Palabras clave
aislante de Mott
transición metal-aislante
dióxido de vanadio
neuristor
sinaptor
Cómo citar
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Societal impact
Resumen
Las crecientes demandas energéticas de la inteligencia artificial moderna han expuesto las limitaciones fundamentales de las arquitecturas de cómputo convencionales. La computación neuromórfica, que busca emular el procesamiento de información altamente paralelo y eficiente del cerebro, ofrece una alternativa convincente cuya realización ha requerido materiales que exhiban de forma natural el comportamiento no lineal, multiestado y adaptativo que caracteriza a las neuronas y las sinapsis biológicas. En esta revisión se plantea que los materiales con electrones fuertemente correlacionados, en particular los aislantes de Mott, proporcionan exactamente ese sustrato físico. Se presenta de manera accesible la física esencial de las transiciones metal-aislante en óxidos de vanadio (VO2, V2O3) y manganitas de perovskita, y se describe cómo su comportamiento de conmutación se traduce en primitivas neuromórficas: el neuristor (neurona artificial) y el sinaptor (sinapsis artificial). La revisión se apoya ampliamente en el trabajo experimental de los autores: la visualización directa de la coexistencia de fases nanotexturadas en V2O3; la técnica de huellas del MIT para la ingeniería de la conmutación resistiva multiestado en VO2; la demostración del disparo subumbral en nanodispositivos de Mott, y la memoria analógica multiestado controlada eléctricamente en manganitas con separación de fases. Se concluye con la presentación de los principales retos y las perspectivas más prometedoras para llevar estas demostraciones de laboratorio a su aplicación en sistemas prácticos de cómputo bioinspirado.
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