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Related Experiment Video

Updated: May 28, 2026

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores

Published on: December 6, 2015

Mining chemical information from open patents.

David M Jessop¹, Sam E Adams, Peter Murray-Rust

¹Unilever Centre for Molecular Science Informatics, Department of Chemistry, Lensfield Road, Cambridge CB2 1EW, UK. pm286@cam.ac.uk.

Journal of Cheminformatics

|October 18, 2011

Summary

PatentEye extracts chemical reactions from patents, making scientific data machine-readable. This system improves data accessibility and usability for chemical research.

Area of Science:

Chemistry
Information Science
Data Science

Background:

Vast amounts of chemical information exist in published literature, but are largely inaccessible in machine-readable formats.
Linked Open Data principles offer a pathway to enhance scientific data availability and usability.
Chemical reaction data within patents remains largely unstructured, hindering computational analysis.

Purpose of the Study:

To develop and evaluate PatentEye, a prototype system for extracting and semantifying chemical reactions from patent literature.
To demonstrate the potential of automated data extraction for improving chemical data accessibility.

Main Methods:

Implementation of PatentEye, a system designed for chemical reaction extraction and semantification.
Processing of 667 European Patent Office (EPO) documents, representing 10 weeks of publications.

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Demonstrating the Simplicity and In Situ Temperature Monitoring of the Mechanochemical Synthesis of Metal Chalcogenides Suitable for Thermoelectrics

Demonstrating the Simplicity and In Situ Temperature Monitoring of the Mechanochemical Synthesis of Metal Chalcogenides Suitable for Thermoelectrics

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Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores

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Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

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Demonstrating the Simplicity and In Situ Temperature Monitoring of the Mechanochemical Synthesis of Metal Chalcogenides Suitable for Thermoelectrics

Demonstrating the Simplicity and In Situ Temperature Monitoring of the Mechanochemical Synthesis of Metal Chalcogenides Suitable for Thermoelectrics

Published on: August 30, 2024

Extraction and analysis of 4444 chemical reactions.

Main Results:

PatentEye achieved 78% precision and 64% recall for identifying reactants and their amounts.
Product identification accuracy reached 92%.
The system also captures Nuclear Magnetic Resonance (NMR) spectra data used for product characterization.

Conclusions:

PatentEye demonstrates a viable method for converting unstructured chemical reaction data from patents into a machine-understandable format.
This approach significantly enhances the availability and usability of chemical data, supporting advancements in scientific research.
Automated extraction of chemical reaction information from patents is crucial for leveraging Linked Open Data in chemistry.