Data Science and High-Throughput Spectroelectrochemistry-Guided Interrogation of Sulfonate

A research dataset from Garrett W. Collins, published on figshare in 2026, containing experimental data on organic mixed ionic–electronic conductors. It includes spectroelectrochemistry measurements for 94 sulfonate anions, used to build regression models correlating performance metrics with molecular descriptors. The work identifies anions enabling doping at lower voltages for enhanced device performance.

Use Cases

• Training regression models to predict OMIEC performance based on molecular descriptors like HOMO energy and dipole moment.
• Screening electrolyte chemistries for improved doping kinetics and stability in organic electrochemical transistors.
• Identifying novel sulfonate anions for low-voltage electrochemical doping in next-generation OMIEC devices.

Strengths

• Contains experimental data for 94 distinct sulfonate anions, providing a broad chemical space for analysis.
• The dataset is 1.5 MB in size and available in XLSX format, facilitating direct analysis in spreadsheet and statistical software.
• The description details a clear research methodology using a custom-built robotic high-throughput spectroelectrochemistry platform.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last updated 2026-05-14 15:38:48; freshness should be verified.

Provenance

Source

figshare

Collection Method

Data gathered via a custom-built robotic high-throughput spectroelectrochemistry (HT-SEC) platform.

Freshness

Last updated 2026-05-14 15:38:48.