Results 51 to 60 of about 1,679,460 (184)

Modulating Electrochemical CO2 Reduction Pathways via Interfacial Electric Field

Advanced Functional Materials, EarlyView.
Engineering interfacial electric fields in Cu/ITO electrodes enables precise control of CO2 reduction pathways. Charge transfer from Cu to ITO generates positively charged Cu species that steer selectivity from ethylene toward methane. This work demonstrates how interfacial electric‐field modulation can direct reaction intermediates and transform ...
Mahdi Salehi, Zhengyuan Gao, Sai Phani Kumar Vangala, Amirhossein Farzi, Hamed Heidarpour, Morgan McKee, Nikolay Kornienko, Ali Seifitokaldani   +7 more
wiley   +1 more source

CO2 Reduction on Copper‐Nitrogen‐Doped Carbon Catalysts Tuned by Pulsed Potential Electrolysis: Effect of Pulse Potential

Advanced Functional Materials, EarlyView.
This study demonstrates that pulsed potential electrolysis significantly improves CO2 reduction performance on copper‐nitrogen doped carbon electrodes. The formation of cationic copper sites and metallic clusters as a function of applied intermittent potential leads to notable selectivity changes compared to potentiostatic reduction.
Dorottya Hursán, Janis Timoshenko, Andrea Martini, Hyo Sang Jeon, Eduardo Ortega, Martina Rüscher, Arno Bergmann, Aram Yoon, Uta Hejral, Antonia Herzog, Clara Rettenmaier, Felix T. Haase, Philipp Grosse, Beatriz Roldan Cuenya   +13 more
wiley   +1 more source

Positive‐Tone Nanolithography of Antimony Trisulfide with Femtosecond Laser Wet‐Etching

Advanced Functional Materials, EarlyView.
A butyldithiocarbamic acid (BDCA) etchant is used to fabricate various micro‐ and nanoscale structures on amorphous antimony trisulfide (a‐Sb2S3) thin film via femtosecond laser etching. Numerical analysis and experimental results elucidate the patterning mechanism on gold (reflective) and quartz (transmissive) substrates.
Abhrodeep Dey, Uwe Hübner, Albane Benardais, Xiaofei Wu, Andrea Dellith, Jan Dellith, Torsten Wieduwilt, Henrik Schneidewind, Markus A Schmidt, Virginie Nazabal, Volker Deckert, Jer‐Shing Huang, Wei Wang   +12 more
wiley   +1 more source

Fast‐Responding O2 Gas Sensor Based on Luminescent Europium Metal‐Organic Frameworks (MOF‐76)

Advanced Functional Materials, EarlyView.
Luminescent MOF‐76 materials based on Eu(III) and mixed Eu(III)/Y(III) show rapid and reversible changes in emission intensity in response to O2 with very short response times. The effect is based on triplet quenching of the linker ligands that act as photosensitizers. Average emission lifetimes of a few milliseconds turn out to be mostly unaffected by
Zhenyu Zhao, Christian Weinberger, Jakob Steube, Matthias Bauer, Martin Brehm, Michael Tiemann   +5 more
wiley   +1 more source

Understanding Decoherence of the Boron Vacancy Center in Hexagonal Boron Nitride

Advanced Functional Materials, EarlyView.
State‐of‐the‐art computations unravel the intricate decoherence dynamics of the boron vacancy center in hexagonal boron nitride across magnetic fields from 0 to 3 T. Five distinct regimes emerge, dominated by nuclear spin interactions, revealing optimal coherence times of 1–20 µs in the 180–350 mT range for isotopically pure samples.
András Tárkányi, Viktor Ivády
wiley   +1 more source

Mechanical Properties of Architected Polymer Lattice Materials: A Comparative Study of Additive Manufacturing and CAD Using FEM and µ‐CT

Advanced Functional Materials, EarlyView.
This study examines how pore shape and manufacturing‐induced deviations affect the mechanical properties of 3D‐printed lattice materials with constant porosity. Combining µ‐CT analysis, FEM, and compression testing, the authors show that structural imperfections reduce stiffness and strength, while bulk material inhomogeneities probably enhance ...
Oliver Walker, Thierry Roland, Damien Favier, Antoine Egele, Michael Heymann, Cosima Stubenrauch   +5 more
wiley   +1 more source

Microporous Microgel Assemblies Facilitating the Recruitment and Osteogenic Differentiation of Progenitor Cells for Bone Regeneration

Advanced Functional Materials, EarlyView.
There is a significant need for biomaterials with well‐defined stability and bioactivity to support tissue regeneration. In this study, we developed a tunable microgel platform that enables the decoupling of stiffness from porosity, thereby promoting bone regeneration.
Silvia Pravato, Haishuo Guan, Bianca M. Carrara, Mira Jacobs, Matteo Monticelli, Lukas Moser, Thomas Moragues, Andrew J. deMello, Tomaso Zambelli, Martin Ehrbar   +9 more
wiley   +1 more source

Fermi Surface Nesting and Anomalous Hall Effect in Magnetically Frustrated Mn2PdIn

Advanced Functional Materials, EarlyView.
Mn2PdIn, a frustrated inverse Heusler alloy, showing electronic‐structure driven anomalous Hall effect with Weyl crossings, Fermi‐surface nesting and near‐zero magnetization ideal for low‐magnetization spintronics. Abstract Noncollinear magnets with near‐zero net magnetization and nontrivial bulk electronic topology hold significant promise for ...
Afsar Ahmed, Arnab Bhattacharya, Prashant Singh, Ajay Kumar, Tukai Singha, Anis Biswas, Yaroslav Mudryk, I. Das   +7 more
wiley   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source