Sustainable and Tunable Synaptic Electrolyte-Gated Organic Field-Effect Transistors (EGOFETs) for Light Adaptive Visual Perceptive Systems
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2025 |
| Outros Autores: | , , , , , |
| Tipo de documento: | Artigo |
| Idioma: | eng |
| Título da fonte: | Repositório Institucional da UNESP |
| Texto Completo: | http://dx.doi.org/10.1002/adfm.202417355 https://hdl.handle.net/11449/303746 |
Resumo: | The recent advances in optic neuromorphic devices have led to a subsequent rise in the development of energy-efficient artificial-vision systems. While the energy consumption of such devices is known to be much lower than conventional vision systems, it is known that manufacturing accounts for the largest share of the climate impact in microelectronics, dominating over the product use phase. Thus, there is a need to develop sustainable manufacturing processes and to adopt low-impact materials for hardware solutions of the future. In this study, an Electrolyte-Gated Organic Field-effect Transistor (EGOFET) is experimentally demonstrated for the implementation of a high-performing synaptic optical sensor using sustainable materials that degrade to benign products at the End of Life (EoL). The device shows remarkable light response with maximum Paired-Pulse Facilitation (PPF) Index of up to 151% at a light power density of 38 µW cm−2, which enables artificial synaptic applications with an average power consumption as low as 2.4 pJ for each training process, representing one of the best among the reported results. To demonstrate the tunability of the vision system, an ensemble decision tree is used to enable the EGOFET to distinguish and remember different primary colors at different power densities with 95.6% accuracy. |
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Sustainable and Tunable Synaptic Electrolyte-Gated Organic Field-Effect Transistors (EGOFETs) for Light Adaptive Visual Perceptive Systemselectro-gated transistorsneuromorphic imaging systemoptical synaptic devicesorganic phototransistorssustainable materialsThe recent advances in optic neuromorphic devices have led to a subsequent rise in the development of energy-efficient artificial-vision systems. While the energy consumption of such devices is known to be much lower than conventional vision systems, it is known that manufacturing accounts for the largest share of the climate impact in microelectronics, dominating over the product use phase. Thus, there is a need to develop sustainable manufacturing processes and to adopt low-impact materials for hardware solutions of the future. In this study, an Electrolyte-Gated Organic Field-effect Transistor (EGOFET) is experimentally demonstrated for the implementation of a high-performing synaptic optical sensor using sustainable materials that degrade to benign products at the End of Life (EoL). The device shows remarkable light response with maximum Paired-Pulse Facilitation (PPF) Index of up to 151% at a light power density of 38 µW cm−2, which enables artificial synaptic applications with an average power consumption as low as 2.4 pJ for each training process, representing one of the best among the reported results. To demonstrate the tunability of the vision system, an ensemble decision tree is used to enable the EGOFET to distinguish and remember different primary colors at different power densities with 95.6% accuracy.Engineering and Physical Sciences Research CouncilJames Watt School of Engineering University of Glasgow, ScotlandDepartment of Physics School of Technology and Applied Sciences São Paulo State University (UNESP), Presidente Prudente, SPSchool of Science and Technology Hong Kong Metropolitan University, Ho Man TinDepartment of Physics School of Technology and Applied Sciences São Paulo State University (UNESP), Presidente Prudente, SPEngineering and Physical Sciences Research Council: EP/W019248/1University of GlasgowUniversidade Estadual Paulista (UNESP)Hong Kong Metropolitan UniversitySerghiou, TheodorosFernandes, José Diego [UNESP]Karthikeyan, VaithinathanAssi, Dani S.Vieira, Douglas Henrique [UNESP]Alves, Neri [UNESP]Kettle, Jeff2025-04-29T19:30:33Z2025-03-11info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1002/adfm.202417355Advanced Functional Materials, v. 35, n. 11, 2025.1616-30281616-301Xhttps://hdl.handle.net/11449/30374610.1002/adfm.2024173552-s2.0-86000436546Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAdvanced Functional Materialsinfo:eu-repo/semantics/openAccess2025-10-22T17:10:34Zoai:repositorio.unesp.br:11449/303746Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462025-10-22T17:10:34Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
| dc.title.none.fl_str_mv |
Sustainable and Tunable Synaptic Electrolyte-Gated Organic Field-Effect Transistors (EGOFETs) for Light Adaptive Visual Perceptive Systems |
| title |
Sustainable and Tunable Synaptic Electrolyte-Gated Organic Field-Effect Transistors (EGOFETs) for Light Adaptive Visual Perceptive Systems |
| spellingShingle |
Sustainable and Tunable Synaptic Electrolyte-Gated Organic Field-Effect Transistors (EGOFETs) for Light Adaptive Visual Perceptive Systems Serghiou, Theodoros electro-gated transistors neuromorphic imaging system optical synaptic devices organic phototransistors sustainable materials |
| title_short |
Sustainable and Tunable Synaptic Electrolyte-Gated Organic Field-Effect Transistors (EGOFETs) for Light Adaptive Visual Perceptive Systems |
| title_full |
Sustainable and Tunable Synaptic Electrolyte-Gated Organic Field-Effect Transistors (EGOFETs) for Light Adaptive Visual Perceptive Systems |
| title_fullStr |
Sustainable and Tunable Synaptic Electrolyte-Gated Organic Field-Effect Transistors (EGOFETs) for Light Adaptive Visual Perceptive Systems |
| title_full_unstemmed |
Sustainable and Tunable Synaptic Electrolyte-Gated Organic Field-Effect Transistors (EGOFETs) for Light Adaptive Visual Perceptive Systems |
| title_sort |
Sustainable and Tunable Synaptic Electrolyte-Gated Organic Field-Effect Transistors (EGOFETs) for Light Adaptive Visual Perceptive Systems |
| author |
Serghiou, Theodoros |
| author_facet |
Serghiou, Theodoros Fernandes, José Diego [UNESP] Karthikeyan, Vaithinathan Assi, Dani S. Vieira, Douglas Henrique [UNESP] Alves, Neri [UNESP] Kettle, Jeff |
| author_role |
author |
| author2 |
Fernandes, José Diego [UNESP] Karthikeyan, Vaithinathan Assi, Dani S. Vieira, Douglas Henrique [UNESP] Alves, Neri [UNESP] Kettle, Jeff |
| author2_role |
author author author author author author |
| dc.contributor.none.fl_str_mv |
University of Glasgow Universidade Estadual Paulista (UNESP) Hong Kong Metropolitan University |
| dc.contributor.author.fl_str_mv |
Serghiou, Theodoros Fernandes, José Diego [UNESP] Karthikeyan, Vaithinathan Assi, Dani S. Vieira, Douglas Henrique [UNESP] Alves, Neri [UNESP] Kettle, Jeff |
| dc.subject.por.fl_str_mv |
electro-gated transistors neuromorphic imaging system optical synaptic devices organic phototransistors sustainable materials |
| topic |
electro-gated transistors neuromorphic imaging system optical synaptic devices organic phototransistors sustainable materials |
| description |
The recent advances in optic neuromorphic devices have led to a subsequent rise in the development of energy-efficient artificial-vision systems. While the energy consumption of such devices is known to be much lower than conventional vision systems, it is known that manufacturing accounts for the largest share of the climate impact in microelectronics, dominating over the product use phase. Thus, there is a need to develop sustainable manufacturing processes and to adopt low-impact materials for hardware solutions of the future. In this study, an Electrolyte-Gated Organic Field-effect Transistor (EGOFET) is experimentally demonstrated for the implementation of a high-performing synaptic optical sensor using sustainable materials that degrade to benign products at the End of Life (EoL). The device shows remarkable light response with maximum Paired-Pulse Facilitation (PPF) Index of up to 151% at a light power density of 38 µW cm−2, which enables artificial synaptic applications with an average power consumption as low as 2.4 pJ for each training process, representing one of the best among the reported results. To demonstrate the tunability of the vision system, an ensemble decision tree is used to enable the EGOFET to distinguish and remember different primary colors at different power densities with 95.6% accuracy. |
| publishDate |
2025 |
| dc.date.none.fl_str_mv |
2025-04-29T19:30:33Z 2025-03-11 |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1002/adfm.202417355 Advanced Functional Materials, v. 35, n. 11, 2025. 1616-3028 1616-301X https://hdl.handle.net/11449/303746 10.1002/adfm.202417355 2-s2.0-86000436546 |
| url |
http://dx.doi.org/10.1002/adfm.202417355 https://hdl.handle.net/11449/303746 |
| identifier_str_mv |
Advanced Functional Materials, v. 35, n. 11, 2025. 1616-3028 1616-301X 10.1002/adfm.202417355 2-s2.0-86000436546 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
Advanced Functional Materials |
| dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
| instname_str |
Universidade Estadual Paulista (UNESP) |
| instacron_str |
UNESP |
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UNESP |
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Repositório Institucional da UNESP |
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Repositório Institucional da UNESP |
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Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
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repositoriounesp@unesp.br |
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1854949168178528256 |