Results 91 to 100 of about 101,043 (267)

Analog readout for optical reservoir computers

, 2012
Reservoir computing is a new, powerful and flexible machine learning technique that is easily implemented in hardware. Recently, by using a time-multiplexed architecture, hardware reservoir computers have reached performance comparable to digital ...
Duport, François, Haelterman, Marc, Massar, Serge, Paquot, Yvan, Schrauwen, Benjamin, Smerieri, Anteo   +5 more
core  

Photon Avalanching Nanoparticles: The Next Generation of Upconverting Nanomaterials?

Advanced Functional Materials, EarlyView.
This Perspective outlines the mechanistic foundations that enable photon‐avalanche (PA) behavior in lanthanide nanomaterials and contrasts them with emerging application spaces and forward‐looking design strategies. By bridging threshold engineering, energy‐transfer dynamics, and materials engineering, we provide a coherent roadmap for advancing the ...
Kimoon Lee, Yunseo Kim, Hyeong‐ku Jo, Dongjoon Yoon, Byeonghyeok Im, WonJeong Yu, Eui‐Rim On, Changhwan Lee   +7 more
wiley   +1 more source

Dispensing Volumetric Additive Manufacturing

Advanced Functional Materials, EarlyView.
Dispensing volumetric additive manufacturing (DVAM) prints 3D structures inside a photocurable resin droplet suspended from the tip of a glass pipette, enabling sequential printing without resin vats or manual part removal. Real‐time droplet profiling and ray‐tracing‐based correction compensate for optical distortion at the curved resin‐air interface ...
Hongryung Jeon, Yunsoo Lee, Seobin Park, Kyung‐Hwan Kim, Junyoung Seo, Im Doo Jung   +5 more
wiley   +1 more source

Reservoir computing with generalized readout based on generalized synchronization

Scientific Reports
Reservoir computing is a machine learning framework that exploits nonlinear dynamics, exhibiting significant computational capabilities. One of the defining characteristics of reservoir computing is that only linear output, given by a linear combination ...
Akane Ohkubo, Masanobu Inubushi
doaj   +1 more source

Dynamic Reservoir Computing with Physical Neuromorphic Networks

2025 International Joint Conference on Neural Networks (IJCNN)
8 pages, 8 figures, IJCNN 2025 ...
Xu, Yinhao, Gottwald, Georg A., Kuncic, Zdenka   +2 more
openaire   +2 more sources

Amyloidogenic Peptide Fragments Designed From Bacterial Collagen‐like Proteins Form Hydrogel

Advanced Functional Materials, EarlyView.
This study identified amyloidogenic sequence motifs in bacterial collagen‐like proteins and exploited these to design peptides that self‐assemble into β‐sheet fibers and form hydrogels. One hydrogel supported healthy fibroblast growth, showing promise for biocompatible materials. Our work demonstrates that bacterial sequences can be harnessed to create
Vamika Sagar, Xuen J Ng, Lukas Lechel, Ashish Chand Rajwar, Hendrik Bargel, Abhishek A. Jalan   +5 more
wiley   +1 more source

Gait Perception via Actual and Estimated Pneumatic Physical Reservoir Output

Advanced Intelligent Systems
Accurately identifying user needs in terms of assist timing and magnitude presents challenges for wearable power‐assist limb devices. Traditional approaches to gait perception—such as estimating joint angles and walking conditions—often rely on ...
Junyi Shen, Tetsuro Miyazaki, Swaninda Ghosh, Toshihiro Kawase, Kenji Kawashima   +4 more
doaj   +1 more source

Toward bio-inspired information processing with networks of nano-scale switching elements

, 2013
Unconventional computing explores multi-scale platforms connecting molecular-scale devices into networks for the development of scalable neuromorphic architectures, often based on new materials and components with new functionalities. We review some work
Konkoli, Zoran, Wendin, Göran
core  

Engineering Strategies for Stable and Long‐Life Alkaline Zinc‐Based Flow Batteries

Advanced Functional Materials, EarlyView.
Alkaline zinc‐based flow batteries face persistent challenges from unstable zinc deposition, including dendrite growth, passivation, corrosion, and hydrogen evolution, which severely limit cycling stability. Current research addresses these issues through coordinated electrode structuring, electrolyte regulation, and membrane design to control zinc ...
Yuran Bai, Xiaoyu Huo, Xin Long, Enkang Fu, Xusong Gong, Lei Wei, Liang An   +6 more
wiley   +1 more source

The Power of Linear Recurrent Neural Networks

, 2020
Recurrent neural networks are a powerful means to cope with time series. We show how a type of linearly activated recurrent neural networks, which we call predictive neural networks, can approximate any time-dependent function f(t) given by a number of ...
Litz, Sandra, Michael, Olivia, Obst, Oliver, Stolzenburg, Frieder   +3 more
core