Alleviating the stability–performance contradiction of cage-like high-energy-density materials by a backbone-collapse and branch-heterolysis competition mechanism

Song, Qingguan; Zhang, Lei; Mo, Zeyao

doi:10.1039/d2cp02061k

Cited by 8 publications

(4 citation statements)

References 60 publications

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“…For centuries, researchers have been faced with the daunting task of finding effective strategies to address the inherent trade‐off between stability and performance in the development of high‐energy‐density materials (HEDMs). Recently, Song et al [297] . demonstrated that caged HEDMs have the potential to show both high thermal stability and high performance using the ML‐accelerated HTC technique.…”

Section: Applications Of Htc In Materials Developmentmentioning

confidence: 99%

Advances in data‐assisted high‐throughput computations for material design

Xu,

Zhang,

Huo

et al. 2023

Materials Genome Engineering Advances

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Extensive trial and error in the variable space is the main cause of low efficiency and high cost in material development. The experimental tasks can be reduced significantly in the case that the variable space is narrowed down by reliable computer simulations. Because of their numerous variables in material design, however, the variable space is still too large to be accessed thoroughly even with a computational approach. High‐throughput computations (HTC) make it possible to complete a material screening in a large space by replacing the conventionally manual and sequential operations with automatic, robust, and concurrent streamlines. The efficiency of HTC, which is one of the pillars of materials genome engineering, has been verified in many studies, but its applications are still limited by demanding computational costs. Introduction of data mining and artificial intelligence into HTC has become an effective approach to solve the problem. In the past years, many studies have focused on the development and application of HTC and data combined approaches, which is considered as a new paradigm in computational materials science. This review focuses on the main advances in the field of data‐assisted HTC for material research and development and provides our outlook on its future development.

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Section: Applications Of Htc In Materials Developmentmentioning

confidence: 99%

Advances in data‐assisted high‐throughput computations for material design

Xu,

Zhang,

Huo

et al. 2023

Materials Genome Engineering Advances

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“…With the development of computational level, theoretical chemistry and high-throughput screen inject new vitality into the search for energetic materials under the consideration of cost and safety. [13][14][15] During the high-throughput screen, machine learning offers a vital tool for effective performance prediction, such as density, [16][17][18] heat of formation, 19,20 detonation properties, [21][22][23] and decomposition temperature. [24][25][26][27] We have explored to some extent in this eld as well: in 2021, we conducted a domain-related knowledge-promoted highthroughput cage scaffold screening from the ZINC15 database containing over 130 000 scaffolds and merged it with a combinatorial design to alleviate the lack of cage energetic materials.…”

Section: Introductionmentioning

confidence: 99%

Bionic inspired multifunctional modular energetic materials: an exploration of new generation of application-oriented energetic materials

Wen,

Tan

et al. 2024

J. Mater. Chem. A

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“…[1][2][3][4][5] Since HEDMs have adjustable thermodynamic and kinetic stability, they can be utilized for various energetic applications in real life. [6] Most organic compounds with a maximum number of heteroatoms, such as nitrogen and oxygen, store abundant chemical energy that is released upon external shock. In general, energy-rich materials are unstable under normal environmental conditions, such as heat, friction, shock, etc., and these properties lead to the instability of the materials.…”

Section: Introductionmentioning

confidence: 99%

In silico investigations of high-energy density properties and effect of ring fusion on dinitropyrazole derivatives

Subramani,

Natarajan,

Lakshmanan

et al. 2023

Struct Chem

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Highlights1. The molecular geometry, AIM analysis, electrostatic and IBSI, PDA and NBO properties of the 34DNP and DNPP molecules were analysed.2. The tilted -NO2 in the isolated pyrazole ring is favorable for increasing the O-O bond character in -NO2 and leads to less favorable bonding with the pyrazole ring.3. The dinitropyrazole ring fusion provides coplanarity to -NO2 with the pyrazole ring and less steric interaction with the molecule.4. The isolated pyrazole ring provides higher acidity to the attached hydrogen than the fused pyrazole ring.

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Alleviating the stability–performance contradiction of cage-like high-energy-density materials by a backbone-collapse and branch-heterolysis competition mechanism

Abstract: Searching for advanced strategies to alleviate the inherent contradiction between stability and performance has been one of the most challenging tasks in the development of high-energy-density materials (HEDMs) for centuries....

Cited by 8 publications

References 60 publications

Advances in data‐assisted high‐throughput computations for material design

Advances in data‐assisted high‐throughput computations for material design

Bionic inspired multifunctional modular energetic materials: an exploration of new generation of application-oriented energetic materials

In silico investigations of high-energy density properties and effect of ring fusion on dinitropyrazole derivatives

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