Results 201 to 210 of about 1,556,228 (248)

Editorial: Integrating computational modeling and organoid technology for enhanced biological research. [PDF]

Front Bioeng Biotechnol
García-Aznar JM, McEvoy E, Verbruggen SW, Van Liedekerke P.   +3 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

Computational modeling of oxygen dynamics in port-wine stain photodynamic therapy: treatment outcome optimization and pain management. [PDF]

J Biomed Opt
Li Y, Li Q, Hu X.
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

Computational modeling and histologic analysis of 6.78- and 2-MHz monopolar radiofrequency-induced thermal reactions. [PDF]

Lasers Med Sci
Ko K, Ryu HG, Park J, Kim W, Kim S, Ko J, Cho SB.   +6 more
europepmc   +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

Computational Modeling of Cellulose Synthase Heterotrimer Assembly and Identification of Antimicrobial Compounds Targeting Interface Sites in <i>Phytophthora infestans</i>. [PDF]

J Fungi (Basel)
Chellappan BV, Shidhi PR, Amritha VS, El-Ganainy SM, Almalki MA.   +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

Computational modeling of oxytocin-receptors interactions with the common marmoset Callithrix jacchus Pro8OT variant. [PDF]

Genet Mol Biol
Veber B, Fuscaldo RDS, Vargas-Pinilla P, Missaggia BO, Bortolini MC, Netz PA.   +5 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