Results 171 to 180 of about 1,254,731 (295)

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

Structural architecture of SNP effects on complex traits. [PDF]

Am J Hum Genet, 2014
Gamazon ER, Cox NJ, Davis LK.
europepmc   +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

Structure and architecture [PDF]

, 2007
openaire   +2 more sources

The Structural Architecture of an Infectious Mammalian Prion Using Electron Cryomicroscopy. [PDF]

PLoS Pathog, 2016
Vázquez-Fernández E, Vos MR, Afanasyev P, Cebey L, Sevillano AM, Vidal E, Rosa I, Renault L, Ramos A, Peters PJ, Fernández JJ, van Heel M, Young HS, Requena JR, Wille H.   +14 more
europepmc   +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

Backbone Heterojunction Photocatalysts for Efficient Sacrificial Hydrogen Production

Advanced Functional Materials, EarlyView.
Herein, a ‘single‐component’ organic semiconductor photocatalyst is presented in which a molecular donor is bonded to a polymer acceptor. The resultant material demonstrates exceptional photocatalytic activity for hydrogen evolution in aqueous triethylamine with an outstanding external quantum efficiency of 38% at 420 nm.
Richard J. Lyons, Rhys J. Bourhill, Ewan McQueen, Sam D. Harding, Krzysztof Pawlak, Thomas Fellowes, Harry W. Capps, Alexander J. Cowan, Andrew I. Cooper, Adrian M. Gardner, Martijn A. Zwijnenburg, Reiner Sebastian Sprick   +11 more
wiley   +1 more source

Structural architecture of the acidic region of the B domain of coagulation factor V. [PDF]

J Thromb Haemost
Mohammed BM, Basore K, Summers B, Pelc LA, Di Cera E.   +4 more
europepmc   +1 more source

MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance

Advanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
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