Results 51 to 60 of about 37,924 (271)

Prospects of Electric Field Control in Perpendicular Magnetic Tunnel Junctions and Emerging 2D Spintronics for Ultralow Energy Memory and Logic Devices

Advanced Functional Materials, EarlyView.
Electric control of magnetic tunnel junctions offers a path to drastically reduce the energy requirements of the device. Electric field control of magnetization can be realized in a multitude of ways. These mechanisms can be integrated into existing spintronic devices to further reduce the operational energy.
Will Echtenkamp, Brahmdutta Dixit, Yifei Yang, Deyuan Lyu, Thomas Peterson, Qi Jia, Yu‐Chia Chen, Jian‐Ping Wang   +7 more
wiley   +1 more source

Demonstration of an energy-efficient Ising solver composed of Ovonic threshold switch (OTS)-based nano-oscillators (OTSNOs)

Nano Convergence
As there is an increasing need for an efficient solver of combinatorial optimization problems, much interest is paid to the Ising machine, which is a novel physics-driven computing system composed of coupled oscillators mimicking the dynamics of the ...
Young Woong Lee, Seon Jeong Kim, Jaewook Kim, Sangheon Kim, Jongkil Park, YeonJoo Jeong, Gyu Weon Hwang, Seongsik Park, Bae Ho Park, Suyoun Lee   +9 more
doaj   +1 more source

Exploring Neuromodulation for Dynamic Learning

Frontiers in Neuroscience, 2020
A continual learning system requires the ability to dynamically adapt and generalize to new tasks with access to only a few samples. In the central nervous system, across species, it is observed that continual and dynamic behavior in learning is an ...
Anurag Daram, Angel Yanguas-Gil, Dhireesha Kudithipudi   +2 more
doaj   +1 more source

Conversion of Artificial Recurrent Neural Networks to Spiking Neural Networks for Low-power Neuromorphic Hardware

, 2016
In recent years the field of neuromorphic low-power systems that consume orders of magnitude less power gained significant momentum. However, their wider use is still hindered by the lack of algorithms that can harness the strengths of such architectures.
Cassidy, Andrew, Diehl, Peter U, IEEE, Neftci, Emre, Pedroni, Bruno U, Zarrella, Guido   +5 more
core   +1 more source

Reconfigurable Three‐Dimensional Superconducting Nanoarchitectures

Advanced Functional Materials, EarlyView.
3D superconducting nanostructures offer new possibilities for emergent physical phenomena. However, fabricating complex geometries remains challenging. Here 3D nanoprinting of complex 3D superconducting nanoarchitectures is established. As well as propagating superconducting vortices in 3D, anisotropic superconducting properties with geometric ...
Elina Zhakina, Luke Alexander Turnbull, Weijie Xu, Markus König, Paul Simon, Wilder Carrillo‐Cabrera, Amalio Fernández‐Pacheco, Uri Vool, Dieter Suess, Claas Abert, Vladimir M. Fomin, Claire Donnelly   +11 more
wiley   +1 more source

PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network

, 2020
We present PyCARL, a PyNN-based common Python programming interface for hardware-software co-simulation of spiking neural network (SNN). Through PyCARL, we make the following two key contributions.
Adiraju, Prathyusha, Balaji, Adarsha, Catthoor, Francky, Das, Anup, Dutt, Nikil D., Kashyap, Hirak J., Krichmar, Jeffrey L.   +6 more
core   +1 more source

Laser‐Induced Graphene from Waste Almond Shells

Advanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova, Anna Chiara Bressi, Marina Galliani, Attilio Marino, Gianni Ciofani, Eduardo Machado‐Charry, Hilda Gomez Bernal, Alessandra Francini, Luca Sebastiani, Francesco Greco   +9 more
wiley   +1 more source

Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing

, 2016
Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons ...
Amir, Arnon, Andreopoulos, Alexander, Appuswamy, Rathinakumar, Arthur, John V., Barch, Davis R., Berg, David J., Cassidy, Andrew S., Datta, Pallab, di Nolfo, Carmelo, Esser, Steven K., Flickner, Myron D., McKinstry, Jeffrey L., Melano, Timothy, Merolla, Paul A., Modha, Dharmendra S., Taba, Brian   +15 more
core   +1 more source

Emergence of Light‐Transforming Layered Hybrid Halide Perovskites

Advanced Functional Materials, EarlyView.
The emerging class of light‐transforming layered halide perovskite materials is reviewed, outlining challenges for their development and perspectives toward application in the future. Abstract Layered hybrid halide perovskites (LHPs) have attracted considerable attention in optoelectronics.
Ghewa AlSabeh, Jovana V. Milić
wiley   +1 more source

Transport characteristics and electrochemical properties of Y3+ doped Li4Ti5O12 as anode material

Cailiao gongcheng, 2022
Li4Ti5-xYxO12 (x=0, 0.05, 0.10, 0.15, 0.20) anode materials were synthesized by ball milling assisted solid-state method used Li2CO3 and anatase TiO2 as raw materials and yttrium nitrate (Y(NO3)3·6H2O) as yttrium source.
WU Bing, LIU Lei, WANG Xianzhi, XIAO Xiao, YANG Bao, ZHAO Jintao, GU Chengqian, MA Lei   +7 more
doaj   +1 more source