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Results for “thermodynamics of computing”

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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

In situ synchrotron X-ray imaging and mechanical properties characterization of additively manufactured high-entropy alloy composites

Laser beam directed energy deposition has become an increasingly popular advanced manufacturing technique for materials discovery as a result of the in situ alloying capability. In this study, we leverage an additive manufacturing enabled high throughput materials discovery approach to explore the composition space of a graded W x (CoCrFeMnNi) 100–x sample spanning 0 ≤ x ≤ 21 at%. In addition to microstructural and mechanical characterization, synchrotron high speed x-ray computer aided tomography was conducted on a W 20 (CoCrFeMnNi) 80 composition to visualize melting dynamics, powder-laser interactions, and remelting effects of previously consolidated material. Results reveal the formation of the Fe 7 W 6 intermetallic phase at W concentrations> 6 at%, despite the high configurational entropy. Unincorporated W particles also occurred at W concentrations> 10 at% accompanied by a dissolution band of Fe 7 W 6 at the W/matrix interface and hardness values greater than 400 HV. In this work, the primary strengthening mechanism is attributed to the reinforcement of the Fe 7 W 6 and W phases as a metal matrix composite. The in situ high speed x-ray imaging during remelting showed that an additional laser pass did not promote further mixing of the Fe 7 W 6 or W phases suggesting that, despite the dissolution of the W into the Fe 7 W 6 phase being thermodynamically favored, it is kinetically limited by the thickness/diffusivity of the intermetallic phase, and the rapid solidification of the laser-based process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Computational analysis of metal–metal bonded dimetal tetrabenzoate redox potentials in the context of ammonia oxidation electrocatalysis

Metal–metal bonded complexes are promising candidates for catalyzing redox transformations. Of particular interest is the oxidation of ammonia to dinitrogen, an important half reaction for the potential utilization of ammonia as a fuel or hydrogen carrier. This work computationally explores 30 different metal–metal bonded dimers (5 different metal centers and 6 different benzoate ligand derivatives) to explore the tunability of the redox potential when ammonia is bound to the complexes as an axial ligand, modeling the first step in ammonia oxidation electrocatalysis. We calculate the redox potentials of these compounds, making reference to experimental data when appropriate, identifying two degrees of tunability: a coarse adjustment, changing the metal center, allows for a wide range of redox potentials to be accessed (from +1.0 to –2.0 V vs. ferrocene/ferrocenium in acetonitrile solution) and a fine adjustment, the para-substituent of the benzoate derivative, which affects the redox potential in a smaller range based on the electron donating/withdrawing effects of the substituent. Ruthenium and osmium tetrabenzoate catalysts are prime candidates for next generation ammonia oxidation catalysts because their redox potentials fall within the direct ammonia fuel cell “viability zone” bracketed by the thermodynamic potentials of oxygen reduction (ORR) and nitrogen reduction (NRR). Rhodium tetrabenzoate species fall above the ORR potential, suggesting ammonia oxidation promoted by Rh 2 catalysts could instead be used to facilitate hydrogen production through coupling to hydrogen evolution at a cathode. The redox potentials of rhenium and iridium tetrabenzoate catalysts fall below the NRR potential suggesting that these compounds could be further investigated in the context of electrochemical ammonia synthesis. Each redox event studied involves electron transfer from the M–M δ* orbital regardless of choice of metal or benzoate ligand derivative; this leads us to believe that the chemical reactivity of the various studied compounds will be similar in the context of ammonia oxidation.

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

The concept of spin ice graphs and a field theory for their charges

Originally detected in rare earth pyrochlores, spin ice physics is now being artificially extended to a variety of geometries that control collective behavior and exotic properties, making graph theory their proper framework. We relate spin ice notions, such as ice rule, ice manifold, Coulomb phases, charges, and monopoles, to graph-theoretical notions, such as balance, in/out-degrees, and Euler paths. We then propose a field-theoretical treatment in which topological charges and monopoles are the degrees of freedom, while the binary spins are subsumed in an entropic interaction among charges. We show that for a spin ice on a graph in a Gaussian approximation, the kernel of the entropic interaction is the inverse of the graph Laplacian, and we compute screening functions from the graph spectra as Green operators for the screened Poisson problem on a graph. We then apply the treatment to star graphs, tournaments, cycles, and regular spin ice in different dimensions. Our aim is twofold: to set spin ice physics in a proper graph setting, where only topological rather than geometrical notions hold, and to invite graph theorists to contribute their powerful tools to the field of spin ice.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Simple Approximation for the Ideal Reference State of Gases Adsorbed on Solid-State Surfaces

Reference states are useful as models for facilitating calculations of equilibrium constants, and they may also serve as standard states that are convenient for organizing and tabulating thermodynamic data; however, standard state conventions and appropriate reference states for adsorbed species have received less attention than those for pure substances and solutes. Here, we compare seven choices of reference states for calculations of equilibrium constants and transition state theory rate constants for flat surfaces, in particular (1) an ideal 2D harmonic oscillator, (2) an ideal rigid-molecule harmonic oscillator, (3) an ideal 2D harmonic oscillator with separable surface modes, (4) a 2D ideal gas, (5) an ideal 2D hindered translator, (6) an ideal 2D hindered translator with lowest-order barriers, and (7) a simple ideal 2D hindered translator proposed in this work. The advantage of models 5–7 is that they can treat both mobile and localized adsorbates in a consistent way, whereas models 1–3 are only appropriate for localized adsorbates, and model 4 is only appropriate for a freely translating adsorbate. Furthermore, models 6 and 7 reduce the computational cost without the user having to calculate barrier heights for diffusion. An advantage of the simple ideal 2D hindered translator is that it has a physical high-temperature limit. We also propose a reference state for nonflat surfaces. Here, the user is encouraged to choose a reference state based on the appropriateness of the model and the practicality of the calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

AN AUTOMATED MACHINE LEARNING-GENETIC ALGORITHM FRAMEWORK WITH ACTIVE LEARNING FOR DESIGN OPTIMIZATION

The use of machine learning (ML)-based surrogate models is a promising technique to significantly accelerate simulation-driven design optimization of internal combustion (IC) engines, due to the high computational cost of running computational fluid dynamics (CFD) simulations. However, training the ML models requires hyperparameter selection, which is often done using trial-and-error and domain expertise. Another challenge is that the data required to train these models are often unknown a priori. In this work, we present an automated hyperparameter selection technique coupled with an active learning approach to address these challenges. The technique presented in this study involves the use of a Bayesian approach to optimize the hyperparameters of the base learners that make up a super learner model. In addition to performing hyperparameter optimization (HPO), an active learning approach is employed, where the process of data generation using simulations, ML training, and surrogate optimization is performed repeatedly to refine the solution in the vicinity of the predicted optimum. The proposed approach is applied to the optimization of a compression ignition engine with control parameters relating to fuel injection, in-cylinder flow, and thermodynamic conditions. It is demonstrated that by automatically selecting the best values of the hyperparameters, a 1.6% improvement in merit value is obtained, compared to an improvement of 1.0% with default hyperparameters. Overall, the framework introduced in this study reduces the need for technical expertise in training ML models for optimization while also reducing the number of simulations needed for performing surrogate-based design optimization.

Owoyele, Opeoluwa↗
DOE OSTI2020

Efficient computational search for lanthanide-binding additive dopants for advanced U-Zr based fuels

A rational design strategy combining theory and experiment is highly desirable for the development of U-Zr based fuels that are resistant to lanthanide-induced fuel-cladding chemical interaction (FCCI). Here, we performed rapid computational screening of FCCI-mitigating (via strong lanthanide-binding) elements across the periodic table by utilizing three simple criteria and density functional theory (DFT) calculated total energies of relevant elements and compounds retrieved from high-throughput DFT databases. In addition to successfully identifying previously demonstrated additives, our search leads to the discovery of Bi as a highly effective element among all 68 elements screened, and its effectiveness was experimentally confirmed in this study.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Uncertainty propagation in pore water chemical composition calculation using surrogate models

Performance assessment in deep geological nuclear waste repository systems necessitates an extended knowledge of the pore water chemical conditions prevailing in host-rock formations. In the last two decades, important progress has been made in the experimental characterization and thermodynamic modeling of pore water speciation, but the influence of experimental artifacts and uncertainties of thermodynamic input parameters are seldom evaluated. In this respect, we conducted an uncertainty propagation study in a reference geochemical model describing the pore water chemistry of the Callovian-Oxfordian clay formation. Nineteen model input parameters were perturbed, including those associated to experimental characterization (leached anions, exchanged cations, cation exchange selectivity coefficients) and those associated to generic thermodynamic databases (solubilities). A set of 13 quantities of interest were studied by the use of polynomial chaos expansions built non-intrusively with a least-squares forward stepwise regression approach. Training and validation sets of simulations were carried out using the geochemical speciation code PHREEQC. The statistical results explored the marginal distribution of each quantity of interest, their bivariate correlations as well as their global sensitivity indices. The influence of the assumed distributions for input parameters uncertainties was evaluated by considering two parametric domain sizes.

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

Electron-impact ionization from excited states method

We present a distorted-wave with exchange (DWE) formulation for computing electron-impact ionization (EII) cross sections within the recently developed excited states method (ESM) for plasmas. The ESM provides a self-consistent quantum-mechanical description of both bound and continuum electronic states in dense plasmas, incorporating finite-temperature and screening effects absent in isolated-atom approaches. Using this framework, we calculate EII cross sections for lithium across a wide range of temperatures and densities. We show that the ESM reproduces the isolated-atom limit at low densities while capturing strong plasma effects, such as pressure ionization and shape resonances, at solid density. Comparisons with isolated-atom DWE and average-atom (AA) calculations reveal that, although AA cross sections can approximate configuration average behavior, the ESM provides more accurate, state-resolved answers. In conclusion, these results demonstrate that the ESM allows one to obtain rate coefficients for collisional-radiative modeling of plasmas out of local thermodynamical equilibrium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Modeling Absolute Redox Potentials of Ferrocene in the Condensed Phase

Absolute thermodynamic quantities for critical chemical reactions are needed to determine the role of solvents and reactive environments in catalysis and electrocatalysis beyond the relative scales typically employed. In principle, theoretical methods can provide such quantification but are often hindered by the innate complexity of strong electron correlation and dynamic relaxation of solvent environments. Here, we present and validate a protocol for calculating the redox potentials of ferrocene/ferrocenium redox pair in the acetonitrile. Equation-of-motion ionization potential coupled-cluster single-double (EOM-IP-CCSD) and effective fragment potential (EFP) methods are used to characterize the adiabatic and vertical ionization potentials (IP) as well as the electron affinity processes. We benchmark molecular mechanics against the EFP model to show the differences in ferrocene electronic polarizability in two redox states. Our best estimate of the redox potential (4.94 eV) agrees well with the experimental value (4.93 eV). This demonstrated the ability of modern computational methods to predict absolute redox potentials quantitatively and, more critically, quantify the correlation of dynamic effects, which underlie their origin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Electrochemically Determined and Structurally Justified Thermochemistry of H atom Transfer on Ti-Oxo Nodes of the Colloidal Metal–Organic Framework Ti-MIL-125

Titanium dioxide (TiO 2 ) has long been employed as (photo)electrodes for reactions relevant to energy storage and renewable energy synthesis. Proton-coupled electron transfer (PCET) reactions with equimolar amounts of protons and electrons at the TiO 2 surface or within the bulk structure lie at the center of these reactions. Because a proton and an electron are thermochemically equivalent to an H-atom, these reactions are essentially H-atom transfer reactions. Thermodynamics of H-atom transfer has a complex dependence on the synthetic protocol and chemical history of the electrode, the reaction medium, and many others; together, these complications preclude the understanding of the H-atom transfer thermochemistry with atomic-level structural knowledge. Herein, we report our success in employing open-circuit potential (E OCP ) measurements to quantitatively determine the H-atom transfer thermochemistry at structurally well-defined Ti-oxo clusters within a colloidally stabilized metal–organic framework (MOFs), Ti-MIL-125. The free energy to transfer H-atom, Ti 3+ O–H bond dissociation free energy (BDFE), was measured to be 68(2) kcal mol -1 . To the best of our understanding, this is the first report on using E OCP measurements to quantify thermochemistry on any MOFs. The proton topology, the structural change upon the redox reaction, and BDFE values were further quantitatively corroborated using computational simulations. Furthermore, comparisons of the E OCP -derived BDFEs of Ti-MIL-125 to similar parameters in the literature suggest that E OCP should be the preferred method for quantitatively accurate BDFE calculations. Here, the reported success in employing E OCP for nanosized Ti- MIL-125 should lay the ground for thermochemical measurements of other colloidal systems, which are otherwise challenging. Implications of these measurements on Ti-MIL-125 as an H-atom acceptor in chemical reactions and comparisons with other MOFs/metal oxides are discussed.

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

Evaporation Sub-model Development for Volume of Fluid (eVOF) Method Applicable to Spray-Wall Interaction Including Film Characteristics with Validation at High Pressure and Temperature Conditions (Final Report)

Internal combustion engines have seen a great evolution over the last several decades through application of high pressure direct injection, multiple injections, and other technologies to reduced fuel consumption, NOx, and PM. Although combustion systems with advanced injection strategies have been studied extensively, there exists a significant fundamental knowledge gap on the fuel-spray interactions with the piston surface and chamber walls. Advanced computational codes validated with experimental techniques have to be developed for accurate representation of the drop impingement, fuel film formation, and vaporization. Current engine CFD spray models utilize a Lagrangian framework for modeling which lacks critical considerations of the physics pertaining to these interactions and thus requiring extensive parameterization, tuning and validation. The team from Michigan Technological University, University of Massachusetts Dartmouth, and Argonne National Laboratory is composed of experts in sprays, combustion, engines and CFD with a wide spectrum of knowledge including specific expertise in the area under consideration. In the proposed work, a VOF modeling approach has been adopted for the spray-wall interaction, film formation and spreading, and vaporization. With the inclusion of a vaporization submodel, a more predictive and accurate simulation of the spray-film was performed without extensive need of parameterization and tuning. Extensive experimentation of the spray-wall interaction under the range of conditions matching the thermodynamic and surface temperatures that occur in diesel and gasoline engines were conducted to validate the SWI submodels and for development of the evaporation sub-model, which has been implemented in the Converge software.

42 ENGINEERING↗
DOE OSTI2023

An integrated statistical-thermodynamic model for fission gas release and swelling in nuclear fuels

Here, we propose a new model for burst fission gas release induced by microcracking in ceramic nuclear fuels such as uranium dioxide. The model stipulates that the densities of defects in the fuel material, such as microcracks and fission gas bubbles on grain boundaries, evolve in accordance with the second law of thermodynamics. Central to the model is the notion of an effective temperature, conjugate to the configurational entropy of the fuel material, and directly linked to the burnup. The model predicts that microcracking, driven by the internal stress state of the fuel material, reduces the bubble storage capacity of grain boundaries, and accounts for burst fission gas release during rapid temperature transients that simulate power transients, reactor startup, and loss-of-coolant accident conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Ion correlations explain kinetic selectivity in diffusion-limited solid-state synthesis reactions

Establishing viable solid-state synthesis pathways for novel inorganic materials remains a major challenge in materials science. Previous pathway design methods using pairwise reaction approaches have navigated the thermodynamic landscape with first-principles data but lack kinetic information, limiting their effectiveness. This gap leads to suboptimal precursor selection and predictions, especially for reactions forming competing phases with similar formation energies, where ion diffusion is a critical influence. Here we demonstrate an inorganic synthesis framework by incorporating machine learning-derived transport properties through ‘liquid-like’ product layers into a thermodynamic cellular reaction model. In the Ba–Ti–O system, known for its competitive polymorphism, we obtain accurate predictions of phase formation with varying BaO:TiO2 ratios as a function of time and temperature. We find that diffusion–thermodynamics interplay governs phase compositions, with cross-ion transport coefficients critical for predicting diffusion-limited selectivity. This work bridges length scales and timescales by integrating solid-state reaction kinetics with first-principles thermodynamics and spatial reactivity.

Atomistic models↗
DOE OSTI2023

The dynamics, mixing, and thermonuclear burn of compressed foams with varied gas fills

Inertial confinement fusion (ICF) implosions involve highly coupled physics and complex hydrodynamics that are challenging to model computationally. Due to the sensitivity of such implosions to small features, detailed simulations require accurate accounting of the geometry and dimensionality of the initial conditions, including capsule defects and engineering features such as fill tubes used to insert gas into the capsule, yet this is computationally prohibitive. It is therefore difficult to evaluate whether discrepancies between the simulation and experiment arise from inadequate fidelity to the capsule geometry and drive conditions, uncertainties in physical data used by simulations, or inadequate physics. We present results from detailed high-resolution three-dimensional simulations of ICF implosions performed as part of the MARBLE campaign on the National Ignition Facility [Albright et al., Phys. Plasmas 29, 022702 (2022)]. These experiments are foam-filled separated-reactant experiments, where deuterons reside in the foam and tritons reside in the capsule gas fill and deuterium–tritium (DT) fusion reactions only occur in the presence of mixing between these materials. Material mixing in these experiments is primarily seeded by shock interaction with the complex geometry of the foam and gas fill, which induces the Richtmyer–Meshkov instability. We compare results for experiments with two different gas fills (ArT and HT), which lead to significant differences in the hydrodynamic and thermodynamic developments of the materials in the implosion. Our simulation results show generally good agreement with experiments and demonstrate a substantial impact of hydrodynamic flows on measured ion temperatures. The results suggest that viscosity, which was not included in our simulations, is the most important unmodeled physics and qualitatively explains the few discrepancies between the simulation and experiment. The results also suggest that the hydrodynamic treatment of shocks is inadequate to predict the heating and yield produced during shock flash, when the shock converges at the center of the implosion. Alternatively, underestimation of the level of radiative preheat from the shock front could explain many of the differences between the experiment and simulation. Nevertheless, simulations are able to reproduce many experimental observables within the level of experimental reproducibility, including most yields, time-resolved X-ray self-emission images, and an increase in burn-weighted ion temperature and neutron down-scattered ratio in the line of sight that includes a jet seeded by the glue spot that joins capsule hemispheres.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Multiscale Modeling of Nanoparticle Precipitation in Oxide Dispersion-Strengthened Steels Produced by Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) enables the efficient production of near-net-shape oxide dispersion-strengthened (ODS) alloys, which possess superior mechanical properties due to oxide nanoparticles (e.g., yttrium oxide, Y-O, and yttrium-titanium oxide, Y-Ti-O) embedded in the alloy matrix. To better understand the precipitation mechanisms of the oxide nanoparticles and predict their size distribution under LPBF conditions, we developed an innovative physics-based multiscale modeling strategy that incorporates multiple computational approaches. These include a finite volume method model (Flow3D) to analyze the temperature field and cooling rate of the melt pool during the LPBF process, a density functional theory model to calculate the binding energy of Y-O particles and the temperature-dependent diffusivities of Y and O in molten 316L stainless steel (SS), and a cluster dynamics model to evaluate the kinetic evolution and size distribution of Y-O nanoparticles in as-fabricated 316L SS ODS alloys. The model-predicted particle sizes exhibit good agreement with experimental measurements across various LPBF process parameters, i.e., laser power (110–220 W) and scanning speed (150–900 mm/s), demonstrating the reliability and predictive power of the modeling approach. The multiscale approach can be used to guide the future design of experimental process parameters to control oxide nanoparticle characteristics in LPBF-manufactured ODS alloys. Additionally, our approach introduces a novel strategy for understanding and modeling the thermodynamics and kinetics of precipitation in high-temperature systems, particularly molten alloys.

Wang, Zhengming (ORCID:0000000241627112)↗
DOE OSTI2023

Thermal hydraulic characteristics of liquid sodium and supercritical CO 2 in a diffusion bonded heat exchanger

Compact heat exchangers are being examined for use in advanced, high-temperature nuclear or concentrated solar power plants to improve thermal efficiencies and reduce capital costs. At the time of this work, no experimental investigation of liquid sodium in the popular diffusion-bonded heat exchanger design had been performed. Herein this paper describes the thermal-hydraulic and overall operations performance observed during testing of a 316/L stainless steel “zig-zag” microchannel heat exchanger operating between a (0.5 kg/s) sodium loop and a (0.3 kg/s) recuperated supercritical CO 2 system with outlet conditions up to 550 °C at 16 MPa. Observed pressure drop is presented in the form of an effective friction factor correlation which aligns closely with recent experimental data. The thermal performance of this heat exchanger, measured by its overall conductance under various flow conditions, was decomposed to examine the independent convection behaviors of both the CO 2 and sodium streams. These results are presented in the form of Nusselt correlations fitted to the experimental data. The sodium heat transfer correlation aligns closely with the widely accepted Lubarsky-Kaufman correlation, while the CO 2 heat transfer correlation lies between previous correlations developed by computational and experimental methods. This was the first long-duration use of sodium in a microchannels (~1.8 mm hydraulic diameter) heat exchanger. The use of an oxide control system enabled trouble-free operation of the heat exchanger for over 150 h of high-temperature operation. This first-of-a-kind demonstration using liquid sodium and supercritical carbon dioxide shows great promise for further application of this technology in advanced nuclear or solar power plants.

42 ENGINEERING↗
DOE OSTI2025

Hydride Accessibility and Reactivity in the Configurational and Stoichiometric Space of β-Ga 2 O 3 for CO 2 Hydrogenation

Understanding how surface species evolve under reaction conditions is essential for improving catalyst design for efficient CO 2 hydrogenation. This work combines systematic DFT calculations with grand canonical sampling to investigate the stability and reactivity of Ga–H species on β-Ga 2 O 3 across a range of reaction conditions. Initial DFT studies reveal that when Ga–H species are present, they facilitate formate formation via a low-barrier pathway, largely independent of the surface termination or hydrogen site. However, grand canonical sampling shows that under a broad range of reaction conditions─especially at high oxygen chemical potentials associated with high water content─Ga–H species are thermodynamically inaccessible. Furthermore, adsorbed water molecules can block reactive sites, inhibiting CO 2 activation even when hydrides are present. These findings suggest that the lack of accessible hydride species, rather than their intrinsic reactivity, could contribute to reduced catalytic performance of β-Ga 2 O 3 under more oxidizing, high-conversion conditions.

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

Effect of initial γ -irradiation on infrared laser ablation of poly(vinyl alcohol) studied by infrared spectroscopy

We report the effect of initial γ-irradiation of poly(vinyl alcohol) (PVA) on the kinetics of polymer ablation under CO 2 laser irradiation was studied using infra-red spectroscopy. The rate of laser ablation rapidly decreases with increasing time of laser ablation up to 10 s. Initial γ-irradiation of a dose up to 100 kGy reduces the rate of the laser ablation, just like the effect of laser exposure. The number of OH and CH groups decrease in PVA both with laser irradiation and with γ-irradiation. The number of OH groups decreases more under laser irradiation. Unsaturated bonds are formed in γ–irradiated PVA on the surface of the crater formed by laser ablation of the polymer that has undergone radiolysis. Increasing the dose of initial γ-irradiation from 100 to 2300 kGy leads to an increase in the intensity of the IR bands of the unsaturated bonds. The number of IR bands in the spectra of the laser ablation crater of PVA does not change with the dose of initial γ-irradiation. A dose of radiolysis of 3500 kGy significantly changes the IR spectra of both the ablation crater and the coating formed from the ablation products. Many bands characteristic for PVA are no longer present and the intensities of bands corresponding to unsaturated bonds are increased. A computational model for loss of water and ketone formation was developed for PVA and PVA including a diol using G3(MP2). The highest activation energy barrier step in the decomposition reaction was formation of the enol species and water was shown to catalyze all decomposition steps.

36 MATERIALS SCIENCE↗