Machine-Learning Assisted Screening of Energetic Materials-Reference-Cited by-同舟云学术

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Machine-Learning Assisted Screening of Energetic Materials

Published:2020-06-08 Issue:26 Volume:124 Page:5341-5351
ISSN:1089-5639
Container-title:The Journal of Physical Chemistry A
language:en
Short-container-title:J. Phys. Chem. A

Author:

Kang Peng¹²^ORCID,Liu Zhongli¹,Abou-Rachid Hakima³,Guo Hong¹²

Affiliation:

1. Center for the Physics of Materials and Department of Physics, McGill University, Montreal, Quebec H3A 2T8, Canada

2. Nanoacademic Technologies Inc., Suite 802, 666 Sherbrooke West, Montreal, Quebec H3A 1E7, Canada

3. Defence Research and Development Canada, Valcartier, Quebec G3J 1X5, Canada

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpca.0c02647

Reference74 articles.

1. Materials informatics

2. Machine learning for molecular and materials science

3. Machine learning in materials informatics: recent applications and prospects

4. Materials informatics: From the atomic-level to the continuum

5. Materials Discovery and Design

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1. Predictive models for inorganic materials thermoelectric properties with machine learning;Machine Learning: Science and Technology;2024-09-01

2. Develop machine learning-based model and automated process for predicting liquid heat capacity of organics at different temperatures;Fluid Phase Equilibria;2024-09

3. Discovery of high-energy nitro-azolo-pyridine compounds with high-throughput computation and machine learning;Journal of Solid State Chemistry;2024-07

4. Kinetics of direct and water‐mediated tautomerization reactions of four‐membered cyclic lactims to amides or lactams;International Journal of Chemical Kinetics;2024-06-25

5. Advancements in methodologies and techniques for the synthesis of energetic materials: A review;Energetic Materials Frontiers;2024-06

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