A new publication titled “Enhancing Phase Identification in Waste-to-Energy Fly Ashes: Role of Raman Spectroscopy, Background Fluorescence, and Photobleaching” is set to be published in The Journal of Hazardous Materials in October 2023.
This article is is the first one from our group’s postdoctoral researcher Dr. Hamza Samouh. Additionally, Ph.D. candidate Vikram Kumar and undergraduate student Halle-Mari Santiago also contributed to this work. Congratulations Hamza, Vikram, and Halle-Mari for this very interesting work!
A new publication titled “Elucidating the Size and Shape of Individual Clinker Phases via Raman Imaging: Impact on Cement Hydration” was published in The Journal of Physical Chemistry C in August 2023.
This is the third article from our group’s Ph.D. candidate Krishna C. Polavaram. Congratulations Krishna for this very interesting work!
A new publication titled “Rapid Prediction of Cementitious Initial Sorptivity via Surface Wettability” was published in npj Materials Degradation, in July 2023.
One of the tests to predict the durability of cement-based materials involves measurement of water uptake over time. This ‘sorptivity’ test, however, is laborious and time-consuming (continuous weight measurements over several hours to days).
Today, we report a rapid test method that exploits fundamental wetting characteristics of cementitious systems to predict their 6-hour initial sorptivity in a matter of few seconds. Enabled by computer vision, the quantification of drop spreading dynamics opens up a new pathway for rapid, automated, and affordable testing of cementitious systems.
This is the second article from our group’s Ph.D. candidate Hossein Kabir. Congratulations Hossein for this very interesting work!
The news release for this publication can be accessed here.
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.
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!
A new publication titled “Tracking Spatiotemporal Evolution of Cementitious Carbonation via Raman Imaging” was published in the Journal of Raman Spectroscopy in December 2022.
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!
A new publication titled “Superhydrophobic and Self-Cleaning Aluminum via a Rapid and Controlled Process” was published in ACS Applied Engineering Materials in October 2022.
Engineers have been often inspired by nature in various ways, ranging from the design of structures to the selection of materials. For e.g., lotus leaves exhibit hydrophobic behavior which has been translated to the creation of self-cleaning materials. One construction material of interest is aluminum for light-weight structural applications. Previously, studies have reported creation of superhydrophobic aluminum surfaces. However, most of the processes are not environmentally friendly, are time-consuming, and some are not feasible for large-scale applications. In our most recent paper, we present a rapid and controlled process to create superhydrophobic aluminum for use in external environments. With a 1 hr of fabrication time, we achieve contact angle of 158.06° and a sliding angle of 1.94°. Finally, the surface is durable and resilient when exposed to a range of extreme temperatures (-18°C to 100°C). These results pave the way for implementation of superhydrophobic aluminum surfaces for large-scale structural and construction applications.
This is the first article from our group’s MS candidate Ravi Sharma.