通过振动上泵模型预测一组扩展的含能材料的冲击敏感性:确定了基于分子的结构-性能关系

IF 2.9 3区 化学 Q3 CHEMISTRY, PHYSICAL
Jack M. Hemingway, Heather M. Quayle, Cian Byrne, Colin R. Pulham, Subrata Mondal, Adam A. L. Michalchuk and Carole A. Morrison
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引用次数: 0

摘要

在此,我们应用振动上泵模型来预测一组33个分子能晶体的机械诱导冲击灵敏度。总的来说,该模型可以成功地识别和排序对机械引发最敏感的化合物,但对灵敏度较低的化合物的区分能力较差。进一步的发展,包括触发键激活的影响,导致预测能力的显著提高。我们表明,这种结构-性质模型强调了分子柔韧性在预测冲击敏感性方面的重要性,此外,我们表明,可以从SMILES字符串中获得的Kier分子柔韧性指数提供了一个简单的基于分子的描述符,可以在某种程度上预测EMs的敏感性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Predicting impact sensitivities for an extended set of energetic materials via the vibrational up-pumping model: molecular-based structure–property relationships identified†

Predicting impact sensitivities for an extended set of energetic materials via the vibrational up-pumping model: molecular-based structure–property relationships identified†

We have applied the vibrational up-pumping model to predict the mechanically-induced impact sensitivities of 33 molecular energetic crystals. Overall, the current model successfully identifies and ranks the compounds that are most sensitive to mechanical initiation, but offers poorer differentiation between compounds with lower sensitivity. Further developments to include the effects of trigger bond activation led to significant improvements in predictive capability. We show that this structure–property model highlights the importance of molecular flexibility in predicting impact sensitivity, and furthermore, we show that the Kier molecular flexibility index, which can be obtained from a SMILES string, offers a simple molecular-based descriptor that goes some way towards predicting the sensitivity of energetic materials.

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来源期刊
Physical Chemistry Chemical Physics
Physical Chemistry Chemical Physics 化学-物理:原子、分子和化学物理
CiteScore
5.50
自引率
9.10%
发文量
2675
审稿时长
2.0 months
期刊介绍: Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.
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