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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

New Global Electron Density Observations from GPS-RO in the D- and E-Region Ionosphere

A novel retrieval technique is developed for electron density (N(sub e)) in the D- and E-region (80-120 km) using the high-quality 50-Hz GPS radio occultation (GPS-RO) phase measurements. The new algorithm assumes a slow, linear variation in the F-region background when the GPS-RO passes through the D- and E-region, and extracts the N(sub e) profiles at 80-130 km from the phase advance signal caused by N(sub e). Unlike the conventional Abel function, the new approach produces a sharp N(sub e) weighting function in the lower ionosphere, and the N(sub e) retrievals are in good agreement with the IRI (International Reference Ionosphere) model in terms of monthly maps, zonal means and diurnal variations. The daytime GPS-RO N(sub e) profiles can be well characterized by the alpha-Chapman function of three parameters (N(sub mE), h(sub mE) and H), showing that the bottom of E-region is deepening and sharpening towards the summer pole. At high latitudes the monthly GPS-RO N(sub e) maps at 80-120 km reveal clear enhancement in the auroral zones, more prominent at night, as a result of energetic electron precipitation (EEP) from the outer radiation belt. The D-/E-region auroral N(sub e) is strongly correlated with K(sub p) on a daily basis. The new N(sub e) data allow further comprehensive analyses of the sporadic E (E(sub s)) phenomena in connection with the background N(sub e) in the E-region. The layered (2-10 km) and fluctuated (less than 2 km) E(sub s) components, namely N(sub e_Layer) than N(sub e_Pert), are extracted with respect to the background N( sub e_Region) on a profile-by-profile basis. The N(sub e_Layer) component has a strong but highly-refined peak at approximately 105 km, with an amplitude smaller than N(sub e_Region) approximately by an order of magnitude. The N(sub e_Pert) component, which was studied extensively in the past, is approximately 2 orders of magnitude weaker than N(sub e_Layer). Both N(sub e_Layer) and N(sub e_Pert) are subject to significant diurnal and semidiurnal variations, showing downward progression with local time in amplitude. The 11-year solar cycle dominates the N(sub e) interannual variations, showing larger N(sub e_Region) and N(sub e_Layer) but smaller N(sub e_Pert) amplitudes in the solar maximum years. Enhanced Ne profiles are often observed in the polar winter, showing good correlation with solar proton events (SPEs) and geomagnetic activity. The new methodology offers great potential for retrieving low N(sub e) in the D-region, where radio propagation and communication blackouts can occur due to enhanced ionization. For space weather applications it is recommended for GPSRO operations to raise the top of high-rate data acquisition to approximately 140 km in the future.

GSP-R↗
DOE OSTI2023

Functionalized Silicon Particles for Enhanced Half- and Full-Cell Cycling of Si-Based Li-Ion Batteries

Vinylene carbonate (VC) and polyethylene oxide (PEO) have been investigated as functional agents that mimic the solid electrolyte interphase (SEI) chemistry of silicon (Si). VC and PEO are known to contribute to the stability of Si-based lithium-ion batteries as an electrolyte additive and as a SEI component, respectively. In this work, covalent surface functionalization was achieved via a facile route, which involves ball-milling the Si particles with sacrificial VC and PEO. Thermogravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), and magic angle spinning nuclear magnetic resonance (MAS NMR) spectroscopy indicate that the additives are strongly bound to Si. In particular, MAS NMR shows Si–R or Si–O–R groups, which confirm functionalization of the Si after milling in VC or PEO. Particle size analysis by dynamic light scattering reveals that the additives facilitate particle size reduction and that the functionalized particles result in more stable dispersions based on zeta potential measurements. Raman mapping of the electrodes fabricated from the VC and PEO-coated active material with a polyacrylic acid (PAA) binder reveals a more homogenous distribution of Si and the carbon conductive additive compared to the electrodes prepared from the neat Si. Furthermore, the VC-milled Si strikingly exhibited the highest capacity in both half- and full-cell configurations, with more than 200 mAh g –1 measured capacity compared to the neat Si in the half-cell format. This is linked to an improved electrode processing based on the Raman and zeta potential measurements as well as a thinner SEI (with more organic components for the functionalized Si relative to the neat Si) based on XPS analysis of the cycled electrodes. In conclusion, the effect of binder was also investigated by comparing PAA with P84 (polyimide type), where an increased capacity is observed in the latter case.

25 ENERGY STORAGE↗
DOE OSTI2023

Evaluation of global teleconnections in CMIP6 climate projections using complex networks

In climatological research, the evaluation of climate models is one of the central research subjects. As an expression of large-scale dynamical processes, global teleconnections play a major role in interannual to decadal climate variability. Their realistic representation is an indispensable requirement for the simulation of climate change, both natural and anthropogenic. Therefore, the evaluation of global teleconnections is of utmost importance when assessing the physical plausibility of climate projections. We present an application of the graph-theoretical analysis tool δ-MAPS, which constructs complex networks on the basis of spatio-temporal gridded data sets, here sea surface temperature and geopotential height at 500 hPa. Complex networks complement more traditional methods in the analysis of climate variability, like the classification of circulation regimes or empirical orthogonal functions, assuming a new non-linear perspective. While doing so, a number of technical tools and metrics, borrowed from different fields of data science, are implemented into the δ-MAPS framework in order to overcome specific challenges posed by our target problem. Those are trend empirical orthogonal functions (EOFs), distance correlation and distance multicorrelation, and the structural similarity index. δ-MAPS is a two-stage algorithm. In the first place, it assembles grid cells with highly coherent temporal evolution into so-called domains. In a second step, the teleconnections between the domains are inferred by means of the non-linear distance correlation. We construct 2 unipartite and 1 bipartite network for 22 historical CMIP6 climate projections and 2 century-long coupled reanalyses (CERA-20C and 20CRv3). Potential non-stationarity is taken into account by the use of moving time windows. The networks derived from projection data are compared to those from reanalyses. Our results indicate that no single climate projection outperforms all others in every aspect of the evaluation. But there are indeed models which tend to perform better/worse in many aspects. Differences in model performance are generally low within the geopotential height unipartite networks but higher in sea surface temperature and most pronounced in the bipartite network representing the interaction between ocean and atmosphere.

58 GEOSCIENCES↗
DOE OSTI2020

A Lagrangian perturbation theory in the presence of massive neutrinos

We develop a Lagrangian Perturbation Theory (LPT) framework to study the clustering of cold dark matter (CDM) in cosmologies with massive neutrinos. We follow the trajectories of CDM particles with Lagrangian displacements fields up to third order in perturbation theory. Once the neutrinos become non-relativistic, their density fluctuations are modeled as being proportional to the CDM density fluctuations, with a scale-dependent proportionality factor. This yields a gravitational back-reaction that introduces additional scales to the linear growth function, which is accounted for in the higher order LPT kernels. Through non-linear mappings from Eulerian to Lagrangian frames, we ensure that our theory has a well behaved large scale behavior free of unwanted UV divergences, which are common when neutrino and CDM densities are not treated on an equal footing, and in resummation schemes that manifestly break Galilean invariance. We use our theory to construct correlation functions for both the underlying matter field, as well as for biased tracers using ConvolutionLPT. Redshift-space distortions effects are modeled using the Gaussian Streaming Model. When comparing our analytical results to simulated data from the Quijote 1 simulation suite, we find good accuracy down to r = 20 Mpc h -1 at redshift z = 0.5, for the real space and redshift space monopole particle correlation functions with no free parameters. The same accuracy is reached for the redshift space quadrupole if we additionally consider an effective field theory parameter that shifts the pairwise velocity dispersion. For modeling the correlation functions of tracers we adopt a simple Lagrangian biasing scheme with only density and curvature operators, which we find sufficient to reach down to r = 20 Mpc h -1 when comparing to simulated halos.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1992

Mars dust and cloud opacities and scattering properties

We have recently completed an analysis of the visible emission-phase function (EPF) sequences obtained with the solar-band channel of the Infrared Thermal Mapping (IRTM) instrument onboard the two Viking Orbiters. Roughly 100 of these EPF sequences were gathered during the 1977-1980 period, in which the total broadband (.3-3.0 microns) reflectances of the atmosphere/surface above specific locations on Mars were measured versus emission angle as the spacecraft passed overhead. A multiple scattering radiative transfer program was employed to model the EPF observations in terms of the optical depths of dust/clouds, their single scattering albedos and phase functions, and the Lambert albedos and phase coefficient of the underlying surfaces. Due to the predominance of atmospheric scattering at large atmospheric pathlengths and/or large dust opacities, we were able to obtain strong constraints on the scattering properties of dust/clouds and their opacities for a wide range of latitudes, longitudes, and seasons on Mars.

Clancy, R. T.↗
NASA NTRS2022

How to Build a Rover: An Overview of the Mars 2020 Mission’s Vehicle System Testbed

While NASA’s Mars rover Perseverance continues to make groundbreaking achievements on the Red Planet, its twin is hard at work here on Earth. The Operational Perseverance Twin for the Integration of Mechanisms and Instruments Sent to Mars, or OPTIMISM, is the Mars 2020 Vehicle System Testbed (VSTB) rover operated by NASA Jet Propulsion Laboratory (JPL) in Pasadena, California. OPTIMISM’s home is the JPL Mars Yard; an outdoor field with red soil that simulates the terrain encountered by Perseverance. The VSTB is a full-scale engineering model of the flight rover, serving a number of functions to ensure mission operations can continue smoothly and on schedule. The VSTB possesses instrumentation, computers, mechanisms, cameras, and a Mobility subsystem that are nearly identical to its extraterrestrial twin. Its high fidelity allows the rover to be a highly effective tool to fully test system functionality and performance prior to commanding the flight rover. The early stages of building OPTIMISM began a few months prior to Perseverance departing JPL for Cape Canaveral, FL in early 2020. Electrical integration of the flight system avionics, and compatibility checkouts of the electrical ground support equipment ensured that the foundation of the electrical system was operational and in place. Next, the internal harnessing was installed and compatibility checks of the rover instrumentation and mechanisms were performed to confirm the system was prepared for full buildup. Finally, mechanical assembly of the rover chassis with its external components completed the integration of the system before it was moved to the Mars Yard for its initial phase of testing to perform verification & validation (V&V) of the Mobility subsystem requirements. By the time Perseverance landed at Jezero Crater in February 2021, the first phase of VSTB operations was underway. Surface guidance, navigation, and control (SGNC) testing for the Mobility subsystem ensured functionality and performance requirements were met for various capabilities such as visual odometry (VO), mapping, and automatic navigation (AutoNav). Subsequent integration of the robotic arm (RA) onto the VSTB enabled the V&V campaign for surface sampling operations (SSO) to commence. As the mission’s engineering operations (EO) have gotten underway, the VSTB has been utilized for an array of purposes including troubleshooting software anomalies, and performing dry-runs for first time activities (FTAs) prior to sending the commands to Perseverance. OPTIMISM will continue to serve mission critical functions as long as Perseverance is roving the Red Planet.

Rojas, Jose Trujillo↗
DOE OSTI2021

Regolith, rock and fluid distributions at the Upper Colorado River Basin via a multicomponent seismic imaging approach

In October 2018, we conducted an exploratory seismic survey of the East River Watershed Function Science Focus Area, near Crested Butte, CO. Our survey goals were to map seismic bedrock, regolith and sediment properties and relate them to geomorphic and hydrologic processes. We acquired ~12 km of seismic data along roads with a 72-channel, 1.25m spaced streamer, an average shot spacing of 2.5m and an average acquisition rate of 3 km/day. We also obtained ~3km of planted geophone data with geophone and shot spacing between 2.5 and 5 meters and an acquisition rate of 0.5 km/day. Vp results show a sharp transition between regolith and bedrock along hillslopes suggesting a similarly abrupt change in porosity. Vp anisotropy in the Mancos Shale is observable in the lower reaches of the watershed, but is absent in regions near crystalline intrusions where contact metamorphism has likely modified pore structure within the shale. Alluvium thickness varies along the river axis from 0 to > 20 meters reflecting variations in depositional processes as function of stream gradient. We show that when strong discontinuities at the regolith base are present, inhomogeneous waves that travel along subsurface interfaces are generated and can be measured on vertical component geophones. We present a summary manuscript in the report appendix.

58 GEOSCIENCES↗
DOE OSTI2022

Path Integrals for Nonadiabatic Dynamics: Multistate Ring Polymer Molecular Dynamics

This review focuses on a recent class of path-integral-based methods for the simulation of nonadiabatic dynamics in the condensed phase using only classical molecular dynamics trajectories in an extended phase space. Specifically, a semiclassical mapping protocol is used to derive an exact, continuous, Cartesian variable path-integral representation for the canonical partition function of a system in which multiple electronic states are coupled to nuclear degrees of freedom. Building on this exact statistical foundation, multistate ring polymer molecular dynamics methods are developed for the approximate calculation of real-time thermal correlation functions. As a result, the remarkable promise of these multistate ring polymer methods, their successful applications, and their limitations are discussed in detail.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evaluation of riverbed magnetic susceptibility for mapping biogeochemical hot spots in groundwater‐impacted rivers

Abstract Redox hot spots occurring as metal‐rich anoxic groundwater discharges through oxic wetland and river sediments commonly result in the formation of iron (Fe) oxide precipitates. These redox‐sensitive precipitates influence the release of nutrients and metals to surface water and can act as ‘contaminant sponges’ by absorbing toxic compounds. We explore the feasibility of a non‐invasive, high‐resolution magnetic susceptibility (MS) technique to efficiently map the spatial variations of magnetic Fe oxide precipitates in the shallow bed of three rivers impacted by anoxic groundwater discharge. Laboratory analyses on Mashpee River (MA, USA) sediments demonstrate the sensitivity of MS to sediment Fe concentrations. Field surveys in the Mashpee and Quashnet rivers (MA, USA) reveal several discrete high MS zones, which are associated with likely anoxic groundwater discharge as evaluated by riverbed temperature, vertical head gradient, and groundwater chemistry measurements. In the East River (CO, USA), widespread cobbles/rocks exhibit high background MS from geological ferrimagnetic minerals, thereby obscuring the relatively small enhancement of MS from groundwater induced Fe oxide precipitates. Our study suggests that, in settings with low geological sources of magnetic minerals such as lowland rivers and wetlands, MS may serve as a complementary tool to temperature methods for efficiently mapping Fe oxide accumulation zones due to anoxic groundwater discharges that may function as biogeochemical hot spots and water quality control points in gaining systems.

Wang, Chen↗
DOE OSTI2020

Poincaré constraints on celestial amplitudes

The functional structure of celestial amplitudes as constrained by Poincare symmetry is investigated in 2, 3, and 4-point cases for massless external particles of various spin, as well as massive external scalars. Functional constraints and recurrence relations are found (akin to the findings in [24]) that must be obeyed by the respective permissible correlator structures and function coefficients. In specific three-point cases involving massive scalars the resulting recurrence relations can be solved, e.g., reproducing purely from symmetry a three-point function coefficient known in the literature. Additionally, as a byproduct of the analysis, the three-point function coefficient for gluons in Minkowski signature is obtained from an amplitude map to the celestial sphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

System risk quantification and decision making support using functional modeling and dynamic Bayesian network

Risk-informed decision-making requires a probabilistic assessment of the likelihood of success of control action, given the system status. This paper presents a systematic state transition modeling approach integrating dynamic probabilistic risk assessment with a decision-making process using a dynamic Bayesian network (DBN) coupled with functional modeling. A functional model designed with multilevel flow modeling (MFM) technique was used to build a system state structure inferred by energy, mass, and information flow so that one can verify the developed model with respect to system functionality. The MFM model represents the causal relationship among the nodes, which captures the structure of process parameters and control units. Each node may have multiple possible states, and the DBN structured by the MFM model represents the time-domain transitions among the defined states. Furthermore, the MFM-DBN integrated state transition modeling is a white-box approach that allows one to draw the system's risk profile by updating the system states and supports the decisions probabilistically with physical inference. An example of a simple heating system has been used to illustrate this process, including decision-making support based on quantitative risk profile. For demonstrating its applicability to a complex system operational decision making, a case study of station blackout accident scenario leading to the seal loss of coolant accident in a nuclear power plant is presented. The proposed approach effectively provided the risk profile along time for each option so that the operators can make the best decision, which minimizes the plant risk.

42 ENGINEERING↗
DOE OSTI2022

Atomic-Scale View of Redox Induced Changes for Monolayer MoO x on α-TiO 2 (110) with Chemical-State Sensitivity

Supported molybdenum oxide (MoO x ) plays an important role in catalytic transformations from alcohol dehydrogenation to transesterification. During these reactions, Mo and oxygen surface species undergo structural and chemical changes. A detailed, chemical-state specific, atomic-scale structural analysis of the catalyst under redox conditions is important for improving catalytic properties. In this study, monolayer of MoO x grown on α-TiO 2 (110) by atomic-layer deposition is analyzed by X-ray standing wave (XSW) excited X-ray photoelectron spectroscopy (XPS). The chemical shifts for Mo 2p 3/2 and O 1s peaks are used to distinguish Mo 6+ from Mo 4+ and surface O from bulk O. Excitation of XPS by XSW allows pin-pointing the location of these surface species relative to the underlying substrate lattice. Finally, measured 3D composite atomic density maps for the oxidized and reduced interfaces compare well with our density functional theory models, and collectively create a unique view of the redoxdriven dynamics for this complex catalytic structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering

Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency or even to unlock new catalytic activities not found in nature. Because the search space of possible proteins is vast, enzyme engineering usually involves discovering an enzyme starting point that has some level of the desired activity followed by directed evolution to improve its “fitness” for a desired application. Recently, machine learning (ML) has emerged as a powerful tool to complement this empirical process. ML models can contribute to (1) starting point discovery by functional annotation of known protein sequences or generating novel protein sequences with desired functions and (2) navigating protein fitness landscapes for fitness optimization by learning mappings between protein sequences and their associated fitness values. In this Outlook, we explain how ML complements enzyme engineering and discuss its future potential to unlock improved engineering outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Nanoscale visualization and spectral fingerprints of the charge order in ScV 6 Sn 6 distinct from other kagome metals

Charge density waves (CDWs) in kagome metals have been tied to many exotic phenomena. Here, using spectroscopic-imaging scanning tunneling microscopy and angle-resolved photoemission spectroscopy, we study the charge order in kagome metal ScV 6 Sn 6 . The similarity of electronic band structures of ScV 6 Sn 6 and TbV 6 Sn6 (where charge ordering is absent) suggests that charge ordering in ScV 6 Sn 6 is unlikely to be primarily driven by Fermi surface nesting of the Van Hove singularities. In contrast to the CDW state of cousin kagome metals, we find no evidence supporting rotation symmetry breaking. Differential conductance dI/dV spectra show a partial gap Δ 1 CO ≈ 20 meV at the Fermi level. Interestingly, dI/dV maps reveal that charge modulations exhibit an abrupt phase shift as a function of energy at energy much higher than Δ 1 CO , which we attribute to another spectral gap. Our experiments reveal a distinctive nature of the charge order in ScV 6 Sn 6 with fundamental differences compared to other kagome metals.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Galaxy properties as revealed by MaNGA – III. Kinematic profiles and stellar population gradients in S0s

ABSTRACT This is the third paper of a series where we study the stellar population gradients (SP; ages, metallicities, α-element abundance ratios, and stellar initial mass functions) of early-type galaxies (ETGs) at $z$ ≤ 0.08 from the Mapping Nearby Galaxies at APO Data Release 15 (MaNGA-DR15) survey. In this work, we focus on the S0 population and quantify how the SP varies across the population as well as with galactocentric distance. We do this by measuring Lick indices and comparing them to SP synthesis models. This requires spectra with high signal-to-noise ratio which we achieve by stacking in bins of luminosity (Lr) and central velocity dispersion (σ0). We find that: (1) there is a bimodality in the S0 population: S0s more massive than $3\times 10^{10}\, \mathrm{M}_\odot$ show stronger velocity dispersion and age gradients (age and σr decrease outwards) but little or no metallicity gradient, while the less massive ones present relatively flat age and velocity dispersion profiles, but a significant metallicity gradient (i.e. [M/H] decreases outwards). Above $2\times 10^{11}\, \mathrm{M}_\odot$, the number of S0s drops sharply. These two mass scales are also where global scaling relations of ETGs change slope. (2) S0s have steeper velocity dispersion profiles than fast-rotating elliptical galaxies (E-FRs) of the same luminosity and velocity dispersion. The kinematic profiles and SP gradients of E-FRs are both more similar to those of slow-rotating ellipticals (E-SRs) than to S0s, suggesting that E-FRs are not simply S0s viewed face-on. (3) At fixed σ0, more luminous S0s and E-FRs are younger, more metal rich and less α-enhanced. Evidently for these galaxies, the usual statement that ‘massive galaxies are older’ is not true if σ0 is held fixed.

Domínguez Sánchez, H.↗
DOE OSTI2024

Vortex Lattices in Active Nematics with Periodic Obstacle Arrays

Here, we numerically model a two-dimensional active nematic confined by a periodic array of fixed obstacles. Even in the passive nematic, the appearance of topological defects is unavoidable due to planar anchoring by the obstacle surfaces. We show that a vortex lattice state emerges as activity is increased, and that this lattice may be tuned from “ferromagnetic” to “antiferromagnetic” by varying the gap size between obstacles. We map the rich variety of states exhibited by the system as a function of distance between obstacles and activity, including a pinned defect state, motile defects, the vortex lattice, and active turbulence. We demonstrate that the flows in the active turbulent phase can be tuned by the presence of obstacles, and explore the effects of a frustrated lattice geometry on the vortex lattice phase.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ICED: An Integrated CGRA Framework Enabling DFVS-Aware Acceleration

oarse-grained reconfigurable arrays (CGRAs) are a promising solution to enable energy-efficient acceleration of applications from different domains. By leveraging reconfiguration at the functional level, they can adapt to significantly different computational patterns. Existing CGRA mapping approaches extract instruction-level parallelism, exploit loop-pipelining opportunities, guarantee the data dependency, and target high throughput of a given loop. However, the recurrence data-dependency in the DFG and the mismatch between required and available computing/communication resources complicate the mapping, and might lead to significant unbalances in the utilization of the CGRA's tiles. This results in wasted power for tiles with low utilization. Applying dynamic voltage and frequency scaling (DVFS) can potentially solve this challenge and improve energy efficiency by adjusting voltage and frequency of different tiles independently. CGRAs have also been successful in accelerating data-dependent streaming applications. However, in these applications, the execution time of each kernel in the pipeline might dynamically vary depending on the characteristics of the input. This also leads to under-utilization of resources for the dynamically changing kernels that do not limit the application throughput. DVFS can also improve energy efficiency for these applications by dynamically changing the voltage and frequency levels of tiles that host non performance-constraining kernels. This paper proposes ICEDTEA -- an integrated DVFS-aware framework to map applications on CGRAs that support power islands. ICEDTEA proposes a CGRA architecture supporting DVFS islands at varying granularity (from a single tile to a group of tiles) and the related DVFS-aware compilation and mapping toolchain. ICEDTEA is the first work that introduces DVFS support for spatio-temporal CGRAs at power-island levels. The experimental evaluation shows that ICEDTEA improves average utilization by 2.3$\times$ and energy-efficiency by 1.32$\times$ over a conventional CGRA. With streaming applications, ICEDTEA improves energy efficiency by 1.12$\times$ over a state-of-the-art CGRA that introduces partial dynamic reconfiguration to adapt to variations in kernels' throughput.

Tan, Cheng↗