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Researchers repurposed semiconductor device nonidealities, like generation-recombination noise and negative differential resistance, into functional resources for advanced stochastic analog computing. This single-device approach enables multifunctional computation using existing CMOS technology.

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Area of Science:

  • Semiconductor Device Physics
  • Analog Computing Architectures
  • Materials Science

Background:

  • Intrinsic device nonidealities are typically minimized in conventional semiconductor engineering.
  • Limited attention has been given to generation-recombination (G-R) noise and impact ionization-induced negative differential resistance (NDR) compared to 1/f noise.

Purpose of the Study:

  • To demonstrate the strategic repurposing of device nonidealities for advanced stochastic analog computing.
  • To leverage G-R noise and NDR for multifunctional analog computation at the single-device level.

Main Methods:

  • Exploited deep-level channel trap-induced G-R noise and impact ionization-induced NDR in body current.
  • Utilized fully depleted silicon-on-insulator transistors fabricated in industry silicon complementary metal-oxide semiconductor (CMOS) process.
  • Achieved multifunctional computation by reconfiguring applied bias conditions.

Main Results:

  • Demonstrated G-R noise with controllable temporal correlation.
  • Achieved NDR with an unprecedented peak-to-valley ratio (2.78 × 10^4).
  • Single transistors performed stochastic encryption, deterministic signal readout, and analog inversion.

Conclusions:

  • Revealed unrecognized computational potential within mature CMOS technologies.
  • Presented a scalable and energy-efficient alternative to architectures based on exotic materials.
  • Laid the foundation for next-generation analog computing systems.