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Molecularly Engineered Highly Stable Memristors with Ultra-Low Operational Voltage: Integrating Synthetic DNA with Quasi-2D Perovskites

  • Kavya S. Keremane
  • , Abhinav Gorthy
  • , Luyao Zheng
  • , Chiranth C. Ravi
  • , Haodong Wu
  • , Jiamao Zheng
  • , Neela H. Yennawar
  • , Shashank Priya
  • , Rashmi Jha
  • , Bed Poudel

Research output: Contribution to journalArticlepeer-review

Abstract

Innovative data storage and processing technologies have attracted tremendous attention alongside the rapid advancement of artificial intelligence (AI) in recent years. The growing demands drive various sectors to explore emerging semiconducting materials beyond conventional silicon and metal oxide-based non-volatile memories. Bio-derived materials such as deoxyribonucleic acid (DNA) present unique opportunities for next-generation non-volatile memory (NVM) due to their programmable architecture and exceptional information density, enabling new possibilities for biogenetic data storage. However, the electronic-biogenetic interface remains largely unexplored. Herein, we report the synthetic DNA-assisted hybrid memory devices combining quasi-2D halide perovskites (OHPs) (PEA)2(MA)n-1PbnI3n+1 (n = 2) and Ag nanoparticle (NP) embedded synthetic 22-mer DNA (Ag-synDNA) composite, demonstrating remarkable resistive switching (RS) performance. The robust Ag/(PEA)2(MA)Pb2I₇/AgNP-DNA/Pt memristor arrays demonstrate exceptional characteristics, including ultra-low operation voltage (<0.1 V), record-low power density (0.01 W/cm2), forming-free operation, stable endurance (103 cycles), and excellent retention (4 × 103 s), maintaining a high ON/OFF ratio (>105) for more than 6 weeks under ambient conditions, outperforming pristine 2D OHP and unmodified DNA-based counterparts. This synergistic integration of customized DNA and 2D OHP enhances charge transport, reduces variability, and significantly boosts storage performance, establishing hybrid DNA-perovskite memristors as promising candidates for future energy-efficient data storage applications.

Original languageEnglish (US)
Article numbere30539
JournalAdvanced Functional Materials
Volume36
Issue number34
DOIs
StatePublished - Apr 27 2026

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Materials Science
  • Condensed Matter Physics

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