Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Machine learning-guided property prediction of energetic materials: Recent advances, challenges, and perspectives
Xiaolan Tian, Siwei Song, Fang Chen, et al.
Energetic Materials Frontiers (2022) Vol. 3, Iss. 3, pp. 177-186
Open Access | Times Cited: 50

Showing 1-25 of 50 citing articles:

Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry
Rizvi Syed Aal E Ali, Jiaolong Meng, Muhammad Ehtisham Ibraheem Khan, et al.
Artificial Intelligence Chemistry (2024) Vol. 2, Iss. 1, pp. 100049-100049
Open Access | Times Cited: 25
Synthesis, design and development of energetic materials: Quo Vadis?
Nikita V. Muravyev, Леонид Л. Ферштат, Qinghua Zhang
Chemical Engineering Journal (2024) Vol. 486, pp. 150410-150410
Closed Access | Times Cited: 22
LSTM-BP neural network analysis on solid-liquid phase change in a multi-channel thermal storage tank
Tian Xiao, Zhengguang Liu, Liu Lu, et al.
Engineering Analysis with Boundary Elements (2022) Vol. 146, pp. 226-240
Closed Access | Times Cited: 59
Which molecular properties determine the impact sensitivity of an explosive? A machine learning quantitative investigation of nitroaromatic explosives
Júlio César Duarte, Romulo Dias da Rocha, Itamar Borges
Physical Chemistry Chemical Physics (2023) Vol. 25, Iss. 9, pp. 6877-6890
Open Access | Times Cited: 24
Dual-channel MIRECL portable devices with impedance effect coupled smartphone and machine learning system for tyramine identification and quantification
Zhiwei Lu, Jun Qin, Wu Chun, et al.
Food Chemistry (2023) Vol. 429, pp. 136920-136920
Closed Access | Times Cited: 19
Machine learning based technique for outlier detection and result prediction in combustion diagnostics
Mingfei Chen, Kaile Zhou, Dong Liu
Energy (2024) Vol. 290, pp. 130218-130218
Closed Access | Times Cited: 7
Energetic 1,2,4-oxadiazoles: synthesis and properties
Alexander V. Shaferov, Леонид Л. Ферштат
Russian Chemical Reviews (2024) Vol. 93, Iss. 2, pp. RCR5109-RCR5109
Closed Access | Times Cited: 7
Insights into Preparation Methods and Functions of Carbon-Based Solid Acids
Shu Dong, Jian Zhang, Roger Ruan, et al.
Molecules (2024) Vol. 29, Iss. 1, pp. 247-247
Open Access | Times Cited: 6
Explainable AI for Material Property Prediction Based on Energy Cloud: A Shapley-Driven Approach
Faiza Qayyum, Murad Ali Khan, Do‐Hyeun Kim, et al.
Materials (2023) Vol. 16, Iss. 23, pp. 7322-7322
Open Access | Times Cited: 13
Machine Learning Determination of New Hammett’s Constants for meta- and para-Substituted Benzoic Acid Derivatives Employing Quantum Chemical Atomic Charge Methods
Gabriel Monteiro‐de‐Castro, Júlio César Duarte, Itamar Borges
The Journal of Organic Chemistry (2023) Vol. 88, Iss. 14, pp. 9791-9802
Open Access | Times Cited: 12
QSPR models for sublimation enthalpy of energetic compounds
Rui Liu, Yuechuan Tang, Jie Tian, et al.
Chemical Engineering Journal (2023) Vol. 474, pp. 145725-145725
Closed Access | Times Cited: 11
Machine learning-assisted quantitative prediction of thermal decomposition temperatures of energetic materials and their thermal stability analysis
Zhixiang Zhang, Yilin Cao, Chao Chen, et al.
Energetic Materials Frontiers (2023)
Open Access | Times Cited: 11
Fluorescence sensor array based on covalent organic frameworks and QSAR study for identification of organic pesticides
Fangxia An, Fang Li, Shengyuan Deng, et al.
Microchemical Journal (2025), pp. 112986-112986
Closed Access
EM-HyChem: Bridging molecular simulations and chemical reaction neural network-enabled approach to modelling energetic material chemistry
Xinzhe Chen, Yabei Xu, Mingjie Wen, et al.
Combustion and Flame (2025) Vol. 275, pp. 114065-114065
Closed Access
Research on GWP Prediction Using Genetic Algorithm and Neural Network
Dongwei Sun, Weipeng Lai, Yiding Ma, et al.
Lecture notes in electrical engineering (2025), pp. 106-123
Closed Access
Modeling the Performance of Energetic Materials
Mohammad Hossein Keshavarz
Challenges and advances in computational chemistry and physics (2025), pp. 311-337
Closed Access
2D flame temperature and soot concentration reconstruction from partial discrete data via machine learning: A case study
Mingfei Chen, R. Zheng, Xuan Zhao, et al.
Case Studies in Thermal Engineering (2025), pp. 106005-106005
Open Access
Harnessing machine learning enabled quickly predicting density of CHON molecules for discovering new energetic materials
Ruoxu Zong, Zi Li, Ziyu Hu, et al.
AIP Advances (2025) Vol. 15, Iss. 4
Open Access
Artificial Intelligence Approaches for Energetic Materials by Design: State of the Art, Challenges, and Future Directions
Joseph B. Choi, Phong Nguyen, Oishik Sen, et al.
Propellants Explosives Pyrotechnics (2023) Vol. 48, Iss. 4
Open Access | Times Cited: 10
Machine learning-assisted design of Al2O3–SiO2 porous ceramics based on few-shot datasets
Zhenhao Sun, Nanyan Hu, Lihua Ke, et al.
Ceramics International (2023) Vol. 49, Iss. 18, pp. 29400-29408
Closed Access | Times Cited: 10
Insight into melting point differences of dinitroimidazoles and dinitropyrazoles from the perspective of intermolecular interactions
Junnan Wu, Siwei Song, Xiujuan Qi, et al.
Physical Chemistry Chemical Physics (2024) Vol. 26, Iss. 5, pp. 4752-4758
Closed Access | Times Cited: 3
Optimized design of composition and brazing process for Cu-Ag-Zn-Mn-Ni-Si-B-P alloy brazing material based on machine learning strategy to improve brazing properties
Jiheng Fang, Ming Xie, Jiming Zhang, et al.
Materials Today Communications (2024) Vol. 39, pp. 109317-109317
Closed Access | Times Cited: 3
Burning Rate Prediction of Solid Rocket Propellant (SRP) with High-Energy Materials Genome (HEMG)
Weiqiang Pang, Victor S. Abrukov, Darya A. Anufrieva, et al.
Crystals (2023) Vol. 13, Iss. 2, pp. 237-237
Open Access | Times Cited: 7
Machine learning-based prediction and interpretation of decomposition temperatures of energetic materials
Junnan Wu, Siwei Song, Xiaolan Tian, et al.
Energetic Materials Frontiers (2023) Vol. 4, Iss. 4, pp. 254-261
Open Access | Times Cited: 7
Develop machine learning-based model and automated process for predicting liquid heat capacity of organics at different temperatures
Yuqing Shan, Qingxing Wu, Hua Yuan, et al.
Fluid Phase Equilibria (2024) Vol. 584, pp. 114132-114132
Closed Access | Times Cited: 2
Page 1 - Next Page

Scroll to top