Matches in SemOpenAlex for { <https://semopenalex.org/work/W4377943258> ?p ?o ?g. }
- W4377943258 abstract "Abstract Organic field effect transistors (OFETs), used in the fabrication of nano‐sensors, are one of the most promising devices in organic electronics because of their lightweight, flexible, and low fabrication cost. However, the numerical modeling of such OFETs is still in an early stage due to the minimal analytical as well as numerical models presented in the literature. This research aims to demonstrate an experimentally verified machine‐learning model by investigating an OFET with polyaniline as a p‐type organic semiconductor. OFET's threshold voltage, on/off current ratio, subthreshold swing, and device mobilities are studied as the primary output chiasmatic parameters. The random‐forest machine learning model has shown the criticality of the doping effect on turning the OFET to depletion mode, with positive threshold voltage, under doping higher than cm −3 . Additionally, the study highlights the effectiveness of the gate oxide thickness in controlling the OFET threshold voltage. A 50 nm oxide thickness showed sufficiency to have a non‐depleted OFET operation." @default.
- W4377943258 created "2023-05-25" @default.
- W4377943258 creator A5004151927 @default.
- W4377943258 creator A5038128870 @default.
- W4377943258 creator A5055250850 @default.
- W4377943258 date "2023-05-23" @default.
- W4377943258 modified "2023-10-17" @default.
- W4377943258 title "<scp>OFET</scp> Informatics: Observing the impact of organic transistor's design parameters on the device output performance using a machine learning algorithm" @default.
- W4377943258 cites W1808656094 @default.
- W4377943258 cites W1983865151 @default.
- W4377943258 cites W2000125048 @default.
- W4377943258 cites W2094195430 @default.
- W4377943258 cites W2167909339 @default.
- W4377943258 cites W2604413789 @default.
- W4377943258 cites W2774559008 @default.
- W4377943258 cites W2885513136 @default.
- W4377943258 cites W2902417400 @default.
- W4377943258 cites W2905097178 @default.
- W4377943258 cites W2946987563 @default.
- W4377943258 cites W2954518636 @default.
- W4377943258 cites W2967752489 @default.
- W4377943258 cites W2970848637 @default.
- W4377943258 cites W2995178624 @default.
- W4377943258 cites W2995452390 @default.
- W4377943258 cites W3000392421 @default.
- W4377943258 cites W3013383045 @default.
- W4377943258 cites W3047043698 @default.
- W4377943258 cites W3087604987 @default.
- W4377943258 cites W3115543300 @default.
- W4377943258 cites W3127621186 @default.
- W4377943258 cites W3162788729 @default.
- W4377943258 cites W3176854579 @default.
- W4377943258 cites W3194985935 @default.
- W4377943258 cites W3196197221 @default.
- W4377943258 cites W3198742496 @default.
- W4377943258 cites W3199752646 @default.
- W4377943258 cites W3202508341 @default.
- W4377943258 cites W3202818712 @default.
- W4377943258 cites W3207473637 @default.
- W4377943258 cites W3214651688 @default.
- W4377943258 cites W4205370198 @default.
- W4377943258 cites W4205740463 @default.
- W4377943258 cites W4206215331 @default.
- W4377943258 cites W4206519438 @default.
- W4377943258 cites W4210579690 @default.
- W4377943258 cites W4214903549 @default.
- W4377943258 cites W4221070670 @default.
- W4377943258 cites W4221077024 @default.
- W4377943258 cites W4229375929 @default.
- W4377943258 cites W4312351172 @default.
- W4377943258 doi "https://doi.org/10.1002/jnm.3132" @default.
- W4377943258 hasPublicationYear "2023" @default.
- W4377943258 type Work @default.
- W4377943258 citedByCount "0" @default.
- W4377943258 crossrefType "journal-article" @default.
- W4377943258 hasAuthorship W4377943258A5004151927 @default.
- W4377943258 hasAuthorship W4377943258A5038128870 @default.
- W4377943258 hasAuthorship W4377943258A5055250850 @default.
- W4377943258 hasConcept C119599485 @default.
- W4377943258 hasConcept C127413603 @default.
- W4377943258 hasConcept C136525101 @default.
- W4377943258 hasConcept C142724271 @default.
- W4377943258 hasConcept C145598152 @default.
- W4377943258 hasConcept C165801399 @default.
- W4377943258 hasConcept C171250308 @default.
- W4377943258 hasConcept C172385210 @default.
- W4377943258 hasConcept C192562407 @default.
- W4377943258 hasConcept C195370968 @default.
- W4377943258 hasConcept C204787440 @default.
- W4377943258 hasConcept C41008148 @default.
- W4377943258 hasConcept C49040817 @default.
- W4377943258 hasConcept C71924100 @default.
- W4377943258 hasConcept C94003879 @default.
- W4377943258 hasConcept C99903730 @default.
- W4377943258 hasConceptScore W4377943258C119599485 @default.
- W4377943258 hasConceptScore W4377943258C127413603 @default.
- W4377943258 hasConceptScore W4377943258C136525101 @default.
- W4377943258 hasConceptScore W4377943258C142724271 @default.
- W4377943258 hasConceptScore W4377943258C145598152 @default.
- W4377943258 hasConceptScore W4377943258C165801399 @default.
- W4377943258 hasConceptScore W4377943258C171250308 @default.
- W4377943258 hasConceptScore W4377943258C172385210 @default.
- W4377943258 hasConceptScore W4377943258C192562407 @default.
- W4377943258 hasConceptScore W4377943258C195370968 @default.
- W4377943258 hasConceptScore W4377943258C204787440 @default.
- W4377943258 hasConceptScore W4377943258C41008148 @default.
- W4377943258 hasConceptScore W4377943258C49040817 @default.
- W4377943258 hasConceptScore W4377943258C71924100 @default.
- W4377943258 hasConceptScore W4377943258C94003879 @default.
- W4377943258 hasConceptScore W4377943258C99903730 @default.
- W4377943258 hasFunder F4320330496 @default.
- W4377943258 hasLocation W43779432581 @default.
- W4377943258 hasOpenAccess W4377943258 @default.
- W4377943258 hasPrimaryLocation W43779432581 @default.
- W4377943258 hasRelatedWork W1187139030 @default.
- W4377943258 hasRelatedWork W1592495383 @default.
- W4377943258 hasRelatedWork W1969097807 @default.
- W4377943258 hasRelatedWork W1985946025 @default.
- W4377943258 hasRelatedWork W1995644683 @default.
- W4377943258 hasRelatedWork W2020920233 @default.