Results 151 to 160 of about 1,029,116 (295)
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
Zinc(II) coordination complexes with tunable aryloxy‐imine ligands exhibit controllable supramolecular self‐assembly into hierarchical fibrous structures. Coordination‐driven stacking, not π–π interactions, enables gelation, dynamic assembly/disassembly, and enhanced nanomechanical properties.
Merlin R. Stühler +10 more
wiley +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
An invasive herbivore structures plant competitive dynamics. [PDF]
Wong L, Grainger TN, Start D, Gilbert B.
europepmc +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
Competitive dynamics on complex networks. [PDF]
Zhao J, Liu Q, Wang X.
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
Competitive dynamics of arbuscular mycorrhizal fungi as depending on fungal traits and host plant species. [PDF]
De La Cruz HJ +4 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

