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At least 595 records · Page 33

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↗

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↗

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↗

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↗

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↗

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↗

DECOVALEX-2023: Task F2 Salt Final Report

The subject of Task F of DECOVALEX-2023 concerns performance assessment modelling of radioactive waste disposal in deep mined repositories. The primary objectives of Task F are to build confidence in the models, methods, and software used for performance assessment (PA) of deep geologic nuclear waste repositories, and/or to bring to the fore additional research and development needed to improve PA methodologies. In Task F2- (salt), these objectives have been accomplished through staged development and comparison of the models and methods used by participating teams in their PA frameworks. Coupled-process submodels and deterministic simulations of the entire PA model for a reference scenario for waste disposal in domal salt have been conducted. The task specification has been updated continuously since the initiation of the project to reflect the staged development of the conceptual repository model and performance metrics. Thermal, hydrological, mechanical, and chemical properties of individual components of the engineered and natural system were chosen for relevance by participating teams. The salt reference case system was characterized using data and measurements collected at relevant underground research laboratories (URLs), field sites, and simulation results from teams with specialized modelling capability. Participating teams made a wide range of model assumptions from compartmentalized networks to full 3D models of the salt formation. No single contributed model includes full-fidelity representation of all the features, events, and processes (FEPs) detailed in the task specification, but almost all features and processes are represented in at least one model. Despite differences in the modelling strategies developed by participating teams, all models indicate that salt compaction and radionuclide diffusion are key processes in the repository, and for the FEPs and model scenario considered, little of the disposed radionuclides will migrate beyond the repository seal over the 100,000 year simulations. In general, the model output quantities have the largest differences over the short term and near the waste. The models tend to be more similar further from waste and at later time. Disparities between the models are believed to be due to differing simplifications from the task specification, some of which are chosen simplifications to reduce complexity, and some are restrictions imposed by the modelling tools. A second round of this task has been accepted for DECOVALEX-2027 in conjunction with Task F1 on crystalline PA modelling. The future round includes waste package heating, improved modelling of salt creep closure, additional comparisons of coupled-process sub-models, and the impact of repository engineering design on radionuclide migration in the repository. Participants will also propose and finalize a set of uncertain inputs for the reference case simulations, propagate these uncertainties in a set of realizations, and conduct sensitivity analyses on the simulation results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Evaluation of subsurface transport processes of delayed gas signatures applicable to underground nuclear explosions

Radioactive gas signatures from underground nuclear explosions (UNEs) result from gas-migration processes occurring in the subsurface. The processes considered in this study either drive or retard upward migration of gases from the detonation cavity. The relative importance of these processes is evaluated by simulating subsurface transport in a dual-permeability medium for the multi-tracer Noble Gas Migration Experiment (NGME) originally intended to study some aspects of transport from a UNE. For this experiment, relevant driving processes include weak two-phase convection driven by the geothermal gradient, over pressuring of the detonation cavity, and barometric pumping while gas sorption, dissolution, radioactive decay, and usually diffusion represent retarding processes. From deterministic simulations we found that over-pressuring of the post-detonation chimney coupled with barometric pumping produced a synergistic effect amplifying the tracer-gas reaching the surface. Bounding simulations indicated that the sorption and dissolution of gases, tending to retard transport, were much smaller than anticipated by earlier laboratory studies. The NGME observations themselves show that differences in gas diffusivity have a larger effect on influencing upward transport than do the combined effects of tracer-gas sorption and dissolution, which is consistent with a Sobol’ sensitivity analysis. Both deterministic simulations and those considering parametric uncertainties of transport-related properties predict that the excess in concentration of SF 6 compared to 127 Xe as might be captured in small volumetric samples should be much smaller than the order-of-magnitude contrast found in the large-volume gas samples taken at the site. While extraction of large-volume subsurface gas samples is shown to be capable of distorting in situ gas compositions, the highly variable injection rate of SF 6 into the detonation cavity relative to that of 127 Xe at the start of the field experiment is the most likely explanation for the large difference in observed concentrations.

58 GEOSCIENCES↗

Direct molecular diffusion and micro-mixing for rapid dewatering of LiBr solution

A slow molecular diffusion rate often limits the desorption process of an absorbate molecule from a liquid absorbent. To enhance the desorption rate, the absorbent is often boiled to increase the liquid vapor interfacial area. However, the growth of bubbles generated during the nucleate boiling process still remains mass-diffusion limited. Here, it is shown that a desorption rate higher than that of boiling can be achieved, if the vapor absorbent interface is continuously replenished with the absorbate-rich solution to limit the concentration boundary layer growth. The study is conducted in a LiBr-water-solution, in which the water molecules' diffusion rate is quite slow. The manipulation of the vapor solution interface concentration distribution is enabled by the mechanical confinement of the solution flow within microchannels, using a hydrophobic vapor-venting membrane and the implementation of microstructures on the flow channel's bottom wall. The microstructures stretch and fold the laminar streamlines within the solution film and produce vortices. The vortices continuously replace the concentrated solution at the vapor solution interface with the water-rich solution brought from the bottom and middle of the flow channel. The physics of the process is described using a combination of experimental and numerical studies. Published by Elsevier Ltd.

Bigham, S↗

Mathematical Modeling of Decarburization in Levitated Fe-Cr-C Droplets

Using carbon dioxide to replace oxygen as an alternative oxidant gas has proven to be a viable solution in the decarburization process, with potential for industrial applications. In a recent study, the transport phenomena governing the carbon dioxide decarburization process through the use of electromagnetic levitation (EML) was examined. CO{sub 2}/CO mass transfer was found to be the principal reaction rate control step, as a result gas diffusion has gained significant attention. In the present study, gas diffusion during decarburization process was investigated using computational fluid dynamics (CFD) modeling coupled with chemical reactions. The resulting model was verified through experimental data in a published paper, and employed to provide insights on phenomena typically unobservable through experiments. Based on the results, a new correction of the Frössling equation was presented which better represents the mass transfer phenomena at the metal-gas interface within the range of this research.

36 MATERIALS SCIENCE↗

A transformed path integral approach for solution of the Fokker–Planck equation

A novel path integral (PI) based method for solution of the Fokker–Planck equation is presented. The proposed method, termed the transformed path integral (TPI) method, utilizes a new formulation for the underlying short-time propagator to perform the evolution of the probability density function (PDF) in a transformed computational domain where a more accurate representation of the PDF can be ensured. The new formulation, based on a dynamic transformation of the original state space with the statistics of the PDF as parameters, preserves the non-negativity of the PDF and incorporates short-time properties of the underlying stochastic process. New update equations for the state PDF in a transformed space and the parameters of the transformation (including mean and covariance) that better accommodate nonlinearities in drift and non-Gaussian behavior in distributions are proposed (based on properties of the SDE). Owing to the choice of transformation considered, the proposed method maps a fixed grid in transformed space to a dynamically adaptive grid in the original state space. The TPI method, in contrast to conventional methods such as Monte Carlo simulations and fixed grid approaches, is able to better represent the distributions (especially the tail information) and better address challenges in processes with large diffusion, large drift and large concentration of PDF. Additionally, in the proposed TPI method, error bounds on the probability in the computational domain can be obtained using the Chebyshev's inequality. The benefits of the TPI method over conventional methods are illustrated through simulations of linear and nonlinear drift processes in one-dimensional and multidimensional state spaces. The effects of spatial and temporal grid resolutions as well as that of the diffusion coefficient on the error in the PDF are also characterized.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Identification of Species from Visible and Near-Infrared Spectral Emission of a Nitromethane-Air Diffusion Flame

The combustion processes of nitromethane, an explosive used in many combustion applications, are not fully captured in current state-of-the-art nitromethane kinetic schemes. There is a need for data on transient species to further improve understanding of nitromethane chemistry and dynamics. This work aims to identify transient species present during nitromethane-air combustion through characterization of the spectral emission of a flame stabilized on an aluminum oxide wick at atmospheric pressure. Assignments were made using a spectral library assembled from prior literature and through comparison with spectra taken in two additional air-diffusion flames, CD 3 NO 2 and CH 3 OH. Several new emitters were detected in excited electronic states: HNO*(A’), CN* (A 2 Σ), NO 2 *, and in ground electronic states: CH, OH, NH, and H 2 O. The previously observed reaction species CH*(A 2 Δ) was also observed, while formaldehyde and the characteristic C 2 *(A 3 Π g ) Swan bands were not.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of Species from Visible and Near-Infrared Spectral Emission of a Nitromethane-Air Diffusion Flame

The combustion processes of nitromethane, an explosive used in many combustion applications, are not fully captured in current state-of-the-art nitromethane kinetic schemes. There is a need for data on transient species to further improve understanding of nitromethane chemistry and dynamics. This work aims to identify transient species present during nitromethane-air combustion through characterization of the spectral emission of a flame stabilized on an aluminum oxide wick at atmospheric pressure. Assignments were made using a spectral library assembled from prior literature and through comparison with spectra taken in two additional air-diffusion flames, CD 3 NO 2 and CH 3 OH. Several new emitters were detected in excited electronic states: HNO*(A’), CN* (A 2 Σ), NO 2 *, and in ground electronic states: CH, OH, NH, and H 2 O. The previously observed reaction species CH*(A 2 Δ) was also observed, while formaldehyde and the characteristic C 2 *(A 3 Π g ) swan bands were not.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A study on atomic diffusion behaviours in an Al-Mg compound casting process

Al and Mg alloys are main lightweight alloys of research interest and they both have superb material properties, i.e., low density and high specific strength, etc. Being different from Al alloys, the corrosion of Mg alloys is much more difficult to control. Therefore to combine merits of these two lightweight alloys as a composite-like structure is an ideal solution through using Al alloys as a protective layer for Mg alloys. Compound casting is a realistic technique to manufacture such a bi-metal structure. In this study, a compound casting technique is employed to fabricate bi-layered samples using Al and Mg and then the samples are analysed using electron probe micro-analyzer (EPMA) to determine diffusion behaviours between Al and Mg. The diffusion mechanism and behaviours between Al and Mg are studied numerically at atomic scale using molecular dynamics (MD) and parametric studies are conducted to find out influences of ambient temperature and pressure on the diffusion behaviours between Al and Mg. The results obtained clearly show the effectiveness of the compound casting process to increase the diffusion between Al and Mg and thus create the Al-base protection layer for Mg.

36 MATERIALS SCIENCE↗

Dynamics of molecular associates in methanol/water mixtures

The dynamics of molecular associates in a methanol/water mixture was investigated using quasielastic neutron scattering. By measuring the signal from four methanol/water samples differing only by their isotopic composition, the relative motion of the water to methanol molecules, i.e. their mutual dynamics, was determined at the nanoscale. The thus obtained nanoscopic mutual diffusion coefficient signals a significantly slower process than the single particle diffusion of either methanol or water in the system as well as their macroscopic mutual diffusion. The data do not provide any indication of microsegregation in this preeminent alcohol/water mixture; however, they do indicate the existence of long lived but dynamic molecular associates of water and methanol molecules. Our analysis of the structural relaxation shows that the lifetime of molecular association through hydrogen bonding determines the fact that viscosity of the mixtures at intermediate concentrations is higher than that of both pure components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aggregation-fragmentation-diffusion model for trail dynamics

We investigate statistical properties of trails formed by a random process incorporating aggregation, fragmentation, and diffusion. In this stochastic process, which takes place in one spatial dimension, two neighboring trails may combine to form a larger one, and also one trail may split into two. In addition, trails move diffusively. The model is defined by two parameters which quantify the fragmentation rate and the fragment size. In the long-time limit, the system reaches a steady state, and our focus is the limiting distribution of trail weights. We find that the density of trail weight has power-law tail P(w)~w –γ for small weight w. We obtain the exponent γ analytically and find that it varies continuously with the two model parameters. In conclusion, the exponent γ can be positive or negative, so that in one range of parameters small-weight trails are abundant and in the complementary range they are rare.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Guideline to Mitigate Interfacial Degradation Processes in Solid‐State Batteries Caused by Cross Diffusion

Abstract Diffusion of transition metals across the cathode–electrolyte interface is identified as a key challenge for the practical realization of solid‐state batteries. This is related to the formation of highly resistive interphases impeding the charge transport across the materials. Herein, the hypothesis that formation of interphases is associated with the incorporation of Co into the Li 7 La 3 Zr 2 O 12 lattice representing the starting point of a cascade of degradation processes is investigated. It is shown that Co incorporates into the garnet structure preferably four‐fold coordinated as Co 2+ or Co 3+ depending on oxygen fugacity. The solubility limit of Co is determined to be around 0.16 per formula unit, whereby concentrations beyond this limit causes a cubic‐to‐tetragonal phase transition. Moreover, the temperature‐dependent Co diffusion coefficient is determined, for example, D 700 °C = 9.46 × 10 −14 cm 2 s −1 and an activation energy E a = 1.65 eV, suggesting that detrimental cross diffusion will take place at any relevant process condition. Additionally, the optimal protective Al 2 O 3 coating thickness for relevant temperatures is studied, which allows to create a process diagram to mitigate any degradation with a minimum compromise on electrochemical performance. This study provides a tool to optimize processing conditions toward developing high energy density solid‐state batteries.

Chemistry↗

Impact of Photon Recycling, Grain Boundaries, and Nonlinear Recombination on Energy Transport in Semiconductors

Energy carrier transport and recombination in semiconductors can be directly monitored with optical microscopy, revealing key insights into fundamental photophysics and informs efficient optoelectronic device design. Oftentimes, energy transport is measured by monitoring a time-resolved expanding carrier profile after optical excitation under a focused laser beam. Although this approach has gained widespread adoption, the presence of competing dynamic processes, such as diffusion and photon recycling, has made it difficult to accurately extract and understand important semiconductor properties. Here, we develop and apply a new framework for modeling energy transport in both excitonic and free carrier semiconductors. Here, we demonstrate that processes such as nonlinear recombination and photon recycling can have a significant impact on the apparent energy carrier profiles, especially for excitonic materials with short radiative lifetimes. Additionally, we find that film microstructure can lead to unique transport profiles that strongly depends on material boundary behavior and the difference between feature size and diffusion length. Here, these findings provide a deeper understanding of energy transport in semiconducting materials and provide new strategies for the design and optimization of electronic and optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗