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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Bounce-averaged theory in arbitrary multi-well plasmas: solution domains and the graph structure of their connections

Bounce-averaged theories provide a framework for simulating relatively slow processes, such as collisional transport and quasilinear diffusion, by averaging these processes over the fast periodic motions of a particle on a closed orbit. This procedure dramatically increases the characteristic time scale and reduces the dimensionality of the modelled system. The natural coordinates for such calculations are the constants of motion (COM) of the fast particle motion, which by definition do not change during an orbit. However, for sufficiently complicated fields – particularly in the presence of local maxima of the electric potential and magnetic field – the COM are not sufficient to specify the particle trajectory. In such cases, multiple domains in COM space must be used to solve the problem, with boundary conditions enforced between the domains to ensure continuity and particle conservation. Previously, these domains have been imposed by hand, or by recognising local maxima in the fields, limiting the flexibility of bounce-averaged simulations. Here, we present a general set of conditions for identifying consistent domains and the boundary condition connections between the domains, allowing the application of bounce-averaged theories in arbitrarily complicated and dynamically evolving electromagnetic field geometries. We also show how the connections between the domains can be represented by a directed graph, which can help to succinctly represent the trajectory bifurcation structure.

fusion plasma↗
DOE OSTI2018

PLUMECALC, Version 2.3.x

PLUMECALC is a post processor to random walk particle tracking simulations of subsurface solute transport. PLUMECALC takes results of a single particle tracking run without retention processes and incorporates the effects of matrix diffusion or other retention processes for a user-specified solute source.

Dash, Zora↗
DOE OSTI2026

Diffusion and Solvation Dynamics of Ions in Water: Beyond the Brownian Approximation

The coupled dynamics of ions and water molecules in their first hydration shell impact a variety of processes including ion diffusion, selective ion transport in water-filled nanopores, and the kinetics of ion-pairing, ion adsorption, and metal-ligand binding reactions. In this work, we study these coupled dynamics for alkali metals (Li, Na, K, Rb, Cs), alkaline Earth metals (Mg, Ca, Sr, Ba), and chloride through the lens of their dependence on ion isotopic mass. Results are validated against previous measurements of the isotopic mass-dependence of ion diffusion coefficients in water and previous ab initio calculations of ion high-frequency dynamics in water. We find that the vibrational power spectra of ions in water consistently exhibit either two or three peaks, i.e., ions have several rattling frequencies within their solvations shells as previously reported for a subset of the species examined here. These frequencies have different sensititivies to isotopic mass that may serve as signatures of ion solvation processes (such as the tendency of ions to orient their first-shell water molecules) and that also may relate to Hofmeister-like effects including the relative affinity of different metals for ribonucleic acid (RNA).

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

The influence of pilot injection on high-temperature ignition processes and early flame structure in a high-speed direct injection diesel engine

Simultaneous high-speed natural luminosity and OH* chemiluminescence imaging is used to characterize high-temperature ignition processes in conventional diesel combustion with a pilot-main injection strategy in a single-cylinder, light-duty optical diesel engine. High-speed imaging provides temporally and spatially resolved information in terms of high-temperature ignition processes and flame structure during the combustion. Using these imaging measurements, the high-temperature inflammation and the diffusion flame development processes are analyzed. The chemiluminescence signal shows a hot, reactive mixture, which gradually decreases after the peak release of the pilot combustion and lasts long after the apparent heat release has ended. Therefore, when the reactive pilot mixture exists near the main injection jets, the high-temperature ignition of the main injection is apparently initiated through interactions with the reactive pilot mixture. High-temperature autoignition, another process by which ignition of the main injection occurs, is observed in main injection plumes where the chemiluminescence signal of the reactive pilot mixture becomes very weak or is absent at the start of main injection. As the reaction of the main injection continues, the non-premixed main injection jet structure is developed and the high-temperature reacting region expands throughout the jet.

Park, Cheolwoong↗
DOE OSTI2025

Phase-field modeling of diffusion bonding in 316H stainless steel: Impact of processing conditions on grain morphology and bonding quality

A novel multi-phase, multi-component phase‐field model is presented to study the diffusion bonding of 316H stainless steel. Combined with targeted experimental investigations, this model simulates the bond-growth process and predicts the bonding quality. Unlike previous models, our approach captures the simultaneous evolution of voids and grain structures, while quantifying bonding quality using defined bonding ratio. A comprehensive analysis of bond process control is performed by changing temperature, pressure and surface roughness observing the resulting bond structure, which is consistent with experimental observations and analytical predictions. Temperature is determined to be the dominant factor, with the transition from a flat to a robust bond occurring between 1000 °C and 1050 °C. At the ideal bonding temperature of 1050 °C, a surface roughness exceeding 0.6 μm or an applied stress below 4 MPa results in poor bonding quality. Beyond this, higher pressures and smoother surfaces reduce void size, accelerate void shrinkage, and lead to improved bond integrity. This diffuse-interface model can be extended to other material systems if supplied with appropriate thermodynamic and kinetic data. In conclusion, this makes it an effective modeling platform for optimizing high-temperature diffusion bonding and developing reliable bonded components such as compact heat exchangers.

Diffusion bonding↗
DOE OSTI2019

Amorphous and crystalline TiO 2 nanoparticle negative electrodes for sodium-ion batteries

Titanium dioxide (TiO 2 ) is a promising negative electrode for sodium ion batteries (SIBS). Although TiO 2 materials with amorphous (A-TiO 2 ) and single-phase crystalline structures (C-TiO 2 ) have been separately explored, the study to compare the fundamental electrochemistry of A-TiO 2 and C-TiO 2 is limited. In this work, we investigated A-TiO 2 and C-TiO 2 nanoparticles with identical chemical composition and morphology. C-TiO 2 exhibits enhanced electrochemical performance than A-TiO 2 in terms of rate capability and cycle life. Cyclic voltammetry (CV) analysis suggests reversible Na ion insertion/extraction in C-TiO 2 . However, such process is irreversible in the case of A-TiO 2 . The charge storage mechanisms in both samples were studied to show that diffusion-controlled intercalation process becomes significant in C-TiO 2 sample. The C-TiO 2 sample has a better Na + diffusivity measured through the galvanostatic intermittent titration technique (GITT) compared to A-TiO 2 , which corroborates well with the rate capability study. Furthermore, the evolution of local structure of the TiO 2 samples was analyzed by ex situ pair distribution function (PDF) to understand the variation in electrochemical properties. In conclusion, it reveals that the corner-shared Ti-Ti distance along Na ion diffusion pathway increases with the increase of crystallinity, leading to the expanded diffusion channels and therefore more active sites and faster diffusion.

25 ENERGY STORAGE↗
DOE OSTI2016

Integrating carbon nanotube forests into polysilicon MEMS: Growth kinetics, mechanisms, and adhesion

The growth of carbon nanotubes (CNTs) on polycrystalline silicon substrates was studied to improve the design of CNT field emission sources for microelectromechanical systems (MEMS) applications and vacuum microelectronic devices (VMDs). Microwave plasma-enhanced chemical vapor deposition (PECVD) was used for CNT growth, resulting in CNTs that incorporate the catalyst particle at their base. The kinetics of CNT growth on polysilicon were compared to growth on Si (100) using the model of Deal and Grove, finding activation energies of 1.61 and 1.54 eV for the nucleation phase of growth and 1.90 and 3.69 eV for the diffusion-limited phase on Si (100) and polysilicon, respectively. Diffusivity values for growth on polysilicon were notably lower than the corresponding values on Si (100) and the growth process became diffusion-limited earlier. Evidence favors a surface diffusion growth mechanism involving diffusion of carbon precursor species along the length of the CNT forest to the catalyst at the base. Explanations for the differences in activation energies and diffusivities were elucidated by SEM analysis of the catalyst nanoparticle arrays and through wide-angle X-ray scattering (WAXS) of CNT forests. As a result, methods are presented to improve adhesion of CNT films during operation as field emitters, resulting in a 2.5× improvement.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Protection of rubbers against aging with the use of structural, diffusion and kinetic effects

Processes of rubber aging in the different kinetic modes and mathematical models of the processes including aging and destruction processes under extreme conditions have been studied. The aging process for rubbers as thermodynamically open nonlinear systems has also been considered in the paper. It has been revealed that the aging process can be controlled by the internal physical-chemical processes organization and by creation of external influences (by organization of thermodynamic forces and flows). According to the Onsager principle, in certain conditions of aging the conjugation of thermodynamic forces and flows is possible. The diffusion and structural aspects of aging in elastomeric rubbers and articles thereof have been considered. The composite antiaging systems of prolonged action based on the use of microparticles with a saturated solution of the antiagers migrating into an elastomeric matrix at the exploitation have been proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An evaluation of size-resolved cloud microphysics scheme numerics for use with radar observations Part II: Condensation and evaporation

Accurate numerical modeling of clouds and precipitation is essential for weather forecasting and climate change research. While size-resolved (bin) cloud microphysics models predict particle size distributions without imposing shapes, results are subject to artificial size distribution broadening owing to numerical diffusion associated with various processes. Whereas Part I of this study addressed collision–coalescence, here we investigate numerical diffusion that occurs in solving condensation and evaporation. In a parcel model framework, all of the numerical schemes examined converge to one solution of condensation and evaporation as the mass grid is refined, and the advection-based schemes are recommended over the reassigning schemes. Including Eulerian vertical advection in a column limits the convergence to some extent, but that limitation occurs at a sufficiently fine mass grid, and the number of iterations in solving vertical advection should be minimized to reduce numerical diffusion. Insubstantial numerical diffusion in solving condensation can be amplified if collision–coalescence is also active, which in turn can be substantially diminished if turbulence effects on collision are incorporated. Here, large-eddy simulations of a drizzling stratocumulus field reveal that changes in moments of Doppler spectra obtained using different mass grids are consistent with those obtained from the simplified framework, and that spectral moments obtained using a mass grid designed to effectively reduce numerical diffusion are generally closer to observations. Notable differences between the simulations and observations still exist, and our results suggest a need to consider whether factors other than numerical diffusion in the fundamental process schemes employed can cause such differences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

AGR-1, AGR-2 and AGR-3/4 Release-to-Birth Ratio Data Analysis

A series of Advanced Gas Reactor (AGR) irradiation tests is being conducted in the Advanced Test Reactor at Idaho National Laboratory in support of development and qualification of tristructural isotropic (TRISO) low enriched fuel used in the High Temperature Gas-cooled Reactor (HTGR). Each AGR test consists of multiple independently controlled and monitored capsules containing fuel compacts placed in a graphite cylinder shrouded by a steel shell. These capsules are instrumented with thermocouples embedded in the graphite enabling temperature control. AGR configuration and irradiation conditions are based on prismatic HTGR technology distinguished primarily by the use of helium coolant, a low-power-density ceramic core capable of withstanding very high temperatures, and TRISO coated particle fuel. Thus, these tests provide valuable irradiation performance data to support fuel process development, qualify fuel for normal operating conditions, and support development and validation of fuel performance and fission product transport models and codes. The release-rate-to-birth-rate ratio (R/B) for each of fission product isotopes (i.e., krypton and xenon) is calculated from release rates in the sweep gas flow measured by the germanium detectors used in the AGR Fission Product Monitoring (FPM) System installed downstream from each irradiated capsule. Birth rates are calculated based on the fission power in the experiment and fission product generation models. Thus, this R/B is a measure of the ability of fuel kernel, particle coating layers, and compact matrix to retain fission gas atoms preventing their release into the sweep gas flow, especially in the event of particle coating failures that occurred during AGR-2 and AGR-3/4 irradiations. The major factors that govern gaseous radioactive decay, diffusion, and release processes are found to be material diffusion coefficient, temperature, and isotopic decay constant. For each of all AGR capsules, ABAQUS-based three-dimensional finite-element thermal models are created to predict daily averages of fuel compact temperatures for the entire irradiation period, which are used in establishing the R/B correlation with temperature and decay constant. This correlation can be used by reactor designers to estimate fission gas release from postulated failed fuel particles in HTGR cores, which is the key safety factor for fuel performance assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

AGR-2 and AGR-3/4 Release-to-Birth Ratio Data Analysis

A series of Advanced Gas Reactor (AGR) irradiation tests is being conducted in the Advanced Test Reactor at Idaho National Laboratory in support of development and qualification of tristructural isotropic (TRISO) low enriched fuel used in the High Temperature Gas-cooled Reactor (HTGR). Each AGR test consists of multiple independently controlled and monitored capsules containing fuel compacts placed in a graphite cylinder shrouded by a steel shell. These capsules are instrumented with thermocouples embedded in the graphite enabling temperature control. AGR configuration and irradiation conditions are based on prismatic HTGR technology distinguished primarily by the use of helium coolant, a low-power-density ceramic core capable of withstanding very high temperatures, and TRISO coated particle fuel. Thus, these tests provide valuable irradiation performance data to support fuel process development, qualify fuel for normal operating conditions, and support development and validation of fuel performance and fission product transport models and codes. The release-rate-to-birth-rate ratio (R/B) for each of fission product isotopes (i.e., krypton and xenon) is calculated from release rates in the sweep gas flow measured by the germanium detectors used in the AGR Fission Product Monitoring (FPM) System installed downstream from each irradiated capsule. Birth rates are calculated based on the fission power in the experiment and fission product generation models. Thus, this R/B is a measure of the ability of fuel kernel, particle coating layers, and compact matrix to retain fission gas atoms preventing their release into the sweep gas flow, especially in the event of particle coating failures that occurred during AGR-2 and AGR-3/4 irradiations. The major factors that govern gaseous radioactive decay, diffusion, and release processes are found to be material diffusion coefficient, temperature, and isotopic decay constant. For each of all AGR capsules, ABAQUS-based three-dimensional finite-element thermal models are created to predict daily averages of fuel compact temperatures for the entire irradiation period, which are used in establishing the R/B correlation with temperature and decay constant. This correlation can be used by reactor designers to estimate fission gas release from postulated failed fuel particles in HTGR cores, which is the key safety factor for fuel performance assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Investigation of desorption of hydrogen gas from polymer matrix using thermal desorption analysis and finite element modeling

Polymer materials are used widely as sealing materials and liners in hydrogen storage and transportation infrastructure. During operating conditions, polymers are exposed to high pressure hydrogen gas periodically. When in contact, the hydrogen gas diffuses through the polymer material with ease due to its smaller sized molecules compared to the polymer molecules. In the event of rapid decompression of outside hydrogen gas, the hydrogen molecules within the polymer diffuse out. This process is known as the desorption of polymer and can cause blisters or cracking causing permanent damage to the polymer. Here, we used a combined experimental and modeling approach to investigate the desorption of the hydrogen gas in the polymer. Thermal desorption analysis (TDA) experiments were performed on the polymer sample exposed to the high-pressure hydrogen gas to measure the diffusion coefficient and equilibrium hydrogen concentration. Experiments also provided the quantity of hydrogen within the polymer during the desorption process which followed Fick’s law. However, for higher pressurization values, some anomaly was observed in the quantity of hydrogen remaining in the polymer sample. A continuum mechanics based coupled diffusion–deformation-damage model was deployed to simulate the gas desorption process in the material using the finite element method to understand its effect on the material. It was found that the anomaly in TDA results were due to the blister formation on the polymer surface which resulted in longer hydrogen retention. Simulations also showed that blister formation can be affected by multiple parameters such as the addition of filler particles, and pre-existing cavity size.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A self-consistent and spatially dependent model of the multiband emission of pulsar wind nebulae

A self-consistent and spatially dependent model is presented to investigate the multiband emission of pulsar wind nebulae (PWNe). In this model, a spherically symmetric system is assumed and the dynamical evolution of the PWN is included. The processes of convection, diffusion, adiabatic loss, radiative loss, and photon–photon pair production are taken into account in the electron’s evolution equation, and the processes of synchrotron radiation, inverse Compton scattering, synchrotron self-absorption, and pair production are included for the photon’s evolution equation. Both coupled equations are simultaneously solved. The model is applied to explain observed results of the PWN in MSH 15–52. Our results show that the spectral energy distributions (SEDs) of both electrons and photons are all a function of distance. The observed photon SED of MSH 15–52 can be well reproduced in this model. With the parameters obtained by fitting the observed SED, the spatial variations of photon index and surface brightness observed in the X-ray band can also be well reproduced. Moreover, it can be derived that the present-day diffusion coefficient of MSH 15–52 at the termination shock is κ{sub 0}=6.6×10{sup 24} cm{sup 2} s{sup −1}, the spatial average has a value of κ-bar =1.4×10{sup 25} cm{sup 2} s{sup −1}, and the present-day magnetic field at the termination shock has a value of B{sub 0}=26.6 μG and the spatial averaged magnetic field is B-bar =14.9 μG. The spatial changes of the spectral index and surface brightness at different bands are predicted.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

WE-FG-202-11: Longitudinal Diffusion MRI for Treatment Assessment of Sarcoma Patients with Pre-Operative Radiation Therapy

Purpose: Diffusion weighted MRI (DWI) is a promising imaging technique for early prediction of tumor response to radiation therapy. A recently proposed longitudinal DWI strategy using a Co-60 MRI guided RT system (MRIgRT) may bring functional MRI guided adaptive radiation therapy closer to clinical utility. We report our preliminary results of using this longitudinal DWI approach performed on the MRIgRT system for predicting the response of sarcoma patient to preop RT. Methods: Three sarcoma patients who underwent fractionated IMRT were recruited in this study. For all three patients DWI images were acquired immediately following his/her treatment. For each imaging session, ten slices were acquired interleaved with the b values covering the gross tumor volume (GTV). The diffusion images were processed to obtain the ADC maps using standard exponential fitting for each voxel. Regions of interest were drawn in the tumor on the diffusion images based on each patient’s clinical GTV contours. Each patient subsequently underwent surgery and the tumor necrosis score was available from standard pathology. The ADC values for each patient were compared to the necrosis scores to assess the predictive value of our longitudinal DWI for tumor response. Results: Each patient underwent 3 to 5 diffusion MRI scans depending on their treatment length. Patient 1 had a relatively unchanged ADC during the course of RT and a necrosis score of 30% at surgery. For patient 2, the mean ADC values decreased from 1.56 × 10-3 to 1.12 × 10-3 mm2/s and the patient’s necrosis score was less than 10%. Patient 3 had a slight increase in the ADC values from 0.59 × 10-3 to 0.71 × 10-3 mm2/s and patient’s necrosis score was 50%. Conclusion: Based on limited data from 3 patients, our longitudinal changes in tumor ADC assessed using the MRIgRT system correlated well with pathology results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Kinetic Monte Carlo Simulations of Chemical Reactions on Surfaces

Lattice based kinetic Monte Carlo (kMC) simulations are a powerful tool for micro-kinetic modeling. The kinetic Monte Carlo technique stochastically simulates chemical reaction processes (e.g. adsorption, desorption, diffusion), where the probability of a given reaction process being selected is weighted by its rate constant. The open source software package, KMOS1, allows fast construction of kMC simulations by automatically implementing a computationally efficient kMC framework, thus allowing the researcher to focus on accurate parameterization and formulation of the kinetic model. From this, the spatiotemporal evolution (e.g. concentration, surface configuration, turnover frequencies) of crystal surfaces or bulk crystalline structures is obtained. KMOS uses the variable step-size method implementation of kMC. At each step, the VSSM updates available events, calculates the corresponding transition rates and simulation time, and selects one of the available events. The lattice based kMC technique has many potential applications within SRNL where chemical kinetics are of interest. By transitioning through time along a trajectory of configuration space, fundamental insights to a system's dominant reactions and parameters can be gained, leading to improved materials and process design. In this work, we have established capabilities for fast implementation of kMC simulations through the installation and testing of the KMOS software on SRNL high performance computing resources. The parameterization of kMC simulations is often performed from first-principles energetic calculations. For the purposes of this work, the test cases use arbitrary species and thus, have arbitrary parameterization. In order to demonstrate the use of KMOS, two primary test cases are shown. Case 1 involves simple adsorption and desorption. Case 2 involves a slightly more complex mechanism. The evolution of the surface concentration and the final surface configuration for simulation Case 2 is shown. Rate-limiting processes and rate-limiting configurations are not always known or understood, but kMC provides information pertaining to both. The capability to implement efficient micro-kinetic models using the kinetic Monte Carlo technique has been established through the testing and installation of KMOS on SRNL HPC resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Unveiling the Role of Critical Impurities in Spent LiFePO 4 Cathodes for Scalable Direct Regeneration

Direct regeneration offers a promising alternative to recycling End-of-Life (EoL) batteries by restoring metal elements and preserving the material structure, yet scaling these technologies to handle practical cathode black mass (CBM) with impurities remains challenging. Here, this study investigates the evolution of impurities, including aluminum (Al), polyvinylidene difluoride (PVDF) binder, and residual carbon (C), during direct recycling of spent LiFePO 4 (LFP) cathodes and their impact on electrochemical performance. Using various ex situ and in situ analyses, it is shown that the formation of lithium fluoride (LiF) during the traditional direct recycling process hinders lithium diffusion and deteriorates the reversible capacity. To address this major challenge, the combination of pH-controlled hydrothermal purification and the two-step sintering process is proposed effectively to regenerate spent LFP cathodes, eliminating the negative effect of Al and fluorine (F) impurities while mitigating any potential impacts of carbon residuals. The regenerated LFP from spent CBM achieves superior performance, retaining 152.5 mAh g −1 at 0.1 C and 133 mAh g −1 at 1 C with 98.7% capacity retention after 200 cycles. This approach is further validated using three distinct waste feedstocks from battery modules, enhancing impurity management and scalability in direct recycling. These findings present a sustainable and economically viable solution for large-scale LFP regeneration.

25 ENERGY STORAGE↗
DOE OSTI2019

Unsupervised machine learning based on non-negative tensor factorization for analyzing reactive-mixing

Analysis of reactive-diffusion simulations representing complex mixing processes requires a large number of independent model runs. For each high-fidelity model simulation, the model inputs are varied and the predicted mixing behavior is represented by temporal and spatial changes in species concentration. It is then required to discern how the model inputs (such as diffusivity, dispersion, anisotropy, and velocity field properties) impact the mixing process. This task is challenging and typically involves interpretation of large model outputs representing temporal and spatial changes of species concentration within the model domain. Yet, the task can be automated and substantially simplified by applying Machine Learning (ML) methods. Here, we present an application of an unsupervised ML method (called NTF k ) using Non-negative Tensor Factorization (NTF) coupled with a custom clustering procedure based on k-means to reveal the temporal and spatial features in product concentrations. An attractive and unique aspect of the proposed ML method is that it ensures the extracted features are non-negative, which is important to obtain a meaningful deconstruction of the mixing processes. The ML methodology is applied to a large set of high-resolution finite-element model simulations representing anisotropic reaction-diffusion processes in perturbed vortex-based velocity fields. The applied finite-element method ensures that spatial and temporal species concentration are always non-negative, even in the case of high anisotropic contrasts. The simulated reaction is a fast irreversible bimolecular reaction A+B→C , where species A and B react to form species C. The reactive-diffusion model input parameters that control mixing include properties of the velocity field (such as vortex structures), anisotropic dispersion, and molecular diffusion. We demonstrate the applicability of the ML feature extraction method to produce a meaningful deconstruction of model outputs to discriminate between different physical processes impacting the reactants, their mixing, and the spatial distribution of the product C. The introduced ML analysis allowed us to identify additive temporal and spatial features that characterize mixing behavior. The application of the proposed NTF k approach is not limited to reactive-mixing. NTFk can be readily applied to any observed or simulated datasets that can be represented as tensors (multi-dimensional arrays) and have separable latent signatures or features.

97 MATHEMATICS AND COMPUTING↗