Overview
Expert-in-the-Loop AI (EITL AI) for Polymer Discovery data set comprises of cyclic lactones that are adjudicated as suitable candidates for further experimental investigation. Experiment includes synthesis and characterization of the polymer materials. Adjudication accounts for the expert-level judgement about the practicality of the lactone synthesis (expectation of the low cost, short synthetic route, and high yield) and utilization as a monomer (no side-reactions, reasonable reactivity under polymerization conditions).
Dataset Metadata
| Field | Value |
|---|---|
| Format | CSV |
| License | CDLA-Sharing |
| Domain | Sequence Classification |
| Number of Records | 125,143 |
| Data Split | 118 accept and 125143 reject sequences |
| Size | 14 MB |
| Author | Nathaniel H. Park, Dmitry Zubarev |
| Dataset Origin | IBM Research |
| Dataset Version Update | Version 1.0.0 – 2020-06-15 |
| Data Coverage | N/A |
| Business Use Case | Materials Discovery: This dataset can be used to assess if a given cyclic lactone is suitable for experimental investigation. Adjudication accounts for the expert-level judgement about the practicality of the lactone synthesis (expectation of the low cost, short synthetic route, and high yield) and utilization as a monomer (no side-reactions, reasonable reactivity under polymerization conditions). |
Dataset Archive Contents
| File or Folder | Description |
|---|---|
EITLAI_CyclicLactones_ROP_v1.csv |
flat file containing the sequences and adjucation |
LICENSE.txt |
Terms of Use |
Data Glossary and Preview
Click here to explore the data glossary, sample records, and additional dataset metadata.
Use the Dataset
This dataset is complemented by a data exploration Python notebook to help you get started:
Quick access in Python (requires the pardata pypi package):
$ pip install pardata
import pardata
data = pardata.load_dataset('expert_in_the_loop_ai_polymer_discovery')