Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing-a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.
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http://dx.doi.org/10.1088/0957-4484/26/20/204003 | DOI Listing |
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January 2025
Environment Research Institute, Shandong University, Qingdao, 266237, China.
The direct electrochemical conversion of bicarbonate solutions (i.e., captured CO) has emerged as a sustainable approach for integrating CO capture and utilization compared to the traditional independent and sequential route.
View Article and Find Full Text PDFJ Phys Chem Lett
January 2025
Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China.
Research on memristive devices to seamlessly integrate and replicate the dynamic behaviors of biological synapses will illuminate the mechanisms underlying parallel processing and information storage in the human brain, thereby affording novel insights for the advancement of artificial intelligence. Here, an artificial electric synapse is demonstrated on a one-step Mo-selenized MoSe memristor, having not only long-term stable resistive switching characteristics (reset 0.51 ± 0.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
Beijing Institute of Technology, Research Center of Materials Science, School of Materials Science and Engineering, No.5 South Street of Zhongguancun, Haidian District, 100081, Beijing, CHINA.
Copper (Cu)-based catalysts exhibit distinctive performance in the electrochemical CO2 reduction reaction (CO2RR) with complex mechanism and sophisticated types of products. The management of key intermediates *CO and *H is a necessary factor for achieving high product selectivity, but lack of efficient and versatile strategies. Herein, we designed Pt modified Cu catalysts to effectively modulate the competitive coverage of those intermediates.
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 PDFSci Rep
January 2025
Key Laboratory of Optoelectronic Sensing and Intelligent Control, Hubei University of Science and Technology, Xianning, 437100, China.
We present a novel approach to realize three-dimensional (3D) matter wave solitons (MWSs) transformation between different optical potential wells by manipulating their depths and centers. The 3D MWSs are obtained by the square operator method, and transformed to other types (elliptical/ring/necklace) by performing time evolution with the split-step Fourier method. The effectiveness and reliability of our approach is demonstrated by comparing the transformed solitons with those obtained iteratively using the square operator method.
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