Parameter extraction from electromagnetic eigenmode simulations of multimodal cavities using MFEM
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We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus ‘super-resolution’). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.
Diatoms contribute to carbon fixation in the oceans by photosynthesis and always form biofouling organized by extracellular polymeric substances (EPS) in the marine environment. Bacteria-produced quorum-sensing signal molecules N-acyl homoserine lactones (AHLs) were found to play an important role in the development of Cylindrotheca sp. in previous studies, but the EPS composition change was unclear. This study used the technology of alcian blue staining and scanning electron microscopy (SEM), confocal laser scanning microscopy (CLSM), and time-of-flight secondary ion mass spectrometry (ToF-SIMS) to directly observe the biofilm formation process. The results showed that AHLs promote the growth rates of diatoms and the EPS secretion of biofilm components. AHLs facilitated the diatom-biofilm formation by a forming process dependent on the length of carbon chains. AHLs increased the biofilm thickness and the fluorescence intensity and then altered the three-dimensional (3D) structures of the diatom-biofilm. In addition, the enhanced EPS content in the diatom-biofilm testified that AHLs aided biofilm formation. This study provides a collection of new experimental evidence of the interaction between bacteria and microalgae in fouling biofilms.
Neural network ensembles for X-ray absorption spectroscopy of molecules and materials. Companion code for preprint https://arxiv.org/abs/2210.00336.
Methods for detection, monitoring, and determination of location of changes in rigid structures with arbitrarily complex geometries are described. Implementations include locating acoustic transducers that generate and receive acoustic signals at multiple locations along a surface of the rigid structure, wherein longitudinal spacing between the transducer locations define measurement zones. Acoustic signals with chosen amplitude-time-frequency characteristics excite multiple vibration modes in the structure within each zone. Small mechanical changes in the inspection zones lead to scattering and attenuation of broadband acoustic signals, which are detectable as changes in received signal characteristics as part of a through-transmission technique. Additional use of short, narrowband pulse acoustic signals as part of a pulse-echo technique allows determination of the relative location of the mechanical change within each zone based on the differential delay profiles.
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Abstract not provided.
The behavior of solar cells is very often limited by inhomogeneously distributed nanoscale defects. This is the case throughout the entire lifecycle of the solar cell, from the distribution of elements and defects during solar cell growth as well as the charge-collection and recombination during operation, to degradation and failure mechanisms due to impurity diffusion, crack formation, and irradiation- and heat-induced cell damage This has been known for a while in the field of crystalline silicon, but inhomogeneities are far more abundant in polycrystalline materials, and are the limiting factor in thin-film solar cells where grain sizes are often on the order of the diffusion length. We showed that the high penetration of hard X-rays combined with the high sensitivity to elemental distribution, structure, and spatial resolution offers a unique avenue for highly correlative studies at the nanoscale. We presented results on Cu-doped CdTe, where carrier collection is directly correlated to the kinetics of Cu inside the absorber and the particular Cu-phases at the ZnTe/CdTe interface. We complemented the results with modeling using PVRD-FASP and PyCDTS, where the X-ray beam induced profile can be reproduced by the equilibrium defect concentrations proposed by the solvers.
Abstract not provided.
Current geochemical analytical techniques such as gas chromatography-mass spectrometry (GC-MS and $G\acute{C}GC-MS$) can effectively determine the composition and structure of the organic biosignatures within a sample but cannot resolve the spatial distribution of organic biosignatures within rocks or sediments. The spatial distribution can be used to determine the character of the organic biosignatures [1], which can be indigenous (deposited with host rocks), non-indigenous (incorporated after deposition via fluid migration), or contaminant. Determining the character of organic biosignatures is critical for ancient samples [2] and will be critical if organics are observed in samples returned from Mars [3].Fs-LDPI-MS has the ability to map organic compounds across the surface of samples at 2 - 10 μm lateral resolution. Furthermore, fs-LDPI-MS can be used to carry out multiple analyses in the same location for micron-scale analysis of previously buried material [4]. We used fs-LDPI-MS to examine a ~164 million year old organic-rich mudstone from SW England (14.2 wt. % total organic carbon) [5] and determined the spatial distribution of likely indigenous components buried below potentially contaminated surface layers.We then used ToF-SIMS to re-analyze the mudstone to directly compare ToF-SIMS to fs-LDPI-MS datasets, and to analyze a series of ~2.7 billion year old geologic samples from Timmins, ON, CA [6]. Ref. [6] previously analyzed the Archean samples and observed a series of archaeal biomarkers, as well as hopanes and steranes. Using ToF-SIMS analysis, we were able to detect hopanes and steranes in the mudstone samples, but not in the Archean samples indicating that the hopanes and steranes are most likely contaminants in the Archean samples. We also did not observe the archaeal biomarkers; however, this may be from the lack of molecular ion preservation during ToF-SIMS.
Acoustic transducers generate and receive acoustic signals at multiple locations along a surface of rigid structure, wherein longitudinal spacing between transducer locations define measurement zones. Acoustic signals with chosen amplitude-time-frequency characteristics excite multiple vibration modes in the structure within each zone. Small mechanical changes in inspection zones lead to scattering and attenuation of broadband acoustic signals, which are detectable as changes in received signal characteristics as part of a through-transmission technique. Additional use of short, narrowband pulse acoustic signals as part of a pulse-echo technique allows determination of the relative location of the mechanical change within each zone based on the differential delay profiles. For accurate acoustic modeling and simulation, the mesh size, time step, time delay, and time-window size are optimized. Frequency normalization of the Short-Time Fourier Transform of acoustic response output improves experiment-simulation cross-validation. Applications of the method to structures with arbitrarily complex geometries are also demonstrated.
We consider the problem of minimizing multi-modal loss functions with a large number of local optima. Since the local gradient points to the direction of the steepest slope in an infinitesimal neighborhood, an optimizer guided by the local gradient is often trapped in a local minimum. To address this issue, we develop a novel nonlocal gradient to skip small local minima by capturing major structures of the loss’s landscape in black-box optimization. The nonlocal gradient is defined by a directional Gaussian smoothing (DGS) approach. The key idea of DGS is to conducts 1D long-range exploration with a large smoothing radius along d orthogonal directions in Rd, each of which defines a nonlocal directional derivative as a 1D integral. Such long-range exploration enables the nonlocal gradient to skip small local minima. The d directional derivatives are then assembled to form the nonlocal gradient. We use the Gauss-Hermite quadrature rule to approximate the d 1D integrals to obtain an accurate estimator. The superior performance of our method is demonstrated in three sets of examples, including benchmark functions for global optimization, and two real-world scientific problems.
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Abstract not provided.
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