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Phase contrast transmission electron microscopy (TEM) is a powerful tool for imaging the local atomic structure of materials. TEM has been used heavily in studies of defect structures of 2D materials such as monolayer graphene due to its…

Materials Science · Physics 2021-09-01 Robbie Sadre , Colin Ophus , Anstasiia Butko , Gunther H Weber

Vertical stacks of two-dimensional (2D) materials, separated by the van der Waals gap and held together by the van der Waals forces, are immensely promising for a plethora of nanotechnological applications. Charge control in these stacks…

Mesoscale and Nanoscale Physics · Physics 2018-11-08 Dhirendra Vaidya , Saurabh Lodha , Swaroop Ganguly

Predicting the properties of a material from the arrangement of its atoms is a fundamental goal in materials science. While machine learning has emerged in recent years as a new paradigm to provide rapid predictions of materials properties,…

Materials Science · Physics 2021-01-29 Chi Chen , Yunxing Zuo , Weike Ye , Xiangguo Li , Shyue Ping Ong

Investigating the polarization properties of light in the mid-infrared (mid-IR) spectrum is crucial for molecular sensing, biomedical diagnostics, and IR imaging system technologies. Traditional methods, limited by bulky size and intricate…

The recent isolation of two-dimensional (2D) magnets offers tantalizing opportunities for spintronics and magnonics at the limit of miniaturization. One of the key advantages of atomically-thin materials is their outstanding deformation…

Materials Science · Physics 2022-11-23 Dorye L. Esteras , Andrey Rybakov , Alberto M. Ruiz , José J. Baldoví

Accurate grain orientation mapping is essential for understanding and optimizing the performance of polycrystalline materials, particularly in energy-related applications. Lithium nickel oxide (LiNiO$_{2}$) is a promising cathode material…

Disordered Systems and Neural Networks · Physics 2025-11-26 Sebastian Wissel , Jonas Scheunert , Aaron Dextre , Shamail Ahmed , Andreas Bayer , Kerstin Volz , Bai-Xiang Xu

We demonstrate a machine learning approach designed to extract hidden chemistry/physics to facilitate new materials discovery. In particular, we propose a novel method for learning latent knowledge from material structure data in which…

Materials Science · Physics 2021-08-03 Tien-Cuong Nguyen , Van-Quyen Nguyen , Van-Linh Ngo , Quang-Khoat Than , Tien-Lam Pham

Material defects (MD) represent a primary challenge affecting product performance and giving rise to safety issues in related products. The rapid and accurate identification and localization of MD constitute crucial research endeavors in…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Jun Bai , Di Wu , Tristan Shelley , Peter Schubel , David Twine , John Russell , Xuesen Zeng , Ji Zhang

Freestanding van der Waals crystals made of single-atom carbon chains (carbynes) have been recently realized technologically. Here we investigate their electronic and optical properties experimentally, by continuous-wave and time-resolved…

Mesoscale and Nanoscale Physics · Physics 2025-10-22 Daniele Barettin , Stella V. Kavokina , Evgeny L. Ivchenko , Alexey V. Kavokin

Continual shrinking of pattern dimensions in the semiconductor domain is making it increasingly difficult to inspect defects due to factors such as the presence of stochastic noise and the dynamic behavior of defect patterns and types.…

Computer Vision and Pattern Recognition · Computer Science 2023-08-16 Vic De Ridder , Bappaditya Dey , Enrique Dehaerne , Sandip Halder , Stefan De Gendt , Bartel Van Waeyenberge

Modeling point defects at an atomic scale requires careful treatment of the long-range atomic relaxations. This elastic field can strongly affect point defect properties calculated in atomistic simulations because of the finite size of the…

Materials Science · Physics 2013-10-23 Céline Varvenne , Fabien Bruneval , Mihai-Cosmin Marinica , Emmanuel Clouet

Layered materials that stack different lattice symmetries are rare in nature. Misfit layered chalcogenides, which combine square and hexagonal lattices of rocksalt monochalcogenides and transition-metal dichalcogenides, provide a platform…

Determining the stability of chemical compounds is essential for advancing material discovery. In this study, we introduce a novel deep neural network model designed to predict a crystal's formation energy, which identifies its stability…

Materials Science · Physics 2026-04-21 V. Torlao , E. A. Fajardo

A method of scanning mid-IR-laser microscopy has recently been proposed for the investigation of large-scale electrically and recombination-active defects in semiconductors and non-destructive inspection of semiconductor materials and…

Materials Science · Physics 2011-05-17 O. V. Astafiev , V. P. Kalinushkin , V. A. Yuryev

Fast Radio Bursts (FRBs) are millisecond-duration radio transients of extragalactic origin, exhibiting a wide range of physical and observational properties. Distinguishing between repeating and non-repeating FRBs remains a key challenge in…

To coupe with the difficulties in the process of inspection and classification of defects in Printed Circuit Board (PCB), other researchers have proposed many methods. However, few of them published their dataset before, which hindered the…

Computer Vision and Pattern Recognition · Computer Science 2019-01-25 Weibo Huang , Peng Wei

Automated experiments in 4D Scanning Transmission Electron Microscopy are implemented for rapid discovery of local structures, symmetry-breaking distortions, and internal electric and magnetic fields in complex materials. Deep kernel…

Materials Science · Physics 2022-04-22 Kevin M. Roccapriore , Ondrej Dyck , Mark P. Oxley , Maxim Ziatdinov , Sergei V. Kalinin

The individual building blocks of van der Waals (vdW) heterostructures host fascinating physical phenomena, ranging from ballistic electron transport in graphene to striking optical properties of MoSe2 sheets. The presence of bonded and…

Disordered Systems and Neural Networks · Physics 2016-06-14 Nouamane Laanait , Zhan Zhang , Christian M. Schleputz , Ying Liu , Michael Wojcik , Rachael L. Myers-Ward , D. Kurt Gaskill , Paul Fenter , Lian Li

Integrated circuit manufacturing is highly complex, comprising hundreds of process steps. Defects can arise at any stage, causing yield loss and ultimately degrading product reliability. Supervised methods require extensive human annotation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-06 Botong. Zhao , Xubin. Wang , Shujing. Lyu , Yue. Lu

Solid-state quantum coherent devices are quickly progressing. Superconducting circuits, for instance, have already been used to demonstrate prototype quantum processors comprising a few tens of quantum bits. This development also revealed…

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