Results 121 to 130 of about 1,758,407 (277)

Challenges and enablers in fluidization technology

open access: yesAIChE Journal, EarlyView.
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley   +1 more source

Magnetic field‐assisted concentration swing adsorption for CO2 capture over Fe3O4/fibrous nanosilica‐PEI adsorbent

open access: yesAIChE Journal, EarlyView.
Abstract Magnetic field‐assisted concentration swing adsorption (CSA) provides an electrification‐compatible alternative to conventional temperature swing adsorption (TSA) by enabling rapid heating/cooling and energy‐efficient regeneration under near‐isothermal conditions, thereby eliminating the need for sensible heat input.
Xiaohao Jia, Fateme Rezaei
wiley   +1 more source

SASICE: Safety and sustainability in civil engineering

open access: yes, 2011
The performance of the built environment and the construction sector are of major importance in Europe’s long term goals of sustainable development in a changing climate. At the same time, the quality of life of all European citizens needs to be improved
Azevedo, J   +10 more
core  

Perimeter‐intensified inverse Zr‐Co oxygen carrier for biomass chemical‐looping gasification with high CO selectivity

open access: yesAIChE Journal, EarlyView.
Abstract Chemical‐looping gasification (CLG) offers a promising route for renewable biomass valorization, yet conventional oxygen carrier regeneration with O₂/H₂O is energy‐intensive and often produces low‐quality syngas. Here, we develop an inverse ZrO2/Co3O4 oxygen carrier that enables selective biochar oxidation and efficient lattice‐oxygen transfer
Junling Gao   +9 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

Modeling the separation of water‐in‐oil emulsions in continuously fed gravity settlers using millifluidic experiments

open access: yesAIChE Journal, EarlyView.
Abstract Emulsion separation remains a persistent challenge in chemical and process industries due to the metastable nature of dispersed droplets. In gravity separators, the overall separation rate is governed by the formation of a densely packed zone (DPZ) of deforming and coalescing droplets that mediates between the dispersed and continuous phases ...
Andrei Zlobin   +8 more
wiley   +1 more source

Asking the 5 W's for designing next‐generation bioprocessing

open access: yesAIChE Journal, EarlyView.
Abstract Biotechnology is expanding beyond traditional, centralized fermentation and toward next‐generation bioprocessing paradigms that emphasize flexible deployment outside the laboratory with application‐specific performance. However, many bioprocesses fail to translate beyond proof‐of‐concept into industrially viable systems because early design ...
Sangdo Yook   +4 more
wiley   +1 more source

A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai   +8 more
wiley   +1 more source

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