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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
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 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 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↗
DOE OSTI2024

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↗
DOE OSTI2022

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↗
DOE OSTI2018

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↗
DOE OSTI2017

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↗
DOE OSTI2019

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↗
DOE OSTI2019

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↗
DOE OSTI2021

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↗