Results 161 to 170 of about 766,564 (291)
Stretching the Printability Metric in Direct‐Ink Writing with Highly Extensible Yield‐Stress Fluids
This study introduces “drawability” as a new metric for assessing printability in direct‐ink writing, focusing on gap‐spanning performance and speed robustness. By designing yield‐stress fluids with high extensibility, we demonstrate that extensional strain‐to‐break significantly enhances printability.
Chaimongkol Saengow +9 more
wiley +1 more source
Verification of systems biology research in the age of collaborative competition
Poussin Carine
doaj +1 more source
Emergent coexistence and the limits of reductionism in ecological communities. [PDF]
Aguadé-Gorgorió G, Kéfi S.
europepmc +1 more source
Selective Benzene Capture by Metal‐Organic Frameworks
Metal‐organic frameworks (MOFs) hold significant potential for capturing benzene from air emissions and hydrocarbon mixtures in liquid phases. This capability stems from their precisely engineered structures, versatile chemistries, and diverse binding interactions.
Zongsu Han +4 more
wiley +1 more source
Reply to van Haastert: Local competition between Ras/actin-driven protrusions. [PDF]
Alonso A, Kirkegaard JB, Endres RG.
europepmc +1 more source
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
Photoswitching Conduction in Framework Materials
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
The role of alternative microbial resources in competition between <i>Daphnia</i> species. [PDF]
Feniova I +7 more
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

