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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Towards a multiscale approach for understanding irradiation induced swelling and creep in 316 stainless steels - A coupled cluster dynamics and crystal plasticity approach

Structural materials undergo mechanical degradation, in part due to irradiation-induced swelling and creep, under nuclear reactor conditions. While swelling results from the migration and clustering of irradiation-induced atomic-scale mobile defects, the interaction of mesoscale dislocations with these defects causes creep deformation. A coupled crystal plasticity (CP) and mean-field cluster dynamics (CD) approach is presented to investigate the effect of irradiation on the long-term mechanical behavior of 316 stainless steel, which are under consideration for use in nuclear reactors. The temporal evolution of Frenkel pairs and extended defect population, under a chosen irradiation flux and temperature, is predicted using the CD model. The impact of the irradiation defects on the stress state, and the resulting dislocation-mediated inelastic deformation, is modeled concurrently with the CP model. The inelastic deformation is irradiation flux dependent, and early-stage defect evolution determines the later-stage mechanical behavior in 316 stainless steel.

36 - MATERIALS SCIENCE↗
DOE OSTI2021

DNTTD (Distributed Non-Negative Tensor Train Decomposition)

The era of exascale computing opens new venues for innovations and discoveries in many scientific, engineering, and commercial fields. However, with the exa flops also come the extra-large high-dimensional data generated by high performance computing. High-dimensional data is presented as multidimensional arrays, aka tensors. The presence of latent (not directly observable) structures in the tensor allows a unique representation and compression of the data by classical tensor factorization techniques. However, the classical tensor methods are not always stable or they can be exponential in their memory requirements, which makes them not suitable for high-dimensional tensors. Tensor train (TT) is a state-of-the-art tensor network introduced for factorization of high-dimensional tensors. TT transforms the initial high-dimensional tensor in a network of three-dimensional tensors that requires only a linear storage. Many real-world data, such as, density, temperature, population, probability, etc., are non-negative and for an easy interpretation, the algorithms preserving non-negativity are preferred. Here, we introduce a distributed non-negative tensor-train and demonstrate its scalability and the compression on synthetic and real world big datasets.

Bhattarai, Manish↗
DOE OSTI2021

Raman Microscopy Investigation of GLP-1 Peptide Association with Supported Phospholipid Bilayers

A wide range of important biological processes occur at phospholipid membranes including cell signaling, where a peptide or small molecule targets a membrane-localized receptor protein. In this work, we report the adaptation of confocal-Raman microscopy to quantify populations of unlabeled glucagon-like peptide-1 (GLP-1), a membrane-active 30-residue incretin peptide, in supported phospholipid bilayers deposited on the interior surfaces of wide-pore porous silica particles. Quantification of lipid bilayer-associated peptide is achieved by measuring the Raman scattering intensity of the peptide relative to that of the supported-lipid bilayer, which serves as an internal standard. The dependence of the bilayer-associated GLP-1 population on the solution-concentration of GLP-1 produces an isotherm used to determine the equilibrium constant for peptide-bilayer association and the maximum peptide surface coverage. The maximum coverage of GLP-1 in the lipid bilayer was found to be only 1/5th of a full monolayer based on its hydrodynamic radius. The saturation coverage, therefore, is not limited by the size of GLP-1 but by the ability of the bilayer to accommodate the peptide at high concentrations within the bilayer. Raman spectra show that GLP-1 association with the supported bilayer is accompanied by structural changes consistent with the intercalation of the peptide into bilayer, where the observed increase in acyl-chain order would increase the lipid density and provide free volume needed to accommodate the peptide. Furthermore, these results were compared with previous measurements of the association of fluorescently-labeled GLP-1 with a planar-supported bilayer; the unlabeled peptide exhibits a 3-fold greater affinity for the lipid-bilayer on the porous-silica support suggesting that the fluorescent label alters GLP-1 lipid-bilayer association.

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

From Images to Dark Matter: End-to-end Inference of Substructure from Hundreds of Strong Gravitational Lenses

Abstract Constraining the distribution of small-scale structure in our universe allows us to probe alternatives to the cold dark matter paradigm. Strong gravitational lensing offers a unique window into small dark matter halos (<10 10 M ⊙ ) because these halos impart a gravitational lensing signal even if they do not host luminous galaxies. We create large data sets of strong lensing images with realistic low-mass halos, Hubble Space Telescope (HST) observational effects, and galaxy light from HST’s COSMOS field. Using a simulation-based inference pipeline, we train a neural posterior estimator of the subhalo mass function (SHMF) and place constraints on populations of lenses generated using a separate set of galaxy sources. We find that by combining our network with a hierarchical inference framework, we can both reliably infer the SHMF across a variety of configurations and scale efficiently to populations with hundreds of lenses. By conducting precise inference on large and complex simulated data sets, our method lays a foundation for extracting dark matter constraints from the next generation of wide-field optical imaging surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Contrasting characteristics of open- and closed-cellular stratocumulus cloud in the eastern North Atlantic

Abstract. Extensive regions of marine boundary layer cloud impact the radiative balance through their significant shortwave albedo while having little impact on outgoing longwave radiation. Despite this importance, these cloud systems remain poorly represented in large-scale models due to difficulty in representing the processes that drive their life cycle and coverage. In particular, the mesoscale organization and cellular structure of marine boundary clouds have important implications for the subsequent cloud feedbacks. In this study, we use long-term (2013–2018) observations from the Atmospheric Radiation Measurement (ARM) Facility's Eastern North Atlantic (ENA) site on Graciosa Island, Azores, Portugal, to identify cloud cases with open- or closed-cellular organization. More than 500 h of each organization type are identified. The ARM observations are combined with reanalysis and satellite products to quantify the cloud, precipitation, aerosol, thermodynamic, and large-scale synoptic characteristics associated with these cloud types. Our analysis shows that both cloud organization populations occur during similar sea surface temperature conditions, but the open-cell cases are distinguished by stronger cold-air advection and large-scale subsidence compared to the closed-cell cases, consistent with their formation during cold-air outbreaks. We also find that the open-cell cases were associated with deeper boundary layers, stronger low-level winds, and higher rain rates compared to their closed-cell counterparts. Finally, raindrops with diameters larger than 1 mm were routinely recorded at the surface during both populations, with a higher number of large drops during the open-cellular cases. The similarities and differences noted herein provide important insights into the environmental and cloud characteristics during varying marine boundary layer cloud mesoscale organization and will be useful for the evaluation of model simulations for ENA marine clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Preprocessing of municipal solid waste towards thermal insulating material

Municipal solid waste (MSW) is one of the significant challenges in today’s world. A continuous surge in population, increasing living standards, and rapid urbanization are generating an enormous quantity of MSW. For example, the Environmental Protection Agency (EPA) reported that the total generation of MSW in the United States in 2018 was 292.4 million tons. Improper management of this MSW often leads to the release of greenhouse gases, emission of particulate matters, and formation of dioxins, which all ultimately contributes to climate change. Recycling these wastes via landfills with gas recovery and/or energy and material production via thermal and chemical conversions could be viable options to manage these challenges. Depending on the inherent chemical and structural properties of unrecycled wastes, the carbon structures can be tailored for processing and reuse in manufacturing of structural composites, building materials such as insulation, carbon dense reactant materials such as activated carbon, and so on. According to the EPA’s estimation, MSW in the United States is approximately 23% paper and paperboard, 12% plastics, 6% wood and 6% is textiles. Thus, this research focused on the feasibility of using the MSW as insulation material for the construction sector. The goal of this work was to determine the range of particle sizes, consolidation ratios, and component blends that can achieve insulation R-values within at least 70% that of traditional blown cellulose fiber. To achieve this goal, we designed the testing matrix based on five different component blends, three different particle sizes, and three different compaction level. An American Society for Testing and Materials (ASTM) method (C-739) was used to measure the R-value of the insulation material. Results showed that, adding more paper component in addition to smaller particle size and loose compaction made the insulation similar to the traditional blown cellulose fiber insulation as the R-value was within a range of 2.5-3.0 per inch.

42 ENGINEERING↗
DOE OSTI2025

Cyclometallated Co(III) Complexes with Lowest-Energy Charge Transfer Excited States Accessible with Visible Light

The Co(III) complexes, cis-[Co(ppy) 2 (L)]PF 6 , where ppy = 2-phenylpyridine and L = bpy (2,2′-bipyridine; 1), phen (1,10-phenanthroline; 2), and DAP (1,12-diazaperylene; 3), are reported and their photophysical properties were investigated to evaluate their potential as sensitizers for applications that include solar energy conversion schemes and photoredox catalysis. Calculations show that cyclometallation in the cis-[Co(ppy) 2 (L)]PF 6 series affords strong Co(dπ)/ppy(π) orbital interactions that result in a Co/ppy(π*) highest occupied molecular orbital (HOMO) and a lowest unoccupied molecular orbital (LUMO) localized on the diimine ligand, L(π*). Complexes 1–3 exhibit relatively invariant oxidation potentials, whereas the reduction event is dependent on the identity of the diimine ligand, L, consistent with the theoretical predictions. For 3 a broad Co/ppy(π*) → L(π*) metal/ligand-to-ligand charge transfer (ML-LCT) absorption band is observed in CH 3 CN with a maxima at 507 nm, extending beyond 600 nm. Upon excitation of the 1ML-LCT transition, transient absorption features consistent with the population of a 3 ML-LCT excited state with lifetimes, τ, of 3.0 ps, 4.6 and 42 ps for 1, 2 and 3 in CH 3 CN respectively are observed. Upon irradiation with 505 nm, 3 is able to reduce methyl viologen (MV 2+ ), an electron acceptor commonly in photocatalytic schemes. Here, to our knowledge, 3 represents the first heteroleptic molecular Co(III) complex that combines cyclometallation with a diimine ligand with lowest-lying metal-to-ligand charge transfer excited states able to undergo photoinduced charge transfer with low-energy green light. As such, the structural design of 3 represents an important step toward d6 photosensitizers based on earth abundant metals.

Energy↗
DOE OSTI2023

iMaNGA: mock MaNGA galaxies based on IllustrisTNG and MaStar SSPs – II. The catalogue

ABSTRACT Strengthening the synergy between simulations and observations is essential to test galaxy formation and evolution theories. To achieve this goal, in the first paper of this series, we presented a method to generate mock SDSS-IV/Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) integral-field spectroscopic galaxy observations from cosmological simulations. In this second paper, we build the iMaNGA catalogue consisting of ∼1000 unique galaxies from the TNG50 cosmological simulations, selected to mimic the SDSS-IV/MaNGA-Primary sample selection. Here, we present and discuss the iMaNGA sample and its comparison to the MaNGA Primary catalogue. The iMaNGA sample well recovers the MaNGA-Primary sample in terms of stellar mass versus angular size relation and spatial resolution. The Sérsic index versus angular size relation, instead, is not reproduced well by the simulations, mostly because of a paucity of high-mass elliptical galaxies in TNG50. We also investigate our ability to recover the galaxy kinematics and stellar population properties with full-spectral fitting. We demonstrate that ‘intrinsic’ and ‘recovered’ stellar kinematics, stellar ages, and metallicities are consistent, with residuals compatible with zero within 1σ. Also ‘intrinsic’ and ‘recovered’ star formation histories display a great resemblance. We conclude that our mock generation and spectral fitting processes do not distort the ‘intrinsic’ galaxy properties. Therefore, in the third paper of this series, we can meaningfully test the cosmological simulations, comparing the stellar population properties and kinematics of the iMaNGA mock galaxies and the MaNGA observational results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Progressing Analysis of Variable Electric Rates (PAVER) Study

The Progressing Analysis of Variable Electric Rates (PAVER) study analyzed the impact of a range of time-varying electric rates on the performance of a regional electric grid and the resulting costs for participating and non-participating customers. This analysis leveraged and extended the work of PNNL’s Distribution System Operator with Transactive (DSO+T) study. Five different rate designs were included: a flat volumetric energy charge, a typical Time of Use (TOU) rate, a dynamic energy (DE) rate (based on wholesale locational marginal prices), a dynamic energy and capacity (DE+C) rate, and, finally, a Block and Swing (B&S) rate that billed customers based on their average load profile at constant pricing, but used the DE+C dynamic price for load deviations from their average profile. These rates were analyzed in a large-scale co-simulation of an entire regional grid with a customer population representative of the current state. A large fraction (80%) of residential and commercial customers were assumed to participate in these time-varying rates with automatically controlled HVAC, water heaters, electric vehicles, and batteries. This study assumed no industrial sector participation. The DE and DE+C rates saw system peak loads reduced by 6-7%, while the large participation in the TOU rate case saw a significant rebound effect and a resulting peak load increase of >5%. The impacts to the annual and peak system demand impacted system wholesale prices and the overall grid operating costs. This cost structure determined the revenue needed to be collected from customers by each rate design. Participating customers on the DE and DE+C rates (located in one of the modeled DSOs) saw reductions in average annual electricity bills of 11-17% with average increases in monthly bill variation of no more than 13%. At such high participation levels, TOU customers saw 10% higher average annual bills (due to system-wide rebound effects) and average increased monthly bill variation of 16%. Residential owners of large flexible loads (such as electric vehicles) saw larger bill savings (17-20%) when on a fully dynamic rate. The presence of on-site generation (such as rooftop solar) did not appear to appreciably change customer outcomes. Customers on the Block and Swing rate did see 6% lower monthly bill variation (as intended) than the flat rate case, but at the expense of appreciable bill savings, which were only 3%, comparable to the savings seen by non-participants. Given this finding we recommend that additional research be conducted into how best various bill protection mechanisms can balance minimizing customer bill variation with providing financial incentives commensurate with the flexibility customers provide. We also recommend that customer outcomes be explored across a range of regions using current actual customer and system cost data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Xylan-cellulose core structure of oat water-extractable β-glucan macromolecule: Insight into interactions and organization of the cell wall complex

Water-extractable β-glucan with high molar mass (HM) determines health benefits of oat food. Oat β-glucan was extracted by a standardized in vitro digestion method and co-existing water-extractable polysaccharide (WEP) fraction and its HM-arabinoxylan (HM-AX) subfraction were isolated to identify their highly acid-resistant subunit and investigate molecular interactions between constituent polymers. The WEP and HM-AX samples consisted of arabinoxylans (AXs) (74 and 76 %, respectively), however, cellulose constituted the secondary component (6.6 and 12.8 %, respectively). Multi-detection HPSEC along with specific enzymatic hydrolysis of AXs revealed the presence of the HM-xylan domain (16 and 34 %, respectively) built of numerous single- and multi-component populations with random coil and rod-like conformations, which were embedded in a xylan matrix with spherical conformation and controlled the macromolecular shape. Unlike single-component populations, the multi-component ones were resistant to hydrolytic action of AX-hydrolyzing enzymes and represented the subunits that anchor matrix polysaccharides onto cellulose surface. These results indicate that water-extractable β-glucan macromolecule comprises as integral element a cellulose core with two linking populations, HM-xylan and low molar mass glucomannan, which are surrounded by a feruloylated AX-arabinan-arabinogalactan composite and next laminated by β-glucan matrix. Here, the stiff cellulose-xylan backbone is the basis of HM β-glucan organization, controlled by its cellulose-like segments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Assessing mechanisms for microbial taxa and community dynamics using process models

Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer–resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer–resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Trace Impurities Identified as Forensic Signatures in CMX-5 Fuel Pellets Using X-ray Spectroscopic Techniques

We report that small-particle analysis is a highly promising emerging forensic tool for analysis of interdicted special nuclear materials. Integration of microstructural, morphological, compositional, and molecular impurity signatures could provide significant advancements in forensic capabilities. We have applied rapid, high-sensitivity, hard X-ray synchrotron chemical imaging to analyze impurity signatures in two differently fabricated fuel pellets from the 5th Collaborative Materials Exercise (CMX5) of the IAEA Nuclear Forensics International Working Group. The spatial distributions, chemical compositions, and morphological and molecular characteristics of impurities were evaluated using X-ray absorption near-edge structure (XANES) and X-ray fluorescence chemical imaging to discover principal impurities, their granularity, particle sizes, modes of occurrence (distinct grains vs incorporation in the UO 2 lattice), and sources and mechanisms of incorporation. Differences in UO 2+x stoichiometry were detected at the microscale in nominally identical UO 2 ceramics (CMX5-A and CMX5-B), implying the presence of multiple UO 2 host phases with characteristic microstructures and feedstock compositions. Al, Fe, Ni, W, and Zr impurities and integrated impurity signature analysis identified distinctly different pellet synthesis and processing methods. For example, two different Al, W, and Zr populations in the CMX5-B sample indicated a more complex processing history than the CMX5-A sample. K-edge XANES measurements reveal both metallic and oxide forms of Fe and Ni but with different proportions between each sample. Altogether, these observations suggest multiple sources of impurities, including fabrication (e.g., force-sieving) and feedstock (mineral oxides). This study demonstrates the potential of synchrotron techniques to integrate different signatures across length scales (angstrom to micrometer) to detect and differentiate between contrasting UO 2 fuel fabrication techniques.

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

Trap States in Reduced Colloidal Titanium Dioxide Nanoparticles Have Different Proton Stoichiometries

Added electrons and holes in semiconducting (nano)materials typically occupy “trap states,” which often determine their photophysical properties and chemical reactivity. However, trap states are usually ill-defined, with few insights into their stoichiometry or structure. Our laboratory previously reported that aqueous colloidal TiO 2 nanoparticles prepared from TiCl 4 + H 2 O have two classes of electron trap states, termed Blue and Red. Herein, we show that the formation of Red from oxidized TiO 2 requires 1e – + 1H + , while Blue requires 1e – + 2H + . The two states are in a protic equilibrium, Blue ⇌ Red + H + , with K eq = 2.65 mM. The Blue states in the TiO 2 NPs behave just like a soluble molecular acid with this K eq as their K a , as supported by solvent isotope studies. Because the trap states have different compositions, their population and depopulation occur with the making and breaking of chemical bonds and not (as commonly assumed) just by the movement of electrons. In addition, the direct observation of a 2H + /1e – trap state contradicts the emerging H atom transfer (1H + /1e – ) paradigm for oxide/solution interfaces. Finally, this work emphasizes the importance of chemical stoichiometries, not just electronic energies, in understanding and directing the reactivity at solid/solution interfaces.

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

Metallofullerene photoswitches driven by photoinduced fullerene-to-metal electron transfer

We report on the discovery and detailed exploration of the unconventional photo-switching mechanism in metallofullerenes, in which the energy of the photon absorbed by the carbon cage π-system is transformed to mechanical motion of the endohedral cluster accompanied by accumulation of spin density on the metal atoms. Comprehensive photophysical and electron paramagnetic resonance (EPR) studies augmented by theoretical modelling are performed to address the phenomenon of the light-induced photo-switching and triplet state spin dynamics in a series of Y x Sc 3-x N@C 80 (x = 0–3) nitride clusterfullerenes. Variable temperature and time-resolved photoluminescence studies revealed a strong dependence of their photophysical properties on the number of Sc atoms in the cluster. All molecules in the series exhibit temperature-dependent luminescence assigned to the near-infrared thermally-activated delayed fluorescence (TADF) and phosphorescence. The emission wavelengths and Stokes shift increase systematically with the number of Sc atoms in the endohedral cluster, whereas the triplet state lifetime and S 1 –T 1 gap decrease in this row. For Sc 3 N@C 80 , we also applied photoelectron spectroscopy to obtain the triplet state energy as well as the electron affinity. Spin distribution and dynamics in the triplet states are then studied by light-induced pulsed EPR and ENDOR spectroscopies. The spin–lattice relaxation times and triplet state lifetimes are determined from the temporal evolution of the electron spin echo after the laser pulse. Well resolved ENDOR spectra of triplets with a rich structure caused by the hyperfine and quadrupolar interactions with 14 N, 45 Sc, and 89 Y nuclear spins are obtained. The systematic increase of the metal contribution to the triplet spin density from Y 3 N to Sc 3 N found in the ENDOR study points to a substantial fullerene-to-metal charge transfer in the excited state. These experimental results are rationalized with the help of ground-state and time-dependent DFT calculations, which revealed a substantial variation of the endohedral cluster position in the photoexcited states driven by the predisposition of Sc atoms to maximize their spin population.

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

A robust method of nuclei isolation for single-cell RNA sequencing of solid tissues from the plant genus Populus

Single-cell transcriptome analysis has been extensively applied in humans and animal models to uncover gene expression heterogeneity between the different cell types of a tissue or an organ. It demonstrated its capability to discover key regulatory elements that determine cell fate during developmental programs. Single-cell analysis requires the isolation and labeling of the messenger RNA (mRNA) derived from each cell. These challenges were primarily addressed in mammals by developing microfluidic-based approaches. For plant species whose cells contain cell walls, these approaches have generally required the generation of isolated protoplasts. Many plant tissues’ secondary cell wall hinders enzymatic digestion required for individual protoplast isolation, resulting in an unequal representation of cell types in a protoplast population. This limitation is especially critical for cell types located in the inner layers of a tissue or the inner tissues of an organ. Consequently, single-cell RNA sequencing (scRNA-seq) studies using microfluidic approaches in plants have mainly been restricted to Arabidopsis roots, for which well-established procedures of protoplast isolation are available. Here we present a simple alternative approach to generating high-quality protoplasts from plant tissue by characterizing the mRNA extracted from individual nuclei instead of whole cells. We developed the protocol using two different plant materials with varying cellular complexity levels and cell wall structure, Populus shoot apices, and more lignified stems. Using the 10× Genomics Chromium technology, we show that this procedure results in intact mRNA isolation and limited leakage, with a broad representation of individual cell transcriptomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A spatially regularized detector for emergent/re-emergent disease outbreaks

Early detection of outbreaks caused by emergent pathogens, using epidemiological surveillance data i.e., daily case counts, is difficult. This is because the data tend to be noisy during the early epoch of the outbreak. In contrast, the spread-rate of the disease tends to be well-behaved, as it depends only on the mixing patterns of the population and the characteristics of the pathogen, neither of which behave erratically in space-time. In this report, we explore whether the spread-rate can be used for epidemiological surveillance, conditional on case count data. Estimating the spread-rate from case count data allows us to exploit exogenous information, e.g., incubation period distributions etc., which can considerably smooth out any erratic temporal behavior. Further, epidemiological dynamics are spatially correlated, and if case counts are available for multiple areal units e.g., counties, these correlations could potentially be used to suppress noise in the early epoch data. These exogenous information and structure are not exploited by conventional syndromic surveillance detectors to extract a well-behaved latent variable for monitoring purposes. The technical challenge lies in the estimation of the spread-rate field jointly over a collection of areal units; further, the spread-rate varies over time. We develop a method based on mean-field variational inference to approximately estimate the spread-rate field, using a Gaussian Random Field Model for spatial regularization. The method is tested on the estimation of spread-rate in the thirty-three counties of New Mexico and detect the arrival of the Fall 2020 COVID-19 wave in September 2020. We find that the method is scalable, but underestimates the uncertainty in the estimated spread-rate field. We detect the arrival of the Fall 2020 wave a week ahead of conventional syndromic surveillance algorithms, but our simplistic detection algorithm, based on simple anomaly detection, suffers from a high false positive rate, similar to conventional detectors.

59 BASIC BIOLOGICAL SCIENCES↗