NIPAM-co-DMAEMA Dataset: Turbidimetry Curves for LCST Polymer Formulation Inverse Design

Turbidimetry data, supplementary figures, and individual turbidimetry curves for the NIPAM-co-DMAEMA dataset. The 12.7 MB ZIP file was authored by Lachlan Alexander and last updated on April 16, 2026.

Use Cases

• Train machine learning models for inverse design of polymer formulations based on turbidimetry data.
• Analyze phase transition behavior of LCST polymers based on individual turbidimetry curves.
• Validate liquid handling robotics protocols for high-throughput polymer synthesis based on the experimental data.
• Correlate polymer composition with cloud point temperatures based on the provided turbidimetry measurements.

Strengths

• Includes individual turbidimetry curves, allowing for granular analysis of phase transitions.
• Data is associated with a published paper, suggesting a research context.
• Released under a CC-BY-4.0 license, permitting reuse with attribution.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale ML.
• The 12.7 MB size suggests a small dataset, potentially limiting model complexity.

Provenance

Source

figshare

Collection Method

Likely generated via automated liquid handling robotics and turbidimetry measurements.

Time Range

null

Freshness

Last updated 2026-04-16 05:56:02; freshness should be verified.

Geography

null