Engineering topics
Publications and source records attributed to Ratner, Daniel.
Recently demonstrated isolated attosecond XFEL pulses should allow the probing of ultrafast electron dynamics at X-ray wavelengths. The authors use ghost imaging to enable high-resolution transient absorption spectroscopy at fluctuating XFEL sources.
On June 5, 2019, the Office of Science (SC) organized a one-day roundtable to focus on enhancing access to high-quality and fully traceable research data, models, and computing resources to increase the value of such resources for artificial intelligence (AI) research and development and the SC mission.1 In this report, we consider AI to be inclusive of, for example, machine learning (ML), deep learning (DL), neural networks (NN), computer vision, and natural language processing (NLP). We consider “data for AI” to mean the digital artifacts used to generate AI models and/or employed in combination with AI models during inference. In part, this roundtable was motivated by the recognition that a large portion of science data currently are not well suited for AI.
To identify specific Priority Research Opportunities (PROs) for artificial intelligence and machine learning (AI/ML) at the US Department of Energy’s scientific user facilities, the Office of Basic Energy Sciences (BES) convened a roundtable of facility experts encompassing the fields of physics, chemistry, materials synthesis science, computational science, detector and accelerator technology, theory, modeling, simulation, and atomic-scale characterization techniques. The roundtable met on October 22–23, 2019, to identify coordinated, long-term AI/ML research efforts that will drive major advances in neutron, photon, and nanoscale sciences. This report describes the four PROs identified at the roundtable: PRO 1 on how AI/ML can extract high-value information from the large datasets; PRO 2 on how AI/ML can use such information in real time to maximize the facilities’ scientific output; PRO 3 on using AI/ML virtual laboratories (i.e., computational models of experimental facilities) to aid the facilities and user community in design and control of machine parameters and the design and execution of experiments, including training AI/ML models for PROs 1 and 2; and PRO 4 on how a shared scientific data infrastructure can provide tools to assemble and analyze the totality of data coming from user facilities. A section of the end of the report provides a summary on computer science and mathematics that highlights where enhanced AI/ML capabilities could be particularly impactful for BES user facilities.
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During X-ray exposure of a molecular solution, photons scattered from the same molecule are correlated. If molecular motion is insignificant during exposure, then differences in momentum transfer between correlated photons are direct measurements of the molecular structure. In conventional small- and wide-angle solution scattering, photon correlations are ignored. This report presents advances in a new biomolecular structural analysis technique, correlated X-ray scattering (CXS), which uses angular intensity correlations to recover hidden structural details from molecules in solution. Due to its intense rapid pulses, an X-ray free electron laser (XFEL) is an excellent tool for CXS experiments. A protocol is outlined for analysis of a CXS data set comprising a total of half a million X-ray exposures of solutions of small gold nanoparticles recorded at the Spring-8 Ångström Compact XFEL facility (SACLA). From the scattered intensities and their correlations, two populations of nanoparticle domains within the solution are distinguished: small twinned, and large probably non-twinned domains. Finally, it is shown analytically how, in a solution measurement, twinning information is only accessible via intensity correlations, demonstrating how CXS reveals atomic-level information from a disordered solution of like molecules.
X-ray free electron lasers (XFELs) enable unprecedented new ways to study the electronic structure and dynamics of transition metal systems. L-edge absorption spectroscopy is a powerful technique for such studies and the feasibility of this method at XFELs for solutions and solids has been demonstrated. But, the required x-ray bandwidth is an order of magnitude narrower than that of self-amplified spontaneous emission (SASE), and additional monochromatization is needed. We compare L-edge x-ray absorption spectroscopy (XAS) of a prototypical transition metal system based on monochromatizing the SASE radiation of the linac coherent light source (LCLS) with a new technique based on self-seeding of LCLS. We demonstrate how L-edge XAS can be performed using the self-seeding scheme without the need of an additional beam line monochromator. Lastly, we show how the spectral shape and pulse energy depend on the undulator setup and how this affects the x-ray spectroscopy measurements.