A stochastic encoder using point defects in two-dimensional materials
While defects are undesirable for the reliability of electronic devices, particularly in scaled microelectronics, they have proven beneficial in numerous quantum and energy-harvesting applications. However, their potential for new computational paradigms, such as neuromorphic and brain-inspired computing, remains largely untapped. In this study, we harness defects in aggressively scaled field-effect transistors based on two-dimensional semiconductors to accelerate a stochastic inference engine that offers remarkable noise resilience. We use atomistic imaging, density functional theory calculations, device modeling, and low-temperature transport experiments to offer comprehensive insight into point defects in WSe<sub>2</sub> FETs and their impact on random telegraph noise. We then use random telegraph noise to construct a stochastic encoder and demonstrate enhanced inference accuracy for noise-inflicted medical-MNIST images compared to a deterministic encoder, utilizing a pre-trained spiking neural network. Our investigation underscores the importance of leveraging intrinsic point defects in 2D materials as opportunities for neuromorphic computing.
Authors
- Aaryan Oberoi (ORCID: https://orcid.org/0000-0003-1001-2198)
- Douglas E. Wolfe (ORCID: https://orcid.org/0009-0004-5090-0290)
- Saptarshi Das (ORCID: https://orcid.org/0000-0002-0188-945X)
- Joan Marie Redwing (ORCID: https://orcid.org/0000-0002-7906-452X)
- Shiva Subbulakshmi Radhakrishnan (ORCID: https://orcid.org/0000-0003-1136-7425)
- Theresia Knobloch (ORCID: https://orcid.org/0000-0001-5156-9510)
- Sergei P. Stepanoff (ORCID: https://orcid.org/0000-0002-5727-4358)
- Tibor Grasser (ORCID: https://orcid.org/0000-0001-6536-2238)
- Christoph Wilhelmer (ORCID: https://orcid.org/0000-0002-9996-2589)
- Bernhard Stampfer (ORCID: https://orcid.org/0000-0001-5424-7488)
- Dominic Waldhoer (ORCID: https://orcid.org/0000-0002-8631-5681)
- Chen Chen (ORCID: https://orcid.org/0000-0001-7165-0391)
- Subir Ghosh (ORCID: https://orcid.org/0000-0002-0883-4478)
- Harikrishnan Ravichandran (ORCID: https://orcid.org/0009-0002-2230-370X)
Institutions
- Pennsylvania State University (US)
- TU Wien (AT)
Publication Details
- Journal
- Nature Communications
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1038/s41467-024-54283-1
- Citations
- 18
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 3.76
Funders
- National Science Foundation
- U.S. Department of Defense
- Australian Government
- Defense Threat Reduction Agency
- Office of Naval Research
- Division of Materials Research
- Division of Electrical, Communications and Cyber Systems
- Army Research Office