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2D materials have emerged as potential building blocks for electrochemical metallization (ECM) memristors with excellent performance. The evolution dynamics of conductive filaments (CFs) directly determine the resistance switching performance of the 2D material-based ECM memristors. However, achieving controllable CFs under the operation conditions remains challenging. Here, in situ transmission electron microscopy was employed to investigate the formation and evolution of CFs in Au/MoS/Ag planar ECM memristors under electric fields, and various growth modes of CFs dependent on electric field strength were revealed. As the electric field intensity increased, the CFs exhibited diverse morphological variations, transitioning from a nanocluster-type to a continuous solid-type. Especially, the nanocluster-induced CF growth and nanobridge-assisted coalescence of nanoclusters under the electric field were observed, wherein bipolar electrochemical reactions were identified as playing a crucial role in the morphological evolution of nanoclusters and the formation of CFs. The results provide insights into the optimization of ECM planar memristors based on 2D materials.
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http://dx.doi.org/10.1021/acsnano.4c11598 | DOI Listing |
Materials (Basel)
August 2025
Institute of Physics of the Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland.
Understanding the resistive switching (RS) mechanisms in memristive devices is crucial for developing non-volatile memory technologies. Here, we investigate the memristor effect in hydrothermally grown Au-nanoseeded CuO films. Based on I-V measurements, conductive-AFM, S/TEM, and EDS analyses, we examine the changes within the switching layer associated with RS.
View Article and Find Full Text PDFAdv Mater
January 2025
Faculty of Physics, University of Warsaw, Pasteura 5, Warsaw, 02-093, Poland.
The electrochemical metallization (ECM) mechanism is emerging as a promising approach for the development of optical memristors-nonvolatile memory systems proposed for use as artificial synapses in neuromorphic computing applications. ECM memristors offer exceptional operating dynamics and power efficiency compared to other systems, but challenges with reproducible cycle-to-cycle state switching and the absence of advanced optical functionalities hinder their integration into photonic systems. In this work, an ECM free-standing memristor structure is proposed, which simultaneously offers wavelength-dependent multilevel nonvolatile optical storage, volatile light modulation, and dynamic polarization control.
View Article and Find Full Text PDFACS Nano
November 2024
SEU-FEI Nano-Pico Center, Key Laboratory of MEMS of Ministry of Education, School of Integrated Circuits, Southeast University, Nanjing 210096, China.
2D materials have emerged as potential building blocks for electrochemical metallization (ECM) memristors with excellent performance. The evolution dynamics of conductive filaments (CFs) directly determine the resistance switching performance of the 2D material-based ECM memristors. However, achieving controllable CFs under the operation conditions remains challenging.
View Article and Find Full Text PDFACS Appl Mater Interfaces
September 2024
Solid State Ionics Laboratory, Department of Physics, National Institute of Technology Silchar, Silchar, Assam 788010, India.
The threshold behavior and the ion diffusion dynamics in diffusive volatile memristors have a very uncanny resemblance to the transduction process of biological nociceptors. Hence, the diffusive memristors are considered the most suited for making artificial nociceptive systems. To facilitate their widespread adoption, it is imperative to develop polymeric or organic-inorganic hybrid material-based diffusive memristors that are economical, biocompatible, and easily processable.
View Article and Find Full Text PDFMater Horiz
August 2024
Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
Device and algorithm co-design aims to develop energy-efficient hardware that directly implements complex algorithms and optimizes algorithms to match the hardware's characteristics. Specifically, neuromorphic computing algorithms are constantly growing in complexity, necessitating an ongoing search for hardware implementations capable of handling these intricate algorithms. Here, we present a memristive Monte Carlo DropConnect (MC-DC) crossbar array developed through a hardware algorithm co-design approach.
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