Engineering topics

Xu, Wenqian (ORCID:0000000248156253)

Publications and source records attributed to Xu, Wenqian (ORCID:0000000248156253).

3 records

DOE OSTI2024

Microstrain screening towards defect-less layered transition metal oxide cathodes

Microstrain and the associated surface-to-bulk propagation of structural defects are known to be major roadblocks to developing high-energy and long-life batteries. However, the origin and effects of microstrain during the synthesis of battery materials remain largely unknown. Here, in this study, we perform microstrain screening during real-time and realistic synthesis of sodium layered oxide cathodes. Evidence gathered from multiscale in situ synchrotron X-ray diffraction and microscopy characterization collectively reveals that the spatial distribution of transition metals within individual precursor particles strongly governs the nanoscale phase transformation, local charge heterogeneity and accumulation of microstrain during synthesis. This unexpected dominance of transition metals results in a counterintuitive outward propagation of defect nucleation and growth. These insights direct a more rational synthesis route to reduce the microstrain and crystallographic defects within the bulk lattice, leading to significantly improved structural stability. The present work on microstrain screening represents a critical step towards synthesis-by-design of defect-less battery materials.

25 ENERGY STORAGE↗

DOE OSTI2023

Machine learning-assisted crystal engineering of a zeolite

Abstract It is shown that Machine Learning (ML) algorithms can usefully capture the effect of crystallization composition and conditions (inputs) on key microstructural characteristics (outputs) of faujasite type zeolites (structure types FAU, EMT, and their intergrowths), which are widely used zeolite catalysts and adsorbents. The utility of ML (in particular, Geometric Harmonics) toward learning input-output relationships of interest is demonstrated, and a comparison with Neural Networks and Gaussian Process Regression, as alternative approaches, is provided. Through ML, synthesis conditions were identified to enhance the Si/Al ratio of high purity FAU zeolite to the hitherto highest level (i.e., Si/Al = 3.5) achieved via direct (not seeded), and organic structure-directing-agent-free synthesis from sodium aluminosilicate sols. The analysis of the ML algorithms’ results offers the insight that reduced Na 2 O content is key to formulating FAU materials with high Si/Al ratio. An acid catalyst prepared by partial ion exchange of the high-Si/Al-ratio FAU (Si/Al = 3.5) exhibits improved proton reactivity (as well as specific activity, per unit mass of catalyst) in propane cracking and dehydrogenation compared to the catalyst prepared from the previously reported highest Si/Al ratio (Si/Al = 2.8).

36 MATERIALS SCIENCE↗

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↗