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DOE OSTI2016

Electronic structure, thermodynamic properties and hydrogenation of LaPtIn and CePtIn compounds by ab-initio methods

The electronic structures and thermodynamic properties of LaPtIn and CePtIn are studied by means of ab-initio full-relativistic full-potential local orbital basis (FPLO) method within densities functional (DFT) methodologies. We have also examined the influence of hydrogen on the electronic structure and stability of CePtInH and LaPtInH systems. The positions of the hydrogen atoms have been found from the minimum of the total energy. Our calculations have shown that band structure and topology of the Fermi surfaces changed significantly during the hydrogenation. The thermodynamic properties (bulk modulus, Debye temperatures, constant pressure heat capacity) calculated in quasi-harmonic Debye-Grüneisen model are in a good agreement with the experimental data. We have applied different methods of the calculation of the equation of states (EOS) (Murnaghan, Birch-Murnaghan, Poirier–Tarantola, Vinet). The thermodynamic properties are presented for the pressure 0<P<9 GPa and the temperature range 0<T<300 K. - Highlights: • Full relativistic band structure of LaPtIn and CePtIn. • Fermi surface of LaPtIn, LaPtInH, CePtIn, CePtInH. • Effect of hydrogenation on the electronic structure of LaPtIn and CePtIn. • Thermodynamic properties in the quasi-harmonic Debye-Grüneisen model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Coupling computational thermodynamics with density-function-theory based calculations to design L12 precipitates in Fe Ni based alloys

Achieving a high-volume fraction of thermodynamically stable L12-type precipitates that are resistant to coarsening is of great importance for the development of low-cost FeNi based austenitic steels. With the aid of computational thermodynamics, this work designed two model alloys: Fe-37.4Ni-6.1Al-2.9Ti (FNAT) and Fe-45.2Ni-5.9Al-8.5Si (FNAS). Both alloys were designed to contain a similar amount of L1 2 precipitate in Fe-Ni matrix without forming other precipitates. Density-Function-Theory (DFT) calculation was coupled with computational thermodynamics to predict the critical radius at which the precipitates change shape from spherical to cuboidal. The calculation results suggest that critical radius for the FNAT alloy is about two orders of magnitude larger than that for the FeNiAlSi alloy. Phase stability and morphology of the L1 2 precipitates in these two alloys were experimentally investigated through X-ray diffraction, atom probe tomography, and scanning and transmission electron microscopy. The L1 2 precipitates in the FeNiAlSi system were found to be cuboidal and rod shaped, with much larger size than the spherical ones in the FeNiAlTi system, agreeing with the calculation results. This work suggested that coupling computational thermodynamics with DFT calculations can be reliably used to design L1 2 precipitates in FeNi based alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Thermodynamic data of Ba{sub 0.6}Sr{sub 0.4}Co{sub 0.8}Fe{sub 0.2}O{sub 3−δ} SOFC cathode material

Graphical abstract: Partial molar energy of oxygen dissolution (ΔG{sup −}{sub O{sub 2}}) and equilibrium partial pressure of oxygen (log⁡p{sub O{sub 2}}) of perovskite material with the composition Ba{sub 0.6}Sr{sub 0.4}Co{sub 0.8}Fe{sub 0.2}O{sub 3−δ} as a function of temperature. - Highlights: • We report relevant data for thermodynamic stability of Ba{sub 0.6}Sr{sub 0.4}Co{sub 0.8}Fe{sub 0.2}O{sub 3−δ} perovskite compound. • Temperature of structural transformations related to the charge compensation of the material system is evidenced. • The results are discussed based on the properties-defect structure relationship. - Abstract: The compound Ba{sub 0.6}Sr{sub 0.4}Co{sub 0.8}Fe{sub 0.2}O{sub 3−δ} with perovskite structure has been studied focusing mainly on the thermodynamic stability in correlation to the change in the oxygen stoichiometry. The thermochemical behavior has been investigated from room temperature to 1300 K by thermal gravimetry and differential thermal analysis in air and by calorimetry in scanning mode in Argon. The temperature dependence of enthalpy (ΔH{sup T}{sub 298}) in the temperature range of 300–900 K was measured by drop calorimetry. Thermodynamic properties represented by the relative partial molar free energies, enthalpies and entropies of oxygen dissolution in the perovskite phase, as well as the equilibrium partial pressures of oxygen have been obtained in the temperature range of 823–1273 K using solid electrolyte electrochemical cells (EMF). The influence of the oxygen stoichiometry on the thermodynamic properties was examined using a coulometric titration technique coupled with EMF measurements. The results are discussed based on the strong correlation between the energetic parameters and the charge compensation of the material system.

36 MATERIALS SCIENCE↗

DOE OSTI2019

A generalized computational framework to streamline thermodynamics and kinetics analysis of metabolic pathways

Metabolic engineering is a critical biotechnological approach in addressing global energy and environment challenges. Most engineering efforts, however, consist of laborious and inefficient trial-and-error of target pathways, due in part to the lack of methodologies that can comprehensively assess pathway properties in thermodynamics and kinetics. Metabolic engineering can benefit from computational tools that evaluate feasibility, expense and stability of non-natural metabolic pathways. Such tools can also help us understand natural pathways and their regulation at systems level. Here we introduce a computational toolbox, PathParser, which, for the first time, integrates multiple important functions for pathway analysis including thermodynamics analysis, kinetics-based protein cost optimization and robustness analysis. Specifically, PathParser enables optimization of the driving force of a pathway by minimizing the Gibbs free energy of least thermodynamically favorable reaction. In addition, based on reaction thermodynamics and enzyme kinetics, it can compute the minimal enzyme protein cost that supports metabolic flux, and evaluate pathway stability and flux in response to enzyme concentration perturbations. In a demo analysis of the Calvin-Benson-Bassham cycle and photorespiration pathway in the model cyanobacterium Synechocystis PCC 6803, the computation results are corroborated by experimental proteomics data as well as metabolic engineering outcomes. This toolbox may have broad application in metabolic engineering and systems biology in other microbial systems.

09 BIOMASS FUELS↗

DOE OSTI2016

Thermodynamics of HMX Polymorphs and HMX/RDX Mixtures

In this paper, we present thermodynamic models for the five most commonly studied phases of the energetic material octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX): liquid HMX and four solid polymorphs (α-, β-, γ-, and δ-HMX). We show results for the density, heat capacity, bulk modulus, and sound speed, as well as a phase diagram that illustrates the temperature and pressure regions over which the various HMX phases are most thermodynamically stable. The models are based on the same equation of state presented in our recently published paper [Myint et al., Ind. Eng. Chem. Res., 2016, 55, 2252] on another energetic material, hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). We combine our HMX and RDX models together so that the equation of state can also be applied to liquid and solid mixtures of HMX/RDX. This allows us to generate an HMX/RDX phase diagram and calculate the enthalpy change associated with a few different kinds of phase transitions that these mixtures may undergo. Our paper is the first to present a single equation of state that is capable of modeling both pure HMX and HMX/RDX mixtures. A distinct feature of HMX is the strongly metastable nature of its polymorphs. This has caused some ambiguity in the literature regarding the thermodynamic stability of α-HMX. Finally, by examining possible arrangements for the relative order of the six different solid-solid transition (α–β, α–γ, α–δ, β–γ, β–δ, and γ–δ) temperatures, we conclude that α-HMX must be thermodynamically stable so that the HMX phase diagram must have an α phase region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Evaluating the Thermodynamics of Electrocatalytic N 2 Reduction in Acetonitrile

The synthesis of ammonia by proton-coupled electroreduction of dinitrogen (N2) represents a sustainable alternative to currently practiced hydrogenation methods. Developments in this area require knowledge of the standard reduction potentials that describe the thermodynamics of N2 reduction. The first collection of N2 reduction standard potentials in organic solvent are reported here. The potentials for reduction of N2 to ammonia (NH3), hydrazine (N2H4), and diazene (N2H2) in acetonitrile (MeCN) solution are derived using thermochemical cycles. Ammonia is the thermodynamically favored product, with a 0.43 V difference between NH3 and N2H4 and a 1.26 V difference between NH3 and N2H2. The thermodynamics for reduction of N2 to the protonated products ammonium (NH4+) and hydrazinium (N2H5+) under strongly acidic conditions are also presented. Comparison with previously determined values for the H+/H2 potential in MeCN reveals a 63 mV thermodynamic preference for N2 reduction to NH3 over H2 production. Combined with knowledge of the kinetics of electrode-catalyzed H2 evolution, a wide working region is identified to guide future electrocatalytic studies.

Lindley, Brian M.↗

DOE OSTI2020

Self-Assembly of Metallo-Supramolecules under Kinetic or Thermodynamic Control: Characterization of Positional Isomers Using Scanning Tunneling Spectroscopy

Coordination-driven self-assembly has been extensively employed to construct a variety of discrete structures as a bottom-up strategy. However, mechanistic understanding regarding whether self-assembly is under kinetic or thermodynamic control is less explored. To date, such mechanistic investigation has been limited to distinct, assembled structures. It still remains a formidable challenge to study the kinetic and thermodynamic behavior of self-assembly systems with multiple assembled isomers due to the lack of characterization methods. Herein, we use a stepwise strategy which combined self-recognition and self-assembly processes to construct giant metallo-supramolecules with 8 positional isomers in solution. With the help of ultrahigh-vacuum, low-temperature scanning tunneling microscopy and scanning tunneling spectroscopy, we were able to unambiguously differentiate 14 isomers on the substrate which correspond to 8 isomers in solution. Through measurement of 162 structures, the experimental probability of each isomer was obtained and compared with the theoretical probability. Finally, such a comparison along with density functional theory (DFT) calculation suggested that although both kinetic and thermodynamic control existed in this self-assembly, the increased experimental probabilities of isomers compared to theoretical probabilities should be attributed to thermodynamic control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Projecting Permafrost Thaw of Sub-Arctic Tundra With a Thermodynamic Model Calibrated to Site Measurements

Northern circumpolar permafrost thaw affects global carbon cycling, as large amounts of stored soil carbon becomes accessible to microbial breakdown under a warming climate. The magnitude of carbon release is linked to the extent of permafrost thaw, which is locally variable and controlled by soil thermodynamics. Soil thermodynamic properties, such as thermal diffusivity, govern the reactivity of the soil-atmosphere thermal gradient, and are controlled by soil composition and drainage. In order to project permafrost thaw for an Alaskan tundra experimental site, we used seven years of site data to calibrate a soil thermodynamic model using a data assimilation technique. The model reproduced seasonal and interannual temperature dynamics for shallow (5–40 cm) and deep soil layers (2–4 m), and simulations of seasonal thaw depth closely matched observed data. The model was then used to project permafrost thaw at the site to the year 2100 using climate forcing data for three future climate scenarios (RCP 4.5, 6.0, and 8.5). Minimal permafrost thawing occurred until mean annual air temperatures rose above the freezing point, after which we measured over a 1 m increase in thaw depth for every 1 °C rise in mean annual air temperature. Under no projected warming scenario was permafrost remaining in the upper 3 m of soil by 2100. We demonstrated an effective data assimilation method that optimizes parameterization of a soil thermodynamic model. The sensitivity of local permafrost to climate warming illustrates the vulnerability of sub-Arctic tundra ecosystems to significant and rapid soil thawing.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Impact of a New Sea Ice Thermodynamic Formulation in the CESM2 Sea Ice Component

Abstract The sea ice component of the Community Earth System Model version 2 (CESM2) contains new “mushy‐layer” physics that simulates prognostic salinity in the sea ice, with consequent modifications to sea ice thermodynamics and the treatment of melt ponds. The changes to the sea ice model and their influence on coupled model simulations are described here. Two simulations were performed to assess the changes in the vertical thermodynamics formulation with prognostic salinity compared to a constant salinity profile. Inclusion of the mushy layer thermodynamics of Turner et al. (2013, https://doi.org/10.1002/jgrc.20171 ) in a fully coupled Earth system model produces thicker and more extensive sea ice in the Arctic, with relatively unchanged sea ice in the Antarctic compared to simulations using a constant salinity profile. While this is consistent with the findings of uncoupled ice‐ocean model studies, the role of the frazil and congelation growth is more important in fully coupled simulations. Melt pond drainage is also an important contribution to simulated ice thickness differences as also found in the uncoupled simulations of Turner and Hunke (2015; https://doi.org/10.1002/2014JC010358 ). However, it is an interaction of the ponds and the snow fraction that impacts the surface albedo and hence the top melt. The changes in the thermodynamics and resulting ice state modify the ice‐ocean‐atmosphere fluxes with impacts on the atmosphere and ocean states, particularly temperature.

Bailey, David A.↗

DOE OSTI2020

Thermodynamics, dynamics, and structure of supercritical water at extreme conditions

Molecular dynamics (MD) simulations to understand the thermodynamic, dynamic, and structural changes in supercritical water across the Frenkel line and the melting line have been performed. The two-phase thermodynamic model [J. Phys. Chem. B(2010), 114(24), 8191-8198] and the velocity autocorrelation functions are used to locate the Frenkel line and to calculate the thermodynamic and dynamic properties. The Frenkel lines obtained from the two-phase thermodynamic model and the velocity autocorrelation criterion do not agree with each other. Structural characteristics and the translational diffusion dynamics of water suggest that this inconsistency could arise from the two oscillatory modes in water, which are associated with the bending of hydrogen bonds and intermolecular collisions inside the first coordination shell. Finally, the overall results lead us to conclude that the universality of the Frenkel line as a dynamic crossover line from rigid to nonrigid fluids is preserved in water.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Thermodynamic guiding principles of high-capacity phase transformation materials for splitting H 2 O and CO 2 by thermochemical looping

Here, thermochemical looping splitting of water and carbon dioxide (CO 2 ) with greenhouse-gas-free (GHG-free) energy has the potential to help address the Gt-scale GHG emissions challenge. Reaction thermodynamics largely contributes to the main bottlenecks of cost reduction for thermochemical looping water/CO 2 splitting cycle. Here, we analyze thermodynamic driving forces in such cycles with two-phase ternary ferrites as model systems. We find that cation configurational entropy chiefly determines the change of partial molar entropy with oxygen stoichiometry. In addition, our phase diagram analysis accurately predicts the optimal Fe ratio for maximal water/CO 2 splitting capacity in thermal reduction and in chemical reduction based cycles, underlining the significance of phase boundary positions. With chemical reduction, >10% CO 2 conversion and high oxygen exchange capacity can both be achieved. Furthermore, our reduced Gibbs free energy model illustrates critical thermodynamic factors that influence the water/CO 2 splitting capacity. Our research reveals the thermodynamic driving forces underlying the unconventional high-capacity Fe-poor ferrites, further explained via phase diagrams of Fe–Co–O, Fe–Ni–O and Fe–Mg–O. Future materials improvements can be guided by our reduced Gibbs free energy model.

08 HYDROGEN↗

DOE OSTI2024

Insights into controlling bacterial cellulose nanofiber film properties through balancing thermodynamic interactions and colloidal dynamics

In recent years, nanocellulose has emerged as a sustainable and environmentally friendly alternative to traditional petroleum-derived structural polymers. Sourced either from plants, algae, or bacteria, nanocellulose can be processed into colloid, gel, film and fiber forms. However, the required fundamental understanding of process parameters that govern the morphology and structure–property relationships of nanocellulose systems, from colloidal suspensions to bulk materials, has not been developed and generalized for all forms of cellulose. This further hinders the more widespread adoption of this biopolymer in applications. Our study investigates the dispersion of cellulose nanofibers (CNFs) produced by a bacterial–yeast co-culture, in solvents, highlighting the role of thermodynamic interactions in influencing their colloidal behavior. By adjusting Hansen solubility parameters, we controlled the thermodynamic relationship between CNFs and solvents across various concentrations, studying the dilute to semi-dilute regimes. Rheological measurements revealed that the threshold at which a concentration-based regime transition occurs is distinctly solvent-dependent. Complementing rheological analysis with small angle X-ray scattering and zeta potential measurements, our findings reveal that enhancing CNF–solvent interactions increases excluded volume in the dilute regime, emphasizing the importance of the balance between fiber–fiber and fiber–solvent interactions. Moreover, we investigated the transition from colloidal to solid state by creating films from dispersions with varying interaction parameters in semi-dilute regimes. Through mechanical testing and scanning electron microscopy imaging of the fracture surfaces, we highlight the significance of electrokinetic effects in such transitions, as dispersions with higher electrokinetic stabilization gave rise to stronger and tougher films despite having less favorable thermodynamic interaction parameters. Finally, our work provides insights into the thermodynamic and electrokinetic interplay that governs bacterial CNF dispersion, offering a foundation for future application and a deeper understanding of nanocellulose's colloidal and structure-property relationships.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Computing chemical potentials with machine-learning-accelerated simulations to accurately predict thermodynamic properties of molten salts

The successful design and deployment of next-generation nuclear technologies heavily rely on thermodynamic data for relevant molten salt systems. However, the lack of accurate force fields and efficient methods has limited the quality of thermodynamic predictions from atomistic simulations. Here we propose an efficient free energy framework for computing chemical potentials, which is the central free energy quantity behind many thermodynamic properties. We accelerate our simulations without sacrificing accuracy by using machine learning interatomic potentials trained on density functional theory (DFT) data. Using lithium chloride as our model system, we compute chemical potentials with DFT-accuracy for solid and liquid phases by transmuting ions into noninteracting particles. Notably, in the liquid phase, we demonstrate consistency whether we transmute one ion pair or the entire system into ideal gas particles. By locating the temperature where the chemical potential of solid and liquid phases cross, we predict a melting point of 880 ± 18 K for lithium chloride, which is remarkably close to the experimental value of 883 K. With this successful demonstration, we lay the foundation for high-throughput thermodynamic predictions of many properties that can be derived from the chemical potentials of the minority and majority components in molten salts.

Gibson, Luke D. [Oak Ridge National Laboratory (OR↗

DOE OSTI2014

An analytical coarse-graining method which preserves the free energy, structural correlations, and thermodynamic state of polymer melts from the atomistic to the mesoscale

Structural and thermodynamic consistency of coarse-graining models across multiple length scales is essential for the predictive role of multi-scale modeling and molecular dynamic simulations that use mesoscale descriptions. Our approach is a coarse-grained model based on integral equation theory, which can represent polymer chains at variable levels of chemical details. The model is analytical and depends on molecular and thermodynamic parameters of the system under study, as well as on the direct correlation function in the k → 0 limit, c{sub 0}. A numerical solution to the PRISM integral equations is used to determine c{sub 0}, by adjusting the value of the effective hard sphere diameter, d{sub HS}, to agree with the predicted equation of state. This single quantity parameterizes the coarse-grained potential, which is used to perform mesoscale simulations that are directly compared with atomistic-level simulations of the same system. We test our coarse-graining formalism by comparing structural correlations, isothermal compressibility, equation of state, Helmholtz and Gibbs free energies, and potential energy and entropy using both united atom and coarse-grained descriptions. We find quantitative agreement between the analytical formalism for the thermodynamic properties, and the results of Molecular Dynamics simulations, independent of the chosen level of representation. In the mesoscale description, the potential energy of the soft-particle interaction becomes a free energy in the coarse-grained coordinates which preserves the excess free energy from an ideal gas across all levels of description. The structural consistency between the united-atom and mesoscale descriptions means the relative entropy between descriptions has been minimized without any variational optimization parameters. The approach is general and applicable to any polymeric system in different thermodynamic conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

The role of material flexibility on the drying transition of water between hydrophobic objects: A thermodynamic analysis

Liquid water confined between hydrophobic objects of sufficient size becomes metastable with respect to its vapor at separations smaller than a critical drying distance. Macroscopic thermodynamic arguments predicting this distance have been restricted to the limit of perfectly rigid confining materials. However, no material is perfectly rigid and it is of interest to account for this fact in the thermodynamic analysis. We present a theory that combines the current macroscopic theory with the thermodynamics of elasticity to derive an expression for the critical drying distance for liquids confined between flexible materials. The resulting expression is the sum of the well-known drying distance for perfectly rigid confining materials and a new term that accounts for flexibility. Thermodynamic arguments show that this new term is necessarily positive, meaning that flexibility increases the critical drying distance. To study the expected magnitude and scaling behavior of the flexible term, we consider the specific case of water and present an example of drying between thin square elastic plates that are simply supported along two opposite edges and free at the remaining two. We find that the flexible term can be the same order of magnitude or greater than the rigid solution for materials of biological interest at ambient conditions. In addition, we find that when the rigid solution scales with the characteristic size of the immersed objects, the flexible term is independent of size and vice versa. Thus, the scaling behavior of the overall drying distance will depend on the relative weights of the rigid and flexible contributions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Thermodynamic scaling of molecular dynamics in supercooled liquid state of pharmaceuticals: Itraconazole and ketoconazole

Pressure-Volume-Temperature (PVT) measurements and broadband dielectric spectroscopy were carried out to investigate molecular dynamics and to test the validity of thermodynamic scaling of two homologous compounds of pharmaceutical activity: itraconazole and ketoconazole in the wide range of thermodynamic conditions. The pressure coefficients of the glass transition temperature (dT{sub g}/dp) for itraconazole and ketoconazole were determined to be equal to 183 and 228 K/GPa, respectively. However, for itraconazole, the additional transition to the nematic phase was observed and characterized by the pressure coefficient dT{sub n}/dp = 258 K/GPa. From PVT and dielectric data, we obtained that the liquid-nematic phase transition is governed by the relaxation time since it occurred at constant τ {sub α} = 10{sup −5} s. Furthermore, we plotted the obtained relaxation times as a function of T{sup −1}v{sup −γ}, which has revealed that the validity of thermodynamic scaling with the γ exponent equals to 3.69 ± 0.04 and 3.64 ± 0.03 for itraconazole and ketoconazole, respectively. Further analysis of the scaling parameter in itraconazole revealed that it unexpectedly decreases with increasing relaxation time, which resulted in dramatic change of the shape of the thermodynamic scaling master curve. While in the case of ketoconazole, it remained the same within entire range of data (within experimental uncertainty). We suppose that in case of itraconazole, this peculiar behavior is related to the liquid crystals’ properties of itraconazole molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Thermodynamic properties and transport coefficients of air thermal plasmas mixed with ablated vapors of Cu and polytetrafluoroethylene

Because the fault arc in aircraft electrical system often causes a fire, it is particularly important to analyze its energy and transfer for aircraft safety. The calculation of arc energy requires the basic parameters of the arc. This paper is mainly devoted to the calculations of equilibrium composition, thermodynamic properties (density, molar weight, enthalpy, and specific heat at constant pressure) and transport coefficients (thermal conductivity, electrical conductivity, and viscosity) of plasmas produced by a mixture of air, Cu, and polytetrafluoroethylene under the condition of local thermodynamic equilibrium. The equilibrium composition is determined by solving a system of equations around the number densities of each species. The thermodynamic properties are obtained according to the standard thermodynamic relationships. The transport coefficients are calculated using the Chapman-Enskog approximations. Results are presented in the temperature range from 3000 to 30 000 K for pressures of 0.08 and 0.1 MPa, respectively. The results are more accurate and are reliable reference data for theoretical analysis and computational simulation of the behavior of fault arc.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Learning thermodynamically constrained equations of state with uncertainty

Numerical simulations of high energy-density experiments require equation of state (EOS) models that relate a material’s thermodynamic state variables—specifically pressure, volume/density, energy, and temperature. EOS models are typically constructed using a semi-empirical parametric methodology, which assumes a physics-informed functional form with many tunable parameters calibrated using experimental/simulation data. Since there are inherent uncertainties in the calibration data (parametric uncertainty) and the assumed functional EOS form (model uncertainty), it is essential to perform uncertainty quantification (UQ) to improve confidence in EOS predictions. Model uncertainty is challenging for UQ studies since it requires exploring the space of all possible physically consistent functional forms. Thus, it is often neglected in favor of parametric uncertainty, which is easier to quantify without violating thermodynamic laws. This work presents a data-driven machine learning approach to constructing EOS models that naturally captures model uncertainty while satisfying the necessary thermodynamic consistency and stability constraints. We propose a novel framework based on physics-informed Gaussian process regression (GPR) that automatically captures total uncertainty in the EOS and can be jointly trained on both simulation and experimental data sources. A GPR model for the shock Hugoniot is derived, and its uncertainties are quantified using the proposed framework. We apply the proposed model to learn the EOS for the diamond solid state of carbon using both density functional theory data and experimental shock Hugoniot data to train the model and show that the prediction uncertainty is reduced by considering thermodynamic constraints.

Sharma, Himanshu (ORCID:000900050235718X)↗