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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. 1: Theoretical development and application to yearly predictions for selected cities in the United States

A rain attenuation prediction model is described for use in calculating satellite communication link availability for any specific location in the world that is characterized by an extended record of rainfall. Such a formalism is necessary for the accurate assessment of such availability predictions in the case of the small user-terminal concept of the Advanced Communication Technology Satellite (ACTS) Project. The model employs the theory of extreme value statistics to generate the necessary statistical rainrate parameters from rain data in the form compiled by the National Weather Service. These location dependent rain statistics are then applied to a rain attenuation model to obtain a yearly prediction of the occurrence of attenuation on any satellite link at that location. The predictions of this model are compared to those of the Crane Two-Component Rain Model and some empirical data and found to be very good. The model is then used to calculate rain attenuation statistics at 59 locations in the United States (including Alaska and Hawaii) for the 20 GHz downlinks and 30 GHz uplinks of the proposed ACTS system. The flexibility of this modeling formalism is such that it allows a complete and unified treatment of the temporal aspects of rain attenuation that leads to the design of an optimum stochastic power control algorithm, the purpose of which is to efficiently counter such rain fades on a satellite link.

Manning, Robert M.↗
DOE OSTI2021

Development of a Turbulent Liquid Spray Atomization Model for Diesel Engine Simulations (Final Technical Report)

This project addresses the systematic lack of predictive capabilities by spray models within engine CFD codes. We develop a new modeling approach to predict the breakup of diesel sprays based on recent literature showing that liquid turbulence plays a fundamental role in spray atomization. A new body of quantitative validation data is also developed as a critical element of the project, leveraging the joint capabilities of Georgia Tech’s high-pressure continuous-flow spray chamber and Argonne National Lab’s near-nozzle x-ray diagnostics at the Advanced Photon Source. This project contributes spatially-resolved measurements of drop size distribution within well-characterized diesel injectors, Spray A and D, from the Engine Combustion Network (ECN) to the engine combustion community for the first time. Utilizing this new body of measurements, we validate and demonstrate a new spray model for diesel sprays, termed the KH-Faeth model, that predicts global and local spray characteristic more accurately than the widely adopted and employed KH model. Predicted drop size distributions are seen to predict measured drops sizes both quantitatively and predictively, with accurate response in droplet size distributions over a wide range of ambient density, injection pressure, and injector nozzle size (Spray A and D) without model tuning. The KH-Faeth model can reduce error in the predicted centerline droplet size profile by up to 80% for ECN Spray D simulations when compared to use of the widely employed KH model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Correlations Between In-Line X-ray Diffraction Data and In-Field Critical Current of Long, 4-μm Thick Film REBCO Tapes Made by Advanced MOCVD

REBa 2 Cu 3 O 7-δ (REBCO, RE = rare earth) tapes with high critical current can be very impactful in high magnetic field applications at low temperatures and power applications at high temperatures. A pilot-scale Advanced Metal Organic Chemical Vapor Deposition (MOCVD) method was used to fabricate 50-m-long, 4+μm-thick REBCO tape in a single pass. Critical currents 3.3x that of commercial HTS tapes were achieved at 20 K, 12 T in these 50-m-long tapes. An in-line 2D X-ray Diffraction (XRD) system has been used to assess the quality of the long tapes in real-time, during manufacturing. The key peaks of REBCO, REO, and BZO phases were identified and utilized for tape quality analysis. Furthermore, a 20-m tape made by Advanced MOCVD was tested over its entire length by reel-to-reel (R2R) scanning Hall-probe microscopy (SHPM) at 65 K, 0.25 T, 2 T, and 4 T. 4-mm-wide strands of Advanced MOCVD tapes showed mean critical currents at 65 K of 530 A, 200 A, and 104 A at 0.25 T, 2 T, and 4 T respectively. The combined use of in-line and offline characterization techniques provides a reliable approach for assessing long REBCO tapes during manufacturing, serving as an effective feedback source for quality control in scaled-up REBCO tape deposition processes. This advancement contributes to the production of longer and more uniform high-performance REBCO tapes for large-scale, high-field superconducting applications

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Advancing Transportation Efficiency and Electric Vehicles in Tonga: A Review of Relevant Trends, Best Practices, and Future Work

Tonga is facing a transportation sector characterized by private passenger vehicles, poorly maintained roads and walkways, and an inadequate public transit system. By understanding detailed global and regional trends for transport energy efficiency and electric vehicles (EVs) within this context, the Government of Tonga can proactively plan its future transportation systems. In addition to global and regional trends, this presentation also briefly examines Tonga's own transportation policies and actions. Jurisdictions leading in EV adoption have implemented policies such as reducing taxes on EVs compared to internal combustion engine (ICE) vehicles, providing subsidies and rebates for EV charger installation, instituting an age limit on imported ICE vehicles, and developing EV maintenance courses to expand the skill set of current automotive technicians. This presentation was developed for the Pacific Islands Workshop on Electric Mobility, held from November 28th to November 30th 2022 in Fiji. NREL presented virtually and the conference was sponsored by the Pacific Centre for Renewable Energy and Energy Efficiency (PCREEE).

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
NASA NTRS1983

Advanced Platform Systems Technology study. Volume 2: Trade study and technology selection

Three primary tasks were identified which include task 1-trade studies, task 2-trade study comparison and technology selection, and task 3-technology definition. Task 1 general objectives were to identify candidate technology trade areas, determine which areas have the highest potential payoff, define specific trades within the high payoff areas, and perform the trade studies. In order to satisfy these objectives, a structured, organized approach was employed. Candidate technology areas and specific trades were screened using consistent selection criteria and considering possible interrelationships. A data base comprising both manned and unmanned space platform documentation was used as a source of system and subsystem requirements. When requirements were not stated in the data base documentation, assumptions were made and recorded where necessary to characterize a particular spacecraft system. The requirements and assumptions were used together with the selection criteria to establish technology advancement goals and select trade studies. While both manned and unmanned platform data were used, the study was focused on the concept of an early manned space station.

Source record↗
NASA NTRSDate not supplied

Advances in X-ray Instruments to Support Mars Sample Return

The Mars 2020 Perseverance rover is currently collecting drill cores of ancient igneous and sedimentary rock in and around Jezero crater for potential transport to Earth. These samples from the martian surface will enable detailed mineralogical, geochemical, and petrological measurements to characterize ancient depositional and diagenetic environments, quantitatively age-date the samples, and identify the building blocks for life or evidence for life itself. Furthermore, these drill cores are especially precious because they may represent the most pristine samples from the martian surface and our best chance at identifying martian life, as future sample return missions may be conducted by humans that can introduce biological contaminants to the samples. Because of the importance of these samples, we must take great care in their handling, curation, and preliminary analyses so that they are preserved for scientific measurements for decades to come. In-situ measurements by Perseverance have identified minerals that further warrant special treatment of the returned samples. Hydrated sulfate carbonate, swelling clay minerals, and oxychlorine salts are extremely sensitive to changes in temperature and relative humidity. The structures of hydrated sulfates and oxychlorine minerals, in particular, readily change when exposed to different conditions, meaning the mineral assemblage of the as-returned samples may be lost if the samples aren’t handled properly. Characterizing the as-returned mineral assemblage, particularly of the salts, is essential for reconstructing past aqueous conditions and habitability. To characterize the as-returned mineral assemblage, the samples must be analyzed rapidly before phase changes occur and/or under controlled conditions (e.g., within a glove box). Significant recent advances in X-ray instrumentation for robotic exploration of the solar system have resulted in high-resolution miniaturized instruments that would provide mineralogical, geochemical, and petrological information on the returned martian samples without degradation of the mineral assemblage. Here, we describe a combined X-ray diffractometer/X-ray fluorescence spectrometer (XRD/XRF), an X-ray computed tomographic (XCT) instrument, and a scanned beam XRF mapping instrument that could be used in a glove box so that the martian samples remain under controlled conditions.

E. B. Rampe↗
DOE OSTI2026

CdTe Core: Final Technical Report (FTR)

CdTe is presently the cost-leading thin-film PV technology, directly competing with Si at scale, even when domestically manufactured. While an impressive technology, its efficiency remains much below the detailed balance limit with the largest cause due to its low photovoltage and fill factor. To realize gains, the carrier concentration, minority carrier lifetime, and interface recombination all need to be improved simultaneously over historic levels. Using a new defect chemistry (group V doping instead of copper) has been identified as a viable route using single crystal systems. This project focused on implementing this new defect chemistry in scalable, polycrystalline thin-film photovoltaic CdTe devices with tasks focusing improvements to the front interface, absorber, and rear interface as well as capability development & stakeholder engagement. The goal of the project was to establish a strategy using devices, test structures, detailed characterization, and modeling to quantify the sources of losses in state-of-the-art CdTe photovoltaic devices. Using this strategy and advanced synthesis, losses at the front interface, absorber, and rear interface were worked on in parallel. The final objective was to significantly improve the voltage deficit in CdTe devices to enable improvements in photovoltage and efficiency that can be implemented by industry in the near-term. Over the course of the project, the team developed new characterization techniques, analysis, and modeling which were then applied to state-of-the-art materials generated internally and collaboratively. In particular to enable rapid progress, NREL worked closely with First Solar where NREL grew complete devices as well as ones that interleaved process steps where First Solar had completed different steps such as absorber growth or absorber growth and activation using their baseline methods. Using detailed characterization and analysis including photoemission, photoluminescence, and scanning probe techniques enabled understanding of the loss pathways and area for improvements in our own and First Solar s materials. Ultimately, this contributed to the first series of new world record CdTe efficiencies since 2016, culminating in a 23.1% certified cell that was P-doped along with As-doped cells of similar performance. Internally, NREL improved the statistical variation in baseline As-doped devices and improved average photovoltage by over 100 mV. This was done through an improvement in absorber quality, changed front interface, and improved back contact. In addition to materially improving the fabrication processes at NREL, characterization, analysis, and modeling were developed and disseminated. NREL also played a pivotal role in community building over the course of this project working closely with the Cadmium Telluride Accelerator Consortium. NREL worked in a series of collaborations with academic and industry partners, leveraging knowledge and innovations from this project, as well as helped organize a series of workshops to ensure rapid progress in the field. Working closely with the academic community has led to a dissemination of knowledge; working with First Solar as increased US competitiveness First Solar expanded domestic production to ~10 GW and opened new facilities.

14 SOLAR ENERGY↗
DOE OSTI2020

An outlook into the flat land of 2D materials beyond graphene: synthesis, properties and device applications

Abstract The field of two-dimensional (2D) and layered materials continues to excite many researchers around the world who are eager to advance and innovate viable routes for large scale synthesis, doping and integration of monolayers and the development of unique characterization approaches for studying and harnessing exotic properties that will enable novel device applications. There has been a large interest in 2D materials beyond graphene, with particular emphasis on monoelemental materials (phosphorene, silicene, tellurene, etc. ), 2D compounds (MXenes, oxides, nitrides, carbides and chalcogenides), their alloys and layered van der Waals heterostructures. This is not only indicated by the significant increase in the number of peer reviewed publications each year in this area of research, but also by the surging number of conference sessions focusing on 2D materials beyond graphene. This Perspective article highlights some of the recent advances in the field from a diverse international community of theoretical and experimental researchers who participated in the symposium ‘Beyond Graphene 2D Materials—Synthesis, Properties and Device Applications’ at the Materials Research Society (MRS) Fall 2019 meeting.

McCreary, Amber (ORCID:0000000299885800)↗
DOE OSTI2021

Modeling household online shopping demand in the U.S.: a machine learning approach and comparative investigation between 2009 and 2017

Despite the rapid growth of online shopping and research interest in the relationship between online and in-store shopping, national-level modeling and investigation of the demand for online shopping with a prediction focus remain limited in the literature. Here, this paper differs from prior work and leverages two recent releases of the U.S. National Household Travel Survey (NHTS) data for 2009 and 2017 to develop machine learning (ML) models, specifically gradient boosting machine (GBM), for predicting household-level online shopping purchases. The NHTS data allow for not only conducting nationwide investigation but also at the level of households, which is more appropriate than at the individual level given the connected consumption and shopping needs of members in a household. We follow a systematic procedure for model development including employing Recursive Feature Elimination algorithm to select input variables (features) in order to reduce the risk of model overfitting and increase model explainability. Among several ML models, GBM is found to yield the best prediction accuracy. Extensive post-modeling investigation is conducted in a comparative manner between 2009 and 2017, including quantifying the importance of each input variable in predicting online shopping demand, and characterizing value-dependent relationships between demand and the input variables. In doing so, two latest advances in machine learning techniques, namely Shapley value-based feature importance and Accumulated Local Effects plots, are adopted to overcome inherent drawbacks of the popular techniques in current ML modeling. The modeling and investigation are performed at the national level, with a number of findings obtained. The models developed and insights gained can be used for online shopping-related freight demand generation and may also be considered for evaluating the potential impact of relevant policies on online shopping demand.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Genome-scale modelling of the primary-specialized metabolism interface

Environmental challenges and development require plants to reallocate resources between primary and specialized metabolites to survive. Genome-scale metabolic models, which map carbon flux through metabolic pathways, are a valuable tool in the study of tradeoffs that arise at this interface. Due to annotation gaps, models that characterize all the enzymatic steps in individual specialized pathways and their linkages to each other and to central carbon metabolism are difficult to construct. Recent studies have successfully curated subsystems of specialized metabolism and characterized the interfaces where flux is diverted to the precursors of glucosinolates, terpenes, and anthocyanins. Although advances in metabolite profiling can help to constrain models at this interface, quantitative analysis remains challenging because of the different timescales on which specialized metabolites from constitutive and reactive pathways accumulate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Probing the In Situ Pseudocapacitive Charge Storage in Ti 3 C 2 MXene Thin Films with X-ray Reflectivity

MXenes are a large family of two-dimensional materials that are attractive for energy storage due to their high-rate charging capabilities as well as for electrochemical actuators, water purification, and many other technologies. Ion intercalation during electrochemically driven charge and discharge processes is the fundamental process associated with MXene functionality, which we have characterized here using in situ and operando X-ray reflectivity (XRR). Experiments performed at the Advanced Photon Source at Argonne National Laboratory monitored the changes in the structure of a Ti 3 C 2 MXene film on a platinum current collector as a function of static applied potential between 0.3 and –0.7 V vs Ag/AgCl in an aqueous 0.1 M Li 2 SO 4 electrolyte. Negative potential sweeps lead to a contraction of 1.2 Å in the interlayer spacing and a loss of electron density between the layers, likely due to Li + ion insertion and water removal. The change in lattice spacing includes a continuous variation vs potential as well as an additional discrete contraction that occurs near –0.35 V that has the characteristics of a first-order transition. The continuous change in the MXene interlayer spacing is associated with the capacitive charge, while the discrete change in structure correlated to the weak feature in the cyclic voltammogram at –0.35 V can be interpreted as either a pseudocapacitive charging process or a potential-dependent change in capacity.

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

Mechanistic Insights toward Accelerated Selenium-Catalyzed Allylic and Propargylic C–H Amination

Catalytic allylic and propargylic C–H aminations present valuable opportunities for the late-stage modification of pharmacophores in drug discovery. However, modern methodology is limited by reliance on expensive transition metal catalysts or slow reactivity. While selenium-catalyzed methods avoid some of these issues, in their current state, they require high catalyst loadings (15 mol %), superstoichiometric quantities of the amine and oxidant source, and long reaction times. Furthermore, our understanding of the mechanism remains incomplete: e.g., what is the catalytically active species, how is the precatalyst converted to it, and what is the role of the ligand? Here, in this paper, we report an N-heterocyclic carbene selenide (NHC-Se) that allows for substantially reduced loadings of selenium without sacrificing reaction time, improves conversions and yields for challenging substrates, and even exhibits the capacity to catalyze 1,4-allylic diamination of alkenes. To understand the origin of the enhanced activity compared to the state-of-the-art NHC-Se precatalyst, we conducted a mechanistic study that supports ligand-free selenium diimide as the active enophile in these systems, while the NHC-derived byproducts, like the corresponding urea, facilitate turnover. We also isolate and structurally characterize NHC-Se mono- and diimido species and explore their mechanistic role. Thus, this work advances C–H amination methodology, our understanding of its mechanistic underpinnings, and selenium chemistry at large.

allylic amination↗
DOE OSTI2021

Is the testing effect ready to be put to work? Evidence from the laboratory to the classroom.

The testing effect refers to the benefits to retention that result from structuring learning activities in the form of a test. As educators consider implementing test-enhanced learning paradigms in real classroom environments, we think it is critical to consider how an array of factors affecting test-enhanced learning in laboratory studies bear on test-enhanced learning in real-world classroom environments. As such, this review discusses the degree to which test feedback, test format (of formative tests), number of tests, level of the test questions, timing of tests (relative to initial learning), and retention duration have import for testing effects in ecologically valid contexts (e.g., classroom studies). Attention is also devoted to characteristics of much laboratory testing-effect research that may limit translation to classroom environments, such as the complexity of the material being learned, the value of the testing effect relative to other generative learning activities in classrooms, an educational orientation that favors criterial tests focused on transfer of learning, and online instructional modalities. We consider how student-centric variables present in the classroom (e.g., cognitive abilities, motivation) may have bearing on the effects of testing-effect techniques implemented in the classroom. We conclude that the testing effect is a robust phenomenon that benefits a wide variety of learners in a broad array of learning domains. Still, studies are needed to compare the benefit of testing to other learning strategies, to further characterize how individual differences relate to testing benefits, and to examine whether testing benefits learners at advanced levels.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Coherent phonon flatband generated in GaAs/AlAs superlattices via layer-selective optical pumping

Flatbands, characterized by their dispersionless energy levels in electronic, magnetic, and phononic systems, hold substantial potential for advancements in electronics and quantum information processing. Most flatbands exist in thermal equilibrium and cannot be easily created or annihilated externally, limiting their flexibility as switchable knobs for use in microelectronics and quantum applications. In our work, we demonstrate the generation of a coherent phonon flatband in a GaAs/AlAs superlattice using 800 nm femtosecond laser pulses. This coherent phonon flatband does not correspond to a phonon eigenmode at equilibrium and exhibits strong coupling with two branches of coherently excited longitudinal phonon modes. With molecular dynamics simulations, we show more generally that the coherent phonon flatband can be induced by coherently and spatially modulated optical excitations of superlattice structures. Our results highlight a pathway for coherent phonon flatband creation in the time domain that can be generalized to various superlattice systems, potentially inspiring the realization of coherent flatband generation of other quasiparticles.

Condensed-matter physics↗
DOE OSTI2021

The synthesis and electrical transport properties of carbon/Cr 2 GaC MAX phase composite microwires

While MAX phases offer an exotic combination of ceramic and metallic properties, rendering them a unique class of materials, their applications remain virtually hypothetical. To overcome this shortcoming, a sol–gel based route is introduced that allows access to microwires in the range of tens of micrometers. Thorough structural characterization through XRD, SEM, EDS, and AFM demonstrates a successful synthesis of carbonaceous Cr2GaC wires, and advanced low temperature electronic transport measurements revealed resistivity behavior dominated by amorphous carbon. Here, the tunability of electronic behavior of the obtained microwires is shown by a halide post-synthesis treatment, allowing purposeful engineering of the microwires’ electrical conductivity. Raman studies revealed the polyanionic nature of the intercalated halides and a slow decrease in halide concentration was concluded from time-dependent conductivity measurements. Based on these findings, the process is considered a viable candidate for fabricating chemiresistive halogen gas sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

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

Efficient sampling of free energy landscapes with functions in Sobolev spaces

Molecular simulations of biological and physical phenomena generally involve sampling complicated, rough energy landscapes characterized by multiple local minima. In this work, we introduce a new family of methods for advanced sampling that draw inspiration from functional representations used in machine learning and approximation theory. As shown here, such representations are particularly well suited for learning free energies using artificial neural networks. As a system evolves through phase space, the proposed methods gradually build a model for the free energy as a function of one or more collective variables, from both the frequency of visits to distinct states and generalized force estimates corresponding to such states. Implementation of the methods is relatively simple and, more importantly, for the representative examples considered in this work, they provide computational efficiency gains of up to several orders of magnitude over other widely used simulation techniques.

Approximation theory↗
DOE OSTI2020

The 2020 photovoltaic technologies roadmap

Over the past decade, the global cumulative installed photovoltaic (PV) capacity has grown exponentially, reaching 591 GW in 2019. Rapid progress was driven in large part by improvements in solar cell and module efficiencies, reduction in manufacturing costs and the realization of levelized costs of electricity that are now generally less than other energy sources and approaching similar costs with storage included. Given this success, it is a particularly fitting time to assess the state of the photovoltaics field and the technology milestones that must be achieved to maximize future impact and forward momentum. This roadmap outlines the critical areas of development in all of the major PV conversion technologies, advances needed to enable terawatt-scale PV installation, and cross-cutting topics on reliability, characterization, and applications. Each perspective provides a status update, summarizes the limiting immediate and long-term technical challenges and highlights breakthroughs that are needed to address them. In total, this roadmap is intended to guide researchers, funding agencies and industry in identifying the areas of development that will have the most impact on PV technology in the upcoming years.

14 SOLAR ENERGY↗