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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

KETCHUP: Parameterizing of large-scale kinetic models using multiple datasets with different reference states

Large-scale kinetic models provide the computational means to dynamically link metabolic reaction fluxes to metabolite concentrations and enzyme levels while also conforming to substrate level regulation. However, the development of broadly applicable frameworks for efficiently and robustly parameterizing models remains a challenge. Challenges arise due to both the heterogeneity, paucity, and difficulty in obtaining flux and/or concentration data but also due to the computational difficulties of the underlying parameter identification problem. Both the computational demands for parameterization, degeneracy of obtained parameter solutions and interpretability of results has so far limited widespread adoption of large-scale kinetic models despite their potential. Herein, we introduce the Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the (non)steady-state fluxes and concentrations in wild-type and perturbed metabolic networks. KETCHUP is benchmarked against previously parameterized large-scale kinetic models demonstrating an at least an order of magnitude faster convergence than the tool K-FIT while at the same time attaining better data fits. Finally, this versatile toolbox accepts different kinetic descriptions, metabolic fluxes, enzyme levels and metabolite concentrations, under either steady-state or instationary conditions to enable robust kinetic model construction and parameterization. KETCHUP supports the SBML format and can be accessed at https://github.com/maranasgroup/KETCHUP.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Radiation Accidents and Malicious Events – Scenarios and Scope of the Work of ICRP Task Group 120

The International Commission on Radiological Protection (ICRP) Task Group 120 (TG120) is developing ICRP recommendations for radiological protection for a wide range of radiation accidents and malicious events, complementing those given in ICRP Publication 146 (2020) for large nuclear accidents. The scope includes accidents involving criticalities, operating faults, and fires and explosions in nuclear facilities, inadvertent damage to sealed radiation sources, as well as malicious events, such as sabotage of nuclear facilities or materials, use of radiological dispersal devices, the contamination of food and drinking water supplies, and the deployment of nuclear weapons. A template has been designed to collate relevant information on a wide range of case studies and hypothetical malicious scenarios to ensure that the recommendations developed are broadly applicable and comprehensive. For all scenarios, a graded approach to protection is being taken, accepting that specific guidance may be required for some distinctive aspects, for example, protection during times of armed conflict. This paper provides an overview of the scenarios and scope of the work of TG120, including some of the radiological and non-radiological impacts of radiation emergencies, along the response and recovery timeline.

ICRP↗
DOE OSTI2020

Controls on Iron Reduction and Biomineralization over Broad Environmental Conditions as Suggested by the Firmicutes Orenia metallireducens Strain Z6

Microbial iron reduction is a ubiquitous biogeochemical process driven by diverse microorganisms in a variety of environments. However, it is often difficult to separate the biological from the geochemical controls on bioreduction of Fe(III) oxides. In this study, we investigated the primary driving factor(s) that mediate secondary iron mineral formation over a broad range of environmental conditions using a single dissimilatory iron reducer, Orenia metallireducens strain Z6. A total of 17 distinct geochemical conditions were tested with differing pH (6.5–8.5), temperature (22–50 °C), salinity (2–20% NaCl), anions (phosphate and sulfate), electron shuttle (anthraquinone-2,6-disulfonate), and Fe(III) oxide mineralogy (ferrihydrite, lepidocrocite, goethite, hematite, and magnetite). The observed rates and extent of iron reduction differed significantly with k int between 0.186 and 1.702 mmol L –1 day –1 and Fe(II) production ranging from 6.3% to 83.7% of the initial Fe(III). Using X-ray absorption and scattering techniques (EXAFS and XRD), we identified and assessed the relationship between secondary minerals and the specific environmental conditions. It was inferred that the observed bifurcation of the mineralization pathways may be mediated by differing extents of Fe(II) sorption on the remaining Fe(III) minerals. These results expand our understanding of the controls on biomineralization during microbial iron reduction and aid the development of practical applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Identifying High-Performance Metal–Organic Frameworks for Low-Temperature Oxygen Recovery from Helium by Computational Screening

Metal–organic frameworks (MOFs) are an important class of porous crystalline materials for applications ranging from gas adsorption and separation to catalysis. There are thousands of potential MOFs available for separation applications. Here, we developed a computational approach to screen MOFs for the separation of oxygen–helium mixtures at low temperatures (100–200 K), conditions that were motivated by issues associated with propulsion in space-based settings. We used detailed molecular simulations for a small number of MOFs to develop screening methods that were then used to estimate the optimum temperatures for separations using pressure swing adsorption for 2932 MOFs from the CoRE MOF database and the swing capacity and oxygen–helium selectivity at these temperatures. We used the stability of the best-performing structures in the presence of moisture as a means to provide a short list of high-performance materials. In addition to identifying specific materials for oxygen–helium separations, this approach could prove useful for selecting adsorbents for other gas separations.

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

Bimolecular Peroxy Radical (RO 2 ) Reactions and Their Relevance in Radical Initiated Oxidation of Hydrocarbons

The kinetics of peroxy radical (RO 2 ) reactions have been of long-standing interest in atmospheric and combustion chemistry. Nevertheless, the lack of kinetic studies at higher temperatures for their reactions with other radicals such as OH has precluded the inclusion of this class of reactions in detailed kinetics models developed for combustion applications. In this work, guided by the limited room temperature experimental studies on selected alkyl-peroxy radicals and literature theoretical kinetics on the prototypical CH 3 O 2 + OH system, we have performed parametric studies on the effect of uncertainties in the rate coefficients and branching ratios to potential product channels for RO 2 + OH reactions at higher temperatures. Literature kinetics models were used to simulate autoignition delays, laminar flame speeds, and speciation profiles in flow and stirred reactors for a variety of common combustion-relevant fuels. Inclusion of RO 2 + OH reactions was found to retard autoignition in fuel-lean (φ = 0.5) mixtures of ethane and dimethyl ether in air. The observed effects were noticeably more pronounced in ozone-enriched combustion of ethane and dimethyl ether. The simulations also examined the influence of ozone doping levels, pressures, and equivalence ratios for both ethane and dimethyl ether oxidation. Sensitivity and flux analyses revealed that the RO 2 + OH reaction is a significant sink of RO 2 radicals at the early stage of autoignition, affecting fuel oxidation through RO 2 ↔ QOOH, RO 2 ↔ alkene + HO 2 , or RO 2 + HO 2 ↔ ROOH + O 2 . Additionally, the kinetic stability of the trioxide formed from RO 2 + OH reactions was investigated using master equation analyses. Last, we discuss other bimolecular reactions that are missing in literature kinetics models but are relevant to hydrocarbon oxidation initiated by external radical sources (plasma-enhanced, ozone-enriched combustion, etc.). In conclusion, the present simulations provide a strong motivation for better characterizing the bimolecular kinetics of peroxy radicals.

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

Ex Machina Determination of Structural Correlation Functions

Determining the structural properties of condensed-phase systems is a fundamental problem in theoretical statistical mechanics. In this study, we present a machine learning method that is able to predict structural correlation functions with significantly improved accuracy in comparison with traditional approaches. The usefulness of this ex machina (from the machine) approach is illustrated by predicting the radial distribution functions of two paradigmatic condensed-phase systems, a Lennard-Jones fluid and a hard-sphere fluid, and then comparing those results to the results obtained using both integral equation methods and empirically motivated analytical functions. We find that application of the developed ex machina method typically decreases the predictive error by more than an order of magnitude in comparison with traditional theoretical methods.

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

Quasiparticle and Optical Properties of Carrier-Doped Monolayer MoTe 2 from First Principles

The intrinsic weak and highly nonlocal dielectric screening of two-dimensional materials is well-known to lead to high sensitivity of their optoelectronic properties to environment. Less studied theoretically is the role of free carriers in those properties. In this report we use ab initio GW and Bethe-Salpeter equation calculations, with a rigorous treatment of dynamical screening and local-field effects, to study the doping dependence of the quasiparticle and optical properties of a monolayer transition-metal dichalcogenide, 2H MoTe 2 . Here we predict a quasiparticle band gap renormalization of several hundreds of meV for experimentally attainable carrier densities and a similarly sizable decrease in the exciton binding energy. This results in an almost constant excitation energy for the lowest-energy exciton resonance with an increasing doping density. Using a newly developed and generally applicable plasmon-pole model and a self-consistent solution of the Bethe-Salpeter equation, we reveal the importance of accurately capturing both dynamical and local-field effects to understand detailed photoluminescence measurements.

2D material↗
DOE OSTI2023

Spectroscopic Characterization of Highly Active Fe–N–C Oxygen Reduction Catalysts and Discovery of Strong Interaction with Nafion Ionomer

Scaling up clean-energy applications necessitates the development of platinum group metal (PGM)-free fuel cell electrocatalysts with high activity, stability, and low cost. Here, X-ray absorption (XAS) at the Fe K-edge and Fe K β X-ray emission (XES) spectroscopies were used to study the electronic structure of Fe centers in highly active Fe–N–C oxygen reduction catalysts with significant commercial potential. X-ray absorption near-edge structure (XANES) analysis has shown that the majority (>95%) of Fe centers are in the Fe 3+ oxidation state, while extended X-ray absorption fine structure (EXAFS) detected a mixture of single site Fe–N 4 centers (>95%) and centers with short (~2.5 Å) Fe–Fe interactions of Fe metal and/or Fe-carbide nanoparticles (<5%) featuring the Fe o oxidation state. Surprisingly, addition of Nafion, the most widely used ionomer, resulted in pronounced changes in the XAS spectra, consistent with a strong catalyst–ionomer interaction where long Fe–Fe interactions at ~3.1 Å were shown to be a feature of Fe 3+ ions bound with the Nafion. We conclude that exposure to Nafion during the device formulation has a different effect from the aggressive acid leaching typically used in the preparation of Fe–N–C catalysts. Furthermore, it was hypothesized that the polymer interacts with single sites’ Fe 3+ centers, as well as with graphene layers protecting the Fe o nanoparticles, and extracts some Fe ions into the Nafion matrix.

25 ENERGY STORAGE↗
DOE OSTI2020

Sequential Doping of Ladder-Type Conjugated Polymers for Thermally Stable n-Type Organic Conductors

Doping of organic semiconductors is a powerful tool to optimize the performance of various organic (opto)electronic and bioelectronic devices. Despite recent advances, the low thermal stability of the electronic properties of doped polymers still represents a significant obstacle to implementing these materials into practical applications. Hence, the development of conducting doped polymers with excellent long-term stability at elevated temperatures is highly desirable. Here, we report on the sequential doping of the ladder-type polymer poly(benzimidazobenzophenanthroline) (BBL) with a benzimidazole-based dopant (i.e., N-DMBI). By combining electrical, UV–vis/infrared, X-ray diffraction, and electron paramagnetic resonance measurements, we quantitatively characterized the conductivity, Seebeck coefficient, spin density, and microstructure of the sequentially doped polymer films as a function of the thermal annealing temperature. Importantly, we observed that the electrical conductivity of N-DMBI-doped BBL remains unchanged even after 20 h of heating at 190 °C. This finding is remarkable and of particular interest for organic thermoelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Opportunities and Limitations of Nuclear Magnetic Resonance Spectroscopy in Astrobiology

For decades, Nuclear Magnetic Resonance (NMR) spectroscopy has been utilized as a powerful tool in various scientific disciplines, most prominently in chemistry, to determine molecular structures or monitor reactions. While well established in various fields, NMR applications in astrobiology are still unclear. This work aims to explore the potential of NMR in astrobiology, highlighting strengths but also weaknesses. We illustrate capabilities of NMR with two applications: (1) recently developed methods for position-specific carbon isotope analysis of complex organics; and (2) well-established tools for performing quantitative compositional analysis of complex organic mixtures. By utilizing samples relevant to astrobiology, specifically the amino acid valine and analogue mixtures of organics, we showcase that molecules retain a source dependent and distinct intramolecular carbon isotope fingerprint. We demonstrate that compositional sample analysis provides an independent and complementary line of evidence pointing towards the origin of a molecule or mixture. Together, these NMR tools have the potential to support life detection efforts, and aid in distinguishing between biotic and abiotic samples. Finally, we discuss sensitivity, detection limits, the portability of NMR, and propose how integration with mass-spectrometry techniques will be imperative to enable more targeted and comprehensive analyses relevant to astrobiology, including in-situ analysis but also sample return missions.

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

Chalcocarbogels as High-Capacity and Cycle-Stable Electrode Materials for Lithium and Sodium Ion Batteries

The low capacities of commercial Li ion batteries and cycle instabilities of amorphous metal sulfide based batteries impose constraints on their utilization for large-scale energy storage. We report here the acid-free, room-temperature (RT), and solution-based synthesis of a chalcogenide–carbonaceous hybrid aerogel, termed as “chalcocarbogel”, comprising molybdenum sulfide (MoS x ) and graphene oxide (GO). The chalcocarbogel is a nanoparticle-aggregated, porous, amorphous gel consisting of Mo 3 S 13 and Mo 2 S 12 -like structures as determined by synchrotron X-ray PDF, XANES, and EXAFS. The MoS x -GO chalcocarbogel demonstrates high specific capacities of ~1215 and ~807 mAh g –1 for Li/MoS x -GO and Na/MoS x -GO cells, respectively, for a 50 mAg –1 discharge rate during the first cycle. After the activation cycles, the MoS x -GO chalcocarbogel stabilizes, maintaining high specific capacities of approximately ~700 mAh g –1 for Li/MoS x -GO and ~473 mAh g –1 for Na/MoS x -GO cells, while continuously cycling. Importantly, the MoS x -GO aerogel reported here serves as a promising platform to develop chalcocarbogels for applications spanning both Li and Na ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Unraveling Interdiffusion Phenomena and the Role of Nanoscale Diffusion Barriers in the Copper–Gold System

Diffusion is one of the most fundamental concepts in materials science, playing a pivotal role in materials synthesis, forming, and degradation. Of particular importance is solid state interdiffusion of metals which defines the usable parameter space for material combinations in the form of alloys. This parameter space can be explored on the macroscopic scale by using diffusion couples. However, this method reaches its limit when going to low temperatures, small scales, and when testing ultrathin diffusion barriers. Therefore, this work transfers the principle of the diffusion couples to small scales by using core–shell nanowires and in situ heating. This allows us to delve into the interdiffusion dynamics of copper and gold, revealing the interplay between diffusion and the disorder–order phase transition. Our in situ TEM experiments in combination with chemical mapping reveal the interdiffusion coefficients of Cu and Au at low temperatures and highlight the impact of ordering processes on the diffusion behavior. The formation of ordered domains within the solid-solution is examined using high-resolution imaging and nanodiffraction including strain mapping. In addition, we examine the effectiveness of ultrathin Al 2 O 3 barrier layers to control interdiffusion of the diffusion couple. Our findings indicate that a 5 nm thick layer serves as an efficient diffusion barrier. Furthermore, this research provides valuable insights into the interdiffusion behavior of Cu and Au on the nanoscale, offering potential applications in the development of miniaturized integrated circuits and nanodevices.

alloys↗
DOE OSTI2021

Systems Analysis Approach to Polyethylene Terephthalate and Olefin Plastics Supply Chains in the Circular Economy: A Review of Data Sets and Models

The environmental and economic impacts of implementing a circular economy in plastic waste supply chains are not well understood. The proposed systems analysis framework assesses environmental, social, and economic impacts of plastic waste supply chains in a circular economy. The first objective of this article is to identify datasets, models and knowledge gaps associated with waste plastic supply chain processes, mainly in the U.S. Our literature review indicated that the best datasets exist for virgin plastic resin production, mechanical recycling, landfilling, and incineration, with materials recovery facility being intermediate, and with chemical recycling the lowest. The second objective of this article is to develop an illustrative application of the framework by conducting a preliminary systems analysis of PET bottles with closed-loop recycling. Here, the preliminary systems analysis of PET bottles utilized a linear programming optimization method. Our optimization model indicated that both chemical and mechanical recycling processes are needed to achieve a true circular economy of PET bottles with the least greenhouse gas emissions, specifically reductions of 24% when compared with the linear economy. Good quality and standardized life cycle assessment and techno-economic analysis studies are needed to better understand the environmental, economic, and social impacts of advanced sorting and chemical recycling technologies.

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

Dynamic Evolution of Palladium Single Atoms on Anatase Titania Support Determines the Reverse Water–Gas Shift Activity

Research interest in single-atom catalysts (SACs) has been continuously rising. However, the lack of understanding of the dynamic behaviors of SACs during applications hinder catalyst development and mechanistic understanding. Herein, we report on the evolution of active sites over Pd/TiO 2 -anatase SAC (Pd 1 /TiO 2 ) in the reverse water-gas shift (rWGS) reaction. Combining kinetics, in-situ characterization, and theory, we show that at T ≥ 350 °C, the reduction of TiO 2 by H 2 alters the coordination environment of Pd, creating Pd sites with partially cleaved Pd-O interfacial bonds and a unique electronic structure that exhibit high intrinsic rWGS activity through the carboxyl pathway. The activation by H 2 is accompanied by the partial sintering of single Pd atoms (Pd 1 ) into disordered, flat, ~1 nm diameter clusters (Pd n ). The highly active Pd sites in the new coordination environment under H 2 are eliminated by oxidation, which, when performed at high temperature, also re-disperses Pd n and facilitates the reduction of TiO 2 . In contrast, Pd 1 sinters into crystalline, ~5 nm particles (Pd NP ) during CO treatment, deactivating Pd 1 /TiO 2 . During the rWGS reaction, the two Pd evolution pathways co-exist. The activation by H 2 dominates, leading to the increasing rate with time-on-stream, and steady-state Pd active sites similar with the ones formed under H 2 . Finally, this work demonstrates how the coordination environment and nuclearity of metal sites on a SAC evolve during catalysis and pre-treatments, and how their activity is modulated by these behaviors. These insights on SAC dynamics and structure-function relationship are valuable to mechanistic understanding and catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Mechanism of O 2 /NO-Promoted Oxidative C–C Bond Cleavage in Linear Alkanes

Selective oxidation of alkanes to oxygenated products remains a fundamental challenge, particularly if the goal is to promote C−C bond cleavage while minimizing formation of CO 2 . Oxidation conditions that use O 2 and nitrogen oxides (NO x ) have been shown to be very effective in promoting radical-mediated functionalization and oxidative carbon−carbon cleavage in saturated hydrocarbon polymers, such as polyethylene. Here, we investigate the mechanism of O 2 /NO-mediated oxidation of ndecane as a prototypical linear alkane substrate. These reactions enable identification and quantification of reactive intermediates, including nitrites, nitrates, alcohols, and ketones. Under the reaction conditions, these species convert into common ketone intermediates that evolve into α-diketones and other α-functionalized ketones, which undergo further conversion into carboxylic acids. Infrared (IR) spectroscopy indicates that HDPE oxidation proceeds through similar key intermediates. Together, these findings establish a mechanistic framework for NO x -mediated alkane oxidation and provide a foundation for the development of broadly applicable oxidative transformations.

Anions↗
DOE OSTI2024

Prediction of Distributed River Sediment Respiration Rates Using Community-Generated Data and Machine Learning

River sediment microbial respiration is a key indicator of ecosystem functioning and the biogeochemical fluxes across this critical zone link surface and subsurface waters. As such, there is tremendous interest in measuring and mapping these respiration rates. Respiration observations are expensive and labor intensive; there is limited data available to the community. An open science, collaborative initiative is collecting samples for respiration rate analysis and multi-scale metadata; this evolving data set is being used for making machine learning (ML) predictions at unsampled sites to help inform continued community engagement. However, it is a challenge to find an optimum configuration for ML models to work with this feature-rich (i.e., 100+ possible input variables) data set. Here, we present results from a two-tiered approach to managing the analysis of this complex data set: (a) a stacked ensemble of models that automatically optimizes hyperparameters and manages the training of many models and (b) feature permutation importance to detect the most important features in the models. The major elements of this workflow are modular, portable, open, and cloud-based thus making this implementation a potential template for other applications. The models developed here predict that sediment organic matter chemistry is one of the most important features for predicting sediment respiration rate. Other larger-scale, important features fall into the categories of climatic, ecological, geological, and fluvial settings. Leveraging these larger-scale features to generate data-driven estimates of river sediment respiration rates reveals spatially consistent but heterogeneous patterns across the river network of the Columbia River Basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Toward a mechanistic understanding of electrocatalytic nanocarbon

Electrocatalytic nanocarbon (EN) is a class of material receiving intense interest as a potential replacement for expensive, metal-based electrocatalysts for energy conversion and chemical production applications. The further development of EN will require an intricate knowledge of its catalytic behaviors, however, the true nature of their electrocatalytic activity remains elusive. This review highlights work that contributed valuable knowledge in the elucidation of EN catalytic mechanisms. Experimental evidence from spectroscopic studies and well-defined molecular models, along with the survey of computational studies, is summarized to document our current mechanistic understanding of EN-catalyzed oxygen, carbon dioxide and nitrogen electrochemistry. We hope this review will inspire future development of synthetic methods and in situ spectroscopic tools to make and study well-defined EN structures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements

Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling of various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards.

59 BASIC BIOLOGICAL SCIENCES↗