Results 141 to 150 of about 3,902,266 (287)

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

Smoking and obsessive-compulsive symptoms in patients with schizophrenia, schizoaffective disorder or bipolar disorder using electronic mental health records. [PDF]

BJPsych Open
Cohen HR, Chang CK, Ahn-Robbins D, Bogdanowicz K, Chandran D, Kartoglu E, Shetty H, Vermeulen JM, Sanyal J, Stewart R, Schirmbeck F, de Haan L, Hayes RD.   +12 more
europepmc   +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

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

A Rapid and High-Recovery Extracellular Vesicle (EVs) Isolation Technique from Blood Samples. [PDF]

Bio Protoc
Sankpal AN, Sankpal NV.
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

Fine-grained identification of greenhouse crop leaf diseases based on reconstruction-generation network. [PDF]

PLoS One
Wu Y, Liu J.
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

Changes in firearm intentions and behaviors after the 2024 United States presidential election. [PDF]

Inj Epidemiol
Anestis MD, Bond AE, Burke KC, Altikriti S, Semenza DC.   +4 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