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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Validation study of RWM stability in DIII-D high- β N plasmas

The n = 1 (n is the toroidal mode number) resistive wall mode (RWM) stability is numerically investigated for two DIII-D high-β N discharges 176440 and 172461, utilizing the MARS-F (Liu et al 2000 Phys. Plasmas 7 3681) and MARS-K (Liu et al 2008 Phys. Plasmas 15 112503) codes. Systematic validation efforts are attempted, for the first time, for discharges with very slow or vanishing toroidal flow for a large fraction of the plasma volume. While gaining physics insights in accessing stable operation regime at β N exceeding the Troyon no-wall limit in these slow-rotation experiments, the predictive capability of fluid and non-perturbative magnetohydrodynamic-kinetic hybrid models for the RWM is further confirmed. The MARS-F fluid model, with a strong but numerically tunable viscosity mimicking ion Landau damping of parallel sound waves, finds complete stabilization of the n = 1 RWM in the considered DIII-D plasmas under the experimental flow conditions. Similarly, either full stabilization (for discharge 176440) or marginal stability (for discharge 172461) of the mode is computed by the MARS-K hybrid model, which is first-principle based without free model parameters. In particular, all drift kinetic resonances, including those of thermal and energetic particles, are found to synergistically act to marginally stabilize the RWM in discharge 172461. These MARS-F/K modeling results explain the experimentally observed stable operational regime in DIII-D, as far as the RWM stability is concerned. Extensive numerical sensitivity studies, with respect to the plasma toroidal flow speed as well as the radial location of the resistive wall, are also carried out to further support the validation study.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Thermodynamic stability versus kinetic accessibility: Pareto fronts for programmable self-assembly

A challenge in designing self-assembling building blocks is to ensure the target state is both thermodynamically stable and kinetically accessible. These two objectives are known to be typically in competition, but it is not known how to simultaneously optimize them. We consider this problem through the lens of multi-objective optimization theory: we develop a genetic algorithm to compute the Pareto fronts characterizing the tradeoff between equilibrium probability and folding rate, for a model system of small polymers of colloids with tunable short-ranged interaction energies. We use a coarse-grained model for the particles' dynamics that allows us to efficiently search over parameters, for systems small enough to be enumerated. For most target states there is a tradeoff when the number of types of particles is small, with medium-weak bonds favouring fast folding, and strong bonds favouring high equilibrium probability. Additionally, the tradeoff disappears when the number of particle types reaches a value m *, that is usually much less than the total number of particles. This general approach of computing Pareto fronts allows one to identify the minimum number of design parameters to avoid a thermodynamic–kinetic tradeoff. However, we argue, by contrasting our coarse-grained model's predictions with those of Brownian dynamics simulations, that particles with short-ranged isotropic interactions should generically have a tradeoff, and avoiding it in larger systems will require orientation-dependent interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Internal calibration of transient kinetic data via machine learning

The temporal analysis of products (TAP) reactor provides a vast amount of transient kinetic information that may be used to describe a variety of chemical features including residence time distributions, kinetic coefficients, number of active sites, reaction mechanism, etc. However, as with any measurement device, the TAP reactor signal is convoluted with noise and drift is common. In order to reduce the uncertainty of the kinetic measurement and any derived parameters or mechanisms, proper preprocessing must be performed prior to any advanced type of analysis. This preprocessing includes baseline correction, i.e., a shift in the voltage response, and calibration, i.e., a scaling of the flux response based on prior experiments. The traditional methodology of preprocessing requires significant user discretion and reliance on separate calibration experiments that may drift over time. Herein we use machine learning techniques combined with physical constraints to understand the noise and drift that is being generated within and between experiments for enhancement of the chemical kinetic signal. As such, the proposed methodology demonstrates clear benefits over the traditional preprocessing approach by eliminating the need for separate calibration experiments or heuristic input from the user.

36 MATERIALS SCIENCE↗
NASA NTRS1988

Theoretical studies of solar lasers and converters

The geometry and setup for the n-C3F7I iodine laser are illustrated. The mathematical modeling of this system is described. The chemical kinetics are summarized. A sensitivity analysis was performed on the parameters occurring in the differential equations describing the chemical kinetics.

Heinbockel, John↗
DOE OSTI2021

Active microbial biomass decreases, but microbial growth potential remains similar across soil depth profiles under deeply-vs. shallow-rooted plants

Climate-smart land management practices that replace shallow-rooted annual crop systems with deeply-rooted perennial plants can contribute to soil carbon sequestration. However, deep soil carbon accrual may be influenced by active microbial biomass and their capacity to assimilate fresh carbon at depth. Incorporating active microbial biomass, dormancy, and growth in microbially-explicit models can improve our ability to predict soil's capacity to store carbon. But, so far, the microbial parameters that are needed for such modeling are poorly constrained, especially in deep soil layers. Here, we used a lab incubation experiment and growth kinetics model to estimate how microbial parameters vary along 240 cm of soil depth in profiles under shallow- (soy) and deeply-rooted (switchgrass) plants 11 years after plant cover conversion. We also assessed resource origin and availability (total organic carbon, 14 C, extractable organic carbon, specific UV absorbance of K 2 SO 4 extractable organic C, total nitrogen, total dissolved nitrogen) along the soil profiles to examine associations between soil chemical and biological parameters. Even though root biomass was greater and rooting depth was deeper under switchgrass than soy, resource availability and microbial growth parameters were generally similar between vegetation types. Instead, depth significantly influenced soil chemical and biological parameters. For example, resource availability and total and relative active microbial biomass decreased with soil depth. Decreases in the relative active microbial biomass coincided with increased lag time (response time to external carbon inputs) along the soil profiles. Even at a depth of 210–240 cm, microbial communities were activated to grow by added resources within a day. Maximum specific growth rate decreased to a depth of 90 cm and then remained consistent in deeper layers. Our findings show that >10 years of vegetation and rooting depth changes may not be long enough to alter microbial growth parameters, and suggest that at least a portion of the microbial community in deep soils can grow rapidly in response to added resources. Our study determined microbial growth parameters that can be used in microbially-explicit models to simulate carbon dynamics in deep soil layers.

14C↗
DOE OSTI2020

A mechanism-based quantitative multi-scale framework for investigating irradiation hardening of tungsten at low temperature

We present the development and validation of a mechanism-based multi-scale modeling framework to quantitatively link the irradiation defect evolution kinetics at the microscopic scale to the macroscopic yield strength and flow stress evolution of tungsten irradiated at low temperature (0.08 < T/T m < 0.18, where T m is the melting point and is equal to 3673 K). The mechanism-based strength model, proposed as the superposition of thermal softening and modified dispersed barrier hardening, is developed to understand the underlying strengthening mechanisms. The thermal softening exponent as defined in the Johnson-Cook model is obtained by fitting unirradiated yield strength at different temperatures. A set of irradiation-induced defect kinetics equations with the thermodynamics parameters derived from the atomic calculations reported in the literature is used to determine the densities and sizes of defect clusters at the meso-scale, and the predicted irradiation damage characteristics are in reasonable quantitative agreement with experimental data from literature. The effects of irradiation condition (temperature and irradiation dose) and test temperature on yield strength are quantitatively predicted and compared with experimental measurements from the literature. Here, the predicted irradiation hardening and strain hardening are compared with experimental data as model validation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research

Leading edge erosion (LEE) of wind turbine blades causes decreased aerodynamic performance leading to lower power production and revenue and increased operations and maintenance costs. LEE is caused primarily by materials stresses when hydrometeors (rain and hail) impact on rotating blades. The kinetic energy transferred by these impacts is a function of the precipitation intensity, droplet size distributions (DSD), hydrometeor phase and the wind turbine rotational speed which in turn depends on the wind speed at hub-height. Hence, there is a need to better understand the hydrometeor properties and the joint probability distributions of precipitation and wind speeds at prospective and operating wind farms in order to quantify the potential for LEE and the financial efficacy of LEE mitigation measures. However, there are relatively few observational datasets of hydrometeor DSD available for such locations. Here, we analyze six observational datasets from spatially dispersed locations and compare them with existing literature and assumed DSD used in laboratory experiments of material fatigue. We show that the so-called Best DSD being recommended for use in whirling arm experiments does not represent the observational data. Neither does the Marshall Palmer approximation. We also use these data to derive and compare joint probability distributions of drivers of LEE; precipitation intensity (and phase) and wind speed. We further review and summarize observational metrologies for hydrometeor DSD, provide information regarding measurement uncertainty in the parameters of critical importance to kinetic energy transfer and closure of data sets from different instruments. A series of recommendations are made about research needed to evolve towards the required fidelity for a priori estimates of LEE potential.

17 WIND ENERGY↗
NASA NTRS1986

Theory of homogeneous nucleation - A chemical kinetic view

A simple function with two undetermined parameters has been used in place of the Thomson-Gibbs relation to relate the activation energy of the vaporization reaction to cluster size. The parameters are iterated to assume optimum values in numerical computation so experimental data may be correlated. Calculations show this approach closely predicts and correlates available data for water, benzene, and ethanol. The nucleation formulism is redeveloped with an emphasis on the chemical kinetic view. Surface tension of the liquid and free energy of droplet formation are not used in its derivation.

Yang, C. H.↗
NASA NTRS1978

The entraining moist boundary layer

A unified theory of entrainment into the planetary boundary layer is presented. It is assumed that the rates of buoyant and shear production of turbulence kinetic energy can be determined in terms of the entrainment mass flux. An expression is derived from the conservation law for turbulence kinetic energy, which, with the introduction of an empirical parameter, can be used together with a second relation between turbulence kinetic energy and the turbulence velocity scale to obtain the mass entrainment flux. The theory provides descriptions of storage-limited entrainment, buoyancy-limited entrainment into a clear mixed layer, and shallowing. It has been incorporated into a simulation of Day 33 of the Wangara experiment using a simple mixed layer model.

Randall, D. A.↗
DOE OSTI2022

Machine Learning Guided Synthesis of Flash Graphene

Advances in nanoscience have enabled the synthesis of nanomaterials, such as graphene, from low-value or waste materials through flash Joule heating. Though this capability is promising, the complex and entangled variables that govern nanocrystal formation in the Joule heating process remain poorly understood. In this work, machine learning (ML) models are constructed to explore the factors that drive the transformation of amorphous carbon into graphene nanocrystals during flash Joule heating. An XGBoost regression model of crystallinity achieves an r 2 score of 0.8051 ± 0.054. Feature importance assays and decision trees extracted from these models reveal key considerations in the selection of starting materials and the role of stochastic current fluctuations in flash Joule heating synthesis. Furthermore, partial dependence analyses demonstrate the importance of charge and current density as predictors of crystallinity, implying a progression from reaction-limited to diffusion-limited kinetics as flash Joule heating parameters change. Finally, a practical application of the ML models is shown by using Bayesian meta-learning algorithms to automatically improve bulk crystallinity over many Joule heating reactions. Furthermore, these results illustrate the power of ML as a tool to analyze complex nanomanufacturing processes and enable the synthesis of 2D crystals with desirable properties by flash Joule heating.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Screening a knowledge‐based library of low molecular weight compounds against the proline biosynthetic enzyme 1‐pyrroline‐5‐carboxylate 1 ( PYCR1)

Abstract Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 1 (PYCR1) is the last enzyme of proline biosynthesis and catalyzes the NAD(P)H‐dependent reduction of Δ 1 ‐pyrroline‐5‐carboxylate toL‐proline. High PYCR1 gene expression is observed in many cancers and linked to poor patient outcomes and tumor aggressiveness. The knockdown of thePYCR1gene or the inhibition of PYCR1 enzyme has been shown to inhibit tumorigenesis in cancer cells and animal models of cancer, motivating inhibitor discovery. We screened a library of 71 low molecular weight compounds (average MW of 131 Da) against PYCR1 using an enzyme activity assay. Hit compounds were validated with X‐ray crystallography and kinetic assays to determine affinity parameters. The library was counter‐screened against human Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 3 and proline dehydrogenase (PRODH) to assess specificity/promiscuity. Twelve PYCR1 and one PRODH inhibitor crystal structures were determined. Three compounds inhibit PYCR1 with competitive inhibition parameter of 100 μM or lower. Among these, (S)‐tetrahydro‐2H‐pyran‐2‐carboxylic acid (70 μM) has higher affinity than the current best tool compoundN‐formyl‐l‐proline, is 30 times more specific for PYCR1 over human Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 3, and negligibly inhibits PRODH. Structure‐affinity relationships suggest that hydrogen bonding of the heteroatom of this compound is important for binding to PYCR1. The structures of PYCR1 and PRODH complexed with 1‐hydroxyethane‐1‐sulfonate demonstrate that the sulfonate group is a suitable replacement for the carboxylate anchor. This result suggests that the exploration of carboxylic acid isosteres may be a promising strategy for discovering new classes of PYCR1 and PRODH inhibitors. The structure of PYCR1 complexed withl‐pipecolate and NADH supports the hypothesis that PYCR1 has an alternative function in lysine metabolism.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Effect of polymer structure and material properties on mechanochemical reaction environments for polymer recycling

Plastic waste accumulation necessitates innovative recycling approaches to achieve sustainability goals. Mechanochemical depolymerization offers a solvent-free, energy-efficient route to convert polymers into valuable monomers. In addition to their chemical properties, the way that polymers absorb kinetic energy is a key parameter of any mechanochemical process. This perspective explores the principles underpinning mechanochemical recycling, emphasizing how deformation and localized transient heating mediate energy transfer between impacts and localized excitations. Key factors such as polymer crystallinity, molecular weight, viscoelasticity, and thermal effects are analyzed to elucidate their role in energy transfer mechanisms during ball milling. This work establishes a foundational framework for the design and optimization of mechanochemical recycling by connecting polymer response to mechanical energy with the intention to improve depolymerization efficiency. Future research opportunities are outlined to advance the integration of polymer science and mechanochemistry for scalable, sustainable plastic upcycling.

ball mill↗
DOE OSTI2020

Reactive chemical transport simulations of geologic carbon sequestration: Methods and applications

Chemical reaction simulations are considerably used to quantitatively assess the long-term geologic carbon sequestration (GCS), such as CO 2 sequestration capacity estimations, leakage pathway analyses, enhanced oil recovery (EOR) efficiency studies, and risk assessments of sealing formations (caprocks), wellbores, and overlying underground water resources. All these require a deep understanding of the CO 2 - associated chemical reactions. To ensure long-term, safe CO 2 sequestration in the intended formations, modeling is the only way to plausibly assess the CO 2 flow, reaction, and transport over thousands of years. This review summarizes the multiple methodologies for describing homogeneous and heterogeneous chemical reaction patterns and multiscale application examples, the recent progress and current status of chemical reaction simulations for GCS, and the impact of such simulations on geological CO2 sequestration performance. Technical gaps and future challenges are also discussed for further study. The trends and challenges of such studies include: (1) the combination of coupled chemical, mechanical, and transport processes with calibrated experiments and associated uncertainty/risk assessments; (2) enhancement of the ability to simulate detailed geophysical and geochemical equations to mimic in situ conditions; and (3) characterization of multiscale subsurface systems with detailed conceptual models and assignment of suitable boundary conditions for field-scale sequestration fields. One major gap remaining is the current lack of accurate (and scale-justified) kinetic and equilibrium chemical reaction parameters under reservoir conditions. Advanced models that couple chemical, mechanical, and transport processes with scale-justified parameters, from lab to field-scale experiments, are required for quantitative assessments of sequestration capacity and the long-term safety of GCS projects.

58 GEOSCIENCES↗
DOE OSTI2022

Chemical Challenges that the Peroxide Dianion Presents to Rechargeable Lithium–Air Batteries

Understanding the fundamental redox reactions and processes that occur in lithium–air and, more generally, metal–air batteries is important to the progress of this promising energy-storage technology. Knowledge of the chemistry of the peroxide dianion, O 2 2– , is especially crucial, as the dianion is at the nexus of the charge/discharge cycle of lithium–air batteries. The intrinsic electron transfer properties and redox chemistry of peroxide dianion are poorly defined because it is difficult to isolate the dianion free of protons and metal ions. We review the results of (i) the electron transfer kinetics and (ii) the redox reaction chemistry of isolated peroxide dianion encapsulated within the cavity of a hexacarboxamide cryptand. With regard to the former, electron transfer kinetics measurements provide fundamental Marcus parameters that will be useful for models that seek to disentangle the precise contributions of Li + ion-coupled electron transfer, electron transfer across the Li 2 O 2 solid particle interface, and charge hopping among Li 2 O 2 particles. With regard to the latter, an underappreciated chemistry of peroxide dianion with CO 2 produces peroxymonocarbonate (OOCO 2 2– ) and peroxydicarbonate (O 2 COOCO 2 2– ). An autocatalytic cycle will lead to oxidative degradation of traditional organic electrolytes and other vulnerable cell components employed in lithium–air batteries. Furthermore, this peroxycarbonate-derived chemistry, in addition to more commonly recognized solution-based oxidation chemistry, will need to be mitigated to realize the long-term cyclability of rechargeable lithium–air batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Theory for transport in magnetized plasmas

We present a two fluid model for anomalous thermal, particle and momentum transport which has been derived from kinetic theory using a small parameter ε~10-2. This small parameter can come from either the ratio of wave frequency to cyclotron frequency or the ratio of potential to thermal energies. This fluid model is strongly nonlinear and has an exact closure within the accuracy ε. It can be used to simulate the full radius of a tokamak including internal and edge transport barriers at the same time without introducing any local assumptions for physics model or grid size. It involves a full transport matrix, thus giving possibility for both density and heat pinches. The model can be derived from the Vlasov equation, adding also close collisions and includes particle pinches of the type found in the magnetosphere and in the Massachusetts Institute of Technology elevated dipole machine. Pinches are also in agreement for the heat pinch experiments on Doublet III D including simultaneous particle and heat pinches. For tokamaks it gives the right scaling of confinement time versus heating power. Finally, we have also recovered the Turbulent Equipartition result that the density scales as inverse safety factor q in typical simulations. Thus this model is both fundamental and of high practical use.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Properties of molecular clumps and cores in colliding magnetized flows

ABSTRACT We simulate the formation of molecular clouds in colliding flows of warm neutral medium with the adaptive mesh refinement code flash in eight simulations with varying initial magnetic field strength, between 0.01–5 μG. We include a chemical network to treat heating and cooling and to follow the formation of molecular gas. The initial magnetic field strength influences the fragmentation of the forming cloud because it prohibits motions perpendicular to the field direction and hence impacts the formation of large-scale filamentary structures. Molecular clump and core formation occurs anyhow. We identify 3D clumps and 3D cores, which are defined as connected, CO-rich regions. Additionally, 3D cores are heavily shielded. While we do not claim those 3D objects to be directly comparable to observations, this enables us to analyse their full virial state. With increasing field strength, we find more fragments with a smaller average mass; yet the dynamics of the forming clumps and cores only weakly depends on the initial magnetic field strength. The molecular clumps are mostly unbound, probably transient objects, which are weakly confined by ram pressure or thermal pressure, indicating that they are swept up by the turbulent flow. They experience significant fluctuations in the mass flux through their surface, such that the Eulerian reference frame shows a dominant time-dependent term due to their indistinct nature. We define the cores to encompass highly shielded molecular gas. Most cores are in gravitational-kinetic equipartition and are well described by the common virial parameter $\alpha _\mathrm{vir}$, while some undergo minor dispersion by kinetic surface effects.

Weis, M. (ORCID:0000000256838860)↗
DOE OSTI2021

Method—Using Microelectrodes to Explore Solid Polymer Electrolytes

Solid polymer electrolytes are an emerging technology in electrochemistry driven by their use in energy applications such as fuel cells, electrolyzers, and solid-state batteries. Compared to traditional liquid electrolytes, solid polymer electrolytes provide safer, cheaper, and potentially improved device performance. However, there is a lack of standard experimental methods for studying solid electrolytes. Microelectrodes have inherent benefits capable of filling this experimental gap due primarily to their integration into model electrochemical cells with solid electrolytes that represent complex interfaces, enabling additional insight into reaction processes. In this tutorial review, we explore the use of microelectrodes to study solid polymer electrolytes, beginning with a brief history of the field including common experimental cell designs and their benefits and drawbacks. Methods of evaluating essential kinetic and mass-transport parameters are then examined. In addition, the key studies of the past 30 years utilizing microelectrode cells and solid polymer electrolytes are summarized, with important results highlighted and compared. Finally, future studies of solid polymer electrolytes with microelectrodes and potential new avenues of research are commented on.

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

BISON BWR Fuel Modeling Capability: Material Models (FY2020)

Until this year the BISON fuel performance code has been developed primarily for pressurized water reactor (PWR), accident tolerant fuel (ATF), and advanced reactor (e.g., tri-structural isotropic (TRISO), metallic) analyses. The main focus of this work is to develop and document required material models that would aid predicting cladding failure with a specific hydride distribution to be investigated for boiling water reactor (BWR) applications in the next fiscal year. In terms of materials, the primary differences between a BWR and PWR is the use of gadolinia doping of the UO 2 fuel, the use of Zircaloy-2 for the cladding, and the addition of a liner on the inner surface of the cladding for improved pellet-clad mechanical interaction (PCMI)performance. The liner is typically made of pure zirconium or a lower tin content zirconium alloy (e.g. Zr-0.3%Sn). This work details the development and documentation of material and behavioral models for BWR analysis such as the addition of material and behavior models for gadolinia doped UO 2 , pure zirconium, Zr-0.3%Sn, and Zircaloy-2 as well as the ease-of-use additions to allow internal meshing capabilities to include liners. Another important aspect affecting cladding performance is hydrogen diffusion and hydride precipitation in the cladding. A model was added previously for non-lined, homogeneous claddings. In this work, instructions are provided on how to apply the model to BWR liner cladding. Representative experimental values are provided for the hydrogen diffusion parameters and precipitation-dissolution kinetics for typical liner materials of interest.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗