Kit Wayne Chew
11 Papers
Kit Wayne Chew is an academic researcher. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 5, co-authored 7 publications.
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Papers
A review on the diverse interactions between microalgae and nanomaterials: growth variation, photosynthesis performance and toxicity.
Zhi Lin Lau,Sze Shin Low,Ejikeme Raphael Ezeigwe,Kit Wayne Chew,Wai Siong Chai,Amit Bhatnagar,Yee Jiun Yap,Pau Loke Show +7 more
TL;DR: In this article , the authors reviewed the interactions between nanomaterials and microalgae in terms of impacts on growth and photosynthetic efficiency, and their toxicity on micro-algae.
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Advancement of wastewater bioremediation technologies via artificial and microalgae photosynthesis.
You Ping Xie,Kuan Shiong Khoo,Kit Wayne Chew,Vishno Vardhan Devadas,Sue Jiun Phang,Hooi Ren Lim,S. Rajendran,Pau Loke Show +7 more
TL;DR: In this paper , the development in artificial photosynthesis to a chemical process that biomimics the natural photosynthesis process to fix CO2 in the air has been discussed, which has led to the emergence of bioenergy sources like biofuels and biohydrogen extracted from microalgae biomass.
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Remediation technologies for contaminated groundwater due to arsenic (As), mercury (Hg), and/or fluoride (F): A critical review and way forward to contribute to carbon neutrality
Tonni Agustiono Kurniawan,Waihung Lo,Xue Liang,Hui Hwang Goh,Mohd Hafiz Dzarfan Othman,Kok-Keong Chong,Kit Wayne Chew +6 more
TL;DR: In this article , the applicability of water technologies for treatment of contaminated groundwater laden with As, Hg, or F through literature reviews using the Web of Sciences (WoS).
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Removal of Cd(II) and Pb(II) from synthetic wastewater using Rosa damascena waste as a biosorbent: An insight into adsorption mechanisms, kinetics, and thermodynamic studies
Fatima Batool,A. I. Mohyuddin,Adnan Amjad,S. Nadeem,M.U. Javed,Mohd Hafiz Dzarfan Othman,Kit Wayne Chew,Abdul Rauf,Tonni Agustiono Kurniawan +8 more
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Application of regression and artificial neural network analysis of Red-Green-Blue image components in prediction of chlorophyll content in microalgae.
Doris Ying Ying Tang,Kit Wayne Chew,H. Ting,Yuk-Heng Sia,Francesco G. Gentili,Young-Kwon Park,Fawzi Banat,Alvin B. Culaba,Zengling Ma,Pau Loke Show +9 more
TL;DR: In this paper , the authors presented a methodology to predict microalgae chlorophyll content from colour models using linear regression and artificial neural network, which was performed using SPSS software and found that the regression model was highly significant, with high R2 of 0.58 and RSME of 3.16.
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