Artificial Intelligence for Crystal Growth and Characterization-Reference-Cited by-同舟云学术

Artificial Intelligence for Crystal Growth and Characterization

Published:2022-09-01 Issue:9 Volume:12 Page:1232
ISSN:2073-4352
Container-title:Crystals
language:en
Short-container-title:Crystals

Author:

Schimmel Saskia^ORCID,Sun Wenhao,Dropka Natasha^ORCID

Abstract

The Special Issue on “Artificial Intelligence for Crystal Growth and Characterization” comprises six original articles in this emerging field of research [...]

Publisher

MDPI AG

Subject

Inorganic Chemistry,Condensed Matter Physics,General Materials Science,General Chemical Engineering

Link

https://www.mdpi.com/2073-4352/12/9/1232/pdf

Reference7 articles.

1. FAIR data enabling new horizons for materials research

2. Crystal Structure Prediction of the Novel Cr2SiN4 Compound via Global Optimization, Data Mining, and the PCAE Method

3. Microstructure Representation Knowledge Graph to Explore the Twinning Formation

4. Real Time Predictions of VGF-GaAs Growth Dynamics by LSTM Neural Networks

5. Development and Optimization of VGF-GaAs Crystal Growth Process Using Data Mining and Machine Learning Techniques

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1. Exploring mc‐Silicon Wafers: Utilizing Machine Learning to Enhance Wafer Quality Through Etching Studies;Crystal Research and Technology;2024-02-29

2. A step forward in food science, technology and industry using artificial intelligence;Trends in Food Science & Technology;2024-01

3. Spiral growth of multicomponent crystals: theoretical aspects;Frontiers in Chemistry;2023-05-12

4. Monitoring MBE Substrate Deoxidation via RHEED Image-Sequence Analysis by Deep Learning;Crystal Growth & Design;2023-01-16