Unconventional PDV applications: detecting plasma and radiation.
Abstract not provided.
Bell, Kate Suzanne↗
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Gravitational wave detection with plasma haloscopes
Searches for high frequency gravitational waves using cavities based on the Gertsenshtein effect were recently proposed, building off existing axion dark matter experiments. In particular, the sensitivity of axion dark matter experiments using metamaterial plasmas (tunable plasma haloscopes) to gravitational waves has not been explored in detail. Here we perform a full analysis of gravitational wave detection in plasma haloscopes, showing that the baseline design of experiments such as ALPHA is several orders of magnitude less sensitive than previously thought. We show how simple changes to the experiment can recover that sensitivity and lead to a powerful gravitational wave detector in the 𝒪(10–50) GHz frequency range.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)
It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Plasma ignition and detection for in-situ cleaning of 1.3 GHz 9-cell cavities
Superconducting Radio Frequency (SRF) cavities performance preservation is crucial, from vertical test to accelerator operation. Field Emission (FE) is still one of the performance limiting factors to overcome and plasma cleaning has been proven successful by the Spallation Neutron Source (SNS), in cleaning field emitters and increasing the work function of Nb. A collaboration has been established between Fermi National Accelerator Laboratory (FNAL), SLAC National Accelerator Laboratory and Oak Ridge National Laboratory (ORNL) with the purpose of applying plasma processing to the Linac Coherent Light Source-II (LCLS-II) cavities, in order to minimize and overcome field emission without affecting the high Q of nitrogen-doped cavities. The cleaning for LCLS-II will follow the same plasma composition adopted at SNS, which allows in-situ processing of cavities installed in cryomodules from hydrocarbon contaminants. A novel method for plasma ignition has been developed at FNAL: a plasma glow discharge is ignited using high order modes to overcome limitations imposed by the fundamental power coupler, allowing in-situ cleaning for cavities in cryomodule. The plasma can be easily ignited and tuned in each of the cavity cells using low RF power. A method for plasma detection has been developed as well, which allows the detection of the plasma location in the cavity without the need of cameras at both cavity ends. The presented method can be applied to other multi-cell cavity designs, even for accelerators where the coupling for the fundamental modes at room temperature is very weak.
43 PARTICLE ACCELERATORS↗
Low RF Power Plasma Ignition and Detection for In-Situ Cleaning of 1.3 GHz 9-Cell Cavities
Superconducting Radio Frequency (SRF) cavities performance preservation is crucial, from vertical test to accelerator operation. Field Emission (FE) is still one of the performance limiting factors to overcome and plasma cleaning has been proven successful by the Spallation Neutron Source (SNS), in cleaning field emitters and increasing the work function of Nb. A collaboration has been established between Fermi National Accelerator Laboratory (FNAL), SLAC National Accelerator Lab- oratory and Oak Ridge National Laboratory (ORNL) with the purpose of applying plasma processing to the Linac Coherent Light Source-II (LCLS-II) cavities, in order to minimize and overcome field emission without affecting the high Q of nitrogen-doped cavities. The cleaning for LCLS-II will follow the same plasma composition adopted at SNS, which allows in-situ processing of cavities installed in cryomod-ules from hydrocarbon contaminants. A novel method for plasma ignition has been developed at FNAL: a plasma glow discharge is ignited using high order modes to overcome limitations imposed by the fundamental power coupler, allowing in-situ cleaning for cavities in cryomodule. The plasma can be easily ignited and tuned in each of the cavity cells using low RF power. A method for plasma detection has been developed as well, which allows the detection of the plasma location in the cavity without the need of cameras at both cavity ends. The presented method can be applied to other multi-cell cavity designs, even for accelerators where the coupling for the fundamental modes at room temperature is very weak.
43 PARTICLE ACCELERATORS↗
Distributed Magnetic Measurements Using Fiber Optic Pulsed Polarimetry (Final Report)
Measurement of the magnetic fields surrounding magnetic fusion energy (MFE) devices, such as tokamaks, is critical for characterizing and monitoring the plasma inside these devices, and it is especially important for detecting plasma instabilities, which can lead to the plasma damaging the inside of these devices. This program successfully demonstrated a new type of magnetic field diagnostic that is capable for the first time of measuring simultaneously the spatial and temporal magnetic field distributions of MFE devices in real-time and with high resolution. This is a capability not feasible with existing magnetic field diagnostics and, moreover, the technique we developed provides other advantages, such as less susceptibility to noise, the ability to operate during both pulsed and steady-state plasma conditions, the ability to detect relatively weak poloidal fields, and potentially lower costs. This new capability of being able in real-time to detect anomalies in the magnetic field distribution corresponding to the onset of plasma instabilities offers the ability to automatically shut down the MFE device before the plasma can damage the machine. Hence, this machine protection capability can be vital for future fusion power stations. Our technique uses optical fibers where changes in the polarization of the laser light traveling through the fiber provide a direct measurement of the magnetic field at any point along the fiber. The small size of the fibers allows them to be easily installed either outside or inside the MFE vacuum vessel, and in any direction one wishes (e.g., poloidal or toroidal). We demonstrated the basic capabilities of our new diagnostic during a proof-of-principle experiment performed on the General Atomics DIII-D tokamak, and published the results in: W. D. Kimura, D. S. Dhillon, S. Munaretto, E. J. Strait, D. Du, S. Loranger, J.-S. Boisvert, and R. Kashyap, “Measurements of DIII-D poloidal field by fiber-optic pulsed polarimetry,” Rev. Sci, Inst. 89, 10J102 (2018).
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Analysis of Liquids Using the Submerged Plasma for Isotopic Detection and Elemental Resolution (SPIDER)
We developed a sensor called the Submerged Plasma for Isotopic Detection and Elemental Resolution (SPIDER) probe, which uses an atmospheric pressure glow discharge below the surface of liquids to excite species in the liquid. Through emission spectroscopy of molten salts, liquid metals, and heavy water, we demonstrated the SPIDER probe’s high resolution, accuracy, and versatility. We successfully identified trace concentrations of transition and rare-earth metals in molten salts and detected the isotopic shift of the H β → D β emission line. Our analysis revealed unconventional spectral alkali line shapes, indicating two competing excitation modes: film explosion and droplet vaporization. The film explosion mode, characterized by dense plasma, exhibited self-reversal and broadband continuum emission, while the droplet vaporization mode, associated with diffusive plasma, produced narrow-line emissions. Furthermore, by analyzing circuit transients alongside individual plasma events, we observed that film explosions generate higher currents, likely due to a shorter plasma length as the current preferentially flows through the thin liquid layer. Altogether, our results highlight the SPIDER probe’s efficacy and flexibility, making it well-suited for online material quantification of liquids in extreme environments.
AES↗
Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements
Abstract A real-time detection of the plasma confinement regime can enable new advanced plasma control capabilities for both the access to and sustainment of enhanced confinement regimes in fusion devices. For example, a real-time indication of the confinement regime can facilitate transition to the high-performing wide-pedestal (WP) quiescent H-mode, or avoid unwanted transitions to lower confinement regimes that may induce plasma termination. To demonstrate real-time confinement regime detection, we use the 2D beam emission spectroscopy (BES) diagnostic system to capture localized density fluctuations of long wavelength turbulent modes in the edge region at a 1 MHz sampling rate. BES data from 330 discharges in either L-mode, H-mode, quiescent H (QH)-mode, or WP QH-mode were collected from the DIII-D tokamak and curated to develop a high-quality database to train a deep-learning classification model for real-time confinement detection. We utilize the 6×8 spatial configuration with a time window of 1024 µ s and recast the input to obtain spectral-like features via fast Fourier transform preprocessing. We employ a shallow 3D convolutional neural network for the multivariate time-series classification task and utilize a softmax in the final dense layer to retrieve a probability distribution over the different confinement regimes. Our model classifies the global confinement state on 44 unseen test discharges with an average F 1 score of 0.94, using only ∼1 ms snippets of BES data at a time. This activity demonstrates the feasibility for real-time data analysis of fluctuation diagnostics in future devices such as ITER, where the need for reliable and advanced plasma control is urgent.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Measuring the electron temperature and identifying plasma detachment using machine learning and spectroscopy
A machine learning approach has been implemented to measure the electron temperature directly from the emission spectra of a tokamak plasma. This approach utilized a neural network (NN) trained on a dataset of 1865 time slices from operation of the DIII-D tokamak using extreme ultraviolet/vacuum ultraviolet emission spectroscopy matched with high-accuracy divertor Thomson scattering measurements of the electron temperature, T e . This NN is shown to be particularly good at predicting T e at low temperatures (T e < 10 eV) where the NN demonstrated a mean average error of less than 1 eV. Trained to detect plasma detachment in the tokamak divertor, a NN classifier was able to correctly identify detached states (T e < 5 eV) with a 99% accuracy (an F 1 score of 0.96) at an acquisition rate 10× faster than the Thomson scattering measurement. The performance of the model is understood by examining a set of 4800 theoretical spectra generated using collisional radiative modeling that was also used to predict the performance of a low-cost spectrometer viewing nitrogen emission in the visible wavelengths. Furthermore, these results provide a proof-of-principle that low-cost spectrometers leveraged with machine learning can be used to boost the performance of more expensive diagnostics on fusion devices and be used independently as a fast and accurate T e measurement and detachment classifier.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Novel biosensor using split-luciferase for detecting vitamin D receptor ligands based on the interaction between vitamin D receptor and coactivator
Highlights: • A novel split-luciferase-based biosensor was developed to detect VDR ligands. • LXXLL-motif peptide and ligand-bound LBD formed a functional complex. • The light intensity was increased by 10-fold compared to our previous versions. • The binding affinity of vitamin D analogs was measured in a short time. Vitamin D receptor (VDR) ligands, such as 1α,25-dihydroxyvitamin D{sub 3} [1α,25(OH){sub 2}D{sub 3}] and its analogs, have been investigated for their potential clinical use in the treatment of various diseases such as type I rickets, osteoporosis, psoriasis, leukemia, and cancer. Previously, we reported a split-luciferase-based biosensor that can detect VDR ligands and assess their affinity for the ligand binding domain (LBD) of the VDR in a short time. However, a further increase in its sensitivity was required to detect plasma levels of 1α,25(OH){sub 2}D{sub 3} and its analogs. In this study, a novel type of biosensor called LXXLL + LBD was successfully developed. Here, the split luciferase forms a functional complex based on the intermolecular interaction between the LXXLL motif and the ligand-bound form of the LBD. This biosensor has an approximately 10-fold increase in the light intensity compared to the previous versions. Additionally, the binding affinity of the vitamin D analogs for the wild-type and the rickets-associated mutant R274L of VDR was evaluated.
60 APPLIED LIFE SCIENCES↗
Activation of the CaR-CSE/H2S pathway confers cardioprotection against ischemia-reperfusion injury
Ischemia-reperfusion (I/R) injury is a multifactorial process triggered when an organ is subjected to transiently reduced blood supply. The result is a cascade of pathological complications and organ damage due to the production of reactive oxygen species following reperfusion. The present study aims to evaluate the role of activated calcium-sensing receptor (CaR)-cystathionine γ-lyase (CSE)/hydrogen sulfide (H2S) pathway in I/R injury. Firstly, an I/R rat model with CSE knockout was constructed. Transthoracic echocardiography, TTC and HE staining were performed to determine the cardiac function of rats following I/R Injury, followed by TUNEL staining observation on apoptosis. Besides, with the attempt to better elucidate how CaR-CSE/H2S affects I/R, in-vitro culture of human coronary artery endothelial cells (HCAECs) was conducted with gadolinium chloride (GdCl3, a CaR agonist), H{sub 2}O{sub 2}, siRNA against CSE (siCSE), or W7 (a CaM inhibitor). The interaction between CSE and CaM was subsequently detected. Plasma oxidative stress indexes, H2S and CSE, and apoptosis-related proteins were all analyzed following cell apoptosis. We found that H2S elevation led to the improvement whereas CSE knockdown decreased cardiac function in rats with I/R injury. Moreover, oxidative stress injury in I/R rats with CSE knockout was aggravated, while the increased expression of H2S and CSE in the aortic tissues resulted in alleviated the oxidative stress injury. Moreover, increased H2S and CSE levels were found to inhibit cell apoptotic ability in the aortic tissues after I/R injury, thus attenuating oxidative stress injury, accompanied by inhibited expression of apoptosis-related proteins. In HCAECs following oxidative stress treatment, siCSE and CaM inhibitor were observed to reverse the protection of CaR agonist. Coimmunoprecipitation assay revealed the interaction between CSE and CaM. Taken together, all above-mentioned data provides evidence that activation of the CaR-CSE/H2S pathway may confer a potent protective effect in cardiac I/R injury.
60 APPLIED LIFE SCIENCES↗
ContourNet: Salient Local Contour Identification for Blob Detection in Fusion Plasma Simulation Data
We present ContourNet, a deep learning approach to identify salient local isocontours as blobs in large-scale 5D gyrokinetic tokamak simulation data. Blobs-regions of high turbulence that run along the edge wall down toward the diverter and can damage the tokamak-are non-well-defined features but have been empirically localized by isocontours in 2D normalized fluctuating density fields. The key of our study is to train ContourNet to follow the empirical rules to detect blobs over the time-varying simulation data. The architecture of ContourNet is a convolutional neural segmentation network: the inputs are the density field and a rasterized isocontour; the output is a set of isocontour encircling blobs. At the training stage, we feed the network with manually identified isocontours and propagated labels. At the inference stage, we extract isocontours from the segmented blob regions. Results show that our approach can achieve both high accuracy and performance, which enables scientists to understand the blob dynamics influencing the confinement of the plasma.
Blob detection↗
Low RF Power Plasma Ignition and Detection for In-situ Cleaning of 1.3 GHZ 9-Cell Cavities
$\bullet$ The project consists in a collaboration between three national labs and it is supported by DOE Basic Energy Sciences (BES). $\bullet$ The main objective is adapting the SNS plasma cleaning to LCLS-II cavities. $\bullet$ Neon-Oxygen plasma reacts with Hydrocarbons generating volatile byproducts.
43 PARTICLE ACCELERATORS↗
Plasma and radiation detection via fiber interferometry
Photonic Doppler velocimetry tracks motion during high-speed, single-event experiments using telecommunication fiber components. The same technology can be applied in situations where there is no actual motion, but rather a change in the optical path length. Migration of plasma into vacuum alters the refractive index near a fiber probe, while intense radiation modifies the refractive index of the fiber itself. Lastly, these changes can diagnose extreme environments in a flexible, time-resolved manner.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
AC compensation of 3D magnetic diagnostic signals in DIII-D and National Spherical Torus Experiment-Upgrade (NSTX-U) for real-time application
A time domain algorithm has been developed to remove the vacuum pickup generated by both coil current (DC) and induced vessel current (AC) in real time from three dimensional (3D) magnetic diagnostic signals in the National Spherical Torus Experiment-Upgrade (NSTX-U) and DIII-D tokamaks. The possibility of detecting 3D plasma perturbations in real time is essential in modern and future tokamaks to avoid and control MHD instabilities. The presence of vacuum field pickup, due to toroidally asymmetric (3D) coils or to misalignment between sensors and axisymmetric (2D) coils, pollutes the measured plasma 3D field, making the detection of the magnetic field produced by the plasma challenging. Although the DC coupling between coils and sensors can be easily calculated and removed, the AC part is more difficult. Here, an algorithm based on a layered low-pass filter approach for the AC compensation and its application for DIII-D and NSTX-U data is presented, showing that this method reduces the vacuum pickup to the noise level. Comparison of plasma response measurements with and without vacuum compensation shows that accurate mode locking detection and plasma response identification require precise AC and DC compensations.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Transversely Excited Atmospheric CO{sub 2} Laser-Induced Plasma Spectroscopy for the Detection of Heavy Metals in Soil
A rapid detection of heavy metals in soil was presented by the metal-assisted gas plasma method using specific characteristics of a pulsed, transversely excited atmospheric (TEA) CO{sub 2} laser. The soil particles were placed in a hole made of acrylic plate. The sample was covered by a to prevent the soil particles from being blown off. The mesh also functioned to initiate a luminous plasma. When a TEA CO{sub 2} laser (1500 mJ, 200 ns) was focused on the soil sample, passing through the metal mesh, some of the laser energy was used to generate the gas plasma on the mesh surface, and the remaining laser energy was employed to ablate the soil particles. The fine, ablated soil particles moved into the gas plasma region to be dissociated and excited. Using this technique, analysis can be made with reduced sample pretreatment, and therefore a rapid analysis can be performed efficiently. The results proved that the signal to noise ratio (S/N) of the emission spectral lines is much better for the case of the present method (mesh method) compared to the case of standard laser-induced breakdown spectroscopy using the pellet method. Rapid detection of heavy metal elements in soil has been successfully carried out. The detection limits of Cu and Hg in soil were estimated to be 3 and 10 mg/kg, respectively. The present method has good potential for rapid and sensitive detection of heavy metals in soil samples.
54 ENVIRONMENTAL SCIENCES↗
Orthologs of human circulating miRNAs associated with hepatocellular carcinoma are elevated in mouse plasma months before tumour detection
Research examining the potential for circulating miRNA to serve as markers for preneoplastic lesions or early-stage hepatocellular carcinoma (HCC) is hindered by the difficulties of obtaining samples from asymptomatic individuals. As a surrogate for human samples, we identified hub miRNAs in gene co-expression networks using HCC-bearing C3H mice. We confirmed 38 hub miRNAs as associated with HCC in F2 hybrid mice derived from radiogenic HCC susceptible and resistant founders. When compared to a panel of 12 circulating miRNAs associated with human HCC, two had no mouse ortholog and 7 of the remaining 10 miRNAs overlapped with the 38 mouse HCC hub miRNAs. Using small RNA sequencing data generated from serially collected plasma samples in F2 mice, we examined the temporal levels of these 7 circulating miRNAs and found that the levels of 4 human circulating markers, miR-122-5p, miR-100-5p, miR-34a-5p and miR-365-3p increased linearly as the time approaching HCC detection neared, suggesting a correlation of miRNA levels with oncogenic progression. Estimation of change points in the kinetics of the 4 circulating miRNAs suggested the changes started 17.5 to 6.8 months prior to HCC detection. These data establish these 4 circulating miRNAs as potential sentinels for preneoplastic lesions or early-stage HCC.
60 APPLIED LIFE SCIENCES↗
Detection of trace contaminants released from rapidly heated pulsed power electrodes by laser diagnostics
Development of a capability to measure trace gas contaminants released from pulsed power electrodes would immediately impact Sandia pulsed power research. These releases occur during ultra-fast heating of metal electrodes during pulsed power discharges and can lead to substantial power losses through plasma formation. Detection of contaminants is a formidable challenge due to the need for in-situ spatially and temporally resolved measurements of trace gases in the extreme environment of ultra-fast heated metal surfaces. We investigate the feasibility of laser diagnostics for detecting contaminants, including H-atom, OH, and H 2 O. Laser-induced fluorescence and photofragmentation fluorescence showed significant plasma emission interferences and did not yield any detectable H-atom, OH, or H 2 O. Our newly developed H-atom detection using femtosecond degenerate four-wave mixing suppressed interferences and enabled detection of H-atoms. A few shots showed large signals in the near-surface region of metal foils, suggesting the formation of a wave of H-atoms from the metal.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗