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Presentation to be presented during the Site-Directed Research and Development (SDRD) FY 2021 review meeting (Webex), September 22–23, 2021.
Mars hosts various auroral processes despite the planet’s tenuous atmosphere and lack of a global magnetic field. To date, all aurora observations have been at ultraviolet wavelengths from orbit. We describe the discovery of green visible-wavelength aurora, originating from the atomic oxygen line at 557.7 nanometers, detected with the SuperCam and Mastcam-Z instruments on the Mars 2020 Perseverance rover. Near–real-time simulations of a Mars-directed coronal mass ejection (CME) provided sufficient lead-time to schedule an observation with the rover. The emission was observed 3 days after the CME eruption, suggesting that the aurora was induced by particles accelerated by the moving shock front. To our knowledge, detection of aurora from a planetary surface other than Earth has never been reported, nor has visible aurora been observed at Mars. This detection demonstrates that auroral forecasting at Mars is possible, and that during events with higher particle precipitation, or under less dusty atmospheric conditions, aurorae will be visible to future astronauts.
Systems and methods are disclosed for detecting a presence of a person in an area of coverage using radar. A transmitter can transmit radio signals in a first direction in an area of coverage defined by a wall and a floor. A receiver can receive the transmitted radio signals reflected back from the area of coverage. A signal conditioning circuit can process the received radio signals. One or more hardware processors can be programmed to analyze the processed radio signals and detect a presence of a person in the area of coverage based on the analysis. The analysis of the processed signals can be performed in both time and frequency domain. In addition to radar, an input from an infrared sensor can also be used in conjunction with radar based detection.
Scattered light imaging has revealed nearly a dozen circumstellar disks around young Herbig Ae/Be stars—enabling studies of structures in the upper disk layers as potential signs of ongoing planet formation. We present the first images of the disk around the variable Herbig Ae star PDS 201 (V* V351 Ori) and an analysis of the images and spectral energy distribution through 3D Monte Carlo radiative transfer simulations and forward modeling. The disk is detected in three data sets with the Large Binocular Telescope Interferometer/Large Binocular Telescope mid-infrared camera at the Large Binocular Telescope, including direct observations in the Ks and L′ filters, and an L′ observation with the 360° vector apodizing phase plate coronagraph. The scattered light disk extends to a very large radius of ∼250 au, which places it among the largest of such disks. Exterior to the disk, we establish detection limits on substellar companions down to ∼5 M {sub Jup} at ≳1.″5 (≳500 au), assuming the Baraffe et al. models. The images show a radial gap extending to ∼0.″4 (∼140 au at a distance of 340 pc) that is also evident in the spectral energy distribution. The large gap is a possible signpost of multiple high-mass giant planets at orbital distances (∼60–100 au) that are unusually massive and widely separated compared to those of planet populations previously inferred from protoplanetary disk substructures.
Waveform cross-correlation is a sensitive phase-matched filtering technique that can detect seismic events for nuclear explosion monitoring. However, there are outstanding challenges with correlation detectors, most notably a direct dependence on the completeness of the waveform template library. To ameliorate these challenges, we investigate how dynamic time warping (DTW) may make waveform correlation more robust. DTW analyzes the differences between two time series and attempts to “warp” one time series relative to another in a recursive manner. We apply DTW to synthetic earthquake and recorded explosion templates to expand the capability of correlation detectors. We explore what conditions (e.g., source, station distance, frequency bands) and/or DTW algorithms generate stronger correlation scores. We show that DTW performs well on noisy signals and can dramatically improve the cross-correlation coefficient between a template and data-stream waveform. We conclude with recommendations on how to utilize DTW in nuclear monitoring detection.
Recent studies have shown that dynamic nuclear polarization (DNP) can be used to detect 17 O solid-state NMR spectra of naturally abundant samples within a reasonable experimental time. Observations using indirect DNP, which relies on 1 H mediation in transferring electron hyperpolarization to 17 O, are currently limited mostly to hydroxyls. Direct DNP schemes can hyperpolarize non-protonated oxygen near the radicals; however, they generally offer much lower signal enhancements. In this study, we demonstrate the detection of signals from non-protonated 17 O in materials containing silicon. The sensitivity boost that made the experiment possible originates from three sources: indirect DNP excitation of 29 Si via protons, indirect detection of 17 O through 29 Si nuclei using two-dimensional 29 Si{ 17 O} D-HMQC, and Carr-Purcell-Meiboom-Gill refocusing of 29 Si magnetization during acquisition. This 29 Si-detected scheme enabled, for the first time, 2D 17 O– 29 Si heteronuclear correlation spectroscopy in mesoporous silica and silica-alumina surfaces at natural abundance. In contrast to the silanols showing motion-averaged 17 O signals, the framework oxygens exhibit unperturbed powder patterns as unambiguous fingerprints of surface sites. Furthermore, along with hydroxyl oxygens, detection of these moieties will help in gaining more atomistic-scale insights into surface chemistry.
The growing global concerns about the effects to public health from human exposure to per- and polyfluoroalkyl substances (PFAS) motivates the development of strategies for reliable monitoring of PFAS in environmental streams, as well as for their rapid, effective removal if detected. For the continuous PFAS monitoring, an inexpensive, field-deployable, in situ sensor is urgently needed; yet the prevalent in situ techniques often struggle to strike a balance between the practical sensitivity and selectivity demands of the real world. Similarly, for effective PFAS removal, strategies for their fast, selective, and quantitative capture are desired, yet the present commercially available sorbents are unable to meet the requirements of rapid, quantitative capture of all PFAS components, and are notably inefficient in removing the more toxic smaller chains. To address these twin challenges, Pacific Northwest National Laboratory is developing strategies for improved detection and remediation of PFAS. For the rapid, selective, quantitative removal of PFAS from environmental streams, the strategy relies on designing capture probes with exclusively tailored electronic and spatial affinities for the PFAS that are able to selectively capture them from environmental streams. For the in situ detection and quantification of PFAS in complex, multicomponent matrices such as groundwater, the approach relies on the targeted capture of specific PFAS by these PFAS-specific capture probes immobilized on a platform. The platform acts as an electrode to directly measure PFAS concentration through a proportional change in electrical response upon their capture. A combination of optimization of platform design and incorporation of additional, sensitive detection modalities have allowed us to achieve detection limits as low as 0.5 ng/L for detection of PFAS compounds (compared to the 70 ng/L Health Advisory Limit of the U.S. Environmental Protection Agency).
The growing global concerns about the effects to public health from human exposure to per- and polyfluoroalkyl substances (PFAS) motivates the development of strategies for reliable monitoring of PFAS in environmental streams, as well as for their rapid, effective removal if detected. For the continuous PFAS monitoring, an inexpensive, field-deployable, in situ sensor is urgently needed; yet the prevalent in situ techniques often struggle to strike a balance between the practical sensitivity and selectivity demands of the real world. Similarly, for effective PFAS removal, strategies for their fast, selective, and quantitative capture are desired, yet the present commercially available sorbents are unable to meet the requirements of rapid, quantitative capture of all PFAS components, and are notably inefficient in removing the more toxic smaller chains. To address these twin challenges, Pacific Northwest National Laboratory is developing strategies for improved detection and remediation of PFAS. For the rapid, selective, quantitative removal of PFAS from environmental streams, the strategy relies on designing capture probes with exclusively tailored electronic and spatial affinities for the PFAS that are able to selectively capture them from environmental streams. For the in situ detection and quantification of PFAS in complex, multicomponent matrices such as groundwater, the approach relies on the targeted capture of specific PFAS by these PFAS-specific capture probes immobilized on a platform. The platform acts as an electrode to directly measure PFAS concentration through a proportional change in electrical response upon their capture. A combination of optimization of platform design and incorporation of additional, sensitive detection modalities have allowed us to achieve detection limits as low as 0.5 ng/L for detection of PFAS compounds (compared to the 70 ng/L Health Advisory Limit of the U.S. Environmental Protection Agency). (authors)
The objective of this project is to design, develop, and evaluate scalable software to enhance resilience, data checkpointing, program restart, and analysis. The proposed tasks are to 1) develop scalable machine learning techniques to learn temporal change patterns in a scalable and in-situ manner, and to minimize data movement and maximize learning locally closest to data; 2) design a concise data representation and indexing mechanism to capture the distribution of changes in data that can guarantee point-wise user-defined tolerable errors while reducing the data storage requirements by an order of magnitude or more; 3) develop data reduction techniques as library modules; 4) exploit local SSD for minimizing data movement in storage hierarchy; 5) develop anomaly detection algorithms that can predict corruptions based on learning of emerging patterns; 6) develop software libraries to be incorporated within widely used data formats and APIs; and 7) evaluate the proposed software using DOE scientific applications. The outcomes of the proposed work are to satisfy many synergistic data reduction and resilience requirements for large-scale data intensive applications executed on extreme-scale computing systems. The developed mechanism for error-bound data approximation is directly applicable to existing scientific applications. Through machine learning from historical events and change distribution, this work will enable anomaly detection for DOE computer facility.
The design of supported heterogeneous catalysts requires a detailed understanding of the structure and chemistry of the active surface. Although the chemical components of the active phase, support material, and process feed are typically considered to be the most important factors governing catalyst structure and performance, many common commercial supports contain trace impurities, which can have profound effects on catalyst properties. In this work, we study silica–supported cobalt–based catalysts, which are widely used in syngas conversion to value–added products. Supported metallic Co is a commercial Fischer–Tropsch catalyst, whereas Co 2 C has shown promise for the direct conversion of syngas to higher oxygenates. This study examines the effects of Na, a commonly detected support impurity and a frequently used promoter, on the structure and reactivity of Co and Co 2 C. We show that trace Na impurities significantly decrease catalyst activity of supported metallic Co, and that high Na concentrations result in Co 2 C formation and a loss in Fischer–Tropsch activity. However, in Co 2 C catalysts, Na plays an important role in stabilizing the Co 2 C phase, but excess Na decreases catalyst activity. We use insitu X–ray absorption spectroscopy to study Co 2 C formation and decomposition in the Na–free catalyst under carburization and reaction conditions. Lastly, the work reveals the importance of carefully controlling alkali metal content, particularly at trace levels, in catalyst design.
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Formulation control is key to achieving consistent target properties of energetic materials, as feedstock variations and slight deviations in the ratios of different ingredients can have major effects on final product properties, particularly in dense pastes with high particle loading >65 vol.%. In large‐scale operations, it is imperative to either correct or remove batches of material that perform outside baseline property specifications as early as possible to avoid unnecessary processing of suboptimal material. Quality monitoring is the practice of measuring material properties during processing using process analytical technologies as opposed to only testing the properties of the final product; it is a key principle in the quality‐by‐design frameworks used for designing formulations and manufacturing processes. Herein, a process analytical technology method for correlating material properties of dense pastes directly after mixing in a Resonant Acoustic Mixer to motor data is developed and used to detect differences in the particle content of dense paste formulations. This method was also capable of detecting variations in powder feedstock properties, such as particle packing efficiency, and is sensitive enough to detect changes of 2 wt.% in the total solids content of the formulation. The techniques presented herein show excellent promise for use as a process analytical technology capable of quantifying formulation effects on material movement modes during resonant acoustic mixing.
Cosmological domain walls can be formed as a result of symmetry breaking at any epoch during the evolution of our universe. We study their interaction with a classical macroscopic object, like Earth or a satellite in Earth’s orbit. We set up an action that includes the interaction term between the massive classical object and the scalar field that the domain wall is made of. We use numerical calculations to solve the coupled equations of motion which describe the crossing between the domain wall and the classical object. Depending on the strength of the interaction, relative velocity and size, the object can be either stopped by the wall, or it can pass through it inducing deformations in the wall that cost energy. At the same time, the coupling to the scalar filed might change the object’s mass during the crossover. The fact that satellites in Earth’s orbit (or planets in Sun’s orbit) can change their mass and/or lose energy interacting with walls can be used as a new domain wall detection probe. For example, a typical velocity precision of a satellite is about 0.5 mm/s, which directly puts an upper limit on its mass change to ΔM/M ≲ 5 × 10 –17 . Alternatively, a known satellite flyby anomaly can easily be explained as an interaction with a closed domain wall. We also show that the presence of matter modifies the scalar filed potential and can locally create a bubble of the true vacuum, and thus trigger the decay of the false vacuum. For a critical bubble which is able to expand, such an interaction with the domain wall must be strong enough.
The BICEP/Keck (BK) experiment aims to detect the imprint of primordial gravitational waves in the cosmic microwave background polarization, which would be direct evidence of the inflation theory. While the tensor-to-scalar ratio has been constrained to be $r_{0.05}<0.06$ at 95% c.l., further improvements on this upper limit are hindered by polarized galactic foreground emissions and removal of gravitational lensing polarization. The 30/40 GHz receiver of the BICEP Array (BA) will deploy at the end of 2019 and will constrain the synchrotron foreground with unprecedented accuracy within the BK sky patch. We will show the design of the 30/40 GHz detectors and test results summarizing its performance. The low optical and atmospheric loading at these frequencies requires our TES detectors to have low saturation power in order to be photon noise dominated. To realize the low thermal conductivity required from a 250 mK base temperature, we developed new bolometer leg designs. We will present the relevant measured detector parameters: $G, T_c, R_n, P_{sat}$, and spectral bands, and noise spectra. We achieved a per bolometer NEP including all noise components of 2.07×10 -17 W/$\sqrt{Hz}$, including an anticipated photon noise level 1.54×10 -17 W/$\sqrt{Hz}$.
Auger recombination in semiconductors is a many-body phenomenon in which the recombination of electrons and holes is accompanied by excitation of other charge carriers. The excess energy of the excited carriers is normally rapidly converted to heat, making Auger processes difficult to probe directly. In this paper, we employ a technique in which the Auger-excited carriers are detected by their ability to tunnel out of the semiconductor through a thin barrier, generating a current. We use vertical van der Waals heterostructures with monolayer WSe 2 as the semiconductor, with hexagonal boron nitride as the tunnel barrier, and a graphite collector electrode. The Auger processes combined with resonant absorption produce characteristic negative photoconductance. We detect holes Auger-excited by both neutral and charged excitons and find that the Auger scattering is surprisingly strong under weak excitation. Our work expands the range of techniques available for probing relaxation processes in 2D materials.
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The cross-field transport in the scrape-off-layers (SOLs) and divertors in tokamaks is of a similar size to the poloidal component of the parallel flow, thereby significantly impacting the plasma transport there. However, its direct observation has been challenging because the drift velocity (102–103 m/s) is significantly below the detection limit of conventional diagnostics. To realize cross-field ion flow measurement, a variety of systematic uncertainties in the system must be narrowed down. Here, we develop a conceptual design of the Doppler spectrometry that enables us to measure the impurity flows with 102-m/s accuracy based on an in situ wavelength-calibration technique developed in the astrophysics field, the iodine-cell method. We discuss its properties and applicability. In particular, the scaling relation between wavelength accuracy and various spectroscopic parameters is newly presented, which suggests the high importance of the wavelength resolution of the system. Based on transport simulations for the JT-60SA divertor, the feasibility of the system is assessed.
Abstract General structural properties and low surface brightness tidal features hold important clues to the formation of galaxies. In this paper, we study a sample of polar-ring galaxies (PRGs) based on optical imaging from the Sloan Digital Sky Survey Stripe 82 and other deep surveys. We investigate the deepest images of candidates for PRGs to date. We carry out photometric decomposition on the host galaxies and associated polar structures that allows us to derive the structural properties of both components. We are able to detect very faint tidal structures around most PRGs in our sample. For several galaxies, we can directly observe the formation of the polar ring due to merging, which is manifested in debris of the victim galaxy and an arc-like polar structure made up of its material. In a few cases, we can discern signs of tidal accretion. The results obtained indicate that the gravitational interaction and merging of galaxies are the most plausible mechanisms for the formation of PRGs.