Results 171 to 180 of about 51,717 (288)

New perspectives in the study of the Earth's magnetic field and climate connection: The use of transfer entropy. [PDF]

open access: yesPLoS One, 2018
Campuzano SA   +4 more
europepmc   +1 more source

Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets

open access: yesAdvanced Intelligent Discovery, EarlyView.
An experimental‐to‐computational workflow is presented that transforms experimental 3D focused ion beam‐scanning electron microscopy data into a simulation‐ready digital microstructure for multiphase functional materials. Using heavy‐rare‐earth‐free Nd–Fe–B magnets as a model system, the approach quantifies grain connectivity across complex secondary ...
Nikita Kulesh   +4 more
wiley   +1 more source

The Role of Chemistry Across Disciplines From Humanities to Life Sciences in Understanding Complexity and Emergence

open access: yesAngewandte Chemie, EarlyView.
This study explores the origins of life by linking prebiotic chemistry, the emergence of information‐carrying molecules such as RNA and proteins, and philosophical questions about consciousness. The study emphasizes the role of molecular evolution in the Central Dogma and provides insights into the chemical origins of biology and the basis of life's ...
Harald Schwalbe   +5 more
wiley   +2 more sources

Multi-centennial fluctuations of radionuclide production rates are modulated by the Earth's magnetic field. [PDF]

open access: yesSci Rep, 2018
Pavón-Carrasco FJ   +4 more
europepmc   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath   +4 more
wiley   +1 more source

Catalysis AI Agent Guides Discovering the Universal Design Principle of Cu‐Based Single‐Atom Alloy Catalysts for CO2 Electroreduction

open access: yesAngewandte Chemie, EarlyView.
Artificial intelligence (AI) enables the systematic analysis and comparative evaluation of experimental and theoretical data, optimizes the catalytic reaction research workflow, and accelerates the discovery of high‐performance electrocatalysts. ABSTRACT Copper (Cu)‐based single‐atom alloys (SAAs) represent a promising strategy for optimizing the ...
Xuning Wang   +5 more
wiley   +2 more sources

Enhancing Sensitivity across Scales with Highly Sensitive Hall Effect‐Based Auxetic Tactile Sensors

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Herein, a tactile sensor based on hall‐effect sensors with an auxetic structure, called Hall effect‐based auxetic tactile sensor (HEATS), is proposed. The change in magnetism resulting from the deformation of the auxetic structure is utilized for sensing.
Youngheon Yun   +6 more
wiley   +1 more source

Intermolecular Nuclear Spin Hyperpolarization Transfer via Cross‐Relaxation Triggers RASER of Solute Molecules

open access: yesAngewandte Chemie, EarlyView.
Radiofrequency amplification by stimulated emission of radiation (RASER) of solutes was achieved via parahydrogen‐induced polarization (PHIP) and polarization transfer from the produced hyperpolarization donors to solutes via the intermolecular nuclear Overhauser effect (NOE).
Ivan A. Trofimov   +8 more
wiley   +2 more sources

Correlation between Changes in Local Earth's Magnetic Field and Cases of Acute Myocardial Infarction. [PDF]

open access: yesInt J Environ Res Public Health, 2018
Jaruševičius G   +5 more
europepmc   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park   +8 more
wiley   +1 more source

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