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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Causal Inference Model Based on Random Forests to Identify the Effect of Soil Moisture on Precipitation

Soil moisture influences precipitation mainly through its impact on land–atmosphere interactions. Understanding and correctly modeling soil moisture–precipitation (SM–P) coupling is crucial for improving weather forecasting and subseasonal to seasonal climate predictions, especially when predicting the persistence and magnitude of drought. However, the sign and spatial structure of SM–P feedback are still being debated in the climate research community, mainly due to the difficulty in establishing causal relationships and the high degree of nonlinearity in land–atmosphere processes. To this end, we developed a causal inference model based on the Granger causality analysis and a nonlinear machine learning model. This model includes three steps: nonlinear anomaly decomposition, nonlinear Granger causality analysis, and evaluation of the quality of SM–P feedback, which eliminates the nonlinear response of interannual and seasonal variability and the memory effects of climatic factors and isolates the causal relationship of local SM–P feedback. We applied this model by using National Climate Assessment–Land Data Assimilation System (NCA-LDAS) datasets over the United States. Here, the results highlight the importance of nonlinear atmosphere responses in land–atmosphere interactions. In addition, the strong feedback over the southwestern United States and the Great Plains both highlight the impacts of topographic factors rather than only the sensitivity of evapotranspiration to soil moisture. Furthermore, the SM–P index defined by our framework is used to benchmark Earth system models (ESMs), which provides a new metric for efficiently identifying potential model biases in modeling local land–atmosphere interactions and may help the development of ESMs in improving simulations of water cycle variability and extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Predicting biomass comminution: Physical experiment, population balance model, and deep learning

An extended population balance model (PBM) and a deep learning-based enhanced deep neural operator (DNO+) model are introduced for predicting particle size distribution (PSD) of comminuted biomass through a large knife mill. Experimental tests using corn stalks with varied moisture contents, mill blade speeds, and discharge screen sizes are conducted to support model development. A novel mechanism in the extended PBM allows for including additional input parameters such as moisture content, which is not possible in the original PBM. The DNO+ model can include influencing factors of different data types such as moisture content and discharge screen size, which significantly extends the engineering applicability of the standard DNO model that only admits feed PSD and outcome PSD. Test results show that both models are remarkably accurate in the calibration or training parameter space and can be used as surrogate models to provide effective guidance for biomass preprocessing design.

09 BIOMASS FUELS↗
DOE OSTI2023

Integration of Yeast Episomal/Integrative Plasmid Causes Genotypic and Phenotypic Diversity and Improved Sesquiterpene Production in Metabolically Engineered Saccharomyces cerevisiae

The variability in phenotypic outcomes among biological replicates in engineered microbial factories presents a captivating mystery. Establishing the association between phenotypic variability and genetic drivers is important to solve this intricate puzzle. Here, we applied a previously developed auxin-inducible depletion of hexokinase 2 as a metabolic engineering strategy for improved nerolidol production in Saccharomyces cerevisiae, and biological replicates exhibit a dichotomy in nerolidol production of either 3.5 or 2.5 g L –1 nerolidol. Harnessing Oxford Nanopore’s long-read genomic sequencing, we reveal a potential genetic cause—the chromosome integration of a 2μ sequence-based yeast episomal plasmid, encoding the expression cassettes for nerolidol synthetic enzymes. This finding was reinforced through chromosome integration revalidation, engineering nerolidol and valencene production strains, and generating a diverse pool of yeast clones, each uniquely fingerprinted by gene copy numbers, plasmid integrations, other genomic rearrangements, protein expression levels, growth rate, and target product productivities. Τhe best clone in two strains produced 3.5 g L –1 nerolidol and ~0.96 g L –1 valencene. Comparable genotypic and phenotypic variations were also generated through the integration of a yeast integrative plasmid lacking 2μ sequences. Our work shows that multiple factors, including plasmid integration status, subchromosomal location, gene copy number, sesquiterpene synthase expression level, and genome rearrangement, together play a complicated determinant role on the productivities of sesquiterpene product. Integration of yeast episomal/integrative plasmids may be used as a versatile method for increasing the diversity and optimizing the efficiency of yeast cell factories, thereby uncovering metabolic control mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Quantifying lithium loss in amorphous silicon thin-film anodes via titration-gas chromatography

Silicon with a high theoretical capacity (3,579 mAh/g) is a promising anode candidate for lithium-ion batteries. However, commercialization is still impeded by low Coulombic efficiency, caused by solid electrolyte interphase (SEI) formation and trapped lithium (Li)-silicon (Si) alloy during repeated volume change. Quantifying capacity losses from each factor is crucial to formulate rational design strategies for further improvement. In this work, titration-gas chromatography and cryogenic transmission electron microscopy are applied to characterize the evolution of trapped Li-Si alloy and SEI growth in a silicon thin-film anode. It is found that continuous growth of the SEI is the dominant factor for lithium inventory loss during cycling, with only a marginal increase in trapped Li-Si alloy. This study offers a quantitative approach to differentiate Li in the SEI from trapped Li in Li-Si alloy through a silicon thin-film anode, providing unique insights into identifying critical bottlenecks for developing Si anodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Life-Cycle Analysis Datasets for Regionalized Plastic Pathways

The carbon intensity (CI) of producing five different resins – polyethylene terephthalate (PET), high-density polyethylene (HDPE), low-density polyethylene (LDPE), polypropylene (PP), and polyvinyl chloride (PVC) – in four different international regions – United States of America (USA), Western Europe, Middle East and Northern Africa (MENA), and China – is calculated on a cradle-to-gate basis using the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. The list of factors that can potentially vary the CI of the five resins in different international regions include the CI of electricity and natural gas (NG) production, steam cracking feedstock mix, propylene sourcing technology mix, terephthalic monomer (TM) mix, use of hydrogen co-product from steam cracking process, and vinyl chloride monomer (VCM) production technology mix.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2015

Deriving Scaling Factors Using a Global Hydrological Model to Restore GRACE Total Water Storage Changes for China's Yangtze River Basin

This study used a global hydrological model (GHM), PCR-GLOBWB, which simulates surface water storage changes, natural and human induced groundwater storage changes, and the interactions between surface water and subsurface water, to generate scaling factors by mimicking low-pass filtering of GRACE signals. Signal losses in GRACE data were subsequently restored by the scaling factors from PCR-GLOBWB. Results indicate greater spatial heterogeneity in scaling factor from PCR-GLOBWB and CLM4.0 than that from GLDAS-1 Noah due to comprehensive simulation of surface and subsurface water storage changes for PCR-GLOBWB and CLM4.0. Filtered GRACE total water storage (TWS) changes applied with PCR-GLOBWB scaling factors show closer agreement with water budget estimates of TWS changes than those with scaling factors from other land surface models (LSMs) in China's Yangtze River basin. Results of this study develop a further understanding of the behavior of scaling factors from different LSMs or GHMs over hydrologically complex basins, and could be valuable in providing more accurate TWS changes for hydrological applications (e.g., monitoring drought and groundwater storage depletion) over regions where human-induced interactions between surface water and subsurface water are intensive.

water↗
DOE OSTI2020

Migration energy barriers and diffusion anisotropy of point defects on tungsten surfaces

We report tungsten is one of the most promising candidates for plasma-facing materials in future fusion devices, owing to its high performance under extreme irradiation conditions. However, irradiation-induced surface morphology varies significantly, depending on the irradiation type, fluence, and flux. Therefore, it is critical to examine the dynamics of point defects on tungsten (W) surfaces to understand how irradiation affects surface morphology. In this study, we employ the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC) method to search for potential migration paths of point defects on W (1 0 0), (1 1 0) and (1 1 1) surfaces. The first-principles calculations are then used to accurately determine the migration energy barriers. The obtained paths and barriers are incorporated into a kinetic Monte Carlo (KMC) model to determine trajectories and diffusivities, which are described by diffusion tensors to demonstrate their anisotropic features. Multiple diffusion mechanisms have been identified on different surfaces, with various anisotropy factors. Particularly, point defects on the W (1 1 0) surface have the highest diffusivities, with anisotropy factors independent of temperatures. In comparison, the anisotropy of the W (1 0 0) surface decreases as temperature increases, while the W (1 1 1) surface is isotropic for point defects. This study provides insights into defect transport properties on different surfaces, which are essential for understanding the early stages of irradiation-induced microstructural evolutions and surface morphology of tungsten.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Turn‐on Circularly Polarized Luminescence in Chiral Indium Chlorides by 5s 2 Metal Centers

Abstract Introducing chirality into the metal‐halide hybrids has enabled many emerging properties including chiroptical activity, spin‐dependent transport, and ferroelectricity. However, most of the chiral metal‐halide hybrids to date are non‐emissive, and the underlying mechanism remains elusive. Here, we show a new strategy to turn on the circularly polarized luminescence (CPL) in chiral metal‐halide hybrids. We demonstrate that alloying Sb 3+ into chiral indium‐chloride hybrids dramatically increases the photoluminescence quantum yield in two new series of chiral indium‐antimony chlorides. These materials exhibit strong CPL signals with tunable energy and a high dissymmetry factor up to 1.5×10 −2 . Mechanistic studies reveal that the emission originates from the self‐trapped excitons centered in 5s 2 Sb 3+ . Moreover, near‐ultraviolet pumped white light is demonstrated with a polarization up to 6.0 %. Our work demonstrates new strategies towards highly luminescent chiral metal‐halide hybrids.

Wang, Zhiyu↗
NASA NTRS1994

Toward Real Time Neural Net Flight Controllers

NASA Ames Research Center has an ongoing program in neural network control technology targeted toward real time flight demonstrations using a modified F-15 which permits direct inner loop control of actuators, rapid switching between alternative control designs, and substitutable processors. An important part of this program is the ACTIVE flight project which is examining the feasibility of using neural networks in the design, control, and system identification of new aircraft prototypes. This paper discusses two research applications initiated with this objective in mind: utilization of neural networks for wind tunnel aircraft model identification and rapid learning algorithms for on line reconfiguration and control. The first application involves the identification of aerodynamic flight characteristics from analysis of wind tunnel test data. This identification is important in the early stages of aircraft design because complete specification of control architecture's may not be possible even though concept models at varying scales are available for aerodynamic wind tunnel testing. Testing of this type is often a long and expensive process involving measurement of aircraft lift, drag, and moment of inertia at varying angles of attack and control surface configurations. This information in turn can be used in the design of the flight control systems by applying the derived lookup tables to generate piece wise linearized controllers. Thus, reduced costs in tunnel test times and the rapid transfer of wind tunnel insights into prototype controllers becomes an important factor in more efficient generation and testing of new flight systems. NASA Ames Research Center is successfully applying modular neural networks as one way of anticipating small scale aircraft model performances prior to testing, thus reducing the number of in tunnel test hours and potentially, the number of intermediate scaled models required for estimation of surface flow effects.

Jorgensen, C. C.↗
DOE OSTI2022

Resonant torque differential magnetometry with high frequency quartz oscillators

Sensitive magnetometry has been a powerful probe for investigating quantum materials. Extreme conditions, such as sub-kelvin cryogenic temperatures and ultrahigh magnetic fields, demand further durability for sensitive magnetometry. However, significant mechanical vibrations and rapid magnetic field changes give enormous challenges to conventional magnetometry. Here, this article presents a possible solution to this problem by developing a new magnetometry technique using high-frequency quartz oscillators. The technique takes advantage of the symmetry and geometry of mechanical vibration configurations of standard commercially available MHz quartz oscillators, and the setup keeps the high quality factor resonance with the sample mounted on the oscillator. We further demonstrate the sensitivity of the technique using bismuth single crystals and a Fe 0.25 TaS 2 ferromagnetic material. Quantum oscillations are observed in the magnetometry response below 1 T, and the detected oscillation frequency is shown to come from the electron pockets of the bismuth.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

LuGo: An enhanced quantum phase estimation implementation

Quantum Phase Estimation (QPE) is a cardinal algorithm in quantum computing that plays a crucial role in various applications, including cryptography, molecular simulation, and solving systems of linear equations. However, the standard implementation of QPE faces challenges related to time complexity and circuit depth, which limit its practicality for large-scale computations. We introduce LuGo, a novel framework designed to enhance the performance of QPE by reducing circuit duplication, as well as using parallelization techniques to achieve faster generation of the QPE circuit and gate reduction. We validate the effectiveness of our framework by generating quantum linear solver circuits, which require both QPE and inverse QPE, to solve linear systems of equations. LuGo achieves significant improvements in both computational efficiency and hardware requirements without compromising on accuracy. Compared to a standard QPE implementation, LuGo reduces time consumption to generate a circuit that solves a 2 6 × 2 6 system matrix by a factor of 50.68 and over 31× reduction of quantum gates and circuit depth, with no fidelity loss on an ideal quantum simulator. Furthermore, we demonstrated the versatility and scalability of LuGo enabled HHL algorithm by simulating a canonical Hele-Shaw fluid problem using a quantum simulator. With these advantages, LuGo paves the way for more efficient implementations of QPE, enabling broader applications across several quantum computing domains.

Quantum algorithm↗
DOE OSTI2025

A comprehensive approach for elucidating the interplay between 4f n +1 and 4f n 5d 1 configurations in Ln 2+ complexes

Lanthanides (Ln) are typically found in the +3 oxidation state. However, in recent decades, their chemistry has been expanded to include the less stable +2 oxidation state across the entire series except promethium (Pm), facilitated by the coordination of ligands such as trimethylsilylcyclopentadienyl, C 5 H 4 SiMe 3 (Cp'). The [LnCp' 3 ] complexes have been the workhorse for the synthesis and theoretical study of the fundamental aspects of divalent lanthanide chemistry, where experimental and computational evidence have suggested the existence of different ground state (GS) configurations, 4f n+1 or 4f n 5d 1 , depending on the specific metal. Standard reduction potentials and 4f n+1 to 4f n 5d 1 promotion energies have been two factors usually considered to rationalize the occurrence of these variable GS configurations, however the driving force behind this phenomenon is still not clear. In this work we present a comprehensive theoretical approach to shed light on this matter using the [LnCp 3 ] - model systems. We begin by calculating 4f n+1 to 4f n 5d 1 promotion energies and successfully correlate them with existing experimental data. Furthermore, we analyze how changes in the GS charge distribution between the Ln ions, LnCp 3 and the reduced [LnCp 3 ] - complexes (Ln = La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu) correlate with experimental trends in redox potentials and the calculated promotion energies. For this purpose, a comprehensive theoretical work that includes relativistic ligand field density functional theory (LFDFT) and relativistic ab initio wavefunction methods was performed. This study will help the rational design of suitable environments to tune the different GS configurations as well as modulating the spectroscopic properties of new Ln 2+ complexes.

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

Turn-on Circularly Polarized Luminescence in Chiral Indium Chlorides by 5s 2 Metal Centers

Introducing chirality into the metal-halide hybrids has enabled many emerging properties including chiroptical activity, spin-dependent transport, and ferroelectricity. However, most of the chiral metal-halide hybrids to date are non-emissive, and the underlying mechanism remains elusive. Here, in this study, we show a new strategy to turn on the circularly polarized luminescence (CPL) in chiral metal-halide hybrids. We demonstrate that alloying Sb 3+ into chiral indium-chloride hybrids dramatically increases the photoluminescence quantum yield in two new series of chiral indium-antimony chlorides. These materials exhibit strong CPL signals with tunable energy and a high dissymmetry factor up to 1.5×10 -2 . Mechanistic studies reveal that the emission originates from the self-trapped excitons centered in 5s 2 Sb 3+ . Moreover, near-ultraviolet pumped white light is demonstrated with a polarization up to 6.0 %. Our work demonstrates new strategies towards highly luminescent chiral metal-halide hybrids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Ab Initio Nuclear Thermodynamics

Here, we propose a new Monte Carlo method called the pinhole trace algorithm for ab initio calculations of the thermodynamics of nuclear systems. For typical simulations of interest, the computational speedup relative to conventional grand-canonical ensemble calculations can be as large as a factor of one thousand. Using a leading-order effective interaction that reproduces the properties of many atomic nuclei and neutron matter to a few percent accuracy, we determine the location of the critical point and the liquid-vapor coexistence line for symmetric nuclear matter with equal numbers of protons and neutrons. We also present the first ab initio study of the density and temperature dependence of nuclear clustering.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Doping with phosphorus reduces anion vacancy disorder in CdSeTe semiconductors enabling higher solar cell efficiency

Doping is used in many pn junction devices, such as polycrystalline solar cells, to increase the strength of the junction field to assist charge carrier collection and thus partially mitigate nonradiative recombination losses. We demonstrate a different doping characteristic for inorganic solar cells: using dopants to reduce charge carrier trapping and electronic band tails. Alloying CdTe with Se to form CdSeTe semiconductor reduced recombination, but CdSeTe has more complex defect states which can limit further efficiency gains due to charge carrier trapping and trap-limited mobility. Doping CdSeTe with P (but not N, As, or Sb in this study) reduces band tails (Urbach energies) and lessens the impact of the near valence band trap states, with ambipolar mobilities improving to >50 cm 2 V −1 s −1 , fill factor increasing from 76% to 79%, and efficiencies increasing by 0.9% absolute. Simulations are used to show how such defect reduction improves performance in the radiative limit.

14 SOLAR ENERGY↗
DOE OSTI2020

Water reuse for sustainable microalgae cultivation: current knowledge and future directions

Microalgae hold great promise as environmentally sustainable sources of food, animal feed, and fuel. However, large amounts of water are used during microalgae cultivation and this negatively impacts economic viability and environmental sustainability. Reusing cultivation water can reduce the direct impacts of water usage and also reduce nutrient requirements and algal wastewater treatment. However, studies have shown that algae growth in reused water can be compromised, unaffected, or sometimes enhanced compared to controls. This review examines recent studies on water reuse to qualitatively understand these varied effects. Growth inhibitors and stimulators in reused water and their underlying mechanisms are discussed, as well as recent pre-treatment technologies and factors affecting the quality of reused water, such as microalgae taxa, culture conditions, and harvesting methods, are considered. A scheme is proposed for water reuse and harvesting methods based on the desired algal end products. Finally, taking these findings together, here we provide recommendations for further research directions as well as new insights into designing and integrating a cultivation strategy with a harvesting platform to reuse water for more efficient microalgae cultivation.

42 ENGINEERING↗
DOE OSTI2023

Impact of Wildfires on Solar Resource Availability in California in a Changing Climate

Wildfires can emit large amounts of atmospheric particulate matters and influence not only air quality but also availability of photovoltaic (PV) generation due to scattering and absorption of solar radiation. Under anthropogenic changing climate, wildfire activity is projected to increase over western North America due to drier and warmer climate, implying increasing impact on solar resource and larger uncertainty in solar generation especially in regions with faster PV penetration. This study focuses on quantifying the impact of wildfires on aerosol optical depth (AOD) and thus solar resource over California using National Solar Radiation Database (NSRDB), developed by the National Renewable Energy Laboratory (NREL). This assessment includes historical analysis and estimation of solar resource under wildfire scenarios (2020 wildfire and an enhanced wildfire scenario based on 2020 wildfires). Historical analysis for the period of July-October 2019/2020 (low/high fire activity period) shows that the averaged global horizontal irradiance (GHI) and direct normal irradiance (DNI) are reduced by about 30 and 90 W m-2 (5.6 and 15.3%), respectively, during high fire activity period. To create AOD dataset for enhanced fire scenario, 165% increase in burn area (in around 2050) is selected based on comprehensive literature review, which is further applied to the Fire INventory from NCAR (FINN) fire emission. WRF-Chem model with the enhanced FINN emissions is used to simulate and represent a preserving spatial distribution of burned areas and wildfire-emitted aerosols. Our initial analysis suggests that the"enhanced 2020 wildfire" AOD can increase by a factor of 1.3 - 2, which can significantly reduce solar irradiance and increase uncertainty in generation and reliability of power system in extreme wildfire events under a high solar penetration scenario. Overall, this study provides an estimate of the impacts of wildfires on solar resource to make informed decisions on reserve planning, generation scheduling, and reliability investments.

aerosol optical depth↗
DOE OSTI2022

Investigation of the 176 Yb Interference Correction during Determination of the 176 Hf/ 177 Hf Ratio by Laser Ablation and Solution Analysis on the Neoma MC-ICP-MS

We utilized the Neoma™, a recently released MC-ICP-MS platform offered by ThermoFisher Scientific, to assess the behavior of the Lu-Yb-Hf system during laser ablation analyses of various zircon standards as well as solution-based analyses of the JMC-475 Hf standard doped with varying quantities of Yb and Lu. The primary goal of this work was to characterize the behavior of the Yb interference correction on the Neoma™ platform since this is one of the biggest issues in the Hf isotope analysis community and because the Neoma™ platform will supplant the Neptune™ series instrument. During laser ablation analysis, we found that the overall data quality scales proportionally with the total Hf signal intensity, with higher signal analyses producing extremely accurate (within 1 ε Hf unit) and precise (sub ε Hf unit within-run standard errors) data. At low Yb signals (<0.1 V 173 Yb), we were not able to produce an accurate internal Yb mass bias factor. However, utilizing an empirical approach allows for the application of session-specific relationships between the Yb and Hf mass bias factors, determined by analysis of standards of varying Yb content, to produce accurate ε Hf values from zircons with higher Yb/Hf ratios even where the total Hf signal intensity is relatively low. Similar behavior was observed in the solution analyses. Lastly, while the behavior of the Yb interference correction on the Neoma™ platform appears comparable to the Neptune™ series MC-ICP-MS, further work will help refine the understanding of the controls on mass bias behavior, oxide formation, session-to-session stability, etc.

36 MATERIALS SCIENCE↗