Results 141 to 150 of about 1,054,546 (305)
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
From Single Atoms to Nanoparticles: Pathways Toward Efficient and Durable Pt/TiO2 Photocatalysts
Platinum single atoms on TiO2 nanosheets evolve into clusters and nanoparticles under ethanol photoreforming and thermal treatments. By controlling deposition and post‐treatments, particle size and location on specific facets are modulated. The study reveals how stability pathways determine efficiency, guiding the design of more durable photocatalysts.
Juan José Delgado +6 more
wiley +1 more source
This paper focuses on a group of 66 recently-arrived Chaldeans and Assyrians from Iraq and the incidence of group members being users and/or providers of interpreting services in Melbourne.
Jim Hlavac
doaj
International human rights lawyers tend to focus on establishing the universality of human rights rather than on improving the usefulness of human rights in addressing local problems.
De Feyter, Koen
core +1 more source
Liquid‐phase transmission electron microscopy enables direct observation of nucleation and growth processes in solution. This review is dedicated to the remembrance of Helmut Cölfen and highlights recent studies on complex materials—oxides, biominerals, organic–inorganic crystals—which were central to his research activity. It summarizes key milestones,
Charles Sidhoum +5 more
wiley +1 more source
Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley +1 more source
Artificial Intelligence as the Next Visionary in Liquid Crystal Research
The functions of AI in the research laboratory are becoming increasingly sophisticated, allowing the entire process of hypothesis formulation, material design, synthesis, experimental design, and reiterative testing to be automated. In our work, we conceive how the incorporation of AI in the laboratory environment will transform the role and ...
Mert O. Astam +2 more
wiley +1 more source
From Bug to Feature: Harnessing Cross‐Sensitivity for Multiparametric Luminescence Sensing
Cross‐sensitivity in luminescence sensing is reframed from a limitation into a resource for multiparametric detection. Using ruby microspheres as a model system, cross‐sensitivity is quantitatively assessed and exploited through linear discriminant analysis, enabling simultaneous, correction‐free pressure and temperature sensing with a single ...
Nikita Panov +5 more
wiley +1 more source
This review maps how MOFs can manage hazardous gases by combining adsorption, neutralization, and reutilization, enabling sustainable air‐pollution control. Covering chemical warfare agent simulants, SO2, NOx, NH3, H2S, and volatile organic compounds, it highlights structure‐guided strategies that boost selectivity, water tolerance, and cycling ...
Yuanmeng Tian +8 more
wiley +1 more source
The citric acid/urea (CA‐Urea) precursor system offers a versatile, scalable route to carbon dots with tunable luminescence and multifunctionality. Mechanistic insights into precursor chemistry and reaction parameters have enabled doping, surface modification, and hybridization strategies, yielding CDs for luminescent devices, sensing, catalysis ...
Yupeng Liu +10 more
wiley +1 more source

