Results 61 to 70 of about 113 (110)

Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries

open access: yesAdvanced Energy Materials, EarlyView.
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu   +5 more
wiley   +1 more source

Do Tax Incentives for Farmland Leases Increase Farm Supply? Evidence From Iowa's Beginning Farmer Tax Credit

open access: yesApplied Economic Perspectives and Policy, EarlyView.
ABSTRACT In recent decades, agriculture has become increasingly concentrated through horizontal mergers and acquisitions via corporate entities, and policy makers are concerned this will be exacerbated by the aging population of farm operators. To reduce market concentration in agriculture, many states have enacted policies to entice new prospective ...
Justin M. Ross   +2 more
wiley   +1 more source

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

open access: yesAdvanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz   +4 more
wiley   +1 more source

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

open access: yesAdvanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun   +8 more
wiley   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +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

Luminescent Donor‐Acceptor Radical With Propeller Chirality: Bright and Photostable Red Circularly Polarized Luminescence and Whispering Gallery Mode Resonance

open access: yesAngewandte Chemie, EarlyView.
A series of donor‐attached brominated chiral luminescent radicals (CzTTBrM, 2CzTTBrM, and 3CzTTBrM) was synthesized, showing red to near‐infrared (NIR) circularly polarized luminescence (CPL) with exceptionally high PLQY of up to 76% and markedly enhanced CPL brightness (BCPL). Doping into polystyrene microspheres further yields whispering gallery mode
Kazuhiro Nakamura   +14 more
wiley   +2 more sources

Sinusoidal Displacement Describes Disorder in CsPbBr<sub>3</sub> Nanocrystal Superlattices. [PDF]

open access: yesACS Nano
Filippi U   +14 more
europepmc   +1 more source

Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy

open access: yesAdvanced Intelligent Systems, EarlyView.
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi   +5 more
wiley   +1 more source

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