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Memoria flash de MoS2 contactada con Sb para búsquedas analógicas en memoria
Guoyun Gao1,2, Bo Wen1,2, Ni Yang3
1Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China.
Nature nanotechnology
|December 15, 2025
Resumen
Los investigadores desarrollaron un nuevo tipo de memoria utilizando dispositivos flash 2D MoS2 para una inteligencia artificial más rápida y eficiente energéticamente. Esta computación en memoria reduce significativamente los cuellos de botella de transferencia de datos en dispositivos de borde.
Área de la Ciencia:
- Ciencia de los Materiales
- Ingeniería Informática
- Inteligencia Artificial
Sus antecedentes:
- El hardware tradicional enfrenta cuellos de botella debido a la lenta transferencia de datos entre la memoria y el procesamiento, lo que dificulta el rendimiento de la IA y los dispositivos de borde.
- Las memorias direccionables por contenido existentes, aunque prometedoras, están limitadas por el rendimiento de los transistores de silicio.
Objetivo del estudio:
- Introducir una solución novedosa de memoria analógica direccionable por contenido.
- Superar las limitaciones de las tecnologías de memoria actuales para aplicaciones de IA.
Principales métodos:
- Se utilizaron memorias flash 2D de MoS2 de espesor atómico con contactos de antimonio semimetálico.
- Se implementó una matriz de memoria analógica direccionable por contenido de 8x16 con 256 dispositivos de memoria flash de MoS2.
- Se demostró la computación de distancia de Hamming analógica para la clasificación k-vecinos más cercanos.
Principales resultados:
- Se logró una alta corriente de lectura (60 μA μm-1) y relaciones ON/OFF (>10^9) en memorias flash 2D de MoS2.
- Se alcanzó un consumo de energía muy bajo (menos de 0.1 fJ por búsqueda por celda) y latencia (36 ps) durante las operaciones de búsqueda en memoria.
- Se demostró alta precisión, eficiencia energética y baja latencia para tareas de aprendizaje automático.
Conclusiones:
- La memoria flash 2D de MoS2 desarrollada ofrece una solución transformadora para la computación en memoria.
- Esta tecnología tiene el potencial de permitir una computación más eficiente y escalable para dispositivos de borde inteligentes.
- Se destaca el papel significativo de los materiales 2D en el avance de las capacidades de hardware para la IA.
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