Results 181 to 190 of about 27,930 (298)

Matrix‐Free Afterglow Carbon Dots: Synthetic Strategies, Luminescence Mechanisms, and Emerging Applications

open access: yesCarbon Innovation, EarlyView.
This review systematically elucidates the luminescence mechanism, synthesis methods of matrix‐free afterglow carbon dots, and their application progress in information encryption, light‐emitting diodes, sensing, bioimaging, and tumor treatment, and finally, discusses the current challenges and future development directions. ABSTRACT Afterglow materials,
Yupeng Liu   +5 more
wiley   +1 more source

Understanding aroma impacts of four important volatile sulfur compounds in Oregon Pinot noir wines

open access: yes
Sensory properties of four important volatile sulfur compounds, dimethyl disulfide (DMDS), diethyl disulfide (DEDS), methanethiol (MeSH) and ethanethiol (EtSH), were determined in base Oregon Pinot noir wine in order to understand their impacts on wine ...
Tsai, I-Min
core  

Mass Spectra of Volatile Sulfur Compounds in Foods

open access: yesAgricultural and Biological Chemistry, 1973
NISHIMURA, Hiroyuki   +2 more
openaire   +2 more sources

Influence of Particle Size, Moisture, and Cloud Density on Wood Dust Ignition

open access: yesChemie Ingenieur Technik, EarlyView.
The ignition and combustion of particle clouds are strongly affected by particle interactions. This study uses spectroscopy to examine effects of particle size, water content, and cloud density. Results show ignition delay rises with larger size and density, whereas combustion duration depends mainly on water and density due to moisture‐driven ...
Matteo Giesen   +2 more
wiley   +1 more source

Carbon2Chem—Innovative Research for the Energy Transition

open access: yesChemie Ingenieur Technik, EarlyView.
The Carbon2Chem project has been working on solutions for the energy transition since 2016. Despite changes in its framework conditions, the project remains on course. The project structure and the collaboration between the project partners are essential for the project's success.
Torsten Müller
wiley   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos   +3 more
wiley   +1 more source

Home - About - Disclaimer - Privacy