Integrated Digital and Analog Resistive Switching in a Bis-Indolyl Derivative-Based Memristor for Artificial Synaptic Applications

🔗 원문 전체 보기 → Royal Society of Chemistry

요약

J. Mater. Chem. C, 2026, Accepted ManuscriptDOI: 10.1039/D6TC00569A, PaperRahul Deb, Swapan Majumdar, KHULOUD A. ALIBRAHIM, Abdullah Alodhayb, Debajyoti Bhattacharjee, Syed Arshad Arshad HussainIn this research, an organic memristor based on a bis-indolyl der…

본문

Integrated Digital and Analog Resistive Switching in a Bis-Indolyl Derivative-Based Memristor for Artificial Synaptic Applications

Abstract

In this research, an organic memristor based on a bis-indolyl derivative, 3,3′-((3,4-dihydroxylphenyl)methylene)bis(1H-indole) (DHPMBI), is developed for integrated digital memory, and artificial synaptic applications. The memristor with the structure, Au/DHPMBI/ITO exhibits stable bipolar resistive switching with a SET voltage of -2.04 V, RESET voltage of 1.24 V, and a memory window of ~10⁴ at 0.1 V. The device shows reliable data retention exceeding 3 × 10⁴ s, and read endurance up to 2 × 10⁴ cycles. Cycle-to-cycle and cell-to-cell variations remain below 12%, and a high device yield of 97.22% is achieved. Conduction analysis reveals trap-controlled space-charge-limited conduction in the high-resistance state. Combined time resolved fluorescence spectroscopy, and density functional theory and time-dependent density functional theory calculations demonstrate that field-induced intramolecular charge transfer and molecular polarization govern the resistive switching process, which gives rise to a long-lived charge-transfer state with an average lifetime of ~2 ns. Under sub-threshold operation (0 to ±1 V), gradual and reversible conductance modulation is observed, leading to symmetric potentiation/depression behavior, paired-pulse facilitation with 88% gain, spike-timing-dependent plasticity with 117% conductance enhancement and associative learning. These results establish DHPMBI-based memristors as promising platforms for unified memory storage and neuromorphic computing.