WK.02 Grazing Incidence SAXS Theory and Data Analysis
Saturday, May 28, 2014
Speakers and Notes:
Walter Van Herck, Jülich Centre for Neutron Science JCNS, Germany
Alex Hexemer, Advanced Light Source, Lawrence Berkeley National Laboratory
Zhang Jiang, Advanced Photon Source, Argonne National Laboratory
Joseph Strzalka, Advanced Photon Source, Argonne National Laboratory
Kevin Yager, National Synchrotron Light Source / Center for Functional Nanomaterials, Brookhaven National Laboratory
GISAXS is a unique method for characterizing the nanostructural features of materials, particularly at surfaces and interfaces, which would otherwise be impossible using traditional transmission-based scattering techniques[ i ]. It is a surface-sensitive tool for probing simultaneously the sample morphology both in-plane and out-of-plane, and is being increasingly utilized to measure the size, shape and spatial organization of nanoscale objects located on top of surfaces or embedded in mono- or multi- layered thin-film materials. Individual GISAXS images serve as static snapshots of nanoscale structure,while successive images provide a means to monitor and probe dynamical processes, including self-assembly or other reorganization events, which occur at nanometer length scales.
The success of GISAXS relies on the unique information that can be extracted from the data. Although microscopy techniques provide very valuable local information on the structure, GISAXS is the only technique able to provide statistical information on nanometer features averaged over square centimeters. Consequently, the method is quickly attracting strong interest as the scattering technique of choice for characterizing nanostructures and is complementary to direct imaging methods such as AFM, SEM or TEM.
Presently, a major bottleneck preventing GISAXS from reaching its full potential persists in the availability of data analysis and modeling resources for interpreting the data. The problem arises mainly because reflections in GISAXS add to the complexity of the analysis and simulation. A common approach adopted for treating the reflection is the distorted wave Born approximation (DWBA). Several DWBA-based software packages have been developed. Due to the increasing number of GISAXS experiments and fast data collection capability,there is an urgent need to be able to analyze the data sets quickly, ideally in real-time during the experiments. The recently developed HipGISAXS package[ii] is designed to benefit from massively parallel computing capability[iii],which reduces the time consuming GISAXS simulation dramatically, and enables modeling of GISAXS pattern from nano-objects of any arbitrary shapes in complex morphologies.
Because of rapid advancement in GISAXS data analysis tools and experimental tools, it is critical to hold a GISAXS School [iv] to ensure that researchers are fully aware of the recent development in this field and ultimately able to take full advantage of the existing GISAXS. This full-day workshop will cover GISAXS theory, data reduction and processing, and forward modeling of GISAXS pattern using two software packages.
The workshop format will include lectures on GISAXS theory,hand-on training for data reduction and forward GISAXS pattern simulation, introduction to sample environments, and an open help session where students can seek expert opinions on difficult problems or proposed experiments. Students will be expected to bring laptops with appropriate pre-installed software. Prior to the workshop, a website will be configured containing installation instructions and software for each tutorial. Students will be sent information sheets by email a month prior to the meeting containing the course web address and other instructions for testing software installations. On-site network connectivity will be provided as part of the course. Pre-loaded portable disks and memory sticks will be available to help reduce the need for large downloads over conference bandwidth.
We expect to have at least 2 tutors for each session. The morning session will focus on basic essential tasks, assuming little previous knowledge, walking students through basic GISAXS theory, and data reduction and processing using Nika. The emphasis will be given to GISAXS experimental geometries at a synchrotron beamline, knowing how to judge data quality, what to do about problematic samples, and basic steps to process the data.
The afternoon session will focus on forward GISAXS pattern modeling using BornAgain and HipGISAXS. GISAXS patterns of nanoparticles of simple/custom shapes in simple/complex morphology will be given.There will also be a brief introduction of implementing massively parallel computing tools for GISAXS pattern simulation and its benefits.
Financial support for WK.02 workshop provided by
Morning session 8AM-12PM
Introduction: What can we learn from GISAXS data?
Theory Essentials: GISAXS theory.
Sample preparation, experimental geometries and current GISAXS capabilities at synchrotron beamlines.
Hand-on data reduction and processing using Nika.
Afternoon session 1-5PM
Hand-on GISAXS pattern simulation using BornAgain [v], and HipGISAXS.
Brief introduction of parallel computing for GISAXS simulation.
Open Help Session, Q & A
Alex Hexemer Advanced Light Source, LBNL
Chenhui Zhu Advanced Light Source, LBNL
i Renaud, G., Lazzari, R. & Leroy, F. (2009). Surf. Sci. Rep. 64, 255-380.
ii Chourou, S.T., Sarje, A., Li, X.S., Chan, E. R. & Hexemer, A. (2013). J. Appl. Crystallo. 46, doi:10.1107/S0021889813025843.
iii Sarje, A., Li, X. S., Chourou, S. T., Chan, E. R. & Hexemer, A. (2012). SC'12
Proceedings of the International Conference on High Performance Computing Networking, Storage and Analysis, Article No. 46. Salt Lake City: IEEE Computer Society Press.
iv The last GISAXS School was held in 2012 during the User Meeting of the Advanced
Light Source, Lawrence Berkeley National Laboratory. http://www.saxswaxs.com/1and1/GISAXS_School_2012_ALS.html