Stewart McIntyre's abstract

Bragg Speaks Seminar
OPAL Auditorium, Building 83, ANSTO

Monday 6 September 2010

2:00 pm - 3:00 pm

Science Studio: a Possible Route to Improved Access to the Worlds Synchrotrons?

Professor Stewart McIntyre

(Canadian manager of a UWO/CLS/IBM partnership at Canadian Light Source)
University of Western Ontario, Canada

Synchrotrons provide unique views of materials and their transformations that are essential to modern scientific progress. Yet, their efficiency is restricted by traditional practices, that require researchers to be physically present at the facility and to rely on data treatment processes that frequently lag behind those used in more conventional scientific circles, both in function and speed. Science Studio is web-based software that is designed to provide a beginning synchrotron user with the tools to control x ray fluorescence (XRF) and x ray diffraction (XRD) experiments from a synchrotron beam line equipped for such experiments. It is also equipped to provide high performance computation of the experimental results using software whose reliability is maintained and updated. Within Science Studio, the researcher will be able to process results from scan in near real time and make adjustments to ongoing experiments.

As well, Science Studio is also a platform for access to other more conventional experiments whose access is limited by distance or hazards. Finally, Science Studio acts as a notebook for the researcher, retaining all details of the experimental process and encouraging verbal and written among the scientific team and later with a wider community. The software and website were designed initially for use at the VESPERS XRF/XRD beamline at the Canadian Light Source, and the Nanofabrication Laboratory at the University of Western Ontario; however, its functions could be adapted for use by the micro XRD/XFM beamline that will be constructed at the AS. In the meantime, Science Studio could provide Australian researchers with a tool for access to other beamlines, including VESPERS as well as the computing resources to process massive data sets that are becoming a staple of modern science.