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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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DOE OSTI2023

A Design of Activity-Based Mobility Intervention

Human mobility influences our society and vice versa. During the COVID-19 pandemic, non-pharmaceutical intervention that alters activity-based mobility such as work-from-home greatly impacted human mobility patterns. Many studies on developing mitigation strategies have employed or implemented their own mobility intervention within their model assumption. For fair evaluation between intervention strategies across models, it is significant to set up compatible experimental environments. However, it is difficult to apply the identical intervention to different kinds of models and compare their effectiveness because each model might have different assumptions, capabilities, and implementations. Even if one can apply intervention to heterogeneous models, it may produce undesirable artifacts due to difference of models and integration with intervention. Therefore, minimizing undesirable artifacts and facilitating intervention experiments across heterogeneous models are substantial. Taking this into account, this paper investigates a design of activity-based mobility intervention (ABMI). We define ABMI together with related concepts and develop an extensible data model and schema of ABMI based on the 5W1H method that can be used in different models. As a case study, we apply the ABMI model to a micro-simulation to demonstrate the usability of the proposed model. We expect that standardized ABMI and interfaces may help to streamline development and experiments of intervention strategies across heterogeneous models.

Kim, Joon-Seok↗
DOE OSTI2020

Bioscience COVID Rapid Response Report

The COVID-19 disease outbreak and its impact on global health and economies have highlighted the national security threat posed by pathogens with pandemic potential and the need for rapid development of effective diagnostics and medical countermeasures. The Bioscience IA selected for funding rapid COVID LDRD project proposals that addressed critical R&D gaps in pandemic response that could be accomplished in 1-3 months with the requested funding. In total, the Bioscience IA funded nine rapid projects that addressed 1) rapid and accurate methods for SARS-CoV-2 RNA detection, 2) modeling tools to help prioritize populations for diagnostic testing, 3) bioinformatic tools to track SARS-CoV-2 genomic sequence changes over time, 4) molecular inhibitors of SARS-CoV-2 cellular infection, and 5) method for rapid staging of COVID19 disease to enable administration of more effective treatments. In addition, LDRD funded one larger project to be completed in FY21 that leverages Sandia capabilities to address the need for platform diagnostics and therapeutics that can be rapidly tailored against emerging pathogen targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The temperature-dependent conformational ensemble of SARS-CoV-2 main protease (M pro )

The COVID-19 pandemic, instigated by the SARS-CoV-2 coronavirus, continues to plague the globe. The SARS-CoV-2 main protease, or M pro , is a promising target for the development of novel antiviral therapeutics. Previous X-ray crystal structures of M pro were obtained at cryogenic temperature or room temperature only. Here we report a series of high-resolution crystal structures of unliganded M pro across multiple temperatures from cryogenic to physiological, and another at high humidity. We interrogate these data sets with parsimonious multiconformer models, multi-copy ensemble models, and isomorphous difference density maps. Our analysis reveals a perturbation-dependent conformational landscape for M pro , including a mobile zinc ion interleaved between the catalytic dyad, mercurial conformational heterogeneity at various sites including a key substrate-binding loop, and a far-reaching intramolecular network bridging the active site and dimer interface. Our results may inspire new strategies for antiviral drug development to aid preparation for future coronavirus pandemics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A protective and broadly binding antibody class engages the influenza virus hemagglutinin head at its stem interface

ABSTRACT Influenza infection and vaccination impart strain-specific immunity that protects against neither seasonal antigenic variants nor the next pandemic. However, antibodies directed to conserved sites can confer broad protection. Here, we identify and characterize a class of human antibodies that engage a previously undescribed, conserved epitope on the influenza hemagglutinin (HA) protein. Prototype antibody S8V1-157 binds at the normally occluded interface between the HA head and stem. Antibodies to this HA head–stem interface epitope are non-neutralizingin vitrobut protect against lethal influenza infection in mice. These antibodies bind to most influenza A subtypes and seasonal human variants, and are present at low frequencies in the memory B cell populations of multiple human donors. Vaccines designed to elicit these antibodies might contribute to “universal” influenza immunity. IMPORTANCE Antibodies to the influenza virus hemagglutinin (HA) protein confer the strongest protection against infection. Human antibodies elicited by infection and/or vaccination fail to protect against antigenically novel animal, pandemic, or human seasonal viruses. Improved vaccines are needed. We identify a novel class of antibodies that bind most divergent HA subtypes and all seasonal human HA antigenic variants tested. These antibodies confer protection from lethal influenza challenge in animal models. The corresponding epitope on the HA head is occluded by its interaction with the stem and is inaccessible in the well-resolved prefusion state. The immunogenicity of this head–stem interface indicates that poorly understood conformations of HA presenting widely conserved surfaces are explored in biochemical, cell-based, andin vivoassays. Head–stem interface antibodies warrant further investigation as an avenue to improve influenza vaccines and therapeutics.

Microbiology↗
DOE OSTI2020

Chaos, percolation and the coronavirus spread: a two-step model

We discuss a two-step model for the rise and decay of a new coronavirus (Severe Acute Respiratory Syndrome-CoV-2) first reported in December 2019, COVID-19. The first stage is well described by the same equation for turbulent flows, population growth and chaotic maps: a small number of infected, d 0 , grows exponentially to a saturation value, d ∞ . The typical growth time (aggressive spreading of the virus) is given by τ = 1/λ where λ is the Lyapunov exponent. After a time t crit determined by social distancing and/or other measures, the spread decreases exponentially analogous to nuclear decays and non-chaotic maps. Some countries, like China, S. Korea and Italy, are in this second stage while others including the USA are near the end of the growth stage. The model predicted 15,000 (±2250) casualties for the Lombardy region (Italy) at the end of the spreading around May 10, 2020. Without the quarantine, the casualties would have been more than 50,000, one hundred days after the start of the pandemic. Here, the data from the 50 US states are of very poor quality because of an extremely late and confused response to the pandemic, resulting unfortunately in a large number of casualties, more than 70,000 on May 6, 2020, and more than 170,000 on August 21, 2020. S. Korea, notwithstanding the high population density (511/km 2 ) and the closeness to China, responded best to the pandemic with 255 deceased as of May 6, 2020, and 301 on August 21, 2020.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Development of Large Scale Extrusion Deposition for Structural Applications

Large Scale Extrusion Deposition (LSED) is an evolving additive manufacturing (AM) technology that research, such as that taking place at Oak Ridge National Laboratory (ORNL) and companies like Local Motors, are continuing to utilize and develop new applications. A major LSED application of interest has been molds and tooling as it allows for much shorter production time and lower cost. However, interest has been expanding into using LSED for more structural applications due to more frequent use of high performing polymer composites as feedstock. The use of LSED for structural applications is of particular interest to Local Motors as it is currently being used to create commercially viable, energy efficient electric vehicles. LSED offers a unique opportunity when compared to traditional manufacturing methods as it can significantly reduce the number of components necessary, while decreasing embodied energy and carbon emissions. Even with these benefits however, it is important that LSED is properly understood from a structural aspect as this field has not been as heavily researched as tooling. To ensure a high level of safety and repeatability is an essential responsibility of a manufacturer whose products are structural in nature. As such it is important to understand the materials and LSED process to make structural objects that the manufacturer can be confident in. The main goals of this project were to: develop and investigate materials that are of interest for structural LSED applications, further develop and understand the current machines used in LSED and develop simulations tools of LSED and the mechanical properties of the created structure. Material development focused on composite materials that have high mechanical properties and are stable in a variety of environments. The materials were tested to determine their as printed mechanical and thermal properties as these are necessary for simulations. Once the materials were investigated thoroughly, it allowed for simulations to be performed to compare to experimental data with simulations. Materials were also vetted to determine candidates for multi-material printing. The machine development focused around the areas of process monitoring, non-destructive evaluation, and quality control. Finally, the goal of the simulations was to develop a realistic model of printed structures, including in-process simulation and dynamic simulation. The routes to get to some of these goals and the depth in which they were investigated changed throughout the project due to personnel changes and the COVID-19 pandemic. This project resulted in many valuable results such as the development of an nondestructive evaluation (NDE) technique for interlayer defects, proof of simulation for warpage in simple parts, the development and utilization of a profilometer to monitor a print for defects or inconsistencies, thorough investigation of a material used commercially for structural LSED applications and valuable experimental data on the applicability and advantages of multi-material crush structures versus their neat counterparts by creation and testing of samples.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Forecasting Multi-Wave Epidemics Through Bayesian Inference

We present a simple, near-real-time Bayesian method to infer and forecast a multiwave outbreak, and demonstrate it on the COVID-19 pandemic. The approach uses timely epidemiological data that has been widely available for COVID-19. It provides short-term forecasts of the outbreak’s evolution, which can then be used for medical resource planning. The method postulates one- and multiwave infection models, which are convolved with the incubation-period distribution to yield competing disease models. The disease models’ parameters are estimated via Markov chain Monte Carlo sampling and information-theoretic criteria are used to select between them for use in forecasting. The method is demonstrated on two- and three-wave COVID-19 outbreaks in California, New Mexico and Florida, as observed during Summer-Winter 2020. We find that the method is robust to noise, provides useful forecasts (along with uncertainty bounds) and that it reliably detected when the initial single-wave COVID-19 outbreaks transformed into successive surges as containment efforts in these states failed by the end of Spring 2020.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

COVID-19 Testing R&D (Final Report)

Eleven Labs within the US Department of Energy (DOE), National Virtual Biotechnology Laboratory (NVBL), came together as a team to address significant R&D gaps in COVID-19 testing. Beginning in March 2020, the NVBL COVID Testing Team developed an R&D agenda, worked with DOE and other agencies to set priorities, and collaborated to deliver timely results. Priority was given to quick implementation as well as development of novel capabilities for immediate and evolving pandemic needs without placing additional burden on operational performers. Priority elements capitalized on DOE National Laboratory strengths and expertise. The Team delivered: testing and evaluation that enabled decisions on testing options, forwardleaning approaches to prepare for future scale-up needs, and models and experiments that supported prioritization of diagnostic and therapeutic candidates.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Sweden surpasses the UNAIDS 95-95-95 target: estimating HIV-1 incidence, 2003 to 2022

Background: Sweden reached the UNAIDS 90–90–90 target in 2015. It is important to reassess the HIV epi- demiological situation due to ever-changing migration patterns, the roll-out of PrEP and the impact of the COVID-19 pandemic. Aim: We aimed to assess the pro- gress towards the UNAIDS 95–95–95 targets in Sweden by estimating the proportion of undiagnosed people with HIV (PWHIV) and HIV incidence trends. Methods: We used routine laboratory data to inform a biomarker model of time since infection. When available, we used previous negative test dates, arrival dates for PWHIV from abroad and transmission modes to inform our incidence model. We also used data collected from the Swedish InfCareHIV register on antiretroviral therapy (ART). Results: The yearly incidence of HIV in Sweden decreased after 2014. In part, this was because the fraction of undiagnosed PWHIV had decreased almost twofold since 2006. After 2015, three of four PWHIV in Sweden were diagnosed within 1.9 and 3.2 years after infection among men who have sex with men and in heterosexual groups, respectively. While 80% of new PWHIV in Sweden acquired HIV before immigration, they make up 50% of the current PWHIV in Sweden. By 2022, 96% of all PWHIV in Sweden had been diag- nosed, and 99% of them were on ART, with 98% virally suppressed. Conclusions: By 2022, about half of all PWHIV in Sweden acquired HIV abroad. Using our new biomarker model, we assess that Sweden has reached the UNAIDS goal at 96–99–98.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Persistent high PM 2.5 pollution driven by unfavorable meteorological conditions during the COVID-19 lockdown period in the Beijing-Tianjin-Hebei region, China

Lockdown measures to curtail the COVID-19 pandemic in China halted most nonessential activities on January 23, 2020. Despite significant reductions in anthropogenic emissions, the Beijing-Tianjin-Hebei (BTH) region still experienced high air pollution concentrations. In this work, employing two emissions reduction scenarios, the Community Multiscale Air Quality (CMAQ) model was used to investigate the PM 2.5 concentrations change in this region. The model using the scenario (C3) with greater traffic reductions performed better compared to the observed PM 2.5 . Compared with the no reductions base-case (scenario C1), PM 2.5 reductions with scenario C3 were 2.70, 2.53, 2.90, 2.98, 3.30, 2.81, 2.82, 2.98, 2.68, and 2.83 µg/m 3 in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai, respectively. During high-pollution days in scenario C3, the percentage reductions in PM 2.5 concentrations in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai were 3.76, 3.54, 3.28, 3.22, 3.57, 3.56, 3.47, 6.10, 3.61, and 3.67%, respectively. However, significant increases caused by unfavorable meteorological conditions counteracted the emissions reduction effects resulting in high air pollution in BTH region during the lockdown period. This study shows that effective air pollution control strategies incorporating these results are urgently required in BTH to avoid severe pollution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Italian Summer Students Program at Fermilab and other US Laboratories: 40 years of education in particle physics and technology

Since 1983 the Italian groups collaborating with Fermilab (US) have been running a 2-month summer training program for Master students. While in the first year the program involved only 4 physics students, in the following years it was extended to engineering students. Many students have extended their collaboration with Fermilab with their Master Thesis and PhD. The program has involved more than 600 Italian students from more than 20 Italian universities. Each intern is supervised by a Fermilab Mentor responsible for the training program. Training programs spanned from Tevatron, CMS, Muon (g-2), Mu2e and SBN (MicroBooNE, Icarus, and SBND) and DUNE design and data analysis, development of particle detectors, design of electronic and accelerator components, development of infrastructures and software for tera-data handling, quantum computing and research on superconductive elements and accelerating cavities. In 2015 the University of Pisa included the program within its own educational programs. Summer Students are enrolled at the University of Pisa for the duration of the internship and at the end of the internship they write summary reports on their achievements. After positive evaluation by a University of Pisa Examining Board, interns are acknowledged 6 ECTS credits for their Diploma Supplement. The program was paused in 2020 and 2021 due to the COVID-19 pandemic, but it resumed in 2022. From 2022 to 2024, a total of 60 students participated in the nine-week training at Fermilab. We are currently organizing the 2025 program. This paper provides an overview of the program, which can serve as a model for other interested laboratories.

Barzi, Emanuela [Ohio State U.]↗
DOE OSTI2021

Evidence of Completion of Milestone 3: Experimental Testbed

Construction and deployment of the experimental testbed encountered scheduling delays, and completion was subsequently further delayed by curtailment of LANL operations due to the COVID–19 pandemic. Between March and October, LANL was in a state of “Limited Operations” such that only certain “mission–critical” work was performed with approximately 25% on–site staffing. In spite of this, much of the lab space preparation was executed and the five initial model house” units were constructed and installed during this period. Still, the pace of construction was impacted by difficulty in coordinating personnel and minimizing contact between workers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Iron at the Air-Sea Interface (Final Report)

Workshop: Seventy-four scientists from twenty-three countries registered to participate and to present their experimental, modeling, and remote sensing studies related to atmospheric supply and speciation of aerosol iron (Fe), its contribution to the dissolved Fe inventory of the ocean, and its potential impacts on primary production and CO 2 uptake. Due to travel restrictions related to the ongoing pandemic, the meeting was conducted in a hybrid mode. The in-person portion of the meeting was held in Asheville, North Carolina and the online participants were able to join using two streaming platforms. The objective of this workshop was to address the most urgent open science questions for improved quantification of Fe at the air-sea interface. Iron is required for the growth of phytoplankton. The availability of iron can limit the growth of phytoplankton and thus the overall productivity of the marine ecosystem. Therefore, the atmospheric supply of iron to the surface oceans may play a key role in regulating biological productivity, atmospheric carbon dioxide (CO 2 ) concentrations, and possibly climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Challenges of COVID-19 Case Forecasting in the US, 2020–2021

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub ( https://covid19forecasthub.org ). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1–4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Earth's record-high greenness and its attributions in 2020

Terrestrial vegetation is a crucial component of Earth's biosphere, regulating global carbon and water cycles and contributing to human welfare. Despite an overall greening trend, terrestrial vegetation exhibits a significant inter-annual variability. The mechanisms driving this variability, particularly those related to climatic and anthropogenic factors, remain poorly understood, which hampers our ability to project the long-term sustainability of ecosystem services. Here, in this work, by leveraging diverse remote sensing measurements, we pinpointed 2020 as a historic landmark, registering as the greenest year in modern satellite records from 2001 to 2020. Using ensemble machine learning and Earth system models, we found this exceptional greening primarily stemmed from consistent growth in boreal and temperate vegetation, attributed to rising CO 2 levels, climate warming, and reforestation efforts, alongside a transient tropical green-up linked to the enhanced rainfall. Contrary to expectations, the COVID-19 pandemic lockdowns had a limited impact on this global greening anomaly. Our findings highlight the resilience and dynamic nature of global vegetation in response to diverse climatic and anthropogenic influences, offering valuable insights for optimizing ecosystem management and informing climate mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures

Enumerated threat agent lists have long driven biodefense priorities. The global SARS-CoV-2 pandemic demonstrated the limitations of searching for known threat agents as compared to a more agnostic approach. Recent technological advances are enabling agent-agnostic biodefense, especially through the integration of multi-modal observations of host-pathogen interactions directed by a human immunological model. Although well-developed technical assays exist for many aspects of human-pathogen interaction, the analytic methods and pipelines to combine and holistically interpret the results of such assays are immature and require further investments to exploit new technologies. In this manuscript, we discuss potential immunologically based bioagent-agnostic approaches and the computational tool gaps the community should prioritize filling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Vaccine-Associated Enhanced Respiratory Disease following Influenza Virus Infection in Ferrets Recapitulates the Model in Pigs

Influenza A virus (IAV) causes respiratory disease in swine and humans. Vaccines are used to prevent influenza illness in both populations but must be frequently updated due to rapidly evolving strains. Mismatch between the circulating strains and the strains contained in vaccines may cause loss of efficacy. Whole inactivated virus (WIV) vaccines with adjuvant, utilized by the swine industry, are effective against antigenically similar viruses; however, vaccine-associated enhanced respiratory disease (VAERD) may happen when the WIV is antigenically mismatched with the infecting virus. VAERD is a repeatable model in pigs, but had yet to be experimentally demonstrated in other mammalian species. We recapitulated VAERD in ferrets, a standard benchmark animal model for studying human influenza infection, in a direct comparison to VAERD in pigs. Both species were vaccinated with WIV with oil-in-water adjuvant containing a d -1 H1N2 (1B.2.2) derived from the pre-2009 human seasonal lineage, then challenged with a 2009 pandemic H1N1 (H1N1pdm09, 1A.3.3.2) 5 weeks after vaccination. Nonvaccinated and challenged groups showed typical signs of influenza disease, but the mismatched vaccinated and challenged pigs and ferrets showed elevated clinical signs, despite similar viral loads. VAERD-affected pigs exhibited a 2-fold increase in lung lesions, while VAERDaffected ferrets showed a 4-fold increase. Similar to pigs, antibodies from VAERD-affected ferrets preferentially bound to the HA2 domain of the H1N1pdm09 challenge strain. These results indicate that VAERD is not limited to pigs, as demonstrated here in ferrets, and the need to consider VAERD when evaluating new vaccine platforms and strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Impact of Proton Activity on Fuel-Cell Performance (CRADA Final Report)

The key attribute that is being investigated is the dependence of the oxygen-reduction and hydrogen-oxidation reaction kinetics on proton activity. The influence of proton activity on the kinetics is also important in the determination of limiting factors that impact overall fuel-cell performance. At lower humidities, which are required to simplify fuel-cell water and thermal management (especially for higher-temperature operation) and enable next generation fuel cells, the ionomer water content will be different than that in today’s fuel cells. Such changes in water content directly impact the activity and concentration of protons. Thus, it is necessary to quantify this impact of proton activity on the reaction kinetics, and to determine means to mitigate any detrimental impacts to enable high performance. To realize the above goals of understanding the intrinsic interactions of proton activity on hydrogen-oxidation and oxygen-reduction kinetics, systematic investigations were carried out and a novel technique, a rapid microelectrode with environmental control, was realized. The experimental campaign at LBNL worked alongside that of TokyoTech and both were complemented by mathematical modeling of the key phenomena. The results demonstrated a robust method to analyze the kinetic behavior and an impact of proton activity, although greater delineation in terms of ion concentration versus activity was not obtained fully due in part to limited lab access during the COVID pandemic.

30 DIRECT ENERGY CONVERSION↗