Results 151 to 160 of about 545,451 (275)
Electroactive Metal–Organic Frameworks for Electrocatalysis
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
There is a significant need for biomaterials with well‐defined stability and bioactivity to support tissue regeneration. In this study, we developed a tunable microgel platform that enables the decoupling of stiffness from porosity, thereby promoting bone regeneration.
Silvia Pravato +9 more
wiley +1 more source
The development and implementation of odd-exponential-ailamujia distribution in python: properties and application in reliability engineering. [PDF]
Alballa T +4 more
europepmc +1 more source
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
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
Gravitational form factors of the Higgs boson. [PDF]
Beißner P +3 more
europepmc +1 more source
A bespoke multilayer thin film configuration has been designed, which overcomes the material dependency of conventional isotope exchange Raman spectroscopy (IERS). This universal IERS methodology is efficient, non‐destructive and provides additional structural information and time resolution, which can be further extended to various isotopic elements ...
Zonghao Shen +7 more
wiley +1 more source
An Intuitive Approach to the Optimal Sampling of an Electromagnetic Field. [PDF]
Migliore MD.
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
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
Two-Level Theory of Second-Order Nonlinear X-ray Response beyond the Electric-Dipole Approximation. [PDF]
Mohan AV, Serrat C.
europepmc +1 more source
A 3D disease model is developed using customized hyaluronic‐acid‐based hydrogels supplemented with extracellular matrix (ECM) proteins resembling brain ECM properties. Neurons, astrocytes, and tumor cells are used to mimic the native brain surrounding.
Esra Türker +16 more
wiley +1 more source

