2017
DOI: 10.1038/natrevmats.2017.37
|View full text |Cite
|
Sign up to set email alerts
|

Computational development of the nanoporous materials genome

Abstract: H1 Abstract.There is currently a large push towards big data and data mining in materials research to accelerate discovery. Zeolites, metal-organic frameworks (MOFs) and other related crystalline porous materials are not immune to this recent phenomenon, as evidenced by the proliferation of porous structure databases and computational gas adsorption screening studies over the past decade. The strive to identify the best materials for a variety of gas separation and storage applications has not only led to coll… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
123
0

Year Published

2018
2018
2023
2023

Publication Types

Select...
5
4

Relationship

2
7

Authors

Journals

citations
Cited by 141 publications
(123 citation statements)
references
References 160 publications
0
123
0
Order By: Relevance
“…An interface between Python and C for this is provided here at https://github.com/peteboyd/mcqd_api. Large-scale screening of databases of hypothetical MOFs for vari-ous gas separation and storage applications has been reported pre-viously [26][27][28][29] ; however, here we have focused on identifying binding pockets-or structural motifs termed adsorbaphores-as synthetic targets, rather than whole materials. This enhances the synthetic viability of the approach, as demonstrated by the identification of one new mate-rial with the targeted adsorbaphore that was synthesized and shown to adsorb CO2 as predicted.…”
Section: Code Availabilitymentioning
confidence: 99%
“…An interface between Python and C for this is provided here at https://github.com/peteboyd/mcqd_api. Large-scale screening of databases of hypothetical MOFs for vari-ous gas separation and storage applications has been reported pre-viously [26][27][28][29] ; however, here we have focused on identifying binding pockets-or structural motifs termed adsorbaphores-as synthetic targets, rather than whole materials. This enhances the synthetic viability of the approach, as demonstrated by the identification of one new mate-rial with the targeted adsorbaphore that was synthesized and shown to adsorb CO2 as predicted.…”
Section: Code Availabilitymentioning
confidence: 99%
“…Data-driven research has recently received attention as a new route to accelerating this step. [1][2][3][4][5][6][7][8][9] This approach uses a pre-computed materials database and statistical tools that efficiently screen candidates in a search for optimal materials. The availability of open-access databases of material properties, [10][11][12][13][14] along with machine learning (ML) techniques, has rapidly advanced research in this area.…”
Section: Introductionmentioning
confidence: 99%
“…An overview of the advances that has been made in this topic is given in refs. . A specific branch of force fields which have recently been developed for applications within MOFs are the so‐called coarse‐grained force fields, in which atoms are united into interacting beads.…”
Section: Introductionmentioning
confidence: 99%