Revolutionizing CO2 reduction with TiO2 photocatalyst immobilized on polytetrafluoroethylene (PTFE) membrane

Mohd Saleh, Syafiqa; Oh, Pei Ching; M Zain, Masniroszaime; Quek, Ven Chian; Zulkifli, Ayuni Shahira; Chew, Thiam Leng

doi:10.1016/j.jiec.2023.10.022

Journal of Industrial and Engineering Chemistry

2024

DOI: 10.1016/j.jiec.2023.10.022

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Revolutionizing CO2 reduction with TiO2 photocatalyst immobilized on polytetrafluoroethylene (PTFE) membrane

Syafiqa Mohd Saleh,

Pei Ching Oh,

Masniroszaime M Zain

et al.

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Predictive Modeling of Energy Consumption in Smart Grids using Artificial Neural Networks

Tkachenko,

Saxena,

Nimmagadda

et al. 2024

E3S Web Conf.

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This study delves into the ground-breaking applications of optical fiber grids for material analysis. In it, we look at the correlation between light intensity and temperature, analyze the material composition, and conduct a comprehensive examination into sensor calibration. Optical fiber grids are quite accurate in detecting changes in temperature and refractive index, as shown by the calibration results, which showed an outstanding average accuracy of 98%. The grids were able to distinguish between different materials with an average accuracy of 96%, according to the material composition research. The correct identification of a polymer sample with 45% polyethylene and 55% polypropylene demonstrated this. Also, the grids were able to properly react to changing temperatures since there was a strong linear relationship between light intensity and temperature (92 percent explanatory power). Taken together, the findings highlight optical fiber grids’ versatility and reliability, showing how they might revolutionize material research across several industries.

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Predictive Modeling of Energy Consumption in Smart Grids using Artificial Neural Networks

Tkachenko,

Saxena,

Nimmagadda

et al. 2024

E3S Web Conf.

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Revolutionizing CO2 reduction with TiO2 photocatalyst immobilized on polytetrafluoroethylene (PTFE) membrane

Cited by 1 publication

References 40 publications

Predictive Modeling of Energy Consumption in Smart Grids using Artificial Neural Networks

Predictive Modeling of Energy Consumption in Smart Grids using Artificial Neural Networks

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