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Recent developments in the interfacing of neurons with silicon chips may pave the way for progress in constructing scalable neurocomputers. The assembly of synthetic neuronal networks with predefined synaptic connections and controlled…

Neurons and Cognition · Quantitative Biology 2009-01-16 Nikesh S. Dattani

A short overview is given of recent advances in the field of nanosemiconductors, which are suitable as materials for spin polarized transport of charge carriers. On the basis of last theoretical and experimental achievements it is shown…

Materials Science · Physics 2007-08-13 P. Kervalishvili

Microtubules (MTs) are important cytoskeletal structures, engaged in a number of specific cellular activities, including vesicular traffic, cell cyto-architecture and motility, cell division, and information processing within neuronal…

Subcellular Processes · Quantitative Biology 2007-05-23 Avner Priel , Arnolt J. Ramos , Jack A. Tuszynski , Horacio F. Cantiello

In this article, we introduce a new nanoscale electromechanical device -- a leaky memcapacitor -- and show that it may be useful for the hardware implementation of spiking neurons. The leaky memcapacitor is a movable-plate capacitor that…

Emerging Technologies · Computer Science 2024-03-05 Zixi Zhang , Yuriy V. Pershin , Ivar Martin

Learning-based methods have made significant progress in physics simulation, typically approximating dynamics with a monolithic end-to-end optimized neural network. Although these models offer an effective way to simulation, they may lose…

Machine Learning · Computer Science 2025-12-18 Yifei Li , Haixu Wu , Zeyi Xu , Tuur Stuyck , Wojciech Matusik

Synaptic plasticity allows cortical circuits to learn new tasks and to adapt to changing environments. How do cortical circuits use plasticity to acquire functions such as decision-making or working memory? Neurons are connected in complex…

Neurons and Cognition · Quantitative Biology 2023-03-08 Néstor Parga , Luis Serrano-Fernández , Joan Falcó-Roget

Synaptic memory is considered to be the main element responsible for learning and cognition in humans. Although traditionally non-volatile long-term plasticity changes have been implemented in nanoelectronic synapses for neuromorphic…

Emerging Technologies · Computer Science 2017-12-20 Abhronil Sengupta , Kaushik Roy

Neuromorphic computing devices attempt to emulate features of biological nervous systems through mimicking the properties of synapses, towards implementing the emergent properties of their counterparts, such as learning. Inspired by recent…

Neural networks have revolutionized the area of artificial intelligence and introduced transformative applications to almost every scientific field and industry. However, this success comes at a great price; the energy requirements for…

A memristor, a two-terminal nanodevice, has garnered substantial attention in recent years due to its distinctive properties and versatile applications. These nanoscale components, characterized by their simplicity of manufacture,…

Applied Physics · Physics 2025-02-20 Nikolaos Vasileiadis , Georgios Ch Sirakoulis , Panagiotis Dimitrakis

This review is written with the goal of informing public health concerns related to nanoscience, while raising awareness of nanomaterials toxicity among scientists and manufacturers handling them. We show that humans have always been…

Medical Physics · Physics 2008-01-23 Cristina Buzea , Ivan I. Pacheco , Kevin Robbie

Hydrophobically modified magnetic nanoparticles (MNPs) were encapsulated within the membrane of poly(trimethylene carbonate)-b-poly(L-glutamic acid) (PTMC-b-PGA) block copolymer vesicles using a nanoprecipitation process. This formulation…

The programmable artificial lattice, based on the controllability of coupling strengths and the scalability of multiple sites, is desperately desired in engineering metamaterials and exploring fundamental physics. In this work, we…

Applied Physics · Physics 2020-09-03 Shaochun Lin , Tian Tian , Pu Huang , Peiran Yin , Liang Zhang , Jiangfeng Du

Chronic diseases can greatly benefit from bioelectronic medicine approaches. Neuromorphic electronic circuits present ideal characteristics for the development of brain-inspired low-power implantable processing systems that can be…

Emerging Technologies · Computer Science 2021-02-22 Elisa Donati , Renate Krause , Giacomo Indiveri

Shape morphing magnetic soft materials, composed of magnetic particles in a soft polymer matrix, can transform shapes reversibly, remotely, and rapidly, finding diverse applications in actuators, soft robotics, and biomedical devices. To…

Soft Condensed Matter · Physics 2020-11-17 Xiao Kuang , Shuai Wu , Yi Jin , Qiji Ze , S. Macrae Montgomery , Liang Yue , H. Jerry Qi , Ruike Zhao

The use of magneto-optical techniques to tune the plasmonic response of nanostructures is a hot topic in active plasmonics, with fascinating implications for several plasmon-based applications and devices. For this emerging field, called…

Optics · Physics 2021-06-16 Alessio Gabbani , Gaia Petrucci , Francesco Pineider

Shape-programmable soft materials that exhibit integrated multifunctional shape manipulations, including reprogrammable, untethered, fast, and reversible shape transformation and locking, are highly desirable for a plethora of applications,…

Molecular electronics is envisioned as a promising candidate for the nanoelectronics of the future. More than a possible answer to ultimate miniaturization problem in nanoelectronics, molecular electronics is foreseen as a possible way to…

Mesoscale and Nanoscale Physics · Physics 2011-08-18 Dominique Vuillaume

This work reports on the synthesis and characterization of a new type of electrospun magnetic nanofibers (MNFs), and their application for degradation of organic pollutants using remote magnetic inductive heating. We describe a simple…

Nanoprecipitation, the rapid solvent-displacement route to nanoscale phase separation, has matured from a simple batch operation into a versatile platform for nanomaterial synthesis. This review synthesizes recent progress in…

Chemical Physics · Physics 2025-11-19 Mingbo Li , Junhao Cai , Yawen Gao
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