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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Dynamic resource allocation drives growth under nitrogen starvation in eukaryotes

Cells can sense changes in their extracellular environment and subsequently adapt their biomass composition. Nutrient abundance defines the capability of the cell to produce biomass components. Under nutrient-limited conditions, resource allocation dramatically shifts to carbon-rich molecules. Here, we used dynamic biomass composition data to predict changes in growth and reaction flux distributions using the available genome-scale metabolic models of five eukaryotic organisms (three heterotrophs and two phototrophs). We identified temporal profiles of metabolic fluxes that indicate long-term trends in pathway and organelle function in response to nitrogen depletion. Surprisingly, our calculations of model sensitivity and biosynthetic cost showed that free energy of biomass metabolites is the main driver of biosynthetic cost and not molecular weight, thus explaining the high costs of arginine and histidine. We demonstrated how metabolic models can accurately predict the complexity of interwoven mechanisms in response to stress over the course of growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Power Density Distributions in Electron Beams

Measuring and controlling the power density distribution of electron beams used for welding is critical for producing repeatable welds and for transferring welding parameters between different machines. On any given machine, the power density distribution is controlled by defocusing the beam relative to its sharpest focused condition. However, measuring the power density distribution can be difficult due to the intense nature of welding beams and is further complicated by imperfect electron optics that can distort the beam, making it difficult to quantify. The enhanced modified Faraday cup (EMFC) diagnostic method was used here for beam analysis that utilizes computed tomography to reconstruct the beam’s power density distribution. These results were compared to the International Standards Organization (ISO) method for characterizing laser beams using a second-moment D4σ calculation. For ideal Gaussian-shaped beams, both methods would give the same result. However, for imperfect beams, the calculated D4σ diameter was shown to be about 25% larger relative to the FWe2 diameter measured by the EMFC due to the heavier weighting of data in the tails of the beam by D4σ. Finally, although both methods produce repeatable welds, it is important to understand the differences in the reported beam diameters, divergence angles, and beam parameter products when transferring parameters between machines.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effects of Coating on the Electrochemical Performance of a Nickel-Rich Cathode Active Material

Due to their safety and high power density, one of the most promising types of all-solid-state lithium batteries is the one made with the argyrodite solid electrolyte (ASE). Although substantial efforts have been made toward the commercialization of this battery, it is still challenged by some technical issues. One of these issues is to prevent the side reactions at the interface of the ASE and the cathode active material (CAM). A solution to address this issue is to coat the CAM particles with a material that is compatible with both ASE and CAM. Prior studies show that the lithium niobate, LiNbO 3 , (LNO) is a promising material for coating CAM particles to reduce the interfacial side reactions. However, no systematic study is available in the literature to show the effect of coating LNO on CAM performance. This paper aims to quantify the effect of LNO coating on the electrochemical performance of a nickel-rich CAM. The electrochemical performance parameters that are studied are the capacity, cycling performance, and rate performance of the coated-CAM; and the effectiveness of the coating to prevent the side reactions at the ASE and CAM interface is out of the scope of this study. To eliminate the effect of side reactions at the ASE and CAM interface, we conduct all tests in the organic liquid electrolyte (OLE) cells to solely present the effect of coating on the CAM performance. For this purpose, 0.5 wt.% and 1 wt.% LNO are used to coat the LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC-60) CAM through two synthesizing methods. Consequently, the effects of the synthesizing method and the coating weight percentage on the NMC-60 performance are presented.

10 SYNTHETIC FUELS↗
DOE OSTI2026

Computing neutrino cross sections from Euclidian responses

Energy integrated neutrino cross sections are integrals of nuclear responses weighted with kinematic prefactors. We decompose the prefactors into a limited set of functions of energy transfer and show the relevant integrals are the moments of the responses, and integrals weighted with $1/(a+ω)^n$ with $n\leq 2$. These can be directly obtained from the Euclidean response, avoiding the need for inversion of the Laplace transform. As a proof of concept we study the procedure with toy-model responses for the quasielastic peak. We show that the different contributions can be straightforwardly organized in terms of relative importance, and how flux-averaged cross sections can be obtained. Using a realistic model for the response and numerical uncertainty we show that it is feasible to obtain the required integrals from the Euclidean response, with large uncertainties only for the third moment. Due to kinematic restrictions, the integrals contain contributions from the unphysical region for neutrino scattering, coming from high-momentum nucleons. We show that (in the absence of two-body currents) robust corrections for this contamination are obtained from the single-nucleon momentum distribution. These results present an opportunity to compute certain neutrino cross sections with ab-initio methods with controlled uncertainties.

Nikolakopoulos, A. [Washington U., Seattle]↗
DOE OSTI2026

Computing neutrino cross sections from Euclidian responses

Energy integrated neutrino cross sections are integrals of nuclear responses weighted with kinematic prefactors. We decompose the prefactors into a limited set of functions of energy transfer and show the relevant integrals are the moments of the responses, and integrals weighted with $1/(a+ω)^n$ with $n\leq 2$. These can be directly obtained from the Euclidean response, avoiding the need for inversion of the Laplace transform. As a proof of concept we study the procedure with toy-model responses for the quasielastic peak. We show that the different contributions can be straightforwardly organized in terms of relative importance, and how flux-averaged cross sections can be obtained. Using a realistic model for the response and numerical uncertainty we show that it is feasible to obtain the required integrals from the Euclidean response, with large uncertainties only for the third moment. Due to kinematic restrictions, the integrals contain contributions from the unphysical region for neutrino scattering, coming from high-momentum nucleons. We show that (in the absence of two-body currents) robust corrections for this contamination are obtained from the single-nucleon momentum distribution. These results present an opportunity to compute certain neutrino cross sections with ab-initio methods with controlled uncertainties.

Nikolakopoulos, A. [Washington U., Seattle]↗
DOE OSTI2022

Photochemical spin-state control of binding configuration for tailoring organic color center emission in carbon nanotubes

Abstract Incorporating fluorescent quantum defects in the sidewalls of semiconducting single-wall carbon nanotubes (SWCNTs) through chemical reaction is an emerging route to predictably modify nanotube electronic structures and develop advanced photonic functionality. Applications such as room-temperature single-photon emission and high-contrast bio-imaging have been advanced through aryl-functionalized SWCNTs, in which the binding configurations of the aryl group define the energies of the emitting states. However, the chemistry of binding with atomic precision at the single-bond level and tunable control over the binding configurations are yet to be achieved. Here, we explore recently reported photosynthetic protocol and find that it can control chemical binding configurations of quantum defects, which are often referred to as organic color centers, through the spin multiplicity of photoexcited intermediates. Specifically, photoexcited aromatics react with SWCNT sidewalls to undergo a singlet-state pathway in the presence of dissolved oxygen, leading to ortho binding configurations of the aryl group on the nanotube. In contrast, the oxygen-free photoreaction activates previously inaccessible para configurations through a triplet-state mechanism. These experimental results are corroborated by first principles simulations. Such spin-selective photochemistry diversifies SWCNT emission tunability by controlling the morphology of the emitting sites.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Assessment of Materials-Based Options for On-Board Hydrogen Storage for Rail Applications

The objective of this project was to evaluate material- and chemical-based solutions for hydrogen storage in rail applications as an alternative to high-pressure hydrogen gas and liquid hydrogen. Three use cases were assessed: yard switchers, long-haul locomotives, and tenders. Four storage options were considered: metal hydrides, nanoporous sorbents, liquid organic hydrogen carriers, and ammonia, using 700 bar compressed hydrogen as a benchmark. The results suggest that metal hydrides, currently the most mature of these options, have the highest potential. Storage in tenders is the most likely use case to be successful, with long-haul locomotives the least likely due to the required storage capacities and weight and volume constraints. Overall, the results are relevant for high-impact regions, such as the South Coast Air Quality Management District, for which an economical vehicular hydrogen storage system with minimal impact on cargo capacity could accelerate adoption of fuel cell electric locomotives. The results obtained here will contribute to the development of technical storage targets for rail applications that can guide future research. Moreover, the knowledge generated by this project will assist in development of material-based storage for stationary applications such as microgrids and backup power for data centers.

08 HYDROGEN↗
DOE OSTI2024

Weaning transition, but not the administration of probiotic candidate Kazachstania slooffiae , shaped the gastrointestinal bacterial and fungal communities in nursery piglets

As in-feed antibiotics are phased out of swine production, producers are seeking alternatives to facilitate improvements in growth typically seen from this previously common feed additive. Kazachstania slooffiae is a prominent commensal fungus in the swine gut that peaks in relative abundance shortly after weaning and has beneficial interactions with other bacteriome members important for piglet health. In this study, piglets were supplemented with K. slooffiae to characterize responses in piglet health as well as fungal and bacterial components of the microbiome both spatially (along the entire gastrointestinal tract and feces) and temporally (before, during, and after weaning). Litters were assigned to one of four treatments: no K. slooffiae (CONT); one dose of K. slooffiae 7 days before weaning (day 14; PRE); one dose of K. slooffiae at weaning (day 21; POST); or one dose of K. slooffiae 7 days before weaning and one dose at weaning (PREPOST). The bacteriome and mycobiome were analyzed from fecal samples collected from all piglets at day 14, day 21, and day 49, and from organ samples along the gastrointestinal (GI) tract at day 21 and day 49. Blood samples were taken at day 14 and day 49 for cytokine analysis, and fecal samples were assayed for antimicrobial resistance. While some regional shifts were seen in response to K. slooffiae administration in the mycobiome of the GI tract, no remarkable changes in weight gain or health of the animals were observed, and changes were more likely due to sow and the environment. Ultimately, the combined microbiome changed most considerably following the transition from suckling to nursery diets. This work describes the mycobiome along the piglet GI tract through the weaning transition for the first time. Based on these findings, K. slooffiae administered at this concentration may not be an effective tool to hasten colonization of K. slooffiae in the piglet GI tract around the weaning transition nor support piglet growth, microbial gut health, or immunity. However, diet and environment greatly influence microbial community development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Engineering donor–acceptor conjugated polymers for high-performance and fast-response organic electrochemical transistors

To date, high-performance organic electrochemical transistors (OECTs) have mostly been based on polythiophene systems. Donor–acceptor (D–A) conjugated polymers are expected to be promising materials for OECTs owing to their high mobility and comparatively low crystallinity (good for ion diffusion). However, the OECT performance of D–A polymers lags far behind that of the polythiophenes. Here we synergistically engineered the backbone and side chain of a series of diketopyrrolopyrrole (DPP)-based D–A polymers and found that redox potential, molecular weight, solution processability, and film microstructures all have a severe impact on their performance. After systematic engineering, P(bgDPP-MeOT2) exhibited the best figure-of-merit (μC*) of 225 F cm -1 V -1 s -1 , amongst the highest performance of the reported D–A polymers. Besides, the DPP polymers exhibited high hole mobility of over 1.6 cm 2 V -1 s -1 , leading to fast response OECTs with a record low turn-off response time of 30 μs. The polymer also exhibited good operation stability with a current retention of 98.8% over 700 electrochemical switching cycles. This work reveals the complexity and systematicness in the development of D–A polymer based high-performance OECTs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An intermediate model for fitting triplet–triplet annihilation in phosphorescent organic light emitting diode materials

Triplet–triplet annihilation (TTA) is one of the primary contributors to efficiency roll-off and permanent material degradation in phosphorescent organic light-emitting diodes. Here, the two limiting case models typically used to quantify this quenching mechanism are multi-step Dexter and single-step Förster, which, respectively, assume ideal Fickian diffusion or perfect trapping of triplet excitons. For device-relevant guest doping levels (typically 5–12 vol. %), both significant diffusion of excitons and trapping due to spatial and energetic disorder exist, so neither conventional model fits experimental data well. We develop and validate an intermediate TTA model, which is a weighted average of the limiting cases of pure radiative decay (no TTA) and multi-step Dexter based TTA that returns an effective TTA rate constant and a parameter quantifying the portion of well-isolated excitons. Kinetic Monte-Carlo simulations and time-resolved photoluminescence measurements of an archetype host–guest system demonstrate that our intermediate model provides significantly improved fits with more realistic physical values, is more robust to variations in experimental conditions, and provides an analysis framework for the effects of trapping on TTA.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Determination of Infinite Dilution Activity Coefficients of Molecular Solutes in Ionic Liquids and Deep Eutectic Solvents by Factorization-Machine-Based Neural Networks

Widely known as “green solvents,” ionic liquids (ILs) and deep eutectic solvents (DESs) have been used as substitutes for traditional organic solvents in separation science. To achieve better separations using ILs and DESs, this work aimed to predict the infinite dilution activity coefficients (IDACs) of molecular solutes in these solvents with the state-of-the-art factorization-machine-based neural network (DeepFM). DeepFM combines the benefits of factorization machines and deep neural networks to learn both low-order and high-order interactions among features. The IDAC prediction model was established with 52,372 experimental IDAC datapoints including 260 solvents (252 ILs and 8 DESs) and 112 molecular solutes collected at various temperatures from 288.15 to 428.15 K. Chemical information describing the ILs, DESs, and molecular solutes was included in the IDAC prediction model, including chemical functional groups, molecular weights, and Abraham solvation parameters. The IDAC prediction model showed an improved accuracy compared with alternative models; additionally, DESs were included in the IDAC prediction model for the first time. Here, the model will reduce the energy and resources needed to optimize the selection of ILs and DESs for specific separations, which will promote the development of these green solvents for sustainable chemical processes.

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

Evolutionary reinforcement learning of dynamical large deviations

In this work, we show how to bound and calculate the likelihood of dynamical large deviations using evolutionary reinforcement learning. An agent, a stochastic model, propagates a continuous-time Monte Carlo trajectory and receives a reward conditioned upon the values of certain path-extensive quantities. Evolution produces progressively fitter agents, potentially allowing the calculation of a piece of a large-deviation rate function for a particular model and path-extensive quantity. For models with small state spaces, the evolutionary process acts directly on rates, and for models with large state spaces, the process acts on the weights of a neural network that parameterizes the model's rates. This approach shows how path-extensive physics problems can be considered within a framework widely used in machine learning.

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

Structure of Lipopolysaccharide from Liberibacter crescens Is Low Molecular Weight and Offers Insight into Candidatus Liberibacter Biology

Huanglongbing (HLB) disease, also known as citrus greening disease, was first reported in the US in 2005. Since then, the disease has decimated the citrus industry in Florida, resulting in billions of dollars in crop losses and the destruction of thousands of acres of citrus groves. The causative agent of citrus greening disease is the phloem limited pathogen Candidatus Liberibacter asiaticus. As it has not been cultured, very little is known about the structural biology of the organism. Liberibacter are part of the Rhizobiaceae family, which includes nitrogen-fixing symbionts of legumes as well as the Agrobacterium plant pathogens. To better understand the Liberibacter genus, a closely related culturable bacterium (Liberibacter crescens or Lcr) has attracted attention as a model organism for structural and functional genomics of Liberibacters. Given that the structure of lipopolysaccharides (LPS) from Gram-negative bacteria plays a crucial role in mediating host-pathogen interactions, we sought to characterize the LPS from Lcr. We found that the major lipid A component of the LPS consisted of a pentaacylated molecule with a β-6-GlcN disaccharide backbone lacking phosphate. The polysaccharide portion of the LPS was unusual compared to previously described members of the Rhizobiaceae family in that it contained ribofuranosyl residues. The LPS structure presented here allows us to extrapolate known LPS structure/function relationships to members of the Liberibacter genus which cannot yet be cultured. It also offers insights into the biology of the organism and how they manage to effectively attack citrus trees.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Revealing the Crystalline Architecture of Semicrystalline Ion Exchange Membranes for the Design of Conductive and Durable Alkaline Anion Exchange Membranes

Alkaline anion exchange membrane (AAEM) fuel cells offer a cost-effective alternative to proton exchange membrane (PEM) fuel cells by eliminating the need for expensive precious metal catalysts. In both PEMs and AAEMs, semicrystalline polymers are a common choice, as the crystalline domains can act as mechanical reinforcements that limit swelling and promote mechanical durability in the material. However, spatially resolved characterization of crystalline organization in ion exchange membranes beyond ensemble-averaged X-ray scattering is underrepresented, likely in part due to ionization damage limitations in soft materials. Here, in this study, we resolve the nanometer-size crystallites in semicrystalline ion exchange membranes by applying cryogenic four-dimensional scanning transmission electron microscopy (cryo-4D-STEM) along with data-processing algorithms designed to optimize signals at a low dose to minimize radiation damage. We investigate the effects of synthesis components, including molecular weight and thermal treatment, on a model system of AAEMs in comparison to Nafion, the most commonly used and commercially successful PEM today. We find that excess water uptake in polymer membranes, a property directly associated with weak mechanical durability and with possible negative impacts on ion conductivity, can be reduced by over 30% by varying the polymer's crystalline morphology through changes in synthesis parameters such as molecular weight and thermal history. Our results indicate that this improvement is correlated with smaller crystalline domains with a more homogeneous distribution. More broadly, these results demonstrate how the crystalline architecture of polymer membranes can be tuned through their chemistry and thermal treatment in order to improve their conductivity and durability for commercial fuel cell performance.

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

A Tchebycheff-based multi-objective combined with a PSO–SQP dynamic real-time optimization framework for cycling energy systems

The aim in this work is to develop an optimization framework to address cycling of baseload energy systems due to the penetration of renewables into the grid. The developed strategy corresponds to a multi-objective and dynamic real-time optimization (MOO-DRTO) framework applied to a postcombustion MEA-based CO 2 capture process from a baseload coal-fired power plant under cycling conditions. A Tchebycheff-based method is used for the multi-objective optimization (MOO) component. Also, a hybrid approach consisting of Particle Swarm Optimization (PSO) and Sequential Quadratic Programming (SQP) is implemented for the first time in process systems engineering to solve the dynamic real-time optimization (DRTO) component. The objectives considered in the MOO-DRTO framework are economic and environmental. The proposed MOO-DRTO strategy is successfully implemented and 24-h optimal output trajectories for the carbon capture system under cycling are generated. Also, the optimal compromise is chosen from the Pareto front according to a set of selected weights for the objectives with minimal interaction between the framework and decision maker. The results indicated that the developed framework has potential to be extended to plant-wide optimization applications under cycling.

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

Synthesis and Characterization of a Bridging Cerium(IV) Nitride Complex

Complexes featuring lanthanide–ligand multiple bonds are rare and highly reactive. They are important synthetic targets to understand 4f/5d-bonding in comparison to d-block and actinide congeners. Herein, the isolation and characterization of a bridging cerium(IV)-nitride complex: [(TriNOx)Ce(Li 2 μ-N)Ce(TriNOx)][BAr F 4 ] is reported, the first example of a molecular cerium-nitride. The compound was isolated by deprotonating a monometallic cerium(IV)-ammonia complex: [Ce IV (NH 3 )(TriNOx)][BAr F 4 ]. The average Ce=N bond length of [(TriNOx)Ce(Li 2 μ-N)Ce(TriNOx)][BAr F 4 ] was 2.117(3) Å. Vibrational studies of the 15 N-isotopomer exhibited a shift of the Ce=N=Ce asymmetric stretch from ν = 644 cm –1 to 640 cm –1 , and X-ray spectroscopic studies confirm the +4 oxidation state of cerium. Furthermore, computational analyses showed strong involvement of the cerium 4f shell in bonding with overall 16% and 11% cerium weight in the σ- and π-bonds of the Ce=N=Ce fragment, respectively.

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

Well-to-Wheels Analysis of Zero-Emission Plug-In Battery Electric Vehicle Technology for Medium- and Heavy-Duty Trucks

Conventional diesel medium- and heavy-duty vehicles (MHDVs) create large amount of air emissions. With the advancement in technology and reduction in the cost of batteries, plug-in battery electric vehicles (BEVs) are increasingly attractive options for improving energy efficiency and reducing air emissions of MHDVs. In this paper, we compared the well-to-wheels (WTW) greenhouse gases (GHGs) and criteria air pollutant emissions of MHD BEVs with their conventional diesel counterparts across weight classes and vocations. We expanded the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET) model to conduct the WTW analysis of MHDVs. The fuel economy for a wide range of MHDV weight classes and vocations, over various driving cycles, was evaluated using a high-fidelity vehicle dynamic simulation software (Autonomie). The environmental impacts of MHD BEVs are sensitive to the source of electricity used to recharge their batteries. The WTW results show that MHD BEVs significantly improve environmental sustainability of MHDVs by providing deep reductions in WTW GHGs, nitrogen oxides, volatile organic compounds, and carbon monoxide emissions, compared to conventional diesel counterparts. Increasing shares of renewable and natural gas technologies in future national and regional electricity generation are expected to reduce WTW particulate matters and sulfur oxide emissions for further improvement of the environmental performance of MHD BEVs.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Carrier control in Sn–Pb perovskites via 2D cation engineering for all-perovskite tandem solar cells with improved efficiency and stability

All-perovskite tandem solar cells are promising for achieving photovoltaics with power conversion efficiencies above the detailed balance limit of single-junction cells, while retaining the low cost, light weight and other advantages associated with metal halide perovskite photovoltaics. However, the efficiency and stability of all-perovskite tandem cells are limited by the Sn-Pb-based narrow-bandgap perovskite cells. Here we show that the formation of quasi-two-dimensional (quasi-2D) structure (PEA) 2 GAPb 2 I 7 from additives based on mixed bulky organic cations phenethylammonium (PEA+) and guanidinium (GA+) provides critical defect control to substantially improve the structural and optoelectronic properties of the narrow-bandgap (1.25 eV) Sn-Pb perovskite thin films. Additionally, this 2D additive engineering results in Sn-Pb-based absorbers with low dark carrier density (~1.3 x 10 14 cm -3 ), long bulk carrier lifetime (~9.2 us) and low surface recombination velocity (~1.4 cm s -1 ), leading to 22.1%-efficient single-junction Sn-Pb perovskite cells and 25.5%-efficient all-perovskite two-terminal tandems with high photovoltage and long operational stability.

14 SOLAR ENERGY↗