Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T15:02:44.638648Z
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2412.11386.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T15:02:44.638648Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
59 of 59 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 0c4b9d08-7509-4dd8-a91f-1aacc733c07c · outbound
Category-Specific Topological Learning of Metal-Organic Frameworks The current status of mof and cof applications
Reference 1
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Category-Specific Topological Learning of Metal-Organic Frameworks Green synthesis of metal–organic frameworks: A state-of-the-art review of potential environmental and medical applications
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Category-Specific Topological Learning of Metal-Organic Frameworks Guest inclusion and structural dynamics in 2-d hydrogen-bonded metal- organic frameworks
Reference 3
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Category-Specific Topological Learning of Metal-Organic Frameworks Unresolved cited work
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Category-Specific Topological Learning of Metal-Organic Frameworks Gas storage in porous metal–organic frameworks for clean energy applications
Reference 5
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Category-Specific Topological Learning of Metal-Organic Frameworks Mof-based membranes for gas separations
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Category-Specific Topological Learning of Metal-Organic Frameworks Metal–organic framework materials as catalysts
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Category-Specific Topological Learning of Metal-Organic Frameworks Zirconium-based metal–organic frameworks for the catalytic hydrolysis of organophosphorus nerve agents
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Category-Specific Topological Learning of Metal-Organic Frameworks Metal–organic framework materials as chemical sensors
Reference 9
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Category-Specific Topological Learning of Metal-Organic Frameworks High-throughput computational screening of metal– organic frameworks
Reference 10
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Category-Specific Topological Learning of Metal-Organic Frameworks Computational screening of trillions of metal–organic frameworks for high- performance methane storage
Reference 11
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Category-Specific Topological Learning of Metal-Organic Frameworks Density functional theory of electronic structure
Reference 12
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Category-Specific Topological Learning of Metal-Organic Frameworks Molecular dynamics simulations in biology
Reference 13
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Category-Specific Topological Learning of Metal-Organic Frameworks Hierarchical materials from high information content macromolecular building blocks: construction, dynamic inter- ventions, and prediction
Reference 14
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Category-Specific Topological Learning of Metal-Organic Frameworks Recent advances, opportunities, and challenges in high- throughput computational screening of mofs for gas separations
Reference 15
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Category-Specific Topological Learning of Metal-Organic Frameworks Rational design of novel biomimetic sequence-defined polymers for mineralization applications
Reference 16
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Category-Specific Topological Learning of Metal-Organic Frameworks Computational and experimental determination of the properties, structure, and stability of peptoid nanosheets and nanotubes
Reference 17
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Category-Specific Topological Learning of Metal-Organic Frameworks Influence of peptoid sequence on the mechanisms and kinetics of 2d assembly
Reference 18
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Category-Specific Topological Learning of Metal-Organic Frameworks Machine learning in materials science
Reference 19
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Category-Specific Topological Learning of Metal-Organic Frameworks Mof synthesis prediction enabled by automatic data mining and machine learning
Reference 20
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Category-Specific Topological Learning of Metal-Organic Frameworks Applications of machine learning in metal-organic frameworks
Reference 21
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Category-Specific Topological Learning of Metal-Organic Frameworks Development of the design and synthesis of metal–organic frameworks (mofs)–from large scale attempts, functional oriented modifications, to artificial intelligence (ai) predictions
Reference 22
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Category-Specific Topological Learning of Metal-Organic Frameworks Metal–organic framework with optimally selective xenon adsorption and separation
Reference 23
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Category-Specific Topological Learning of Metal-Organic Frameworks Progress toward the compu- tational discovery of new metal–organic framework adsorbents for energy applications
Reference 24
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Category-Specific Topological Learning of Metal-Organic Frameworks Advances, updates, and analytics for the computation-ready, experimental metal– organic framework database: Core mof 2019
Reference 25
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Category-Specific Topological Learning of Metal-Organic Frameworks Large-scale screening of hypothetical metal–organic frameworks
Reference 26
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Category-Specific Topological Learning of Metal-Organic Frameworks Prediction of o2/n2 selectivity in metal–organic frameworks via high-throughput computational screening and machine learning
Reference 27
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Category-Specific Topological Learning of Metal-Organic Frameworks Using machine learning and data mining to leverage community knowledge for the engineering of stable metal–organic frameworks
Reference 28
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Category-Specific Topological Learning of Metal-Organic Frameworks Energy-based descriptors to rapidly predict hydrogen storage in metal–organic frameworks
Reference 29
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Category-Specific Topological Learning of Metal-Organic Frameworks Machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery
Reference 30
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Category-Specific Topological Learning of Metal-Organic Frameworks Crystal graph convolutional neural networks for an accurate and interpretable prediction of material properties
Reference 31
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Category-Specific Topological Learning of Metal-Organic Frameworks A multi-modal pre-training transformer for universal transfer learning in metal–organic frameworks
Reference 32
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Category-Specific Topological Learning of Metal-Organic Frameworks Enhancing structure–property relationships in porous materials through transfer learning and cross-material few-shot learning
Reference 33
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Category-Specific Topological Learning of Metal-Organic Frameworks Moformer: self- supervised transformer model for metal–organic framework property prediction
Reference 34
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Category-Specific Topological Learning of Metal-Organic Frameworks Interpretable graph transformer network for predicting adsorption isotherms of metal–organic frameworks
Reference 35
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Category-Specific Topological Learning of Metal-Organic Frameworks Agl-score: algebraic graph learning score for protein– ligand binding scoring, ranking, docking, and screening
Reference 36
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Category-Specific Topological Learning of Metal-Organic Frameworks Algebraic graph-assisted bidirectional transformers for molecular property prediction
Reference 37
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Category-Specific Topological Learning of Metal-Organic Frameworks Computing persistent homology
Reference 38
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Category-Specific Topological Learning of Metal-Organic Frameworks Unresolved cited work
Reference 39
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Category-Specific Topological Learning of Metal-Organic Frameworks Path topology in molecular and materials sciences
Reference 40
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Category-Specific Topological Learning of Metal-Organic Frameworks Persistent spectral graph
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Category-Specific Topological Learning of Metal-Organic Frameworks Topologynet: Topology based deep convolutional and multi- task neural networks for biomolecular property predictions
Reference 42
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Category-Specific Topological Learning of Metal-Organic Frameworks Topological represen- tations of crystalline compounds for the machine-learning prediction of materials properties
Reference 43
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Category-Specific Topological Learning of Metal-Organic Frameworks Multiscale topology-enabled structure-to-sequence transformer for protein–ligand interaction predictions
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Category-Specific Topological Learning of Metal-Organic Frameworks Mathematical deep learning for pose and binding affinity prediction and ranking in d3r grand challenges
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Category-Specific Topological Learning of Metal-Organic Frameworks High- temperature carbon dioxide capture in a porous material with terminal zinc hydride sites
Reference 47
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Category-Specific Topological Learning of Metal-Organic Frameworks Geometry and topology for mesh generation
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Reference 49
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Category-Specific Topological Learning of Metal-Organic Frameworks Smooth surfaces for multi-scale shape representation
Reference 52
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Category-Specific Topological Learning of Metal-Organic Frameworks Barcodes: the persistent topology of data
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Category-Specific Topological Learning of Metal-Organic Frameworks Neighborhood path complex for the quantitative analysis of the structure and stability of carboranes
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Reference 57
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Category-Specific Topological Learning of Metal-Organic Frameworks Combinatorial algebraic topology , volume 21
Reference 58
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Category-Specific Topological Learning of Metal-Organic Frameworks Evolutionary khovanov homology
Reference 59
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No inbound Pith citation observations are available.