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Multiphysics Co-Optimization Design and Analysis of Double-Side Cooled Silicon Carbide-Based Power Module: Preprint
With the rapid growth of Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs), much more rigorous design targets have been set for automotive power electronics, including high power density, high reliability, and low cost. Novel power module and inverter technologies based on wide bandgap (WEG) semiconductors have been developed to meet these design targets, while providing optimal power semiconductor operating temperature and promising thermomechanical performance. Compared with conventional cooling techniques which are normally applied only on one side of power module, double-side cooling approach is now believed to be the solution to enable high power density and low thermal resistance of WEG semiconductor-based power electronics. In this work, we develop a three-phase power module that is double-sided cooled using dielectric fluid jet impingement. In each phase, four silicon carbide (SiC) power semiconductors are bonded to copper busbars without electrical insulation layers. A finite element analysis (FEA) model is created for thermal and thermomechanical analysis. Based on FEA modeling results, we select particular dimensions for a parametric study to optimize thermal and mechanical performance. Using a multi-objective genetic algorithm (MOGA)-based optimization method, we have minimized the maximum junction temperature and thermal stresses within the power module. The multiphysics co-optimization approach has enabled an efficient design process of power modules with greatly reduced computational cost, as compared to conventional processes that rely on exhaustive numerical simulations and iterations.
Application of automated iterative target detection for standoff hyperspectral imaging
The utility of hyperspectral imaging (HSI) has been well established for a wide array of applications but has generated a need for automated screening of high volumes of large HSI cubes. We report two important automated algorithms for more efficient standoff processing: atmospheric correction and target detection. The atmospheric correction method is based on a fast asymmetric least squares approach that is applied on a pixel-by-pixel basis. Here, the correction can be applied to entire images without manually identifying regions of interest and utilizes only in-scene information, no ancillary modeling of the atmosphere is required. An iterative target detection approach is also introduced which demonstrates faster speeds relative to moving window approaches. The target detection algorithm classifies each pixel as true target detections, near target detections, clutter, and no-calls. The algorithms were tested on forty images of twenty-two solid mineral targets placed at a 14-meter standoff distance allowing general observations on expected detection performance for a variety of minerals. In addition to identifying anomalous pixels, the inclusion of “no-calls” reduced the number of false detections significantly.
Experimental observation of chiral phonons in monolayer WSe2
Copyright © 2019 SPIE. Chirality characterizes an object that is not identical to its mirror image. In condensed matter physics, Fermions have been demonstrated to obtain chirality through structural and time-reversal symmetry breaking. These systems display unconventional electronic transport phenomena such as the quantum Hall effect and Weyl semimetals. However, for bosonic collective excitations in atomic lattices, chirality was only theoretically predicted and has never been observed. We experimentally show that phonons can exhibit intrinsic chirality in monolayer tungsten diselenide, whose lattice breaks the inversion symmetry and enables inequivalent electronic K and -K valley states. The time-reversal symmetry is also broken when we selectively excite the valley polarized holes by circularly polarized light. Brillouin-zone-boundary phonons are then optically created by the indirect infrared absorption through the hole-phonon interactions. The unidirectional intervalley transfer of holes ensures that only the phonon modes in one valley are excited. We found that such photons are chiral through the transient infrared circular dichroism, which proves the valley phonons responsible to the indirect absorption has non-zero pseudo-angular momentum. From the spectrum we further deduce the energy transferred to the phonons that agrees with both the first principle calculation and the double-resonance Raman spectroscopy. The chiral phonons have significant implications for electron-phonon coupling in solids, lattice-driven topological states, and energy efficient information processing.
Binary pseudo-random array standards for calibration of 3D optical surface profilers used for metrology with aspheric x-ray optics
High-accuracy surface metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate x-ray light with nanometer-scale wavelengths. The current and potential capabilities of x˗ray mirror manufacturing are limited by inherent imperfections of the integrated metrology tools. Metrology tools are currently calibrated with super-polished flat test-standard/reference mirrors. This is acceptable for fabrication of slightly curved x-ray optics. However, for even moderately curved aspherical x-ray mirrors the flat-reference calibration is not sufficiently accurate. For micro-stitching interferometry developed for surface measurements with curved x-ray mirrors, the tool aberration errors are known to be transferred into the optical surface topography of x-ray mirrors. Our approach to improving metrology is to thoroughly calibrate the measuring tool and apply the results of the calibration to deconvolution of the measured data. Here we explore the application of a recently developed technique for calibrating the instrument transfer function (ITF) of 3D optical surface profilers to metrology with significantly curved x-ray optics. The technique, based on test standards patterned with two-dimensional (2D) binary pseudo-random arrays (BPRAs), employs the unique properties of the BPRA patterns in the spatial frequency domain. The inherent 2D power spectral density of the pattern has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range and field of view of an instrument. The high efficacy of the technique has been previously demonstrated in application to metrology with flat and slightly curved optics. Here, we concentrate on development of an efficient fabrication process for production of highly randomized (HR) BPRA test standards on flat and 500-mm spherical optical substrates. We also compare and discuss the results of the ITF calibration of an interferometric microscope when using the HR BPRA standards on flat and curved substrates.
Optimizing transmit field inhomogeneity of parallel RF transmit design in 7T MRI using deep learning
Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) provides a higher signal-to-noise ratio and, thereby, higher spatial resolution. However, UHF MRI introduces challenges such as transmit radiofrequency (RF) field (B+1) inhomogeneities, leading to uneven flip angles and image intensity anomalies. These issues can significantly degrade imaging quality and its medical applications. This study addresses B+1 field homogeneity through a novel deep learning-based strategy. Traditional methods like Magnitude Least Squares (MLS) optimization have been effective but are time-consuming and dependent on the patient’s presence. Recent machine learning approaches, such as RF Shim Prediction by Iteratively Projected Ridge Regression and deep learning frameworks, have shown promise but face limitations like extensive training times and oversimplified architectures. We propose a two-step deep learning strategy. First, we obtain the desired reference RF shimming weights from multi-channel B+1 fields using random-initialized Adaptive Moment Estimation. Then, we employ Residual Networks (ResNets) to train a model that maps B+1 fields to target RF shimming outputs. Our approach does not rely on pre-calculated reference optimizations for the testing process and efficiently learns residual functions. Comparative studies with traditional MLS optimization demonstrate our method’s advantages in terms of speed and accuracy. The proposed strategy achieves a faster and more efficient RF shimming design, significantly improving imaging quality at UHF. This advancement holds potential for broader applications in medical imaging and diagnostics.
Generation of a novel phase-space-based cylindrical dose kernel for IMRT optimization
Purpose: Improving dose calculation accuracy is crucial in intensity-modulated radiation therapy (IMRT). We have developed a method for generating a phase-space-based dose kernel for IMRT planning of lung cancer patients. Methods: Particle transport in the linear accelerator treatment head of a 21EX, 6 MV photon beam (Varian Medical Systems, Palo Alto, CA) was simulated using the EGSnrc/BEAMnrc code system. The phase space information was recorded under the secondary jaws. Each particle in the phase space file was associated with a beamlet whose index was calculated and saved in the particle's LATCH variable. The DOSXYZnrc code was modified to accumulate the energy deposited by each particle based on its beamlet index. Furthermore, the central axis of each beamlet was calculated from the orientation of all the particles in this beamlet. A cylinder was then defined around the central axis so that only the energy deposited within the cylinder was counted. A look-up table was established for each cylinder during the tallying process. The efficiency and accuracy of the cylindrical beamlet energy deposition approach was evaluated using a treatment plan developed on a simulated lung phantom. Results: Profile and percentage depth doses computed in a water phantom for an open, square field size were within 1.5% of measurements. Dose optimized with the cylindrical dose kernel was found to be within 0.6% of that computed with the nontruncated 3D kernel. The cylindrical truncation reduced optimization time by approximately 80%. Conclusions: A method for generating a phase-space-based dose kernel, using a truncated cylinder for scoring dose, in beamlet-based optimization of lung treatment planning was developed and found to be in good agreement with the standard, nontruncated scoring approach. Compared to previous techniques, our method significantly reduces computational time and memory requirements, which may be useful for Monte-Carlo-based 4D IMRT or IMAT treatment planning.
Technical Note: Multipurpose CT, ultrasound, and MRI breast phantom for use in radiotherapy and minimally invasive interventions
Purpose: To develop a multipurpose gel-based breast phantom consisting of a simulated tumor with realistic imaging properties in CT, ultrasound and MRI, or a postsurgical cavity on CT. Applications for the phantom include: deformable image registration (DIR) quality assurance (QA), autosegmentation validation, and localization testing and training for minimally invasive image-guided procedures such as those involving catheter or needle insertion. Methods: A thermoplastic mask of a typical breast patient lying supine was generated and then filled to make an array of phantoms. The background simulated breast tissue consisted of 32.4 g each of ballistic gelatin (BG) powder and Metamusil™ (MM) dissolved in 800 ml of water. Simulated tumors were added using the following recipe: 12 g of barium sulfate (1.4% v/v) plus 0.000 14 g copper sulfate plus 0.7 g of MM plus 7.2 g of BG all dissolved in 75 ml of water. The phantom was evaluated quantitatively in CT by comparing Hounsfield units (HUs) with actual breast tissue. For ultrasound and MRI, the phantoms were assessed based on subjective image quality and signal-difference to noise (SDNR) ratio, respectively. The stiffness of the phantom was evaluated based on ultrasound elastography measurements to yield an average Young’s modulus. In addition, subjective tactile assessment of phantom was performed under needle insertion. Results: The simulated breast tissue had a mean background value of 24 HU on CT imaging, which more closely resembles fibroglandular tissue (40 HU) as opposed to adipose (−100 HU). The tumor had a mean CT number of 45 HU, which yielded a qualitatively realistic image contrast relative to the background either as an intact tumor or postsurgical cavity. The tumor appeared qualitatively realistic on ultrasound images, exhibiting hypoechoic characteristics compared to background. On MRI, the tumor exhibited a SDNR of 3.7. The average Young’s modulus was computed to be 15.8 ± 0.7 kPa (1 SD). Conclusions: We have developed a process to efficiently and inexpensively produce multipurpose breast phantoms containing simulated tumors visible on CT, ultrasound, and MRI. The phantoms have been evaluated for image quality and elasticity and can serve as a medium for DIR QA, autosegmentation QA, and training for minimally invasive procedures.
SU-F-T-355: Evaluation of Knowledge-Based Planning Model for the Cervical Cancer Radiotherapy
Purpose: The Varian RapidPlan™ is a commercial knowledge-based optimization process which uses a set of clinically used treatment plans to train a model that can predict individualized dose-volume objectives. The purpose of this study is to evaluate the performance of RapidPlan to generate intensity modulated radiation therapy (IMRT) plans for cervical cancer. Methods: Totally 70 IMRT plans for cervical cancer with varying clinical and physiological indications were enrolled in this study. These patients were all previously treated in our institution. There were two prescription levels usually used in our institution: 45Gy/25 fractions and 50.4Gy/28 fractions. 50 of these plans were selected to train the RapidPlan model for predicting dose-volume constraints. After model training, this model was validated with 10 plans from training pool(internal validation) and additional other 20 new plans(external validation). All plans used for the validation were re-optimized with the original beam configuration and the generated priorities from RapidPlan were manually adjusted to ensure that re-optimized DVH located in the range of the model prediction. DVH quantitative analysis was performed to compare the RapidPlan generated and the original manual optimized plans. Results: For all the validation cases, RapidPlan based plans (RapidPlan) showed similar or superior results compared to the manual optimized ones. RapidPlan increased the result of D98% and homogeneity in both two validations. For organs at risk, the RapidPlan decreased mean doses of bladder by 1.25Gy/1.13Gy (internal/external validation) on average, with p=0.12/p<0.01. The mean dose of rectum and bowel were also decreased by an average of 2.64Gy/0.83Gy and 0.66Gy/1.05Gy,with p<0.01/ p<0.01and p=0.04/<0.01 for the internal/external validation, respectively. Conclusion: The RapidPlan model based cervical cancer plans shows ability to systematically improve the IMRT plan quality. It suggests that RapidPlan has great potential to make the treatment planning process more efficient.
Biomimetic potassium-selective nanopores
Reproducing the exquisite ion selectivity displayed by biological ion channels in artificial nanopore systems has proven to be one of the most challenging tasks undertaken by the nanopore community, yet a successful achievement of this goal offers immense technological potential. Here, we show a strategy to design solid-state nanopores that selectively transport potassium ions and show negligible conductance for sodium ions. The nanopores contain walls decorated with 4'-aminobenzo-18-crown-6 ether and single-stranded DNA (ssDNA) molecules located at one pore entrance. The ionic selectivity stems from facilitated transport of potassium ions in the pore region containing crown ether, while the highly charged ssDNA plays the role of a cation filter. Achieving potassium selectivity in solid-state nanopores opens new avenues toward advanced separation processes, more efficient biosensing technologies, and novel biomimetic nanopore systems.
Electric field control of magnon spin currents in an antiferromagnetic insulator
Pure spin currents can be generated via thermal excitations of magnons. These magnon spin currents serve as carriers of information in insulating materials, and controlling them using electrical means may enable energy efficient information processing. Here, we demonstrate electric field control of magnon spin currents in the antiferromagnetic insulator Cr 2 O 3 . We show that the thermally driven magnon spin currents reveal a spin-flop transition in thin-film Cr 2 O 3 . Crucially, this spin-flop can be turned on or off by applying an electric field across the thickness of the film. Using this tunability, we demonstrate electric field–induced switching of the polarization of magnon spin currents by varying only a gate voltage while at a fixed magnetic field. We propose a model considering an electric field–dependent spin-flop transition, arising from a change in sublattice magnetizations via a magnetoelectric coupling. These results provide a different approach toward controlling magnon spin current in antiferromagnets.
Molecular Mechanisms of Viral and Host Cell Substrate Recognition by Hepatitis C Virus NS3/4A Protease
Hepatitis C NS3/4A protease is a prime therapeutic target that is responsible for cleaving the viral polyprotein at junctions 3-4A, 4A4B, 4B5A, and 5A5B and two host cell adaptor proteins of the innate immune response, TRIF and MAVS. In this study, NS3/4A crystal structures of both host cell cleavage sites were determined and compared to the crystal structures of viral substrates. Two distinct protease conformations were observed and correlated with substrate specificity: (i) 3-4A, 4A4B, 5A5B, and MAVS, which are processed more efficiently by the protease, form extensive electrostatic networks when in complex with the protease, and (ii) TRIF and 4B5A, which contain polyproline motifs in their full-length sequences, do not form electrostatic networks in their crystal complexes. These findings provide mechanistic insights into NS3/4A substrate recognition, which may assist in a more rational approach to inhibitor design in the face of the rapid acquisition of resistance.
System Architecture Directions for Post-SoC/32-bit Networked Sensors
The emergence of low-power 32-bit Systems-on-Chip (SoCs), which integrate a 32-bit MCU, radio, and flash, presents an opportunity to re-examine design points and trade-offs at all levels of the system architecture of networked sensors. To this end, we develop a post-SoC/32-bit design point called Hamilton, showing that using integrated components enables a ~$7 core and shifts hardware modularity to design time. We study the interaction between hardware and embedded operating systems, identifying that (1) post-SoC motes provide lower idle current (5.9 μA) than traditional 16-bit motes, (2) 32-bit MCUs are a major energy consumer (e.g., tick increases idle current >50 times), comparable to radios, and (3) thread-based concurrency is viable, requiring only 8.3 μs of context switch time. We design a system architecture, based on a tickless multithreading operating system, with cooperative/adaptive clocking, advanced sensor abstraction, and preemptive packet processing. Its efficient MCU control improves concurrency with ~30% less energy consumption. Together, these developments set the system architecture for networked sensors in a new direction.
PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs
PuLP/XtraPulp is software for partitioning graphs from several real-world problems. Graphs occur in several places in real world from road networks, social networks and scientific simulations. For efficient parallel processing these graphs have to be partitioned (split) with respect to metrics such as computation and communication costs. Our software allows such partitioning for massive graphs.
APPRENTICE
SF-19-096 In this software, there are multiple approaches to compute approximations to multivariate functions. This includes: (a) an approach that builds on Stieltjes process to efficiently compute the coefficients of the rational approximation, (b) an approach that is based on an optimization formulation to get pole-free coefficients of the rational approximation and (c) approaches that finds the coefficients of rational and polynomial approximations by finding the linear least-squares solution using singular value decomposition.
TOMOCUPY
ANL REFERENCE SF-22-102 DESCRIPTION: Tomocupy is a Python package and a command-line interface for GPU reconstruction of tomographic/laminographic data in 16-bit and 32-bit precision. It implements an efficient data processing conveyor allowing to overlap all data transfers with computations. First, independent Python threads are started for reading data chunks from the hard disk into a Python data queue and for writing reconstructed chunks from the Python queue to the hard disk. Second, CPU-GPU data transfers are overlapped with GPU computations by using CUDA streams.
Data for Solvent-Free Enzymatic Esterification of Free Fatty Acids with Glycerol for Biodiesel Application: Optimized Using the Taguchi Experimental Method
Presence of free fatty acids along with glycerides poses a technical difficulty for biodiesel production. This work used a Taguchi L9 design to optimize the solvent-free enzymatic process to result in the esterification of oleic acid with glycerol. Under optimal conditions the esterification reaction temperature of 60°C, enzyme dose of 5 wt%, glycerol: oleic acid molar ratio of 5:1, and reaction time of 3 h, a 75.235 ± 2.19% conversion of oleic acid to esters was achieved. With the addition of molecular sieves, the conversion increased to 86.73% ± 1.09%. However, using the parameters predicted by Taguchi design (60°C, 5 wt%, 5:1, and 4.5 h), 88.5% ± 1.11% of oleic acid could be converted to esters derivative. Diglycerides were the major product, and the reaction equilibrium was attained after 4 h. The immobilized enzyme could be used up to seven times with only a 10% reduction in the conversion. Thus, the process can efficiently reduce the free fatty acid content of oil to make it suitable for biodiesel production.
Ultra-broadband quadrature squeezing with thin-film lithium niobate nanophotonics
Squeezed light is a key quantum resource that enables quantum advantages for sensing, networking, and computing applications. The scalable generation and manipulation of squeezed light with integrated platforms are highly desired for the development of quantum technology with continuous variables. In this Letter, we demonstrate squeezed light generation with thin-film lithium niobate integrated photonics. Parametric down-conversion is realized with quasi-phase matching using ferroelectric domain engineering. With sub-wavelength mode confinement, efficient nonlinear processes can be observed with single-pass configuration. We measure 0.56 ± 0.09 dB quadrature squeezing (∼2.6 dB inferred on-chip). The single-pass configuration further enables the generation of squeezed light with large spectral bandwidth up to 7 THz. This work represents a significant step towards the on-chip implementation of continuous-variable quantum information processing.