condensed Matter · Physics 2025-02-12 Eric Brown , Kevin A. Mitchell , Alice Nasto , Athanasios Athanassiadis , Heinrich M. Jaeger

Elastomeric mechanical metamaterials exhibit unconventional behaviour, emerging from their microstructures often deforming in a highly nonlinear and unstable manner. Such microstructural pattern transformations lead to non-local behaviour…

Soft Condensed Matter · Physics 2025-02-18 S. O. Sperling , T. Guo , R. H. J. Peerlings , V. G. Kouznetsova , M. G. D. Geers , O. Rokoš

Selective laser melting is receiving increasing interest as an additive manufacturing technique. Residual stresses induced by the large temperature gradients and inhomogeneous cooling process can favour the generation of cracks. In this…

Materials Science · Physics 2021-07-20 Nicolò Grilli , Daijun Hu , Dewen Yushu , Fan Chen , Wentao Yan

We propose an approach for exploiting machine learning to approximate electronic fields in crystalline solids subjected to deformation. Strain engineering is emerging as a widely used method for tuning the properties of materials, and this…

Materials Science · Physics 2021-12-28 Ying Shi Teh , Swarnava Ghosh , Kaushik Bhattacharya

We consider a sheared granular system experiencing intermittent dynamics of stick-slip type via discrete element simulations. The considered setup consists of a two-dimensional system of soft frictional particles sandwiched between solid…

Soft Condensed Matter · Physics 2023-05-24 Philip Bretz , Lou Kondic , Miro Kramar

A novel original method of determination of stresses and critical resolved shear stresses (CRSSs) using neutron diffraction was proposed. In this method, based on the crystallite group method, the lattice strains were measured in different…

In recent years, there has been a growing interest in accelerated materials innovation in the context of the process-structure-property chain. In this regard, it is essential to take into account manufacturing processes and tailor materials…

Materials Science · Physics 2024-11-12 Lukas Morand , Tarek Iraki , Johannes Dornheim , Stefan Sandfeld , Norbert Link , Dirk Helm

Adhesion is a fundamental phenomenon that plays a role in many engineering and biological applications. This paper concerns the use of machine learning to characterize the effective adhesive properties when a thin film is peeled from a…

Applied Physics · Physics 2023-09-04 Maximo Cravero Baraja , Kaushik Bhattacharya

When dense granular gases are continuously excited under microgravity conditions, spatial inhomogeneities of the particle number density can emerge. A significant share of particles may collect in strongly overpopulated regions, called…

Soft Condensed Matter · Physics 2025-06-19 Sai Preetham Sata , Ralf Stannarius , Benjamin Noack , Dmitry Puzyrev

Deformation heterogeneities within microstructures of polycrystalline shape memory alloys (SMAs) during superelastic stressing are studied using both experiments and simulations. In situ X-ray diffraction, specifically the far-field high…

We study theoretically the dynamics of soft glassy materials during the process of stress relaxation following the rapid imposition of a shear strain. By detailed numerical simulations of a mesoscopic soft glassy rheology model and three…

Soft Condensed Matter · Physics 2019-07-15 Henry A. Lockwood , Matthew P. Carrington , Suzanne M. Fielding

The mechanical properties of complex concentrated alloys (CCAs) depend on their forming phases and corresponding structures, the prediction of the phase formation for a given CCA is essential to its discovery and applications. 541 sample…

Applied Physics · Physics 2025-11-07 Jie Xiong , San-Qiang Shi , Tong-Yi Zhang