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
Objective tremor monitoring using tri-axis accelerometer in MRgFUS thalamotomy for essential tremor: a feasibility study. [PDF]
Liu KC +7 more
europepmc +1 more source
A novel approach for peak-to-average power ratio reduction and spectral efficiency enhancement in 5G and beyond networks [PDF]
S. Pavithra, S. Chitra
openalex +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
Dynamic Characteristics of Coupled Dual-Oscillator Piezoelectric Vibration Energy Harvester with External Magnet. [PDF]
Huang Z +5 more
europepmc +1 more source
Magnetic Control of Chiral Hybridized Phonon Magnetic Moments in Ferrimagnets Fe2‐xZnxMo3O8
Helicity‐resolved magneto‐Raman spectroscopy reveals magnetic control of chiral phonon magnetic moments in polar ferrimagnet (ZnxFe2−xMo3O₈). Large spontaneous zero‐field phonon splittings, selective phonon–magnon coupling, and asymmetric Zeeman responses demonstrate that phonon chirality is governed by magnon‐phonon coupling and magnetization.
Youngsu Choi +8 more
wiley +1 more source
Scalable optical vortex arrays enabled by the decomposition of Laguerre-Gaussian beams into three Hermite-Gaussian modes and multibeam interference. [PDF]
Nakata Y +3 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
Planar ICP Assisted One-Step Synthesis of pH-Responsive PDEAEMA Polymer Thin Films. [PDF]
Tosun Z.
europepmc +1 more source

