Results 91 to 100 of about 6,454,315 (251)

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Physics‐Informed Neural Networks to Model and Control Robots: A Theoretical and Experimental Investigation

Advanced Intelligent Systems
This work concerns the application of physics‐informed neural networks to the modeling and control of complex robotic systems. Achieving this goal requires extending physics‐informed neural networks to handle nonconservative effects. These learned models
Jingyue Liu, Pablo Borja, Cosimo Della Santina   +2 more
doaj   +1 more source

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Implantable Ionic Memristors Based on Natural Polymer Heterojunctions

Advanced Functional Materials, EarlyView.
We report an implantable natural polymer‐based ionic memristor composed of hyaluronic acid, chitosan, and PDMS. The device achieved 98.94% accuracy in MNIST classification while reducing training time by 36.8% compared with a conventional artificial neural network (ANN).
Dong‐yup Lee, Byung Ik Park, Gihyeon Yim, Hyunjae Yoo, Sangjun Ma, Jundong Park, Jeong‐Yun Sun   +6 more
wiley   +1 more source

Multi-level physics informed deep learning for solving partial differential equations in computational structural mechanics

Communications Engineering
Physics-informed neural network has emerged as a promising approach for solving partial differential equations. However, it is still a challenge for the computation of structural mechanics problems since it involves solving higher-order partial ...
Weiwei He, Jinzhao Li, Xuan Kong, Lu Deng   +3 more
doaj   +1 more source

Biodegradable and Biocompatible Functional Polymers for Biomedical Applications

Advanced Functional Materials, EarlyView.
Biodegradable and biocompatible functional polymers integrate electrical, mechanical, and stimuli‐responsive functionalities while enabling programmed degradation under physiological conditions. This review introduces recent advances in conductive, shape‐memory, self‐healing, photocurable, and adhesive polymer systems, emphasizing material design ...
Won Bae Han, Shuvra Mondal, Sungkeun Han, Chan‐Hwi Eom, Venkata Ramesh Naganaboina, Suk‐Won Hwang   +5 more
wiley   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities ...
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
doaj   +1 more source

Light‐Induced Field‐Tunneling Synapses in Solution‐Processed Van Der Waals Heterostructures for Scalable, Retina‐Inspired Optical Sensing

Advanced Functional Materials, EarlyView.
A scalable, solution‐processed WSe2/ZrO2‐x van der Waals heterostructure realizes a light‐induced field‐tunneling synapse (LIFTS) that activates exclusively under bright illumination, emulating the photopic adaptation of the human retina at the device level.
Kijeong Nam, Jihyun Kim, Soobeen Ji, In Soo Kim, Sejin Kim, Eungseon Yeon, Do Kyung Hwang, Iva Plutnarová, Zdeněk Sofer, Sang Min Won, Joohoon Kang   +10 more
wiley   +1 more source

Memristive‐Gated RC‐Delay Synaptic Transistors for Time‐Encoded Analog in‐Memory Computing

Advanced Functional Materials, EarlyView.
A Memristive‐Gated Transistor for Time‐Encoded Analog In‐Memory Computing — By exploiting the RC delay of a self‐rectifying interface‐type memristor, nonlinear I–V distortion is structurally bypassed, enabling 3‐bit nonvolatile memory, spike‐timing‐based analog encoding, and hardware‐calibrated reservoir‐computing validation within a unified device ...
Yun‐Seo Shin, Eunjoo Yoo, Ki‐Hoon Son, Hyun‐Sik Kim, Dae‐Hee Han, Jeong Hyeon Son, Seung Hwan Lee, Hong‐Sub Lee   +7 more
wiley   +1 more source

Advancing deformation calculation: a physics-informed deep graph learning framework for hyperelastic materials

Advanced Modeling and Simulation in Engineering Sciences
In elastohydrodynamic lubrication (EHL) simulations, classical numerical methods like the finite difference method (FDM) and the finite element method (FEM) are commonly employed. While PINNs have proven to be a suitable alternative for fluid simulation,
Faras Brumand-Poor, Matthias Trautmann, Katharina Schmitz   +2 more
doaj   +1 more source