Results 221 to 230 of about 17,255,193 (320)

AI in chemical engineering: From promise to practice

open access: yesAIChE Journal, Volume 72, Issue 7, July 2026.
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

Solubility of Glibenclamide in supercritical solvent versus pressure and temperature via development of machine learning and rain optimization algorithm. [PDF]

open access: yesSci Rep
Alotaibi HF   +9 more
europepmc   +1 more source

Dictionary‐based weak‐form training for noise‐robust series hybrid models with multiplicative unknowns

open access: yesAIChE Journal, EarlyView.
ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho   +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

Rectification of Material Model for Fibrous Materials in Compressive Mode. [PDF]

open access: yesMaterials (Basel)
Petronienė JJ   +3 more
europepmc   +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

Quadratic Motion Polynomials with Irregular Factorizations. [PDF]

open access: yesAdv Appl Clifford Algebr
Thimm DA   +3 more
europepmc   +1 more source

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