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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Cyberinfrastructure for the democratization of smart manufacturing

“Smart Manufacturing” is the transformation of U.S. manufacturing that results from disrupting traditional business, organizational, operating, and market structures with a radical increase in the availability and use of real-time operations data to produce value in previously inconceivable ways—a transformation process known as “manufacturing digitalization” or “manufacturing digital transformation.” There are significant economic and investment opportunities with substantially increased supply chain productivity and far better product design with process and machine precision and performance for highervalue products manufactured better, faster, cheaper with less energy and material.

Advanced sensor controls platforms and modeling↗
DOE OSTI2026

Evaluating alternative steam generation pathways in the food industry

Steam generation in the food sector requires substantial energy and cost expenditures, requiring nearly half of its energy intake. Here, we used life cycle assessment and life cycle cost assessment to investigate the cost and energy impacts of steam generating alternatives: NG, biomass and hydrogen boilers and grid-supplied and self-generated electric steam generation systems (electric boilers, renewable thermal energy storage and industrial heat pumps). The analysis starts with a set of average U.S. conditions, where biomass boilers are the most cost-competitive alternative to NG. In a series of scenarios beyond average conditions, the analysis shows energy procurement costs dominate the total life cycle cost for all technologies and, unfortunately, are highly variable geographically and temporally, significantly affecting the viability of the alternatives. Results show that site-energy consumption ranges from 0.3 MMBtu/klb for industrial heat pumps to 1.6 MMBtu/klb for biomass boilers, with heat pumps achieving up to 78% lower energy use compared to natural gas systems. For the steam costs, the results show a range between $\$$8 and $\$$50/klb for NG, with biomass following closely ($\$$11 – $\$$44/klb) and grey hydrogen and IHP next ($\$$13 – $\$$33/klb and $\$$6 - $\$$78/klb), with cost reductions if IHP's cooling is utilized. Factors like operating hours, the need for cooling, and the ability to negotiate utility rates complicate the decision, making site-specific analyses critical. Therefore, we present a decision-making matrix to help manufacturers identify which steam generating technology is the best business decision for their situation. Overall, these results highlight the importance of steam generation for the facility's organizational goals, as well as the criticality of conducting individual site analyses.

Biomass boilers↗
DOE OSTI2023

A chloroplast protein atlas reveals punctate structures and spatial organization of biosynthetic pathways

Chloroplasts are eukaryotic photosynthetic organelles that drive the global carbon cycle. Despite their importance, our understanding of their protein composition, function, and spatial organization remains limited. Here, we determined the localizations of 1,034 candidate chloroplast proteins using fluorescent protein tagging in the model alga Chlamydomonas reinhardtii. The localizations provide insights into the functions of poorly characterized proteins; identify novel components of nucleoids, plastoglobules, and the pyrenoid; and reveal widespread protein targeting to multiple compartments. We discovered and further characterized cellular organizational features, including eleven chloroplast punctate structures, cytosolic crescent structures, and unexpected spatial distributions of enzymes within the chloroplast. We also used machine learning to predict the localizations of other nuclear-encoded Chlamydomonas proteins. The strains and localization atlas developed here will serve as a resource to accelerate studies of chloroplast architecture and functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

From clutter to clarity: Emergent neural operators via questionnaire metrics

Real-world datasets in chemical engineering and bioengineering processes—such as those from catalytic reactors, multiphase flows, polymerization reactors, bioreactors, and clinical trials—can often be unlabeled or disorganized, rendering the training of existing supervised learning models ineffective at learning the underlying dynamics. To salvage these datasets for decision-making, we first seek to obtain clarity from the cluttered data. Here, we present a framework for developing “structural” generative models, discovering emergent equations, and constructing efficient emulators from scrambled datasets by integrating unsupervised organizational learning techniques (Questionnaires) with advanced deep learning architectures (Deep Hidden Physics Models and Deep Operator Networks). Our approach is demonstrated on two illustrative model systems: (a) a 1D advection–diffusion partial differential equation representing a winding underground pipe and (b) an ensemble of Stuart–Landau oscillators, an agent-based system of coupled ordinary differential equations. In both cases, we successfully reconstruct meaningful spatial, temporal, and parameter embeddings from scrambled data, enabling good predictions of system dynamics. As a result, we highlight the framework’s potential for broader applications, enabling data-driven system identification in fields with inherently disorganized or hidden parameter spaces.

42 ENGINEERING↗
DOE OSTI2024

Self-organization in collisionless, high- β turbulence

The magnetohydrodynamic (MHD) equations, as a collisional fluid model that remains in local thermodynamic equilibrium (LTE), have long been used to describe turbulence in myriad space and astrophysical plasmas. Yet, the vast majority of these plasmas, from the solar wind to the intracluster medium (ICM) of galaxy clusters, are only weakly collisional at best, meaning that significant deviations from LTE are not only possible but common. Recent studies have demonstrated that the kinetic physics inherent to this weakly collisional regime can fundamentally transform the evolution of such plasmas across a wide range of scales. Here, we explore the consequences of pressure anisotropy and Larmor-scale instabilities for collisionless, β $\gg$ 1, turbulence, focusing on the role of a self-organizational effect known as ‘magneto-immutability’. We describe this self-organization analytically through a high-β, reduced ordering of the Chew–Goldberger–Low-MHD (CGL-MHD) equations, finding that it is a robust inertial-range effect that dynamically suppresses magnetic-field-strength fluctuations, anisotropic-pressure stresses and dissipation due to heat fluxes. As a result, the turbulent cascade of Alfvénic fluctuations continues below the putative viscous scale to form a robust, nearly conservative, MHD-like inertial range. These findings are confirmed numerically via Landau-fluid CGL-MHD turbulence simulations that employ a collisional closure to mimic the effects of microinstabilities. We find that microinstabilities occupy a small (~5%) volume-filling fraction of the plasma, even when the pressure anisotropy is driven strongly towards its instability thresholds. We discuss these results in the context of recent predictions for ion-vs-electron heating in low-luminosity accretion flows and observations implying suppressed viscosity in ICM turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Leveraging Radiofrequency Identification Success Beyond Hazardous Material Inventory Management at a National Laboratory

Effective inventory management can be overshadowed by conflicting priorities in organizational procedures, particularly in research-focused institutions such as national laboratories that handle expensive, delicate, and hazardous materials. Here, this study investigated the potential of radiofrequency identification (RFID) technology, currently used for hazardous chemical inventory, in applications with higher metal interference and absorption, specifically pressure release device (PRD) compliance and nuclear container management, at Lawrence Livermore National Laboratory (LLNL). This study was done to document best practices to enhance inventory identification speeds for inventory reconciliation and inventory recall and to explore optimal configurations for RFID implementation compared to traditional manual methods of equipment management. Tests were conducted to determine the ideal RFID tag orientation (read at angles of 0°, 90°, and 270°), various container layouts (linear, separated, curved, operational), and ID methods such as manual, barcode, and RFID performing three trials per method per orientation. Results indicated that 0° was the optimal read angle for minimizing metallic interference, and the operational and curved arrangements significantly outperformed the linear and separated configurations in read speed. 3D printed mounts were developed and tested, increasing the read range of the RFID reader by up to 235% in cases of high metallic interference. The RFID technology demonstrated an average speed increase of 65% over a simplified manual identification, which supports the conclusion that RFID is a more efficient method for large hazardous inventory management and equipment reconciliation. Additionally, capturing meta-data, such as location and date, can be used to query for inventory recall and automated updating of record information.

42 ENGINEERING↗
DOE OSTI2021

Origins of Clustering of Metalate–Extractant Complexes in Liquid–Liquid Extraction

Effective and energy-efficient separation of precious and rare metals is very important for a variety of advanced technologies. Liquid-liquid extraction (LLE) is a relatively less energy intensive separation technique, widely used in separation of lanthanides, actinides, and platinum group metals (PGMs). In LLE, the distribution of an ion between an aqueous phase and an organic phase is determined by enthalpic (coordination interactions) and entropic (fluid reorganization) contributions. The molecular scale details of these contributions are not well understood. Preferential extraction of an ion from the aqueous phase is usually correlated with the resulting fluid organization in the organic phase, as the longer-range organization increases with metal loading. However, it is difficult to determine the extent to which organic phase fluid organization causes, or is caused by, metal loading. In this study, we demonstrate that two systems with the same metal loading may impart very different organic phase organizations and investigate the underlying molecular scale mechanism. Small-angle X-ray scattering shows that the structure of a quaternary ammonium extractant solution in toluene is affected differently by the extraction of two metalates (octahedral PtCl 6 2- and square-planar PtCl 6 2- ), although both are completely transferred into the organic phase. The aggregates formed by the metalate-extractant complexes (approximated as reverse micelles) exhibit a more long-range order (clustering) with PtCl 6 2- compared to that with PtCl 6 2- . Vibrational sum frequency generation spectroscopy and complementary atomistic molecular dynamics simulations on model Langmuir monolayers indicate that the two metalates affect the interfacial hydration structures differently. Furthermore, the interfacial hydration is correlated with water extraction into the organic phase. Overall, these results support a strong relationship between the organic phase organizational structure and the different local hydration present within the aggregates of metalate-extractant complexes, which is independent of metalate concentration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Scrambling Signal Modularity in Bottom-up Assembled Synthetic Pseudomonas Consortia Reveals Robust Information Transfer

There is immense potential in crafting synthetic microbial communities for application in human health, agriculture, the environment, and even biomanufacturing where an appropriately constructed consortium can be assembled with tremendous biosynthetic or degradative capabilities. In many of these cases, bacterial signaling serves as a form of intercellular information transfer that guides the collective’s behavior. Such communication is complex, as many signals, signal disruptors, microbial species, physical barriers, and spatiotemporal constraints may be involved. Here, in this work, we demonstrate that a multisignal pathway for molecular information transfer within a consortium of several Pseudomonas spp. can be scrambled (genetically and organizationally) while the original message is still effectively conveyed. Assembled from the bottom up, we have employed two types of signaling molecules (i) a redox active secondary metabolite (rhizospheric signal, phloroglucinol), and (ii) a bacterial quorum sensing signal (3-oxo-C12 acylhomoserine lactone, AI-1). These signals can be intraconverted and acted upon by designated community members. We show how the order in which the signals are received, transduced, and subsequently transmitted can be rearranged with minimal impact on the intended outcome. In the consortial context, we found this messaging structure can be remarkably robust. Inspired by rhizospheric molecular signaling mechanisms, this work provides a conceptual framework for designing signaling and information transfer processes within assembled communities.

Biological and medical sciences↗
DOE OSTI2025

Flower‐Type Organized Trade‐Wind Cumulus: A Multi‐Day Lagrangian Large Eddy Simulation Intercomparison Study

Shallow cumulus cloud fields in subtropical marine trade wind environments, particularly over the tropical Atlantic Ocean, show distinct organizational patterns. Among these, Flower‐type clouds are characterized by expansive stratiform cloud patches surrounded by regions of scattered convection. The objectives of this study were (a) to construct a case study of a time period during the EUREC 4 A/ATOMIC field campaign when Flower‐type organization was observed, (b) to evaluate the fidelity of a multi‐model ensemble of large eddy simulations of that case, and (c) to analyze the interaction between cloud and precipitation processes and mesoscale organization in the simulations. The simulations follow a quasi‐Lagrangian trajectory, allowing mesoscale features to develop over time in a domain that follows the boundary‐layer airmass. The results show a broad agreement in simulated thermodynamic properties across different LES codes, with Flower‐type cloud patches appearing within hours of each other. The consensus among models is consistent with observations made during the EUREC 4 A/ATOMIC field campaign on the specific day of interest. The cloud structure reveals three distinct peaks in the joint probability densities of cloud base and cloud top height, with the dominant peak at any given time influenced by the stage of cloud organization. The simulated cloud system evolution reveals consistent occurrence of maxima in liquid water path and rain rate before Flower reaches its maximum length scale. Targeted sensitivity tests reveal a weak relationship between Cloud Droplet Number concentration and the extent/degree/type of organization.

EUREC4A↗
DOE OSTI2023

The breakdown of both strange metal and superconducting states at a pressure-induced quantum critical point in iron-pnictide superconductors

Here we report the first observation of the concurrent breakdown of the strange metal (SM) normal state and superconductivity at a pressure-induced quantum critical point in Ca 10 (Pt 4 As 8 )((Fe 0.97 Pt 0.03 ) 2 As 2 ) 5 superconductor. We find that, upon suppressing the superconducting state, the power exponent (α) changes from 1 to 2, and the slope of the temperature-linear resistivity per FeAs layer (A $\Box$ ) gradually diminishes. At a critical pressure, A $\Box$ and superconducting transition temperature (T c ) go to zero concurrently, where a quantum phase transition from a superconducting state with a SM normal state to a non-superconducting Fermi liquid state occurs. Scaling analysis reveals that the change of A $\Box$ with T c obeys the relation of T c ~ (A $\Box$ ) 0.5 , similar to what is seen in other chemically doped unconventional superconductors. These results suggest that there is a simple but powerful organizational principle of connecting the SM normal state with the high-T c superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

NADH-bound AIF activates the mitochondrial CHCHD4/MIA40 chaperone by a substrate-mimicry mechanism

Mitochondrial metabolism requires the chaperoned import of disulfide-stabilized proteins via CHCHD4/MIA40 and its enigmatic interaction with oxidoreductase Apoptosis-inducing factor (AIF). By crystallizing human CHCHD4’s AIF-interaction domain with an activated AIF dimer, we uncover how NADH allosterically configures AIF to anchor CHCHD4’s β-hairpin and histidine-helix motifs to the inner mitochondrial membrane. The structure further reveals a similarity between the AIF-interaction domain and recognition sequences of CHCHD4 substrates. NMR and X-ray scattering (SAXS) solution measurements, mutational analyses, and biochemistry show that the substrate-mimicking AIF-interaction domain shields CHCHD4’s redox-sensitive active site. Disrupting this shield critically activates CHCHD4 substrate affinity and chaperone activity. Regulatory-domain sequestration by NADH-activated AIF directly stimulates chaperone binding and folding, revealing how AIF mediates CHCHD4 mitochondrial import. These results establish AIF as an integral component of the metazoan disulfide relay and point to NADH-activated dimeric AIF as an organizational import center for CHCHD4 and its substrates. Importantly, AIF regulation of CHCHD4 directly links AIF’s cellular NAD(H) sensing to CHCHD4 chaperone function, suggesting a mechanism to balance tissue-specific oxidative phosphorylation (OXPHOS) capacity with NADH availability.

Brosey, Chris A↗
DOE OSTI2026

Mapping Critical Vulnerabilities in Natural Gas Pipeline Systems through Network Centrality and GIS Analytics

Natural gas plays a central role in the US energy landscape, providing 43% of electricity generation in 2023. Its exclusive recovery ability on pipelines for transmission underscores the importance of understanding the disruption recovery ability of this infrastructure. This study employs a network-based analytical framework integrating geographic information systems (GIS) with multiple centrality measures—betweenness, closeness, degree, and eigenvector—to pinpoint key segments and evaluate the structural robustness of the national pipeline network. Pipelines are grouped by System ID and Operator ID to capture variations across organizational and physical structures. The analysis reveals uneven patterns of network influence, where certain pipelines function as critical connectors or dominant hubs. Spatial mapping highlights geographic dependencies and potential chokepoints, offering a clear view of where targeted risk prevention measures would be most effective. The findings provide practical guidance for prioritizing maintenance, enhancing system robustness, and mitigating risks to ensure a stable and secure energy supply. Future research will expand the framework to incorporate dynamic operational data and real-time network behavior.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗
DOE OSTI2024

A customizable data management framework for high-repetition-rate high-energy-density science

The high-energy-density (HED) physics community is moving toward a new paradigm of high-repetition-rate (HRR) operation. To fully leverage the scientific power of HRR HED facilities, all of the components of each subsystem (laser, targetry, and performance diagnostics) must be connected and synchronized in a reliable and robust manner while the data acquired are tagged and archived in real time. To this end, GA has begun developing a generalized NoSQL-database framework, the MongoDB repository for information and archiving. An organizational strategy has been developed that shifts HED data organization from a shot-based to a diagnostic-based approach in order to increase archival and retrieval efficiency that lends itself to optimization applications. This work is a first step in pushing HRR HED science toward data management solutions that emphasize machine actionability and aim to stimulate community engagement to define data standards in HED science.

Instruments & Instrumentation↗
DOE OSTI2021

An industrial policy framework for transforming energy and emissions intensive industries towards zero emissions

The target of zero emissions sets a new standard for industry and industrial policy. Industrial policy in the twenty-first century must aim to achieve zero emissions in the energy and emissions intensive industries. Sectors such as steel, cement, and chemicals have so far largely been sheltered from the effects of climate policy. A major shift is needed, from contemporary industrial policy that mainly protects industry to policy strategies that transform the industry. For this purpose, we draw on a wide range of literatures including engineering, economics, policy, governance, and innovation studies to propose a comprehensive industrial policy framework. The policy framework relies on six pillars: directionality, knowledge creation and innovation, creating and reshaping markets, building capacity for governance and change, international coherence, and sensitivity to socio-economic implications of phase-outs. Complementary solutions relying on technological, organizational, and behavioural change must be pursued in parallel and throughout whole value chains. Current policy is limited to supporting mainly some options, e.g. energy efficiency and recycling, with some regions also adopting carbon pricing, although most often exempting the energy and emissions intensive industries. An extended range of options, such as demand management, materials efficiency, and electrification, must also be pursued to reach zero emissions. New policy research and evaluation approaches are needed to support and assess progress as these industries have hitherto largely been overlooked in domestic climate policy as well as international negotiations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Standard model physics and the digital quantum revolution: thoughts about the interface

Advances in isolating, controlling and entangling quantum systems are transforming what was once a curious feature of quantum mechanics into a vehicle for disruptive scientific and technological progress. Pursuing the vision articulated by Feynman, a concerted effort across many areas of research and development is introducing prototypical digital quantum devices into the computing ecosystem available to domain scientists. Through interactions with these early quantum devices, the abstract vision of exploring classically-intractable quantum systems is evolving toward becoming a tangible reality. Beyond catalyzing these technological advances, entanglement is enabling parallel progress as a diagnostic for quantum correlations and as an organizational tool, both guiding improved understanding of quantum many-body systems and quantum field theories defining and emerging from the standard model. Here, from the perspective of three domain science theorists, this article compiles thoughts about the interface on entanglement, complexity, and quantum simulation in an effort to contextualize recent NISQ-era progress with the scientific objectives of nuclear and high-energy physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Design methodologies and engineering applications for ecosystem biomimicry: an interdisciplinary review spanning cyber, physical, and cyber-physical systems

Abstract Ecosystem biomimicry is a promising pathway for sustainable development. However, while typical form- and process-level biomimicry is prevalent, system-level ecosystem biomimicry remains a nascent practice in numerous engineering fields. This critical review takes an interdisciplinary approach to synthesize trends across case studies, evaluate design methodologies, and identify future opportunities when applying ecosystem biomimicry to engineering practices, including cyber systems (CS), physical systems (PS), and cyber-physical systems (CPS). After systematically sourcing publications from major databases, the papers were first analyzed at a meta level for their bibliographic context and for statistical correlations among categorical variables. Then, we investigated deeper into the engineering applications and design methodologies. Results indicate that CPS most frequently mimic organisms and ecosystems, while CS and PS frequently mimic populations-communities and molecules-tissues-organ systems, respectively (statistically highly significant). An indirect approach is most often used for mimicry at organizational levels from populations to ecosystems, while a direct approach frequently suits levels from molecules to organisms (highly significant). Dominant themes across engineering applications include symbiotic organism search algorithms for CS and ecological network analysis for CPS, while PS are highly diverse. For design methodologies, this work summarizes and details ten well-documented biomimetic process models among literature, which addresses an outdated concern for a lack of systematic methods for ecosystem biomimicry. In addition to the Biomimetics Standard ISO 18458, these methods include the Natural Step and Techno-Ecological Synergy framework, among others. Further, the analyses revealed future opportunities from less utilized design methods (e.g. interdisciplinary teams tackling indirect, ecosystem-level projects) to well-established engineering concepts ready for technological advancement (e.g. implementing membrane computing for physical applications). For future studies, this review provides a comprehensive reference for ecosystem biomimetic design practices and application opportunities across multiple engineering domains.

42 ENGINEERING↗
DOE OSTI2021

Benchmarking SARS CoV-2 Infection in the Workplace to Support Continuity of Operations

Objective: The COVID-19 pandemic jeopardizes continuity of operations of workplaces and the health and safety of workers. Exemplar workplace-related SARS-CoV-2 benchmarks are described and illustrated with empirical data. Methods: Benchmarks were collected over a 9-month period on a large workplace (N = 5500+). These ranged from quantitative indices associated with RT-qPCR targeted testing and random surveillance screening, surveillance for new variants of SARS-CoV-2, intensive contact tracing, case management, return to work procedures, to monitoring of antibody seropositive status. Results: Data and analyses substantiated effectiveness of interventions. This was evidenced in suppressed infection rates, rapid case identification and isolation, acceptance of the program by employees, documentation of presumptive immunity, and working relationships with senior management. Conclusions: These SARS-CoV-2 exemplar benchmarks provided an evidence-base for practice and contributed strategically to organizational decisions.

60 APPLIED LIFE SCIENCES↗