Computational and Machine Learning Techniques

Read this cutting-edge collection of articles and get up to speed with new advancements in the field!. View in Browser SUBMIT AN ARTICLE MANAGE MY ALERTS ABOUT THE JOURNAL Chemical Physics Reviews Cutting-Edge Research in Computational and Machine- Learning Techniques Predictions of materials properties and chemical processes are being significantly improved thanks to the cutting-edge computational methods and machine-learning techniques. Read this exciting collection of articles and get up to speed with new advancements in the field! Is your next article ready for submission? Get Read Researchers from nearly 4,000 institutions spanning 190+ countries read us online. SUBMIT AN ARTICLE Machine learning on neutron and x-ray scattering and spectroscopies Zhantao Chen, Nina Andrejevic, Nathan C. Drucker, Thanh Nguyen, et al. READ MORE > Hybrid QM/classical models: Methodological advances and new applications Filippo Lipparini, Benedetta Mennucci READ MORE > Structure–property correlations for analysis of heterogeneous electrocatalysts Elif Pınar Alsaç, Nataraju Bodappa, Alexander W. H. Whittingham, Yutong Liu, et al. READ MORE > Molecular library of OLED host materials—Evaluating the multiscale simulation workflow Anirban Mondal, Leanne Paterson, Jaeyoung Cho, Kun-Han Lin, et al. READ MORE > Ab initio methods for L-edge x-ray absorption spectroscopy Joseph M. Kasper, Torin F. Stetina, Andrew J. Jenkins, Xiaosong Li READ MORE > RELATED ARTICLES FROM APPLIED PHYSICS REVIEWS GRYFFIN: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge Florian Häse, Matteo Aldeghi, Riley J. Hickman, Loïc M. Roch, et al. Data-assisted polymer retrosynthesis planning Lihua Chen, Joseph Kern, Jordan P. Lightstone, Rampi Ramprasad Photonic tensor cores for machine learning Mario Miscuglio, Volker J. Sorger Featureless adaptive optimization accelerates functional electronic materials design Yiqun Wang, Akshay Iyer, Wei Chen, James M. Rondinelli Quantitative digital microscopy with deep learning Benjamin Midtvedt, Saga Helgadottir, Aykut Argun, Jesús Pineda, et al. Share on your social channels Follow us on social media   Copyright © 2022 AIP Publishing. All rights reserved. 1305 Walt Whitman Rd., Melville, NY 11747 You are receiving this email because you have opted-in to receive alerts from us. To guarantee delivery of this email please add journals@aip-info.org to your address book and safe senders list. If you no longer wish to receive emails from us then please unsubscribe or amend your settings.