Results 141 to 150 of about 724,033 (296)
Fast‐Responding O2 Gas Sensor Based on Luminescent Europium Metal‐Organic Frameworks (MOF‐76)
Luminescent MOF‐76 materials based on Eu(III) and mixed Eu(III)/Y(III) show rapid and reversible changes in emission intensity in response to O2 with very short response times. The effect is based on triplet quenching of the linker ligands that act as photosensitizers. Average emission lifetimes of a few milliseconds turn out to be mostly unaffected by
Zhenyu Zhao +5 more
wiley +1 more source
Exploring the photocatalytic reverse water–gas shift (RWGS) reaction on doped SrTiO3 nanoparticle films, reveals that normalizing catalytic rates by the catalyst's specific surface area (SSA) disentangled surface area effects from the catalyst's intrinsic material properties.
Dikshita Bhattacharyya +6 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
Band Alignment in In‐Oxo Metal Porphyrin SURMOF Heterojunctions
Porphyrin core metalation in indium‑oxo SURMOFs enables systematic tuning of band edge positions without altering the crystal structure. First‑principles calculations reveal type‑I and type‑II heterostructures as well as multi‑junction energy cascades, establishing a modular strategy for exciton funneling and charge separation in optoelectronic ...
Puja Singhvi, Nina Vankova, Thomas Heine
wiley +1 more source
In view of problem of low reliability caused by single-factor gradient method for predicting gas content in coal mine, the paper proposed a method of visualization multivariable prediction for gas content based on grey system theory, and established ...
HAO Tian-xuan, ZHANG Hai-bo
doaj
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
Emergent Spin‐Glass Behavior in an Iron(II)‐Based Metal–Organic Framework Glass
A one‐pot, solvent‐free synthesis yields an Fe2+‐based metal‐organic framework (MOF) glass featuring a continuous random network structure. The material exhibits spin‐glass freezing at 14 K, driven by topological‐disorder and short‐range magnetic frustration, showcasing the potential of MOF glasses as a plattform for cooperative magnetic phenomena in ...
Chinmoy Das +8 more
wiley +1 more source
Research on the prediction model of gas emission based on grey system theory. [PDF]
Bai L, Geng H, Yu G.
europepmc +1 more source
Chemoselective Sequential Polymerization: An Approach Toward Mixed Plastic Waste Recycling
Inspired by biological protein metabolism, this study demonstrates the closed‐loop recycling of mixed synthetic polymers via ring‐closing depolymerization followed by a chemoselective sequential polymerizations process. The approach recovers pure polymers from mixed feedstocks, even in multilayer formats, highlighting a promising strategy to overcome a
Gadi Slor +5 more
wiley +1 more source
Exciton Binding Energy Modulation in 2D Perovskites: A Phenomenological Keldysh Framework
The intrinsic screening effects are successfully decoupled from structural distortion by rigorously designing a series of 2D perovskites. This enabled us to demonstrate how the dielectric environment modulates the quasiparticle bandgap and exciton binding energy.
Kitae Kim +15 more
wiley +1 more source

