纳米技术
纳米颗粒
材料科学
分散性
沉积(地质)
电泳沉积
纳米光刻
化学气相沉积
原子层沉积
过程(计算)
粒子(生态学)
计算机科学
图层(电子)
纳米制造
工艺工程
纳米结构
可扩展性
制作
无定形二氧化硅
化学工程
电泳
二氧化硅
粒径
气相沉积
聚合物
作者
Karmakar, Srabani,Deo Milind,Rahaman, Imteaz,Mohanty, Swomitra Kumar
出处
期刊:Cornell University - arXiv
日期:2025-03-28
标识
DOI:10.48550/arxiv.2503.22593
摘要
Silica nanoparticles have emerged as key building blocks for advanced applications in electronics, catalysis, energy storage, biomedicine, and environmental science. In this review, we focus on recent developments in both the synthesis and deposition of these nanoparticles, emphasizing the widely used Stöber method and the versatile technique of electrophoretic deposition (EPD). The Stöber method is celebrated for its simplicity and reliability, offering precise control over particle size, morphology, and surface properties to produce uniform, monodisperse silica nanoparticles that meet high-quality standards for advanced applications. EPD, on the other hand, is a cost-effective, room-temperature process that enables uniform coatings on substrates with complex geometries. When compared to traditional techniques such as chemical vapor deposition, atomic layer deposition, and spin coating, EPD stands out due to its scalability, enhanced material compatibility, and ease of processing. Moreover, Future research should integrate AI-driven optimization with active learning to enhance electrophoretic deposition (EPD) of silica nanoparticles, leveraging predictive modeling and real-time adjustments for improved film quality and process efficiency. This approach promises to accelerate material discovery and enable scalable nanofabrication of advanced functional films.
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