Artigo2026

Tunable multicomponent emission from carbon nanomaterials for neuromorphic optical synaptic functions

Optical Materials

Autores

BASTOS, Ana R.; DIAS, Lília M. S.; FU, Lianshe; PEREIRA, Rui F. P.; BERMUDEZ, Verónica de Zea; ANDRÉ, Paulo S. B.; FERREIRA, Rute A. S.

Resumo

Multi-component luminescent materials provide an effective route to engineer complex optical responses and temporal emission dynamics for neuromorphic photonics. In this work, we present a neuromorphic photonic layer based on a multi-component carbon-based nanomaterial (THR@BA) composed of a rigid boron oxide matrix derived from the calcination of boric acid (BA), which embeds three organic molecules, terephthalic acid (TPA), 1-hydroxy-2-naphthoic acid (HNA) and rhodamine B (RhB), forming a confined host-guest system with enhanced intermolecular interactions. The rigid matrix promotes energy transfer and excited-state coupling between the molecular components. The multi-component nanomaterial exhibits dual emission of fluorescence and long-lived phosphorescence and simultaneously provides complex responses upon multi-wavelength excitation. These responses result from the superposition of the optical properties of each single-component nanomaterial functionalized with the respective organic molecule, namely TPA@BA, HNA@BA, and RhB@BA. By tuning the excitation parameters, THR@BA reproduces key synaptic functions, including short- and long-term memory as well as potentiation involved in synaptic plasticity, deriving from the dynamic balance between fluorescence and phosphorescence emission with lifetimes ranging from nanoseconds to seconds. This work demonstrates that multi-component molecular systems confined within simple inorganic matrices can serve as versatile platforms for engineering programmable luminescence dynamics, making them ideal candidates for artificial optical synapses and neuromorphic computing.

Temas Prioritários

Fotônica Integrada e Tecnologias Quânticas

Laboratório(s)

Instituto de Telecomunicações

Palavras-chave

#artificial intelligence#Artificial synapse#Carbon-based nanomaterial#Neuromorphic photonics#Photoluminescence

DOI: 10.1016/j.optmat.2026.118255

Idioma: Inglês

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