Neural ordinary differential equations for predicting the temporal dynamics of a ZnO solid electrolyte FET
A neural ordinary differential equation continuous time model of a ZnO/Ta 2 O 5 synaptic Solid Electrolyte FET, with a unique negative differential resistance in its gate current characteristics.
Authors
- Xiaoyao Song (ORCID: https://orcid.org/0000-0002-8647-4324)
- S. K. Manhas (ORCID: https://orcid.org/0000-0003-3360-9683)
- Ankit Gaurav (ORCID: https://orcid.org/0000-0001-8280-1968)
- Maria Ivaldete Siqueira de Souza (ORCID: https://orcid.org/0009-0002-4833-431X)
Institutions
- Indian Institute of Technology Roorkee (IN)
- University of Sheffield (GB)
Publication Details
- Journal
- Journal of Materials Chemistry C
- Published
- 2024-12-07
- DOI
- https://doi.org/10.1039/d4tc03696d
- Citations
- 4
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.39
Funders
- UK Research and Innovation
- Indian Institute of Technology Roorkee
- Ministry of Education, India
- Scheme for Promotion of Academic and Research Collaboration
- Engineering and Physical Sciences Research Council