Applying machine learning for predicting thermal conductivity coefficient of polymeric aerogels
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10973-021-10960-7.pdf
Reference54 articles.
1. Karamikamkar S, Behzadfar E, Naguib HE, Park CB. Insights into in-situ sol-gel conversion in graphene modified polymer-based silica gels for multifunctional aerogels. Chem Eng J. 2020;392:1813.
2. Noroozi M, Panahi-Sarmad M, Abrisham M, Amirkiai A, Asghari N, Golbaten-Mofrad H, Bahramian AR, et al. Nanostructure of aerogels and their applications in thermal energy insulation. ACS Appl Energy Mater. 2019;2:5319–49.
3. Shinko A, Jana SC, Meador MA. Crosslinked polyurea aerogels with controlled porosity. RSC Adv. 2015;5:105329–38.
4. Liu L, Wang Y, Alhassan S, Sun H, Choi K, Yu C, et al. Clay-facilitated aqueous dispersion of graphite and poly(vinyl alcohol) aerogels filled with binary nanofillers. Gels. 2018;4:8.
5. Seraji MM, Ghafoorian NS, Bahramian AR. Investigation of microstructure and mechanical properties of Novolac/Silica and C/SiO2/SiC aerogels using mercury porosimetry method. J Non Cryst Solids. 2016;435:1–7.
Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Polymer composites with high thermal conductivity: Theory, simulation, structure and interfacial regulation;Progress in Materials Science;2025-02
2. Thermal conductivity prediction of Al2O3-doped tetragonal YSZ coatings using deep learning;Journal of the European Ceramic Society;2024-09
3. Predicting effective thermal conductivity of HGM composite using ML;Thermal Science and Engineering Progress;2024-09
4. Artificial intelligence schemes to predict the mechanical performance of lignocellulosic fibers with unseen data to enhance the reliability of biocomposites;Engineering Computations;2024-06-04
5. Interpretable Machine Learning Framework to Predict the Glass Transition Temperature of Polymers;Polymers;2024-04-10
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3