What is it about?
Silver iodide (AgI) is a material famous for its ability to make supercooled water freeze, a property used in technologies like cloud seeding. In this work, we asked a simple question: what happens if that surface isn't perfect? Using large-scale computer simulations, we studied how water behaves on AgI surfaces where we had systematically removed atoms to create defects of different sizes. We discovered that these defects act as "growth inhibitors" for ice. They do this by promoting the formation of the "wrong" kind of ice. The perfectly hexagonal AgI surface acts as an ideal template for hexagonal ice to grow upon. However, the defects encourage the growth of cubic ice, creating a "template mismatch" at the molecular level that disrupts and slows down the entire freezing process. We analyzed these complex structures using advanced topological network methods, which were the early precursors to the d-SEAMS software.
Featured Image
Photo by Aaron Burden on Unsplash
Why is it important?
This study provides a clear, molecular-level explanation for why surface imperfections can hinder ice formation, even on an otherwise excellent ice-promoting material. The "template mismatch" concept offers an intuitive way to understand a very complex phenomenon. This insight is valuable for any technology where controlling ice is critical, from designing more efficient materials for cloud seeding to developing better anti-icing surfaces for airplanes and power lines. Methodologically, it was an early demonstration of using advanced topological analysis to extract detailed structural insights from complex simulation data, revealing a story that simpler metrics might have missed.
Perspectives
This was my very first journal publication, a formative experience for me as a researcher fresh out of my undergrad. I was brought onto a flagging project to support a master's student, and my role was to run the massive computer simulations and make sense of the complex data. It was a tough environment, and I came into the project too late to fix some of the underlying sampling issues. But I dove into the analysis, applying and developing the topological network methods that would eventually become the bedrock of my d-SEAMS software. I learned everything on the fly, relying almost entirely on the guidance of my senior lab mate, Amrita Goswami, who was an invaluable mentor. Her intellectual guidance was foundational to the entire analysis, and the methods I developed were a direct result of her mentorship. The scientific story in this paper would not exist without her contributions which she later honed into a series of stellar publications. In some sense, this paper was still a huge milestone for me. It was where I first saw how better analytical tools could pull a clear, physical story—the "template mismatch" idea—out of messy simulation data, and it solidified my passion for building better software to do better science.
Rohit Goswami
University of Iceland
Read the Original
This page is a summary of: Study of ice nucleation on silver iodide surface with defects, Molecular Physics, August 2019, Taylor & Francis,
DOI: 10.1080/00268976.2019.1657599.
You can read the full text:
Contributors
The following have contributed to this page
