New Publication on Machine Learning Enabled Contact Angle Goniometry

A new publication titled “Machine Learning Enabled Orthogonal Camera Goniometry for Accurate and Robust Contact Angle Measurements” was published in Scientific Reports, in January 2023. 

Machine learning enabled dual camera goniometry for contact angle measurements.

Understanding the wetting properties of surfaces is crucial for physical, chemical, and biological processes. However, conventional methods for accurately estimating contact angles, especially on hydrophilic surfaces, can be limited by optical distortions caused by moving droplets. In response, we have developed a new setup that combines Convolutional Neural Networks (CNN) with an automated orthogonal camera goniometer to estimate contact angles with high precision.

Our algorithm was trained on a dataset of 3375 images, including different lighting conditions and various degrees of Gaussian blurring, and was found to be less sensitive to edge effects than existing goniometers. In addition, our method was able to accurately analyze droplets of different colors and chemistries on a range of surfaces. The resulting contact angle measurements from our automated orthogonal camera goniometer exhibited significantly lower average standard deviation (6.7°) and coefficient of variation (14.9%) compared to existing techniques (average standard deviation of 14.6° and coefficient of variation of 29.2%). This demonstrates the reliability and precision of our method for characterizing the wetting properties of non-spherical droplets on heterogeneous surfaces.

This is the first article from our group’s Ph.D. candidate Hossein Kabir. Congratulations Hossein!

The article can be accessed here

New Publication on Tracking Cementitious Carbonation via Raman Imaging

A new publication titled “Tracking Spatiotemporal Evolution of Cementitious Carbonation via Raman Imaging” was published in the Journal of Raman Spectroscopy in December 2022.

Raman imaging of calcium carbonate after specified time of CO2 exposure to Ordinary Portland Cement paste sample.

Carbonation of cement systems is a growing area of interest as it offers a permanent solution to store CO2. Various analytical techniques like measuring pH changes and calcite content over time have been used to study this dynamic process. However, these methods rely on bulk measurements, which may miss the fine microstructural changes that occur during carbonation. In this work, we report the use of Raman imaging to follow the carbonation process in cement pastes at a micron-scale resolution. Results show that 40% of the sample surface was covered with calcite after 2 weeks of exposure and portlandite content declined from 15% to 5%. These findings suggest that other hydration products such as calcium silicate hydrate and ettringite also undergo carbonation simultaneously along with calcium hydroxide, opening up the possibility of using Raman imaging to understand the nature and kinetics of complex dynamic phenomena.

This is the first article from our group’s M.S. graduate Sonali Srivastava. Congratulations Sonali!

This article can be accessed here.