English
Related papers

Related papers: Towards Automating Structural Discovery in Scannin…

200 papers

Electrochemistry is the underlying mechanism in a variety of energy conversion and storage systems, and it is well known that the composition, structure, and properties of electrochemical materials near active interfaces often deviates…

Materials Science · Physics 2018-02-07 Ahmad Eshghinejad , Ehsan Nasr Esfahani , Chihou Lei , Jiangyu Li

Controlling crystalline material defects is crucial, as they affect properties of the material that may be detrimental or beneficial for the final performance of a device. Defect analysis on the sub-nanometer scale is enabled by…

Materials Science · Physics 2021-06-03 Nik Dennler , Antonio Foncubierta-Rodriguez , Titus Neupert , Marilyne Sousa

Constructing of molecular structural models from Cryo-Electron Microscopy (Cryo-EM) density volumes is the critical last step of structure determination by Cryo-EM technologies. Methods have evolved from manual construction by structural…

Machine Learning · Computer Science 2019-02-13 Kui Xu , Zhe Wang , Jiangping Shi , Hongsheng Li , Qiangfeng Cliff Zhang

State-of-the-art electron microscopes such as scanning electron microscopes (SEM), scanning transmission electron microscopes (STEM) and transmission electron microscopes (TEM) have become increasingly sophisticated. However, the quality of…

Computational Physics · Physics 2023-03-31 I. Lobato , T. Friedrich , S. Van Aert

Transmission electron diffraction is a powerful and versatile structural probe for the characterization of a broad range of materials, from nanocrystalline thin films to single crystals. With recent developments in fast electron detectors…

Materials Science · Physics 2021-10-06 Jian-Min Zuo , Renliang Yuan , Yu-Tsun Shao , Haw-Wen Hsiao , Saran Pidaparthy , Yang Hu , Qun Yang , Jiong Zhang

Autonomous experimentation systems have been used to greatly advance the integrated computational materials engineering (ICME) paradigm. This paper outlines a framework that enables the design and selection of data collection workflows for…

Materials Science · Physics 2022-06-20 Rohan Casukhela , Sriram Vijayan , Joerg R. Jinschek , Stephen R. Niezgoda

Characterizing materials using electron micrographs is crucial in areas such as semiconductors and quantum materials. Traditional classification methods falter due to the intricatestructures of these micrographs. This study introduces an…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Sakhinana Sagar Srinivas , Geethan Sannidhi , Sreeja Gangasani , Chidaksh Ravuru , Venkataramana Runkana

Instrumentation developments in electron energy-loss spectroscopy (EELS) in the scanning transmission electron microscope (STEM) one decade ago paved the way for combining milli-electronvolt energy resolution in spectroscopy with…

Mesoscale and Nanoscale Physics · Physics 2024-10-15 Benedikt Haas , Christoph T. Koch , Peter Rez

Fluid ferroelectrics, a recently discovered class of liquid crystals that exhibit switchable, long-range polar order, offer opportunities in ultrafast electro-optic technologies, responsive soft matter, and next-generation energy materials.…

To solve large-scale or high-resolution topology optimization problem, a novel algorithm is developed based on modified bi-directional evolutionary structure optimization (BESO) and extended finite element method (XFEM). Within XFEM, a set…

Applied Physics · Physics 2026-04-07 Hongxin Wang , Jie Liu , Guilin Wen

As computers get faster, researchers -- not hardware or algorithms -- become the bottleneck in scientific discovery. Computational study of colloidal self-assembly is one area that is keenly affected: even after computers generate massive…

Soft Condensed Matter · Physics 2018-03-28 Matthew Spellings , Sharon C Glotzer

Scanning Transmission Electron Microscopy (STEM) has enabled mapping of atomic structures of solids with sub-pm precision, providing insight to the physics of ferroic phenomena and chemical expansion. However, only a subset of information…

Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since these complex models may have difficultly learning physical…

Image and Video Processing · Electrical Eng. & Systems 2019-12-13 James P. Horwath , Dmitri N. Zakharov , Remi Megret , Eric A. Stach

Electronic materials exhibiting phase transitions between metastable states (e.g., metal-insulator transition materials with abrupt electrical resistivity transformations) are challenging to decode. For these materials, conventional machine…

Materials Science · Physics 2020-11-09 Yiqun Wang , Akshay Iyer , Wei Chen , James M. Rondinelli

Epitaxial growth has become a promising route to achieve highly crystalline continuous two-dimensional layers. However, high-quality layer production with expected electrical properties is still challenging due to the defects induced by the…

Spatial confinement of matter in functional nanostructures has propelled these systems to the forefront of nanoscience, both as a playground for exotic physics and quantum phenomena and in multiple applications including plasmonics,…

Spatial transcriptomics (ST) enables the visualization of gene expression within the context of tissue morphology. This emerging discipline has the potential to serve as a foundation for developing tools to design precision medicines.…

Image and Video Processing · Electrical Eng. & Systems 2024-11-12 Shivam Kumar , Samrat Chatterjee

Understanding the relationship between atomic structure (order) and chemical composition (chemistry) is critical for advancing materials science, yet traditional spectroscopic techniques can be slow and damaging to sensitive samples.…

Materials Science · Physics 2025-08-29 Mridul Kumar , Yevgeny Rakita

Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these areas, new electrochemical…

The advent of material databases provides an unprecedented opportunity to uncover predictive descriptors for emergent material properties from vast data space. However, common reliance on high-throughput ab initio data necessarily inherits…