Results 91 to 100 of about 265 (212)

Modeling the limiting performance of resistive superconductor fault current limiters for 2G HTS tape

Firat University Journal of Experimental and Computational Engineering, 2022
Fault currents in power systems force valuable power system elements thermally, electro-dynamically and electromagnetically. Due to the increase in fault current levels, the installation of components resistant to fault currents and the damage of these ...
Muhsin Tunay Gençoğlu, Buğra Yılmaz
doaj  

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

An Optimal Design Approach for Resistive and Inductive Superconducting Fault Current Limiters via MCDM Techniques

Iranian Journal of Electrical and Electronic Engineering, 2011
The design process of a superconducting current limiter (SFCL) requires simulation and definition of its electrical, magnetic and thermal properties in form of equivalent circuits and mathematical models. However, any change in SFCL parameters: dimension,
H. Heydari, R. Sharifi
doaj  

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Field‐Programable Dynamics in a Soft Magnetic Actuator Enabling True Random Number Generation and Reservoir Computing

Advanced Intelligent Systems, EarlyView.
Complex dynamics, often avoided in electromechanical design, can enhance soft robotics. We develop durable magnetic soft actuators operating in tunable dynamic regimes, enabling random number generation, stochastic computing, and time‐series prediction.
Eduardo Sergio Oliveros‐Mata, Oleksandr V. Pylypovskyi, Eleonora Raimondo, Rico Illing, Yevhen Zabila, Lin Guo, Guannan Mu, Mónica Navarro López, Xu Wang, Georgios Tzortzinis, Angelos Filippatos, Gilbert Santiago Cañón Bermúdez, Francesca Garescì, Giovanni Finocchio, Denys Makarov   +14 more
wiley   +1 more source

Ising Solver Using Vertical NAND Flash Memory

Advanced Intelligent Systems, EarlyView.
Commercial V‐NAND flash memory is repurposed as a discrete‐time Ising solver by exploiting in‐memory current summation and read‐voltage‐controlled intrinsic noise. The system implements Hopfield neural‐network updates with simulated‐annealing‐like behavior, solving max‐cut problems with high accuracy and energy efficiency while using mass‐produced ...
Sung‐Ho Park, Yeongheon Yang, Jong‐Won Back, Jiseong Im, Ryun‐Han Koo, Jonghyun Ko, Dongseok Kwon, Jong‐Ho Lee   +7 more
wiley   +1 more source

Quantum Phenomena in Molecular and Biological Systems: A Decoherence‐Based Decision Framework With Falsifiable Predictions and a Failure‐Mode Taxonomy

Advanced Physics Research, EarlyView.
A physics‐grounded framework based on decoherence timescales (τ_dec vs τ_func), Markovian validity, and falsifiability criteria is applied across molecular systems to distinguish where quantum effects are necessary, marginal, or irrelevant. The analysis integrates quantum chemistry, biological quantum mechanisms, and quantum computing under a unified ...
Sarfaraz K. Niazi
wiley   +1 more source

Geometry‐Based Neural‐Network Prediction of Electron Localization Function Topology in Dense Hydrogen

Chemistry – A European Journal, EarlyView.
We present a machine‐learning framework that predicts the electron localization function (ELF) of dense hydrogen directly from atomic geometry, bypassing explicit electronic‐structure calculations. Trained on ab initio data for fluid hydrogen across multiple pressures, the model achieves high accuracy and reveals pressure‐dependent nonlocal ...
Xiaoyu Wang, Miriam Marqués, Sergio Gómez, Francesc Serratosa, Eva Zurek, Julia Contreras‐García   +5 more
wiley   +1 more source

Experimental methods in chemical engineering: Magnetometry

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Magnetometry is a non‐invasive technique to characterize the behaviour of magnetic materials of which the most common contain Fe, Co, and Ni. Vibrating sample magnetometers (VSMs) vibrate samples at a fixed frequency in a static, homogeneous magnetic field to induce a voltage in pick up coils according to Faraday's law of induction.
Michael Claeys, Dominic De Oliveira, Gregory S. Patience, M. Olga Guerrero‐Pérez   +3 more
wiley   +1 more source