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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 OSTI2024

Nitrogen acquisition and retention pathways in sustainable perennial bioenergy grass cropping systems

Abstract Perennial tall grasses show promise as bioenergy crops due to high productivity and efficient nutrient use. Ongoing research on bioenergy grasses seeks to reduce their reliance on synthetic nitrogen (N) fertilizer, the manufacture of which relies on fossil fuel combustion. Excessive use of fertilizers also causes adverse environmental consequences and leads to the evolutionary loss of plant traits beneficial to sustainable N cycle. Notably, perennial tall grasses have exhibited the potential to maintain high biomass yield without the need for N fertilizer or causing soil N depletion. Perennial grasses can be adept at interacting with their microbial partners to facilitate N acquisition and retention via mechanisms such as biological N fixation and nitrification inhibition. These inherent N management traits should be preserved and optimized at the this early stage of bioenergy grass breeding programs. This review examines the impact of external N on bioenergy grass production and explores the potential of leveraging advantageous N‐cycling attributes of perennial tall grasses, laying groundwork for future management and research efforts. With minimized dependency on external N input, the cultivation of perennial energy grasses will pave the way toward more resilient agricultural systems and play a significant role in addressing key global energy and environmental challenges.

Agriculture↗

DOE OSTI2023

Laminar Burning Speed Measurements of Hydrogen/Natural Gas Mixtures

Abstract To address the shortage of fossil fuels and the environmental impact of exhaust emissions, research efforts in combustion seek to identify candidates for sustainable fuels. Hydrogen is an example, from which water is produced as the main combustion product. However, when used as neat hydrogen, it is very difficult to control hydrogen combustion due to its high flame speed, pre-ignition propensity, and flashback characteristics. One method to control hydrogen combustion is to blend it with a well-established fuel. Natural gas is a common fuel for use in engines or gas turbines. Natural gas is characterized by slow flame speeds and poor lean-burn ability; thus, engine power is decreased in the lean-burn region. Consequently, natural gas engines are typically operated at stoichiometric conditions to maximize output. Blending hydrogen to natural gas has several advantages: (i) Control of hydrogen’s ignition characteristics, (ii) extension of Natural gas’s lower flammability limit — making it easier to ignite, and (iii) reduced greenhouse gas emissions. In this study, the laminar burning speed (LBS) for neat natural gas and natural gas/hydrogen mixtures at 5 atm and 296 K were measured. Schlieren optical imaging was utilized to validate laminar flame conditions and further investigate the structure of natural gas/hydrogen flames. Results indicate that replacing 50% of natural gas with hydrogen increases the peak laminar burning velocity by a factor of ∼1.6 times. LBS simulations were conducted with NUI 1.1 and UCF NG/H2 mechanisms; Predictions by both mechanisms were found to be satisfactory for neat NG mixtures. However, for 50% NG/ 50% H2 mixture, the true LBS for fuel-lean conditions was under-predicted by both models, while predictions for fuel-rich conditions were satisfactory. Additionally, a literature review and similar experimental analysis will be performed for methane, ammonia, and hydrogen fuel blends to better understand the combustion phenomena of natural gas fuels.

Yovino, Louis↗

DOE OSTI2024

Sequential infiltration of two-photon polymerized 3D photonic crystals for mid-IR spectroscopic applications

Photonic crystals (PhCs) are spatially organized structures with lattice parameters equivalent to the operational wavelength of light. PhCs have been subject to extensive research efforts in the last two decades and are known for controlling light propagation with applications in sensing and time-delayed communication due to the slow-light phenomenon. Despite their exceptional properties, PhCs are difficult to fabricate using planar micromachining techniques due to their periodic structures. Techniques like two-photon stereolithography have been discussed for PhC fabrication in the literature, but the inherent disadvantage of poor refractive index (RI) contrast results in limited application. In this work, we present sequential infiltration synthesis performed on two-photon stereolithographically printed 3D PhCs for infiltration with zinc oxide to increase the RI of 3D PhCs. Further, finite element analysis was performed over a range of RI contrast values to study the change in photonic bandgap (PBG) with RI contrast. The transmission spectra were recorded on 3D PhCs before and after infiltration to demonstrate the change experimentally. An increase in the PBG width and absorbance is seen postinfiltration due to enhanced RI. This work presents the first, to our knowledge, sequentially infiltrated enhanced 3D PhC fabricated with two-photon stereolithography.

3D printing↗

DOE OSTI2022

Multifunctional fiber-reinforced composites for passive sensing and energy harvesting with enhanced mechanical performance

Fiber-reinforced polymer composites (FRPCs) are valid alternatives to metals, especially in the aerospace industry, for their superior strength-to-weight ratio. FRPCs are generally manufactured by stacking layers of fibers and infusing them with epoxy-based adhesives to result in laminates. Such layer-by-layer structure often ensues a poor interlaminar property of the composites. Additionally, FRPCs can sustain complex damage modes because of their inherent anisotropic characteristics. For example, delamination can occur due to low-velocity impact at a subsurface level, which can result in premature catastrophic failures if undetected. Thus, structural monitoring is crucial to identify such damage. Point-based sensors (e.g., strain gauges, accelerometers, among many) can be embedded in the FRPCs for structural monitoring. However, their electrical power demand often embroils their usage. Therefore, the main objective of this research is to design and implement multifunctional composites that can simultaneously perform passive sensing and energy harvesting while exhibiting better mechanical performance. Previous research efforts have demonstrated that a continuous feed-through deposition of functional materials on fiber surfaces simultaneously enhanced the mechanical and sensing properties of the FRPCs. This study explores a similar approach to encode passive sensing and energy harvesting properties in the FRPCs by integrating ferroelectric microparticles on the fiber surfaces. Upon ensuring their superior interlaminar shear strength, sensing and energy harvesting properties were characterized through experimental studies. The outcome is a multifunctional composite fabricated by coating the fibers with functional microparticles through a high throughput, scalable, and low-cost approach that enables passive sensing, energy harvesting, and improved mechanical performance.

Gupta, Sumit↗

DOE OSTI2022

Alkali metal halide–coated perovskite redox catalysts for anaerobic oxidative dehydrogenation of n -butane

Oxidative dehydrogenation (ODH) of n-butane has the potential to efficiently produce butadiene without equilibrium limitation or coke formation. Despite extensive research efforts, single-pass butadiene yields are limited to <23% in conventional catalytic ODH with gaseous O 2 . This article reports molten LiBr as an effective promoter to modify a redox-active perovskite oxide, i.e., La 0.8 Sr 0.2 FeO 3 (LSF), for chemical looping–oxidative dehydrogenation of n-butane (CL-ODHB). Under the working state, the redox catalyst is composed of a molten LiBr layer covering the solid LSF substrate. Characterizations and ab initio molecular dynamics (AIMD) simulations indicate that peroxide species formed on LSF react with molten LiBr to form active atomic Br, which act as reaction intermediates for C–H bond activation. Meanwhile, molten LiBr layer inhibits unselective CO 2 formation, leading to 42.5% butadiene yield. The redox catalyst design strategy can be extended to CL-ODH of other light alkanes such as iso-butane conversion to iso-butylene, providing a generalized approach for olefin production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

In situ atomic-resolution imaging of water vapor–driven multistep oxidation dynamics in strontium cobaltite

Understanding how water vapor interacts with transition metal oxides (TMOs) is critical for tailoring material properties to improve performance and enable new technologies. Despite extensive research efforts, atomic-scale mechanisms underpinning dynamic reactions and reaction-induced phase transitions remain elusive. Here, we use in situ environmental transmission electron microscopy to investigate how water vapor oxidizes vacancy-ordered SrCoO 2.5 at moderately elevated temperatures, demonstrating that water molecules can initiate oxidation more effectively than oxygen under comparable conditions. We discover a distinct “staging” behavior during the oxidation process: A fully ordered intermediate phase, SrCoO 2.75 , forms before transitioning into a near-perovskite SrCoO 3−δ . In addition, antiphase boundaries, originating at step terraces of SrTiO 3 , alleviate strain by creating reversible nanoscale “gaps” during lattice contraction under oxidation, providing a pathway for preserving structural integrity throughout redox cycling. This work provides atomic-level guidance for engineering TMOs by leveraging water vapor to control their redox behavior and tailor functional properties.

Science & Technology - Other Topics↗

DOE OSTI2023

Eukaryotic genomes from a global metagenomic data set illuminate trophic modes and biogeography of ocean plankton

ABSTRACT Metagenomics is a powerful method for interpreting the ecological roles and physiological capabilities of mixed microbial communities. Yet, many tools for processing metagenomic data are neither designed to consider eukaryotes nor are they built for an increasing amount of sequence data. EukHeist is an automated pipeline to retrieve eukaryotic and prokaryotic metagenome-assembled genomes (MAGs) from large-scale metagenomic sequence data sets. We developed the EukHeist workflow to specifically process large amounts of both metagenomic and/or metatranscriptomic sequence data in an automated and reproducible fashion. Here, we applied EukHeist to the large-size fraction data (0.8–2,000 µm) from Tara Oceans to recover both eukaryotic and prokaryotic MAGs, which we refer to as TOPAZ (Tara Oceans Particle-Associated MAGs). The TOPAZ MAGs consisted of >900 environmentally relevant eukaryotic MAGs and >4,000 bacterial and archaeal MAGs. The bacterial and archaeal TOPAZ MAGs expand upon the phylogenetic diversity of likely particle- and host-associated taxa. We use these MAGs to demonstrate an approach to infer the putative trophic mode of the recovered eukaryotic MAGs. We also identify ecological cohorts of co-occurring MAGs, which are driven by specific environmental factors and putative host-microbe associations. These data together add to a number of growing resources of environmentally relevant eukaryotic genomic information. Complementary and expanded databases of MAGs, such as those provided through scalable pipelines like EukHeist, stand to advance our understanding of eukaryotic diversity through increased coverage of genomic representatives across the tree of life. IMPORTANCE Single-celled eukaryotes play ecologically significant roles in the marine environment, yet fundamental questions about their biodiversity, ecological function, and interactions remain. Environmental sequencing enables researchers to document naturally occurring protistan communities, without culturing bias, yet metagenomic and metatranscriptomic sequencing approaches cannot separate individual species from communities. To more completely capture the genomic content of mixed protistan populations, we can create bins of sequences that represent the same organism (metagenome-assembled genomes [MAGs]). We developed the EukHeist pipeline, which automates the binning of population-level eukaryotic and prokaryotic genomes from metagenomic reads. We show exciting insight into what protistan communities are present and their trophic roles in the ocean. Scalable computational tools, like EukHeist, may accelerate the identification of meaningful genetic signatures from large data sets and complement researchers’ efforts to leverage MAG databases for addressing ecological questions, resolving evolutionary relationships, and discovering potentially novel biodiversity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Machine Learning Assisted HPC Workload Trace Generation for Leadership Scale Storage Systems

Monitoring and analyzing a wide range of I/O activities in an HPC cluster is important in maintaining mission-critical performance in a large-scale, multi-user, parallel storage system. Center-wide I/O traces can provide high-level information and fine-grained activities per application or per user running in the system. Studying such large-scale traces can provide helpful insights into the system. It can be used to develop predictive methods for making predictive decisions, adjusting scheduling policies, or providing decisions for the design of next-generation systems. However, sharing real-world I/O traces to expedite such research efforts leaves a few concerns; i) the cost of sharing the large traces is expensive due to this large size, and ii) privacy concern is an issue.We address such issues by building an end-to-end machine learn- ing (ML) workflow that can generate I/O traces for large-scale HPC applications. We leverage ML based feature selection and gener- ative models for I/O trace generation. The generative models are trained on I/O traces collected by the darshan I/O characterization tool over a period of one year. We present a two-step generation process consisting of two deep-learning models, called the feature generator and the trace generator. The combination of two-step generative models provides robustness by reducing the bias of the model and accounting for the stochastic nature of the I/O traces across different runs of an application. We evaluate the performance of the generative models and show that the two-step model can generate time-series I/O traces with less than 20% root mean square error.

Paul, Arnab↗

DOE OSTI2024

Large Language Models for the Creation and Use of Semantic Ontologies in Buildings: Requirements and Challenges

Semantic ontologies offer a formalized, machine-readable framework for representing knowledge, enabling the structured description of complex systems. In the building domain, the adoption of ontologies like the Brick schema has transformed how buildings and their systems are modeled by providing a standardized, interoperable language. However, the complexity and the steep learning curve involved in developing and querying semantic models present substantial challenges, often requiring a workforce with specialized expertise. This paper builds on our experience in investigating how Large Language Models (LLMs) can help address these challenges, focusing on their role in constructing and querying of semantic models, particularly using the Brick Schema. Our study outlines the requirements and metrics for evaluating the scalability and effectiveness of LLM-based tools, while also discussing the current challenges and limitations in developing such tools. Ultimately, this paper aims to orient research efforts as various groups experiment with diverse techniques, while enabling more effective comparison of emerging solutions and fostering collaboration across the field.

Mulayim, Ozan Baris↗

DOE OSTI2022

Editors’ Choice—Review—Designing Defects and Diffusion through Substitutions in Metal Halide Solid Electrolytes

Ternary metal halides A 3 MX 6 , ( A = Li + , Na + ; M = trivalent metal; X = halide) are a promising family of solid electrolytes for potential applications in all-solid-state batteries. Recent research efforts have demonstrated that chemical substitution at all three sites is an effective strategy to controlling battery-relevant material properties. The A 3 MX 6 family exhibits a wide breadth of structure and anion sublattice types, making it worthwhile to comprehend how chemical substitutions manifest desirable functional properties including ion transport, electrochemical stability, and environmental tolerance. Yet, a cohesive understanding of the materials design principles for these substitutions have not yet been developed. Here, we bring together prior literature focused on chemical substitutions in the A 3 MX 6 ternary metal halide solid electrolytes. Using materials chemistry perspectives and principles, we aim to provide insights into the relationships between crystal structure, choice of substituting ions and the extent of substitutions, ionic conductivity, and electrochemical stability. We further present targeted approaches to future substitution studies to enable transformative advances in A 3 MX 6 solid electrolytes and all-solid-state batteries.

25 ENERGY STORAGE↗

DOE OSTI2021

sas-temper

Modeling remains a considerable challenge for practitioners of SAXS and SANS because the materials being studied are not highly ordered, the length scales being studied are large, and the information content of the data is low. Data analysis is both challenging and time consuming. Novices often rely on the assistance of an expert, such as the instrument scientist who supported them at the facility where the experiment was performed, to analyze their data. The high flux provided by modern facilities makes it possible to study dozens of samples or sample conditions during a single trip. Ultimately, the high throughput of modern instruments limits access to instrument scientists. A bottleneck in the research effort results that reduces facility productivity. Sas-temper seeks to address this problem, as well as the intrinsic difficulties of being confident in non-linear least squared fitting of data, by providing tools that automate much of the manual process of initial data fitting and refinement, as well as by providing tools for characterizing the nature of the parameter space that fits the measured data. The tools provided by sas-temper help small-angle scattering practitioners transition data into results.

Heller, William [Oak Ridge National Lab. (ORNL), O↗

DOE OSTI2022

Stardust Network Measurement Components (esnet-stardust-components) v1

This software contains a set of components that allow us to measure and analyze the use and performance of computer networks using existing off the shelf Open Source components organized into a scalable and extensible system. The components were developed for and used within ESnet's Stardust Measurement Environment. The components are used to collect, process and display network measurement data in an architecture that employs a combination of Elasticsearch, Logstash and Grafana. The advantage of this approach is we can tailor system behavior to our analytical needs and expand its capability with new types of network measurement without waiting for a commercial vendor to support our fairly niche use cases. Additionally we have existing collaborations within our community that came about from prior research efforts that will benefit from the release of this software so that others can also contribute features.

Balas, Edward↗

DOE OSTI2021

Cyote Research Tool Library

The software is a library of individual proof-of-concept tools to be further developed in research efforts with partner utilities to detect indicators of Cyber Attacks within the Operational Technology Environments.

Wellman, LawrenceR.↗

DOE OSTI2025

Lassa virus protein–protein interactions as mediators of Lassa fever pathogenesis

Viral hemorrhagic Lassa fever (LF), caused by Lassa virus (LASV), is a significant public health concern endemic in West Africa with high morbidity and mortality rates, limited treatment options, and potential for international spread. Despite advances in interrogating its epidemiology and clinical manifestations, the molecular mechanisms driving pathogenesis of LASV and other arenaviruses remain incompletely understood. This review synthesizes current knowledge regarding the role of LASV host-virus interactions in mediating the pathogenesis of LF, with emphasis on interactions between viral and host proteins. Through investigation of these critical protein–protein interactions, we identify potential therapeutic targets and discuss their implications for development of medical countermeasures including antiviral drugs. This review provides an update in recent literature of significant LASV host-virus interactions important in informing the development of targeted therapies and improving clinical outcomes for LF patients. Knowledge gaps are highlighted as opportunities for future research efforts that would advance the field of LASV and arenavirus pathogenesis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Mapping the immunogenic landscape of near-native HIV-1 envelope trimers in non-human primates

The induction of broad and potent immunity by vaccines is the key focus of research efforts aimed at protecting against HIV-1 infection. Soluble native-like HIV-1 envelope glycoproteins have shown promise as vaccine candidates as they can induce potent autologous neutralizing responses in rabbits and non-human primates. In this study, monoclonal antibodies were isolated and characterized from rhesus macaques immunized with the BG505 SOSIP.664 trimer to better understand vaccine-induced antibody responses. Our studies reveal a diverse landscape of antibodies recognizing immunodominant strain-specific epitopes and non-neutralizing neo-epitopes. Additionally, we isolated a subset of mAbs against an epitope cluster at the gp120-gp41 interface that recognize the highly conserved fusion peptide and the glycan at position 88 and have characteristics akin to several human-derived broadly neutralizing antibodies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

The Geochemistry and Microbial Ecology of Produced Waters from Three Different Unconventional Oil and Gas Regions

One of the most significant challenges associated with predicting reservoir fluid properties is accounting for the effect of microbial activity, which catalyzes chemical reactions that lead to corrosion and sulfide release during or after hydraulic fracturing operations. The current understanding of microbial populations living in hydraulic fracturing systems is based on a limited number of samples and well sites, necessitating additional research efforts to confirm preliminary findings and identify factors driving the microbial ecology. The project objective is to profile the geochemistry and microbiology of three different oil and gas basins to order increase the understanding of how microbial activity affects reservoir fluids.

Lipus, Daniel↗

DOE OSTI2024

Rethinking hysteresis in magnetic materials

Abstract Magnetic materials with zero hysteresis are posed to have a significant impact on sustainable energy conversion, electronics, and communication technologies. As the global market for soft magnetic materials continues to expand, driven by increasing demand in renewable energy, automotive, and power transmission sectors, it is important to design magnets that can be cycled under an external field reversibly and rapidly multiple times without a decay in magnetic response. However, designing magnets with small hysteresis has been a challenge because we do not fully understand its origins. In this article, I outline key research efforts investigating the fundamental mechanisms underpinning hysteresis in soft magnets and, highlight recent developments in the use of nonlinear analysis and nucleation barrier methods to predict coercivity in these materials. Graphical abstract

Renuka Balakrishna, Ananya (ORCID:0000000306015257↗

DOE OSTI2021

Catalytic Hydroprocessing of Single-Cell Oils to Hydrocarbon Fuels : Converting microbial lipids to fuels is a promising approach to replace fossil fuels

Microbial lipids hold great promise as biofuel precursors, and research efforts to convert such lipids to renewable diesel fuels have been increasing in recent years. In contrast to the numerous literature reviews on growing, characterising and extracting lipids from oleaginous microbes, and on converting vegetable oils to hydrocarbon fuels, this review aims to provide insight into aspects that are specific to hydroprocessing microbial lipids. While standard hydrotreating catalysts generally perform well with terrestrial oils, differences in lipid speciation and the presence of co-extracted compounds, such as chlorophyll and sterols, introduce additional complexities into the process for microbial lipids. Lipid cleanup steps can be introduced to produce suitable feedstocks for catalytic upgrading.

09 BIOMASS FUELS↗