Results 161 to 170 of about 778,284 (301)

Flexibility and Dynamicity Enhances and Controls Supramolecular Self‐Assembly of Zinc(II) Metallogels

Advanced Functional Materials, EarlyView.
Zinc(II) coordination complexes with tunable aryloxy‐imine ligands exhibit controllable supramolecular self‐assembly into hierarchical fibrous structures. Coordination‐driven stacking, not π–π interactions, enables gelation, dynamic assembly/disassembly, and enhanced nanomechanical properties.
Merlin R. Stühler, Hesam Makki, Dorothee Silbernagl, Mathias Dimde, Kai Ludwig, Bengt E. Tegner, Christopher Greve, Konstantin Rausch, Eva M. Herzig, Anna Köhler, Alex J. Plajer   +10 more
wiley   +1 more source

The trajectoRIR database: room acoustic recordings along a trajectory of moving microphones. [PDF]

J Audio Speech Music Process
Damiano S, MacWilliam K, Lorenzoni V, Dietzen T, van Waterschoot T.   +4 more
europepmc   +1 more source

Electroactive Metal–Organic Frameworks for Electrocatalysis

Advanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska, Yutong Luo, Ruyan Zhao, Jianjun Zhang, Mingchao Wang, Xinliang Feng, Eike Brunner, Stefan Kaskel   +7 more
wiley   +1 more source

Multilateration-based needle tracking with 3D ultrasound imaging for guiding minimally invasive procedures. [PDF]

Phys Med Biol
Liang W, Baker C, Rostami J, West S, Diamantopoulos A, Ourselin S, Peralta L, Xia W.   +7 more
europepmc   +1 more source

On‐Surface Indigo‐Based Bimolecular Coordination Networks with Programmable Regular or Vitreous Structure

Advanced Functional Materials, EarlyView.
A previously unreported coordination motif stabilising single Fe atoms by indigo chelation and pyridyl coordination on Au(111) has been revealed. By using planar tritopic pyridyl linkers (TPyB), extended 2D porous networks of indigo3(TPyB)2Fe6 form. These networks can be crystalline or vitreous and offer an environment where individual coordination ...
Hongxiang Xu, Ritam Chakraborty, Biao Yang, Dennis Meier, Joachim Reichert, Svetlana Klyatskaya, Mario Ruben, Shobhana Narasimhan, Johannes V. Barth, Anthoula C. Papageorgiou   +9 more
wiley   +1 more source

Enhanced Range Resolution Beamforming for Subarray-Based FDA. [PDF]

Sensors (Basel)
Wang A, Lu Y, Xu Y.
europepmc   +1 more source

Photoswitching Conduction in Framework Materials

Advanced Functional Materials, EarlyView.
This mini‐review summarizes recent advances in state‐of‐the‐art proton and electron conduction in framework materials that can be remotely and reversibly switched on and off by light. It discusses the various photoswitching conduction mechanisms and the strategies employed to enhance photoswitched conductivity.
Helmy Pacheco Hernandez, Stefan Hecht, Wolfgang Wenzel, Lars Heinke, Mariana Kozlowska   +4 more
wiley   +1 more source

3D‐Printed Sulfur‐Derived Polymers With Controlled Architectures for Lithium‐Sulfur Batteries

Advanced Functional Materials, EarlyView.
Rheology‐guided formulation design for direct ink writing enables the fabrication of 3D sulfur copolymer cathodes with controlled architectures for lithium‐sulfur batteries. The printed electrodes exhibit multiscale porosity and high sulfur utilization, delivering enhanced electrochemical performance compared to conventional cast electrodes.
Bin Ling, Haoran Wang, Pan Yang, Rishav Agrawal, Alex R. Neale, Laurence J. Hardwick, Tom Hasell, Esther García‐Tuñón   +7 more
wiley   +1 more source

Color-filter-array-based multispectral photoplethysmography optical sensor and its motion artifact correction algorithm. [PDF]

J Biomed Opt
Wei Y, Cong S, Yan R, He Z, Li H, Yu G, Zou M.   +6 more
europepmc   +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