Results 191 to 200 of about 85,726 (243)

Descriptor‐Guided Computational Screening of Non‐Fullerene Acceptor Cores for Organic Solar Cells

open access: yesAdvanced Energy Materials, EarlyView.
We screen over 4000 non‐fullerene acceptors using their ionization energy, electron affinity, quadrupole, and dipole moments to select the top‐ten candidates for a given donor polymer. The workflow recovers known high‐performance motifs and reveals how molecular components influence material properties.
Kun‐Han Lin   +9 more
wiley   +1 more source

Effects of Environmental and Health Information on Willingness to Pay for Local and Organic Foods in Taiwan

open access: yesAgribusiness, EarlyView.
ABSTRACT Using a lab‐in‐the‐field experiment, we investigate how providing information about food miles and pesticide residue influences willingness to pay (WTP) for potatoes among 407 shoppers in Taiwan, split between a supermarket and a farmers market.
Chiu‐Lin Huang   +3 more
wiley   +1 more source

Regional Differences in U.S. Consumer Preferences for Native Woody Shrubs With Varying Aesthetic Characteristics

open access: yesAgribusiness, EarlyView.
ABSTRACT Native plants offer a variety of aesthetic (e.g., fall colour, fruit, flowers) and functional benefits (e.g., pollinator friendly, wildlife friendly, water management). How these benefits influence consumer choice and perceived value of native versus introduced plants is not well understood.
Alicia Rihn   +3 more
wiley   +1 more source

Is There a Market for Organic Milk in Serbia? Insights From Integrated Choice and Latent Variable Model

open access: yesAgribusiness, EarlyView.
ABSTRACT Past growth in the global organic market has been concentrated in high‐income countries, while in middle‐income countries such as Serbia the organic market remains nascent and characterized by a sparse assortment of organic products, high retail premia and limited evidence on consumer preferences and their drivers.
Milan Tatic   +3 more
wiley   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

open access: yesAdvanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez   +4 more
wiley   +1 more source

Education Without Borders: Psychological Well-Being and Associated Factors Among Children and Young People With Foreign Nationality Living in Portugal. [PDF]

open access: yesJ Sch Health
Virgolino A   +7 more
europepmc   +1 more source

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