Chemistry and Microphysics of Small Particles
EMSL Project ID
42299
Abstract
This research is focused on the development and application of unique tools and methods to study the fundamental properties and processes that govern the chemistry and microphysics of particles at the nano scale. The centerpiece of our proposed research is SPLAT II, an ultra-sensitive, high-precision instrumentation system we developed for the in-situ, real-time multidimensional characterization of the size, composition, density, shape, morphology, hygroscopicity, and fractal dimension of. We plan to take advantage of the instrument's high sensitivity and develop a new data acquisition mode, in which particle number concentrations, size distributions, densities, and asphericity are characterized at high rate. This approach should yield detailed information on particle physical properties with unprecedented temporal resolution. We will apply these tools to investigate methods to characterize particles composed of a mixture of organic compounds and use this capability to investigate particle formation, chemical and physical transformations, and evaporation. In particular, we will look into the effect of coatings on particle properties and temporal evolution. To take full advantage of the vast amounts of detailed data that this system produces, we have developed novel approaches to data analysis. SpectraMiner, our interactive data visualization and mining software package offers the user a wide range of visually driven controls to explore datasets containing millions of individual particle mass spectra without loss of information. ClusterSculptor is a program that overcomes the limitations of traditional statistical approaches by placing the scientist at the center of the data organization process to expertly-steer the data classification. We will apply this hardware's software system to advance our understanding of the processes responsible for the formation of atmospheric particles containing organics; characterize the particles that act as cloud condensation and ice cloud nuclei; investigate the relationship between combustion processes and the detailed chemical and microphysical properties of the particles that it generates; and characterize the formation and properties of particles with core-shell morphologies. We shall advance the hardware-software package by developing a third generation system that offers high-resolution mass spectra and advanced data visualization and mining tools.
Project Details
Project type
Exploratory Research
Start Date
2010-10-18
End Date
2011-10-23
Status
Closed
Released Data Link
Team
Principal Investigator
Team Members
Related Publications
Abramson EH, D Imre, J Beranek, J Wilson, and A Zelenyuk. 2013. "Experimental Determination of Chemical Diffusion within Secondary Organic Aerosol Particles." Physical Chemistry Chemical Physics. PCCP 15(8):2983-2991. doi:10.1039/C2CP44013J
Lee HJ, KT McDonnell, A Zelenyuk, D Imre, and K Mueller. 2014. "A Structure-Based Distance Metric for High-Dimensional Space Exploration with Multi-Dimensional Scaling." IEEE Transactions on Visualization and Computer Graphics 20(3):351-364. doi:10.1109/TVCG.2013.101
Papenhausen E, Wang B, Ha S, Zelenyuk A, Imre D, and Mueller K. 2013. "GPU-Accelerated Incremental Correlation Clustering of Large Data with Visual Feedback," The First Workshop on Big Data Visualization, Santa Clara, CA, October, 2013 doi:10.1109/BigData.2013.6691716
Wang J ,Mueller K 2015. "The Visual Causality Analyst: An Interactive Interface for Causal Reasoning" IEEE Transactions on Visualization and Computer Graphics 22(1):230 - 239. 10.1109/TVCG.2015.2467931
Zelenyuk A, D Imre, J Wilson, Z Zhang, J Wang, and K Mueller. 2015. "Airborne Single Particle Mass Spectrometers (SPLAT II & miniSPLAT) and New Software for Data Visualization and Analysis in a Geo-Spatial Context." Journal of The American Society for Mass Spectrometry:1-14. doi:10.1007/s13361-014-1043-4
Zhang Z, X Tong, KT McDonnell, A Zelenyuk, D Imre, and K Mueller. 2013. "An Interactive Visual Analytics Framework for Multi-Field Data in a Geo-Spatial Context." Tsinghua Science and Technology 18(2):111-124.