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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Tea ( Camellia sinensis ) Extract-Mediated Green Synthesis of Co 3 O 4 and Co 3 O 4 @Graphene Nanocomposites for Multifunctional Applications in Pollutant Degradation, Sensing, and Energy Storage

A novel solution-mixing method was proposed to synthesize Co 3 O 4 /graphene nanocomposites (Co 3 O 4 @Gr) using a green tea leaf (Camellia sinensis) extract as the reducing agent. XRD analysis shows that the as-prepared Co 3 O 4 @Gr exhibits a cubic spinel crystal structure. From morphological analysis, the obtained Co 3 O 4 NS forms spherical clusters that are uniformly distributed on the graphene surface. FT-IR and Raman analyses confirmed the strong molecular and vibrational interactions between the Co 3 O 4 NS and Gr. The suppressed PL intensity peak of the Co 3 O 4 @Gr NCs indicated significant inhibition in the recombination of charge carriers between the hybrid orbitals within the composites. As a result, the catalytic efficiency of Co 3 O 4 @Gr NCs increased to 80% compared to pristine Co 3 O 4 , which exhibited only 45% efficiency against methylene blue (MB) dye. Moreover, the as-prepared NCs exhibited a detection limit of 0.01−224 μM, demonstrating a superior low-DPA detection with high sensitivity. The Co 3 O 4 @Gr/GCE exhibits admirable selectivity for various pesticides, fungicides, and metal ions, with outstanding reproducibility and stability. From electrochemical investigations, the highest specific capacitance values of the as-synthesized Co 3 O 4 @Gr were 349 F/g at a scan rate of 5 mV/s and 158 F/g at a current density of 1 A/g.

Capacitors↗
DOE OSTI2020

Direct Measure of Electrode Spatial Heterogeneity: Influence of Processing Conditions on Anode Architecture and Performance

The spatial (in)homogeneity of aqueous processed silicon electrodes using standard poly(acrylic acid)-based binders and slurry preparation conditions is demonstrated in this work. X-ray nanotomography shows segregation of materials into submicron-thick layers depending on the mixing method and starting binder molecular weights. Using a dispersant, or in situ production of dispersant from the cleavage of the binder into smaller molecular weight species, increases the resulting lateral homogeneity while drastically decreasing the vertical homogeneity as a result of sedimentation and separation due to gravitational forces. This data explains some of the variability in the literature with respect to silicon electrode performance and demonstrates two potential ways to improve slurry-based electrode fabrications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

In Situ Structural Observation of a Substrate- and Peroxide-Bound High-Spin Ferric-Hydroperoxo Intermediate in the P450 Enzyme CYP121

The P450 enzyme CYP121 from Mycobacterium tuberculosis catalyzes a carbon–carbon (C–C) bond coupling cyclization of the dityrosine substrate containing a diketopiperazine ring, cyclo(l-tyrosine-l-tyrosine) (cYY). An unusual high-spin (S = 5/2) ferric intermediate maximizes its population in less than 5 ms in the rapid freeze-quenching study of CYP121 during the shunt reaction with peracetic acid or hydrogen peroxide in acetic acid solution. Here, we show that this intermediate can also be observed in the crystalline state by EPR spectroscopy. By developing an on-demand-rapid-mixing method for time-resolved serial femtosecond crystallography with X-ray free-electron laser (tr-SFX-XFEL) technology covering the millisecond time domain and without freezing, we structurally monitored the reaction in situ at room temperature. After a 200 ms peracetic acid reaction with the cocrystallized enzyme–substrate microcrystal slurry, a ferric-hydroperoxo intermediate is observed, and its structure is determined at 1.85 Å resolution. The structure shows a hydroperoxyl ligand between the heme and the native substrate, cYY. The oxygen atoms of the hydroperoxo are 2.5 and 3.2 Å from the iron ion. The end-on binding ligand adopts a near-side-on geometry and is weakly associated with the iron ion, causing the unusual high-spin state. This compound 0 intermediate, spectroscopically and structurally observed during the catalytic shunt pathway, reveals a unique binding mode that deviates from the end-on compound 0 intermediates in other heme enzymes. The hydroperoxyl ligand is only 2.9 Å from the bound cYY, suggesting an active oxidant role of the intermediate for direct substrate oxidation in the nonhydroxylation C–C bond coupling chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Efficient DNA sequence compression with neural networks

Abstract Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

Silva, Milton↗
DOE OSTI2021

Octupole correlations near Te 110

The lifetime of the 2 + and 9 – , 11 – , 13 – , 15 – states in the neutron-deficient 110 Te was measured for the first time using the recoil distance Doppler shift technique. The reported value of the reduced transition probability B(E2; $0$$^{+}_{g.s}$ → 2 + ) = 4.3(8) × 10 3 e 2 fm 4 supports the systematic for even-mass Te isotopes and was interpreted in the framework of the large-scale shell model and cranked shell model calculations. The measured reduced transition probabilities in the negative-parity yrast band revealed the upward trend towards the high spins. Furthermore, the enhanced collectivity is discussed in terms of the tilted axis cranking approach and the symmetry configuration mixing method with the Gogny D1S interaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Interpolating between small- and large-$\mathscr{g}$ expansions using Bayesian model mixing

Bayesian model mixing (BMM) is a statistical technique that can be used to combine models that are predictive in different input domains into a composite distribution that has improved predictive power over the entire input space. We explore the application of BMM to the mixing of two expansions of a function of a coupling constant $\mathscr{g}$ that are valid at small and large values of $\mathscr{g}$ respectively. This type of problem is quite common in nuclear physics, where physical properties are straightforwardly calculable in strong and weak interaction limits or at low and high densities or momentum transfers, but difficult to calculate in between. Interpolation between these limits is often accomplished by a suitable interpolating function, e.g., Padé approximants, but it is then unclear how to quantify the uncertainty of the interpolant. We address this problem in the simple context of the partition function of zero-dimensional Φ 4 theory, for which the (asymptotic) expansion at small $\mathscr{g}$ and the (convergent) expansion at large $\mathscr{g}$ are both known. We consider three mixing methods: linear mixture BMM, localized bivariate BMM, and localized multivariate BMM with Gaussian processes. Here, we find that employing a Gaussian process in the intermediate region between the two predictive models leads to the best results of the three methods. The methods and validation strategies we present here should be generalizable to other nuclear physics settings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Coulomb excitation of 102 Ru with 12 C and 16 O

Here, the Coulomb excitation of 102 Ru was performed with beams of 12 C and 16 O ions. The beam particles scattered at forward angles were momentum analyzed with a magnetic spectrograph. The resolution achieved enabled the populations of the $2^{+}_{1}$ state, the unresolved $2^{+}_{2}$/ $4^{+}_{1}$, and $2^{+}_{4}$/$3^{-}_{1}$, doublets of states, and the $3^{-}_{2}$ state to be determined as a function of the scattering angle. These populations are compared with gosia calculations, yielding B(E2; $2^{+}_{1}$→$0^{+}_{1}$) = 41.5 ± 2.3 W.u., B(E2; $2^{+}_{2}$→$0^{+}_{1}$) = 1.75 ± 0.11 W.u., B(E3; $3^{-}_{1}$→$0^{+}_{1}$) = 31.5 ± 3.5 W.u., and B(E3; $3^{-}_{2}$→$0^{+}_{1}$) = 6.8 ± 0.5 W.u. The B(E3; $3^{-}_{1}$→$0^{+}_{1}$) value is significantly larger than previously measured. The weakly populated $2^{+}_{3}$ state, presumed to be a member of the band built on the $0^{+}_{2}$ state, was observed clearly for a single angle only, and a fit to its population results in B(E2; $2^{+}_{3}$→$0^{+}_{1}$) = 0.053 ± 0.011 W.u. Using the known γ -ray branching ratios for the $2^{+}_{3}$ level, the B(E2; $2^{+}_{3}$→$0^{+}_{2}$) value is calculated to be 18 ± 4 W.u., substantially less than the B(E2; $2^{+}_{1}$→$0^{+}_{1}$) . This suggests that the deformation of the $0^{+}_{2}$ state is lower than that of the $0^{+}_{1}$ state. The results are compared with beyond-mean-field calculations with the Gogny-D1S interaction using the symmetry-conserving configuration-mixing method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Designing Remote Monitoring for Smart Manufacturing Facilities: Hazard Identification and Classification

This study investigates the process of hazard identification in complex manufacturing environments during the design phase, emphasizing the significance of the design process in developing designs that effectively mitigate hazards in contexts with numerous variables, such as a variety of machines, sensors, actuators, and agents. Through a mixed-methods approach, the objective of this work is to understand how the evolution of design outcomes across various stages might influence a designer’s ability to recognize both standard and novel hazards. To achieve this understanding, an experimental design task was conducted with six designers from a national lab specializing in manufacturing technologies. This approach combined qualitative and quantitative data analysis from a one-hour virtual session with participants. Findings suggest that the complexity of identifying hazards in a high-dimensional design space is challenging within a limited time frame and that the identification of hazards is significantly influenced by the stage of the design task and the initial design decisions, indicating the need for extended time and strategic initial planning in the design process to enhance hazard identification.

Ballestas, Caseysimone↗
DOE OSTI2020

Necessary and sufficient conditions for resonant mixing of plane waves in elastic solids with quadratic nonlinearity

This paper studies the interactions of two plane waves in elastic solids with quadratic nonlinearity. In particular, the necessary and sufficient conditions for resonant mixing of two plane waves are derived. It is shown that the conventional resonance condition for resonant mixing of plane waves is only a necessary condition, not sufficient. Based on the newly derived necessary and sufficient conditions, resonant mixing of various types of plane waves are investigated and specific conditions for generating a resonant mixed wave are obtained for each case. These results are useful for developing nonlinear ultrasonic nondestructive evaluation techniques using the wave mixing method.

Gao, Xiang↗
DOE OSTI2021

Estimating the Value of Automation for Concentrating Solar Power Industry Operations (Final Report)

This report summarizes findings from a small, mixed-method research study examining industry perspectives on the potential for new forms of automation to invigorate the concentrating solar power (CSP) industry. In Fall 2021, the Solar Energy Technologies Office (SETO) of the United States Department of Energy (DOE) funded Sandia National Laboratories to elicit industry stakeholder perspectives on the potential role of automated systems in CSP operations. We interviewed eleven CSP professionals from five countries, using a combination of structured and open comment response modes. Respondents indicated a preference for automated systems that support heliostat manufacturing and installation, calibration, and responsiveness to shifting weather conditions. This pilot study demonstrates the importance of engaging industry stakeholders in discussions of technology research and development, to promote adoptable, useful innovation.

14 SOLAR ENERGY↗
DOE OSTI2025

Equity-Centered Engagement Through Climate Resilience Policy in Massachusetts

Communities who experience disproportionate climate change impacts tend to be excluded from resilience planning (Vale, 2014). Those efforts typically follow top-down processes within established governance practices that are inaccessible to marginalized folks and reinforce inequalities (Malloy & Ashcraft, 2020; Adger, 2003). Such participatory planning processes may offer the public little opportunity to influence the process itself or the outcomes (Smith & McDonough, 2001). They might ignore important public values or alternative ways of knowing which can be critical assets in resilience (Few et al., 2007). Designing communities for climate action and resilience means creating opportunities for everyone to meaningfully shape those decisions and experience related benefits. Having the opportunity to shape one’s community is necessary for human flourishing (Allen, 2016). Resilience planning that shifts power into communities and focuses on social vulnerability can affect how people survive and thrive in a climate changed world. The Massachusetts Municipal Vulnerability Preparedness (MVP) 2.0 program is an attempt to change the status quo in resilience planning by bringing new voices into decision-making power, recognizing their labor, addressing root causes of vulnerability, and investing in social infrastructure. It aspires to build capacity for equity-focused community engagement within teams of municipal staff and community liaisons, and ultimately build social capital and community cohesion. My mixed methods research investigates implementation of this state grant program in several western Massachusetts towns. I am using document review, participant observation, and interviews to understand the MVP 2.0 process as written, how different towns navigate it, and how individuals make sense of their experiences in it. I seek to understand how those experiences explain relationships between engagement approaches, mediating factors, and process outcomes. I am interested in the conditions that allow for community empowerment and how a model like MVP 2.0 can shift conditions that hold systems in place. In a practical sense, our findings will help municipalities reflect on their work during MVP 2.0 and plan for future community engagement. They may be informative for designing future iterations of the MVP program and for other municipalities, offices of community engagement, and practitioners. The findings will also contribute to the participation, resilience, and climate justice literatures, by adding perspectives on equity-centered resilience and community engagement approaches in smaller towns and rural settings. References: Adger, W. N. (2003). Social capital, collective action, and adaptation to climate change. Economic Geography, 79, 387-404. Allen, D. (2016). Toward a connected society. Our compelling interests: The value of diversity for democracy and a prosperous society, 71-105. Few, R., Brown, K., & Tompkins, E. L. (2007). Public participation and climate change adaptation: avoiding the illusion of inclusion. Climate Policy, 7(1), 46–59. Malloy, J. T., & Ashcraft, C. M. (2020). A framework for implementing socially just climate adaptation. Climatic Change, 160(1), 1–14. Smith, P. D., & McDonough, M. H. (2001). Beyond public participation: Fairness in natural resource decision making. Society & natural resources, 14(3), 239-249. Vale, L. J. (2014). The politics of resilient cities: whose resilience and whose city? Building Research & Information, 42(2), 191–201.

Callaham, Shannon↗
DOE OSTI2025

Equity-Centered Engagement Through Climate Resilience Policy in Massachusetts

Resilience efforts tend to reinforce injustices. Communities who experience disproportionate climate impacts are often excluded from resilience planning, and those plans do not typically address root causes of social vulnerability. More transformational approaches to resilience would shift decision-making power into communities and affect how people survive and thrive in a climate changing world. The Massachusetts Municipal Vulnerability Preparedness (MVP) 2.0 program is an attempt to change the status quo in resilience planning by bringing new voices into decision-making power, recognizing their labor, addressing root causes of vulnerability, and investing in social infrastructure. It aims to build capacity for equity-focused community engagement within teams of municipal staff and community liaisons, and ultimately build community cohesion. My mixed methods research investigates implementation of this state grant program in several Massachusetts towns. I am using document review, participant observation, and interviews to understand the MVP 2.0 process as written, how different municipalities navigate it, and how individuals make sense of their experiences in it. I seek to understand how those experiences explain relationships between engagement approaches, mediating factors, and process outcomes. I am interested in the conditions that allow for community empowerment and how a model like MVP 2.0 can shift conditions that hold systems in place. In a practical sense, my empirical results will help municipalities reflect on their work during MVP 2.0 and plan for future community engagement. They may be informative for designing future iterations of the MVP program and for other municipalities, offices of community engagement, and practitioners. The findings will also contribute to the participation, resilience, and climate justice literatures, by adding perspectives on equity-centered resilience and community engagement approaches in smaller towns and rural settings.

Callaham, Shannon↗
DOE OSTI2022

How Management and Leadership Training Can Impact a Health System: Evaluation Findings From a Public Health Management Training Program in Cambodia

In 2017, the National Institute of Public Health in Cambodia collaborated with the U.S. Centers for Disease Control and Prevention to provide management and leadership training for 20 managers and senior staff from 10 health centers. We conducted a mixed methods evaluation of the program's outcomes and impact on the graduates and health centers. From June 2018 (baseline) to January 2019 (endpoint), we collected data from a competency assessment, observational visits, and interviews. From baseline to endpoint, all 20 participants reported increased competence in seven management areas. Comparing baseline and endpoint observational visits, we found improvements in leadership and governance, health workforce, water, sanitation, and hygiene, and health centers' use of medical products and technologies. When evaluating the improvements made by participants against the World Health Organization's key components of a well-functioning health system, the program positively contributed toward building four of the six components—leadership and governance, health information systems, human resources for health, and service delivery. While these findings are specific to the context of Cambodian health centers, we hope this evaluation adds to the growing body of research around the impact of skilled public health management on health systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Risk Inequality and the Food-Energy-Water (FEW) Nexus: A Study of 43 City Adaptation Plans

Goals aimed at adapting to climate change in sustainable and just ways are embedded in global agreements such as the Sustainable Development Goals and the New Urban Agenda. However, largely unexamined, are the ways that narrative understandings conveyed in adaptation plans consider and attempt to address inequality in climate risk to urban populations and FEW-systems. In this paper, we examine whether and how adaptation plans from C40 member cities address inequality in risk, by planning actions to reduce hazard exposure or tackling the drivers of social vulnerability. C40 is a network of 94 of the world's cities fostering policies to address climate change. We apply a mixed methods approach, including a discourse analysis and meta-analysis of adaptation plans. The discourse analysis helps to unpack framings of urban equity issues as they relate to policy actions, and the meta-analysis seeks to quantitatively investigate patterns of framing and policy across adaptation plans. Our findings suggest that FEW-nexus thinking is not yet embedded in narrative understandings of risk and planned adaptation actions, within the adaptation plans we studied. In the city adaptation plans we analyzed, we found multiple frames coexisting behind the broader adaptation visions (e.g., risk and resilience). Rather than converging, issues, and principles such as those of equality, coexist with economic issues in an imbalance of incongruent political movements and priorities. Techno-infrastructural and economic investments and concerns tend to take precedence over concerns and interests for inequality in climate risks. We discuss some of the institutional factors explaining this. Knowledge integration, for instance, is constrained by the existence of a plurality of sectors, levels of government, power, values, and ways of understanding and managing climate risk. We also suggest that the relatively low importance of equality considerations in the adaptation plans will likely limit the capacity of cities to support broader goals such as those of the New Urban Agenda and the Sustainable Development Goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Transforming Agricultural Productivity with AI-Driven Forecasting: Innovations in Food Security and Supply Chain Optimization

Global food security is under significant threat from climate change, population growth, and resource scarcity. This review examines how advanced AI-driven forecasting models, including machine learning (ML), deep learning (DL), and time-series forecasting models like SARIMA/ARIMA, are transforming regional agricultural practices and food supply chains. Through the integration of Internet of Things (IoT), remote sensing, and blockchain technologies, these models facilitate the real-time monitoring of crop growth, resource allocation, and market dynamics, enhancing decision making and sustainability. The study adopts a mixed-methods approach, including systematic literature analysis and regional case studies. Highlights include AI-driven yield forecasting in European hydroponic systems and resource optimization in southeast Asian aquaponics, showcasing localized efficiency gains. Furthermore, AI applications in food processing, such as plasma, ozone and Pulsed Electric Field (PEF) treatments, are shown to improve food preservation and reduce spoilage. Key challenges—such as data quality, model scalability, and prediction accuracy—are discussed, particularly in the context of data-poor environments, limiting broader model applicability. The paper concludes by outlining future directions, emphasizing context-specific AI implementations, the need for public–private collaboration, and policy interventions to enhance scalability and adoption in food security contexts.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1975

Validity of trace element cosmothermometer

A reply is made to previous criticisms of the claim that the range of accretion of ordinary chondrites can be narrowed to 500-420 K (from 560-405 K) using volatile metals as cosmothermometers. Questions concerning uncertainties in vapor pressure data, entropy of mixing, methods of analysis, uncertainties in condensation curves, metamorphic transport, alloy formation, condensation of Tl, condensation of In, and concordance with other thermometers (FeO contents of silicates) are addressed. It is concluded that the original claim is valid.

Anders, E.↗
NASA NTRS1987

Advances in flow visualization using liquid-crystal coatings

This paper discusses a new four-part mixing method for visualizing boundary layer flows, including transitions, separation, and shock locations, by the use of liquid-crystal coatings. The method controls the event temperature and color-play bandwidth best suited to specific experimental conditions, and is easily learned. The method is applicable almost throughout the altitude and speed ranges for subsonic aircraft flight envelopes, and is also applicable to supersonic flow visualization and for general use in high- and low-speed wind tunnel and water tunnel testing.

Holmes, Bruce J.↗
NASA NTRS1986

Improved silicon nitride for advanced heat engines

Silicon nitride is a high temperature material currently under consideration for heat engine and other applications. The objective is to improve the net shape fabrication technology of Si3N4 by injection molding. This is to be accomplished by optimizing the process through a series of statistically designed matrix experiments. To provide input to the matrix experiments, a wide range of alternate materials and processing parameters was investigated throughout the whole program. The improvement in the processing is to be demonstrated by a 20 percent increase in strength and a 100 percent increase in the Weibull modulus over that of the baseline material. A full characterization of the baseline process was completed. Material properties were found to be highly dependent on each step of the process. Several important parameters identified thus far are the starting raw materials, sinter/hot isostatic pressing cycle, powder bed, mixing methods, and sintering aid levels.

Yeh, H. C.↗