Materials informatics for mechanical deformation: A review of applications and challenges
K Frydrych, K Karimi, M Pecelerowicz, R Alvarez… - Materials, 2021 - mdpi.com
In the design and development of novel materials that have excellent mechanical properties,
classification and regression methods have been diversely used across mechanical …
classification and regression methods have been diversely used across mechanical …
Advances of machine learning in materials science: Ideas and techniques
In this big data era, the use of large dataset in conjunction with machine learning (ML) has
been increasingly popular in both industry and academia. In recent times, the field of …
been increasingly popular in both industry and academia. In recent times, the field of …
Incorporating sparse model machine learning in designing cultural heritage landscapes
Managing, protecting, and the evolutionary development of historical landscapes require
robust frameworks and processes for forming datasets and advanced decision support tools …
robust frameworks and processes for forming datasets and advanced decision support tools …
Microstructure segmentation with deep learning encoders pre-trained on a large microscopy dataset
This study examined the improvement of microscopy segmentation intersection over union
accuracy by transfer learning from a large dataset of microscopy images called MicroNet …
accuracy by transfer learning from a large dataset of microscopy images called MicroNet …
Rapid and flexible segmentation of electron microscopy data using few-shot machine learning
Automatic segmentation of key microstructural features in atomic-scale electron microscope
images is critical to improved understanding of structure–property relationships in many …
images is critical to improved understanding of structure–property relationships in many …
Deep learning for electron and scanning probe microscopy: From materials design to atomic fabrication
Abstract Machine learning and artificial intelligence (ML/AI) are rapidly becoming an
indispensable part of physics research, with applications ranging from theory and materials …
indispensable part of physics research, with applications ranging from theory and materials …
Adaptable physics-based super-resolution for electron backscatter diffraction maps
In computer vision, single-image super-resolution (SISR) has been extensively explored
using convolutional neural networks (CNNs) on optical images, but images outside this …
using convolutional neural networks (CNNs) on optical images, but images outside this …
An automated scanning transmission electron microscope guided by sparse data analytics
M Olszta, D Hopkins, KR Fiedler, M Oostrom… - Microscopy and …, 2022 - cambridge.org
Artificial intelligence (AI) promises to reshape scientific inquiry and enable breakthrough
discoveries in areas such as energy storage, quantum computing, and biomedicine …
discoveries in areas such as energy storage, quantum computing, and biomedicine …
Detecting novel ototoxins and potentiation of ototoxicity by disease settings
Over 100 drugs and chemicals are associated with permanent hearing loss, tinnitus, and
vestibular deficits, collectively known as ototoxicity. The ototoxic potential of drugs is rarely …
vestibular deficits, collectively known as ototoxicity. The ototoxic potential of drugs is rarely …
Forecasting of in situ electron energy loss spectroscopy
NR Lewis, Y Jin, X Tang, V Shah, C Doty… - npj Computational …, 2022 - nature.com
Forecasting models are a central part of many control systems, where high-consequence
decisions must be made on long latency control variables. These models are particularly …
decisions must be made on long latency control variables. These models are particularly …