Synaptic learning functionalities of inverse biomemristive device based on trypsin for artificial intelligence application

Trishala R. Desai, Tukaram D. Dongale, Swapnil R. Patil, Arpita Pandey Tiwari, Pankaj K. Pawar, Rajanish K. Kamat, Tae Geun Kim

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents an organic memristive device based on the soft and quasi-liquid trypsin biomaterial. Accordingly, trypsin is isolated from the bovine pancreas and deposited on a conducting fluorine-doped tin oxide (FTO) substrate. The current-voltage (I-V) measurements of the trypsin/FTO device show a hysteresis loop at multiple frequencies and voltages. The results demonstrate that the current and resistance of the device can be modulated by altering the frequency and magnitude of the applied signal, suggesting the feasibility of this material for brain-inspired computing devices. The hysteresis area of the device increases in proportion to the frequency of the signal, signifying the inverse-memristive phenomenon. The time-domain flux, time-domain charge, and charge-flux properties are calculated from the experimental I-V data to demonstrate the memristive nature of the trypsin hydrogel. Interestingly, the trypsin hydrogel memristive device mimics bio-synaptic properties such as potentiation-depression and four complex spike-time-dependent plasticity learning rules. Electrochemical studies are performed to understand the electrochemical kinetics of the device. A possible switching mechanism is illustrated to show the memristive effect of the trypsin hydrogel. The results of the present investigation suggest that trypsin can be a possible biomaterial to develop an electronic synaptic device for neuromorphic computing applications.

Original languageEnglish
Pages (from-to)1100-1110
Number of pages11
JournalJournal of Materials Research and Technology
Volume11
DOIs
Publication statusPublished - 2021 Mar

Keywords

  • Biomaterial
  • Inverse-memristive device
  • Resistive switching
  • Synaptic learning
  • Trypsin

ASJC Scopus subject areas

  • Ceramics and Composites
  • Biomaterials
  • Surfaces, Coatings and Films
  • Metals and Alloys

Fingerprint Dive into the research topics of 'Synaptic learning functionalities of inverse biomemristive device based on trypsin for artificial intelligence application'. Together they form a unique fingerprint.

Cite this