RHEED pattern classification by a convolutional neural network for the growth of chalcogenide thin films and nanostructures

The use of reflection high-energy electron diffraction (RHEED) plays a critical role for in situ characterization in molecular beam epitaxy, pulsed laser deposition, and sputtering. While sensitive to crystal symmetries and morphology, it is used ubiquitously to determine the growth modes of thin fi...

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Detaylı Bibliyografya
Asıl Yazarlar:	Nathan Muetzel, Viet Luu, Sara Bey, Muhsin Abdul Karim, Kota Yoshimura, Xinyu Liu, Marwan Gebran, Badih A. Assaf
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	AIP Publishing LLC 2026-03-01
Seri Bilgileri:	AIP Advances
Online Erişim:	https://pubs.aip.org/aip/adv/article-pdf/doi/10.1063/5.0308043/20932478/035317_1_5.0308043.pdf
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RHEED pattern classification by a convolutional neural network for the growth of chalcogenide thin films and nanostructures

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