Results 181 to 190 of about 263,843 (270)

Animal‐Based Brands Taking the Plant‐Based Opportunity: A Tasting Experiment Exploring Consumer Acceptance of Plant‐Based Brand Extensions

open access: yesAgribusiness, EarlyView.
ABSTRACT This study investigates how consumer taste and brand equity perceptions shape the acceptance of plant‐based milk products. Using a blind/informed tasting experiment, we evaluated consumers' willingness to buy (WTB) and taste perception of a plant‐based milk alternative produced by a traditional dairy brand, compared with competing plant‐based ...
Federico Parmiggiani   +6 more
wiley   +1 more source

Design and optimization of processes for recovering rare earth elements from end‐of‐life permanent magnets

open access: yesAIChE Journal, EarlyView.
Abstract Recovery of rare earth elements (REEs) from end‐of‐life (EOL) products represents a strategic opportunity to strengthen the domestic supply chain for rare earth elements. This work presents a superstructure‐based optimization framework for finding the most economical processing pathway for different EOL rare earth permanent magnets (REPMs ...
Chris Laliwala   +6 more
wiley   +1 more source

A multiscale Bayesian optimization framework for process and material codesign

open access: yesAIChE Journal, EarlyView.
Abstract The simultaneous design of processes and enabling materials such as solvents, catalysts, and adsorbents is challenging because molecular‐ and process‐level decisions are strongly interdependent. Sequential approaches often yield suboptimal results since improvements in material properties may not translate into superior process performance. We
Michael Baldea
wiley   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

open access: yesAdvanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob   +2 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

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