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Resistive switching devices and other components with negative differential resistance (NDR) are emerging as possible electronic constituents of next-generation computing architectures. Due to the NDR effects exhibited, switching operations…

Instrumentation and Detectors · Physics 2024-06-19 T. Hennen , E. Wichmann , R. Waser , D. J. Wouters , D. Bedau

Negative differential resistance (NDR) behavior observed in several transition metal oxides is crucial for developing next-generation memory devices and neuromorphic computing systems. NbO2-based memristors exhibit two regions of NDR at…

Mesoscale and Nanoscale Physics · Physics 2024-11-12 Nitin Kumar , Jong E. Han , Karsten Beckmann , Nathaniel Cady , G. Sambandamurthy

New nanotechnology based devices are replacing CMOS devices to overcome CMOS technology's scaling limitations. However, many such devices exhibit non-monotonic I-V characteristics and uncertain properties which lead to the negative…

Performance · Computer Science 2011-11-09 Bharat Sukhwani , Uday Padmanabhan , Janet M. Wang

In this article, we present a configurable field-effect transistor (FET), where not only polarity (n- and p-type), but the conduction mechanism of a FET can also be configured dynamically. As a result, we can have both types of devices,…

Mesoscale and Nanoscale Physics · Physics 2014-12-17 Chitrakant Sahu , Avinash Lahgere , Jawar Singh

Two-dimensional (2D) semiconductors have emerged as leading candidates for the development of low-power and multifunctional computing applications, thanks to their qualities such as layer-dependent band gap tunability, high carrier…

Field effect transistors with channels made of graphene layer(s) were explored. The graphene layer(s) contacted a distributed array of well-separated semiconductor quantum dots (QDs). The dots were embedded in nano-structured hole-array;…

Mesoscale and Nanoscale Physics · Physics 2013-07-26 Samarth Trivedi , Haim Grebel

We demonstrate a top-down fabricated reconfigurable field effect transistor (RFET) based on a silicon nanowire that can be electrostatically programmed to p- and n-configuration. The device unites a high symmetry of transfer…

We investigate the operation of dual-gate reconfigurable field-effect transistor (RFET) in the programgate at drain (PGAD) and program-gate at source (PGAS) configurations. To this end, dual-gate silicon nanowire (SiNW) FETs are fabricated…

Current-controlled (also known as "S-type") negative differential resistance (NDR) is of crucial importance to many emerging applications including neuromorphic computing and high-density memristors integration. However, the experimental…

Mesoscale and Nanoscale Physics · Physics 2019-01-23 Miao Wang , Chengyu Wang , Chenchen Wu , Qiao Li , Chen Pan , Cong Wang , Shi-Jun Liang , Feng Miao

Radio Frequency Neural Networks (RFNNs) have demonstrated advantages in realizing intelligent applications across various domains. However, as the model size of deep neural networks rapidly increases, implementing large-scale RFNN in…

Signal Processing · Electrical Eng. & Systems 2023-12-19 Yang Sui , Minning Zhu , Lingyi Huang , Chung-Tse Michael Wu , Bo Yuan

High frequency operation of tunneling real-space transfer transistor (TRSTT) in the negative differential resistance (NDR) regime is assessed by calculating the device common source unity current gain frequency (fT) range with a small…

Mesoscale and Nanoscale Physics · Physics 2011-12-12 Wen Huang , Xin Yu , Shi-Lin Zhang , Lu-Hong Mao , Jean-Pierre Leburton

The emergence of Deep Neural Networks (DNNs) in mission- and safety-critical applications brings their reliability to the front. High performance demands of DNNs require the use of specialized hardware accelerators. Systolic array…

Hardware Architecture · Computer Science 2025-11-05 Natalia Cherezova , Artur Jutman , Maksim Jenihhin

The electronic property of NiFe$_2$O$_4$ nanowire device is investigated through nonequilibrium Green's functions (NEGF) in combination with density functional theory (DFT). The electronic transport properties of NiFe$_2$O$_4$ nanowire are…

Mesoscale and Nanoscale Physics · Physics 2017-07-03 V. Nagarajan , R. Chandiramouli

Nonlinear electrical properties, such as negative differential resistance (NDR), are essential in numerous electrical circuits, including memristors. Several physical origins have been proposed to lead to the NDR phenomena in semiconductor…

Compute-in-memory accelerators built upon non-volatile memory devices excel in energy efficiency and latency when performing deep neural network (DNN) inference, thanks to their in-situ data processing capability. However, the stochastic…

Machine Learning · Computer Science 2025-08-19 Yifan Qin , Zheyu Yan , Dailin Gan , Jun Xia , Zixuan Pan , Wujie Wen , Xiaobo Sharon Hu , Yiyu Shi

Highly efficient and widely applicable working mechanisms that allow nanomaterials and devices to respond to external stimuli with controlled mechanical motions could make far-reaching impact to reconfigurable, adaptive, and robotic…

Applied Physics · Physics 2018-05-16 Zexi Liang , Donglei , Fan

Graphene nanoribbons (GNRs) have been proposed as potential building blocks for field effect transistor (FET) devices due to their quantum confinement bandgap. Here, we propose a novel GNR device concept, enabling the control of both charge…

Mesoscale and Nanoscale Physics · Physics 2017-03-03 Peter Vancso , Imre Hagymasi , Levente Tapaszto

Nanobundle network transistors (NBTs) have emerged as a viable, higher performance alternative to poly-silicon and organic transistors with possible applications in macroelectronic displays, chemical/biological sensors, and photovoltaics. A…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 N. Pimparkar , J. Guo , M. A. Alam

Indium selenide (In2Se3), a ferroelectric semiconductor, offers a unique platform for multifunctional nanoelectronics owing to the interplay between polarization dynamics, interlayer sliding, and structural polymorphism. Ferroelectric…

Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Their additive…

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