Literature DB >> 34231360

CMOS-Compatible Protonic Programmable Resistor Based on Phosphosilicate Glass Electrolyte for Analog Deep Learning.

Murat Onen1,2, Nicolas Emond2,3, Ju Li2,3,4, Bilge Yildiz2,3,4, Jesús A Del Alamo1,2.   

Abstract

Ion intercalation based programmable resistors have emerged as a potential next-generation technology for analog deep-learning applications. Proton, being the smallest ion, is a very promising candidate to enable devices with high modulation speed, low energy consumption, and enhanced endurance. In this work, we report on the first back-end CMOS-compatible nonvolatile protonic programmable resistor enabled by the integration of phosphosilicate glass (PSG) as the proton solid electrolyte layer. PSG is an outstanding solid electrolyte material that displays both excellent protonic conduction and electronic insulation characteristics. Moreover, it is a well-known material within conventional Si fabrication, which enables precise deposition control and scalability. Our scaled all-solid-state three-terminal devices show desirable modulation characteristics in terms of symmetry, retention, endurance, and energy efficiency. Protonic programmable resistors based on phosphosilicate glass, therefore, represent promising candidates to realize nanoscale analog crossbar processors for monolithic CMOS integration.

Entities:  

Keywords:  analog computing; doped silicon dioxide films; programmable resistors; proton intercalation

Year:  2021        PMID: 34231360     DOI: 10.1021/acs.nanolett.1c01614

Source DB:  PubMed          Journal:  Nano Lett        ISSN: 1530-6984            Impact factor:   11.189


  1 in total

Review 1.  Ion-Movement-Based Synaptic Device for Brain-Inspired Computing.

Authors:  Chansoo Yoon; Gwangtaek Oh; Bae Ho Park
Journal:  Nanomaterials (Basel)       Date:  2022-05-18       Impact factor: 5.719

  1 in total

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