Hysteresis, Impedance, and Transients Effects in Halide Perovskite Solar Cells and Memory Devices Analysis by Neuron-Style Models

dc.contributor.affiliationInstituto Universitario Mixto de Tecnología Química
dc.contributor.authorBisquert, Juan
dc.contributor.funderEuropean Research Counciles_ES
dc.date.accessioned2024-07-01T18:38:08Z
dc.date.available2024-07-01T18:38:08Z
dc.date.issued2024-07es_ES
dc.description.abstract[EN] Halide perovskites are at the forefront of active research in many applications, such as high performance solar cells, photodetectors, and synapses and neurons for neuromorphic computation. As a result of ion transport and ionic-electronic interactions, current and recombination are influenced by delay and memory effects that cause hysteresis of current¿voltage curves and long switching times. A methodology to formulate device models is shown, in which the conduction and recombination electronic variables are influenced by internal state variables. The models are inspired in biological frameworks of the Hodgkin¿Huxley class of models. Here, the theoretical precedents, the main physical components of the models, and their application to describe dynamical measurements in halide perovskite devices are summarized. The application of several measurement methods is analyzed, as the current¿voltage curves at different scan rates, the impedance spectroscopy response, and the time transients. The transition from normal (capacitive) to inverted (inductive) hysteresis, and the convergence of current¿voltage curves to a stable value, are described. It is proposed that neuron-style models capture dynamical complexity with a favorable economy of parameters, toward the identification of the dominant global dynamic processes across a wide voltage span that determines the practical response of different types of devices.en_EN
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationBisquert, J. (2024). Hysteresis, Impedance, and Transients Effects in Halide Perovskite Solar Cells and Memory Devices Analysis by Neuron-Style Models. Advanced energy materials (Online). 14(6):1-35. https://doi.org/10.1002/aenm.202400442es_ES
dc.description.issue6
dc.description.sponsorshipThis work was funded by the European Research Council (ERC) via Horizon Europe Advanced Grant, grant agreement no. 101097688 ("PeroSpiker").es_ES
dc.description.upvformatpfin35es_ES
dc.description.upvformatpinicio1es_ES
dc.description.volume14
dc.identifier.doi10.1002/aenm.202400442es_ES
dc.identifier.eissn1614-6840es_ES
dc.identifier.urihttps://riunet.upv.es/handle/10251/205680
dc.languageIngléses_ES
dc.publisherJohn Wiley & Sonses_ES
dc.relation.ispartofAdvanced energy materials (Online)es_ES
dc.relation.pasarelaS\521082es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/HE/101097688/EU/Perovskite Spiking Neurons for Intelligent Networks/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ERC//20240401//Perovskite Spiking Neurons for Intelligent Networks/es_ES
dc.relation.publisherversionhttps://doi.org/10.1002/aenm.202400442es_ES
dc.relation.urihttps://doi.org/10.5281/zenodo.10972532
dc.rightsReserva de todos los derechoses_ES
dc.rights.accessRightsAbiertoes_ES
dc.subjectHysteresises_ES
dc.subjectImpedance, Memory deviceses_ES
dc.subjectTransients effectses_ES
dc.subjectPerovskite solar cellses_ES
dc.titleHysteresis, Impedance, and Transients Effects in Halide Perovskite Solar Cells and Memory Devices Analysis by Neuron-Style Modelses_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
person.identifier302749
person.identifier.orcid0000-0003-4987-4887
relation.isAuthorOfPublicationac76c529-a55b-47a6-b7f7-18e17a41c318
relation.isAuthorOfPublication.latestForDiscoveryac76c529-a55b-47a6-b7f7-18e17a41c318
relation.isOrgUnitOfPublicationb97c2806-5147-442a-a1a8-a2c75cc2a941
relation.isOrgUnitOfPublication.latestForDiscoveryb97c2806-5147-442a-a1a8-a2c75cc2a941
upv.uuid4645afe2-324a-43ab-ba74-cbc2bdf2128des_ES

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