Multiobjective Optimization of Metal-Organic Framework Structural Properties and Synthesis Costs through Machine Learning.

Zhang H, Pan C, Liang Q, Zhong L, Pan WP

DOI: 10.1021/acs.jcim.5c01730
Published: 2026 Jan 12
Container: Journal of chemical information and modeling
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1021/acs.jcim.5c01730,
  title = {Multiobjective Optimization of Metal-Organic Framework Structural Properties and Synthesis Costs through Machine Learning.},
  author = {Zhang H and Pan C and Liang Q and Zhong L and Pan WP},
  year = {2026},
  journal = {Journal of chemical information and modeling},
  doi = {10.1021/acs.jcim.5c01730},
  url = {https://doi.org/10.1021/acs.jcim.5c01730}
}

RIS

TY  - JOUR
TI  - Multiobjective Optimization of Metal-Organic Framework Structural Properties and Synthesis Costs through Machine Learning.
AU  - Zhang H
AU  - Pan C
AU  - Liang Q
AU  - Zhong L
AU  - Pan WP
PY  - 2026
JO  - Journal of chemical information and modeling
DO  - 10.1021/acs.jcim.5c01730
UR  - https://doi.org/10.1021/acs.jcim.5c01730
ER  -

APA

H, Z., C, P., Q, L., L, Z., & WP, P. (2026). Multiobjective Optimization of Metal-Organic Framework Structural Properties and Synthesis Costs through Machine Learning.. Journal of chemical information and modeling. https://doi.org/10.1021/acs.jcim.5c01730

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pubmed · retrieved 2026-09-26T06:25:13.472Z