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Here, we describe a new synchrotron X-ray Fluorescence (XRF) imaging instrument with an integrated High Energy Fluorescence Detection X-ray Absorption Spectroscopy (HERFD-XAS) spectrometer at the Stanford Synchrotron Radiation Lightsource at beamline 6-2. The X-ray beam size on the sample can be defined via a range of pinhole apertures or focusing optics. XRF imaging is performed using a continuous rapid scan system with sample stages covering a travel range of 250 × 200 mm2, allowing for multiple samples and/or large samples to be mounted. The HERFD spectrometer is a Johann-type with seven spherically bent 100 mm diameter crystals arranged on intersecting Rowland circles of 1 m diameter with a total solid angle of about 0.44% of 4π sr. A wide range of emission lines can be studied with the available Bragg angle range of ∼64.5°–82.6°. With this instrument, elements in a sample can be rapidly mapped via XRF and then selected features targeted for HERFD-XAS analysis. Furthermore, utilizing the higher spectral resolution of HERFD for XRF imaging provides better separation of interfering emission lines, and it can be used to select a much narrower emission bandwidth, resulting in increased image contrast for imaging specific element species, i.e., sparse excitation energy XAS imaging. This combination of features and characteristics provides a highly adaptable and valuable tool in the study of a wide range of materials.

The proposed X-ray spatial light modulator (SLM) concept is based on the difference of X-ray scattering from amorphous and crystalline regions of phase change materials (PCMs) such as Ge2Sb2Te5 (GST). In our X-ray SLM design, the “on” and “off” states correspond to a patterned and homogeneous state of a GST thin film, respectively. The patterned state is obtained by exposing the homogeneous film to laser pulses. In this paper, we present patterning results in GST thin films characterized by microwave impedance microscopy and X-ray small-angle scattering at the Stanford Synchrotron Radiation Lightsource.

Combinatorial materials science strategies have accelerated materials development in a variety of fields, and we extend these strategies to enable structure–property mapping for light absorber materials, particularly in high order composition spaces. High throughput optical spectroscopy and synchrotron X-ray diffraction are combined to identify the optical properties of Bi–V–Fe oxides, leading to the identification of Bi_4V_(1.5)Fe_(0.5)O_(10.5) as a light absorber with direct band gap near 2.7 eV. The strategic combination of experimental and data analysis techniques includes automated Tauc analysis to estimate band gap energies from the high throughput spectroscopy data, providing an automated platform for identifying new optical materials.

© 2017 American Chemical Society. Investment in brighter sources and larger and faster detectors has accelerated the speed of data acquisition at national user facilities. The accelerated data acquisition offers many opportunities for the discovery of new materials, but it also presents a daunting challenge. The rate of data acquisition far exceeds the current speed of data quality assessment, resulting in less than optimal data and data coverage, which in extreme cases forces recollection of data. Herein, we show how this challenge can be addressed through the development of an approach that makes routine data assessment automatic and instantaneous. By extracting and visualizing customized attributes in real time, data quality and coverage, as well as other scientifically relevant information contained in large data sets, is highlighted. Deployment of such an approach not only improves the quality of data but also helps optimize the usage of expensive characterization resources by prioritizing measurements of the highest scientific impact. We anticipate our approach will become a starting point for a sophisticated decision-tree that optimizes data quality and maximizes scientific content in real time through automation. With these efforts to integrate more automation in data collection and analysis, we can truly take advantage of the accelerating speed of data acquisition.