Localized engineering of grain boundary morphology by electro-nano-pulsing processing
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Al-Si alloys processed by laser rapid solidification yield eutectic microstructures with ultrafine and interconnected fibers. Such fibrous structures have long been thought to bear resemblance to those formed in impurity-doped alloys upon conventional casting. Here, we show that any similarity is purely superficial. By harnessing high-throughput characterization and computer vision techniques, we perform a three-dimensional analysis of the branching behavior of the ultrafine eutectic and compare it against an impurity-modified eutectic as well as a random fractal (as a benchmark). Differences in the branching statistics point to different microstructural origins of the impurity- and quench-modified eutectic. Finally, our quantitative approach is not limited to the data presented here but can be used to extract abstract information from other volumetric datasets, without customization.
In this study, the growth of ZrO x on Au (111) was investigated using scanning tunneling microscopy (STM) and synchrotron-based ambient pressure X-ray photoelectron spectroscopy (AP-XPS). Nanostructures of ZrO x (x= 1,2) at the sub-monolayer (≤ 0.3 ML) level were prepared by vapor depositing Zr metal onto Au (111) followed by oxidation with O 2 or CO 2 . At low coverages of the admetal (< 0.05 ML), the formed ZrO x nanostructures were dispersed randomly on the terraces and steps of the Au(111) substrate. Strong oxide-metal interactions prevented the formation of islands of zirconia. The ZrO x nanostructures displayed a reactivity towards CO 2 and H 2 not seen for bulk zirconia. C 1 s AP-XPS results indicated that CO 2 molecules adsorbed on Zr/ZrO x /Au(111) surfaces could undergo partial decomposition on Zr (CO 2 , gas → CO gas + O ads ), or react with oxygen sites from ZrO x to yield carbonates (Zr-CO 3, ads ). Further, after exposing ZrO 2 /Au (111) surfaces to 1:3 mixtures of CO 2 :H 2 , the formation of HCOO, CO 3 , and CH 3 O was detected in AP-XP spectra. These chemical species decomposed at temperatures in the range of 400-600 K, making them possible reaction intermediates for methanol synthesis.
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Abstract The present work discusses the use of a weakly-supervised deep learning algorithm that reduces the cost of labelling pixel-level masks for complex radio galaxies with multiple components. The algorithm is trained on weak class-level labels of radio galaxies to get class activation maps (CAMs). The CAMs are further refined using an inter-pixel relations network (IRNet) to get instance segmentation masks over radio galaxies and the positions of their infrared hosts. We use data from the Australian Square Kilometre Array Pathfinder (ASKAP) telescope, specifically the Evolutionary Map of the Universe (EMU) Pilot Survey, which covered a sky area of 270 square degrees with an RMS sensitivity of 25–35 $\mu$ Jy beam $^{-1}$ . We demonstrate that weakly-supervised deep learning algorithms can achieve high accuracy in predicting pixel-level information, including masks for the extended radio emission encapsulating all galaxy components and the positions of the infrared host galaxies. We evaluate the performance of our method using mean Average Precision (mAP) across multiple classes at a standard intersection over union (IoU) threshold of 0.5. We show that the model achieves a mAP $_{50}$ of 67.5% and 76.8% for radio masks and infrared host positions, respectively. The network architecture can be found at the following link: https://github.com/Nikhel1/Gal-CAM
Microstructural control in metal-dielectric hybrid metamaterials presents enormous opportunities in tailoring the physical properties including the magnetic and optical properties. In this paper, we demonstrate a strong tunability achieved in the microstructure of self-assembled ordered three-phase Au-BaTiO 3 –ZnO hybrid metamaterial along with its optical properties, grown by a pulsed laser deposition method. Varying the growth temperature, deposition frequency, and template thickness evolves the microstructure by tuning the Au and ZnO pillar geometry as well as the shape and size of the Au nanoparticles capping the ZnO nanowires. The three-phase hybrid metamaterials exhibit unique optical properties, including enhanced nonlinear optical properties, hyperbolic dispersion in the visible and near-infrared wavelength region, and tuned epsilon-near-zero (ENZ) wavelength upon varying the deposition parameters. This study suggests that the three-phase hybrid metamaterials present great potential in the microstructure and optical property tuning that can also be applied to other two-phase and three-phase nanocomposite systems.