LDRD seminar: August 28
Three Argonne researchers will discuss their Laboratory-Directed Research and Development (LDRD) sponsored work at the LDRD Seminar Series presentation Tuesday, Aug. 28, 2018, at 12:30 p.m. in the Building 203 Auditorium. All are welcome to attend.
Visit the LDRD website to view upcoming seminars.
Circular Dichroism in the Single- and Multiphoton Ionization of Small Molecules by Senior Chemist and Department Head Stephen Pratt (CSE)
The chemistry of life is based on chiral molecules, that is, molecules in which the mirror image is not superimposable on the original. While such pairs of molecules generally have the same physical properties, they can show a slight asymmetry in the absorption of left and right circular polarized light, a phenomenon known as circular dichroism. In photoabsorption, this effect is typically very small, but the effect can be much larger in photoelectron angular distributions following photoionization. This LDRD project is aimed at using laboratory laser sources to observe and exploit this effect, and I will describe our progress towards this goal.
Stephen Pratt is a senior chemist and leader of the Gas-Phase Chemical Physics Group in CSE. He is also the theme leader for Fundamental Interactions. He earned his undergraduate at Bennington College and his graduate at Yale University. He first came to Argonne as a guest graduate student and worked in the Radiological and Environmental Research Division. After finishing his degree, he returned to Argonne as a postdoc in the Environmental Research Division, and has remained here ever since. He transferred to the Chemistry Division in 1997. Pratt is interested in the photoionization and photodissociation dynamics of small molecules and reactive species.
Limited-Area Atmospheric Modeling Using Structured and Unstructured Grid by Assistant Atmospheric Scientist Jiali Wang (EVS)
In this talk, I will compare atmospheric simulations by using the continuous refined grid and nested grid models. Two questions will be explored: (1) the way each of these grids handles the atmospheric waves along the boundaries of the area of interest and (2) whether limited-area atmospheric modeling is doing a better job than global modeling in terms of time efficiency and accuracy.
Jiali Wang is an assistant atmospheric scientist in the Environmental Sciences Division. She received her Ph.D. in meteorology from the Institute of Atmospheric Physics, Chinese Academy of Sciences and her Bachelor of Science degree in meteorology from the Nanjing University of Information Science and Technology. Wang has a strong expertise in climate modeling and extreme climate analysis. Her research includes physical understanding and evaluation of climate and climate variability through regional climate and hydrological modeling and analysis of observations. Her outreach collaboration includes using statistical tools and techniques to evaluate the model performance in terms of extreme events and space-time dependence; climate change impact on water quality and resources, infrastructure (road construction, power generation, biology and agriculture).
Genome Annotation with Deep Learning by Computer Scientist Fangfang Xia (DSL)
Genome research is generating large amounts of sequencing and phenotype screening data. We look at the role of deep learning in bridging the genotype-to-phenotype gap. We present neural network models for protein function prediction and genomic pattern discovery. We discuss how we might learn a better representation of DNA sequence with unsupervised methods.
Fangfang Xia is a computer scientist in the Data Science and Learning Division. He is interested in applying machine learning to computational biology.