A closer look at high-energy X-ray-induced bubble formation during soft tissue imaging.

Improving the scalability of tissue imaging throughput with bright, coherent X-rays requires identifying and mitigating artifacts resulting from the interactions between X-rays and matter. At synchrotron sources, long-term imaging of soft tissues in solution can result in gas bubble formation or cavitation, which dramatically compromises image quality and integrity of the samples. By combining in-line phase-contrast imaging with gas chromatography in real time, we were able to track the onset and evolution of high-energy X-ray-induced gas bubbles in ethanol-embedded soft tissue samples for tens of minutes (two to three times the typical scan times). We demonstrate quantitatively that vacuum degassing of the sample during preparation can significantly delay bubble formation, offering up to a twofold improvement in dose tolerance, depending on the tissue type. However, once nucleated, bubble growth is faster in degassed than undegassed samples, indicating their distinct metastable states at bubble onset. Gas chromatography analysis shows increased solvent vaporization concurrent with bubble formation, yet the quantities of dissolved gasses remain unchanged. By coupling features extracted from the radiographs with computational analysis of bubble characteristics, we uncover dose-controlled kinetics and nucleation site-specific growth. These hallmark signatures provide quantitative constraints on the driving mechanisms of bubble formation and growth. Overall, the observations highlight bubble formation as a critical yet often overlooked hurdle in upscaling X-ray imaging for biological tissues and soft materials and we offer an empirical foundation for their understanding and imaging protocol optimization. More importantly, our approaches establish a top-down scheme to decipher the complex, multiscale radiation-matter interactions in these applications.

Thermodynamic Insights into the Oxidation Mechanisms of CrMnFeCoNi High-Entropy Alloy Using In Situ X-ray Diffraction.

This paper utilizes in situ X-ray diffraction (XRD) to investigate the high-temperature oxidation behaviour of CrMnFeCoNi high-entropy alloy (HEA). We found that (1) Mn is the major oxide-forming element in both vacuum and air environments, leading to the formation of non-protective oxides that deplete the bulk alloy of Mn; (2) no oxides like Cr2O3, Fe2O3, or Fe3O4 were observed during the high-temperature oxidation behaviour of CrMnFeCoNi, which contradicts some previous studies on the isothermal oxidation of CrMnFeCoNi HEA. We also analysed and compared the experimental results with thermodynamic calculations by using ThermoCalc version 2022b software following the CALPHAD method. ThermoCalc predicted spinel oxide in a vacuum environment, along with halite oxides observed in experimental results; also, in an atmospheric environment, it predicted only spinel, indicating the need for further investigation into factors to validate the thermodynamic predictions. Our study shows that the in situ HTXRD technique is a powerful tool to accurately identify time-temperature-dependent phase formation/transformation for studying oxidation behaviours and understanding oxidation mechanisms in HEAs.

Quasi-Continuous Wave Pulsed Laser Welding of Copper Lap Joints Using Spatial Beam Oscillation.

Laser beam welding of copper (Cu) using near-infrared radiation is extremely challenging due to its high thermal conductivity and large laser reflectivity. In the present study, the challenges and benefits of using spatial beam oscillation during quasi-continuous wave (QCW) pulsed laser beam welding of 0.4 mm Cu to 1 mm Cu in lap joint configuration are presented. This work demonstrates how laser beam oscillating parameters can be used to control the laser weld quality and laser weld dimensions for Cu-Cu joining. Compared to a non-oscillated laser beam, welds made using laser beam oscillation showed fewer spatters, porosities, and better surface quality. Four levels of oscillating amplitudes (0.2 mm, 0.4 mm, 0.6 mm, and 0.8 mm) and oscillating frequencies (100 Hz, 200 Hz, 300 Hz, and 400 Hz) were compared to reveal the effect of beam oscillation parameters. The weld width was mainly controlled by oscillating amplitude, while weld penetration was affected by both oscillating amplitude and frequency. As the oscillating amplitude increased, the weld width increased while the weld penetration decreased. Increasing the oscillating frequency reduced the weld penetration but had a negligible effect on the weld width. The maximum tensile force of approximately 1944 N was achieved for the joint with a high width-to-depth ratio with an oscillating amplitude of 0.8 mm and an oscillating frequency of 200 Hz.

Effects of galactosyltransferase on EPS biosynthesis and freeze-drying resistance of Lactobacillus acidophilus NCFM.

Galactosyltransferase (GalT) is an important enzyme in synthesizing exopolysaccharide (EPS), the major polymer of biofilms protecting cells from severe conditions. However, the contribution to, and regulatory mechanism of GalT, in stressor resistance are still unclear. Herein, we successfully overexpressed GalT in Lactobacillus acidophilus NCFM by genetic engineering. The GalT activity and freeze-drying survival rate of the recombinant strain were significantly enhanced. The EPS yield also increased by 17.8%, indicating a positive relationship between freeze-drying resistance and EPS. RNA-Seq revealed that GalT could regulate the flux of the membrane transport system, pivotal sugar-related metabolic pathways, and promote quorum sensing to facilitate EPS biosynthesis, which enhanced freeze-drying resistance. The findings concretely prove that the mechanism of GalT regulating EPS biosynthesis plays an important role in protecting lactic acid bacteria from freeze-drying stress.

Keyhole fluctuation and pore formation mechanisms during laser powder bed fusion additive manufacturing.

Keyhole porosity is a key concern in laser powder-bed fusion (LPBF), potentially impacting component fatigue life. However, some keyhole porosity formation mechanisms, e.g., keyhole fluctuation, collapse and bubble growth and shrinkage, remain unclear. Using synchrotron X-ray imaging we reveal keyhole and bubble behaviour, quantifying their formation dynamics. The findings support the hypotheses that: (i) keyhole porosity can initiate not only in unstable, but also in the transition keyhole regimes created by high laser power-velocity conditions, causing fast radial keyhole fluctuations (2.5-10 kHz); (ii) transition regime collapse tends to occur part way up the rear-wall; and (iii) immediately after keyhole collapse, bubbles undergo rapid growth due to pressure equilibration, then shrink due to metal-vapour condensation. Concurrent with condensation, hydrogen diffusion into the bubble slows the shrinkage and stabilises the bubble size. The keyhole fluctuation and bubble evolution mechanisms revealed here may guide the development of control systems for minimising porosity.

Time-Aware Service Ranking Prediction in the Internet of Things Environment.

With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets.