Mercapto-methylimidazole molecular memristors for high-performance resistive switching and artificial synaptic emulation
| Title | Mercapto-methylimidazole molecular memristors for high-performance resistive switching and artificial synaptic emulation |
| Publication Type | Journal Article |
| Year of Publication | 2026 |
| Authors | Karmakar, K, Ganaie, MMushtaq, Biswas, A, Betal, A, Kumar, M, Rath, AK, Sahu, S |
| Journal | Nanoscale |
| Volume | 18 |
| Issue | 31 |
| Pagination | 16710-16722 |
| Date Published | AUG |
| Type of Article | Article |
| ISSN | 2040-3364 |
| Abstract | Organic molecule-based memristive devices are promising candidates for next-generation data storage devices due to their scalability and low cost. This work discusses a resistive memory device based on a small organic molecule 2-mercapto-1-methylimidazole (MMI) and the polymer poly 4-vinylpyridine (PVP), which exhibits stable resistive switching with a high on-off ratio (5.48 & times; 103), retention over 3.6 & times; 104 s and endurance over 700 cycles. In addition to memory behavior, the MMI organic molecule-based memristor exhibits synaptic functions crucial for neuromorphic computing. The device shows analog modulation of conductance in accordance with voltage pulse protocols, mimicking essential biological learning mechanisms, including potentiation, depression, short-term plasticity (STP), long-term plasticity (LTP), and paired-pulse facilitation (PPF). The device also demonstrates associative learning via Pavlovian conditioning, demonstrating its potential as a hardware-implemented artificial synapse in emerging brain-inspired systems. The carrier transport in these devices follows multiple conduction mechanisms including trap-free and trap-assisted space-charge limited conduction (SCLC), and Ohmic conduction. The switching is attributed to metallic filament formation from the top electrode which is further supported by impedance measurements. This study highlights the potential of organic molecular memristors for next-generation memory and neuromorphic computing. |
| DOI | 10.1039/d6nr00930a |
| Type of Journal (Indian or Foreign) | Foreign |
| Impact Factor (IF) | 5.2 |

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