Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Zhuoying Jiang"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Air contaminants lead to various environmental and health issues. Titanium dioxide (TiO2) features the benefits of autogenous photocatalytic degradation of air contaminants. To evaluate its performance, laboratory experiments are commonly us
Externí odkaz:
https://doaj.org/article/46dae1e21c354e298e28e21667ee1e6c
Publikováno v:
Toxics, Vol 12, Iss 9, p 663 (2024)
Air pollution has become a serious public health problem and there is evidence that air pollution affects the incidence of allergic rhinitis. To further investigate the effect of ambient air pollutants on the severity of allergic rhinitis symptoms, a
Externí odkaz:
https://doaj.org/article/b36d6166e0d5417e869c3ce1094713e2
Publikováno v:
Applied Sciences, Vol 14, Iss 3, p 1045 (2024)
Real-time visual object tracking (VOT) may suffer from performance degradation and even divergence owing to inaccurate noise statistics typically engendered by non-stationary video sequences or alterations in the tracked object. This paper presents a
Externí odkaz:
https://doaj.org/article/96407ea2e312415f8079672a3b78babe
Publikováno v:
Catalysts, Vol 12, Iss 7, p 746 (2022)
Machine-learning models have great potential to accelerate the design and performance assessment of photocatalysts, leveraging their unique advantages in detecting patterns and making predictions based on data. However, most machine-learning models a
Externí odkaz:
https://doaj.org/article/cde45bb994e04a8ca68c01c7dcb6af9c
Autor:
Zhuoying Jiang, Jiajie Hu, Matthew Tong, Anna C. Samia, Huichun (Judy) Zhang, Xiong (Bill) Yu
Publikováno v:
Catalysts, Vol 11, Iss 9, p 1107 (2021)
This paper describes an innovative machine learning (ML) model to predict the performance of different metal oxide photocatalysts on a wide range of contaminants. The molecular structures of metal oxide photocatalysts are encoded with a crystal graph
Externí odkaz:
https://doaj.org/article/8c680d2210f8405f9d495687afcc5ad4
Autor:
Zhuoying Jiang, Sameera Wickramasinghe, Yu Hsin Tsai, Anna Cristina S. Samia, David Gurarie, Xiong Yu
Publikováno v:
Catalysts, Vol 10, Iss 12, p 1449 (2020)
Nitrogen-doped TiO2 has a great potential as a photocatalyst under visible light irradiation with applications in the removal of air and water pollutants, and the treatment of bacterial contaminations. In this study, nitrogen-doped TiO2 nanoparticles
Externí odkaz:
https://doaj.org/article/3036546c054d4b5d932eb364079d26e7
Publikováno v:
Materials, Vol 13, Iss 24, p 5701 (2020)
The purpose of this study was to develop a data-driven machine learning model to predict the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced polyesters featuring excellent performance, to guide future design and synthesi
Externí odkaz:
https://doaj.org/article/c672c45ff9fd45fc80435bfa316a9e3b
Autor:
Zhuoying Jiang, Xiong Yu
Publikováno v:
Transportation Research Record: Journal of the Transportation Research Board. 2674:512-519
Titanium dioxide (TiO2) is a widely used photocatalyst that can oxidize motor vehicle exhaust, for example, carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons, and sulfur dioxide, under the irradiation of sunlight. It has been reported that na
Publikováno v:
Catalysts
Volume 11
Issue 9
Catalysts, Vol 11, Iss 1107, p 1107 (2021)
Volume 11
Issue 9
Catalysts, Vol 11, Iss 1107, p 1107 (2021)
This paper describes an innovative machine learning (ML) model to predict the performance of different metal oxide photocatalysts on a wide range of contaminants. The molecular structures of metal oxide photocatalysts are encoded with a crystal graph