![β-Fragmentation of Primary Alkoxyl Radicals versus Hydrogen Abstraction: Synthesis of Polyols and α,ω-Differently Substituted Cyclic Ethers from Carbohydrates | The Journal of Organic Chemistry β-Fragmentation of Primary Alkoxyl Radicals versus Hydrogen Abstraction: Synthesis of Polyols and α,ω-Differently Substituted Cyclic Ethers from Carbohydrates | The Journal of Organic Chemistry](https://pubs.acs.org/cms/10.1021/jo034442f/asset/images/large/jo034442fn00001.jpeg)
β-Fragmentation of Primary Alkoxyl Radicals versus Hydrogen Abstraction: Synthesis of Polyols and α,ω-Differently Substituted Cyclic Ethers from Carbohydrates | The Journal of Organic Chemistry
![NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J](https://pubs.rsc.org/image/article/2019/CP/c9cp02803j/c9cp02803j-f1_hi-res.gif)
NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J
![NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J](https://pubs.rsc.org/image/article/2019/CP/c9cp02803j/c9cp02803j-f4_hi-res.gif)
NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J
![Anti-Inflammatory Therapy With Canakinumab for the Prevention of Hospitalization for Heart Failure | Circulation Anti-Inflammatory Therapy With Canakinumab for the Prevention of Hospitalization for Heart Failure | Circulation](https://www.ahajournals.org/cms/asset/2cdbab2c-eedd-418e-ba3b-1f28b0461332/1289fig03.gif)
Anti-Inflammatory Therapy With Canakinumab for the Prevention of Hospitalization for Heart Failure | Circulation
![A Data Mining-based Prognostic Algorithm for NAFLD-related Hepatoma Patients: A Nationwide Study by the Japan Study Group of NAFLD | Scientific Reports A Data Mining-based Prognostic Algorithm for NAFLD-related Hepatoma Patients: A Nationwide Study by the Japan Study Group of NAFLD | Scientific Reports](https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41598-018-28650-0/MediaObjects/41598_2018_28650_Fig1_HTML.jpg)
A Data Mining-based Prognostic Algorithm for NAFLD-related Hepatoma Patients: A Nationwide Study by the Japan Study Group of NAFLD | Scientific Reports
![NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J](https://pubs.rsc.org/image/article/2019/CP/c9cp02803j/c9cp02803j-f2_hi-res.gif)
NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J
![NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J](https://pubs.rsc.org/image/article/2019/CP/c9cp02803j/c9cp02803j-f8_hi-res.gif)
NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J
![Performance and Cost Assessment of Machine Learning Interatomic Potentials | The Journal of Physical Chemistry A Performance and Cost Assessment of Machine Learning Interatomic Potentials | The Journal of Physical Chemistry A](https://pubs.acs.org/cms/10.1021/acs.jpca.9b08723/asset/images/medium/jp9b08723_0009.gif)
Performance and Cost Assessment of Machine Learning Interatomic Potentials | The Journal of Physical Chemistry A
![NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J](https://pubs.rsc.org/image/article/2019/CP/c9cp02803j/c9cp02803j-f5_hi-res.gif)
NMR shifts in aluminosilicate glasses via machine learning - Physical Chemistry Chemical Physics (RSC Publishing) DOI:10.1039/C9CP02803J
![First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library](https://onlinelibrary.wiley.com/cms/asset/64d05967-95be-4a7d-a49b-fb28f633cc9b/anie201703114-fig-0007-m.jpg)
First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library
![First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library](https://onlinelibrary.wiley.com/cms/asset/3d2af2b2-d15b-4464-9da9-dbd230c4f270/anie201703114-fig-0008-m.jpg)
First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library
![First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library](https://onlinelibrary.wiley.com/cms/asset/7e247fdb-0a9b-48c7-87e8-59ccfd67fbcf/anie201703114-fig-0011-m.jpg)
First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library
![Pushing the boundaries of lithium battery research with atomistic modelling on different scales - IOPscience Pushing the boundaries of lithium battery research with atomistic modelling on different scales - IOPscience](https://cf-images.eu-west-1.prod.boltdns.net/v1/jit/105920850001/96239965-7989-4f35-b3da-f45087829774/main/1280x720/1m56s961ms/match/image.jpg)
Pushing the boundaries of lithium battery research with atomistic modelling on different scales - IOPscience
Evaluating Polymer Representations via Quantifying Structure–Property Relationships | Journal of Chemical Information and Modeling
![First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library](https://onlinelibrary.wiley.com/cms/asset/98d9c2cd-afd1-46e0-9511-b024c6da8584/anie201703114-toc-0001-m.png)
First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems - Behler - 2017 - Angewandte Chemie International Edition - Wiley Online Library
![Pushing the boundaries of lithium battery research with atomistic modelling on different scales - IOPscience Pushing the boundaries of lithium battery research with atomistic modelling on different scales - IOPscience](https://cfn-live-content-bucket-iop-org.s3.amazonaws.com/journals/2516-1083/4/1/012002/revision4/prgeac3894f8_hr.jpg?AWSAccessKeyId=AKIAYDKQL6LTV7YY2HIK&Expires=1676473751&Signature=lFSISUicCUoBPlD%2FXQpyZETGtXA%3D)