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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 217 records · Page 12

TQEA: Temporal Quantum Error Analysis

For the last few years quantum computers have captured researchers’ interest in solving complicated problems in finance, chemistry, machine learning, and many other NP problems. Quantum computing benefits from parallel computation, entanglement, and calculation speedup compared to classical computing. Even though the operations and number of qubits in quantum computers are limited, previous research showed that using quantum computers can be beneficial. These benefits gained researchers’ interest to work on the improvement of quantum computers and overcome the limitations by building more advanced quantum computers with fault tolerance capability, more physical qubits, and better operational gates. In practice, Quantum applications would be translated into Quantum Circuits and each circuit can contain one or many entanglements (s), single qubits operations, and readouts. The importance of running Quantum applications with controlled errors or without errors is critical to the desired result from Quantum readout. In this paper, we study the characteristics of superconducting quantum machines along with the previously proposed methods of Quantum error detection/correction and in order to build a better error model we propose a temporal method for analyzing the the behavior of qubits errors (T1 and T2), frequency of operation, entanglement errors, and readout errors. In order to detect and predict the behavior of each machine, we use simple exponential smoothing analysis on heuristic calibration data. Finally, based on observation, we show that based on frequency, qubits, readout and single operation errors we can build a temporal based model to study and predict the outcome of runs on each Quantum machine.

Baheri, Betis↗

Cultural Shifts in High Energy Physics Collaboration from the Cold War to the Present: A Historical and Philosophical Perspective

Here, this article employs empirical history and the philosophy of science to study cultural convergences and divergences in international collaborations in high energy physics. We examine two cases: (1) E-36, an experiment on small angle proton-proton scattering conducted during the Cold War at the National Accelerator Laboratory (NAL) in the USA by Soviet and US scientists and (2) an ongoing collaborative experiment, NICA, at the Joint Institute for Nuclear Research (JINR, Dubna), which is a project devoted to heavy-ion physics. The JINR, particularly its Laboratory of High Energy Physics (formerly the “Laboratory of High Energies”) is the main mediating actor between these two cases (i.e., E-36 and NICA), as the majority of Soviet participants in E-36 were representatives of the Institute. Using empirical data collected through archival searches, field observations conducted at JINR in 2018–2019, and in-depth interviews, we tell a story of cultural differences in high energy physics by applying the concepts of ‘trading zones’ (P. Galison) and the translation of interests in actor-networks (B. Latour, M. Callon and others). We analyze three types of cultural diversity (specialization, nationality, and generational) in light of the implications of temporal context and the dichotomy between East and West, showing the roles cultural diversity plays in scientific collaboration (which is an integral part of as well as obstacle to scientific research that can nevertheless provide learning opportunities). Our study aims to demonstrate how disunity and diversity may function in scientific research and how high energy physics collaborations can remain productive despite sometimes deep divergences, including those between East and West.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Translating dosimetry of Dibenzo[ def,p ]chrysene (DBC) and metabolites across dose and species using physiologically based pharmacokinetic (PBPK) modeling

We report that Dibenzo[def,p]chrysene (DBC) is an environmental polycyclic aromatic hydrocarbon (PAH) that causes tumors in mice and has been classified as a probable human carcinogen by the International Agency for Research on Cancer. Animal toxicity studies often utilize higher doses than are found in relevant human exposures. Additionally, like many PAHs, DBC requires metabolic bioactivation to form the ultimate toxicant, and species differences in DBC and DBC metabolite metabolism have been observed. To understand the implications of dose and species differences, a physiologically based pharmacokinetic model (PBPK) for DBC and major metabolites was developed in mice and humans. Metabolism parameters used in the model were obtained from experimental in vitro metabolism assays using mice and human hepatic microsomes. PBPK model simulations were evaluated against mice dosed with 15 mg/kg DBC by oral gavage and human volunteers orally microdosed with 29 ng of DBC. DBC and its primary metabolite DBC-11,12-diol were measured in blood of mice and humans, while in urine, the majority of DBC metabolites were obeserved as conjugated DBC-11,12-diol, conjugated DBC tetrols, and unconjugated DBC tetrols. The PBPK model was able to predict the time course concentrations of DBC, DBC-11,12-diol, and other DBC metabolites in blood and urine of human volunteers and mice with reasonable accuracy. Agreement between model simulations and measured pharmacokinetic data in mice and human studies demonstrate the success and versatility of our model for interspecies extrapolation and applicability for different doses. Furthermore, our simulations show that internal dose metrics used for risk assessment do not necessarily scale allometrically, and that PBPK modeling provides a reliable approach to appropriately account for interspecies differences in metabolism and physiology.

59 BASIC BIOLOGICAL SCIENCES↗

Embracing Anisotropy – Opportunities and Challenges to the Functional Application of Advanced Manufacturing of Energetic Materials

The growing use of additive manufacturing (AM) to manipulate materials, such as metals and plastics, is a result of the desire to realize the potential benefits (i.e., cheaper, faster, and simpler production of complex parts) of the process and the efforts of countless researchers to reduce the method to practice for a broad range of materials. However, in the field of energetic materials (EMs), similar benefits have been broadly claimed, but the transition to practical, industrial applications is still not obvious. The translation of small-scale experimental results to real-world application will have unique challenges, especially due to the nature and requirements of EM functionality. Some of the benefits of AM, such as simpler and faster part creation, are more easily realized. However, attaining the most profound benefits, such as added functionality enabled by spatial gradations of composition or density, will require much more effort from the EMs community to put them into general use.

36 MATERIALS SCIENCE↗

Media matters! Alterations in the loading and release of Histoplasma capsulatum extracellular vesicles in response to different nutritional milieus

Histoplasma capsulatum is a dimorphic fungus that most frequently causes pneumonia, but can also disseminate and proliferate in diverse tissues. H. capsulatum has a complex secretion system that mediates the release of macromolecule-degrading enzymes and virulence factors. The formation and release of extracellular vesicles (EVs) are an important mechanism for non-conventional secretion in both ascomycetes and basidiomycetes. H. capsulatum EVs contain diverse proteins associated with virulence and are immunologically active. Despite the growing knowledge of EVs from H. capsulatum and other pathogenic fungi, the extent that changes in the environment impact the sorting of organic molecules in EVs has not been investigated. In our research, we cultivated H. capsulatum with distinct culture media to investigate the potential plasticity in EV loading in response to differences in nutrition. Our findings reveal that nutrition plays an important role in EV loading and formation, which may translate into differences in biological activities of these fungi in various fluids and tissues.

59 BASIC BIOLOGICAL SCIENCES↗

Decayheatml

This code is designed to predict and analyze the decay heat generated in molten salt reactors (MSRs) using a hybrid approach that combines machine learning and segmented polynomial fitting. The accurate prediction of decay heat is essential for reactor safety and the optimization of spent fuel storage. The code operates through several key components: 1) Data Architecture: It incorporates a modular data architecture that handles various MSR-specific operational parameters such as power density, humidity content, and air ingress. These parameters are sampled using Sobol sequences to ensure comprehensive coverage of operational uncertainties. 2) Machine Learning Framework: The code employs a diverse set of machine learning models, including polynomial regression, decision trees, random forests, gradient boosting, support vector regression, k-nearest neighbors, multi-layer perceptrons, and symbolic regression. These models are trained to predict decay heat over a wide temporal range, from immediate shutdown up to 10,000 years. 3) Region-Optimized Training: The temporal domain is divided into multiple regions, each modeled separately to capture distinct decay heat characteristics across different time scales. This approach significantly improves the accuracy and interpretability of predictions. 4) Segmented Polynomial Interpretation (SPI): The SPI method translates machine learning predictions into piecewise polynomial equations. These equations are physically interpretable and can be directly integrated into existing engineering workflows and safety analyses. 5) Front-End Interfaces: The code includes both a Jupyter notebook interface for research development and a Streamlit web application for operational deployment. These interfaces allow users to interactively explore decay heat predictions, adjust operational parameters, and visualize results in real-time. 6) Applications: The framework supports various applications, including safety system validation and spent fuel container optimization. It enables real-time evaluation of worst-case decay heat scenarios, informing the design of passive safety systems and optimizing container designs for long-term storage. Overall, this code provides a robust, accurate, and user-friendly tool for predicting decay heat in MSRs, enhancing reactor safety, and optimizing spent fuel management.

Retamales, Mauricio Eduardo Tano [Idaho National L↗

Foundations of plasma standards

Abstract The field of low-temperature plasmas (LTPs) excels by virtue of its broad intellectual diversity, interdisciplinarity and range of applications. This great diversity also challenges researchers in communicating the outcomes of their investigations, as common practices and expectations for reporting vary widely in the many disciplines that either fall under the LTP umbrella or interact closely with LTP topics. These challenges encompass comparing measurements made in different laboratories, exchanging and sharing computer models, enabling reproducibility in experiments and computations using traceable and transparent methods and data, establishing metrics for reliability, and in translating fundamental findings to practice. In this paper, we address these challenges from the perspective of LTP standards for measurements, diagnostics, computations, reporting and plasma sources. This discussion on standards, or recommended best practices, and in some cases suggestions for standards or best practices, has the goal of improving communication, reproducibility and transparency within the LTP field and fields allied with LTPs. This discussion also acknowledges that standards and best practices, either recommended or at some point enforced, are ultimately a matter of judgment. These standards and recommended practices should not limit innovation nor prevent research breakthroughs from having real-time impact. Ultimately, the goal of our research community is to advance the entire LTP field and the many applications it touches through a shared set of expectations.

data and reaction mechanisms↗

Airborne Acoustic Vortex End Effector‐Based Contactless, Multi‐Mode, Programmable Control of Object Surfing

Abstract Tweezers based on optical, electric, magnetic, and acoustic fields have shown great potential for contactless object manipulation. However, current tweezers designed for manipulating millimeter‐sized objects such as droplets, particles, and small animals exhibit limitations in translation resolution, range, and path complexity. Here, a novel acoustic vortex tweezers system is introduced, which leverages a unique airborne acoustic vortex end effector integrated with a three‐degree‐of‐freedom (DoF) linear motion stage, for enabling contactless, multi‐mode, programmable manipulation of millimeter‐sized objects. The acoustic vortex end effector utilizes a cascaded circular acoustic array, which is portable and battery‐powered, to generate an acoustic vortex with a ring‐shaped energy pattern. The vortex applies acoustic radiation forces to trap and spin an object at its center, simultaneously protecting this object by repelling other materials away with its high‐energy ring. Moreover, The vortex tweezers system facilitates contactless, multi‐mode, programmable object surfing, as demonstrated in experiments involving trapping, repelling, and spinning particles, translating particles along complex paths, guiding particles around barriers, translating and rotating droplets containing zebrafish larvae, and merging droplets. With these capabilities, It is anticipated that the tweezers system will become a valuable tool for the automated, contactless handling of droplets, particles, and bio‐samples in biomedical and biochemical research.

Li, Teng↗

Spontaneous Raman–LIF–CO–OH measurements of species concentration in turbulent spray flames

This paper presents new measurements of species concentrations, temperature and mixture fraction in selected regions of a turbulent ethanol spray flame. The line-Raman–LIF–COsingle bondOH setup developed at the Sandia's Combustion Research Facility is utilised to probe regions of a spray flame where laser breakdown of liquid droplets is avoided and the remaining interferences can be corrected. The spray flame is stabilised on the piloted Sydney needle spray burner, where axial translation of the liquid injecting needle in the air-blast stream can transition the spray from dilute to dense. The solution to obtaining successful measurements is found to be multifaceted and includes: the appropriate selection of flame conditions; high sensitivity of the Raman detection system permitting reduced laser energies; development of a pre-processing algorithm to reject strong droplet interferences; and application of the hybrid matrix inversion method combined with wavelet denoising to account for interference corrections and noise at the very low signal levels obtained. Unique and necessary for the successful measurements reported in this paper, a pre-processing algorithm is outlined that removes data points corrupted with strong interferences from droplets. These interferences arise from a range of sources, but the most intense are due to the laser interaction with surrounding mist or liquid fragments, such that measurements near the jet centreline are corrupted and hence discarded. Reliable measurements of mixture fraction, temperature obtained from the sum of the species number densities, and species mole fractions are reported for regions in the flames sufficiently far from the centreline. The paper demonstrates the feasibility of the judicious use of Raman scattering in turbulent spray flames, the results of which will be extremely useful for validating numerical simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving transition to IPv6-only via RFC8925 and IPv4 DNS Interventions

Nine years have passed since the American Registry for Internet Numbers exhausted its allocation of Internet Protocol version 4 (IPv4) addresses, and four years have passed since the United States Government mandated federal agencies to complete the transition to Internet Protocol version 6 (IPv6). Despite the IPv4 address shortage and IPv6 mandate, Federally Funded Research and Development Centers (FFRDCs) are still struggling to sunset IPv4. As demonstrated on SC23’s SC23v6 wireless network, newer tooling such as RFC8925 allows clients to disable their IPv4 protocol stack while retaining legacy IP connectivity via the RFC6145 translation algorithm. However, SC23v6 wireless clients without RFC8925 support or a disabled IPv6 stack would continue to receive internet access via legacy IPv4. This paper introduces a method of using poisoned IPv4 Domain Name System (DNS) records to gracefully inform IPv4-only clients at SC24’s SC24v6 wireless network about their inability to use the current version of internet protocol, with a goal of minimal impact to RFC8925 and dual-stack clients. When implemented as designed, this method may improve supportability and user experience of IPv6-only deployments at FFRDCs.

Costello, Thomas M↗

Leveraging generative artificial intelligence to bridge domain gaps in wind turbine research

A central challenge in wind turbine health monitoring is the scarcity of real-world data due to limited instrumentation, leading researchers to rely on simulation models that often suffer from reduced fidelity. However, even within simulation environments, discrepancies arise because of modeling assumptions, and configuration fidelities, creating domain gaps that limit the transferability of learned representations. Here, to investigate domain translation under controlled conditions, this project explores the use of generative artificial intelligence, specifically cycle-consistent generative adversarial networks (CGANs), to bridge the gap between OpenFAST simulation models representing 1.5 MW and 5 MW wind turbines. A physics-informed CGAN architecture is introduced, where a simplified turbine tower dynamics model is incorporated into the training loss to ensure physically consistent outputs. Quantitative results showed moderate to high agreement in frequency-domain features. Incorporating the physics-informed loss function improved the R 2 values by 30%, reduced the RMSE from 1.39 to 1.1 m/s 2 , and reduced training time by 82%. Furthermore, under increased turbulence intensity (IEC Category A), the RMSE remained stable at approximately 1.1 m/s 2 . While the present study is entirely simulation-based, it establishes a pipeline for evaluating physics-informed generative domain translation, which may serve as a foundation for future simulation-to-reality validation studies.

17 WIND ENERGY↗

Assembly and Repair of Photosystem II in Chlamydomonas reinhardtii

Oxygenic photosynthetic organisms use Photosystem II (PSII) to oxidize water and reduce plastoquinone. Here, we review the mechanisms by which PSII is assembled and turned over in the model green alga Chlamydomonas reinhardtii. This species has been used to make key discoveries in PSII research due to its metabolic flexibility and amenability to genetic approaches. PSII subunits originate from both nuclear and chloroplastic gene products in Chlamydomonas. Nuclear-encoded PSII subunits are transported into the chloroplast and chloroplast-encoded PSII subunits are translated by a coordinated mechanism. Active PSII dimers are built from discrete reaction center complexes in a process facilitated by assembly factors. The phosphorylation of core subunits affects supercomplex formation and localization within the thylakoid network. Proteolysis primarily targets the D1 subunit, which when replaced, allows PSII to be reactivated and completes a repair cycle. While PSII has been extensively studied using Chlamydomonas as a model species, important questions remain about its assembly and repair which are presented here.

59 BASIC BIOLOGICAL SCIENCES↗

OpenACC Unified Programming Environment for Multi-hybrid Acceleration with GPU and FPGA

Accelerated computing in HPC such as with GPU, plays a central role in HPC nowadays. However, in some complicated applications with partially different performance behavior is hard to solve with a single type of accelerator where GPU is not the perfect solution in these cases. We are developing a framework and transpiler allowing the users to program the codes with a single notation of OpenACC to be compiled for multi-hybrid accelerators, named MHOAT (Multi-Hybrid OpenACC Translator) for HPC applications. MHOAT parses the original code with directives to identify the target accelerating devices, currently supporting NVIDIA GPU and Intel FPGA, dispatching these specific partial codes to background compilers such as NVIDIA HPC SDK for GPU and OpenARC research compiler for FPGA, then assembles binaries for the final object with FPGA bitstream file. In this paper, we present the concept, design, implementation, and performance evaluation of a practical astrophysics simulation code where we successfully enhanced the performance up to 10 times faster than the GPU-only solution.

Boku, Taisuke↗

The lowdown on breakdown: Open questions in plant proteolysis

Abstract Proteolysis, including post-translational proteolytic processing as well as protein degradation and amino acid recycling, is an essential component of the growth and development of living organisms. In this article, experts in plant proteolysis pose and discuss compelling open questions in their areas of research. Topics covered include the role of proteolysis in the cell cycle, DNA damage response, mitochondrial function, the generation of N-terminal signals (degrons) that mark many proteins for degradation (N-terminal acetylation, the Arg/N-degron pathway, and the chloroplast N-degron pathway), developmental and metabolic signaling (photomorphogenesis, abscisic acid and strigolactone signaling, sugar metabolism, and postharvest regulation), plant responses to environmental signals (endoplasmic-reticulum-associated degradation, chloroplast-associated degradation, drought tolerance, and the growth-defense trade-off), and the functional diversification of peptidases. We hope these thought-provoking discussions help to stimulate further research.

Eckardt, Nancy A. (ORCID:0000000316581412)↗

The Kinematics of Proal Chewing in Rats

Chewing kinematics are well-documented in several mammal species with fused mandibular symphyses, but relatively understudied in mammals with an unfused symphysis, despite the fact that more than half of extant Mammalia have an unfused mandibular symphysis. The Wistar brown rat (Rattus norvegicus) is widely used in human health research, including studies of mastication or neurological studies where mastication is the output behavior. These animals are known to have unfused mandibular symphyses and proal jaw (rostrocaudal) motion during occlusion, but the lack of high resolution, 3-dimensional analysis of rat chewing leaves the functional significance of symphyseal mobility unknown. We used biplanar fluoroscopy and the X-ray reconstruction of moving morphology workflow to quantify chewing kinematics in 3 brown rats, quantifying overall jaw kinematics, including motions about the temporomandibular joint and unfused mandibular symphysis. During occlusion, the teeth and the mandibular condyle translate almost exclusively anteriorly (proal) during occlusion, with little motion in any other degrees of freedom. At the symphysis, we observed minimal flexion throughout the chew cycle. Overall, there are fundamental differences in jaw kinematics between rats and other mammals and therefore rats are not an appropriate proxy for ancestral mammal jaw mechanics. Additionally, differences between humans and rat chewing kinematics must be considered when using rats as a clinical model for pathological feeding research.

59 BASIC BIOLOGICAL SCIENCES↗

Selective activation of methane C–H bond in the presence of methanol

Direct methane to methanol (MTM) conversion over heterogeneous catalysts is a promising route for valorization of methane. The methane C-H bond activation is considered as the key step of the MTM and is the focus of considerable research activity. However, the formed methanol typically suffers from overoxidation largely due to the cleavage of a methanol C-H bond, whose bond dissociation energy is ca. 0.5 eV lower than that of the methane C-H bond, which usually translates to a transition state energy of the methanol C-H bond cleavage that is ca. 0.55 eV lower than that of methane whenever the reactions proceed through a radical mechanism. Furthermore, we propose a general approach for decreasing the transition state energy difference between the CH 4 and CH 3 OH C-H bond dissociation. When a metal-oxide supported cationic transition metal atom and a neighboring oxygen on the oxide surface serve as the active site, the transition state energy difference through a surface-stabilized pathway can be noticeably narrowed as compared with that of a radical pathway. For Ir, Pt and Rh-doped anatase TiO 2 (101), the CH 4 C-H bond activation can be preferred over that of CH 3 OH at significant methanol mole fraction. Also, for PdAu alloys containing adsorbed oxygen and positively charged Pd, calculations suggest in agreement with recent experiments (Science 367 (6474), 193-197) that the CH 4 C-H bond can be selectively activated in the presence of CH 3 OH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Validating Connected, Automated, and Electric Vehicle Models and Simulation - Research Performance Progress Report

The objective of this project is to test connected and automated vehicles with both electrified and internal combustion engine powertrains to support updates and validation of modeling and simulation tools. This includes the development of the components and network architecture to execute and collect empirical data for multiple scenarios and traffic interactions. Specific program objectives include: • Translate Lab algorithms into vehicle and infrastructure controls • Conduct physical testing at realistic scale • Evaluate system performance • Improve models using empirical data • Improve control algorithms from lessons learned • Identify system and algorithm assumptions which need refinement It is important to note that the objective of this project was not to demonstrate the efficacy of the selected algorithms to improve energy efficiency but rather to validate and improve modeling and simulation tools using empirical data. While it is a desirable outcome to concurrently demonstrate improved energy efficiency through use of these algorithms, and in most cases that was the outcome, the success of this project was not predicated on the performance of the algorithm towards improving energy efficiency across all scenarios and test matrices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dynamically Downscaled Hourly Future Weather Data with 12-km Resolution Covering Most of North America

This is an hourly future weather dataset for energy modeling applications. The dataset is primarily based on the output of a regional climate model (RCM), i.e., the Weather Research and Forecasting (WRF) model version 3.3.1. The WRF simulations are driven by the output of a general circulation model (GCM), i.e., the Community Climate System Model version 4 (CCSM4). This dataset is in the EPW format, which can be read or translated by more than 25 building energy modeling programs (e.g., EnergyPlus, ESP-r, and IESVE), energy system modeling programs (e.g., System Advisor Model (SAM)), indoor air quality analysis programs (e.g., CONTAM), and hygrothermal analysis programs (e.g., WUFI). It contains 13 weather variables, which are the Dry-Bulb Temperature, Dew Point Temperature, Relative Humidity, Atmospheric Pressure, Horizontal Infrared Radiation Intensity from Sky, Global Horizontal Irradiation, Direct Normal Irradiation, Diffuse Horizontal Irradiation, Wind Speed, Wind Direction, Sky Cover, Albedo, and Liquid Precipitation Depth. The weather data is created for two emissions scenarios: RCP4.5 and RCP8.5 and spans two 10-year time slices in the future: 2045 - 2054 and 2085 - 2094. It offers a spatial resolution of 12 km by 12 km with extensive coverage across most of North America. Due to the enormous size of the entire dataset, in the first stage of its distribution, we provide 20 years of future weather data for the centroid of each Public Use Microdata Area (PUMA), excluding Hawaii. PUMAs are non-overlapping, statistical geographic areas that partition each state or equivalent entity into geographic areas containing no fewer than 100,000 people each. The 2,378 PUMAs as a whole cover the entirety of the U.S. The weather data can be utilized alongside the large-scale energy analysis tools, ResStock and ComStock, developed by National Renewable Energy Laboratory, whose smallest resolution is at the PUMA scale. The data for RCP4.5 is still being processed and will be published soon.

Array↗