Newly formed atmospheric aerosol particles exert a considerable impact on global climate by affecting the Earth's radiation balance. Nucleation plays a pivotal role in the formation of these particles. Understanding how particles nucleate in a multi-component gas mixture has important implications not only for climate and weather but also wide-ranging technological applications including gas separations, pollution control, and nanotechnology. Atmospheric nucleation involves multi-scale processes ranging from proton transfer to molecular condensation and evaporation events and culminating in the rare formation of the critical nucleus. The goals of this project are (i) to develop computational algorithms and analysis tools for efficient investigations of multi-component gas-to-particle nucleation processes, (ii) to elucidate atmospherically relevant nucleation processes and to validate the rate predictions through strategically selected laboratory experiments measuring cluster size and mass distributions at the sub-3 nm scale, and (iii) to deploy a freely-available cyber-tool that transforms data to knowledge by enabling large-scale modelers and experimental researchers to harvest predicted atmospheric nucleation rates and learn about mechanisms, by providing a general framework to visualize and analyze the abundance of digital data generated by particle-based simulations for any type of gas-to-particles nucleation process, and by being an aid for teaching about nucleation.
The project impacts our understanding of atmospheric nucleation pathways and sheds light on how quantitative modeling of the nucleation kinetics affects global climate models and impacts the ability to influence atmospheric nucleation. Driven by the partnership of researchers from different fields, diverse academic institutions, and international collaborators, the education, training, and mentoring of undergraduate and graduate students is advanced in a unique way that broadens participation. Knowledge gained from this project infuses the excitement of discovery in courses and laboratories taught by the team members. Outreach activities to junior high schools and science museums allow a broader community to learn about atmospheric nucleation.
This is a Cyber-Enabled Discovery and Innovation Program award and is co-funded by the Division of Chemistry, the Division of Civil, Mechanical & Manufacturing Innovation, the Office of International Science & Engineering, and the Experimental Program to Stimulate Competitive Research.
Intellectual Merit: Developed a new Monte Carlo technique for extremely efficient conformational sampling of a broad range of complex molecular systems, including those encountered in atmospheric nucleation; Improved AVUS-HR to allow efficient study of nucleation in heterogeneous environment, such as ion-induced nucleation, surface-induced nucleation and crystallization, and solute aggregation in solution; Integrated empirical valence bond into our nucleation methodology framework toenable the study of multi-component nucleation involving reactive species; Formulated a nucleation-based approach for a study of the solvation effectsimportant for many chemical and biological phenomena, such as aggregation ofhydrophobic solutes and protein folding; Assisted co-PI Dr. Jinzhu Gao from Univ. of the Pacific with the development of a cyber-tool for investigating gas-to-particle (atmospheric) nucleation pathways (CT-IANP) by providing the nucleation data obtained and testing the CT-IANP tool. Broader Impacts: Developed new computational methodologies that are applicable to studies of nucleation processes in diverse science and engineering applications; Advanced the cyber-infrastructure via the development of a freely-available cyber-tool for the prediction and analysis of gas-to-particle nucleation processes; Improved the fundamental understanding of nucleation phenomena and the deficiencies of the popular classical nucleation theory. 6 peer-reviewed publications, 1 PhD thesis, and 15 national/international presentations have resulted from this work. 3 PhD students (H Kim, T Loeffler, and A Sepehri) and 2 undergraduate students (D Henderson and A Galatas) have been supported from this grant.
