Data-driven search for functional materials
Lead Research Organisation:
University of Cambridge
Department Name: Physics
Abstract
The project utilises and augments the chemistry-aware natural language processing toolkit, ChemDataExtractor, in order to automatically generate a database of seminal properties for functional materials. This database will be analysed using machine learning algorithms in order to discover underlying trends and make predictions which aim to streamline the process of novel materials discovery.
Organisations
People |
ORCID iD |
| Jacqueline Cole (Primary Supervisor) | |
| Odysseas Sierepeklis (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R513180/1 | 30/09/2018 | 29/09/2023 | |||
| 2437634 | Studentship | EP/R513180/1 | 30/09/2020 | 31/03/2024 | Odysseas Sierepeklis |
| EP/T517847/1 | 30/09/2020 | 29/09/2025 | |||
| 2437634 | Studentship | EP/T517847/1 | 30/09/2020 | 31/03/2024 | Odysseas Sierepeklis |