Publication2024
A data-driven compact drain current model for InGaAs FinFET using TCAD assisted machine learning approach
The record
- Type
- Publication
- Date
- 1 December 2024
- Level
- National
- Journal
- Engineering Research Express
- Volume
- 6
- Issue
- 4
- Published
- 1 December 2024
- DOI
- 10.1088/2631-8695/ad980c
- Scopus ID
- 85211433182
- ISSN
- 26318695
- Authors
- 3
- Open access
- No
- Citations
- 1
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Machine learning-based compact drain current modeling for InGaAs FinFET represents research and innovation in semiconductor technology.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-3.1 Research and development
Machine learning for semiconductor device modeling advances research and development in materials and electronics.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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Provenance
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “A data-driven compact drain current model for InGaAs FinFET using TCAD assisted machine learning approach”. Kortex.