Materials Informatics with PoreBlazer v4.0 and the CSD MOF Database

文档 可视化 编码(集合论) 源代码 Fortran语言 计算机科学 材料信息学 计算科学 数据挖掘 健康信息学 程序设计语言 医学 公共卫生 工程信息学 护理部 集合(抽象数据类型)
作者
Lev Sarkisov,Rocío Bueno-Pérez,Mythili Sutharson,David Fairen‐Jiménez
出处
期刊:Chemistry of Materials [American Chemical Society]
卷期号:32 (23): 9849-9867 被引量:298
标识
DOI:10.1021/acs.chemmater.0c03575
摘要

The development of computational methods to explore crystalline materials has received significant attention in the last decades. Different codes have been reported to help researchers to evaluate and learn about the structure of materials and to understand and predict their properties. Here, we present an updated version of PoreBlazer, an open-access, open-source Fortran 90 code to calculate structural properties of porous materials. The article describes the properties calculated by the code, their physical meaning and their relationship to the properties that can be measured experimentally. Here, we reflect on the methods in the code and discuss features of the most recent version. First, we demonstarte the capabilities of PoreBlazer on the prototypical metal-organic framework (MOF) materials, HKUST-1, IRMOF-1 and ZIF-8, and compare the results to those obtained with other codes, Zeo++ and RASPA. Second, we apply PoreBlazer to the recently assembled database of MOF materials-the CSD MOF subset-and compare properties such as accessible surface area and pore volume from PoreBlazer and the two other codes, and reflect on the possible sources of the differences. Finally, we use PoreBlazer to illustrate how correlations between various structural characteristics can be mined using interactive, dynamic data visualization and how material informatics approaches-including principal component analysis and machine learning-can accelerate the discovery of new materials and new functionalities. The results of these calculations, along with the PoreBlazer code, documentation, and case studies are available online from https://github.com/SarkisovGroup/PoreBlazer. The data visualization tool is available at https://aaml-explorer-geo-prop.herokuapp.com), and the principal component analysis is available at https://aaml-pca-geo-prop.herokuapp.com.
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
傲娇的咖啡豆完成签到,获得积分10
1秒前
1秒前
1秒前
凶狠的半山完成签到,获得积分10
2秒前
2秒前
2秒前
3秒前
科目三应助带仙气的小仙采纳,获得10
3秒前
3秒前
喷火战斗鸡完成签到,获得积分10
4秒前
4秒前
Asiprinal发布了新的文献求助10
4秒前
大喵发布了新的文献求助10
5秒前
11223发布了新的文献求助10
5秒前
yue发布了新的文献求助10
5秒前
NexusExplorer应助3d54s2采纳,获得10
6秒前
烟花应助ilk666采纳,获得10
7秒前
Wang发布了新的文献求助30
7秒前
gene完成签到 ,获得积分10
8秒前
8秒前
yi417发布了新的文献求助10
9秒前
聪明凡之完成签到,获得积分10
9秒前
剑来不来完成签到,获得积分10
9秒前
9秒前
weiweiwei完成签到,获得积分10
10秒前
hhhc发布了新的文献求助20
10秒前
CipherSage应助fionadong采纳,获得10
10秒前
科研通AI6应助哎哟采纳,获得10
10秒前
11秒前
11秒前
11秒前
咕咕咕发布了新的文献求助10
12秒前
12秒前
12345发布了新的文献求助10
12秒前
乐乐应助bailubailing采纳,获得10
13秒前
opair完成签到,获得积分10
13秒前
15秒前
15秒前
zkyyinf_zero发布了新的文献求助10
16秒前
Lily发布了新的文献求助10
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
Encyclopedia of Agriculture and Food Systems Third Edition 2000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 临床微生物学程序手册,多卷,第5版 2000
人脑智能与人工智能 1000
King Tyrant 720
Silicon in Organic, Organometallic, and Polymer Chemistry 500
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5601274
求助须知:如何正确求助?哪些是违规求助? 4686785
关于积分的说明 14846051
捐赠科研通 4680352
什么是DOI,文献DOI怎么找? 2539276
邀请新用户注册赠送积分活动 1506151
关于科研通互助平台的介绍 1471283