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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 OSTI2024

Effect of XC functionals and dispersion corrections on the DFT‐computed structural and vibrational properties of SrCl 2 –NaCl and ZrF 4 –LiF

Density functional theory (DFT) calculations were performed to examine the impact of exchange–correlation (XC) functionals and van der Waals corrections (specifically the D3 method) on the structural and vibrational properties of the SrCl 2 –NaCl and ZrF 4 –LiF salt systems. Multiple XC functionals, including the local density approximation (LDA), the generalized gradient approximation using the Perdew–Burke–Ernzerhof (PBE) model, and its modified form suitable for solids (PBEsol), the dispersion-corrected PBE-D3 and PBEsol-D3, were considered. Of these functionals, LDA was found to exhibit the highest degree of error, while PBEsol and PBE-D3 displayed the least error. Underestimated lattice parameters compared with experimental values were observed to result in higher force constants, leading to an overprediction of vibrational frequencies. Conversely, an overestimation of lattice parameters was associated with lower vibrational frequencies. The methodology presented in this study yielded results that are in good agreement with experiment, irrespective of the method (finite differences vs. density functional perturbation theory) employed for calculating infrared and Raman spectra. It was further demonstrated that for alkali halides with weak Raman scattering, utilizing a supercell constructed from primitive cells better predicts Raman features than does the use of conventional cells.

Raman↗
NASA NTRS2013

Urban Image Classification: Per-Pixel Classifiers, Sub-Pixel Analysis, Object-Based Image Analysis, and Geospatial Methods: Chapter - 10

Remote sensing methods used to generate base maps to analyze the urban environment rely predominantly on digital sensor data from space-borne platforms. This is due in part from new sources of high spatial resolution data covering the globe, a variety of multispectral and multitemporal sources, sophisticated statistical and geospatial methods, and compatibility with GIS data sources and methods. The goal of this chapter is to review the four groups of classification methods for digital sensor data from space-borne platforms; per-pixel, sub-pixel, object-based (spatial-based), and geospatial methods. Per-pixel methods are widely used methods that classify pixels into distinct categories based solely on the spectral and ancillary information within that pixel. They are used for simple calculations of environmental indices (e.g., NDVI) to sophisticated expert systems to assign urban land covers. Researchers recognize however, that even with the smallest pixel size the spectral information within a pixel is really a combination of multiple urban surfaces. Sub-pixel classification methods therefore aim to statistically quantify the mixture of surfaces to improve overall classification accuracy. While within pixel variations exist, there is also significant evidence that groups of nearby pixels have similar spectral information and therefore belong to the same classification category. Object-oriented methods have emerged that group pixels prior to classification based on spectral similarity and spatial proximity. Classification accuracy using object-based methods show significant success and promise for numerous urban 3 applications. Like the object-oriented methods that recognize the importance of spatial proximity, geospatial methods for urban mapping also utilize neighboring pixels in the classification process. The primary difference though is that geostatistical methods (e.g., spatial autocorrelation methods) are utilized during both the pre- and post-classification steps. Within this chapter, each of the four approaches is described in terms of scale and accuracy classifying urban land use and urban land cover; and for its range of urban applications. We demonstrate the overview of four main classification groups in Figure 1 while Table 1 details the approaches with respect to classification requirements and procedures (e.g., reflectance conversion, steps before training sample selection, training samples, spatial approaches commonly used, classifiers, primary inputs for classification, output structures, number of output layers, and accuracy assessment). The chapter concludes with a brief summary of the methods reviewed and the challenges that remain in developing new classification methods for improving the efficiency and accuracy of mapping urban areas.

Myint, Soe W.↗
DOE OSTI2020

Multivariate discrimination in quantum target detection

In this work, we describe a simple multivariate technique of likelihood ratios for improved discrimination of signal and background in multi-dimensional quantum target detection. Furthermore, the technique combines two independent variables, time difference and summed energy, of a photon pair from the spontaneous parametric down-conversion source into an optimal discriminant. The discriminant performance was studied in experimental data and in Monte-Carlo modelling with clear improvement shown compared to previous techniques. As novel detectors become available, we expect this type of multivariate analysis to become increasingly important in multi-dimensional quantum optics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Product selectivity and mass transport in levulinic acid transfer hydrogenation by monolithic MIL-100, MIL-88B and ZIF-8@Pd MOFs

The diffusion processes between adsorbent and adsorbate naturally play a significant role in the efficiency and selectivity of the heterogenous catalytic process. This paper considers the importance of diffusion processes in the transfer hydrogenation reaction of levulinic acid to γ-valerolactone by MIL-88B, MIL-100, and ZIF8@Pd monolithic catalysts. Over a period of five catalytic cycles, it was shown that the Fe-based catalysts can achieve similar conversions to the ZIF-8 supported Pd, with the only current limitation being the lower aqueous stability of these MOFs. Diffusion constants were calculated using the ZLC method, with micropore diffusion limitation found for ZIF-8 and MIL-100 monolithic frameworks at 2.7 x 10 -8 and 4.6 x 10 -8 cm 2 s -1 respectively. This diffusion limitation was also confirmed by IR spectroscopy with an increasing concentration of C—H bands on the MOF substrate post-reaction. Mass transfer coefficients, also calculated by ZLC, revealed increased mass transport for the hydrophobic ZIF-8 framework, which perhaps aids in the γ-valerolactone selectivity over side products that are produced in the absence of catalytic material, as seen for MIL-88B and MIL-100 after multiple uses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

High-Fidelity Simulation of Flow-Induced Vibrations in Helical Steam Generators for Small Modular Reactors

Flow-induced vibration (FIV) is a widespread problem in energy systems as they rely on fluid movement for energy conversion. Vibrating structures may be damaged as fatigue or wear occur. Given the importance of reliable components in the nuclear industry, FIV has long been a major concern in the safety and operation of nuclear reactors. In particular, nuclear fuel rods and steam generators have been known to suffer from FIV and related failures. In this paper we discuss the use of the computational fluid dynamics code Nek5000 coupled to the structural code Diablo to simulate the flow in helical coil heat exchangers and associated FIV. In particular, one-way coupled calculations are performed, where pressure and tractions data are loaded into the structural model. The main focus of this paper is on validation of this capability. Fluid-only Nek5000 large eddy simulations are first compared against dedicated high-resolution experiments. Then, one-way coupled calculations are performed with Nek5000 and Diablo for two data sets that provide FIV data for validation. These calculations were aimed at simulating available legacy FIV experiments in helical steam generators in the turbulent buffeting regime. In this regime one-way coupling is judged sufficient since the pressure loads do not cause substantial displacements. It is also the most common source of vibration in helical steam generators at the low flows expected in integral pressurized water reactors. We discuss validation of two-way coupled experiments and benchmarks toward the simulation of fluid elastic instability. We briefly discuss the application of these methods to grid-to-rod fretting.

Flow-Induced Vibration↗
DOE OSTI2022

Highly Selective Methane to Methanol Conversion on Inverse SnO 2 /Cu 2 O/Cu(111) Catalysts: Unique Properties of SnO 2 Nanostructures and the Inhibition of the Direct Oxidative Combustion of Methane

Direct methane to methanol (CH 4 → CH 3 OH) conversion in heterogeneous catalysis has been a long-standing challenge due to the difficulties in equalizing the activation of methane and protection of the methanol product at the same reaction conditions. Here, we report an inverse catalyst, consisting of small structures of SnO 2 (0.5-1 nm in size) dispersed on Cu 2 O/Cu(111), for highly selective CH 3 OH production from CH 4 . This system was investigated by combining theoretical [density functional theory calculations (DFT), kinetic Monte Carlo simulations (KMC)] and experimental methods [scanning tunneling microscopy (STM), ambient-pressure X-ray photoelectron spectroscopy (AP-XPS)]. The DFT and AP-XPS studies showed that on SnO 2 /Cu 2 O/Cu(111) the conversion of CH 4 by oxygen (O 2 ) preferred complete combustion to carbon dioxide (CO 2 ). The addition of water (H 2 O) enhanced the production of CH 3 OH to nearly 100% selectivity in KMC simulations. This trend was consistent with results of AP-XPS. The presence of water in the reaction environment rendered an extremely high amount of methoxy species (*CH 3 O), a precursor for CH 3 OH production. Further, the high CH 3 OH selectivity of SnO 2 /Cu 2 O/Cu(111) reflected the unique atomic and electronic structure of the supported SnO 2 nanoparticles. As a result, the O 2 adsorption and dissociation, and thus the full combustion of CH 4 to CO 2 , was completely suppressed; while the H 2 O dissociative adsorption was still feasible, providing active hydroxyl species for a truly selective CH 4 to CH 3 OH conversion.

03 NATURAL GAS↗
DOE OSTI2019

Construction of a Nanoporous Highly Crystalline Hexagonal Boron Nitride from an Amorphous Precursor for Catalytic Dehydrogenation

Abstract Hexagonal boron nitride (h‐BN) is regarded as a graphene analogue and exhibits important characteristics and vast application potentials. However, discovering a facile method for the preparation of nanoporous crystalline h‐BN nanosheets (h‐BNNS) is still a challenge. Herein, a novel and simple route for the conversion of amorphous h‐BN precursors into highly crystalline h‐BNNS was achieved through a successive dissolution–precipitation/crystallization process in the presence of magnesium. The h‐BNNS has high crystallinity, high porosity with a surface area of 347 m 2 g −1 , high purity, and enhanced thermal stability. Improved catalytic performance of crystalline h‐BNNS was evidenced by its much higher catalytic efficiency in the dehydrogenation of dodecahydro‐N‐ethylcarbazole, compared with its amorphous h‐BN precursor, as well as other precious‐metal‐loaded heterogeneous catalysts.

Chen, Hao↗
DOE OSTI2019

Construction of a Nanoporous Highly Crystalline Hexagonal Boron Nitride from an Amorphous Precursor for Catalytic Dehydrogenation

Abstract Hexagonal boron nitride (h‐BN) is regarded as a graphene analogue and exhibits important characteristics and vast application potentials. However, discovering a facile method for the preparation of nanoporous crystalline h‐BN nanosheets (h‐BNNS) is still a challenge. Herein, a novel and simple route for the conversion of amorphous h‐BN precursors into highly crystalline h‐BNNS was achieved through a successive dissolution–precipitation/crystallization process in the presence of magnesium. The h‐BNNS has high crystallinity, high porosity with a surface area of 347 m 2 g −1 , high purity, and enhanced thermal stability. Improved catalytic performance of crystalline h‐BNNS was evidenced by its much higher catalytic efficiency in the dehydrogenation of dodecahydro‐N‐ethylcarbazole, compared with its amorphous h‐BN precursor, as well as other precious‐metal‐loaded heterogeneous catalysts.

Chen, Hao↗
DOE OSTI2024

Metal Phosphide Nanoparticles Generated via a Molecular Precursor Route for Hydrotreatment of Methyl Laurate

Transition metal phosphide nanoparticles supported on silica were used as catalysts to investigate the hydrodeoxygenation of methyl laurate (used as a model compound for vegetable oils). Ni 2 P, Ni 1 Mo 1 P, and Ni 1.6 Mo 0.4 P were synthesized using a molecular precursor route. The nanoparticles were added to the silica support without any changes in their structure or particle size. As a reference and for comparison, MoP/SiO 2 was also prepared by the phosphite method. The prepared catalysts were characterized by X-ray diffraction, X-ray photoelectron spectroscopy, transmission electron microscopy, and chemical analysis. A higher conversion is reached with the MoP/SiO 2 monometallic catalyst, close to that with Ni 1 Mo 1 P/SiO 2 . However, this observation is misleading because the differences in dispersion obscure the result that the intrinsic activity (turnover frequency) of the bimetallic catalyst, prepared by a molecular precursor route, is significantly higher than that of the monometallic catalyst, prepared by the phosphite route, revealing a synergistic effect on the catalytic activity due to the formation of the bimetallic phosphide.

09 BIOMASS FUELS↗
DOE OSTI2025

Unimodal Imaging of Monovalent Metal-Chelator Complexes and Lipids by MALDI Imaging Mass Spectrometry

Careful regulation of monovalent metal ions (M + ) is necessary to maintain a functional cellular system. Of these ions, appropriate sodium (Na + ) and potassium (K + ) concentrations are particularly integral for electrochemical signaling, as well as the secondary transport of nutrients and waste. Dysregulation of M + homeostasis can disrupt these mechanisms, potentially influencing the metabolism of downstream biomolecules such as lipids. Thus, the relationship between M + abundances and related biomolecular distributions must be elucidated to better understand the physiology of healthy and disordered tissues. Traditional techniques for imaging biological metal distributions include SIMS, LA-ICP-MS, and XRF; however, these capabilities are limited to elemental analysis or the analysis of molecular fragments and must be paired with other modalities to visualize distributions of more complex biomolecules within the same or similar samples. Conversely, matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool often used for mapping such biomolecular distributions, but current methods are unable to detect metals within tissue. This study illustrates a novel methodology that adds metal detection to the MALDI IMS repertoire through which the simultaneous detection of M + metals and lipids is achievable. Using a robotic sprayer for homogeneous application, on-tissue deposition of the chelator deferiprone (DEF) enables subsequent detection of the ionizable metal-chelator complex by MALDI without hindering lipid detection. Our work provides proof-of-concept data for the simultaneous detection of K + , Na + , and intact lipids using MALDI IMS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Fast predictions of liquid-phase acid-catalyzed reaction rates using molecular dynamics simulations and convolutional neural networks

The rates of liquid-phase, acid-catalyzed reactions relevant to the upgrading of biomass into high-value chemicals are highly sensitive to solvent composition and identifying suitable solvent mixtures is theoretically and experimentally challenging. We show that the complex atomistic configurations of reactant–solvent environments generated by classical molecular dynamics simulations can be exploited by 3D convolutional neural networks to enable accurate predictions of Brønsted acid-catalyzed reaction rates for model biomass compounds. We develop a 3D convolutional neural network, which we call SolventNet, and train it to predict acid-catalyzed reaction rates using experimental reaction data and corresponding molecular dynamics simulation data for seven biomass-derived oxygenates in water–cosolvent mixtures. We show that SolventNet can predict reaction rates for additional reactants and solvent systems an order of magnitude faster than prior simulation methods. This combination of machine learning with molecular dynamics enables the rapid, high-throughput screening of solvent systems and identification of improved biomass conversion conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Parametric interaction of optical waves in metamaterials under low-frequency pumping

The influence of phase effects under three-wave parametric interaction and low-frequency pumping in metamaterials is studied in the case of a negative refractive index at a signal-wave frequency. It is found that the efficiency of the backward signal-wave amplification is the higher, the greater the ratio of the intensities of the idler and signal waves at the input to the metamaterial. An increase in the idler wave intensity at the input by five times, as compared to the signal-wave intensity, leads to a nonlinear increase in the signal-wave amplification by almost 20 times. According to the analytic expressions obtained in the constant-intensity approximation, the choice of the optimal parameters for the pump intensity, total length of the metamaterial and phase detuning will facilitate the implementation of regimes of effective amplification and generation of the signal wave. A comparison is made with the results obtained in the constant-field approximation, and a numerical estimate of the expected efficiency of the frequency conversion is presented. Control of frequency and pump power is shown to make possible the smooth tuning of the parametric converter frequency. The developed method can be used to design frequency converters based on nonlinear metamaterials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Remote operation of the DIII-D National Fusion Facility

Abstract Full remote scientific operation of the DIII-D National Fusion Facility is now possible through significant advances in the computer science hardware and software infrastructure made over the last decade. Capabilities around information visualization, data movement, and communication have all been enhanced. The level of capability deployed to remotely operate DIII-D required an infrastructure advancement over what had previously been achieved in the fusion community. The large quantity of real-time data that is automatically displayed on DIII-D’s control room screens can now be visualized by remote participants via web-based applications. New audio/video solutions using the VoIP and instant messaging application Discord have been implemented to mimic the dynamic and ad-hoc scientific conversations that are critical in successfully operating an experimental campaign. Discord’s ability for a user to rapidly move between audio channels, text with images, and share screens is a significant enhancement over traditional videoconferencing tools. In addition, multiple combinations of broadcast audio are made available via a web-based application to allow remote participants to simultaneously listen to general announcements/sounds while conducting their own specific conversations. Secure methodologies have been put into place to allow remote control of hardware including DIII-D’s plasma control system application. Secure methods also included the ability of the on-site team to closely coordinate their work with remote team members which has been enhanced through extensions to the wireless network and the use of tablet computers for audio/video/screen sharing. However, no amount of software can fully replace the need for ‘hands on hardware.’ This infrastructure was severely stress tested during the COVID-19 pandemic where occupancy of the DIII-D control room was restricted. Operational efficiency during the pandemic, measured in discharges per hour, remained high (3.8 ± 0.8) compared to values obtained pre-pandemic (3.7 ± 0.8).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Stable tuning of photorefractive microcavities using an auxiliary laser

Cavity nonlinear optics enables intriguing physical phenomena to occur at micro- or nano-scales with modest input powers. While this enhances capabilities in applications such as comb generation, frequency conversion, and quantum optics, undesired nonlinear effects including photorefraction and thermal bistability are exacerbated. In this Letter, we propose and demonstrate a highly effective method of achieving cavity stabilization using an auxiliary laser for controlling photorefraction in a z-cut periodically poled lithium niobate (LN) microcavity system. Our numerical study accurately models the photorefractive effect under high input powers, guiding future analyses and development of LN microcavity systems.

42 ENGINEERING↗
DOE OSTI2017

Transplant rejection and tolerance – advancing the field through integration of computational and experimental investigation

This Research Topic provides a venue for stimulating these interdisciplinary conversations in the context of transplantation. The articles collected under this Research Topic introduce new theoretical and experimental studies that describe novel techniques and methods for understanding the interactions between the immune response and transplants and for establishing more effective strategies of diagnosis and intervention that will promote transplant tolerance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Performance and Reliability of Bonded Interfaces for High-temperature Packaging: Annual Progress Report

As maximum device temperatures approach 200 °Celsius, continuous operation, sintered silver materials promise to maintain bonds at these high temperatures without excessive degradation rates. A detailed characterization of the thermal performance and reliability of sintered silver materials and processes has been initiated for the next year. Future steps in crack modeling include efforts to simulate crack propagation directly using the extended finite element method (X-FEM), a numerical technique that uses the partition of unity method for modeling discontinuities such as cracks in a system.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

Final Report: Scale-up of Algal Biofuel Production Using Waste Nutrients

Renewable fuels can be more environmentally friendly than conventional fuels and can be produced locally, supporting energy independence. Liquid renewable fuels are of special interest due to their high energy density. Algae are a promising prospective feedstock for low carbon intensity liquid biofuels, due to their high productivity and potential for high lipid or carbohydrate content. Their ability to grow on wastewater and waste nutrients and on non-arable land are cost and sustainability advantages. The organic matter content of wastewater promotes mixotrophic and/or heterotrophic growth of both algae and bacteria, boosting biomass productivity further. However, economic and technologic challenges persist that prevent the scale-up of algal biofuels to commercial relevance. These challenges include algal harvesting, drying, dewatering, and the conversion of algal biomass to usable fuels (Hannon et al 2010, Dunlap and Shaw 2009, Pienkos et al. 2009). The US Department of Energy (DOE) Bioenergy Technologies Office (BETO) supports research to overcome these challenges and outlines the research and development goals for algal biofuels in their Multi-Year Program Plan (MYPP). The long-term goals of the MYPP for algal biofuels research are briefly as follows: develop the domestic ability to produce algal biofuels at a scale of 5 billion gallons per year (BGY) by 2030 and demonstrate technologies that produce biofuel intermediates from algae at a cost of $3/gallon of gasoline equivalent (GGE) by 2022 (BETO MYPP 2016). This research reported herein was funded to investigate methods of meeting an intermediate milestone of 2,500 gallons of biofuel intermediate per acre per year for a non-integrated process by improving algal productivity, harvesting efficiency, and conversion to biofuel intermediates. Use of wastewater and wastewater nutrients was a key distinguishing characteristic of this project. In pursuit of 2,500 gallons of biofuel intermediate (BFI) per acre per year, California Polytechnic State University, San Luis Obispo (Cal Poly) sought to develop the capability to produce biofuel intermediates from microalgae grown on municipal wastewater at a 20-acre algae-based wastewater treatment facility in Delhi, California (37.43° N), which includes 7 acres of raceway ponds. Coupling algal biofuel production with wastewater treatment capitalizes on the abundant waste nutrients and carbon present in wastewater and reduces use of clean water in algal biorefinery systems. In this research, the performance of the full-scale wastewater treatment plant was characterized by measuring productivity, wastewater treatment performance, hydraulic characteristics, and energy consumption. Nine 1,000-L pilot raceways with CO2 addition were used in experiments to maximize productivity. Low-cost, energy-efficient algae bioflocculation and settling were monitored. Population genetics were monitored in an attempt to correlate taxa with superior productivity and/or settling. Algae-bacterial biomass was converted to biofuel intermediates via bench-scale hydrothermal liquefaction (HTL), and the resulting fuel quality was characterized. To develop rapid strain screening capabilities, a climate simulating photobioreactor (“LEAPS”) was developed and validated against outdoor raceways. A techno-economic analysis (TEA) and a lifecycle assessment (LCA) were performed to model process economics and sustainability. The major outcomes of this research included demonstration of 33 g/m2-day annual average algal-bacterial productivity in pilot raceways, and a biofuel intermediate yield of 0.35 g intermediate/g algae biomass via HTL, for a yield of 4,100 gallons BFI per acre per year, assuming a 90% harvest efficiency and ignoring other minor losses. This exceeded the project goal of 2,500 gallons of BFI per acre per year and nearly met the 2030 program goal, highlighting the promise of integrating wastewater treatment and biofuels production. The biocrude BFI produced by the process is refined to diesel and naphtha fuels. These fuels are normalized to the energy content of gasoline (gallons gasoline equivalent, GGE, for comparison to other fuels). Results from the TEA of the this complete “well-to-wheel” process demonstrated that, at a 400-ha scale, a minimum fuel selling price (MFSP) of $12.55/GGE, which could be decreased 57% to $7.14/GGE when including revenue from coupling the biofuel production with the co-products of wastewater treatment services and low carbon fuel credits from California and Federal programs. Due mainly to the high capital costs of thickener centrifuges and hydrothermal processing equipment, the fuel cost is sensitive to scale, with significantly lower costs expected for larger farms. In this research project, significant advances were made in improving raceway algal productivity and fuel production from algae biomass, while also improving process economics. These outcomes brought the algal biofuel technology closer to being a sustainable and marketable process. The remainder of this executive summary is organized into the following six primary project tasks: (1) to optimize biomass productivity for a selected strain at Delhi, (2) to maximize algal productivity and harvesting efficiency in Delhi pilot ponds, (3) a full-scale raceway hydraulic characterization, (4) biomass processing to biofuel intermediates, and (5) scale-up engineering analysis, modeling, and planning.

09 BIOMASS FUELS↗
DOE OSTI2025

Multimodal Ligand Non-Innocence for Reduction Catalysis (Final Technical Report)

The goal of this project was to develop multimodal ligand non-innocence in late transition metal complexes of aminophenolate ligands and to apply this ligand-centered reactivity to small-molecule reduction reactions relevant to energy-conversion chemistry. Specific aims were, 1) Prepare new coordination complexes of aminophenolate ligands and characterize them using a battery of structural, spectroscopic, and computational methods. 2) Benchmark the thermodynamics and kinetics of e - , H + , H • , and H - transfer reactivity to establish the baseline reactivity of new metal complexes containing aminophenolate ligands. 3) Apply new aminophenolate complexes to catalytic reduction reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗