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Characterization of structural diversity within soft materials is key for engineering new materials for various applications. Small-angle scattering (SAS) is a widely used characterization technique that provides structural information in…

Soft Condensed Matter · Physics 2024-03-29 Sri Vishnuvardhan Reddy Akepati , Nitant Gupta , Arthi Jayaraman

In material research, structural characterization often requires multiple complementary techniques to obtain a holistic morphological view of the synthesized material. Depending on the availability of and accessibility of the different…

Soft Condensed Matter · Physics 2023-05-29 Shizhao Lu , Arthi Jayaraman

In this paper, five different approaches for reduced-order modeling of brittle fracture in geomaterials, specifically concrete, are presented and compared. Four of the five methods rely on machine learning (ML) algorithms to approximate…

Computational Engineering, Finance, and Science · Computer Science 2018-06-07 A. Hunter , B. A. Moore , M. K. Mudunuru , V. T. Chau , R. L. Miller , R. B. Tchoua , C. Nyshadham , S. Karra , D. O. Malley , E. Rougier , H. S. Viswanathan , G. Srinivasan

The electronic properties of two-dimensional (2D) materials depend sensitively on the underlying atomic arrangement down to the monolayer level. Here we present a novel strategy for the determination of the band gap and complex dielectric…

The virtual element method (VEM) allows discretization of the problem domain with polygons in 2D. The polygons can have an arbitrary number of sides and can be concave or convex. These features, among others, are attractive for meshing…

Numerical Analysis · Mathematics 2023-10-06 L. L. Yaw

Properties of crystalline materials are closely linked to microstructure arising from the spatial arrangement, orientation, and phase of nanocrystals. Rapid characterization of crystalline microstructure can accelerate the identification of…

Materials Science · Physics 2026-02-16 Kwanghwi Je , Ellis R. Kennedy , Sungin Kim , Yao Yang , Erik H. Thiede

Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here we…

This thesis explores the application of the Symmetry-Breaking/Symmetry-Restoration methodology on quantum computers to better approximate a Hamiltonian's ground state energy within a variational framework in many-body physics. This involves…

Quantum Physics · Physics 2023-11-10 Andres Ruiz

Symmetry is a cornerstone of quantum mechanics and materials theory, underpinning the classification of electronic states and the emergence of complex phenomena such as magnetism and superconductivity. While symmetry breaking in density…

Recent advances in materials discovery have been driven by structure-based models, particularly those using crystal graphs. While effective for computational datasets, these models are impractical for real-world applications where atomic…

Machine Learning · Computer Science 2025-07-03 Jithendaraa Subramanian , Linda Hung , Daniel Schweigert , Santosh Suram , Weike Ye

Current generative models struggle to synthesize dynamic 4D driving scenes that simultaneously support temporal extrapolation and spatial novel view synthesis (NVS) without per-scene optimization. A key challenge lies in finding an…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Jiazhe Guo , Yikang Ding , Xiwu Chen , Shuo Chen , Bohan Li , Yingshuang Zou , Xiaoyang Lyu , Feiyang Tan , Xiaojuan Qi , Zhiheng Li , Hao Zhao

The performance of electron energy-loss spectrometers can often be limited by their electron-optical aberrations. Due to recent developments in high energy-resolution and momentum-resolved electron energy loss spectroscopy (EELS), there is…

Materials Science · Physics 2023-02-28 Yueming Guo , Andrew R. Lupini

We establish a series of deep convolutional neural networks to automatically analyze position averaged convergent beam electron diffraction patterns. The networks first calibrate the zero-order disk size, center position, and rotation…

Data Analysis, Statistics and Probability · Physics 2018-06-05 Weizong Xu , James M. LeBeau

Here a new microscopic method is proposed to image and characterize very thin samples like few-layer materials, organic molecules, and nanostructures with nanometer or sub-nanometer resolution using electron beams of energies lower than 20…

Instrumentation and Detectors · Physics 2016-01-06 Ing-Shouh Hwang

The dynamic of complex ordering systems with active rotational degrees of freedom exemplified by protein self-assembly is explored using a machine learning workflow that combines deep learning-based semantic segmentation and rotationally…

Soft Condensed Matter · Physics 2021-04-26 Sergei V. Kalinin , Shuai Zhang , Mani Valleti , Harley Pyles , David Baker , James J. De Yoreo , Maxim Ziatdinov

The nature of the atomic defects on the hydrogen passivated Si (100) surface is analyzed using deep learning and scanning tunneling microscopy (STM). A robust deep learning framework capable of identifying atomic species, defects, in the…

Materials Science · Physics 2020-02-19 Maxim Ziatdinov , Udi Fuchs , James H. G. Owen , John N. Randall , Sergei V. Kalinin

Symmetry in differential equations reveals invariances and offers a powerful means to reduce model complexity. Lie group analysis characterizes these symmetries through infinitesimal generators, which provide a local, linear criterion for…

Numerical Analysis · Mathematics 2025-11-14 Max Kreider , John Harlim , Daning Huang

A real-time image reconstruction method for scanning transmission electron microscopy (STEM) is proposed. With an algorithm requiring only the center of mass (COM) of the diffraction pattern at one probe position at a time, it is able to…

Materials Science · Physics 2021-12-15 Chu-Ping Yu , Thomas Friedrich , Daen Jannis , Sandra Van Aert , Johan Verbeeck

Layout design with complex constraints is a challenging problem to solve due to the non-uniqueness of the solution and the difficulties in incorporating the constraints into the conventional optimization-based methods. In this paper, we…

Signal Processing · Electrical Eng. & Systems 2018-06-11 Yujie Zhang , Wenjing Ye

An effective way to model the complex real world is to view the world as a composition of basic components of objects and transformations. Although humans through development understand the compositionality of the real world, it is…

Computer Vision and Pattern Recognition · Computer Science 2022-03-23 T. Takada , W. Shimaya , Y. Ohmura , Y. Kuniyoshi
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