重要提醒:2025.12.15 12:00-12:50期间发布的求助,下载出现了问题,现在已经修复完毕,请重新下载即可。如非文件错误,请不要进行驳回。

Transferring the available fused cyclic scaffolds for high—throughput combinatorial design of highly energetic materials via database mining

恶唑 吞吐量 计算机科学 组合化学 起爆 数据库 灵敏度(控制系统) 纳米技术 化学 材料科学 工程类 有机化学 电信 电子工程 无线 爆炸物
作者
Linyuan Wen,Tao Yu,Weipeng Lai,Maochang Liu,Bozhou Wang,Jinwen Shi,Yingzhe Liu
出处
期刊:Fuel [Elsevier]
卷期号:324: 124591-124591 被引量:20
标识
DOI:10.1016/j.fuel.2022.124591
摘要

Recently, the fused cyclic compounds have been the object of an increased interest in the field of energetic materials (EMs) due to the trade-off between energy and safety. Compared with the fused cyclic EMs consisting of the azoles or azines, the oxazole-based fused EMs which possibly possess higher energy–density are very lacking. Here, we proposed an efficient approach to design the highly energetic oxazole-based fused materials. The domain-related knowledge promoted an advanced database search for the aromatic oxazole-based scaffolds from the buyable subset of the ZINC20 database, ensuring scaffolds are available for purchase. Then, 171 target scaffolds were transferred into the EM field and cooperated with combinatorial design to construct a chemical space containing over 107 potential energetic molecules. The high-throughput screening was performed in four aspects, namely, density, difficulty of synthesis, detonation performance, and sensitivity, to accelerate the search for candidates. Meanwhile, the statistical analysis through the hierarchical filtrations clarified the potential of 2r-3s and 2r-4s scaffold types for creating highly energetic molecules. Finally, several candidates stood out owing to nearly 10000 m/s detonation velocity and acceptable predicted sensitivity, elucidating the effectiveness of our approach. We anticipate this investigation could not only be a vital point for subsequent fused cyclic EM research, but also offered a new avenue for material design in other fields.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
顾矜应助毛毛0427采纳,获得10
刚刚
moxi摩西发布了新的文献求助10
1秒前
1秒前
1秒前
汤婆婆完成签到,获得积分20
2秒前
lyric完成签到,获得积分10
2秒前
12345完成签到,获得积分10
3秒前
Orange应助Emma采纳,获得10
4秒前
甜甜秋荷发布了新的文献求助10
4秒前
夏弥桥完成签到 ,获得积分10
4秒前
莫名完成签到,获得积分10
5秒前
哈哈哈6056完成签到,获得积分10
5秒前
ruiz完成签到,获得积分10
5秒前
6秒前
7秒前
肥基德发布了新的文献求助10
7秒前
汤婆婆发布了新的文献求助10
7秒前
ding应助研友_Zlx3aZ采纳,获得10
7秒前
面包鱼完成签到,获得积分10
8秒前
怕孤独的鑫完成签到,获得积分10
9秒前
Akim应助万重山采纳,获得10
10秒前
赘婿应助甜甜秋荷采纳,获得10
10秒前
luckydog完成签到,获得积分10
11秒前
科研通AI6应助ribuluoba采纳,获得10
11秒前
一笑发布了新的文献求助10
11秒前
12秒前
trj发布了新的文献求助10
12秒前
福福yu完成签到,获得积分10
12秒前
12秒前
优美的谷完成签到,获得积分10
12秒前
12秒前
12秒前
朱朱发布了新的文献求助10
13秒前
凛冬完成签到,获得积分10
13秒前
13秒前
leavesziqi完成签到,获得积分10
15秒前
15秒前
luckydog发布了新的文献求助10
16秒前
ZllMea完成签到,获得积分10
16秒前
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1001
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Haematolymphoid Tumours (Part A and Part B, WHO Classification of Tumours, 5th Edition, Volume 11) 400
Virus-like particles empower RNAi for effective control of a Coleopteran pest 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5467656
求助须知:如何正确求助?哪些是违规求助? 4571307
关于积分的说明 14329661
捐赠科研通 4497890
什么是DOI,文献DOI怎么找? 2464141
邀请新用户注册赠送积分活动 1452961
关于科研通互助平台的介绍 1427673