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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Issue Summary of INL Phase IV Transient Results for IAEA CRP on HTGR UAM Benchmark

This report details the Parallel and Highly Innovative Simulation for Idaho National Laboratory (INL) Code System (PHISICS)/Reactor Excursions and Leak Analysis Program (RELAP5)-3D results obtained for the transient core exercises defined for Phase IV of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on high-temperature gas cooled reactor (HTGR) uncertainty analysis in modeling (UAM). The Phase III models and results are linked to the earlier Standardized Computer Analyses for Licensing Evaluation (SCALE)/Sampler/New ESC-based Weighting Transport (NEWT) data generated for the lattice physics (lattice) stage Phase I of the CRP. The focus of this report is the Uncertainty/Sensitivity Assessment (U/SA) of the prismatic modular high-temperature gas cooled reactor (MHTGR)-350 design, and specifically for Exercises IV-1 and IV-2 of the benchmark: the Control Rod Withdrawal (CRW) and Pressurised Loss of Cooling (PLOFC) events. The statistical U/SA methodology is implemented and demonstrated using the RAVEN code, based on perturbed cross-section libraries obtained from the SCALE/Sampler sequence. Uncertainties in nuclear data (cross-sections and the average number of neutrons produced per fission, 235U[¯v ]) lead to standard deviations (uncertainties of one s) of approximately 0.5% in the core eigenvalues of the MHTGR-350 and core models. For the coupled neutronics/thermal fluid model, local power density uncertainties up to 3.6% were observed in the colder regions of the core, while the local maximum fuel temperature uncertainties reached 1.5% for the models that included thermal fluid uncertainties. The addition of thermal fluid uncertainties dominated the impacts of nuclear data uncertainties in all cases. The main contributors to uncertainties in the power density and fuel temperatures during the transients were uncertainties in the reactor operating conditions (total power, inlet mass flow rate and inlet gas temperature). Variations in the bypass flows did not have significant impact on any of the output variables. For the nuclear data uncertainties it was found that the 235U(¯v ) / 235U(¯v ) covariance produced the largest sensitivities in terms of its impact on the eigenvalue and peak reactor power. It was also observed that the impact of any nuclear data uncertainties on the maximum fuel temperature was much less significant that the impact on eigenvalue and power. Another important finding was that although the use of eight or more energy groups is recommended for best-estimate HTGR simulation, two-group models produced acceptable uncertainty and sensitivity results for most FOMs. Since the statistical U/SA methodology is computationally expensive, and most transient solver requirements will scale directly with the number of energy groups, two energy groups could be used by HTGR developers during the early stages of design when larger uncertainty margins can be tolerated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Chemical Interpretation of Charged Point Defects in Semiconductors: A Case Study of Mg 2 Si

The electronic structures of charged point defects influence electrical and optical properties of semiconductors. Understanding the orbital interactions responsible for the electronic structures of defects therefore promotes a chemical intuition for defect-driven mechanisms in semiconductors. In this tutorial, we discuss a molecular orbital theory-based framework for understanding defect-induced electronic states based on local chemical interactions between the defect and the atoms surrounding the defect site. By using Mg 2 Si as a case study, we show how both the chemical interactions and molecular orbitals (i. e., wave functions) responsible for the charge state(s) of a defect can be understood from the bonding symmetry of the defect site. We anticipate that a chemistry-based perspective of charged defects will enrich defect engineering efforts for electronic and optical materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electric Field Effects on Water and Ion Structure and Diffusion at the Orthoclase (001)–Water Interface

Understanding the electrochemical properties of mineral–water interfaces tends to rely upon electrical double layer (EDL) models, but these models are based on the assumption that electrostatic equilibrium is constantly maintained. In reality, interfacial reactions, ion diffusion, and their electrochemical signatures are based in nonequilibrium conditions of locally or globally imbalanced electrical fields where current EDL models have limited purview. In this work, we performed molecular dynamics (MD) simulations of the orthoclase (001) surface in contact with a 1 M NaCl aqueous solution under various electric fields, to explore the interplay between EDL structure and dynamics when perturbed by electric fields of different direction and strength, by confinement, and by different distributions of structural surface charge. The simulations showed that confinement between two opposing (001) surfaces led to the development of an induced field when the applied field was perpendicular to the surfaces and, as a result, to ionic diffusion coefficients that were independent of electric field strength. In contrast, when the applied field was parallel to the surfaces, confinement resulted in ionic diffusion coefficients that were more strongly dependent on the magnitude of the electric field than in bulk water. Differences in the density and distribution of aluminol groups on the two surfaces had a significant impact on how the interfacial structure and dynamics varied in the presence of an electric field. Notably, these differences resulted in an electro-osmotic flow with opposite directions at the two surfaces under parallel applied electric field. Overall, the MD simulations highlighted the importance of considering atomic-level structure and heterogeneities when developing models of the electrochemical properties of mineral–water interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Hot-Carrier Injection and Millisecond Charge Separation from a Robust Heteroleptic Iron(II) Chromophore Immobilized on TiO 2

The synthesis, spectroscopic characterization, computational analysis, and photoelectrochemical behavior of a new iron-based chromophore, [(Cpy) 2 Fe- (deeb)](PF 6 ) 2 (Fe(Cpy) 2 (deeb)), where Cpy is 1-methyl-3-(2-pyridyl)imidazole and deeb is 4,4’-(CO 2 CH 2 CH 3 ) 2 -2,2’-bipyridine, is reported. Electrochemically reversible waves assigned to a metal-centered E o (Fe III/II ) = +0.48 and a ligand-centered E o (Fe 2+/+ ) = −1.47 V vs Fc +/0 reduction were evident in cyclic voltammetry measurements. The combination of a strong σ-donor and a π-acceptor lowered the energy of the metal-toligand charge-transfer (MLCT) excited state relative to the metal-centered state. Two MLCT transitions appear in the visible region at 424 and 580 nm. TDDFT calculations revealed that the lower-energy band was well formulated as Fe(II)→deeb, and the higher-energy transition was charge transfer to both the deeb and Cpy ligands. Resonance Raman spectroscopy supports these findings showing enhanced deeb vibrational modes with 532 nm excitation, both deeb and Cpy modes with 473 nm excitation, and exclusively Cpy with 405 nm excitation. Ultrafast spectroscopy reveals a short-lived (∼2 ps) MLCT excited state and a longer-lived (∼20 ps) metal-centered state. Efficient methods to deprotect the ester groups and anchor the complex to mesoporous TiO 2 (anatase) thin films in high surface coverages, Fe(Cpy) 2 (dcb)|TiO 2 σ = 3 × 10 −8 mol/cm 2 , were established. Pulsed light excitation of Fe(Cpy) 2 (dcb)|TiO 2 resulted in rapid excited state injection (k inj > 10 8 s −1 ) and formation of a charge-separated state, Fe III (Cpy) 2 (dcb)|TiO 2 (e), which persists on the millisecond time scale before returning cleanly to the ground state with secondorder kinetics. Injection yields measured 50 ns after light excitation were found to double from Φ = 0.15 with green (532 nm) light to 0.30 with blue (457 nm) light excitation. Incident photon-to-current efficiency (% IPCE) measurements as a function of excitation wavelength in a 0.5 M LiI/I 2 /CH 3 CN electrolyte provide clear evidence for band-selective “hot carrier” injection from the remote Cpy-localized excited state. Collectively, the spectroscopic and photoelectrochemical data indicate that a semiconductor can intercept hot electrons from iron chromophores even when the excited-state dipole is oriented away from the surface-anchoring ligand.

Charge transfer↗
DOE OSTI2024

Entanglement Renormalization for Quantum Field Theories with Discrete Wavelet Transforms

We propose an adaptation of Entanglement Renormalization for quantum field theories that, through the use of discrete wavelet transforms, strongly parallels the tensor network architecture of the Multiscale Entanglement Renormalization Ansatz (a.k.a. MERA). Our approach, called wMERA, has several advantages of over previous attempts to adapt MERA to continuum systems. In particular, (i) wMERA is formulated directly in position space, hence preserving the quasi-locality and sparsity of entanglers; and (ii) it enables a built-in RG flow in the implementation of real-time evolution and in computations of correlation functions, which is key for efficient numerical implementations. As examples, we describe in detail two concrete implementations of our wMERA algorithm for free scalar and fermionic theories in (1+1) spacetime dimensions. Possible avenues for constructing wMERAs for interacting field theories are also discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

DFT Analysis of the Binding of Rare Earth Nitrates at Internal and External Surfaces of MCM-22

MCM-22-type zeolites constitute a well-characterized tunable class of aluminosilicates suitable for elucidating the fundamental aspects of the binding of rare earth elements (REEs) in layered materials. Starting from the pure silica version ITQ-1 with a unit cell of Si 72 O 144 , a model for periodic bulk crystalline MCM-22 with a finite Al concentration is provided by replacing a Si atom with an Al atom in the unit cell at suitable tetrahedral sites near an internal pore surface. Then, a H atom is added to an O atom bridging Si and Al atoms to create a Brønsted acid site (BAS). There are no internal silanol groups in this bulk model. To generate a model for an external surface, we adopt the fully hydroxylated surface structure of a layer within the ITQ-1 precursor with two silanols per lateral unit cell. A BAS on the external surface can be generated by replacing a near-surface Si atom with an Al atom and adding a H atom, as above. The strength of binding at a BAS of REE, X, taken to be present in the solution phase as nitrates, is determined from the energy change in the reaction X(NO 3 ) 3 + ≡Si–{OH}–Al≡ → ≡Si–{OX(NO 3 ) 2 }–Al≡+ HNO 3 . The strength of binding at the silanols is determined similarly. Binding energies are determined from two approaches. The first performs periodic plane-wave density functional theory (DFT) total energy analysis for an entire unit cell of MCM-22. The second utilizes cluster models capturing the local environment of REE binding sites and performs DFT analysis with localized basis sets. The two approaches yield consistent results for Nd, revealing similarly strong binding at either an external or internal BAS, but much weaker binding at a silanol site. This is consistent with the picture deduced from recent experiments. Here, we also comment on binding at Al-bridged siloxane sites, which have been suggested as alternative binding sites to BAS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

WellPINN: Accurate Well Representation for Transient Fluid Pressure Diffusion in Subsurface Reservoirs With Physics‐Informed Neural Networks

Accurate representation of pumping wells is essential for reliable reservoir characterization and simulation of operational scenarios in subsurface flow models. Physics-informed neural networks (PINNs) are emerging as a promising alternative to numerical models for reservoir modeling, offering seamless integration of monitoring data and governing physical equations. However, existing PINN-based studies face major challenges in capturing fluid pressure near wells when using a source/sink term, particularly during the early stages after pumping begins. We address this problem by introducing WellPINN, a workflow in which an initially trained PINN infers fluid pressure across the entire reservoir domain using a large equivalent well radius. This initial PINN solution is then locally refined around the well by a set of subdomain PINNs that are trained for smaller equivalent well radii. Continuity across these subdomain interfaces as well as at the initial condition is ensured by hard-constraining each PINN on its subdomain boundary. Our results demonstrate WellPINN as the first workflow of its kind to focus on accurate inference of fluid pressure from pumping rates throughout the entire injection period, significantly advancing the potential of PINNs for inverse modeling and operational scenario simulations. All data and code for this paper are openly available at https://doi.org/10.20350/DIGITALCSIC/17260.

58 GEOSCIENCES↗
DOE OSTI2025

A Pride of Satellites in the Constellation Leo? Discovery of the Leo VI Milky Way Satellite Ultra-faint Dwarf Galaxy with DELVE Early Data Release 3

Abstract We report the discovery and spectroscopic confirmation of an ultra-faint Milky Way satellite in the constellation of Leo. This system was discovered as a spatial overdensity of resolved stars observed with Dark Energy Camera (DECam) data from an early version of the third data release of the DECam Local Volume Exploration (or DELVE) survey. The low luminosity ( M V = − 3.5 6 − 0.37 + 0.47 ; L V = 230 0 − 700 + 1200 L ⊙ ), large size ( R 1 / 2 = 9 0 − 30 + 30 pc), and large heliocentric distance ( D = 11 1 − 6 + 9 kpc) are all consistent with the population of ultra-faint dwarf galaxies (UFDs). Using Keck/DEIMOS observations of the system, we were able to spectroscopically confirm nine member stars, while measuring a tentative mass-to-light ratio of 70 0 − 500 + 1400 M ⊙ / L ⊙ and a nonzero metallicity dispersion of σ [ Fe / H ] = 0.1 9 − 0.11 + 0.14 , further confirming Leo VI’s identity as a UFD. While the system has a highly elliptical shape, ϵ = 0.5 4 − 0.29 + 0.19 , we do not find any conclusive evidence that it is tidally disrupting. Moreover, despite the apparent on-sky proximity of Leo VI to members of the proposed Crater-Leo infall group, its smaller heliocentric distance and inconsistent position in energy–angular momentum space make it unlikely that Leo VI is part of the proposed infall group.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) (Final Technical Report)

The Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) project advances resilience science and engineering by addressing challenges in rural Kansas communities where aging infrastructure, extreme weather, and socioeconomic disparities heighten vulnerability to energy disruptions. Traditional approaches often focus on technical performance while overlooking community concerns and priorities. SAFER responds by integrating community perspectives with advanced analytical frameworks to create a holistic model for measuring and improving resilience. Project objectives included developing novel resilience metrics, advancing modeling frameworks that capture interdependencies across infrastructures, and embedding community-centric indicators directly into planning processes for distributed energy resources. The key technical innovations included the creation of self-organizing map (SOM)-based indices for objective resilience quantification, hetero-functional graph theory (HFGT) models linking power, water, transportation, and community assets, and graph neural network (GNN) tools for identifying critical nodes in complex systems. Community-centric energy planning was demonstrated through optimal siting and sizing of (photovoltaic) PV and battery storage, ensuring resilience enhancements also addressed energy burden and energy insecurity. SAFER engaged community partners in Dodge City and Ford County through surveys, focus groups, and workshops, generating more than 600 responses that established baseline measures of energy burden, financial insecurity, and willingness-to-pay to avoid outages. This data, organized in terms of a community capitals framework, informed the development of weighted reliability indices that better reflect community costs than traditional utility metrics. SAFER’s GNN-based critical node identification framework identified expert-labelled critical nodes with over 99% accuracy, while also uncovering additional functionalities essential for proactive resilience planning. The project’s models demonstrated that optimal PV and storage deployment could improve resilience indices by over 11 percent, with dispatch strategies further enhancing outcomes, confirming both the technical effectiveness and economic feasibility of these approaches. Through its combined emphasis on rigorous modeling, community-focused planning, and community engagement, SAFER advances the state of resilience research while delivering direct benefits to rural communities. The project provides tools, guidelines, and resilience heatmaps that help utilities, local governments, and residents better anticipate disruptions, prioritize investments, and strengthen the capacity to withstand and recover from energy-related hazards. Furthermore, the developed HFG and GNN frameworks are designed for transferability, allowing them to be adapted for resilience planning in other communities with minimal retraining. This inductive learning capability provides a scalable pathway to extend the SAFER project’s impact. Thus, creating a foundation for a nationally applicable model of infrastructure resilience. Additionally, the HFG can also be extended to include other FEMA community lifelines.

14 SOLAR ENERGY↗
DOE OSTI2022

Controlled Environment Agriculture - Farming and Food Access for Healthy Diets

Fruits and vegetables are critical for a healthy diet and USDA guidelines recommend increasing fruit and vegetable consumption for almost all Americans. However, most food system lifecycle assessments do not capture the importance of these food groups in the food system. Moreover, long supply chains and limited access to fresh produce are particularly prevalent in disadvantaged neighborhoods. Many of these communities are food deserts or food swamps characterized by a lack of full-scale groceries, and a prevalence of convenience stores and fast-food restaurants. Stocking of fresh produce is difficult and often unprofitable for small stores. Convenience stores are usually space-limited, unable to achieve economies-of-scale in purchasing and have difficulty managing the short shelf-life of fresh produce. Controlled-Environment (CE) farming, including greenhouses and fully indoor vertical farms, have the potential to address persistent food access issues for disadvantaged communities. CE farming offers several potential advantages for food desert and food swamp neighborhoods, including shorter or non-existent transport distances and fewer middlemen, which could reduce costs. CE farming can be integrated into existing buildings at virtually any scale, providing local jobs and revitalization of community hubs such as shopping malls, or larger-scale farms located in close-in warehouse or industrial areas. Rainwater harvesting and recovery of nutrients from wastewater could further improve food system resilience and circularity. Geospatial modeling of CE farming in case study cities of various sizes and densities will help to quantify the benefits of CE farming. Geospatial modeling can help to answer questions such as whether sufficient collection area is available for rainwater harvesting for a CE farm, and what size of farm would be required to serve the community living within walking distance of the farm. This paper reports on progress in geospatial modeling of CE farming integration into several case study cities.

controlled environment agriculture↗
DOE OSTI2021

Electromagnetic duality and D3-brane scattering amplitudes beyond leading order

We use on-shell methods to study the non-supersymmetric and supersymmetric low-energy S-matrix on a probe D3-brane, including both the 1-loop contributions of massless states as well as the effects of higher-derivative operators. Our results include: (1) A derivation of the duality invariance of Born-Infeld electrodynamics as the dimensional oxidation of the group of spatial rotations transverse to a probe M2-brane; this is done using a novel implementation of subtracted on-shell recursion. (2) The first explicit loop-level BCJ double-copy in a non-gravitational model, namely the calculation of the 4-point self-dual amplitude of non-supersymmetric Born-Infeld. (3) From previous results for n-point self-dual 1-loop BI amplitudes and the conjectured dimension-shifting relations in Yang-Mills, we obtain an explicit all-multiplicity, at all orders in E, expression for the 1-loop integrand of the MHV sector of N = 4 DBI. (4) For all n > 4, the explicitly integrated duality-violating 1-loop amplitudes (self-dual and next-to-self-dual in pure BI as well as MHV in N = 4 DBI) are shown to be removable at O(ε 0 ) by adding finite local counterterms; we propose that this may be true more generally at 1-loop order. (5) We find that in non-supersymmetric Born-Infeld, not all finite local counterterms needed to restore electromagnetic duality can be constructed using the double-copy with higher-derivative corrections, suggesting a fundamental tension between electromagnetic duality and color-kinematics duality at loop-level. Finally we comment on oxidation of duality symmetries in supergravity and the parallels it has to the M2-brane to D3-brane oxidation demonstrated in this paper.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Identifying and Tuning the In Situ Oxygen-Rich Surface of Molybdenum Nitride Electrocatalysts for Oxygen Reduction

Rigorous in situ studies of electrocatalysts are required to enable the design of higher performing materials. Nonplatinum group metals for oxygen reduction reaction (ORR) catalysis containing light elements such as O, N, and C are known to be susceptible to both ex situ and in situ oxidation, leading to challenges associated with ex situ characterization methods. We have previously shown that the bulk O content plays an important role in the activity and selectivity of Mo–N catalysts, but further understanding of the role of composition and morphological changes at the surface is needed. Here, we report the measurement of in situ surface changes to a molybdenum nitride (MoN) thin film under ORR conditions using grazing incidence X-ray absorption and reflectivity. We show that the half-wave potential of MoN can be improved by ~90 mV by potential conditioning up to 0.8 V versus RHE. Utilizing electrochemical analysis, dissolution monitoring, and surface-sensitive X-ray techniques, we show that under moderate polarization (0.3–0.7 V vs RHE) there is local ligand distortion, O incorporation, and amorphization of the MoN surface, without changes in roughness. Furthermore, with a controlled potential hold procedure, we show that the surface changes concurrent with potential conditioning are stable under ORR relevant potentials. Conversely, at higher potentials (≥0.8 V vs RHE), the film incorporates O, dissolves, and roughens, suggesting that in this higher potential regime, the performance enhancements are due to increased access to active sites. Density functional theory calculations and Pourbaix analysis provide insights into film stability and O incorporation as a function of potential. These findings coupled with in situ electrochemical surface-sensitive X-ray techniques demonstrate an approach to studying nontraditional surfaces in which we can leverage our understanding of surface dynamics to improve performance with the rational, in situ tuning of active sites.

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

Molecular engineering of fluoroether electrolytes for lithium metal batteries

Fluoroether solvents are promising electrolyte candidates for high-energy-density lithium metal batteries, where high ionic conductivity and oxidative stability are important metrics for design of new systems. Recent experiments have shown that these performance metrics, particularly stability, can be tuned by changing the fraction of ether and fluorine content. However, little is known about how different molecular architectures influence the underlying ion transport mechanisms and conductivity. Here, we use all-atom molecular dynamics simulations to elucidate the ion transport and solvation characteristics of fluoroether chains of varying length, and having different ether segment and fluorine terminal group contents. The design rules that emerge from this effort are that solvent size determines lithium-ion transport kinetics, solvation structure, and solvation energy. In particular, the mechanism for lithium-ion transport is found to shift from ion hopping between solvation sites located in different fluoroether chains in short-chain solvents, to ion–solvent co-diffusion in long-chain solvents, indicating that an optimum exists for molecules of intermediate length, where hopping is possible but solvent diffusion is fast. Consistent with these findings, our experimental measurements reveal a non-monotonic behavior of the effects of solvent size on lithium-ion conductivity, with a maximum occurring for medium-length solvent chains. Finally, a key design principle for achieving high ionic conductivity is that a trade-off is required between relying on shorter fluoroether chains having high self-diffusivity, and relying on longer chains that increase the stability of local solvation shells.

25 ENERGY STORAGE↗
DOE OSTI2022

Data-driven approach to parameterize SCAN + U for an accurate description of 3 d transition metal oxide thermochemistry

Semilocal density-functional theory (DFT) methods exhibit significant errors for the phase diagrams of transition-metal oxides that are caused by an incorrect description of molecular oxygen and the large self-interaction error in materials with strongly localized electronic orbitals. Empirical and semiempirical corrections based on the DFT + U method can reduce these errors, but the parameterization and validation of the correction terms remains an on-going challenge. Here we develop a systematic methodology to determine the parameters and to statistically assess the results by considering interlinked thermochemical data across a set of transition metal compounds. We consider three interconnected levels of correction terms: (1) a constant oxygen binding correction, (2) Hubbard-U correction, and (3) DFT/DFT + U compatibility correction. The parameterization is expressed as a unified optimization problem. We demonstrate this approach for 3d transition metal oxides, considering a target set of binary and ternary oxides. With a total of 37 measured formation enthalpies taken from the literature, the dataset is augmented by the reaction energies of 1710 unique reactions that were derived from the formation energies by systematic enumeration. To ensure a balanced dataset across the available data, the reactions were grouped by their similarity using clustering and suitably weighted. The parameterization is validated using leave-one-out cross validation (CV), a standard technique for the validation of statistical models. We apply the methodology to the strongly constrained and appropriately normed (SCAN) density functional. Based on the CV score, the error of binary (ternary) oxide formation energies is reduced by 40% (75%) to 0.10 (0.03) eV/atom. A simplified correction scheme that does not involve SCAN/SCAN + U compatibility terms still achieves an error reduction of 30% (25%). The method and tools demonstrated here can be applied to other classes of materials or to parameterize the corrections to optimize DFT + U performance for other target physical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Histopathological characteristics of PRRS and expression profiles of viral receptors in the piglet immune system

Porcine reproductive and respiratory syndrome (PRRS) is a highly contagious viral disease that causes significant economic losses to the swine industry worldwide. PRRS virus (PRRSV) infection is a receptor-mediated endocytosis and replication process. The purpose of this study was to determine the localization and expression of four important PRRSV receptors in immunological organs of piglets. After piglets were infected with PRRSV, Hematoxylin and Eosin staining, immunofluorescence, and Western blot were used to perform histopathological examination and receptors distribution analysis. The results showed that PRRSV caused severe damage to the piglets’ immune organs, including atrophy of the thymus and swelling of lymph node. Histopathological lesions were mainly observed in the lung and lymph node and were characterized by interstitial pneumonia, collapsed follicles, exhaustion of germinal centers, and extensive hemorrhage. Immunofluorescence staining and Western blot results showed that the receptors of CD163 and NMHCII-A were mainly distributed in the thymus, hilar lymph nodes, and mesenteric lymph nodes. However, Sn and vimentin receptors were expressed at low levels in the immune organs of piglets. The distribution of the four receptors in the immune organs was more concentrated in the cortex but was more scattered in the medulla. Compared to the control group, the relative expression of the four receptors increased significantly in most immune organs after viral infection. In conclusion, our study examined the distribution and expression of four PRRSV receptors in immunological organs. We observed a significant increase in the expression of Sn, CD163, and vimentin following viral infection. These findings may provide potential targets for future antiviral reagent design or vaccine development.

Chen, Hong↗
DOE OSTI2020

Montana Community-Scale Solar Strategy Project (Final Technical Report)

Grid-tied solar photovoltaic (PV) development began gradually in Montana, initially taking root in the early 2000s, largely in the form of small residential systems, rarely larger than two kilowatts. Utility support for solar technology through public benefit funding triggered the installation of the state’s first solar PV installations on community-owned facilities including schools, libraries, fire stations and local government buildings in the mid-2000s. By 2016, solar PV installations totaled approximately 28 megawatts of installed capacity, generating less than 0.05% of electricity sold in Montana. Montana’s solar fleet in 2016 included 17 megawatts of utility-scale solar farms, and three shared solar projects developed by rural electric cooperatives that ranged from 25 to 50 kilowatts in size. However, with only 3,000 households utilizing solar PV, either through an on-site installation or participation in a shared solar project, the potential benefits and reach of solar technology was limited. The Montana Solar Community Project (MSCP) was developed by the Montana Energy Office (MEO) at the Department of Environmental Quality in order to implement a “community-scale” solar energy strategy for the state that would cost-effectively expand Montanans’ access to solar PV. This project defines three types of community-scale solar projects: shared solar, community-sited solar, and group purchasing programs. The MSCP project conducted research and stakeholder engagement that helped to inform and develop model community-scale initiatives and an overarching community-scale solar strategy for Montana. Specifically, the project included a solar market assessment, stakeholder meetings across Montana, development of a menu of community-scale solar options, a study of solar potential on schools, community solar market research, and community-scale project implementation support. MSCP activities were successful in implementing solar projects and supporting solar development in communities across Montana. Project activities realized 280 kW of newly installed solar from two solarize programs, a shared solar array at a rural electric cooperative, and a solar array atop a Bozeman high school. The community-scale project implementation support and Solar on Schools components of the project resulted directly in the analysis and design of nearly 2 MW of distributed solar systems across the state. The Solar on Schools analysis alone produced solar designs for 25 schools, representing 920.8 kW of solar potential. Many of the deliverables from this project provide guidance on future development of community-scale solar in Montana, and resulted in a number of important conclusions about community-scale solar in Montana. There is strong interest in community-scale solar in Montana, as noted during stakeholder meetings, in response to solar market research surveys, and as seen by applications for implementation support grants provided by MEO. Project activities also suggest that Montanans demonstrated a desire and need for more information about solar energy technology, solar financing options, and the state’s policy and regulatory framework. Additionally, the project found that schools will be key partners for future community-scale solar programs. In addition to being excellent hosts for solar arrays, schools have the opportunity to use the installation of a solar array to develop educational materials and curricula to educate Montana’s future leaders about these technologies, which can be shared and replicated across the state. Project activities laid a clear path forward for solar energy in Montana. Certain activities have concrete next steps. For example, numerous solar arrays were designed for schools and other public buildings around the state. Many of those designs will be used as soon as funding becomes available. Other activities have less developed next steps, though lay the foundation for future work. The solar market assessment, solar market research, and community stakeholder meetings are good examples. These documents can be used as stepping stones to increase renewable energy education, increase stakeholder outreach, and support communities as they seek to develop community-scale solar projects.

14 SOLAR ENERGY↗
DOE OSTI2022

Geometry, Disorder and Phase Transitions in Topological States of Matter

The quantum Hall effect is the birthplace of topological states of matter, a major theme at the forefront of condensed matter physics in the past two decades. The fractional quantum Hall (FQH) effect revolutionized our understanding of phases of electronic matter. FQH states support exotic fractionally charged excitations that obey Abelian or non-Abelian fractional statistics, which are topological excitations that result from the underlying topological order. During this project, our group discovered a previously unrecognized geometric degree of freedom of incompressible FQH states and studied that for a variety of gapped FQH states. We brought this new concept into direct contact with experiments for the first time by generalizing it to Fermi-liquid states of composite fermions. Using the newly formulated powerful infinite Density Matrix Renormalization Group method, our numerical calculations yielded a parameter free prediction that was found to be in excellent agreement with experimental findings on electron systems in semiconductor heterostructures. In parallel, we performed extensive numerical studies on different, competing phases at various Landau level filling factors, and quantum phase transitions that result from such a competition, e.g. Abelian-non-Abelian phase transitions in bilayer systems. We studied geometrical excitations dubbed “gravitons” (because of their analogy with excitations in the theory of gravitation) and ways to excite and detect them, and explored how they couple with topological excitations. In graphene-based chiral materials, we realized the ability to tune through different incompressible and compressible states in a single Landau level, and found appropriate experimental parameters for the exploration of universal Luttinger liquid behavior not obtained in semiconductor-based electron systems. We showed that topological systems had a very different response from nontopological systems to strong disorder (many-body localization) as well as periodic drives.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

I Know I'm Right, But Does My Phone?

Transportation is the largest source of green-house gas emissions in the United States. Reducing transportation emissions depends on human travel behavior, which relies on local land use and planning. Travel diaries, consisting of sequences of trips between places for a particular individual, are typically used to instrument human travel behavior. However, these diaries are only as accurate as the underlying methods used to construct them. Travel diary algorithms have been a popular research topic since the advent of GPS tracking surveys. Mode inference algorithms in particular have been well represented in literature. However, these algorithms have typically been validated using prompted recall of pre-segmented trips, which doesn't account for segmentation error, thus disregarding the continuity of mode inference. Furthermore, phone operating systems and applications have adopted battery-conserving techniques, but we are not aware of prior work that has characterized the resulting data collection errors or evaluated procedures to mitigate them. We introduce a framework to evaluate accuracy of trip length computations and mode inference. We develop a temporal alignment procedure in analyzing continuous mode-segmented trajectories for groups of trips. We then apply our framework to evaluate an example set of travel diary algorithms from the open-source OpenPATH travel diary platform against MobilityNet, a public dataset containing information from three artificial timelines that cover 15 different travel modes. Our results show that inference based on an integration with map features results in weighted F_1 scores of 0.60 (iOS) and 0.74 (android). We also show that OpenPATH tends to under count trip length, with mean of signed relative error of -0.0438 on android and -0.0704 on iOS. We hope that other travel diary algorithms will be evaluated using this standardized process, and that the results used to understand and improve the state-of-the-art in this field.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗