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DOE OSTI2025

Effects of equilibrium pressure on plasma response to RMPs in a spherical tokamak

This study presents a comprehensive analysis of the equilibrium pressure on the plasma response to resonant magnetic perturbations (RMPs) in the spherical tokamak (ST) MAST-U, employing both single-fluid and MHD-kinetic hybrid models (implemented via the MARS-F/K codes). As a key finding, the study identifies two different pressure-driven eigenmodes, exhibiting Sturmian property, that affect the Troyon no-wall limits for the onset of the n = 1 and n = 2 ( n is the toroidal mode number) ideal external kink instabilities as well as the corresponding plasma response to the applied RMP. With increasing equilibrium pressure, the plasma response to RMPs is significantly enhanced in the ST plasma, particularly in the high-pressure regime where kinetic effects strongly stabilize the external kink instability. The Troyon no-wall limit divides the plasma response into two regions: well below the limit, the response amplitudes and trends (versus pressure) are similar between the fluid and kinetic models; as the equilibrium pressure approaches the Troyon limit, the kinetic model predicts significant amplification of the RMP field, up to 30 times for cases considered. A relatively weak dependence of the optimal coil phasing on the equilibrium pressure is computed in this ST plasma, similar to the trend obtained for the conventional aspect ratio devices. These findings underscore the importance of incorporating kinetic effects in accurate prediction of the plasma response to RMPs in high-pressure ST tokamak plasmas and provide a theoretical basis for optimizing RMP-based control of the edge-localized modes in future ST devices.

RMP↗
DOE OSTI2024

Accelerating Thermochemical Equilibrium Calculations for Nuclear Reactor Applications

Thermochemical properties play a key role in modeling and simulation of several key phenomena in nuclear reactors. There has been an increasing interest in incorporating CALPHAD-based formulations in multiphysics simulations including for Molten Salt Reactors where knowledge of phase evolution of the salt and the chemical potentials of various elements are of utmost importance in source term analyses and redox control. However, the size of such simulations is often limited by the high computational cost of full thermodynamic equilibrium calculations. This work discusses the current efforts aimed at accelerating thermochemical equilibrium calculations for multiphysics simulations performed using the open-source finite element / finite volume code Multiphysics Object Oriented Simulation Environment (MOOSE) [1]. While several methods have been proposed for accelerating phase equilibrium calculations [2], most focus on relatively small systems and often rely on a- priori knowledge of the state-space of the system. Nuclear materials, however, are often multi-component systems owing to the evolution of composition under irradiation and an approach based on a-priori mapping of phase diagram is often not enough. This work is aimed at demonstrating an on-the-fly surrogate modeling framework that uses active learning to reduce the number of full equilibrium calculations that must be performed. By combining with efficient coupling approaches, the surrogate framework helps in reducing the computational cost of thermodynamic equilibrium informed multiphysics simulations of nuclear materials. The performance is benchmarked against full coupling with the thermochemistry library Thermochimica [3]. This work uses a machine learning based approach for constructing surrogate models to predict the stable phases in a multicomponent system. The surrogates were constructed using neural networks and Gaussian process classification. In this work, we compare the relative performance of the two methods. We also demonstrate the use of caching previous calculations by interpolating the values from nearest neighbors. References [1] Lindsay, A.D., et al. "2.0 – MOOSE: Enabling massively parallel multiphysics simulation", SoftwareX, 20 (2022): 101202. [2] Roos, W.A. and Zietsman J.H. "Accelerating complex chemical equilibrium calculations – A Review", Calphad, 77 (2022): 102380. [3] Piro, M.H.A., et al. "The thermochemistry library Thermochimica", Computational Materials Science, 67 (2013): 266-272.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Impact of phase state and non-ideal mixing on equilibration timescales of secondary organic aerosol partitioning

Abstract. Evidence has accumulated that secondary organic aerosols (SOAs) exhibit complex morphologies with multiple phases that can adopt amorphous semisolid or glassy phase states. However, experimental analysis and numerical modeling on the formation and evolution of SOA still often employ equilibrium partitioning with an ideal mixing assumption in the particle phase. Here we apply the kinetic multilayer model of gas–particle partitioning (KM-GAP) to simulate condensation of semi-volatile species into a core–shell phase-separated particle to evaluate equilibration timescales of SOA partitioning. By varying bulk diffusivity and the activity coefficient of the condensing species in the shell, we probe the complex interplay of mass transfer kinetics and the thermodynamics of partitioning. We found that the interplay of non-ideality and phase state can impact SOA partitioning kinetics significantly. The effect of non-ideality on SOA partitioning is slight for liquid particles but becomes prominent in semisolid or solid particles. If the condensing species is miscible with a low activity coefficient in the viscous shell phase, the particle can reach equilibrium with the gas phase long before the dissolution of concentration gradients in the particle bulk. For the condensation of immiscible species with a high activity coefficient in the semisolid shell, the mass concentration in the shell may become higher or overshoot its equilibrium concentration due to slow bulk diffusion through the viscous shell for excess mass to be transferred to the core phase. Equilibration timescales are shorter for the condensation of lower-volatility species into semisolid shell; as the volatility increases, re-evaporation becomes significant as desorption is faster for volatile species than bulk diffusion in a semisolid matrix, leading to an increase in equilibration timescale. We also show that the equilibration timescale is longer in an open system relative to a closed system especially for partitioning of miscible species; hence, caution should be exercised when interpreting and extrapolating closed-system chamber experimental results to atmosphere conditions. Our results provide a possible explanation for discrepancies between experimental observations of fast particle–particle mixing and predictions of long mixing timescales in viscous particles and provide useful insights into description and treatment of SOA in aerosol models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Measuring the Loschmidt Amplitude for Finite-Energy Properties of the Fermi-Hubbard Model on an Ion-Trap Quantum Computer

Calculating the equilibrium properties of condensed-matter systems is one of the promising applications of near-term quantum computing. Recently, hybrid quantum-classical time-series algorithms have been proposed to efficiently extract these properties from a measurement of the Loschmidt amplitude ⟨ ψ | e − i H ^ t | ψ ⟩ from initial states | ψ ⟩ and a time evolution under the Hamiltonian H ^ up to short times t . In this work, we study the operation of this algorithm on a present-day quantum computer. Specifically, we measure the Loschmidt amplitude for the Fermi-Hubbard model on a 16 -site ladder geometry (32 orbitals) on the Quantinuum H2-1 trapped-ion device. We assess the effect of noise on the Loschmidt amplitude and implement algorithm-specific error-mitigation techniques. By using a thus-motivated error model, we numerically analyze the influence of noise on the full operation of the quantum-classical algorithm by measuring expectation values of local observables at finite energies. Finally, we estimate the resources needed for scaling up the algorithm. Published by the American Physical Society 2024

Physics↗
DOE OSTI2022

Calorimetric study of skutterudite (CoAs2.92) and heazlewoodite (Ni3S2)

Abstract Nickel and cobalt arsenides, sulfarsenides, and sulfides occur in many hydrothermal ore deposits, but their thermodynamic properties are not well known, in some cases not known at all. In this work, we determined a full set of thermodynamic properties for heazlewoodite and skutterudite. Both phases were synthesized in evacuated silica tubes at elevated temperatures, and electron microprobe analyses gave their compositions as Ni3S2 and CoAs2.92, respectively. Enthalpies of formation were measured by high-temperature oxide-melt solution calorimetry. The reference phases were pure elements, thus eliminating any systematic errors related to such phases. The enthalpies of formation at T = 298.15 K and P = 105 Pa are –216.0 ± 8.4(2σ) and –88.2 ± 6.1 kJ·mol−1 for Ni3S2 and CoAs2.92, respectively. Entropies were calculated from low-temperature heat capacity (CP) data from relaxation (PPMS) calorimetry and are 133.8 ± 1.6 and 106.4 ± 1.3 J·mol–1·K–1, respectively. The calculated Gibbs free energies of formation are –210.0 ± 8.4 and –79.9 ± 6.2 kJ·mol−1 for Ni3S2 and CoAs2.92, respectively. The PPMS CP data, together with a set of differential scanning calorimetry measurements, were used to derive CP polynomials up to 700 K with the Kieffer model based on previously published frequencies of acoustic and optic modes. Equilibrium constants for selected reactions with an aqueous phase were calculated up to 700 K. Geochemical modeling in these systems, however, should await until more reliable data for other phases from the system Co-Ni-As-S are available.

Geochemistry & Geophysics↗
DOE OSTI2022

Air Exchange Rate Impact on Activity Equilibrium Factors and Inhalation Fractional Equilibrium Factors for Rn, Xe, Kr, Ar, Ne, and Their Progeny in Vapor Intrusion, Risk, and Dose Models

Exposure to the radioactive noble gasses, especially radon, is of high concern and poses a significant risk to humans in an indoor air environment as the second leading cause of lung cancer in the United States. To evaluate and minimize the risks posed by these gasses, it is important to understand their radiological and physical properties. The EPA’s Radon Vapor Intrusion Screening Level (RVISL) calculator calculates indoor air RVISLs based on target working levels (WLs), target excess lifetime cancer risk (ELCR), and annual dose limits for the actinon (Rn-219), thoron (Rn-220), and radon (Rn-222) decay series. The RVISLs are based on inhalation and submersion in gas cloud exposure routes for residential and commercial settings. The RVISLs are analogous to preliminary remediation goals (PRGs) and dose compliance concentrations (DCCs), where the isotope-specific values are in units of activity concentration (activity per unit volume). If the concentration of a parent isotope of radon or its progeny is found to exceed the RVISL, then further action to ensure cleanup of the contaminant may be necessary. In residential and commercial settings, the RVISLs will vary based on the air exchange rate present. The EPA’s Radionuclide PRG and DCC Calculators also assess the risk/dose from noble gases in the air due to household use of water like showering. In this study, a computational method in MATLAB was developed to determine the impact of the air exchange rate on the activity equilibrium factor (A eq ) and the inhalation fractional equilibrium factor (F eq ). Both factors are values that reflect the equilibrium concentrations of progeny to their parent in the air. These factors have a direct impact on the RVISL, PRG, and DCC calculations of WL, ELCR, and annual dose, respectively. This study builds on a previous report that only focused on actinon, thoron, and radon by revisiting the original A eq and F eq calculation methods, as well as including the values for the Rn-207, Rn-209, Rn-210, Rn-211, Rn-215, Rn-216, Rn-217, Rn-218, Rn-223, Ne-24, Ar-42, Ar-43, Ar-44, Kr-74, Kr-75, Kr-76, Kr-77, Kr-88, Kr-89, Xe-120, Xe-121, Xe-122, Xe-123, Xe-135m, and Xe-138 decay chains, which are not currently available in literature. The EPA’s RVISL calculator will be updated to include the new A eq and F eq values for the actinon, thoron, and radon decay chains, while the rest of the calculators will incorporate all the new A eq and F eq values as appropriate.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Database-wide hazard modelling of the onset of DIII-D tearing modes with field features

The rate of onset (hazard) of tearing modes is modelled probabilistically using statistical learning algorithms. Axisymmetric energy-density equilibrium fields are taken as raw high-dimensional input features which are reduced with principal component analysis. Signal processing of non-axisymmetric magnetics fluctuation array data provides the target information from which to learn. Model selection, visualization and calibration assessment procedures are detailed. Here, the analysis is deployed at large scale across the DIII-D tokamak database. Standard model selection criteria suggest that the energy-density post-processed feature is a better choice for modelling the onset rate compared to the non-processed equilibrium reconstruction solution. Two example applications of the learned rate function are demonstrated: (i) proximity-to-onset discharge monitoring and (ii) database analysis showing an (expected) observational global trend that the general hazard increases as a plasma performance metric increases. An important connection between the hazard function and its use as a conditional probability generator is reviewed in the Appendix.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Dynamical instability of collapsed dark matter halos

A self-interacting dark matter halo can experience gravothermal collapse, resulting in a central core with an ultrahigh density. It can further contract and collapse into a black hole, a mechanism proposed to explain the origin of supermassive black holes. We study dynamical instability of the core in general relativity. Here we use a truncated Maxwell-Boltzmann distribution to model the dark matter distribution and solve the Tolman-Oppenheimer-Volkoff equation. For given model parameters, we obtain a series of equilibrium configurations and examine their dynamical instability based on considerations of total energy, binding energy, fractional binding energy, and adiabatic index. Our numerical results indicate that the core can collapse into a black hole when the fractional binding energy reaches 0.035 with a central gravitational redshift of 0.5. We further show for the instability to occur in the classical regime, the boundary temperature of the core should be at least 10% of the mass of dark matter particles; for a 10 9 M ⊙ seed black hole, the particle mass needs to be larger than a few keV. These results can be used to constrain different collapse models, in particular, those with dissipative dark matter interactions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Intermodel Spread in the Pattern Effect and Its Contribution to Climate Sensitivity in CMIP5 and CMIP6 Models

Radiative feedbacks depend on the spatial patterns of sea surface temperature (SST) and thus can change over time as SST patterns evolve—the so-called pattern effect. In this study, we investigate intermodel differences in the magnitude of the pattern effect and how these differences contribute to the spread in effective equilibrium climate sensitivity (ECS) within CMIP5 and CMIP6 models. Effective ECS in CMIP5 estimated from 150-yr-long abrupt4×CO2 simulations is on average 10% higher than that estimated from the early portion (first 50 years) of those simulations, which serves as an analog for historical warming; this difference is reduced to 7% on average in CMIP6. The (negative) net radiative feedback weakens over the course of the abrupt4×CO2 simulations in the vast majority of CMIP5 and CMIP6 models, but this weakening is less dramatic on average in CMIP6. For both ensembles, the total variance in the effective ECS is found to be dominated by the spread in radiative response on fast time scales, rather than the spread in feedback changes. Using Green’s functions derived from two AGCMs shows that the spread in feedbacks on fast time scales may be primarily due to differences in atmospheric model physics, whereas the spread in feedback evolution is primarily governed by differences in SST patterns. Intermodel spread in feedback evolution is well explained by differences in the relative warming in the West Pacific warm-pool regions for the CMIP5 models, but this relation fails to explain differences across the CMIP6 models, suggesting that a stronger sensitivity of extratropical clouds to surface warming may also contribute to feedback changes in CMIP6.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Mapping the kinetic evolution of metastable grain boundaries under non-equilibrium processing

The kinetic evolution of a multiplicity of metastable grain boundaries (GBs) under fast driving conditions are studied by atomistic modeling. Assisted with an enhanced statistical analysis, the energetic evolution of GBs over a broad metastability-temperature space is mapped out, wherein two distinct regimes—an ageing regime and a rejuvenating regime—are retrieved with high fidelity. By comparing the results under various conditions (e.g. random perturbations, isothermal annealing, and fast heating/cooling), it is shown that such ageing/rejuvenating mechanism map is universal, irrespective of the actual stimuli used to elicit the metastable GBs. Here, the ageing/rejuvenating phenomena are demonstrated to stem from the energy imbalance of uphill climbing and downhill dropping during sequential transitions in the system's potential energy landscape. Without the necessity of introducing free parameters, such model can reconcile experimentally measured hardness variation of nanocrystalline metals subjected to femto-second laser irradiation, and it therefore provides a novel perspective on achieving a plurality of interfacial states and facilitating previously inaccessible property regimes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Can machine learning improve the model representation of turbulent kinetic energy dissipation rate in the boundary layer for complex terrain?

Current turbulence parameterizations in numerical weather prediction models at the mesoscale assume a local equilibrium between production and dissipation of turbulence. As this assumption does not hold at fine horizontal resolutions, improved ways to represent turbulent kinetic energy (TKE) dissipation rate (ϵ) are needed. Here, we use a 6-week data set of turbulence measurements from 184 sonic anemometers in complex terrain at the Perdigão field campaign to suggest improved representations of dissipation rate. First, we demonstrate that the widely used Mellor, Yamada, Nakanishi, and Niino (MYNN) parameterization of TKE dissipation rate leads to a large inaccuracy and bias in the representation of ϵ. Next, we assess the potential of machine-learning techniques to predict TKE dissipation rate from a set of atmospheric and terrain-related features. We train and test several machine-learning algorithms using the data at Perdigão, and we find that the models eliminate the bias MYNN currently shows in representing ϵ, while also reducing the average error by up to almost 40 %. Of all the variables included in the algorithms, TKE is the variable responsible for most of the variability of ϵ, and a strong positive correlation exists between the two. These results suggest further consideration of machine-learning techniques to enhance parameterizations of turbulence in numerical weather prediction models.

58 GEOSCIENCES↗
DOE OSTI2023

Geochemical Modeling of the Confining Unit at a CO 2 Storage Site in the Williston Basin, North Dakota

Conference presentation for American Association of Petroleum Geologists (AAPG) Carbon Capture, Utilization, and Storage (CCUS) Conference, Houston, TX, April 25–27, 2023. This geochemical modeling study investigates the evolution of geochemical reactions among CO 2 , formation water, and rocks of the two confining units above and below the CO 2 storage unit at one of the permitted CO 2 storage sites in the Williston Basin. The model is built on PHREEQC-coded chemical equilibrium thermodynamics.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Path Properties of Atmospheric Transitions: Illustration with a Low-Order Sudden Stratospheric Warming Model

Many rare weather events, including hurricanes, droughts, and floods, dramatically impact human life. To accurately forecast these events and characterize their climatology requires specialized mathematical techniques to fully leverage the limited data that are available. Here we describe transition path theory (TPT), a framework originally developed for molecular simulation, and argue that it is a useful paradigm for developing mechanistic understanding of rare climate events. TPT provides a method to calculate statistical properties of the paths into the event. As an initial demonstration of the utility of TPT, we analyze a low-order model of sudden stratospheric warming (SSW), a dramatic disturbance to the polar vortex that can induce extreme cold spells at the surface in the midlatitudes. SSW events pose a major challenge for seasonal weather prediction because of their rapid, complex onset and development. Climate models struggle to capture the long-term statistics of SSW, owing to their diversity and intermittent nature. We use a stochastically forced Holton–Mass-type model with two stable states, corresponding to radiative equilibrium and a vacillating SSW-like regime. In this stochastic bistable setting, from certain probabilistic forecasts TPT facilitates estimation of dominant transition pathways and return times of transitions. These “dynamical statistics” are obtained by solving partial differential equations in the model’s phase space. With future application to more complex models, TPT and its constituent quantities promise to improve the predictability of extreme weather events through both generation and principled evaluation of forecasts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Exotic Kondo Phases: the non-Kramers Doniach phase diagram

This is the final report for the early career award “Exotic Kondo Phases: the non-Kramers Doniach phase diagram”. This project searched for exotic novel phases in heavy fermion materials and explored the possible phases of the two-channel Kondo model. Significant results include an enhanced understanding of the channel-symmetry breaking heavy Fermi liquid and its spinorial nature; a novel platform for realizing Majorana defects in topological defects in two-channel Kondo insulators; and a new non-equilibrium way to realize multi-channel Kondo models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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 OSTI2023

Calorimetric Energies and Chemical Potentials of Metal Atoms in Catalytic Nanoparticles on Oxide and Carbon Supports: Improved Size Dependencies and Adhesion Energies

The chemical potential of metal atoms, μM, in supported metal nanoparticles is an important descriptor related to both the catalytic activity and the stability of the nanoparticles. Here, we derive an expression relating μM to the radius of the particle’s contact area with the support and the adhesion energy at the metal/support interface (E adh ) that assumes the particles have the shape of spherical caps but of arbitrary contact angle with the support (θ c ) and includes an empirical correction for the increase in metal surface energy and adhesion energy with decreasing radius of curvature. We then show that, at any assumed contact angle, we can simultaneously fit previously reported measurements of both calorimetric μ M (from heats of metal vapor adsorption during nanoparticle growth by vapor deposition) versus metal coverage data and the He + low-energy ion scattering (LEIS) intensities for the metal and/or support versus metal coverage (using our recently developed spherical cap model for quantitative LEIS intensities), to determine the particle size versus coverage and E adh . Only one choice of contact angle gives a pair of values for contact angle and E adh , which is consistent with the Young–Dupré equation for the equilibrium shape of a spherical particle. At this equilibrium shape, we then applied this spherical cap model (SCM) to reanalyze microcalorimetric metal chemical potentials and LEIS signals versus coverage data for nine metal/support combinations that were previously analyzed by assuming that the particles had the shape of hemispherical caps, i.e., with a contact angle of 90°. We show that this revised approach gives close agreement with the calorimetric and LEIS data; the best-fit contact angles vary from 64 to 84°, correcting the earlier assumption of 90°. Furthermore, these results provide significant accuracy improvements in particle size versus coverage, metal chemical potential versus size and coverage, metal/support adhesion energies and contact angles for Cu, Ag and Au on CeO 2 (111), Ni on MgO(100), Ag on Fe 3 O 4 (111) and TiO 2 (100), and Ag, Ni and Pd on Ni-supported graphene. This revised approach is much more broadly applicable than the earlier hemispherical cap model (HCM).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

A general predictive methodology for fuel-mixture properties up to supercritical conditions

A predictive thermodynamic model is utilized for the calculation of fuel properties of oxymethylene dimethyl ethers (OME 3–4 ), surrogates for gasoline, diesel and aviation fuel, as well as alcohol blends with gasoline and diesel. The alcohols used for these blends are methanol, ethanol, propanol, butanol and pentanol; their mixing ratio ranges from 10 to 50% by volume. The model is based on the Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EoS) and Vapor Liquid Equilibrium (VLE) calculations at constant temperature, density and composition. The model includes the association term, with the assumption of two association sites (2B scheme), to enable the modeling of alcohols. The pure-component parameters are estimated based on the Group Contribution (GC) method of various sources, as well as a parametrization model specifically designed for the case of OME 3–4 . The results of the computational model for the density, vapor pressure and distillation curves at various conditions, including high-pressure, high-temperature (HPHT), are compared to experimental and computational data available in the literature. In the cases where no measurements are available for the surrogates, experimental data for the corresponding target fuel are used, taking into consideration the inherent deviation in properties between real and surrogate fuel. Overall, the results are in good agreement with the data from the literature, with the average deviation not exceeding 12% for temperature (Kelvin) on the distillation curves, 10% for density and 46% for vapor pressure and the general trend being captured successfully. The use of different pure component parameter estimation techniques can further improve the prediction quality in the cases of OME3–4 and the aviation fuel surrogate, especially for the vapor pressure, leading to an average deviation lower than 18%. These results demonstrate the predictive capabilities of the model, which extend to a wide range of fuel types and pressure/temperature conditions. Through this investigation, the present work aims to establish the limits of applicability of this thermodynamic property prediction methodology.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Linear relationships for modeling CO 2 absorption in aqueous alkanolamine solutions in a thermodynamically consistent way

A thermodynamically consistent model for the carbon dioxide (CO 2 ) absorption in aqueous alkanolamine system is of great importance in the research and development of a CO 2 capture process. To facilitate the development of thermodynamic models, linear Gibbs free energy, enthalpy, and heat capacity relationships using well-known amines as reference are used to correlate the standard reference state properties of ionic species with those of molecular species in the electrolyte system, which has been approved to provide a reliable and consistent way to estimate required parameters when there is minimal or no appropriate experimental data available. Here, the proposed relationships have been applied to the development of an electrolyte nonrandom two liquid (NRTL) activity coefficient model for CO 2 absorption in aqueous 1-amino-2-propanol (A2P) solution, as an example to demonstration the methodology. With limited vapor–liquid equilibrium data and other thermodynamic properties, the parameters in the electrolyte NRTL model are identified with good accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗