Balancing accuracy and generalisability for predicting hole and electron reorganisation energy of next Generation organic semiconductors

Zollner, Malin and Moshfeghi, Yashar and Nematiaram, Tahereh (2025) Balancing accuracy and generalisability for predicting hole and electron reorganisation energy of next Generation organic semiconductors. In: RSC Theoretical Chemistry Graduate Student Meeting 2025, 2025-09-04 - 2025-09-05, Zoom.

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Abstract

This work investigates how input characteristics, particularly feature set length, dataset diversity and quantity, affect the performance of machine learned hole & electron reorganisation energy prediction, ultimately aiding the identification of promising organic semiconductors candidates.

ORCID iDs

Zollner, Malin ORCID: https://orcid.org/0009-0000-9662-0869

Moshfeghi, Yashar ORCID: https://orcid.org/0000-0003-4186-1088

Nematiaram, Tahereh ORCID: https://orcid.org/0000-0002-0371-4047

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• Item metadata

  Item type:	Conference or Workshop Item(Poster)
  ID code:	95783
  Dates:	Date Event 4 September 2025 Published
  Subjects:	Technology > Electrical engineering. Electronics Nuclear engineering > Production of electric energy or power
  Department:	Faculty of Science > Pure and Applied Chemistry Faculty of Science > Computer and Information Sciences
  Depositing user:	Pure Administrator
  Date deposited:	16 Mar 2026 09:36
  Last modified:	02 Jun 2026 01:31
  Related URLs:	Event
  URI:	https://strathprints.strath.ac.uk/id/eprint/95783