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Versatile Titanium Carbide MXene Thin-Film Memristors with Adaptive Learning Behavior

With the advent of the modern era, there is a huge demand for memristor-based neuromorphic computing hardware to overcome the von Neumann bottleneck in traditional computers. Here, we have prepared two-dimensional titanium carbide (Ti3C2T x ) MXene following the conventional HF etching technique in...

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Bibliographic Details
Published in:ACS applied materials & interfaces 2024-04, Vol.16 (16), p.20693-20704
Main Authors: Thomas, Athulya, Saha, Puranjay, Sahad E, Muhammed, Krishnan K, Navaneeth, Das, Bikas C.
Format: Article
Language:English
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Summary:With the advent of the modern era, there is a huge demand for memristor-based neuromorphic computing hardware to overcome the von Neumann bottleneck in traditional computers. Here, we have prepared two-dimensional titanium carbide (Ti3C2T x ) MXene following the conventional HF etching technique in solution. After confirmation of Ti3C2T x properties by Raman scattering and crystallinity measurements, high-quality thin-film deposition is realized using an immiscible liquid–liquid interfacial growth technique. Following this, the memristor is fabricated by sandwiching a Ti3C2T x layer with a thickness of 70 nm between two electrodes. Subsequently, current–voltage (I–V) characteristics are measured, revealing a nonvolatile resistive switching property characterized by a swift switching speed of 30 ns and an impressive current On/Off ratio of approximately 103. Furthermore, it exhibits endurance through 500 cycles and retains the states for at least 1 × 104 s without observable degradation. Additionally, it maintains a current On/Off ratio of about 102 while consuming only femtojoules (fJ) of electrical energy per reading. Systematic I–V results and conductive AFM-based current mapping image analysis are converged to support the electroforming mediated filamentary conduction mechanism. Furthermore, our Ti3C2T x memristor was found to be truly versatile as an all-in-one device for demonstrating edge computation, logic gate operation, and classical conditioning of learning by the brain in Psychology.
ISSN:1944-8244
1944-8252
DOI:10.1021/acsami.3c19177