Results 91 to 100 of about 256,585 (269)
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.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
Advanced Functional Materials, EarlyView.A multivalent antiviral platform based on honeycomb‐shaped DNA nanostructures (HC–Urumin) is developed to enhance the potency and breadth of the host defense peptide Urumin. Through spatially patterned trimeric presentation, HC–Urumin disrupts influenza A virus entry, improves cell viability, and reduces disease severity in vivo‐offering a modular and ...
Saurabh Umrao +11 more
wiley +1 more source
Stacked Ensemble for Bioactive Molecule Prediction
IEEE Access, 2019 Bioactive molecular compounds are essential for drug discovery. The biological activity of these compounds needs to be predicted as this is used to determine the drug-target ability.
Olutomilayo Olayemi Petinrin +1 more
doaj +1 more source
Advanced Functional Materials, EarlyView.In‐situ doping during growth of SnSe and subsequent attachment of SnS produces high‐quality lateral pn‐heterojunctions between van der Waals semiconductors. Electron beam induced current measurements demonstrate electrically active pn‐junctions, paving the way for devices that harness charge separation at lateral interfaces in layered heterostructures.
Peter Sutter +4 more
wiley +1 more source
Equipment Health Assessment: Time Series Analysis for Wind Turbine Performance
Applied SciencesIn this study, we leverage SCADA data from diverse wind turbines to predict power output, employing advanced time series methods, specifically Functional Neural Networks (FNN) and Long Short-Term Memory (LSTM) networks.
Jana Backhus +5 more
doaj +1 more source
Advanced Functional Materials, EarlyView.Multi‐metal Cu─Ce─Ag nanoparticles harness synergistic interactions to drive efficient electrochemical CO2 reduction reaction toward C2+ products at high current densities. Ag enhances CO production, Ce modulates Cu oxidation states, and together they boost *CO coverage and local pH to enhance C─C coupling, enabling record C2+ yields with suppressed ...
Nini Zhang +9 more
wiley +1 more source
AtmosphereThis study evaluates the performance of the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) models in simulating the historical precipitation extremes and uses the best-performing model to project changes in extreme ...
Ifeanyi Chukwudi Achugbu +3 more
doaj +1 more source
Lithium Intercalation in the Anisotropic Van Der Waals Semiconductor CrSBr
Advanced Functional Materials, EarlyView.We report the lithium intercalation in the layered van der Waals crystal CrSBr, revealing strongly anisotropic ion‐migration dynamics. Optical and electrical characterization of exfoliated CrSBr shows lithium diffusion coefficients that differ by more than an order of magnitude along a‐ and b‐directions, consistent with molecular dynamics simulations ...
Kseniia Mosina +13 more
wiley +1 more source
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
Advanced Functional Materials, EarlyView.An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source