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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dynamic structure of active sites in ceria-supported Pt catalysts for the water gas shift reaction

Oxide-supported noble metal catalysts have been extensively studied for decades for the water gas shift (WGS) reaction, a catalytic transformation central to a host of large volume processes that variously utilize or produce hydrogen. There remains considerable uncertainty as to how the specific features of the active metal-support interfacial bonding—perhaps most importantly the temporal dynamic changes occurring therein—serve to enable high activity and selectivity. Here we report the dynamic characteristics of a Pt/CeO 2 system at the atomic level for the WGS reaction and specifically reveal the synergistic effects of metal-support bonding at the perimeter region. We find that the perimeter Pt 0 -O vacancy -Ce 3+ sites are formed in the active structure, transformed at working temperatures and their appearance regulates the adsorbate behaviors. We find that the dynamic nature of this site is a key mechanistic step for the WGS reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Scalable multiphoton quantum metrology with neither pre- nor post-selected measurements

The quantum statistical fluctuations of electromagnetic fields establish a limit, known as the shot-noise limit, on the sensitivity of optical measurements performed with classical technologies. However, quantum technologies are not constrained by this shot-noise limit. In this regard, the possibility of using every photon produced by quantum sources of light to estimate small physical parameters, beyond the shot-noise limit, constitutes one of the main goals of quantum optics. Here, we experimentally demonstrate a scalable protocol for quantum-enhanced optical phase estimation across a broad range of phases, with neither pre- nor post-selected measurements. This is achieved through the efficient design of a source of spontaneous parametric downconversion in combination with photon-number-resolving detection. The robustness of two-mode squeezed vacuum states against loss allows us to outperform schemes based on N00N states, in which the loss of a single photon is enough to remove all phase information from a quantum state. In contrast to other schemes that rely on N00N states or conditional measurements, the sensitivity of our technique could be improved through the generation and detection of high-order photon pairs. This unique feature of our protocol makes it scalable. Furthermore, our work is important for quantum technologies that rely on multiphoton interference such as quantum imaging, boson sampling, and quantum networks.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey quasar sample: testing observational systematics on the Baryon Acoustic Oscillation measurement

ABSTRACT Baryon Acoustic Oscillations (BAO) are considered to be a very robust standard ruler against various systematics. This premise has been tested against observational systematics, but not to the level required for the next generation of galaxy surveys such as the Dark Energy Spectroscopic Instrument (DESI) and Euclid. In this paper, we investigate the effect of observational systematics on the BAO measurement of the final sample of quasars from the extended Baryon Oscillation Spectroscopic Survey Data Release 16 in order to prepare and hone a similar analysis for upcoming surveys. We employ catalogues with various treatments of imaging systematic effects using linear and neural network-based non-linear approaches and consider how the BAO measurement changes. We also test how the variations to the BAO fitting model respond to the observational systematics. As expected, we confirm that the BAO measurements obtained from the DR16 quasar sample are robust against imaging systematics well within the statistical error, while reporting slightly modified constraints that shift the line-of-sight BAO signal by less than 1.1 per cent. We use realistic simulations with similar redshift and angular distributions as the DR16 sample to conduct statistical tests for validating the pipeline, quantifying the significance of differences, and estimating the expected bias on the BAO scale in future high-precision data sets. Although we find a marginal impact for the eBOSS QSO data, the work presented here is of vital importance for constraining the nature of dark energy with the BAO feature in the new era of big data cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A framework for materials informatics education through workshops

The burgeoning field of materials informatics necessitates a focus on educating the next generation of materials scientists in the concepts of data science, artificial intelligence (AI), and machine learning (ML). In addition to incorporating these topics in undergraduate and graduate curricula, regular hands-on workshops present the most effective medium to initiate researchers to informatics and have them start applying the best AI/ML tools to their own research. With the help of the Materials Research Society (MRS), members of the MRS AI Staging Committee, and a dedicated team of instructors, we successfully conducted workshops covering the essential concepts of AI/ML as applied to materials data, at both the Spring and Fall Meetings in 2022, with plans to make this a regular feature in future meetings. Here, in this article, we discuss the importance of materials informatics education via the lens of these workshops, including details such as learning and implementing specific algorithms, the crucial nuts and bolts of ML, and using competitions to increase interest and participation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

MetaHeuristic Feature Selection for Energy Group Optimization and Analysis

Energy discretization is a crucial component of deterministic neutron transport simulations. Metaheuristic (MH) optimizers are effective algorithms to determine group structures that maximize both solution accuracy and computational efficiency. This project establishes a framework for optimizing group structures for PARTISN simulations using the Python library MEALPY. Group structure optimization is formulated as a binary feature selection problem, and results are investigated with permutation and material importance techniques to determine physically relevant energy bounds. We conclude that MH optimizers find group structures that drastically improve flux calculations while preserving k-effective accuracy. Further, we find that individual energy bounds are not necessarily physically relevant, but rather specific energy ranges are.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Transcriptome and Degradome Profiling Reveals a Role of miR530 in the Circadian Regulation of Gene Expression in Kalanchoë marnieriana

Crassulacean acid metabolism (CAM) is an important photosynthetic pathway for plant adaptation to dry environments. CAM plants feature a coordinated interaction between mesophyll and epidermis functions that involves refined regulations of gene expression. Plant microRNAs (miRNAs) are crucial post-transcription regulators of gene expression, however, their roles underlying the CAM pathway remain poorly investigated. Here, we present a study characterizing the expression of miRNAs in an obligate CAM species Kalanchoë marnieriana. Through sequencing of transcriptome and degradome in mesophyll and epidermal tissues under the drought treatments, we identified differentially expressed miRNAs that were potentially involved in the regulation of CAM. In total, we obtained 84 miRNA genes, and eight of them were determined to be Kalanchoë-specific miRNAs. It is widely accepted that CAM pathway is regulated by circadian clock. We showed that miR530 was substantially downregulated in epidermal peels under drought conditions; miR530 targeted two tandem zinc knuckle/PLU3 domain encoding genes (TZPs) that were potentially involved in light signaling and circadian clock pathways. Our work suggests that the miR530-TZPs module might play a role of regulating CAM-related gene expression in Kalanchoë.

Kalanchoë↗
DOE OSTI2021

IoT Intrusion Detection Taxonomy, Reference Architecture, and Analyses

This paper surveys the deep learning (DL) approaches for intrusion-detection systems (IDSs) in Internet of Things (IoT) and the associated datasets toward identifying gaps, weaknesses, and a neutral reference architecture. A comparative study of IDSs is provided, with a review of anomaly-based IDSs on DL approaches, which include supervised, unsupervised, and hybrid methods. All techniques in these three categories have essentially been used in IoT environments. To date, only a few have been used in the anomaly-based IDS for IoT. For each of these anomaly-based IDSs, the implementation of the four categories of feature(s) extraction, classification, prediction, and regression were evaluated. We studied important performance metrics and benchmark detection rates, including the requisite efficiency of the various methods. Four machine learning algorithms were evaluated for classification purposes: Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), and an Artificial Neural Network (ANN). Therefore, we compared each via the Receiver Operating Characteristic (ROC) curve. The study model exhibits promising outcomes for all classes of attacks. The scope of our analysis examines attacks targeting the IoT ecosystem using empirically based, simulation-generated datasets (namely the Bot-IoT and the IoTID20 datasets).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Light-duty Plug-in Electric Vehicles in China: Evolution, Competition, and Outlook

China's plug-in electric vehicle (PEV) market with stocks at 7.8 million is the world's largest in 2021, and it accounts for half of the global PEV growth in 2021. The PEV market in China has dramatically evolved since the pandemic in 2020: over 20% of all new PEV sales are from China by mid-2022. Recent features of PEV market dynamics, consumer acceptance, policies, and infrastructure have important implications for both the global energy market and manufacturing stakeholders. From the perspective of demand pull-supply push, this study analyzes China's PEV industry with a market dynamics framework by reviewing sales, product and brand, infrastructure, and government policies from the last few years and outlooking the development of the new government’s 14th Five-Year Plan (2021-2025). From the demand side, small-sized sedans and compact sport utility vehicles with increased electric ranges are both popular for PEVs, and the electric range of over 60% of new battery electric vehicles in 2021 has been longer than 400 km. From the supply side, although foreign brands like Tesla are still competitive, the products by Chinese domestic automakers like BYD are becoming more attractive and cannibalizing the high-end market. However, the production capacity and cost of PEVs may be limited by the upstream of the supply chain – the battery manufacturing and supply chain inflation. In addition, it is also uncertain how much sales demand impacts will be caused by the potential global economic recession. The government firmly supports electrification and decarbonization of the vehicle industry by emphasizing the importance of the vehicle industry for promoting the greenhouse gas net zero by 2060. The dual-credit policy is regarded as the most critical regulation in a bid to restrain fuel consumption and promote PEV share. Still, the market is facing some technological obstacles, such as battery safety and driving range anxiety, before real prosperity. In addition, the Chinese electric vehicle market is seeing a trend toward the development of new technologies such as vehicle-to-X, autonomous driving, and connected vehicles.

Hao, Xu↗
NASA NTRS1976

Hydrogen molecules in interstellar space

The most important results obtained from Copernicus satellite observations of ultraviolet H2 absorption features are summarized. The properties of the hydrogen molecule are described along with the radiative processes in which it can be involved. Techniques and equipment used in observing H2 absorption features from space are reviewed. The results are discussed in terms of the fraction of hydrogen in molecular form, rotational excitation of H2, physical conditions within interstellar gas clouds, and approaching clouds characterized by high excitation and negative radial velocity. It is shown that: (1) an appreciable fraction of the hydrogen in denser and thicker clouds is molecular, (2) at least some of the interstellar clouds are far from pressure equilibrium, (3) the approaching clouds are apparently dense thick sheets moving toward the sun as viewed in the local standard of rest, (4) these clouds are probably shock waves produced in the interstellar gas by old supernova remnants or expanding H II regions, and (5) the abundances relative to H of such elements as O, Mg, Si, and Cl in these clouds are nearly equal to the solar values, which is in contrast to the depletions observed in many other interstellar clouds.

Spitzer, L.↗
NASA NTRS1976

Development of the earth-moon system with implications for the geology of the early earth

Established facts regarding the basic features of the earth and the moon are reviewed, and some important problems involving the moon are discussed (extent of melting, time of crustal differentiation and nature of bombardment, bulk chemical composition, and nature and source of mare basins), with attention given to the various existing theories concerning these problems. Models of the development of the earth-moon system from the solar nebula are examined, with particular attention focused on those that use the concept of capture with disintegration. Impact processes in the early crust of the earth are briefly considered, with attention paid to Green's (1972) suggestion that Archaean greenstone belts may be the terrestrial equivalent of lunar maria.

Smith, J. V.↗
NASA NTRS1986

Field spectroscopy of agricultural crops

The development of the full potential of multispectral data acquired from satellites, requires quantitative knowledge, and physical models of the spectral properties of specific earth surface features. Knowledge of the relationships between spectral-radiometric characteristics and important biophysical parameters of agricultural crops and soils can best be obtained by carefully controlled studies of fields or plots. It is important to select plots where data describing the agronomic-biophysical properties of the crop canopies and soil background are attainable, taking into account also the feasibility of frequent timely calibrated spectral measurements. The term 'field spectroscopy' is employed for this research. The present paper is concerned with field research which was sponsored by NASA as part of the AgRISTARS Supporting Research Project. Attention is given to field research objectives, field research instrumentation, measurement procedures, spectral-temporal profile modeling, and the effects of cultural and environmental factors on crop reflectance.

Bauer, M. E.↗
NASA NTRS1985

Hyperion - Analysis of Voyager observations

Voyager imges of Hyperion are analyzed with respect to spin state, dimensions and shape, surface features, photometry, and colors. It is suggested that the two most important observations concerning Hyperion are the demonstration of the satellite's unusual spin state and the discovery of the apparent low density of large craters on the satellite's surface. A possible implication of such a reduced density of craters is that the last important fragmentation of Hyperion might have occurred near the end or after the period of initial heavy bombardment.

Thomas, P.↗
NASA NTRS1990

Effects of the driving mechanism in MHD simulations of coronal mass ejections

Results of time-dependent MHD simulations of mass ejections in the solar coronal are presented. Previous authors have shown that results from simulations using a thermal driving mechanism are consistent with the observations only if an elaborate model of the initial corona is used. The first simulation effort, using a simple model of a plasmoid as the driving mechanism and a simple model of the initial corona, produces results that are also consistent with many observational features, suggesting that the nature of the driving mechanism plays an important role in determining the subsequent evolution of mass ejections. First simulations are based on the assumption that mass ejections are driven by magnetic forces.

Linker, J. A.↗
NASA NTRS1991

Analysis of Fluctuating Static Pressure Measurements in a Large High Reynolds Number Transonic Cryogenic Wind Tunnel

Dynamic measurements of fluctuating static pressure levels were made using flush mounted high frequency response pressure transducers at eleven locations in the circuit of the National Transonic Facility (NTF) over the complete operating range of this wind tunnel. Measurements were made at test section Mach numbers from 0.2 to 1.2, at pressure from 1 to 8.6 atmospheres and at temperatures from ambient to -250 F, resulting in dynamic flow disturbance measurements at the highest Reynolds numbers available in a transonic ground test facility. Tests were also made independently at variable Mach number, variable Reynolds number, and variable drivepower, each time keeping the other two variables constant thus allowing for the first time, a distinct separation of these three important variables. A description of the NTF emphasizing its flow quality features, details on the calibration of the instrumentation, results of measurements with the test section slots covered, downstream choke, effects of liquid nitrogen injection and gaseous nitrogen venting, comparisons between air and nitrogen, isolation of the effects of Mach number, Reynolds number, and fan drive power, and identification of the sources of significant flow disturbances is included. The results indicate that primary sources of flow disturbance in the NTF may be edge-tones generated by test section sidewall re-entry flaps and the venting of nitrogen gas from the return leg of the tunnel circuit between turns 3 and 4 in the cryogenic mode of operation. The tests to isolate the effects of Mach number, Reynolds number, and drive power indicate that Mach number effects predominate. A comparison with other transonic wind tunnels shows that the NTF has low levels of test section fluctuating static pressure especially in the high subsonic Mach number range from 0.7 to 0.9.

Igoe, William B.↗
NASA NTRS1993

Plasma waves as indicators of the termination shock

The plasma wave receivers on the Voyager spacecraft will likely provide indicators of both the actual crossing of the termination shock as well as precursors of the shock crossing. Since the electron foreshock can extend considerable distances upstream of the termination shock, the detection of these waves can provide as many as several weeks warning that a crossing of the termination shock is imminent. Electrostatic turbulence associated with planetary bow shocks themselves is also an expected feature of the solar wind termination shock and will provide an important signature with which to identify the shock and to provide information on its thickness and fundamental processes. Both upstream Langmuir waves and electrostatic wave turbulence can often be found in conjunction with interplanetary shocks, although the generally weaker nature of these shocks often leads to weaker plasma wave signatures than observed at planetary bow shocks. We demonstrate with Voyager observations that the amplitudes expected for each of these phenomena are well within the range of detectability by the Voyager plasma wave receiver even for termination shock distances exceeding 100 AU.

Kurth, W. S.↗
NASA NTRS1995

Airborne spectrograph for the thermal IR: Broadband Array Spectrograph System

Spectroscopic studies in the 'fingerprint' region of the thermal IR from 3 to 14 microns of celestial dust components and the overall energy distribution of the sources are best served by moderate spectral resolution (R = lambda/Delta lambda approximately 30 to 200), high sensitivity observations. Spectral purity and the reproducibility of the spectral shape are critical as well, when using the spectral shape to assign temperatures to dust grains or to gas clouds based on the wavelength and shape of molecular bands. These sensor attributes are also important to the use of wavelengths and ratios of solid state features to derive compositions of dust grains in celestial sources. The advent of high quality linear arrays of blocked impurity band (BIB) detectors of Si:As permitted the development of a state-of-the-art, patented, cooled prism spectrograph. Developed at The Aerospace Corporation largely with in-house funds, the Broadband Array Spectrograph System (BASS) has been used for a variety of remote sensing applications, but especially for IR astronomical studies on the Kuiper Airborne Observatory and at the NASA Infrared Telescope Facility (IRTF). The attributes of the spectrograph, specifically having the pupil imaged onto the 2 linear 58 element detector arrays so that the effects of guiding errors are minimized, being able to maximally exploit the limited observing time by acquiring all 116 spectral channels simultaneously, and having all spectral channels imaged through the same aperture so that spectral mapping is readily and reliably accomplished, afford the scientist with a unique opportunity to conduct both surveys of examples of many different types of sources as well as in-depth studies of a given class of object by thoroughly sampling the class members. This duality was demonstrated with the BASS through a combination of KAO flights where spectral maps were obtained as part of in-depth studies of specific source regions (such as Orion and W3) and flights where up to 21 legs/flight were used to survey many different sources of different types.

Russell, Ray W.↗
NASA NTRS1995

Inductive Approaches to Improving Diagnosis and Design for Diagnosability

The first research area under this grant addresses the problem of classifying time series according to their morphological features in the time domain. A supervised learning system called CALCHAS, which induces a classification procedure for signatures from preclassified examples, was developed. For each of several signature classes, the system infers a model that captures the class's morphological features using Bayesian model induction and the minimum message length approach to assign priors. After induction, a time series (signature) is classified in one of the classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. A second area of research assumes two sources of information about a system: a model or domain theory that encodes aspects of the system under study and data from actual system operations over time. A model, when it exists, represents strong prior expectations about how a system will perform. Our work with a diagnostic model of the RCS (Reaction Control System) of the Space Shuttle motivated the development of SIG, a system which combines information from a model (or domain theory) and data. As it tracks RCS behavior, the model computes quantitative and qualitative values. Induction is then performed over the data represented by both the 'raw' features and the model-computed high-level features. Finally, work on clustering for operating mode discovery motivated some important extensions to the clustering strategy we had used. One modification appends an iterative optimization technique onto the clustering system; this optimization strategy appears to be novel in the clustering literature. A second modification improves the noise tolerance of the clustering system. In particular, we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus making post-clustering analysis easier.

Fisher, Douglas H.↗