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

Garrett W. Collins published a dataset on figshare in May 2026 containing experimental data from a high-throughput spectroelectrochemistry platform. The dataset includes measurements for 94 sulfonate anions used to build regression models correlating OMIEC performance with molecular descriptors. It is stored in an XLSX file sized at 341.4 KB.

Use Cases

• Training regression models to predict OMIEC doping performance based on molecular descriptors like HOMO energy and dipole moment.
• Identifying electrolyte anions that enable lower-voltage doping for improved device capacitance, as described in the study.
• Analyzing relationships between anion molecular features (size, hydrogen bonding propensity) and electrochemical doping kinetics.
• Screening sulfonate anion libraries for optimal electrolyte chemistry in organic electrochemical transistor (OECT) design.

Strengths

• Dataset is based on measurements from a custom-built robotic high-throughput spectroelectrochemistry (HT-SEC) platform.
• Includes data for 94 distinct sulfonate anions.
• Models derived from the data identified three anions enabling doping at substantially lower voltages than Cl⁻.

Limitations

• The dataset is small in scale at 341.4 KB, suggesting limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Garrett W. Collins via figshare

Collection Method

Spectroelectrochemistry measurements performed using a custom-built robotic high-throughput spectroelectrochemistry (HT-SEC) platform.

Freshness

Last updated 2026-05-14 15:38:47; freshness should be verified.