Results 61 to 70 of about 23,119 (204)

Phase Diagrams and Piezoelectric Properties of Wurtzite Al1−x−yScxGdyN Heterostructural Alloys

Advanced Science, EarlyView.
This study demonstrates ferroelectricity and piezoelectric properties improvement of quaternary wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films, guided by density functional theory calculations. Wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films have a high optical bandgap, enhanced piezoelectric ...
Julia L. Martin, Cheng‐Wei Lee, Nate S.P. Bernstein, Thi Nguyen, Ande Bryan, Eli Cooper, John S. Mangum, Sage R. Bauers, Andriy Zakutayev, Keisuke Yazawa, Prashun Gorai, Rebecca W. Smaha   +11 more
wiley   +1 more source

A Molecular Engineering Strategy to Fine‐Tune Phototoxicity of AIE Probes for Super‐Resolution Imaging of Mitochondrial Cristae Dynamics

Advanced Science, EarlyView.
Regulation of molecular packing, phototoxicity, and ROS output of AIE photosensitizers is achieved through carboxylation and alkyl‐chain‐length tuning. The probe designed via this strategy enables super‐resolution visualization of inner‐mitochondrial‐membrane cristae dynamics under controlled oxidative stress, and fluorescence‐lifetime imaging of ...
Kongqi Chen, Mengjie Wang, Chuen Kam, Zhiming Wang, Qinrong Zhang, Sijie Chen   +5 more
wiley   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Construction of Sabatier Volcanoes for CO2 Hydrogenation to C1‐2 Oxygenates Using Data‐Efficient Machine Learning

Advanced Science, EarlyView.
A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley   +1 more source

Microwave Multicomponent Synthesis

Molecules, 2009
In the manner that very important research is often performed by multidisciplinary research teams, the applications of multicomponent reactions involving the combination of multiple starting materials with different functional groups leading to the ...
Helmut M. Hügel
doaj   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

A catalyst-free multicomponent domino sequence for the diastereoselective synthesis of (E)-3-[2-arylcarbonyl-3-(arylamino)allyl]chromen-4-ones

Beilstein Journal of Organic Chemistry, 2014
The three-component domino reactions of (E)-3-(dimethylamino)-1-arylprop-2-en-1-ones, 3-formylchromone and anilines under catalyst-free conditions afforded a library of novel (E)-3-(2-arylcarbonyl-3-(arylamino)allyl)-4H-chromen-4-ones in good to ...
Pitchaimani Prasanna, Pethaiah Gunasekaran, Subbu Perumal, J. Carlos Menéndez   +3 more
doaj   +1 more source

Probing Electrocatalyst Design for Product Selectivity in CO2 Reduction

Advanced Science, EarlyView.
Selective CO2 electroreduction is controlled by catalyst structure, dynamic surface reconstruction, adsorbate interactions, and reaction microenvironment. This review summarizes Cu‐ and non‐Cu‐based catalysts, single‐atom and molecular systems, degradation pathways, and operando/computational strategies for steering CO2RR toward hydrocarbons ...
Suvodeep Sen, Bapan Biswas, Apinya Ngoipala, Julia Wiktor, Ujjwal Pal, Shalini Singh   +5 more
wiley   +1 more source

Data‐Driven Design of Self‐Adhesive Epidermal Electrodes and Sensors

Advanced Science, EarlyView.
This work presents self‐adhesive, stretchable epidermal electrodes and sensors developed through a data‐driven design framework that integrates artificial neural networks with genetic algorithms. By tailoring optimization objectives, either maximizing electrical conductivity and adhesion or enhancing piezoresistive sensitivity, the study enables the ...
Xuan Li, Shilei Wang, Milad Razbin, Danish Tahir, Chen Sang, Shuhua Peng, Markus Müllner, Wenlong Cheng, Wei Chen, Chun Hui Wang, Shuying Wu   +10 more
wiley   +1 more source