BetaCitation Atlas

RESEARCH PAPER · Chemometrics and Intelligent Laboratory Systems · 2021

Probing impact of molecular structure on bulk modulus and impact sensitivity of energetic materials by machine learning methods

Qianqian Deng, Jing Hu, Liying Wang, Yijing Liu, Yanzhi Guo, Tao Xu, Xuemei Pu

Read original paper ↗

See where this research leads.

25 direct citing papers in this saved network. Explore the next layer with second-order citations.

Open in your workspace →Saved 2026-10-14 · complete coverage
Filter Citing Papers
Press Enter or comma to add · × to remove · searches titles and available abstracts
Journals
All journals
Most represented first · select one or more
Explore Terms In These PapersHide SuggestionsShow Suggestions

Original and current center papers stay visible as anchors.
Numbers show citations received
42 direct citing works

Probing impact of molecular structure on bulk modulus and impact sensitivity of energetic materials by machine learning methodsOriginalCan a shock-induced phonon up-pumping model relate to impact sensitivity of molecular crystals, polymorphs and cocrystals?19HATS5m as an Example of GETAWAY Molecular Descriptor in Assessing the Similarity/Diversity of the Structural Features of 4-Thiazolidinone5Recent Progress on Synthesis, Characterization, and Performance of Energetic Cocrystals: A Review36Machine learning-guided property prediction of energetic materials: Recent advances, challenges, and perspectives92Prediction and Construction of Energetic Materials Based on Machine Learning Methods53Prediction of impact sensitivity, heat of formation and heat of explosion using atomic connectivity3Which molecular properties determine the impact sensitivity of an explosive? A machine learning quantitative investigation of nitroaromatic explosives34Modélisation de la décomposition des matériaux énergétiques et de leurs sensibilités0Neural Network Prediction Model of Cocrystal Melting Temperature Based on Molecular Descriptors and Graphs15Searching for the analogues of 1,1-dinitro-2,2-diamino ethylene (FOX-7) by high-throughput computation and machine learning11Machine learning for shock compression of solids using scarce data1Identifying the determining factors of detonation properties for linear nitroaliphatics with high-throughput computation and machine learning13Discovery of high energy and stable prismane derivatives by the high-throughput computation and machine learning combined strategy9Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry93Discovery of high-energy nitro-azolo-pyridine compounds with high-throughput computation and machine learning2Modeling High Energy Molecules and Screening to Find Novel High Energy Candidates2Evaluating the impact sensitivity of energetic materials using inelastic neutron scattering and low frequency THz-Raman spectroscopies2Understanding impact sensitivity of energetic molecules by supervised machine learning9Predicting the Mutagenic Activity of Nitroaromatics Using Conceptual Density Functional Theory Descriptors and Explainable No-Code Machine Learning Approaches7Construction of reliable QSPR models for predicting the impact sensitivity of nitroenergetic compounds using correlation weights of the fragments of molecular structures6Machine-learning-driven QSPR models for energetic molecules: A review on safety and energetic properties prediction13High-pressure behavior of energetic metal-organic frameworks: A first-principles study1AI/ML Enabled High‐Throughput Design and Synthesis for Energetic Molecules0Deep learning-based QSPR for predicting impact sensitivity of energetic nitro compounds0Research progress of molecular perovskite as a new platform for multicomponent energetic crystals0

Arrows point to the paper being cited. Selecting a paper shows its incoming citations and its known path back to the original paper.

Drag to pan · Use + / − to zoom · Escape to close43 nodes / 53 citation links
Browse Matching Papers

Papers that cite this work

25 direct citing papers saved.

  1. Can a shock-induced phonon up-pumping model relate to impact sensitivity of molecular crystals, polymorphs and cocrystals?

    RSC Advances · 2022-01-01

    Xavier Bidault, Santanu Chaudhuri

    Read original paper ↗ ·

  2. HATS5m as an Example of GETAWAY Molecular Descriptor in Assessing the Similarity/Diversity of the Structural Features of 4-Thiazolidinone

    International Journal of Molecular Sciences · 2022-06-12

    Mariusz Zapadka, Przemysław Dekowski, Bogumiła Kupcewicz

    Read original paper ↗ ·

  3. Recent Progress on Synthesis, Characterization, and Performance of Energetic Cocrystals: A Review

    Molecules · 2022-07-26

    Manzoor Sultan, Junying Wu, Ihtisham Ul Haq, Muhammad Imran, Lijun Yang, JiaoJiao Wu, JiaoJiao Wu, Lang Chen

    Read original paper ↗ ·

  4. Machine learning-guided property prediction of energetic materials: Recent advances, challenges, and perspectives

    Energetic Materials Frontiers · 2022-08-18

    Xiaolan Tian, Siwei Song, Fang Chen, Xiujuan Qi, Yi Wang, Qinghua Zhang

    Read original paper ↗ ·

  5. Prediction and Construction of Energetic Materials Based on Machine Learning Methods

    Molecules · 2022-12-31

    Xiaowei Zang, Xiang Zhou, Haitao Bian, Weiping Jin, Xuhai Pan, Juncheng Jiang, M. Yu. Koroleva, Ruiqi Shen

    Read original paper ↗ ·

  6. Prediction of impact sensitivity, heat of formation and heat of explosion using atomic connectivity

    AIP conference proceedings · 2023-01-01

    Jack V. Davis, Frank W. Marrs, Alexandra C. Burch, Nicholas Lease, Marc J. Cawkwell, Virginia W. Manner

    Read original paper ↗ ·

  7. Which molecular properties determine the impact sensitivity of an explosive? A machine learning quantitative investigation of nitroaromatic explosives

    Physical Chemistry Chemical Physics · 2023-01-01

    Júlio César Duarte, Romulo Dias da Rocha, Itamar Borges

    Read original paper ↗ ·

  8. Modélisation de la décomposition des matériaux énergétiques et de leurs sensibilités

    Unknown journal · 2023-02-16

    Romain Claveau

    Read original paper ↗ ·

  9. Neural Network Prediction Model of Cocrystal Melting Temperature Based on Molecular Descriptors and Graphs

    Crystal Growth & Design · 2023-02-27

    Hong Yue, Jingtao Wang, Meijin Lu

    Read original paper ↗ ·

  10. Searching for the analogues of 1,1-dinitro-2,2-diamino ethylene (FOX-7) by high-throughput computation and machine learning

    FirePhysChem · 2023-04-06

    Wen Hui Qian, Jing Huang, Shitai Guo, Bowen Duan, Weiyu Xie, Jian Liu, Chaoyang Zhang

    Read original paper ↗ ·

  11. Machine learning for shock compression of solids using scarce data

    Journal of Applied Physics · 2023-04-21

    Sangeeth Balakrishnan, Francis G. VanGessel, Brian C. Barnes, Ruth M. Doherty, William H. Wilson, Zois Boukouvalas, Mark Fuge, Peter W. Chung

    Read original paper ↗ ·

  12. Identifying the determining factors of detonation properties for linear nitroaliphatics with high-throughput computation and machine learning

    Energetic Materials Frontiers · 2023-05-26

    Wen Hui Qian, Jing Huang, Shitai Guo, Bowen Duan, Weiyu Xie, Jian Liu, Chaoyang Zhang

    Read original paper ↗ ·

  13. Discovery of high energy and stable prismane derivatives by the high-throughput computation and machine learning combined strategy

    FirePhysChem · 2023-07-06

    Shitai Guo, Jing Huang, Wen Hui Qian, Jian Liu, Weihua Zhu, Chaoyang Zhang

    Read original paper ↗ ·

  14. Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry

    Artificial Intelligence Chemistry · 2024-01-18

    Rizvi Syed Aal E Ali, Jiaolong Meng, Muhammad Ehtisham Ibraheem Khan, Xuefeng Jiang

    Read original paper ↗ ·

  15. Discovery of high-energy nitro-azolo-pyridine compounds with high-throughput computation and machine learning

    Journal of Solid State Chemistry · 2024-04-09

    Wen Hui Qian

    Read original paper ↗ ·

  16. Modeling High Energy Molecules and Screening to Find Novel High Energy Candidates

    ACS Omega · 2024-10-11

    Mazal Rachamim, Abraham Jacob Domb, Amiram Goldblum

    Read original paper ↗ ·

  17. Evaluating the impact sensitivity of energetic materials using inelastic neutron scattering and low frequency THz-Raman spectroscopies

    Physical Chemistry Chemical Physics · 2025-01-01

    Adam A. L. Michalchuk∞, Carole A. Morrison, Colin R. Pulham, Svemir Rudić

    Read original paper ↗ ·

  18. Understanding impact sensitivity of energetic molecules by supervised machine learning

    Digital Discovery · 2025-01-01

    Heather M. Quayle, Karthik Mohan, Sohan Seth, Colin R. Pulham, Carole A. Morrison

    Read original paper ↗ ·

  19. Predicting the Mutagenic Activity of Nitroaromatics Using Conceptual Density Functional Theory Descriptors and Explainable No-Code Machine Learning Approaches

    Journal of Chemical Information and Modeling · 2025-02-27

    Andrés Halabi Díaz, Mario Duque‐Noreña, Elizabeth Rincón, Eduardo E. Chamorro

    Read original paper ↗ ·

  20. Construction of reliable QSPR models for predicting the impact sensitivity of nitroenergetic compounds using correlation weights of the fragments of molecular structures

    Scientific Reports · 2025-04-01

    Shahram Lotfi, Shahin Ahmadi, Alla P. Toropova, Andrey Andreevich Toropov

    Read original paper ↗ ·

  21. Machine-learning-driven QSPR models for energetic molecules: A review on safety and energetic properties prediction

    Chemical Engineering Journal Advances · 2025-07-03

    Mingchi Gao, Tengxin Huang, Mingtian Li, Yingjun Zhang, Liangliang Wang, Junjie Ding

    Read original paper ↗ ·

  22. High-pressure behavior of energetic metal-organic frameworks: A first-principles study

    Computational Materials Science · 2025-12-11

    Mustafa Erkartal

    Read original paper ↗ ·

  23. AI/ML Enabled High‐Throughput Design and Synthesis for Energetic Molecules

    Materials Genome Engineering Advances · 2026-05-19

    Wen Hui Qian

    Read original paper ↗ ·

  24. Deep learning-based QSPR for predicting impact sensitivity of energetic nitro compounds

    Molecular Physics · 2026-05-27

    Yali Xu, Lu Jiang, Jie Li, Zhengjun Fang, Jianxia Qiu

    Read original paper ↗ ·

  25. Research progress of molecular perovskite as a new platform for multicomponent energetic crystals

    Energetic Materials Frontiers · 2026-09-01

    Feng Gu, Ji Jun Xiao

    Read original paper ↗ ·
Citation Atlas · A map of research, not a ranking.