Results 141 to 150 of about 401,172 (292)

Physics‐Grounded Probabilistic Bits for Hardware‐Efficient Intelligent Inference and Optimization

Advanced Intelligent Systems, EarlyView.
Si–SiNx interface traps are harnessed as a complementary metal–oxide–semiconductor‐compatible source of controllable randomness for probabilistic bits. Pulse‐width‐programmed stochastic capture converts nanoscale defect dynamics into Boltzmann‐consistent binary outputs, while a physics‐based Simulation Program with Integrated Circuit Emphasis model ...
Dokyoung Lee, Jun‐Young Park, Joon‐Kyu Han, Sungho Kim   +3 more
wiley   +1 more source

Direct Access to Chiral Piperidines by Enantioselective HAT‐Initiated C(sp3)─H Oxidation

Angewandte Chemie, EarlyView.
The direct desymmetrization of piperidines is achieved through manganese‐catalyzed enantioselective α‐C(sp3)─H oxidation with hydrogen peroxide, affording versatile chiral N,O‐acetals in good yields and with high enantio‐ and diastereoselectivity. These intermediates provide access to diverse functionalized piperidines with retention of chirality ...
Sethuraman Muthuramalingam, Josep M. Luis, Arnau Call, Quentin Lefebvre, Matthew S. Sigman, Miquel Costas   +5 more
wiley   +2 more sources

Characterization and Selection of Contractile Actuators for Soft Robotics Operating in the Quasistatic Regime

Advanced Intelligent Systems, EarlyView.
We developed methods to characterize soft contractile actuators using force–displacement measurements in the passive state and the total force in the active state and define the operational range of thermal, electrothermal, and pneumatic muscles. A graphical method enables the selection of an actuator based on the required mechanical force–displacement
Qiong Wang, Liuyang Cheng, Jeongmin Kim, Samuel Tsai, Devin Roach, Sameh Tawfick   +5 more
wiley   +1 more source

Development of a cantilever beam generator employing vibration energy harvesting

, 2006
This paper details the development of a generator based upon a cantilever beam inertial mass system which harvests energy from ambient environmental vibrations. The paper compares the predicted results from Finite Element Analysis (FEA) of the mechanical
Tudor, M.J., Beeby, S.P., O'Donnell, T., Roy, S., Torah, R.   +4 more
core   +1 more source

Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training

Advanced Intelligent Systems, EarlyView.
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez, Raúl Parada, Jordi Casas‐Roma, Laia Subirats   +3 more
wiley   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Advanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica, Kostya S. Novoselov, Seongmin Kim, Yousung Jung, Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Marivi Fernandez‐Serra, Sara Navarro‐Rodriguez, Aakash Ashok Naik, Janine George, Ömer Hasan Omar, Victor Trinquet, Gian‐Marco Rignanese, Andrey Ustyuzhanin, Sonia Conesa‐Boj, Juan Rojo, Minh‐Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, Jose H. Garcia, Romain Gautier, Rachid Laref, Junfeng Qiao, Giovanni Pizzi, Nicola Marzari, Camilla Coletti, Antonio Rossi, Jan‐Lucas Uslu, Chiara Zanardi, Vincenzo Palermo, Wide Hogenhout, Natalia Konchakova, Peter Klein, Tejs Vegge, Stephan Roche   +38 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Perioperative management of cardiac implantable electronic devices: a state of the art narrative review. [PDF]

J Thorac Dis
Fernando RJ, Crimi E, Puttur Rajkumar K, Marchant BE, Garner CR, Eastlack SC, Hicks MH, Royster RL.   +7 more
europepmc   +1 more source

Induction or Asynchronous Generator

Induction or Asynchronous Generator
種別 ...
openaire   +1 more source

Objectives and Key Results–Driven Multiagent Framework for Mechanical Design and Simulation

Advanced Intelligent Systems, EarlyView.
Objectives and key results (OKR)‐agent, an OKR‐driven multiagent framework, turns a plain‐language engineering goal into completed mechanical simulations. Three peer agents—supervisor, modeler, and simulator—share a compact board of OKR and coordinate external molecular dynamics (MD) and finite‐element solvers through a standardized tool interface. The
Jie Tian, Lin Pang, Jixin Hou, Xiao Sun, James Jaraczewski, Xianyan Chen, Kenan Song, Xiaoming Zhai, Tianming Liu, Keke Tang, Xianqiao Wang   +10 more
wiley   +1 more source