Atomic Octahedral Network Data for Perovskites and Iodoplumbates

R. Patrick Xian's dataset, published on figshare in April 2026, operationalizes chemical intuition to automate the geometric parsing and classification of coordination octahedral networks using unsupervised machine learning. The 136.0 KB XLSX file contains results from analyzing two data sets: computationally generated single oxide perovskite polymorphs and measured hybrid iodoplumbate structures.

Use Cases

• Uncovering axis-dependent tilting trends in perovskite polymorphs based on geometric parsing results.
• Taxonomizing octahedral networks in hybrid iodoplumbates based on unsupervised classification.
• Detecting oxidation state changes in materials based on identified tilting trends.
• Informing high-throughput screening for specific structure types based on revealed design principles.

Strengths

• Dataset is openly available under a CC-BY-NC-4.0 license.
• Workflow is applied to two distinct material families (perovskites and iodoplumbates) to demonstrate effectiveness.
• File is provided in the widely compatible XLSX format.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect bias inherent to the specific computational and experimental sources used.

Provenance

Source

R. Patrick Xian via figshare.

Collection Method

Results from applying an automated geometric parsing and unsupervised machine learning workflow to two material data sets.

Time Range

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Freshness

Last updated 2026-04-13 12:35:33; freshness should be verified.

Geography

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