Results 241 to 250 of about 2,797,733 (334)

Emerging 2D Materials and Their Hybrid Nanostructures for Label‐Free Optical Biosensing: Recent Progress and Outlook

open access: yesAdvanced Functional Materials, EarlyView.
This review highlights recent advances in label‐free optical biosensors based on 2D materials and rationally designed mixed‐dimensional nanohybrids, emphasizing their synergistic effects and novel functionalities. It also discusses multifunctional sensing platforms and the integration of machine learning for intelligent data analysis.
Xinyi Li, Yonghao Fu, Yuehe Lin, Dan Du
wiley   +1 more source

Validated spectrofluorimetric method for the determination of atorvastatin in pharmaceutical preparations

open access: yesJournal of Pharmaceutical Analysis, 2012
M. S. Sharaf El-Din   +4 more
semanticscholar   +1 more source

Harnessing Non‐Covalent Protein–Protein Interaction Domains for Production of Biocatalytic Materials Systems

open access: yesAdvanced Functional Materials, EarlyView.
Non‐covalent protein–protein interactions mediated by SH3, PDZ, or GBD domains enable the self‐assembly of stable and biocatalytically active hydrogel materials. These soft materials can be processed into monodisperse foams that, once dried, exhibit enhanced mechanical stability and activity and are easily integrated into microstructured flow ...
Julian S. Hertel   +5 more
wiley   +1 more source

Host‐Guest Inclusion Chemistry From Supramolecular Architecture Enabling Anti‐Biofouling Surfaces for Oesophagus Stents

open access: yesAdvanced Functional Materials, EarlyView.
A slippery coating with exceptional anti‐biofouling performance is developed using biocompatible materials for oesophagus stents. Host‐guest inclusion complex formation capabilities of FDA‐approved supramolecules, cyclodextrins are exploited, which significantly enhances the stability of the surface.
Jianhui Zhang   +7 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced 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   +7 more
wiley   +1 more source

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