Results 221 to 230 of about 262,161 (280)

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

AI in chemical engineering: From promise to practice

open access: yesAIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew   +4 more
wiley   +1 more source

Solid–liquid equilibria in the LiOH–ethanol–water system: Solubility measurements and thermodynamic modeling

open access: yesAIChE Journal, EarlyView.
Abstract The demand for LiOH is driven by the growth of the electric vehicle industry. Evaporative crystallization of LiOH·H2O is energy intensive, whereas ethanol‐based antisolvent crystallization has emerged as a more sustainable alternative. From a process design perspective, the crystallization yield depends on the ethanol dosage, and thermodynamic
Xiaoqi Xu   +3 more
wiley   +1 more source

CFD modeling and sensitivity‐guided design of silicon filament CVD reactors

open access: yesAIChE Journal, EarlyView.
Abstract Filament‐based chemical vapor deposition (CVD) for silicon (Si) coatings is often treated as an adaptation of planar deposition. But this overlooks fundamental shifts in transport phenomena and reaction kinetics. In filament CVD, the filament acts as a substrate, heat source, and flow disruptor simultaneously. In this work, we ask: What really
G. P. Gakis   +8 more
wiley   +1 more source

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

open access: yesAdvanced 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

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