Zobrazeno 1 - 10 of 45 pro vyhledávání: '"M C, Scott"'
1
Akademický článek
A robust synthetic data generation framework for machine learning in high-resolution transmission electron microscopy (HRTEM)
Autor: Luis Rangel DaCosta, Katherine Sytwu, C. K. Groschner, M. C. Scott
Publikováno v: npj Computational Materials, Vol 10, Iss 1, Pp 1-11 (2024)
Abstract Machine learning techniques are attractive options for developing highly-accurate analysis tools for nanomaterials characterization, including high-resolution transmission electron microscopy (HRTEM). However, successfully implementing such
Externí odkaz: https://doaj.org/article/06d22d94fd9449a49007bcefdb85c95e
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2
Akademický článek
One dimensional wormhole corrosion in metals
Autor: Yang Yang, Weiyue Zhou, Sheng Yin, Sarah Y. Wang, Qin Yu, Matthew J. Olszta, Ya-Qian Zhang, Steven E. Zeltmann, Mingda Li, Miaomiao Jin, Daniel K. Schreiber, Jim Ciston, M. C. Scott, John R. Scully, Robert O. Ritchie, Mark Asta, Ju Li, Michael P. Short, Andrew M. Minor
Publikováno v: Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)
Corrosion is a ubiquitous failure mode in materials. Here the authors report a percolating 1D wormhole corrosion morphology using advanced electron microscopy and theoretical simulations. The work presents a vacancy mapping method with nm-resolution,
Externí odkaz: https://doaj.org/article/275ee5021a4743068a9dc01ef61ef3bb
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3
Akademický článek
Classifying handedness in chiral nanomaterials using label error robust deep learning
Autor: C. K. Groschner, Alexander J. Pattison, Assaf Ben-Moshe, A. Paul Alivisatos, Wolfgang Theis, M. C. Scott
Publikováno v: npj Computational Materials, Vol 8, Iss 1, Pp 1-7 (2022)
Abstract High-throughput scanning electron microscopy (SEM) coupled with classification using neural networks is an ideal method to determine the morphological handedness of large populations of chiral nanoparticles. Automated labeling removes the ti
Externí odkaz: https://doaj.org/article/2c2a7f42e40a4d5485be4f1937d3156d
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4
Akademický článek
Robust design of semi-automated clustering models for 4D-STEM datasets
Autor: Alexandra Bruefach, Colin Ophus, M. C. Scott
Publikováno v: APL Machine Learning, Vol 1, Iss 1, Pp 016106-016106-7 (2023)
Materials discovery and design require characterizing material structures at the nanometer and sub-nanometer scale. Four-Dimensional Scanning Transmission Electron Microscopy (4D-STEM) resolves the crystal structure of materials, but many 4D-STEM dat
Externí odkaz: https://doaj.org/article/c875ad92918c4ac88ee7d89c1884a8a2
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6
Akademický článek
RETRACTED ARTICLE: Supported black phosphorus nanosheets as hydrogen-evolving photocatalyst achieving 5.4% energy conversion efficiency at 353 K
Autor: Bin Tian, Bining Tian, Bethany Smith, M. C. Scott, Ruinian Hua, Qin Lei, Yue Tian
Publikováno v: Nature Communications, Vol 9, Iss 1, Pp 1-11 (2018)
Abstract Solar-driven water splitting using powdered catalysts is considered as the most economical means for hydrogen generation. However, four-electron-driven oxidation half-reaction showing slow kinetics, accompanying with insufficient light absor
Externí odkaz: https://doaj.org/article/cc26625f876f4271a9a977b39e4dfce6
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7
Akademický článek
Phase-contrast imaging of multiply-scattering extended objects at atomic resolution by reconstruction of the scattering matrix
Autor: Philipp M. Pelz, Hamish G. Brown, Scott Stonemeyer, Scott D. Findlay, Alex Zettl, Peter Ercius, Yaqian Zhang, Jim Ciston, M. C. Scott, Colin Ophus
Publikováno v: Physical Review Research, Vol 3, Iss 2, p 023159 (2021)
Three-dimensional phase-contrast imaging of multiply-scattering samples in x-ray and electron microscopy is challenging due to small numerical apertures, the unavailability of wave front shaping optics, and the highly nonlinear inversion required fro
Externí odkaz: https://doaj.org/article/1378481ff34248f3b64a8dd72538eca6
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