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ECRAM Materials, Devices, Circuits and Architectures: A Perspective.
Talin, A Alec; Li, Yiyang; Robinson, Donald A; Fuller, Elliot J; Kumar, Suhas.
Afiliación
  • Talin AA; Sandia National Laboratories, Livermore, CA, 94551, USA.
  • Li Y; Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
  • Robinson DA; Sandia National Laboratories, Livermore, CA, 94551, USA.
  • Fuller EJ; Sandia National Laboratories, Livermore, CA, 94551, USA.
  • Kumar S; Sandia National Laboratories, Livermore, CA, 94551, USA.
Adv Mater ; 35(37): e2204771, 2023 Sep.
Article en En | MEDLINE | ID: mdl-36354177
ABSTRACT
Non-von-Neumann computing using neuromorphic systems based on two-terminal resistive nonvolatile memory elements has emerged as a promising approach, but its full potential has not been realized due to the lack of materials and devices with the appropriate attributes. Unlike memristors, which require large write currents to drive phase transformations or filament growth, electrochemical random access memory (ECRAM) decouples the "write" and "read" operations using a "gate" electrode to tune the conductance state through charge-transfer reactions, and every electron transferred through the external circuit in ECRAM corresponds to the migration of ≈1 ion used to store analogue information. Like static dopants in traditional semiconductors, electrochemically inserted ions modulate the conductivity by locally perturbing a host's electronic structure; however, ECRAM does so in a dynamic and reversible manner. The resulting change in conductance can span orders of magnitude, from gradual increments needed for analog elements, to large, abrupt changes for dynamically reconfigurable adaptive architectures. In this in-depth perspective, the history of ECRAM, the recent progress in devices spanning organic, inorganic, and 2D materials, circuits, architectures, the rich portfolio of challenging, fundamental questions, and how ECRAM can be harnessed to realize a new paradigm for low-power neuromorphic computing are discussed.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Adv Mater Asunto de la revista: BIOFISICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Adv Mater Asunto de la revista: BIOFISICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
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