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Ecofriendly Printed Wood-Based Honey-Gated Transistors for Artificial Synapse Emulation
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Orientador(es)
Resumo(s)
Printed electronics have traditionally used substrates and materials derived from fuel-based or less abundant and toxic resources, raising environmental concerns. Wood as a substrate reduces processing steps and enables the integration of intelligent functionalities in wooden furniture, offering biodegradability, nontoxicity, and derivation from renewable sources. In this work, sustainably printed transistors using zinc oxide nanoparticles as the active layer and honey electrolyte on wood substrates are demonstrated as a promising approach to reduce the environmental footprint of electronics. Despite the substrate's high roughness, the transistor exhibits excellent performance for screen-printed devices, with low on-voltage of 0.32 ± 0.12 V and high Ion/Ioff of (2.4 ± 0.9) × 104. Further analysis of hysteresis in transfer curves under varying scan rates and sweep ranges reveals the device's ability to adjust memory windows and on-current. Notably, these devices successfully emulate synapses, exhibiting neural facilitation and plasticity, indicating a shift toward sustainable computing. The device's dynamic response to single and successive presynaptic pulses demonstrates its ability to adjust synaptic weight, transition from transient to persistent memory, and pulse width-, frequency-, voltage-, and number-dependent excitatory postsynaptic currents. The successful emulation of the learning–forgetting–relearning–forgetting process underscores the device's potential for use in sustainable high-performance neuromorphic systems.
Descrição
Funding Information:
The authors acknowledge Fundação de Amparo à Pesquisa do Estado deSão Paulo (FAPESP, grants 2023/06645-5, 2022/16125-6, 2022/12332-7,2023/14843-1), Coordenação de Aperfeiçoamento de Pessoal de NívelSuperior (CAPES) - Finance Code 001, and Conselho Nacional deDesenvolvimento Científico e Tecnológico (CNPq) for the financial sup-port. The authors also acknowledge Programa de Pós-Graduação emCiência e Tecnologia de Materiais (POSMAT), Instituto Nacional deEletrônica Orgânica (INEO) for technical support. The authors acknowledge the SUPERIOT project whichhad received funding from the Smart Networks and Services JointUndertaking (SNS JU) under the European Union’s Horizon Europeresearch and innovation programme under grant agreement no 101096021, including funding under the UK government’s HorizonEurope funding guarantee. This work also received funding from the HORIZON-EIC-2023-PATHFINDERCHALLENGES-01 program [grant agreement no.101161114 (ELEGANCE)]
Publisher Copyright:
© 2024 The Author(s). Advanced Intelligent Systems published by Wiley-VCH GmbH.
Palavras-chave
artificial synapses honey-gated transistors printed electronics sustainable electronics wood substrates Artificial Intelligence Computer Vision and Pattern Recognition Human-Computer Interaction Mechanical Engineering Control and Systems Engineering Electrical and Electronic Engineering Materials Science (miscellaneous) SDG 7 - Affordable and Clean Energy SDG 12 - Responsible Consumption and Production