Eggshells biowaste filler for improving the anticorrosive behaviour of waterborne polyurethane coatings on mild steel in artificial seawater

Kamaruzzaman, Wan Mohamad Ikhmal Wan Mohamad; Shaifudin, Muhamad Syaizwadi; Nasir, Nursabrina Amirah Mohd; Hamidi, Nur Aiman Syafiq Mohd; Yusof, Nusaibah; Adnan, Azila; Jew, Lee Oon; Nik, W.B. Wan; Ghazali, Mohd Sabri Mohd

doi:10.1016/j.jmrt.2022.10.135

Cited by 11 publications

(7 citation statements)

References 47 publications

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“…Several businesses generate eggshell trash, including restaurants, residences, and bakeries. It has been suggested by multiple sources that prolonged deposition of eggshell waste in landfills without appropriate management may lead to the development of diverse allergic reactions [10]. Improper disposal of eggshells causes persistent problems, including a strong and unpleasant odor [11].…”

Section: Introductionmentioning

confidence: 99%

Strength Reduction Due to Acid Attack in Cement Mortar Containing Waste Eggshell and Glass: A Machine Learning-Based Modeling Study

Zhu,

Wu,

et al. 2024

Buildings

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The present study utilized machine learning (ML) techniques to investigate the effects of eggshell powder (ESP) and recycled glass powder (RGP) on cement composites subjected to an acidic setting. A dataset acquired from the published literature was employed to develop machine learning-based predictive models for the cement mortar’s compressive strength (CS) decrease. Artificial neural network (ANN), K-nearest neighbor (KNN), and linear regression (LR) were chosen for modeling. Also, RreliefF analysis was performed to study the relevance of variables. A total of 234 data points were utilized to train/test ML algorithms. Cement, sand, water, silica fume, superplasticizer, glass powder, eggshell powder, and 90 days of CS were considered as input variables. The outcomes of the research showed that the employed models could be applied to evaluate the reduction percentage of CS in cement composites, including ESP and RGP, after being exposed to acid. Based on the R2 values (0.87 for the ANN, 0.81 for the KNN, and 0.78 for LR), as well as the assessment of variation between test values and anticipated outcomes and errors (1.32% for ANN, 1.57% for KNN, and 1.69% for LR), it was determined that the accuracy of the ANN model was superior to the KNN and LR. The sieve diagram exhibited a correlation amongst the model predicted and target results. The outcomes of the RreliefF analysis suggested that ESP and RGP significantly influenced the CS loss of samples with RreliefF scores of 0.26 and 0.21, respectively. Based on the outcomes of the research, the ANN approach was determined suitable for predicting the CS loss of mortar subjected to acidic environments, thereby eliminating lab testing trails.

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Section: Introductionmentioning

confidence: 99%

Strength Reduction Due to Acid Attack in Cement Mortar Containing Waste Eggshell and Glass: A Machine Learning-Based Modeling Study

Zhu,

Wu,

et al. 2024

Buildings

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show abstract

“…Corrosion is estimated to be responsible for losses amounting to 3-4% of the global gross domestic product [1,2]. Owing to adequate corrosion protection, the costs can be reduced by up to 35%, but, most importantly, the risk of construction disasters can be limited [3]. Steel corrosion protection involves applying organic coatings as well as using inhibitors or electrochemical protection [4].…”

Section: Introductionmentioning

confidence: 99%

“…This study focuses on eco-friendly waterborne organic coatings. They are not as popular as solvent-based coatings in construction but have become increasingly widespread due to limitations in the use of pigmented paints, e.g., containing lead tetroxide or chromium compounds with oxidation state +6 [3,5].…”

Section: Introductionmentioning

confidence: 99%

“…The main advantage of waterborne coatings compared to solvent-based ones is an up to 95% lower content of volatile organic compounds (VOCs) and lower price [3]. Still, they are less prevalent than solvent-based coatings because of their higher application regime.…”

Section: Introductionmentioning

confidence: 99%

“…Environmental conditions should be observed more strictly during application as well. They are less efficient, have limited coating thickness, and have much longer drying times [3,4].…”

Section: Introductionmentioning

confidence: 99%

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Artificial Weathering Test Methods of Waterborne Acrylic Coatings for Steel Structure Corrosion Protection

Ładosz,

Sudoł,

Kozikowska

et al. 2024

Materials

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Corrosion protection technologies based on waterborne paints have become increasingly popular as steel structure protection, which implies the need to determine relevant assessment methods considering the conditions of use and product-specific characteristics. This study attempts to evaluate the fitness of standard corrosion protection weathering methods and an original cyclic test for verifying the resistance of waterborne acrylic coatings to environmental conditions. Changes to the properties of artificially weathered coatings were analysed with reference to those observed during exposure in natural conditions. The degree of coating degradation after exposure to neutral salt spray and condensation humidity was determined to significantly exceed the changes observed in natural conditions. An original cyclic test caused changes in the appearance, microstructure, FT-IR spectrum and utility properties of the coatings, such as thickness, colour, hardness, adhesion and impedance, similar to those observed in the natural environment. The results confirm that the programming direction of waterborne coatings artificial weathering tests is adequate and promising.

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Dual-action epoxy coating with anti-corrosion and antibacterial properties based on well-dispersed ZnO/basalt composite

Liu

Meng

Wang

et al. 2023

Composites Communications

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Eggshells biowaste filler for improving the anticorrosive behaviour of waterborne polyurethane coatings on mild steel in artificial seawater

Cited by 11 publications

References 47 publications

Strength Reduction Due to Acid Attack in Cement Mortar Containing Waste Eggshell and Glass: A Machine Learning-Based Modeling Study

Strength Reduction Due to Acid Attack in Cement Mortar Containing Waste Eggshell and Glass: A Machine Learning-Based Modeling Study

Artificial Weathering Test Methods of Waterborne Acrylic Coatings for Steel Structure Corrosion Protection

Dual-action epoxy coating with anti-corrosion and antibacterial properties based on well-dispersed ZnO/basalt composite

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