Results 171 to 180 of about 1,066,085 (279)

Band Alignment in In‐Oxo Metal Porphyrin SURMOF Heterojunctions

Advanced Functional Materials, EarlyView.
Porphyrin core metalation in indium‑oxo SURMOFs enables systematic tuning of band edge positions without altering the crystal structure. First‑principles calculations reveal type‑I and type‑II heterostructures as well as multi‑junction energy cascades, establishing a modular strategy for exciton funneling and charge separation in optoelectronic ...
Puja Singhvi, Nina Vankova, Thomas Heine
wiley   +1 more source

Slicing overcomes the bacterial cell wall barrier to fluorescence <i>in situ</i> hybridization. [PDF]

Microbiol Spectr
Gundrum J, Ramirez-Puebla ST, Mark Welch JL, Borisy GG.   +3 more
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

Topological Advantage for Adsorbate Chemisorption on Conjugated Chains. [PDF]

J Phys Chem Lett
Martinez-Gomez L, Ribeiro RF.
europepmc   +1 more source

Supraparticles Composed of Graphitic Carbon Nitride Nanoparticles and Silica‐Supported Horseradish Peroxidase as Customizable Hybrid Catalysts for Photo‐Biocatalytic Cascade Reactions in Continuous Flow

Advanced Functional Materials, EarlyView.
Herein presented supraparticles combine the nanoparticulate photocatalyst graphitic carbon nitride with the enzyme horseradish peroxidase, which is immobilized on silica nanoparticles. In an optimized compatibility range, both catalysts operate effectively within the hybrid supraparticles and catalyze a cascade reaction consisting of the photocatalytic
Bettina Herbig, Egzon Cermjani, Doris Hanselmann, Johannes Prieschl, Angelika Schmitt, Michael S. Moritz, Christian Papp, Greta Nölke, Stefano Di Fiore, Christoph Deckers, Thomas H. Rehm, Susanne Wintzheimer   +11 more
wiley   +1 more source

Detecting EGFR Gene Mutations on a Nanobioarray Chip. [PDF]

Biomedicines
Xu F, Boparai M, Oberc C, Li PCH.
europepmc   +1 more source

Inactivating SARS‐CoV‐2 Virus with MOF‐Composites as Smart Face Masks

Advanced Functional Materials, EarlyView.
In situ preparation and functionalization of MOF@Cotton fabrics as smart face masks for the immobilization of proteins and inactivation viruses, such as SARS‐CoV‐2. Abstract The significant impact of the SARS‐CoV‐2 (COVID‐19) pandemic outbreak on people's lives has highlighted the urgent need for effective personal protective equipment.
Romy Ettlinger, Aamod V. Desai, Hau Lam Jody Cheong, Louise L. Major, Terry K. Smith, Aaron B. Naden, Jane Hilton, Catherine S. Adamson, A. Robert Armstrong, Russell E. Morris   +9 more
wiley   +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

Recasting Nitrogenase's Carbide Role as a Beating Heart of Steel: A Joint Inorganic and Organic Perspective for μ₆Carbide-Iron Bonding. [PDF]

Inorg Chem
Joyce JP, DeBeer S.
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