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

и другие.

FirePhysChem, Год журнала: 2023, Номер 4(1), С. 55 - 62

Опубликована: Июль 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.

Язык: Английский

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

и другие.

Chemical Engineering Journal, Год журнала: 2024, Номер 486, С. 150410 - 150410

Опубликована: Март 14, 2024

Язык: Английский

Процитировано

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

Xiaolan Tian,

Siwei Song, Fang Chen

и другие.

Energetic Materials Frontiers, Год журнала: 2022, Номер 3(3), С. 177 - 186

Опубликована: Авг. 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.

Язык: Английский

Процитировано

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

и другие.

Chemometrics and Intelligent Laboratory Systems, Год журнала: 2024, Номер 245, С. 105058 - 105058

Опубликована: Янв. 2, 2024

Язык: Английский

Процитировано

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

и другие.

Energetic Materials Frontiers, Год журнала: 2024, Номер unknown

Опубликована: Июнь 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.

Язык: Английский

Процитировано

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

Xiue Jiang,

Dangyue Yin,

Mingren Fan

и другие.

ACS Applied Materials & Interfaces, Год журнала: 2024, Номер 16(37), С. 49434 - 49441

Опубликована: Сен. 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 (

Язык: Английский

Процитировано

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

и другие.

Journal of Materials Chemistry A, Год журнала: 2024, Номер 12(16), С. 9427 - 9437

Опубликована: Янв. 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.

Язык: Английский

Процитировано

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

Kairui Xue,

Chunjie Zuo

и другие.

Crystal Growth & Design, Год журнала: 2024, Номер 24(7), С. 3065 - 3076

Опубликована: Март 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.

Язык: Английский

Процитировано

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

и другие.

Fuel, Год журнала: 2022, Номер 324, С. 124591 - 124591

Опубликована: Май 13, 2022

Язык: Английский

Процитировано

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

и другие.

Molecules, Год журнала: 2022, Номер 28(1), С. 322 - 322

Опубликована: Дек. 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.

Язык: Английский

Процитировано

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

Wen‐Shuai Dong

и другие.

The Journal of Physical Chemistry C, Год журнала: 2023, Номер 127(38), С. 18832 - 18842

Опубликована: Сен. 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.

Язык: Английский

Процитировано

11