157 related articles for article (PubMed ID: 35010109)
1. Machine Learning-Assisted Computational Screening of Metal-Organic Frameworks for Atmospheric Water Harvesting.
Li L; Shi Z; Liang H; Liu J; Qiao Z
Nanomaterials (Basel); 2022 Jan; 12(1):. PubMed ID: 35010109
[TBL] [Abstract][Full Text] [Related]
2. Prediction of O
Orhan IB; Daglar H; Keskin S; Le TC; Babarao R
ACS Appl Mater Interfaces; 2022 Jan; 14(1):736-749. PubMed ID: 34928569
[TBL] [Abstract][Full Text] [Related]
3. High-Throughput Screening of the CoRE-MOF-2019 Database for CO
Kancharlapalli S; Snurr RQ
ACS Appl Mater Interfaces; 2023 Jun; 15(23):28084-28092. PubMed ID: 37262369
[TBL] [Abstract][Full Text] [Related]
4. Combining Computational Screening and Machine Learning to Predict Metal-Organic Framework Adsorbents and Membranes for Removing CH
Li H; Wang C; Zeng Y; Li D; Yan Y; Zhu X; Qiao Z
Membranes (Basel); 2022 Aug; 12(9):. PubMed ID: 36135849
[TBL] [Abstract][Full Text] [Related]
5. Machine Learning Using Combined Structural and Chemical Descriptors for Prediction of Methane Adsorption Performance of Metal Organic Frameworks (MOFs).
Pardakhti M; Moharreri E; Wanik D; Suib SL; Srivastava R
ACS Comb Sci; 2017 Oct; 19(10):640-645. PubMed ID: 28800219
[TBL] [Abstract][Full Text] [Related]
6. Rapid Screening of Metal-Organic Frameworks for Propane/Propylene Separation by Synergizing Molecular Simulation and Machine Learning.
Tang H; Xu Q; Wang M; Jiang J
ACS Appl Mater Interfaces; 2021 Nov; 13(45):53454-53467. PubMed ID: 34665615
[TBL] [Abstract][Full Text] [Related]
7. In Silico Screening of Metal-Organic Frameworks for Formaldehyde Capture with and without Humidity by Molecular Simulation.
Li W; Liang T; Lin Y; Wu W; Li S
Int J Mol Sci; 2022 Nov; 23(22):. PubMed ID: 36430151
[TBL] [Abstract][Full Text] [Related]
8. Machine-learning-driven discovery of metal-organic framework adsorbents for hexavalent chromium removal from aqueous environments.
Jiang M; Fu W; Wang Y; Xu D; Wang S
J Colloid Interface Sci; 2024 May; 662():836-845. PubMed ID: 38382368
[TBL] [Abstract][Full Text] [Related]
9. Machine Learning-Assisted Discovery of Propane-Selective Metal-Organic Frameworks.
Wang Y; Jiang ZJ; Wang DR; Lu W; Li D
J Am Chem Soc; 2024 Mar; 146(10):6955-6961. PubMed ID: 38422479
[TBL] [Abstract][Full Text] [Related]
10. Computational Screening of Metal⁻Organic Framework Membranes for the Separation of 15 Gas Mixtures.
Yang W; Liang H; Peng F; Liu Z; Liu J; Qiao Z
Nanomaterials (Basel); 2019 Mar; 9(3):. PubMed ID: 30897779
[TBL] [Abstract][Full Text] [Related]
11. Large-Scale Screening and Machine Learning for Metal-Organic Framework Membranes to Capture CO
Situ Y; Yuan X; Bai X; Li S; Liang H; Zhu X; Wang B; Qiao Z
Membranes (Basel); 2022 Jul; 12(7):. PubMed ID: 35877903
[TBL] [Abstract][Full Text] [Related]
12. Mapping the Porous and Chemical Structure-Function Relationships of Trace CH
Wu X; Che Y; Chen L; Amigues EJ; Wang R; He J; Dong H; Ding L
ACS Appl Mater Interfaces; 2022 Oct; 14(41):47209-47221. PubMed ID: 36197758
[TBL] [Abstract][Full Text] [Related]
13. Accelerating In Silico Discovery of Metal-Organic Frameworks for Ethane/Ethylene and Propane/Propylene Separation: A Synergistic Approach Integrating Molecular Simulation, Machine Learning, and Active Learning.
Daoo V; Singh JK
ACS Appl Mater Interfaces; 2024 Feb; 16(6):6971-6987. PubMed ID: 38289235
[TBL] [Abstract][Full Text] [Related]
14. Database for CO
Altintas C; Avci G; Daglar H; Nemati Vesali Azar A; Velioglu S; Erucar I; Keskin S
ACS Appl Mater Interfaces; 2018 May; 10(20):17257-17268. PubMed ID: 29722965
[TBL] [Abstract][Full Text] [Related]
15. Deep learning and big data mining for Metal-Organic frameworks with high performance for simultaneous desulfurization and carbon capture.
Guan K; Xu F; Huang X; Li Y; Guo S; Situ Y; Chen Y; Hu J; Liu Z; Liang H; Zhu X; Wu Y; Qiao Z
J Colloid Interface Sci; 2024 May; 662():941-952. PubMed ID: 38382377
[TBL] [Abstract][Full Text] [Related]
16. Prediction of arsenic adsorption onto metal organic frameworks and adsorption mechanisms interpretation by machine learning.
Xiong T; Cui J; Hou Z; Yuan X; Wang H; Chen J; Yang Y; Huang Y; Xu X; Su C; Leng L
J Environ Manage; 2023 Dec; 347():119065. PubMed ID: 37801942
[TBL] [Abstract][Full Text] [Related]
17. Screening metal-organic frameworks for adsorption-driven osmotic heat engines via grand canonical Monte Carlo simulations and machine learning.
Long R; Xia X; Zhao Y; Li S; Liu Z; Liu W
iScience; 2021 Jan; 24(1):101914. PubMed ID: 33385115
[TBL] [Abstract][Full Text] [Related]
18. Molecular fingerprint and machine learning enhance high-performance MOFs for mustard gas removal.
Ni J; Li J; Li S; Zheng H; Ming Z; Li L; Li H; Zhang S; Zhao Y; Liang H; Qiao Z
iScience; 2024 Jun; 27(6):110042. PubMed ID: 38883811
[TBL] [Abstract][Full Text] [Related]
19. Computational Screening of Metal-Organic Frameworks for Ammonia Capture from H
Zhu Z; Wang H; Wu XY; Luo K; Fan J
ACS Omega; 2022 Oct; 7(42):37640-37653. PubMed ID: 36312414
[TBL] [Abstract][Full Text] [Related]
20. In Silico Evolution of High-Performing Metal Organic Frameworks for Methane Adsorption.
Beauregard N; Pardakhti M; Srivastava R
J Chem Inf Model; 2021 Jul; 61(7):3232-3239. PubMed ID: 34264660
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
