Discovery of high energy and stable prismane derivatives by the high-throughput computation and machine learning combined strategy DOI Creative Commons
Shitai Guo, Jing Huang, Wen Qian

et al.

FirePhysChem, Journal Year: 2023, Volume and Issue: 4(1), P. 55 - 62

Published: July 6, 2023

Motivated by the excellent detonation performance of octanitrocubane, prismane is another potential backbone with high strain energy in energetic molecule design. In this work, we aim to screen out candidates highly molecules from space derivatives. The high-throughput computation (HTC) performed based on 200 derived 1503 derivatives four substituents. Based calculated results, machine learning (ML) models density, velocity, pressure, heat formation and are established, thereby performances remaining 1303 samples predicted. It found that –NHNO2 group increases while both –NO2 –C(NO2)3 groups promote performances. velocity bond dissociation as criteria representing molecular stability, were screened good acceptable thermal stability. This work demonstrates efficiency HTC ML combined strategy for screening high-quality molecules.

Language: Английский

Synthesis, design and development of energetic materials: Quo Vadis? DOI
Nikita V. Muravyev, Леонид Л. Ферштат, Qinghua Zhang

et al.

Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 486, P. 150410 - 150410

Published: March 14, 2024

Language: Английский

Citations

24
Machine learning-guided property prediction of energetic materials: Recent advances, challenges, and perspectives DOI Creative Commons

Xiaolan Tian,

Siwei Song, Fang Chen

et al.

Energetic Materials Frontiers, Journal Year: 2022, Volume and Issue: 3(3), P. 177 - 186

Published: Aug. 18, 2022

Predicting chemical properties is one of the most important applications machine learning. In recent years, prediction energetic materials using learning has been receiving more attention. This review summarized advances in predicting compounds' (e.g., density, detonation velocity, enthalpy formation, sensitivity, heat explosion, and decomposition temperature) Moreover, it presented general steps for applying to practical from aspects data, molecular representation, algorithms, accuracy. Additionally, raised some controversies specific its possible development directions. Machine expected become a new power driving soon.

Language: Английский

Citations

51
Aging prediction in single based propellants using hybrid strategy of machine learning and genetic algorithm DOI

Faizan Khalid,

Muhammad Nouman Aslam,

Muhammad Abdaal Ghani

et al.

Chemometrics and Intelligent Laboratory Systems, Journal Year: 2024, Volume and Issue: 245, P. 105058 - 105058

Published: Jan. 2, 2024

Language: Английский

Citations

6
Advancements in methodologies and techniques for the synthesis of energetic materials: A review DOI Creative Commons
Wei Du, Lei Yang, Jing Feng

et al.

Energetic Materials Frontiers, Journal Year: 2024, Volume and Issue: unknown

Published: June 1, 2024

Recent years have witnessed significant advancements in methodologies and techniques for the synthesis of energetic materials, which are expected to shape future manufacturing applications. Techniques including continuous flow chemistry, electrochemical synthesis, microwave-assisted biosynthesis been extensively employed pharmaceutical fine chemical industries and, gratifyingly, found broader This review comprehensively introduces recent utilization these emerging techniques, aiming provide a catalyst development novel green methods synthesizing materials.

Language: Английский

Citations

6
Approaching the Thermostability Limit of Nitrogen-Rich Heterocyclic Perchlorate-Based Energetic Materials DOI

Xiue Jiang,

Dangyue Yin,

Mingren Fan

et al.

ACS Applied Materials & Interfaces, Journal Year: 2024, Volume and Issue: 16(37), P. 49434 - 49441

Published: Sept. 4, 2024

In recent years, driven by ever-increasing application of energetic materials in deep-seated mineral resource exploitation and aerospace engineering, the mining advanced safe with significant thermal stability has drawn widespread publicity. Here, a tricyclic bridged compound 2-amino-4,6-bis(3,5-diamino-4-nitropyrazol-1-yl)-1,3,5-triazine (

Language: Английский

Citations

5
Bionic inspired multifunctional modular energetic materials: an exploration of new generation of application-oriented energetic materials DOI
Yujia Wen, Linyuan Wen, Bojun Tan

et al.

Journal of Materials Chemistry A, Journal Year: 2024, Volume and Issue: 12(16), P. 9427 - 9437

Published: Jan. 1, 2024

Aiming to balance the pertinence and universality of energetic materials, this study proposes a new concept bionic inspired multifunctional modular materials seeks out potential monomers via high-throughput screening strategy.

Language: Английский

Citations

4
Planar Layer-Stacking of CHON-Containing Molecules DOI
Shitai Guo,

Kairui Xue,

Chunjie Zuo

et al.

Crystal Growth & Design, Journal Year: 2024, Volume and Issue: 24(7), P. 3065 - 3076

Published: March 18, 2024

Understanding the relationship between molecular structure and crystal packing is fundamental while challenging engineering. Planar layer-stacking structures have attracted widespread attention for their potential to enhance charge transport performance of organic semiconductors reduce sensitivity energetic molecules. Still, it lacks insights into such stacking. We conduct in this work a comprehensive understanding 65 planar layer-stacked CHON-containing molecules based on intermolecular interaction. All 59 hydrogenous each always form HB packing, ascribed H atoms possessing largest positive electrostatic extremes, requires negative ones against them attraction consolidate layers. Meanwhile, intralayer interaction strength not decisive factor either H-free or molecules, its dependence interlayer distance coefficient found, even though there seemingly exist some rough trends. It seems that we can hardly understand alone, further study covering other compositions required.

Language: Английский

Citations

4
Transferring the available fused cyclic scaffolds for high—throughput combinatorial design of highly energetic materials via database mining DOI
Linyuan Wen, Tao Yu, Weipeng Lai

et al.

Fuel, Journal Year: 2022, Volume and Issue: 324, P. 124591 - 124591

Published: May 13, 2022

Language: Английский

Citations

19
Prediction and Construction of Energetic Materials Based on Machine Learning Methods DOI Creative Commons
Xiaowei Zang, Xiang Zhou, Haitao Bian

et al.

Molecules, Journal Year: 2022, Volume and Issue: 28(1), P. 322 - 322

Published: Dec. 31, 2022

Energetic materials (EMs) are the core of weapons and equipment. Achieving precise molecular design efficient green synthesis EMs has long been one primary concerns researchers around world. Traditionally, advanced were discovered through a trial-and-error processes, which required research development (R&D) cycles high costs. In recent years, machine learning (ML) method matured into tool that compliments aids experimental studies for predicting designing EMs. This paper reviews critical process ML methods to discover predict EMs, including data preparation, feature extraction, model construction, performance evaluation. The main ideas basic steps applying analyzed outlined. state-of-the-art about applications in property prediction inverse material is further summarized. Finally, existing challenges strategies coping with proposed.

Language: Английский

Citations

19
From Concept to Synthesis: Developing Heat-Resistant High Explosives through Automated High-Throughput Virtual Screening DOI
Zujia Lu, Yong Hu,

Wen‐Shuai Dong

et al.

The Journal of Physical Chemistry C, Journal Year: 2023, Volume and Issue: 127(38), P. 18832 - 18842

Published: Sept. 14, 2023

In this paper, we investigate the utilization of high-throughput virtual screening (HTVS) to identify and develop novel heat-resistant high explosives (HRHEs) that possess a decomposition temperature exceeding 300 °C detonation velocity surpassing 8000 m·s–1. To achieve this, constructed molecular library composed pyrimidine as parent ring various five-membered heterocycles guest rings connected by an amino bridge. The GFN-xTB method, extended tight binding is employed facilitate geometry optimization vibrational analysis, thereby enabling application more precise versatile quantum chemical calculation in HTVS workflow. Our efforts resulted synthesis three compounds exhibited remarkable stability with temperatures 320 °C, suggesting their potential HRHEs. Notably, compound K19-21 demonstrated 324.6 8293 m·s–1, both 2,2′,4,4′,6,6′-hexanitrostilbene (HNS) 2,6-bis(picrylamino)-3,5-dinitropyridine (PYX) rivaling l,3,5-triamino-2,4,6-trinitrobenzene (TATB). These results support efficacy our design concepts Overall, study underscores importance accelerating discovery new materials possessing desired properties, especially field energetic materials.

Language: Английский

Citations

11