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Optimization of Process Parameters for Anti-Glare Spray Coating by Pressure-Feed Type Automatic Air Spray Gun Using Response Surface Methodology
The process of preparing anti-glare thin films by spray-coating silica sol-gel to soda-lime glass was exclusively and statistically studied in this paper. The effects of sol-gel deliver pressure, air transport pressure, and spray gun displacement speed on the gloss, haze, arithmetic mean surface rou...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427158/ https://www.ncbi.nlm.nih.gov/pubmed/30841570 http://dx.doi.org/10.3390/ma12050751 |
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author | Huang, Yu-Hui Chen, Lung-Chuan Chou, Huann-Ming |
author_facet | Huang, Yu-Hui Chen, Lung-Chuan Chou, Huann-Ming |
author_sort | Huang, Yu-Hui |
collection | PubMed |
description | The process of preparing anti-glare thin films by spray-coating silica sol-gel to soda-lime glass was exclusively and statistically studied in this paper. The effects of sol-gel deliver pressure, air transport pressure, and spray gun displacement speed on the gloss, haze, arithmetic mean surface roughness, and total transmittance light were analyzed. The experimental results indicate that the factors of sol-gel deliver pressure, air transport pressure, and displacement speed exhibit a significant effect on the haze, gloss, and Ra. In contrast, the variation of total transmittance light with these three factors are insignificant. Because the anti-glare property is predominantly determined by low gloss and high haze, we therefore aim to minimize gloss and maximize haze to achieve high anti-glare. Central composite design and response surface methodology are employed to analyze the main and interaction effects of the three factors through quadratic polynomial equations, which are confirmed by the analysis of variance and R(2). The response surface methodology predict the lowest gloss and highest haze are 9.2 GU and 57.0%, corresponding to the sol-gel deliver pressure, air-transport pressure, and displacement speed of 250 kPa, 560 kPa, and 140 mm/s, and 340 kPa, 620 kPa, and 20 mm/s, respectively. Comparing the predicted optimal data with the real experimental results validates the applicability of the mathematical model. This study provides an important basis for the subsequent production of anti-glare glass with different specifications to satisfy the market demand. |
format | Online Article Text |
id | pubmed-6427158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64271582019-04-15 Optimization of Process Parameters for Anti-Glare Spray Coating by Pressure-Feed Type Automatic Air Spray Gun Using Response Surface Methodology Huang, Yu-Hui Chen, Lung-Chuan Chou, Huann-Ming Materials (Basel) Article The process of preparing anti-glare thin films by spray-coating silica sol-gel to soda-lime glass was exclusively and statistically studied in this paper. The effects of sol-gel deliver pressure, air transport pressure, and spray gun displacement speed on the gloss, haze, arithmetic mean surface roughness, and total transmittance light were analyzed. The experimental results indicate that the factors of sol-gel deliver pressure, air transport pressure, and displacement speed exhibit a significant effect on the haze, gloss, and Ra. In contrast, the variation of total transmittance light with these three factors are insignificant. Because the anti-glare property is predominantly determined by low gloss and high haze, we therefore aim to minimize gloss and maximize haze to achieve high anti-glare. Central composite design and response surface methodology are employed to analyze the main and interaction effects of the three factors through quadratic polynomial equations, which are confirmed by the analysis of variance and R(2). The response surface methodology predict the lowest gloss and highest haze are 9.2 GU and 57.0%, corresponding to the sol-gel deliver pressure, air-transport pressure, and displacement speed of 250 kPa, 560 kPa, and 140 mm/s, and 340 kPa, 620 kPa, and 20 mm/s, respectively. Comparing the predicted optimal data with the real experimental results validates the applicability of the mathematical model. This study provides an important basis for the subsequent production of anti-glare glass with different specifications to satisfy the market demand. MDPI 2019-03-05 /pmc/articles/PMC6427158/ /pubmed/30841570 http://dx.doi.org/10.3390/ma12050751 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Huang, Yu-Hui Chen, Lung-Chuan Chou, Huann-Ming Optimization of Process Parameters for Anti-Glare Spray Coating by Pressure-Feed Type Automatic Air Spray Gun Using Response Surface Methodology |
title | Optimization of Process Parameters for Anti-Glare Spray Coating by Pressure-Feed Type Automatic Air Spray Gun Using Response Surface Methodology |
title_full | Optimization of Process Parameters for Anti-Glare Spray Coating by Pressure-Feed Type Automatic Air Spray Gun Using Response Surface Methodology |
title_fullStr | Optimization of Process Parameters for Anti-Glare Spray Coating by Pressure-Feed Type Automatic Air Spray Gun Using Response Surface Methodology |
title_full_unstemmed | Optimization of Process Parameters for Anti-Glare Spray Coating by Pressure-Feed Type Automatic Air Spray Gun Using Response Surface Methodology |
title_short | Optimization of Process Parameters for Anti-Glare Spray Coating by Pressure-Feed Type Automatic Air Spray Gun Using Response Surface Methodology |
title_sort | optimization of process parameters for anti-glare spray coating by pressure-feed type automatic air spray gun using response surface methodology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427158/ https://www.ncbi.nlm.nih.gov/pubmed/30841570 http://dx.doi.org/10.3390/ma12050751 |
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