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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Wing-section optimization for supersonic viscous flow

To improve the shape of a supersonic wing, an automated method that also includes higher fidelity to the flow physics is desirable. With this impetus, an aerodynamic optimization methodology incorporating thin-layer Navier-Stokes equations and sensitivity analysis had been previously developed. Prior to embarking upon the wind design task, the present investigation concentrated on testing the feasibility of the methodology, and the identification of adequate problem formulations, by defining two-dimensional, cost-effective test cases. Starting with two distinctly different initial airfoils, two independent shape optimizations resulted in shapes with similar features: slightly cambered, parabolic profiles with sharp leading- and trailing-edges. Secondly, the normal section to the subsonic portion of the leading edge, which had a high normal angle-of-attack, was considered. The optimization resulted in a shape with twist and camber which eliminated the adverse pressure gradient, hence, exploiting the leading-edge thrust. The wing section shapes obtained in all the test cases had the features predicted by previous studies. Therefore, it was concluded that the flowfield analyses and sensitivity coefficients were computed and fed to the present gradient-based optimizer correctly. Also, as a result of the present two-dimensional study, suggestions were made for the problem formulations which should contribute to an effective wing shape optimization.

Item, Cem C.↗
DOE OSTI2022

One‐Step Thermal Gradient‐ and Antisolvent‐Free Crystallization of All‐Inorganic Perovskites for Highly Efficient and Thermally Stable Solar Cells

Abstract All‐inorganic perovskites have emerged as promising photovoltaic materials due to their superior thermal stability compared to their heat‐sensitive hybrid organic–inorganic counterparts. In particular, CsPbI 2 Br shows the highest potential for developing thermally‐stable perovskite solar cells (PSCs) among all‐inorganic compositions. However, controlling the crystallinity and morphology of all‐inorganic compositions is a significant challenge. Here, a simple, thermal gradient‐ and antisolvent‐free method is reported to control the crystallization of CsPbI 2 Br films. Optical in situ characterization is used to investigate the dynamic film formation during spin‐coating and annealing to understand and optimize the evolving film properties. This leads to high‐quality perovskite films with micrometer‐scale grain sizes with a noteworthy performance of 17% (≈16% stabilized), fill factor (FF) of 80.5%, and open‐circuit voltage ( V OC ) of 1.27 V. Moreover, excellent phase and thermal stability are demonstrated even after extreme thermal stressing at 300 °C.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Influence of ion-pairing reagents on the separation of intact glycoproteins using hydrophilic-interaction liquid chromatography - high-resolution mass spectrometry

Hydrophilic-interaction liquid chromatography (HILIC) of intact proteins offers high-resolution separations of glycoforms of glycoproteins differing in the number of (neutral) glycans. However, to obtain efficient separations it is essential that the positively charged sites of the proteins are shielded by acidic (negative) ion-pair reagents (IPRs), so as to enhance the contribution of the hydroxyl groups of the (neutral) sugars in the glycoprotein. Here, we studied the influence of various IPRs that differ in physico-chemical properties, such as hydrophobicity and acidity, on the capillary-scale HILIC separation of intact (glyco)proteins. We evaluated the use of fluoroacetic acid (MFA), difluoroacetic acid (DFA), trifluoroacetic acid (TFA), and heptafluorobutyric acid (HFBA) as diluents for sample preparation, as solvents for sample loading on a reversed-phase trap prior to the HILIC separation, and as mobile-phase components for HILIC and HILIC-MS. To reduce the contribution of ion-exchange interaction with the (silica-based) stationary phase, we used an acrylamide-based monolithic column. We studied the influence of the different IPRs on each step of the separation of a mixture of proteins of different size and hydrophilicity and on the separation of the five glycoforms of ribonuclease B. The content of IPR in the sample was shown not to affect the separation and the MS detection. However, a low content of TFA and DFA in the mobile phase is favourable, as it reduces adduct formation and leads to higher signal intensity. The optimized HILIC conditions successfully resolved nine major glycoforms groups of a ~40 kDa glycoprotein horseradish peroxidase (HRP), as an example of a complex glycoprotein.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Dual-shell silicate and alumina coating for long lasting and high capacity lithium ion batteries

In this work we demonstrate a theory-driven, novel dual-shell coating system of Li 2 SrSiO 4 and Al 2 O 3 , achieved via a facile and scalable sol-gel technique on LiCoO 2 electrode particles. The optimal thickness of each coating can lead to increased specific capacity (~185 mAh/g at 0.5 C-rate) at a cut-off potential of 4.5 V, and greater cycling stability at very high C rates (up to 10 C) in half-cells with lithium metal. The mechanism of this superior performance was investigated using a combination of X-ray and electron characterization methods. It shows that the results of this investigation can inform future studies to identify still better dual-shell coating schemes, achieved by such industrially feasible techniques, for application on similar, nickel-rich cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Looking Beyond Bill Savings to Equity in Renewable Energy Microgrid Deployment

Microgrids powered by renewable energy can provide backup power to critical infrastructure during grid outages. These systems can also play an important role in advancing energy justice by providing economic, environmental, health, and resilience benefits for underserved communities. The value of microgrids is often measured by the economic savings and resilience provided, but there are other energy justice factors that should be considered. This paper describes a methodology for quantifying broader costs and benefits including utility bill savings, value of resilience, social cost of carbon, public health costs, and jobs associated with the construction and operation of microgrids. We evaluate these factors at three case study sites and find that including energy justice values in the cost-benefit analysis of microgrids can change investment decisions. When climate, health, resilience, and job creation are considered, cost-optimal microgrids include more renewable generation, leading to a 52-82% reduction in emissions and diesel fuel use. The net present values of the microgrids grow from negative $626,000-843,000 in the diesel only case to $10-16 million in the hybrid microgrid case and $12-19 million in the renewable microgrid case, indicating potential for greater microgrid deployment if energy justice values are incorporated in decision making. However, we also see large increases in capital expenses, which could limit deployment unless accompanied by innovative financing measures. These findings may be useful to communities as they seek to strengthen resilience to natural disasters while also improving public health, meeting climate goals, and providing economic opportunity for residents.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Printing thermoelectric inks toward next-generation energy and thermal devices

The ability of thermoelectric (TE) materials to convert thermal energy to electricity and vice versa highlights them as a promising candidate for sustainable energy applications. Despite considerable increases in the figure of merit zT of thermoelectric materials in the past two decades, there is still a prominent need to develop scalable synthesis and flexible manufacturing processes to convert high-efficiency materials into high-performance devices. Scalable printing techniques provide a versatile solution to not only fabricate both inorganic and organic TE materials with fine control over the compositions and microstructures, but also manufacture thermoelectric devices with optimized geometric and structural designs that lead to improved efficiency and system-level performances. In this review, we aim to provide a comprehensive framework of printing thermoelectric materials and devices by including recent breakthroughs and relevant discussions on TE materials chemistry, ink formulation, flexible or conformable device design, and processing strategies, with an emphasis on additive manufacturing techniques. Additionally, we review recent innovations in the flexible, conformal, and stretchable device architectures and highlight state-of-the-art applications of these TE devices in energy harvesting and thermal management. Perspectives of emerging research opportunities and future directions are also discussed. While this review centers on thermoelectrics, the fundamental ink chemistry and printing processes possess the potential for applications to a broad range of energy, thermal and electronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

First principles reaction discovery: from the Schrodinger equation to experimental prediction for methane pyrolysis

Our recent success in exploiting graphical processing units (GPUs) to accelerate quantum chemistry computations led to the development of the ab initio nanoreactor, a computational framework for automatic reaction discovery and kinetic model construction. In this work, we apply the ab initio nanoreactor to methane pyrolysis, from automatic reaction discovery to path refinement and kinetic modeling. Elementary reactions occurring during methane pyrolysis are revealed using GPU-accelerated ab initio molecular dynamics simulations. Subsequently, these reaction paths are refined at a higher level of theory with optimized reactant, product, and transition state geometries. Reaction rate coefficients are calculated by transition state theory based on the optimized reaction paths. The discovered reactions lead to a kinetic model with 53 species and 134 reactions, which is validated against experimental data and simulations using literature kinetic models. We highlight the advantage of leveraging local brute force and Monte Carlo sensitivity analysis approaches for efficient identification of important reactions. Both sensitivity approaches can further improve the accuracy of the methane pyrolysis kinetic model. The results in this work demonstrate the power of the ab initio nanoreactor framework for computationally affordable systematic reaction discovery and accurate kinetic modeling.

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

Active meta-learning for predicting and selecting perovskite crystallization experiments

Autonomous experimentation systems use algorithms and data from prior experiments to select and perform new experiments in order to meet a specified objective. In most experimental chemistry situations, there is a limited set of prior historical data available, and acquiring new data may be expensive and time consuming, which places constraints on machine learning methods. Active learning methods prioritize new experiment selection by using machine learning model uncertainty and predicted outcomes. Meta-learning methods attempt to construct models that can learn quickly with a limited set of data for a new task. Here in this paper, we applied the model-agnostic meta-learning (MAML) model and the Probabilistic LATent model for Incorporating Priors and Uncertainty in few-Shot learning (PLATIPUS) approach, which extends MAML to active learning, to the problem of halide perovskite growth by inverse temperature crystallization. Using a dataset of 1870 reactions conducted using 19 different organoammonium lead iodide systems, we determined the optimal strategies for incorporating historical data into active and meta-learning models to predict reaction compositions that result in crystals. We then evaluated the best three algorithms (PLATIPUS and active-learning k-nearest neighbor and decision tree algorithms) with four new chemical systems in experimental laboratory tests. With a fixed budget of 20 experiments, PLATIPUS makes superior predictions of reaction outcomes compared to other active-learning algorithms and a random baseline.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Debris-induced consequences on turbulence and vorticity in solar photovoltaic module-generated array wakes

Particle-laden flows in solar photovoltaic (PV) systems are inevitable, where wind-swept debris in open environments are carried by high winds and turbulence, coating panel surfaces or damaging structures. Particle deposition, or soiling, is a well-known issue for large-scale plants which rely on uninhibited solar rays for optimal production. But understanding the mechanisms leading to soiling requires a physical and fluid dynamics-centered focus, since turbulence dominates PV panel wakes and is also known to alter particle concentration and trajectories. This study presents an experimental campaign toward consequences of particle-laden flow between two model PV panels using time-resolved particle image velocimetry. The model array was subjected to varied particle volume fractions, including a tracer particle case and a water droplet case. Characterization of mean velocity, turbulence statistics, and mean kinetic energy within the single phase and, separately, particle phase flows showed modified features due to particle inertia. Images captured at a frequency of 1 kHz in the near wake of the upstream panel allow for a first experimental look at vorticity and convective velocity of vortex structures for single-phase and particle-phase flows which are crucial to debris transport and soiling in PV environments.

Energy & Fuels↗
DOE OSTI2021

Thermal stability and magnetization switching of composite free layer with perpendicular magnetic anisotropy

We present a micromagnetic study of a ferromagnetically exchange-coupled composite free layer design for perpendicular magnetic tunnel junctions. The thermal stability factor and critical switching current density depend on the exchange coupling strength and effective anisotropy ratio between the sublayers of the composite free layer. The energy barrier increases with an increase of the exchange coupling strength until it reaches a plateau in the strong-coupling limit. An optimal exchange coupling strength exists that leads to the minimal critical switching current and a significant improvement of the figure of merit defined as the ratio between the energy barrier and critical switching current. This behavior is obtained for smaller device sizes with uniform reversal and larger sizes with domain wall reversal.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Tritium Breeding Ratio Evaluation of Solid Breeder Concepts for the FESS-FNSF

This paper presents a parametric study of the Fusion Energy System Studies-Fusion Nuclear Science Facility’s (FNSF’s) tritium breeding performance for several solid breeder concepts, neutron multiplying materials, and blanket materials, assuming volume fractions based on the most recent FNSF design as a realistically representative fusion facility. In this study, we initially surveyed the tritium breeding ratio (TBR) of several solid breeder concepts by employing a simplified but efficient one-dimensional (1-D) infinite cylinder reduced-order model (ROM). Parametric studies were performed with the ROMs for the full range of breeder-to-multiplier ratios to identify the optimum mixture compositions for each breeder type that would lead to a maximum TBR. These optimized breeder-multiplier combinations were then homogenized with FNSF blanket component materials to estimate their impacts on the TBR. Subsequently, as a validation step for the optimal designs, TBR calculations were performed using a more realistic modified 1-D ROM with inner and outer breeding regions, as well as with a fully detailed 22.5-deg three-dimensional (3-D) sector of the FNSF to assess the impact of geometry details on the TBR. The differences between the two 1-D models were negligible, while the ROMs were able to correctly predict trends and identify the maximum and minimum TBR cases, as well as show consistent biases relative to the results produced by the full 3-D, 22.5-deg sector for specific breeder/multiplier combinations. Solid breeder concepts such as Li 2 O, Li 4 SiO 4 , and Li 8 ZrO 6 outperformed all others in this study in terms of TBR performance when combined with all the neutron multiplier materials selected. Here, an underlying goal of this study was to develop and improve rapid and reliable ROMs to aid designers during parametric optimizations of highly complex and computationally expensive fusion models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Quantum simulation of second-quantized Hamiltonians in compact encoding

We describe methods for simulating general second-quantized Hamiltonians using the compact encoding, in which qubit states encode only the occupied modes in physical occupation number basis states. These methods apply to second-quantized Hamiltonians composed of a constant number of interactions, i.e., linear combinations of ladder operator monomials of fixed form. Compact encoding leads to qubit requirements that are optimal up to logarithmic factors. Here, we show how to use sparse Hamiltonian simulation methods for second-quantized Hamiltonians in compact encoding, give explicit implementations for the required oracles, and analyze the methods. We also describe several example applications including the free boson and fermion theories, the φ 4 -theory, and the massive Yukawa model, all in both equal-time and light-front quantization. Our methods provide a general-purpose tool for simulating second-quantized Hamiltonians, with optimal or near-optimal scaling with error and model parameters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Novel small molecule FGF 23 inhibitors increase serum phosphate and improve skeletal abnormalities in Hyp mice

We report that excess fibroblast growth factor 23 (FGF23) causes hereditary hypophosphatemic rickets, such as X-linked hypophosphatemia (XLH) and tumor induced osteomalacia (TIO). A small molecule that specifically binds to FGF23 to prevent activation of the FGFR/a-Klotho complex has potential advantages over the currently approved systemically administered FGF23 blocking antibody. Using structure-based drug design we previously identified ZINC13407541 (N-[[2-(2-phenylethenyl)cyclopenten-1-yl]methylidene]hydroxylamine) as a small molecule antagonist for FGF23. Additional structure-activity studies developed a series of ZINC13407541 analogues with enhanced drug-like properties. In this study, we tested in a pre-clinical Hyp mouse homologue of XLH a direct connect analogue (8n) [(E)-2-(4-(tert-butyl)phenyl)cyclopent-1-ene-1-carbaldehyde oxime] that exhibited the greatest stability in microsomal assays, and 13a [(E)-2-((E)-4-methylstyryl)benzaldehyde oxime] that exhibited increased in vitro potency. Using cryo-electron microscopy (Cryo-EM) structure and computational docking, we identified a key binding residue (Q156) of the FGF23 antagonists, ZINC13407541 and its analogues (8n and 13a) in the N-terminal domain of FGF23 protein. Site-directed mutagenesis and bimolecular fluorescence complementation (BiFC)-fluorescence resonance energy transfer (FRET) assay confirmed the binding site of these three antagonists. We found that pharmacological inhibition of FGF23 with either of these compounds blocked FGF23 signaling and increased serum phosphate and 1,25(OH)2D concentrations in Hyp mice. Long-term parenteral treatment with 8n or 13a also enhanced linear bone growth, increased mineralization of bone, and narrowed the growth plate in Hyp mice. The more potent 13a compound had greater therapeutic effects in Hyp mice. Further optimization of these FGF23 inhibitors may lead to versatile drugs to treat excess FGF23-mediated disorders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Smoothing Lexis diagrams using kernel functions: A contemporary approach

Lexis diagrams are rectangular arrays of event rates indexed by age and period. Analysis of Lexis diagrams is a cornerstone of cancer surveillance research. Typically, population-based descriptive studies analyze multiple Lexis diagrams defined by sex, tumor characteristics, race/ethnicity, geographic region, etc. Inevitably the amount of information per Lexis diminishes with increasing stratification. Several methods have been proposed to smooth observed Lexis diagrams up front to clarify salient patterns and improve summary estimates of averages, gradients, and trends. In this article, we develop a novel bivariate kernel-based smoother that incorporates two key innovations. First, for any given kernel, we calculate its singular values decomposition, and select an optimal truncation point—the number of leading singular vectors to retain—based on the bias-corrected Akaike information criterion. Second, we model-average over a panel of candidate kernels with diverse shapes and bandwidths. The truncated model averaging approach is fast, automatic, has excellent performance, and provides a variance-covariance matrix that takes model selection into account. We present an in-depth case study (invasive estrogen receptor-negative breast cancer incidence among non-Hispanic white women in the United States) and simulate operating characteristics for 20 representative cancers. The truncated model averaging approach consistently outperforms any fixed kernel. Our results support the routine use of the truncated model averaging approach in descriptive studies of cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The past, present, and future of nuclear fuel

Abstract New reactor concepts have motivated study of a variety of nuclear fuel types. Most nuclear fuels have their origins dating back to the very beginnings of nuclear materials. We survey the most prevalent types of nuclear fuels and their properties and give some historical context as to their development. We end with our perspective on what the next 50 years of nuclear fuel research might lead to. In our opinion, while optimized microstructures and chemistries are certainly on the horizon, the biggest developments will be the continued integration of modeling and simulation with experiments to extract the greatest amount of energy possible from existing fuel candidates in a safe and economical way. Graphical abstract

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Cost-Optimized Cold Climate Heat Pump Development and Field Test

Cold climate heat pumps (CCHPs) expand the heat pump market to climates where heating demand is dominant. They can achieve more than 70% energy savings compared with electric resistance heating and operate at lower cost than using tank-stored propane to fuel a furnace. A high-efficiency heat pump with a heating seasonal performance factor (HSPF)—as defined by the Air-Conditioning, Heating, and Refrigeration Institute (AHRI 2008)—greater than 10.0 would be more efficient than gas heating in terms of source energy. However, developing a cost-effective CCHP involves some challenges. A typical single-speed, air-source heat pump (ASHP) with an HSPF of 7.7 Btu/Wh does not work well under cold outdoor temperature conditions typical of cold climate locations for four major reasons: 1. Discharge temperature is too high—The low suction pressure and high compression pressure ratio at low ambient temperatures causes high compressor discharge temperatures in excess of the maximum limit for many of the compressors on the market. Furthermore, system charge of a heat pump is usually optimized in the cooling mode, which leads to overcharge conditions in the heating mode, further increasing the discharge temperature. 2. Heating capacity is insufficient if sized to meet the building design cooling load— Heating capacity of a single-speed heat pump decreases with ambient temperature. The heating capacity at -13°F (-25°C) typically decreases to 20%–40% of the rated heating capacity at 47°F (8.3°C) (~equivalent to the rated cooling capacity at 95°F [35°C]). Therefore, a single-speed heat pump, typically sized to match the building design cooling load, cannot provide adequate heating capacity to match the building heating load at low ambient temperatures. The capacity deficit is filled by inefficient resistance heat, thus lowering the system efficiency and significantly increasing power demand. 3. Cyclic loss is significant if sized to meet the building design heating load—If a single-speed heat pump is sized to meet the heating load, it will be significantly oversized relative to the cooling load in many cold climates. This will cause excessive on/off cyclic loss during the cooling and heating operations at moderately low ambient temperatures. Thus, capacity modulation capability (e.g., using a variable-speed or multi-stage compressor) is necessary for a CCHP, which uses its full capacity to meet the peak heating load and partial capacity to meet the cooling and part-load heating loads. 4. Coefficient of performance (COP) is low—Heating COP degrades significantly at low ambient temperatures owing to the large temperature difference between the heat source and sink. A target CCHP should be sized to meet the building design heating load while minimizing the cyclic loss for the cooling and heating operations at moderate ambient temperatures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Development of Advanced Solid Sorbents for Direct Air Capture (Final Report)

RTI International is partnering with Creare, and Mohammed VI Polytechnic University (UM6P) successfully met all major technical objectives as outlined below: Identified one MOF adsorbent for DAC; Identified one amine-P-dendrimer adsorbent for DAC; Performed Computational fluid dynamics simulations of the MOF and amine-P-dendrimer adsorbents and validate them with experimental data; Selected one adsorbent for DAC; Demonstrated the scale-up of selected candidate and perform cost review; Performed a preliminary process design; Performed technology maturation plan and environmental health and safety risk assessment. After a thorough comparison between both adsorbents (MOFs and P-dendrimers) and based on their technical merits, the amine-based P-dendrimers sorbent was selected as the best performing adsorbent for DAC. In fact, the amine-based P-dendrimers have demonstrated superior performance over the MOF sorbents under relevant DAC conditions. The selected sorbent has been used in subsequent projects (DE-FE0032099 and DE-AR0001412) and has demonstrated similar superior performance with no loss of activity after long-term sorption-desorption testing (e.g., 100 cycles). This sorbent has demonstrated a very high and stable sorption performance, excellent kinetics, and fast regeneration at 80 °C, specifically at 75% relative humidity (RH). The incorporation of RTI’s high-performance, high-durability amine-based P-dendrimers sorbent and Creare’s hybrid additive manufacturing (H-AM) technology that will produce high performance, compact heat and mass exchange structures at low cost using methods, will lead to a contactor that is optimized for wind-driven operation. This contactor technology provides a technically viable pathway for reducing the cost of DAC to <$100/tonne of CO 2 .

36 MATERIALS SCIENCE↗