Results 161 to 170 of about 164,858 (197)

Computational and Machine‐Learning Studies of Ethylene Oligomerization

Carbon and Hydrogen, EarlyView.
This review focuses on recent advances in computational and machine‐learning studies of ethylene oligomerization, highlighting mainstream catalyst systems based on Co, Ta, Ti, Zr, and Hf, with particular emphasis on Fe‐ and Cr‐based catalysts and their controlling factors governing reactivity and LAO distribution.
Zhixin Qin, Zhihui Song, Heying Feng, Li Jin   +3 more
wiley   +1 more source

Polyphenol-Enriched Extracts from Leaves of Mediterranean Plants as Natural Inhibitors of Monoamine Oxidase (MAO)-A and MAO-B Enzymes. [PDF]

Nutrients
D'Errico A, Nasso R, Ruggiero M, Rullo R, De Vendittis E, Masullo M, Mazzeo F, Arcone R.   +7 more
europepmc   +1 more source

Oxophilicity‐Driven Potential Window Engineering Enables Scalable and Low‐Emission Paired Electrosynthesis on Asymmetric CuOx@Ag Platform

Carbon and Hydrogen, EarlyView.
An asymmetric CuOx@Ag electrocatalyst platform enables paired electrochemical valorization of glycerol and 4‐nitrophenol, while effectively decoupling both half‐reactions from OER and HER. Ag‐mediated surface engineering expands the potential window and boosts reaction selectivity, achieving > 90% Faradaic efficiencies at both electrodes.
Xulai Gong, Linjie Zhao, Yongde Long, Hongwu Chen, Jiaxin Bai, Lei Chao, Xinyou Han, Baoguang Mao, Xianwei Liu, Yuanqing Shen, Wei Liu, Bowen Liu, Husitu Lin, Yang Song, Chuangang Hu   +14 more
wiley   +1 more source

A “Two‐Pronged” Strategy Boosting the Activity and Stability of Nickel–Iron Catalysts Toward Anion Exchange Membrane Water Electrolysis

Carbon Energy, EarlyView.
A “two‐pronged” strategy has been developed to construct a substrate‐strengthened, organophosphorus‐protected nickel‐iron electrode for efficient and robust OER electrocatalysis. Owing to the reinforced catalyst–substrate interaction and minimized active site loss by organophosphorus protection, the integrated electrode serves as an robust and ...
Yansong Zhou, Tianze Xu, Tianyu Qiu, Zhitong Wang, Zhuming Mao, Yanjing Liu, Bingqian Pang, Yina Guo, Tianyang Liu, Xianlong Zhou, Qiongrong Ou, Xinlong Tian, Shuyu Zhang   +12 more
wiley   +1 more source

TET2 germline mutation in a patient with sequential lymphoid malignancies: a novel case report. [PDF]

Ann Hematol
Mao X, Shen K, Wang J, Wang Z, Ao Q, Wang C, Xiao M.   +6 more
europepmc   +1 more source

Unlocking Iron Redox Depth for High‐Energy Layered Sodium Oxide Cathodes

Carbon Energy, EarlyView.
Valence engineering strategy is introduced into layered NiFeMn‐based oxide cathodes to intensify the cationic redox capacity by reconfiguring Fe's local chemical environment and unlocking unprecedented redox depth. The cathode shows reversible O3 → P3 → OP2 transition, low volume variation, and high structural integrity.
Yadong Song, Wujie Dong, Zhuoran Lv, Bingyuan Han, Jiaming Li, Xin Wang, Xinxin Wang, Jingjing Chen, Chenlong Dong, Zhiyong Mao, Lianqi Zhang   +10 more
wiley   +1 more source

Effect of psychomotor rehabilitation on rehabilitation exercise in elderly patients with mental disorders and its impact on cognitive function and risk incidence. [PDF]

Medicine (Baltimore)
Jiang T, Li H, Ming L, Mao D.
europepmc   +1 more source

Shedding Light on Synthetic Autocatalysis: From Conventional Closed‐Shell Chemistries to Overlooked Open‐Shell Occurrences

Chemistry – A European Journal, EarlyView.
Why add another catalyst when the product itself holds the power to catalyze its own formation? Autocatalysis in synthetic chemistry enhances reaction efficiency and uncovers novel catalytic behavior across both closed‐shell and open‐shell systems, expanding reactivity and enabling innovative design strategies.
Jaspreet Kaur, Joshua P. Barham
wiley   +1 more source

Surface Engineering of Non-Equiatomic TiZrNbTaMo HEA by MAO Treatment in a Cu-Rich Electrolyte for Biomedical Applications. [PDF]

Materials (Basel)
Bonetti SP, Torrento JEM, Grandini CR, Sousa TDSP, Almeida GS, Zambuzzi WF, Correa DRN.   +6 more
europepmc   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

The Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 more
wiley   +1 more source