Results 171 to 180 of about 7,226 (242)

Challenges and enablers in fluidization technology

AIChE 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

Alkali Treatment Implications for Microwave-Assisted Rare Earth Elements Extraction from Coal Mine Tailings. [PDF]

Environ Sci Technol
Ajayi LO, Lejeune B, Struppe J, Guo J, Daramola DA, Daramola DA.   +5 more
europepmc   +1 more source

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

AIChE 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, Chentao He, Janet A. W. Elliott, Liuyin Xia   +3 more
wiley   +1 more source

Shrinkage and Creep Properties of Low-Carbon Hybrid Cement. [PDF]

Materials (Basel)
Šmilauer V, Dohnalová L, Martauz P.
europepmc   +1 more source

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

Soluble Epoxide Hydrolase Inhibitors Improve Cornea Alkali Wound Healing. [PDF]

FASEB J
Lu X, Morisseau C, Jain K, Chen Z, Estes AJ, Zeldin D, Gruzdev A, Ahmed A, Cook H, Hammock BD, Watsky MA.   +10 more
europepmc   +1 more source

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

Neighboring Alkali Cations as an Efficient Strategy for N₂ Activation: A DFT Analysis. [PDF]

Int J Mol Sci
Villa-Arpi JC, Guañuna R, Saucedo-Vazquez JP, Terencio T.   +3 more
europepmc   +1 more source

Materials Representation Learning Based on a Material–Motif Network and Heterogeneous Graphs

Advanced Intelligent Discovery, EarlyView.
Structure motifs in materials are used to construct a bipartite material–motif network that links each material to its constituent motifs and establishes connectivity among materials sharing common motifs. Network analysis reveals material clusters associated with different functional applications and supports motif‐guided screening of materials.
Anoj Aryal, Weiyi Gong, Huta Banjade, Qimin Yan   +3 more
wiley   +1 more source

Comprehensive evaluation of compound saline-alkali tolerance and gene mining by GWAS in Vicia faba L. [PDF]

BMC Plant Biol
Peng X, Zhou X, Sun Z, Wu X, Teng C, Hou W, Li P, Zheng D, Zhang H, Fan H, Liu Y.   +10 more
europepmc   +1 more source