ArticleRSC advances2020
Identifying misbonded atoms in the 2019 CoRE metal-organic framework database.
Article in RSC advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
14 citing papers in PubMed.
- Accelerating discovery of MOFs for hydrogen storage via machine learning in energy related applications.Scientific reports · 2026Article
- Examination of Replicate Syntheses of Metal Organic Frameworks as a Window into Reproducibility in Materials Chemistry.The journal of physical chemistry. C, Nanomaterials and interfaces · 2026Review
- Molecular Modeling-Based Machine Learning for Accurate Prediction of Gas Diffusivity and Permeability in Metal-Organic Frameworks.ACS materials Au · 2026Article
- Comparing Classical and Machine Learning Force Fields for Modeling Deformation of Metal-Organic Frameworks Relevant for Direct Air Capture.The journal of physical chemistry. C, Nanomaterials and interfaces · 2025Article
- Identification of Metal-Organic Frameworks for near Practical Energy Limit COACS central science · 2025Article
- MOFChecker: a package for validating and correcting metal-organic framework (MOF) structures.Digital discovery · 2025Article
- An automated protocol to construct flexibility parameters for classical forcefields: applications to metal-organic frameworks.RSC advances · 2024Article
- The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture.ACS central science · 2024Article
- Machine learning insights into predicting biogas separation in metal-organic frameworks.Communications chemistry · 2024Article
- MEPO-ML: a robust graph attention network model for rapid generation of partial atomic charges in metal-organic frameworks.npj computational materials · 2024Article
- Predicting hydrogen storage in MOFs via machine learning.Patterns (New York, N.Y.) · 2021Article
- Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation.Journal of chemical information and modeling · 2021Review
- Effect of Metal-Organic Framework (MOF) Database Selection on the Assessment of Gas Storage and Separation Potentials of MOFs.Angewandte Chemie (International ed. in English) · 2021Article
- Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution.ACS central science · 2020Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Databases of experimentally-derived metal-organic framework (MOF) crystal structures are useful for large-scale computational screening to identify which MOFs are best-suited for particular applications. However, these crystal structures must be cleaned to identify and/or correct various artifacts. The recently published 2019 CoRE MOF database (Chung
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.