Micromachines (Basel)
School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 41566, Republic of Korea.
Published: February 2023
In the era of digital transformation, a memristor and memristive circuit can provide an advanced computer architecture that efficiently processes a vast quantity of data. With the unique characteristic of memristor, a memristive crossbar array has been utilized for realization of nonvolatile memory, logic-in-memory circuit, and neuromorphic system. However, the crossbar array architecture suffers from leakage of current, known as the sneak current, which causes a cross-talk interference problem between adjacent memristor devices, leading to an unavoidable operational error and high power consumption. Here, we present an amorphous In-Sn-Zn-O (a-ITZO) oxide semiconductor-based selector device to address the sneak current issue. The a-ITZO-selector device is realized with the back-to-back Schottky diode with nonlinear current-voltage (I-V) characteristics. Its nonlinearity is dependent on the oxygen plasma treatment process which can suppress the surface electron accumulation layer arising on the a-ITZO surface. The a-ITZO-selector device shows reliable characteristics against electrical stress and high temperature. In addition, the selector device allows for a stable read margin over 1 Mbit of memristor crossbar array. The findings may offer a feasible solution for the development of a high-density memristor crossbar array.
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http://dx.doi.org/10.3390/mi14030506 | DOI Listing |
Nat Comput Sci
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IBM Research Europe, Rüschlikon, Switzerland.
Large language models (LLMs), with their remarkable generative capacities, have greatly impacted a range of fields, but they face scalability challenges due to their large parameter counts, which result in high costs for training and inference. The trend of increasing model sizes is exacerbating these challenges, particularly in terms of memory footprint, latency and energy consumption. Here we explore the deployment of 'mixture of experts' (MoEs) networks-networks that use conditional computing to keep computational demands low despite having many parameters-on three-dimensional (3D) non-volatile memory (NVM)-based analog in-memory computing (AIMC) hardware.
View Article and Find Full Text PDFNat Commun
January 2025
Institute of Theoretical Computer Science, Graz University of Technology, Graz, Austria.
Recent experimental studies in the awake brain have identified a rule for synaptic plasticity that is instrumental for the instantaneous creation of memory traces in area CA1 of the mammalian brain: Behavioral Time scale Synaptic Plasticity. This one-shot learning rule differs in five essential aspects from previously considered plasticity mechanisms. We introduce a transparent model for the core function of this learning rule and establish a theory that enables a principled understanding of the system of memory traces that it creates.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Physics, Indian Institute of Technology, Patna, 801106, Bihar, India.
A highly effective method for creating a supramolecular metallogel of Ni(II) ions (NiA-TA) has been developed in our work. This approach uses benzene-1,3,5-tricarboxylic acid as a low molecular weight gelator (LMWG) in DMF solvent. Rheological studies assessed the mechanical properties of the Ni(II)-metallogel, revealing its angular frequency response and thixotropic behaviour.
View Article and Find Full Text PDFACS Nano
December 2024
Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea.
Physical unclonable functions (PUFs), often referred to as digital fingerprints, are emerging as critical elements in enhancing hardware security and encryption. While significant progress has been made in developing optical and memory-based PUFs, integrating reconfigurability with sensitivity to circularly polarized light (CPL) remains largely unexplored. Here, we present a chiroptical synaptic memristor (CSM) as a reconfigurable PUF, leveraging a two-dimensional organic-inorganic halide chiral perovskite.
View Article and Find Full Text PDFACS Energy Lett
December 2024
Center for Nanophotonics, AMOLF, 1098 XG Amsterdam, The Netherlands.
The efficient conduction of mobile ions in halide perovskites is highly promising for artificial synapses (or memristive devices), devices with a conductivity that can be varied by applying a bias voltage. Here we address the challenge of downscaling halide perovskite-based artificial synapses to achieve low energy consumption and allow high-density integration. We fabricate halide perovskite artificial synapses in a back-contacted architecture to achieve microscale devices despite the high solubility of halide perovskites in polar solvents that are commonly used in lithography.
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