Results 201 to 210 of about 128,263 (290)

Recent Advances in Nano‐Microstructured Catalysts for Electrochemical Seawater Electrocatalysis

Advanced Energy Materials, EarlyView.
This review highlights advances in nano‐ and microstructured catalysts for electrochemical seawater conversion. It elucidates design principles, mechanistic understanding, and machine‐learning‐assisted discovery, and outlines key challenges and future opportunities toward efficient, selective, and durable seawater electrocatalysis.
Xiaodong Shao, Mengfang Liang, Xiaotong Han, Xu Yu, Huan Pang, Ho Seok Park   +5 more
wiley   +1 more source

Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries

Advanced Energy Materials, EarlyView.
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu, Huaping Zhao, Lizhuang Chen, Weidong Shi, Guosheng Shao, Yong Lei   +5 more
wiley   +1 more source

Supramolecularly Directed Confined Crystallization of Lamellar Carbon Nitride for Efficient Photocatalytic Hydrogen Generation

Advanced Energy Materials, EarlyView.
ABSTRACT Sustainable hydrogen generation through water splitting is key to realizing a future hydrogen economy. In this study, we achieved molecular‐level control over self‐assembled supramolecular complexes of cyanuric acid and 3‐amino 1,2,4 triazole (AT) monomers. This was coupled with molten‐salt‐assisted thermal polymerization in a eutectic mixture
Nithinraj Panangattu Dharmarajan, Mohammed Fawaz, Jae‐Hun Yang, Matej Huš, Xuan Minh Chau Ta, Ayona K. Jose, Vibin Perumalsamy, Aathira M. Sadanandan, CI Sathish, Blaž Likozar, Byoung‐Hwa Lee, Chung‐Hwan Jeon, Antonio Tricoli, Ajayan Vinu   +13 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

AIChE 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, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Band Gap Tuneability in Antiperovskite‐Based Nitrides AE3PnN and Imides AE5Pn2(NH)2 (AE = Ca, Sr; Pn = As, Sb, Bi)

Angewandte Chemie, EarlyView.
A series of imide‐based defect antiperovskites AE5Pn2(NH)2 (AE = Ca, Sr; Pn = As, Sb, Bi) has been synthesized using the ammonothermal method. DFT calculations and spectroscopy revealed direct band gaps suitable for photovoltaic absorber materials. The discovered compounds can further be used as precursors for the synthesis of AE3PnN antiperovskites as
Thanh G. Chau, Florian Wolf, Dan Han, Saloni, Teak D. Boyko, Stefan S. Rudel, Thomas Bein, Hubert Ebert, Alexander Moewes, Wolfgang Schnick   +9 more
wiley   +2 more sources

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

Deprotonative C(sp3)/C(sp2)–H (Multi)Silylation of (Hetero)Arenes Mediated by NaTMP

Angewandte Chemie, EarlyView.
An operationally simple protocol using a strongly basic sodium amide in combination with sterically emcumbered silicon electrophiles enables the deprotonative C–H (multi)silylation of a myriad of (hetero)arenes. Mechanistic investigations highlight the pivotal role of steric and coordination effects in controlling the regioselectivity and efficiency of
David Sánchez‐Roa, Sophia Belrhomari, Ana McGinley, Clevin Anto Liju, Manting Mu, Max García‐Melchor, Eva Hevia   +6 more
wiley   +2 more sources

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

Catalysis AI Agent Guides Discovering the Universal Design Principle of Cu‐Based Single‐Atom Alloy Catalysts for CO2 Electroreduction

Angewandte Chemie, EarlyView.
Artificial intelligence (AI) enables the systematic analysis and comparative evaluation of experimental and theoretical data, optimizes the catalytic reaction research workflow, and accelerates the discovery of high‐performance electrocatalysts. ABSTRACT Copper (Cu)‐based single‐atom alloys (SAAs) represent a promising strategy for optimizing the ...
Xuning Wang, Zhong Li, Di Zhang, Hao Li, Haoxiang Xu, Daojian Cheng   +5 more
wiley   +2 more sources

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