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Expert in the Loop AI – Polymer Discovery

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

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Use the Dataset

This dataset is complemented by a data exploration Python notebook to help you get started:

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