Disorder recovers the Wiedemann-Franz law in the metallic phase of VO2

At temperatures higher than 341 K, vanadium dioxide (VO2) is a strongly correlated metal with resistivity exceeding the Mott-Ioffe-Regel limit. Its electronic thermal conductivity is lower than that predicted by the Wiedemann-Franz (WF) law, and can be explained by nonquasiparticle transport where heat and charge currents follow separate diffusive modes. In contradiction, the Wiedemann-Franz law is a direct consequence of quasiparticle transport where charge carriers are elastically scattered. In this work, we enhance elastic electron scattering in VO2 by introducing atomic disorder with ion irradiation. A gradual and eventually full recovery of the WF law is observed at high defect densities. This observation provides an example that connects hydrodynamic quasiparticle transport to nonquasiparticle transport in metallic systems

Disorder recovers the Wiedemann-Franz law in the metallic phase of VO2

At temperatures higher than 341 K, vanadium dioxide (VO2) is a strongly correlated metal with resistivity exceeding the Mott-Ioffe-Regel limit. Its electronic thermal conductivity is lower than that predicted by the Wiedemann-Franz (WF) law, and can be explained by nonquasiparticle transport where heat and charge currents follow separate diffusive modes. In contradiction, the Wiedemann-Franz law is a direct consequence of quasiparticle transport where charge carriers are elastically scattered. In this work, we enhance elastic electron scattering in VO2 by introducing atomic disorder with ion irradiation. A gradual and eventually full recovery of the WF law is observed at high defect densities. This observation provides an example that connects hydrodynamic quasiparticle transport to nonquasiparticle transport in metallic systems

Extreme mixing in nanoscale transition metal alloys

The ability to alloy different elements is critical for property tuning and materials discovery. However, general alloying at the nanoscale remains extremely challenging due to strong immiscibility and easy oxidation, particularly for early transition metals that are highly reactive. Here, we report nanoscale alloying using a high-temperature- and high-entropy-based strategy (T∗ΔSmix) to significantly expand the possible alloys and include early transition metals. While high-temperature synthesis favors alloy formation and metal reduction, the high-entropy compositional design is critical to further extending the alloying to strongly repelling combinations (e.g., Au-W) and easily oxidized elements (e.g., Zr). In particular, we explicitly characterized a record 15-element nanoalloy, which showed a solid-solution structure featuring localized strain and lattice distortions as a result of extreme mixing. Our study significantly broadens available compositions of nanoalloys and provides clear guidelines by utilizing the less-explored entropic chemistry

py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project

Algorithm for Applying 3D Printing in Prototype Realization – Case: Enclosure for an Industrial Pressure Transmitter

Additive manufacturing technology helped many organizations to save money in the product design process by reducing prototype costs, and also by providing a means for early evaluation and decision making. The idea of this paper is to design an electronics enclosure for an intelligent industrial pressure transmitter, using the additive technology. All enclosure elements are made on a 3D printer WANHAO duplicator i3 plus, using PLA materials. The enclosure realization, from CAD drawings to the finished model, enables a designer to correct existing errors, or make certain modifications as required by end-users. A process is described that enables designers to review their decisions at any stage of product realization, thus providing much more freedom in rapid prototyping. In this example, the advantages and disadvantages of additive manufacturing over conventional manufacturing are outlined. Some deficiencies have also been observed, such as mechanical damage to surfaces, burning of surfaces, tearing of prints, and surface roughness. To mitigate such irregularities, both mechanical and chemical finishing methods were used. The example confirmed that the finishing methods can affect the final enclosure dimensions and shape. Further prototype development should focus more on print quality, which depends on the shape of surfaces, the accuracy of the geometry, the uniformity of structure and shape, material density, and the resolution of details.Proceedings of the International Conference of Experimental and Numerical Investigations and New Technologies, CNNTech 2020, vol 153, June 29 – July 02, Zlatibor, Serbia