Results 201 to 210 of about 1,597,523 (296)
Substrate Stress Relaxation Regulates Cell‐Mediated Assembly of Extracellular Matrix
Advanced Functional Materials, EarlyView.Silicone‐based viscoelastic substrates with tunable stress relaxation reveal how matrix mechanics regulates cellular mechanosensing and cell‐mediated matrix remodelling in the stiff regime. High stress relaxation promotes assembly of fibronectin fibril‐like structures, increased nuclear localization of YAP and formation of β1 integrin‐enriched ...
Jonah L. Voigt +2 more
wiley +1 more source
Elastic Die Technology for Spur Gear Powder Compaction: Experimental Measurements and Simulation-Based Validation. [PDF]
Materials (Basel)Noveanu DC.
europepmc +1 more source
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 +7 more
wiley +1 more source
Background selection in recombining genomes and its consequences for the maintenance of variation in complex traits. [PDF]
Proc Natl Acad Sci U S ALi X, Berg JJ.
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 +4 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
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 +7 more
wiley +1 more source