Flexible Laser-Induced Graphene Memristor: Fabrication and SPICE based Emulation of an Artificial Neural Network García Palomo, Mikel Ganeriwala, Mohit Dineshkumar Fernández-Sánchez, María del Carmen Motos-Espada, Roberto González Marín, Enrique Ruiz, Francisco G. Godoy Medina, Andrés Project PID2020-116518GB-I00 funded by MCIN/AEI/10.13039/501100011033; and TED2021-129769B-I00 FlexPowHar and CNS2023-143727 RECAMBIO both funded by MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR. This work also acknowledges the research project P21 00149 ENERGHENE funded by the University, Research and Innovation Council of the Board of Andalusia. M. D. Ganeriwala ac- knowledges funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 101032701. This work demonstrates laser-induced graphene memristors, fabricated using a patterning-free, low cost and simple process directly on a flexible polyimide substrate. The fabricated memristors show repeatable non-volatile bipolar resistive switching with state retention up to 103 seconds. A simple perceptron network for the classification of black-and-white images is later implemented using an experimentally extracted compact model. Successful training of the network by integrating SPICE model with MATLAB shows the possibility to emulate the on-chip learning process. Further, by properly modulating the applied voltage pulse amplitude and period, a reduction in the energy consumed by training the neural network is achieved. 2024-04-23T10:09:48Z 2024-04-23T10:09:48Z 2024 info:eu-repo/semantics/conferenceObject Published version: García Palomo, Mikel et al. Flexible Laser-Induced Graphene Memristor: Fabrication and SPICE based Emulation of an Artificial Neural Network. 2024 https://hdl.handle.net/10481/91076 eng info:eu-repo/grantAgreement/EC/H2020/101032701 http://creativecommons.org/licenses/by-nc-nd/3.0/ info:eu-repo/semantics/openAccess Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License