Engineering topics

Weng, James

Publications and source records attributed to Weng, James.

3 records

DOE OSTI2023

In situ X-ray area detector flat-field correction at an operating photon energy without flat illumination

Flat-field calibration of X-ray area detectors is a challenge due to the inability to generate an X-ray flat-field at the selected photon energy the beamline operates at, which has a strong influence on the measurement behavior of the detector. A method is presented in which a simulated flat-field correction is calculated without flat-field measurements. Instead, a series of quick scattering measurements from an amorphous scatterer is used to calculate a flat-field response. The ability to rapidly obtain a flat-field response allows for recalibration of an X-ray detector as needed without significant expenditure of either time or effort. Area detectors on the beamlines used, such as the Pilatus 2M CdTe, PE XRD1621 and Varex XRD 4343CT, were found to have detector responses that drift slightly over timescales of several weeks or after exposure to high photon flux, suggesting the need to more frequently recalibrate with a new flat-field correction map.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Artifact identification in X-ray diffraction data using machine learning methods

In situ synchrotron high-energy X-ray powder diffraction (XRD) is highly utilized by researchers to analyze the crystallographic structures of materials in functional devices ( e.g. battery materials) or in complex sample environments ( e.g. diamond anvil cells or syntheses reactors). An atomic structure of a material can be identified by its diffraction pattern along with a detailed analysis of the Rietveld refinement which yields rich information on the structure and the material, such as crystallite size, microstrain and defects. For in situ experiments, a series of XRD images is usually collected on the same sample under different conditions ( e.g. adiabatic conditions) yielding different states of matter, or is simply collected continuously as a function of time to track the change of a sample during a chemical or physical process. In situ experiments are usually performed with area detectors and collect images composed of diffraction patterns. For an ideal powder, the diffraction pattern should be a series of concentric Debye–Scherrer rings with evenly distributed intensities in each ring. For a realistic sample, one may observe different characteristics other than the typical ring pattern, such as textures or preferred orientations and single-crystal diffraction spots. Textures or preferred orientations usually have several parts of a ring that are more intense than the rest, whereas single-crystal diffraction spots are localized intense spots owing to diffraction of large crystals, typically >10 µm. In this work, an investigation of machine learning methods is presented for fast and reliable identification and separation of the single-crystal diffraction spots in XRD images. The exclusion of artifacts during an XRD image integration process allows a precise analysis of the powder diffraction rings of interest. When it is trained with small subsets of highly diverse datasets, the gradient boosting method can consistently produce high-accuracy results. The method dramatically decreases the amount of time spent identifying and separating single-crystal diffraction spots in comparison with the conventional method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Circumventing thermodynamics to synthesize highly metastable perovskites: nano eggshells of SnHfO 3

Sn(II)-based perovskite oxides, being the subject of longstanding theoretical interest for the past two decades, have been synthesized for the first time in the form of nano eggshell particle morphologies. All past reported synthetic attempts have been unsuccessful owing to their metastable nature, i.e., by their thermodynamic instability towards decomposition to their constituent oxides. A new approach was discovered that finally provides an effective solution to surmounting this intractable synthetic barrier and which can be the key to unlocking the door to many other predicted metastable oxides. A low-melting KSn 2 Cl 5 salt was utilized to achieve a soft topotactic exchange of Sn(II) cations into a Ba-containing perovskite, i.e., BaHfO 3 with particle sizes of ~350 nm, at a low reaction temperature of 200 °C. The resulting particles exhibit nanoshell-over-nanoshell morphologies, i.e., with SnHfO 3 forming as ~20 nm thick shells over the surfaces of the BaHfO 3 eggshell particles. Formation of the metastable SnHfO 3 is found to be thermodynamically driven by the co-production of the highly stable BaCl 2 and KCl side products. Despite this, total energy calculations show that Sn(II) distorts from the A-site asymmetrically and randomly and the interdiffusion has a negligible impact on the energy of the system (i.e., layered vs. solid solution). Additionally, nano eggshell particle morphologies of BaHfO 3 were found to yield highly pure SnHfO 3 for the first time, thus circumventing the intrinsic ion-diffusion limits occurring at this low reaction temperature. In summary, these results demonstrate that the metastability of many theoretically predicted Sn(II)-perovskites can be overcome by leveraging the high cohesive energies of the reactants, the exothermic formation of a stable salt side product, and a shortened diffusion pathway for the Sn(II) cations.

36 MATERIALS SCIENCE↗