Memristors, when utilized as electronic components in circuits, can offer opportunities for the implementation of novel reconfigurable electronics. While they have been used in large arrays, studies in ensembles of devices are comparatively limited. Here we propose a vertically stacked memristor configuration with a shared middle electrode. We study the compound resistive states presented by the combined in-series devices and we alter them either by controlling each device separately, or by altering the full configuration, which depends on selective usage of the middle floating electrode. The shared middle electrode enables a rare look into the combined system, which is not normally available in vertically stacked devices. In the course of this study, it was found that separate switching of individual devices carries over its effects to the Complete device (albeit non-linearly), enabling increased resistive state range, which leads to a larger number of distinguishable states (above SNR variance limits) and hence enhanced device memory. Additionally, by applying a switching stimulus to the external electrodes it is possible to switch both devices simultaneously, making the entire configuration a voltage divider with individual memristive components. Through usage of this type of configuration and by taking advantage of the voltage division, it is possible to surge-protect fragile devices, while it was also found that simultaneous reset of stacked devices is possible, significantly reducing the required reset time in larger arrays.
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http://dx.doi.org/10.1038/s41598-022-14462-w | DOI Listing |
ACS Appl Mater Interfaces
January 2025
Department of Physics, Indian Institute of Technology Guwahati, Guwahati 781039, India.
The discovery of moiré physics in two-dimensional (2D) materials has opened new avenues for exploring unique physical and chemical properties induced by intralayer/interlayer interactions. This study reports the experimental observation of moiré patterns in 2D bismuth oxyselenide (BiOSe) nanosheets grown through one-pot chemical reaction methods and a sonication-assisted layer separations technique. Our findings demonstrate that these moiré patterns result from the angular stacking of the nanosheets at various twist angles, leading to the formation of moiré superlattices (MSLs) with distinct periodicities.
View Article and Find Full Text PDFSmall
January 2025
SUNAG Laboratory, Institute of Physics, Sachivalaya Marg, Bhubaneswar, 751 005, India.
Understanding the resistive switching (RS) behavior of oxide-based memory devices at nanoscale is crucial for advancement of high-integration density in-memory computing platforms. This study explores a comprehensive growth parameter space to address the RS behavior of pulsed-laser-deposited substoichiometric TiO (TiO) thin films in search of tailored nanoscale memristors with low-power consumption and high stability. Conductive-atomic-force-microscopy-based measurements facilitate deciphering the switching behavior at nanoscale, providing a direct avenue to understand the microstructure-property relationships.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
January 2025
Institute for Solid State Physics, Friedrich Schiller University Jena, Jena, Germany.
Memristive technology mitigates the memory wall issue in von Neumann architectures by enabling in-memory data processing. Unlike traditional complementary metal-oxide semiconductor (CMOS) technology, memristors provide a new paradigm for implementing cryptographic functions and security considerations. While prior research explores memristors for cryptographic functions and side-channel attack vulnerabilities, our study uniquely addresses memristor-oriented countermeasures.
View Article and Find Full Text PDFSci Adv
January 2025
Institute of Materials Research and Engineering (IMRE), Agency for Science Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore.
Combining physics with computational models is increasingly recognized for enhancing the performance and energy efficiency in neural networks. Physical reservoir computing uses material dynamics of physical substrates for temporal data processing. Despite the ease of training, building an efficient reservoir remains challenging.
View Article and Find Full Text PDFJ Phys Chem Lett
January 2025
Instituto de Tecnología Química (Universitat Politècnica de València-Agencia Estatal Consejo Superior de Investigaciones Científicas), Av. dels Tarongers, 46022, València, Spain.
Memristors stand out as promising components in the landscape of memory and computing. Memristors are generally defined by a conductance mechanism containing a state variable that imparts a memory effect. The current-voltage cycling causes transitions of conductance, which are determined by different physical mechanisms, such as the formation of conducting filaments in an insulating surrounding.
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