Pressure-Induced High-Energy-Density BeN6 Materials: First-Principles study

IF 3.1 3区 材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY Computational Materials Science Pub Date : 2024-08-13 DOI:10.1016/j.commatsci.2024.113272
Xunjiang Zhang, Huafeng Dong, Le Huang, Hui Long, Xin Zhang, Fugen Wu, Zhongfei Mu, Minru Wen
{"title":"Pressure-Induced High-Energy-Density BeN6 Materials: First-Principles study","authors":"Xunjiang Zhang, Huafeng Dong, Le Huang, Hui Long, Xin Zhang, Fugen Wu, Zhongfei Mu, Minru Wen","doi":"10.1016/j.commatsci.2024.113272","DOIUrl":null,"url":null,"abstract":"Recently, the use of polymeric nitrogen in the search for high-energy–density materials (HEDMs) has attracted widespread attention. However, synthesizing polymeric nitrogen materials is quite challenging; for instance, the synthesis of cubic gauche nitrogen requires a high pressure of 110 GPa. Previous theoretical predictions and experiments have shown that adding alkaline earth metals as cationic ligands can stabilize polymeric nitrogen and reduce the synthesis pressure. Using the USPEX structural prediction code and first-principles calculations, this study predicted 2 new nitrogen salt with nitrogen contents up to 89.80 %, namely -BeN and -BeN, with their unique nitrogen chain structures, have energy densities as high as 3.32 and 3.59 kJ/g, respectively. The exceptional explosive properties reveal these two BeN are potential HEDMs. In addition, -BeN is a direct bandgap semiconductor.","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Materials Science","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1016/j.commatsci.2024.113272","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Recently, the use of polymeric nitrogen in the search for high-energy–density materials (HEDMs) has attracted widespread attention. However, synthesizing polymeric nitrogen materials is quite challenging; for instance, the synthesis of cubic gauche nitrogen requires a high pressure of 110 GPa. Previous theoretical predictions and experiments have shown that adding alkaline earth metals as cationic ligands can stabilize polymeric nitrogen and reduce the synthesis pressure. Using the USPEX structural prediction code and first-principles calculations, this study predicted 2 new nitrogen salt with nitrogen contents up to 89.80 %, namely -BeN and -BeN, with their unique nitrogen chain structures, have energy densities as high as 3.32 and 3.59 kJ/g, respectively. The exceptional explosive properties reveal these two BeN are potential HEDMs. In addition, -BeN is a direct bandgap semiconductor.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
压力诱导的高能量密度 BeN6 材料:第一原理研究
最近,利用聚合氮寻找高能量密度材料(HEDMs)引起了广泛关注。然而,合成聚合氮材料具有相当大的挑战性;例如,合成立方高气氮需要 110 GPa 的高压。以往的理论预测和实验表明,添加碱土金属作为阳离子配体可以稳定聚合氮并降低合成压力。本研究利用 USPEX 结构预测代码和第一性原理计算,预测出两种含氮量高达 89.80% 的新型氮盐,即 -BeN 和 -BeN,它们具有独特的氮链结构,能量密度分别高达 3.32 和 3.59 kJ/g。其特殊的爆炸特性表明,这两种 BeN 是潜在的 HEDM。此外,-BeN 还是一种直接带隙半导体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Computational Materials Science
Computational Materials Science 工程技术-材料科学:综合
CiteScore
6.50
自引率
6.10%
发文量
665
审稿时长
26 days
期刊介绍: The goal of Computational Materials Science is to report on results that provide new or unique insights into, or significantly expand our understanding of, the properties of materials or phenomena associated with their design, synthesis, processing, characterization, and utilization. To be relevant to the journal, the results should be applied or applicable to specific material systems that are discussed within the submission.
期刊最新文献
QuantumShellNet: Ground-state eigenvalue prediction of materials using electronic shell structures and fermionic properties via convolutions Computational insights into the tailoring of photoelectric properties in graphene quantum dot-Ru(II) polypyridyl nanocomposites Coexisting Type-I nodal Loop, Hybrid nodal loop and nodal surface in electride Li5Sn Effect of very slow O diffusion at high temperature on very fast H diffusion in the hydride ion conductor LaH2.75O0.125 Equivariance is essential, local representation is a need: A comprehensive and critical study of machine learning potentials for tobermorite phases
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1