Exploration of Key Factors in the Preparation of Highly Hydrophobic Silica Aerogel from Rice Husk Ash Assisted by Machine Learning
To expand the applications of hydrophobic silica aerogels derived from rice husk ash (HSA) through simple traditional methods (without adding special materials or processes), this paper employs machine learning to establish mathematical models to identify optimal conditions for extracting water glas...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Gels |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2310-2861/11/1/74 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832588456481521664 |
|---|---|
| author | Yun Deng Ziyan Sha Xingxing Wang Ke Duan Weijie Xue Ian Beadham Xiaolan Xiao Changbo Zhang |
| author_facet | Yun Deng Ziyan Sha Xingxing Wang Ke Duan Weijie Xue Ian Beadham Xiaolan Xiao Changbo Zhang |
| author_sort | Yun Deng |
| collection | DOAJ |
| description | To expand the applications of hydrophobic silica aerogels derived from rice husk ash (HSA) through simple traditional methods (without adding special materials or processes), this paper employs machine learning to establish mathematical models to identify optimal conditions for extracting water glass and investigates how preparation conditions and heat treatment temperatures affect properties such as the porosity and hydrophobicity of HSA. The results indicate that the decision tree regression model provides the most accurate predictions for the extraction rate and modulus of water glass. Notably, the water contact angle of HSA produced using nitric acid as a catalyst can reach as high as 159.5°, classifying it as a superhydrophobic material. Additionally, while moderately increasing the concentration of the hydrophobic modifier enhances HSA’s hydrophobicity, it concurrently reduces its porosity. The HSA maintained hydrophobicity until 500 °C. The pore structure of HSA collapsed gradually with the increase in heat temperature. After treatment at 700 °C, HSA lost its hydrophobicity and the porous structure was severely damaged. Compared with silica aerogel using traditional silicon sources, the damage to pore structure and the crystallization occurred at lower temperatures, but the hydrophobicity remained at higher temperatures. |
| format | Article |
| id | doaj-art-f9e315804a7a45398a958574dfd6b97b |
| institution | Kabale University |
| issn | 2310-2861 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Gels |
| spelling | doaj-art-f9e315804a7a45398a958574dfd6b97b2025-01-24T13:34:02ZengMDPI AGGels2310-28612025-01-011117410.3390/gels11010074Exploration of Key Factors in the Preparation of Highly Hydrophobic Silica Aerogel from Rice Husk Ash Assisted by Machine LearningYun Deng0Ziyan Sha1Xingxing Wang2Ke Duan3Weijie Xue4Ian Beadham5Xiaolan Xiao6Changbo Zhang7College of Environment and Ecology, Jiangnan University, Wuxi 214122, ChinaCollege of Environment and Ecology, Jiangnan University, Wuxi 214122, ChinaCollege of Environment and Ecology, Jiangnan University, Wuxi 214122, ChinaCollege of Environment and Ecology, Jiangnan University, Wuxi 214122, ChinaKey Laboratory of Original Agro-Environmental Pollution Prevention and Control (Ministry of Agriculture and Rural Affairs (MARA)), Tianjin Key Laboratory of Agro-Environment and Agro-Product Safety, Agro-Environmental Protection Institute, MARA, Tianjin 300191, ChinaSchool of Pharmacy and Chemistry, Kingston University, London KT1 2EE, UKCollege of Environment and Ecology, Jiangnan University, Wuxi 214122, ChinaKey Laboratory of Original Agro-Environmental Pollution Prevention and Control (Ministry of Agriculture and Rural Affairs (MARA)), Tianjin Key Laboratory of Agro-Environment and Agro-Product Safety, Agro-Environmental Protection Institute, MARA, Tianjin 300191, ChinaTo expand the applications of hydrophobic silica aerogels derived from rice husk ash (HSA) through simple traditional methods (without adding special materials or processes), this paper employs machine learning to establish mathematical models to identify optimal conditions for extracting water glass and investigates how preparation conditions and heat treatment temperatures affect properties such as the porosity and hydrophobicity of HSA. The results indicate that the decision tree regression model provides the most accurate predictions for the extraction rate and modulus of water glass. Notably, the water contact angle of HSA produced using nitric acid as a catalyst can reach as high as 159.5°, classifying it as a superhydrophobic material. Additionally, while moderately increasing the concentration of the hydrophobic modifier enhances HSA’s hydrophobicity, it concurrently reduces its porosity. The HSA maintained hydrophobicity until 500 °C. The pore structure of HSA collapsed gradually with the increase in heat temperature. After treatment at 700 °C, HSA lost its hydrophobicity and the porous structure was severely damaged. Compared with silica aerogel using traditional silicon sources, the damage to pore structure and the crystallization occurred at lower temperatures, but the hydrophobicity remained at higher temperatures.https://www.mdpi.com/2310-2861/11/1/74rice husk ashsilica aerogelhydrophobicitythermal stability |
| spellingShingle | Yun Deng Ziyan Sha Xingxing Wang Ke Duan Weijie Xue Ian Beadham Xiaolan Xiao Changbo Zhang Exploration of Key Factors in the Preparation of Highly Hydrophobic Silica Aerogel from Rice Husk Ash Assisted by Machine Learning Gels rice husk ash silica aerogel hydrophobicity thermal stability |
| title | Exploration of Key Factors in the Preparation of Highly Hydrophobic Silica Aerogel from Rice Husk Ash Assisted by Machine Learning |
| title_full | Exploration of Key Factors in the Preparation of Highly Hydrophobic Silica Aerogel from Rice Husk Ash Assisted by Machine Learning |
| title_fullStr | Exploration of Key Factors in the Preparation of Highly Hydrophobic Silica Aerogel from Rice Husk Ash Assisted by Machine Learning |
| title_full_unstemmed | Exploration of Key Factors in the Preparation of Highly Hydrophobic Silica Aerogel from Rice Husk Ash Assisted by Machine Learning |
| title_short | Exploration of Key Factors in the Preparation of Highly Hydrophobic Silica Aerogel from Rice Husk Ash Assisted by Machine Learning |
| title_sort | exploration of key factors in the preparation of highly hydrophobic silica aerogel from rice husk ash assisted by machine learning |
| topic | rice husk ash silica aerogel hydrophobicity thermal stability |
| url | https://www.mdpi.com/2310-2861/11/1/74 |
| work_keys_str_mv | AT yundeng explorationofkeyfactorsinthepreparationofhighlyhydrophobicsilicaaerogelfromricehuskashassistedbymachinelearning AT ziyansha explorationofkeyfactorsinthepreparationofhighlyhydrophobicsilicaaerogelfromricehuskashassistedbymachinelearning AT xingxingwang explorationofkeyfactorsinthepreparationofhighlyhydrophobicsilicaaerogelfromricehuskashassistedbymachinelearning AT keduan explorationofkeyfactorsinthepreparationofhighlyhydrophobicsilicaaerogelfromricehuskashassistedbymachinelearning AT weijiexue explorationofkeyfactorsinthepreparationofhighlyhydrophobicsilicaaerogelfromricehuskashassistedbymachinelearning AT ianbeadham explorationofkeyfactorsinthepreparationofhighlyhydrophobicsilicaaerogelfromricehuskashassistedbymachinelearning AT xiaolanxiao explorationofkeyfactorsinthepreparationofhighlyhydrophobicsilicaaerogelfromricehuskashassistedbymachinelearning AT changbozhang explorationofkeyfactorsinthepreparationofhighlyhydrophobicsilicaaerogelfromricehuskashassistedbymachinelearning |