Twisted Metal Intercalated Bilayer Data for Electrocatalytic Urea Synthesis

Haoxiang Zhang's dataset from figshare, last updated May 2026, contains computational results for 31 representative twisted BC4N-TM-BC4N sandwich structures. The data likely includes electronic properties and catalytic performance metrics for urea synthesis, derived from systematic screening and SISSO-based machine learning. The dataset is 51.3 KB in size and is shared under a CC-BY-NC-4.0 license.

Use Cases

• Training machine learning models for catalyst activity prediction based on the derived descriptor linking electronic properties and twist angle.
• Analyzing the relationship between metal intercalation, structural twisting, and catalytic performance for urea synthesis.
• Benchmarking new electrocatalyst designs against the 31 identified systems with optimal performance at specific twist angles.
• Studying charge redistribution and electron transfer pathways in twisted bilayer materials for multielectron coupling reactions.

Strengths

• Dataset is focused on 31 representative systems identified through stability and activity screening.
• Includes a machine-learned descriptor quantitatively correlating activity to electronic properties and twist angle.
• Results indicate a specific optimal twist angle of 98.213° for most systems, providing a concrete design parameter.

Limitations

• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The dataset's 51.3 KB size suggests a limited scope, likely containing summary results rather than raw simulation data.
• Data may reflect the specific computational methods and assumptions inherent to the theoretical study.

Provenance

Source

Haoxiang Zhang via figshare

Collection Method

Computational design and systematic investigation via density functional theory (DFT) and SISSO-based machine learning, as described.

Time Range

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Freshness

Last updated 2026-05-14 09:04:50.

Geography

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