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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Development of Control System Functional Capabilities within the IES Plug-and-Play Simulation Environment

The concept of an Integrated Energy System (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. A new RAVEN (Risk Analysis Virtual ENvironment) plugin for grid and capacity optimization (HERON) has been developed for optimizing the production variables of the IES given the demand profile. Currently, only the limits that affect the production variables and their corresponding time rates of change are considered (explicit constraints). However, other variables are additionally subject to constraints, but the associated limits are not accounted for (implicit constraints). In particular, for the power dispatch problem, the optimization algorithm takes into account the limits on the electrical power output and the corresponding hourly power variations but does not consider other constraints on process variables whose response effects the service life of the IES. This report describes a scheme that allows accounting for implicit constraints without increasing the size of the optimization problem. The Reference Governor (RG) algorithm is traditionally used for enforcing state and control constraints by modifying the set-point trajectories supplied to the feedback regulators. In our application, the RG is coupled within an iterative loop with the HERON-power dispatcher to generate optimal trajectories that ensure the operational constraints are met. A data-driven procedure to derive a representation of the dynamics of the controlled system was developed. First, the variables that represented the state of the system are selected (PCA-based approach), and then state-space representation matrices are derived from the collected measurements (DMDc algorithm). A preliminary version of the developed workflow based on Linear Time Invariant matrices was assessed by adopting a two-unit test case. More sophisticated versions of this workflow foreseeing the on-line derivation of system matrices will be deployed in FY 2021. Finally, a “plug-and-play” library of controllers and state observers was developed in Dymola. Some aspects of the current configuration of the IES unit components, e.g., the encapsulation of the control schemes into dedicated blocks, are consistent with the “plug-and-play” philosophy. Other features, e.g., the system buses collecting the input and the output variables, are not. For this reason, once listed and described the limits of the current configuration, necessary modifications to the plant model interface are presented. As a test-case, the interfaces of the SES model in the RAVEN-based HYBRID framework were reworked accordingly, and two different control schemes were applied to the same plant model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Distributed non-negative matrix factorization with determination of the number of latent features

The holistic analysis and understanding of the latent (that is, not directly observable) variables and patterns buried in large datasets is crucial for data-driven science, decision making and emergency response. Such exploratory analyses require devising unsupervised learning methods for data mining and extraction of the latent features, and non-negative matrix factorization (NMF) is one of the prominent such methods. NMF is based on compute-intense non-convex constrained minimization, which, for large datasets requires fast and distributed algorithms. However, current parallel implementations of NMF fail to estimate the number of latent features. In practice, identifying these features is both difficult and significant for pattern recognition and latent feature analysis, especially for large dense matrices. Here, we introduce a distributed NMF algorithm coupled with distributed custom clustering followed by a stability analysis on dense data, which we call DnMFk, to determine the number of latent variables. The results on synthetic data and the classical Swimmer data set demonstrate the accuracy of model determination while scaling nearly linearly across multiple processors for large data. Further, we employ DnMFk to determine the number of hidden features from a terabyte matrix.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Vertical Architecture Solution-Processed Quantum Dot Photodetectors with Amorphous Selenium Hole Transport Layer

Colloidal quantum dots (CQDs) provide wide spectral tunability and high absorption coefficients owing to quantum confinement and large oscillator strengths, which along with solution processability, allow a facile, low-cost, and room-temperature deposition technique for the fabrication of photonic devices. However, many solution-processed CQD photodetector devices demonstrate low specific-detectivity and slow temporal response. To achieve improved photodetector characteristics, limiting carrier recombination and enhancing photogenerated carrier separation are crucial. In this study, we develop and present an alternate vertical-stack photodetector wherein we use a solution-processed quantum dot photoconversion layer coupled to an amorphous selenium (a-Se) wide-bandgap charge transport layer that is capable of exhibiting single-carrier hole impact ionization and is compatible with active-matrix readout circuitry. This a-Se chalcogenide transport layer enables the fabrication of high-performance and reliable solution-processed quantum dot photodetectors, with enhanced charge extraction capabilities, high specific detectivity (D* ~ 0.5–5 × 10 12 Jones), fast 3 dB electrical bandwidth (3 dB BW ~ 22 MHz), low dark current density (J D ~ 5–10 pA/cm 2 ), low noise current (i n ~ 20–25 fW/Hz 1/2 ), and high linear dynamic range (LDR ~130–150 dB) across the measured visible electromagnetic spectrum (~405–656 nm).

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Oxaliplatin–DNA Adducts as Predictive Biomarkers of FOLFOX Response in Colorectal Cancer: A Potential Treatment Optimization Strategy

FOLFOX is one of the most effective treatments for advanced colorectal cancer (CRC). However, cumulative oxaliplatin neurotoxicity often results in halting the therapy. Oxaliplatin functions predominantly via the formation of toxic covalent drug-DNA adducts. We hypothesize that oxaliplatin-DNA adduct levels formed in vivo in peripheral blood mononuclear cells (PBMC) are proportional to tumor shrinkage caused by FOLFOX therapy. We further hypothesize that adducts induced by sub-therapeutic "diagnostic microdoses" are proportional to those induced by therapeutic doses and are also predictive of response to FOLFOX therapy. These hypotheses were tested in CRC cell lines and a pilot clinical study. Four CRC cell lines were cultured with therapeutically relevant (100 µM) or diagnostic microdose (1 µM) concentrations of [ 14 C]oxaliplatin. The C-14 label enabled quantification of oxaliplatin-DNA adduct level with accelerator mass spectrometry (AMS). Oxaliplatin-DNA adduct formation was correlated with oxaliplatin cytotoxicity for each cell line as measured by the MTT viability assay. Six CRC patients received by IV a diagnostic microdose containing [ 14 C]oxaliplatin prior to treatment, as well as a second [ 14 C]oxaliplatin dose during FOLFOX chemotherapy, termed a "therapeutic dose." Oxaliplatin-DNA adduct levels from PBMC correlated significantly to mean tumor volume change of evaluable target lesions (5 of the 6 patients had measurable disease). Finally, oxaliplatin-DNA adduct levels were linearly proportional between microdose and therapeutically relevant concentrations in cell culture experiments and patient samples, as was plasma pharmacokinetics, indicating potential utility of diagnostic microdosing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations

Abstract. Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first time, how model-simulated INP concentrations compare with year-round INP measurements during the Macquarie Island Cloud Radiation Experiment (MICRE) campaign from 2017–2018. We simulate immersion-mode INP concentrations using the Energy Exascale Earth System Model version 1 (E3SMv1) by combining simulated aerosols with recently developed deterministic INP parameterizations and the native classical nucleation theory (CNT) for mineral dust in E3SMv1. Because MICRE did not collect aerosol measurements of super-micron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and overestimates sea spray aerosol concentrations by 1 to 2 orders of magnitude for most of the high-latitude sites in the Southern Hemisphere. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 d) and processed offline using the Colorado State University ice spectrometer (IS) in immersion freezing mode. We find that when deterministic parameterizations for both dust and sea spray INPs are used, simulated INPs are within a factor of 10 of observed INPs more than 60 % of the time during summer. Our results also indicate that the E3SM's current treatment of mineral dust immersion freezing in the SO is impacted by compensating biases – an underprediction of dust amount was compensated by an overprediction of its effectiveness as INPs. We also perform idealized droplet freezing experiments to quantify the implications of the time-dependent behavior assumed by the E3SM's CNT-parameterization and compare with the ice spectrometer observations. We find that the E3SM CNT 10 s diagnostic used in this study is a reasonable approximation of the exact formulation of CNT, when applied to ice spectrometer measurements in low-INP conditions similar to Macquarie Island. However, the linearized 10 s diagnostic underestimates the exact formula by an order of magnitude or more in places with high-INP conditions like the Sahara. Overall, our findings suggest that it is important to correct the biases in E3SM's simulated dust life cycle and update E3SM's INP parameterizations. INP prediction errors of 2 to 3 orders of magnitude can have considerable impacts on the simulated cloud and radiative properties in global climate models. On comparing INP concentrations during MICRE against ship-based campaigns, Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) and Antarctic Circumnavigation Expedition (ACE), we find that INPs from the latter are significantly higher only in regions closer to Macquarie Island. This alludes to the fact that physical, chemical and biological processes affecting INP concentrations as stimulated by the island could be partly responsible for the high INP concentrations observed at Macquarie Island during the MICRE campaign. Therefore, improvements to both aerosol simulation and INP parameterizations are required to adequately simulate INPs and their cloud impacts in E3SM. It will be helpful to include a parallel measurement of the size-resolved aerosol composition and explore opportunities for long-term measurement platforms in future field campaigns studying INP sources in remote marine regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Unbalancing Symbiotic Nitrogen Fixation: Can We Make Effectiveness More Effective?

One of the most critical uses of carbon fuels is in generating nitrogen fertilizer. Atmospheric dinitrogen is too stable to be used directly by plants, so plants need other chemical forms of nitrogen. Nitrogen fertilizer production uses ~4% of the world’s natural gas. Making N fertilizers leverages methane’s energy content by enabling additional energy to be captured into food and fiber through increased photosynthesis. Manufacturing fertilizer is essential—without it there would only be enough combined nitrogen to feed ~3 billion of the world’s ~7 billion people. How to alter this addiction is not obvious, but the best chance to secure substantial and sustainable amounts of future N might be through symbiotic nitrogen fixation (SNF). SNF describes mutualistic interactions where nitrogen-fixing bacteria provide fixed nitrogen to their plant hosts, freeing them from the need for nitrogen fertilizers. SNF already occurs on a large scale; "biological nitrogen” contributes about 5 Tg N/yr to American agriculture, a quarter of the nitrogen needed. Improving SNF and replacing inorganic fertilizers are both important goals in establishing sustainable and more energy-efficient farming. SNF has been used in agriculture for millennia, largely by using legumes like beans or alfalfa in mixed cropping systems. Legume SNF occurs in root nodules, organs that develop after a growing root is infected by bacteria called rhizobia. In the plant cells of a legume nodule, specialized forms of rhizobia fix nitrogen and can produce enough ammonia to supply the growing plant. The exchange of photosynthetically derived plant carbon compounds for nitrogen reduced by the bacteria is the engine that drives the symbiosis. Important details about the organization of development and metabolism in SNF remain to be determined, such as how plant and bacterial metabolism are coordinated as nitrogen is being fixed and what governs the overall level of nitrogen fixation. Most bacterial mutations that affect SNF completely block fixation (e.g. are Fix – ), providing a limited window into the feedback interactions that must be part of the process. We have investigated an unusual mutant of Sinorhizobium meliloti, a symbiotic partner of alfalfa, that fixes dinitrogen at a normal rate (i.e., it is Fix + ) but is not effective in supporting plant growth (i.e., it is ineffective or Eff – ). We have shown that the mutant has a specific mutation in the glnD gene, which codes for a protein that regulates the bacterial response to nitrogen stress, among other key pathways. A Fix + Eff – phenotype contains an unavoidable puzzle—how is it possible for the bacteria to fix nitrogen at a normal rate and without benefiting the nitrogen starved plant host? After eliminating other possibilities, we proposed that the bacteria synthesize a nitrogen-containing compound that the plant can’t use so that acquiring this compound does not relieve plant nitrogen stress. Extracts of nodules made by glnD mutant strains have high concentrations of pyruvate canaline oxime (PCO), a derivative of the plant defensive compound canaline, a toxic analog of ornithine, an amino acid. Many legumes produce canaline and the related arginine mimic canavanine. For reasons we do not yet understand, the mutation in glnD appears to trigger significant overproduction of canaline in a defense response that leads to substantial synthesis of PCO. We expected the bacteria to be able to use PCO, but we have not been able to grow S. meliloti on PCO under several conditions. PCO thus appears to be a metabolic dead end for both the plant and bacteria. We also examined bacterial catabolic pathways that degrade arginine and canavanine and showed that mutation of these did not alter the symbiosis in an obvious way. In related experiments to examine the metabolic development of root nodules, we carried out an ambitious experiment to simultaneously measure metabolites and protein changes during nodule maturation. For these experiments we used a related symbiotic interaction between S. medicae and Medicago truncatula. M. truncatula has a simpler genome than alfalfa so we could identify plant proteins based on predictions from the DNA sequence. Nodules formed on Medicago grow linearly, with the least mature tissues at the tip. Because development of nitrogen fixation is accompanied by the production of the pigmented plant oxygen carrier protein leghemoglobin, we were able to locate and manually separate the tip, transitional, and mature nitrogen-fixing regions from each other. Advances in proteomic and metabolomic techniques allowed us to analyze these tissues from a pool of as few as 10 nodules. We observed correlated transitions of various enzymes in the plant and bacterial proteomes from those characteristic of free-living metabolism to the microaerobic metabolism of the nitrogen-fixing tissues. The metabolome could not be separated into plant and bacterial domains but was consistent with this overall transition. A subsequent paper examined proteolysis in nodule bacteria. Protein turnover in mature regions of the nodule is significant. We were able to show complexes between various proteins and important proteases, using precipitation capture techniques to isolate the proteases and sensitive proteomic analysis to reveal the associated proteins.

09 BIOMASS FUELS↗
DOE OSTI2026

Hydrogen Analysis by Gas Chromatography–Mass Spectrometry

The detection of hydrogen in complex gas mixtures is essential for many applications. Conventional approaches such as gas chromatography (GC) with thermal conductivity detection (TCD) and residual gas analyzers (RGAs) face significant limitations: TCD exhibits poor response when helium is used as a carrier gas, whereas RGAs lack chromatographic separation, preventing reliable quantification of hydrogen because of interference from other species. Traditional GC methods rely on dual-column configurations with packed or molecular-sieve porous layer open tubular (PLOT) columns to separate hydrogen from O2, N2, CO, CO2, CH4, and other hydrocarbons, increasing system complexity and limiting compatibility with mass spectrometry (MS) detection. In this work, we developed and validated a robust GC–MS method capable of directly detecting and quantifying hydrogen using electron ionization (EI) without dopants, reagent gases, or ion–molecule reaction schemes. By integrating a modified EI source and a cryogenically cooled single capillary column configuration, we achieved baseline separation of hydrogen from all major permanent gases and hydrocarbons in a refinery gas mixture using helium as the carrier gas. The method demonstrated excellent linearity, high sensitivity, and exceptional reproducibility. Adjustable sample-loop volumes and split ratios enabled optimization of peak shape and signal-to-noise performance for trace-level and percent-level hydrogen concentrations. Beyond hydrogen quantitation, the method provides simultaneous compositional profiling of other gases in a mixture in a single run, making it valuable for a wide range of tasks.

Lobodin, Vlad [ORNL]↗
DOE OSTI2021

Breeding latitude is associated with the timing of nesting and migration around the annual calendar among Purple Martin (Progne subis) populations

Timing is critical for species that migrate seasonally, as timing mismatches can lead to reduced reproductive success and population declines. We investigated the effect of breeding latitude on the migration timing of a long-distance migratory songbird (Purple Martin, Progne subis subis) by using light-level geolocators deployed across breeding sites between 26° and 53° latitude (n = 329). We used nesting data (1st egg dates; n=28,165) to explore latitudinal patterns in the timing of breeding. Using generalized linear mixed models (GLMMs) we found that breeding latitude was highly associated with timing around the calendar, explaining population-level timing across both spring and fall migration. Populations breeding at more northern latitudes migrated later in fall (mean days/degree latitude =2), in spring (mean days/degree latitude =3), and nested later (days/degree latitude = 3) than populations breeding at more southern latitudes. Generalized additive mixed models (GAMMs) revealed significant non-linearity between breeding latitude and spring and fall migration timing, and the timing of nesting. In spring, the most northern breeders (> 40 degrees N) were more synchronous in their timing, departing their nonbreeding sites and arriving earlier at their breeding sites relative to their breeding latitude. These most northern breeders also had similar nest timing and fall migration departure timing. Breeding latitude was also associated with seasonal partitioning of migratory and sedentary periods. The most northern breeders spent 10% more time on fall migration, 2% more at wintering grounds, 1% more on spring migration, and 13% less time at their breeding sites. Our results support the notion that selection for timing at breeding latitudes can have year-round effects on the timing of seasonal events in long-distance migratory songbirds. Future studies should examine whether these timing patterns associated with latitude limit phenotypic responses to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Selected Negative Linear Compressibilities in the Metal–Organic Framework of [Cu(4,4'-bpy) 2 (H 2 O) 2 ]·SiF 6

Negative linear compressibility (NLC) is a rare high-pressure observation that lattice contraction is accompanied by the structural expansion along a specific direction. Generally, this counterintuitive phenomenon only derives from the intrinsic structural characteristics of materials and cannot be tuned by external perturbations. Searching for an effective method to control NLC effect is still a challenge in both chemical and material science. In this work, we successfully discover and select the NLC behaviors in the metal-organic framework (MOF) of [Cu(4,4'-bpy) 2 (H 2 O) 2 ]·SiF 6 (Cu(bpy)·SiF) through controlling the pressure conditions therein. The NLC effect of Cu(bpy)·SiF originates from the wine-rack mechanism that quasi-square grids transfer to rhombic ones with the structural expansion along the diagonal direction at high pressure. Meanwhile, both of the pressure range and magnitude of the NLC responses are enlarged with optimized pressure conditions. This study not only presents the intriguing selected NLC behaviors of a MOF but also proves the effects of pressure conditions on NLC, which offers promising strategies for further design and applications of NLC materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Measuring nonlinearities of a cantilever beam using a low-cost efficient wireless intelligent sensor for strain (LEWIS-S)

In the context of experimental vibration data, strain gauges can obtain linear and nonlinear dynamic measurements. However, measuring strain can be disincentivizing and expensive due to the complexity of data acquisition systems, lack of portability, and high costs. This research introduces the use of a low-cost efficient wireless intelligent sensor for strain (LEWIS-S) that is based on a portable-sensor-design platform that streamlines strain sensing. Additionally, the softening behavior of a cantilever beam with geometric and inertial nonlinearities is characterized by the LEWIS-S based on high force level inputs. Two experiments were performed on a nonlinear cantilever beam with measurements obtained by the LEWIS-S sensor and an accelerometer. First, a sine sweep test was performed through the fundamental resonance of the system, then a ring-down test was performed from a large initial static deformation. Good agreement was revealed in quantities of interest such as frequency response functions, the continuous wavelet transforms, and softening behavior in the backbone curves.

42 ENGINEERING↗
DOE OSTI2021

Flow-driven spectral chaos (FSC) method for simulating long-time dynamics of arbitrary-order non-linear stochastic dynamical systems

Uncertainty quantification techniques such as the time-dependent generalized polynomial chaos (TD-gPC) use an adaptive orthogonal basis to better represent the stochastic part of the solution space (aka random function space) in time. However, because the random function space is constructed using tensor products, TD-gPC-based methods are known to suffer from the curse of dimensionality. Here, we introduce a new numerical method called the flow-driven spectral chaos (FSC) which overcomes this curse of dimensionality at the random-function-space level. The proposed method is not only computationally more efficient than existing TD-gPC-based methods but is also far more accurate. The FSC method uses the concept of enriched stochastic flow maps to track the evolution of a finite-dimensional random function space efficiently in time. To transfer the probability information from one random function space to another, two approaches are developed and studied herein. In the first approach, the probability information is transferred in the mean-square sense, whereas in the second approach the transfer is done exactly using a new theorem that was developed for this purpose. The FSC method can quantify uncertainties with high fidelity, especially for the long-time response of stochastic dynamical systems governed by ODEs of arbitrary order. Six representative numerical examples, including a nonlinear problem (the Van-der-Pol oscillator), are presented to demonstrate the performance of the FSC method and corroborate the claims of its superior numerical properties. Finally, a parametric, high-dimensional stochastic problem is used to demonstrate that when the FSC method is used in conjunction with Monte Carlo integration, the curse of dimensionality can be overcome altogether.

(nonlinear) stochastic dynamical systems↗
DOE OSTI2021

Correlated Response of Protein Side-Chain Fluctuations and Conformational Entropy to Ligand Binding

The heterogeneous fast side-chain dynamics of proteins plays crucial roles in molecular recognition and binding. Site-specific NMR experiments quantify these motions by measuring the model-free order parameter (O axis 2 ) on a scale of 0 (most flexible) to 1 (least flexible) for each methyl-containing residue of proteins. In this work, we have examined ligand-induced variations in the fast side-chain dynamics and conformational entropy of calmodulin (CaM) using five different CaM–peptide complexes. O axis 2 of CaM in the ligand-free (O axis,U 2 ) and ligand-bound (O axis,B 2 ) states are calculated from molecular dynamics trajectories and conformational energy surfaces obtained using the adaptive biasing force (ABF) method. ΔO axis 2 = O axis,B 2 – O axis,U 2 follows a Gaussian-like unimodal distribution whose second moment is a potential indicator of the binding affinity of these complexes. The probability for the binding-induced O axis,U 2 → O axis,B 2 transition decreases with increasing magnitude of ΔO axis 2 , indicating that large flexibility changes are improbable for side chains of CaM after ligand binding. A linear correlation established between ΔOaxis2 and the conformational entropy change of the protein makes possible the determination of the conformational entropy of binding of protein–ligand complexes. The results not only underscore the functional importance of fast side-chain fluctuations but also highlight key motional and thermodynamic correlates of protein–ligand binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A New Plasma Radar Concept for Simultaneous Magnetic and Density Measurements

An innovative, compact 288GHz interferometer has been fabricated, tested, installed and successfully demonstrated on the LAPD-U magnetized plasma at UCLA. The system takes advantage of frequency modulated (FM) radar techniques to deliver a compact heterodyne system. In addition, the reflected power from the source is taken advantage of to eliminate the need for additional quasi-optical components. Electron density in LAPD-U plasma has recently been increased substantially thereby requiring a higher frequency/shorter wavelength interferometer to avoid deleterious refractive effects. This system satisfies those needs. The system uses a 96GHz varactor tuned Gunn oscillator which passes to a passive tripler. This tripler has ~3% conversion efficiency. The 288GHz radiation is then coupled to free space using a so-called dual-mode or Pickett horn. The output 288GHz beam is then coupled to an aspheric lens manufactured from low-loss, high-density polyethylene. This lens is employed to collimate the emerging beam. Small axial adjustment of the lens position can also be used to create a slowly focusing beam so as to optimize the measured signal. In addition, up-down or side-to-side adjustment of the lens can be utilized to steer the beam vertically or horizontally – again to optimize alignment. The propagating beam passes through a beam splitter and then through a water-free, bubble-free fused quartz window into the LAPD-U vacuum vessel. The beam-splitter is a thin sheet of G10 which reflects a small fraction of the incident power (~5 %) towards a zero-bias detector optimized for the frequency range from 220 to 300GHz. Note that waveguides at this frequency have dimensions of ~0.9mm x 0.45mm and so have very large conductive losses. This drives the use of quasi-optical propagation. The detector requires no DC bias and is very responsive (> 1V/mW into 1MΩ). Radiation is coupled to the detector via a similar lens-horn arrangement used for the launch. This reflected beam acts as the local oscillator or reference millimeter-wave beam for the detector. The remainder of the launched source beam then enters the LAPD-U vacuum vessel and passes through the plasma at the mid-plane until reaching the opposing port which is closed off with an aluminum flange. This flange is used as a mirror to retroreflect the incident 288GHz beam back along its path. The retroreflected beam exits the input port but does NOT couple directly into the zero-bias detector. Instead, the majority of the return power continues towards the 288GHz source. As mentioned above the transmitted beam enters the source a second time. This would appear undesirable. However, at these frequencies multipliers are highly non-linear elements which results in a significant portion of the return beam (~20%) re-emerging from the multiplier and horn and then coupling via the G10 beam-splitter to the zero-bias detector. This approach eliminated the need for a second quasi-optical beam-splitter. The system is extremely compact measuring approximately 28 inches x 20 inches. The above did not explain how heterodyne operation was achieved. As mentioned above the Gunn oscillator is able to be varactor tuned. This allows a low voltage to be applied to control the operating frequency of the Gunn oscillator. During heterodyne operation a sawtooth shaped voltage is applied to the varactor at 750kHz using an 80MHz Arbitrary Waveform Generator (AWG). This voltage changes the Gunn frequency linearly during the up-sweep which is then reset abruptly at the sawtooth crash to be immediately followed by another linear sweep. Passage through the 288GHz multiplier triples the frequency change experienced by the electromagnetic wave. These frequency changes are small – tens of megahertz. This FM radar approach results in the launched electromagnetic wave frequencies at the detector for the reference and plasma wave to be different. The approximately 10 ns delay propagation delay for the plasma beam results in the local oscillator and plasma beams NOT having an identical frequency – there is in fact a fixed difference frequency. The frequency tuning level of the Gunn oscillator is then adjusted so that there is ONE cycle of this difference frequency during each linear ramp. During the sawtooth crash or downward re-sweep this one cycle replays in reverse but on a very fast timescale. The process then repeats. Low-pass filtering eliminates the fast re-sweep to leave a pure sine wave heterodyne signal. When the plasma is present it introduces a phase delay in the sine wave (caused by the extremely small Doppler shift resulting from the optical path length change). Of course, to measure this phase change we need a reference. This is simply obtained from an arbitrary waveform generator which provides a synchronized output pulse train which again is low pass filtered to obtain a 750kHz sinusoidal voltage reference for the interferometer. The interferometer was installed on LAPD-U where it has worked reliably and has established that electron densities exceeding 1x10 13 cm -3 are routinely achieved. In addition, the system sensitivity was able to easily observe density fluctuation at frequencies up to 50kHz. FM Radar techniques have enabled a full demonstration of a compact, sensitive, high frequency (288GHz/1mm) heterodyne interferometer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Utility of anthesis–silking interval information to predict grain yield under water and nitrogen limited conditions

Delayed silking relative to pollen shed, measured as the anthesis–silking interval (ASI, the period between pollen shed and silking), is a good indicator of response to abiotic stresses in maize ( Zea mays L.). This research was conducted to investigate how ASI is affected by nitrogen (N) and water availability and to assess the utility of ASI to indirectly predict grain yield (GY) under contrasting water and N treatments. Two experiments were conducted in Hancock, WI, in 2018 and 2019. One experiment (Diverse hybrids) included 302 hybrids resulting from the cross of diverse inbred lines by a single tester evaluated at four different treatment levels resulting from combining nonlimited and low N with nonlimited and low water treatments. The second experiment (NSS FAC) included a set of 408 hybrids derived from the cross of biparental doubled-haploid lines from 13 factorial populations and evaluated under nonlimited and low N treatments. Anthesis and silk time in growing degree days, and GY (Mg ha -1 ) were measured. Genomic prediction was assessed using a genomic best linear unbiased prediction model, and predictive ability was calculated as the correlation between genomic predictions and adjusted means in the different treatments. Predictive ability ranged from .15 to .49 for NSS FAC and from .06 to .51 for Diverse hybrids across traits and treatments. The ASI was a good indicator of stress and showed higher heritability than GY in the limited treatments for both experiments; however, it did not improve yield predictability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Models of bars − II. Exponential profiles

ABSTRACT We present a new model for galactic bars with exponentially falling major axis luminosity profiles and Gaussian cross-sections. This is based on the linear superposition of Gaussian potential–density pairs with an exponential weight function, using an extension of the method originally introduced by Long & Murali. We compute the density, potential, and forces, using Gaussian quadrature. These quantities are given as explicit functions of position. There are three independent scaled bar parameters that can be varied continuously to produce bespoke bars of a given mass and shape. We categorize the effective potential by splitting a reduced parameter space into six regions. Unusually, we find bars with three stable Lagrange points on the major axis are possible. Our model reveals a variety of unexpected orbital structure, including a bifurcating x1 orbit coexisting with a stable x4 orbit. Propeller orbits are found to play a dominant role in the orbital structure, and we find striking similarities between our bar configuration and the model of Kaufmann & Contopoulos. We find a candidate orbital family, sired from the propeller orbits, that may be responsible for the observed high-velocity peaks in the Milky Way’s bar. As a cross-check, we inspect, for the first time, the proper motions of stars in the high-velocity peaks, which also match our suggested orbital family well. This work adds to the increasing body of evidence that real galactic bars may be supported at least partly by propeller orbits rather than solely by elliptical-like orbits of the x1 family.

McGough, D. P.↗
DOE OSTI2020

Unexpected Conformational Behavior of Poly(poly(ethylene glycol) methacrylate)-Poly(propylene carbonate)-Poly(poly(ethylene glycol) methacrylate) (PPEGMA-PPC-PPEGMA) Amphiphilic Block Copolymers in Micellar Solution and at the Air-Water Interface

Self-assemblies (bulk micelles and Langmuir monolayers) of a new amphiphilic block copolymer, poly(poly(ethylene glycol) methacrylate)-poly(propylene carbonate)-poly(poly(ethylene glycol) methacrylate) (PPEGMA-PPC-PPEGMA), were investigated in dilute aqueous solution and at the air-water interface. An important feature that distinguishes PPEGMA-PPC-PPEGMA from conventional linear PEG-based polymer surfactants is that in the hydrophilic PPEGMA block the PEG moieties exist as side chains attached to the poly(methacrylate) (PMA) backbone. This study was performed using three PPEGMA-PPC-PPEGMA samples having an identical PPC molecular weight (5.6 kDa) and different PPEGMA molecular weights (7.3, 2.8 and 2.1 kDa on either side) (named as “G7C6G7”, “G3C5G3”, and “G2C6G2”, respectively). Cryo-TEM images revealed that G2C6G2 micelles form large clusters, whereas G7C6G7 micelles exist as unimers; the behavior of G3C6G3 is intermediate. The average core surface distance between two adjacent G2C6G2 micelles in a cluster was estimated to be only about 3.7 nm, which suggests that in the micelle corona layer only the PEG side chains (but not the PMA backbone) exist as hydrated brush chains. A calculation showed that at the small micelle separation distance observed, the van der Waals attractive forces become significant, and are thus likely responsible for the cluster formation. Steady shear rheometry measurements confirmed that G2C6G2 micelles are indeed only weakly bound in clusters, and these micelle clusters are thus prone to breakup even under mild steady shear. The micelle breakup force estimated from the shear viscosity data is in reasonable agreement with an estimate obtained from the theoretical van der Waals interaction potential. Langmuir monolayers formed at the air-water interface by PPEGMA-PPC-PPEGMA were also characterized; surface pressure-area measurements were performed. Detailed features of the surface pressure-area isotherms further supported that only the PEG side chains are hydrated in the subphase, while the PMA backbone remains unhydrated and situated on the water surface.

Lee, Jaewon↗
DOE OSTI2022

Quantification of the effect of uncertainty on impurity migration in PISCES-A simulated with GITR

A Bayesian inference strategy has been used to estimate uncertain inputs to global impurity transport code (GITR) modeling predictions of tungsten erosion and migration in the linear plasma device, PISCES-A. This allows quantification of GITR output uncertainty based on the uncertainties in measured PISCES-A plasma electron density and temperature profiles (n e , T e ) used as inputs to GITR. The technique has been applied for comparison to dedicated experiments performed for high (4 × 10 22 m –2 s –1 ) and low (5 × 10 21 m –2 s –1 ) flux 250 eV He–plasma exposed tungsten (W) targets designed to assess the net and gross erosion of tungsten, and corresponding W impurity transport. The W target design and orientation, impurity collector, and diagnostics, have been designed to eliminate complexities associated with tokamak divertor plasma exposures (inclined target, mixed plasma species, re-erosion, etc) to benchmark results against the trace impurity transport model simulated by GITR. The simulated results of the erosion, migration, and re-deposition of W during the experiment from the GITR code coupled to materials response models are presented. Specifically, the modeled and experimental W I emission spectroscopy data for a 429.4 nm line and net erosion through the target and collector mass difference measurements are compared. Furthermore, the methodology provides predictions of observable quantities of interest with quantified uncertainty, allowing estimation of moments, together with the sensitivities to plasma temperature and density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

B56$δ$ long-disordered arms form a dynamic PP2A regulation interface coupled with global allostery and Jordan’s syndrome mutations

Intrinsically disordered regions (IDR) and short linear motifs (SLiMs) play pivotal roles in the intricate signaling networks governed by phosphatases and kinases. B56δ (encoded by PPP2R5D) is a regulatory subunit of protein phosphatase 2A (PP2A) with long IDRs that harbor a substrate-mimicking SLiM and multiple phosphorylation sites. De novo missense mutations in PPP2R5D cause intellectual disabilities (ID), macrocephaly, Parkinsonism, and a broad range of neurological symptoms. Our single-particle cryo-EM structures of the PP2A-B56δ holoenzyme reveal that the long, disordered arms at the B56δ termini fold against each other and the holoenzyme core. This architecture suppresses both the phosphatase active site and the substrate-binding protein groove, thereby stabilizing the enzyme in a closed latent form with dual autoinhibition. The resulting interface spans over 190 Å and harbors unfavorable contacts, activation phosphorylation sites, and nearly all residues with ID-associated mutations. Our studies suggest that this dynamic interface is coupled to an allosteric network responsive to phosphorylation and altered globally by mutations. Furthermore, we found that ID mutations increase the holoenzyme activity and perturb the phosphorylation rates, and the severe variants significantly increase the mitotic duration and error rates compared to the normal variant.

59 BASIC BIOLOGICAL SCIENCES↗