Cogni-e-Spin DB 1.0: open dataset of electrospinning parameter configurations and resultant nanofiber morphologies

Description:
This dataset presents a curated collection of experimental data on electrospinning processes and resulting nanofiber morphologies. Electrospinning is a widely used technique for producing nanofibers, but the relationships between input parameters (such as voltage, polymer concentration, flow rate, or humidity) and final fiber characteristics (like diameter or uniformity) are complex and often non-intuitive.

To support research, modeling, and optimization efforts, this dataset compiles 809 high-quality experimental records, each capturing key process, solution, and environmental parameters, along with the resulting nanofiber diameter and its variation. The data were manually extracted from peer-reviewed scientific publications and harmonized into a consistent, machine-learning–friendly format.

This version is a curated and filtered subset of a larger preliminary collection:

Mahdian, M., Stummer, T., Sepsik, N., Balogh-Weiser, D., Ender, F., & Pardy, T. (2025). An open dataset of electrospinning parameter configurations and resultant nanofiber morphologies [Data set]. TalTech Data Repository. https://doi.org/10.48726/vv924-p9b06

Key features:

• Covers a diverse range of materials (polymers and solvents) and experimental setups

• Includes both single and binary solvent systems

• Designed for data-driven modeling, including regression and ML

• Each record includes information such as voltage, feed rate, tip-to-collector distance, humidity, temperature, polymer type, and resulting fiber diameter