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At least 55 records · Page 3

Modeling aqueous association constants and mineral solubilities at subcritical and supercritical temperatures

The need for sustainable power generation has increased interest in the use of hydrothermal fluids for industrial applications. New high-enthalpy geothermal systems and biowaste-to-fuel processes are two relevant examples that employ supercritical fluids which require an in-depth understanding of complex chemical reactions occurring near the supercritical temperature of water (374 °C). As these processes operate in thermodynamic regimes that are not currently covered by a standard molar Gibbs energy of formation model, only empirical fits for single reaction systems are available which limit the use of multi-component phase equilibria calculations that are standard practice for less extreme environments. Here, in this paper, we advance a standard molar Gibbs energy of formation model able to operate in these otherwise inaccessible thermodynamic states to include species needed for key mineral solubility systems and ion association reactions. This work extends a model based on molecular statistical thermodynamics (MST) into four new systems (Na 3 PO 4 -H 2 O, LiOH-H 2 O, KOH-H 2 O, and BaSO 4 -H 2 O) by extending the model to cover 10 new species. For each of these systems, model predictions were consistently within the experimental uncertainties for the new systems covered. A breakdown of MST contributions to the model revealed that electrostatic and hard sphere contributions were key to reproducing density dependencies of standard molar Gibbs energy of formation values around the critical point of water.

42 ENGINEERING↗

Thermal Weight Determination and Interstate Coupling in State-Averaged ADAPT-VQE

Characterizing electronic thermal states at low temperatures is an important but challenging task in quantum chemistry and condensed matter physics, making it a prime candidate for a useful application in quantum computing. One of the most successful methods for state preparation on quantum computers is the Adaptive, Problem-Tailored (ADAPT) Variational Quantum Eigensolver (VQE), which has recently been generalized to treat excited states within a state-averaged framework as well as Gibbs states. In this work, we introduce Helmholtz-Optimized Thermal (HOT) ADAPT-VQE, an ancilla-free strategy for preparing Gibbs states that directly minimizes the Helmholtz free energy by targeting the dominant eigenstates of the thermal ensemble. We demonstrate the usefulness of HOT-ADAPT-VQE by predicting the free energy of two model systems with strongly correlated ground states: (1) the Fe 2+ cation in a magnetic field and (2) a [Cu 2 O 7 ] 10– fragment of the Mott insulator La 2 CuO 4 . Our results demonstrate that HOT-ADAPT-VQE significantly improves upon Gibbs-state estimates from multistate variants of ADAPT-VQE, often with substantially shallower quantum circuits, making it a promising candidate for thermal-state calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computationally Predicted High-Throughput Free-Energy Phase Diagrams for the Discovery of Solid-State Hydrogen Storage Reactions

The design of multinary solid-state material systems that undergo reversible phase changes via changes in temperature and pressure provides a potential means of safely storing hydrogen. However, fully mapping the stabilities of known or newly targeted compounds relative to competing phases at reaction conditions has previously required many stringent experiments or computationally demanding calculations of each compound’s change in Gibbs energy with respect to temperature, G(T). Here, we have extended the approach of constructing chemical potential phase diagrams based on ΔG f (T) to enable the analysis of phase stability at non-zero temperatures. We first performed density functional theory calculations to compute the formation enthalpies of binary, ternary, and quaternary compounds within several compositional spaces of current interest for solid-state hydrogen storage. Temperature effects on solid compound stability were then accounted for using our recently introduced machine learned descriptor for the temperature-dependent contribution G δ (T) to the Gibbs energy G(T). From these Gibbs energies, we evaluated each compound’s stability relative to competing compounds over a wide range of conditions and show using chemical potential and composition phase diagrams that the predicted stable phases and H2 release reactions are consistent with experimental observations. This demonstrates that our approach rapidly computes the thermochemistry of hydrogen release reactions for compounds at sufficiently high accuracy relative to experiment to provide a powerful framework for analyzing hydrogen storage materials. This framework based on G(T) enables the accelerated discovery of active materials for a variety of technologies that rely on solid-state reactions involving these materials.

08 HYDROGEN↗

Semi-empirical model for Henry’s law constant of noble gases in molten salts

Henry’s law constant, which describes the proportionality of dissolved gas to partial pressure of free gas in liquid–gas equilibrium systems, can also be applied to mass transport applications. In this work, we investigated an approach for determining the solubility of noble gases in a molten salt liquid utilizing the equilibrium concept of Henry’s gas constant. Henry’s gas constant is described as a mathematical function dependent on the van der Waals radius of the noble gas and the temperature of the molten salt. The alteration in Gibbs free energy encompasses contributions from both surface and volume energies. Enthalpy and entropy are deduced from these surface and volume energies in the Gibbs free energy formulation. A comparative analysis was conducted between the conventional method and our proposed model. Moreover, useful chemical properties can be determined from examination of surface and volume energies. Our findings provide an accurate and general theory of Gibbs free energy that can be validated experimentally based on the model proposed herein. This work unifies the prediction of Henry gas constant and subsequently the entropy and enthalpy calculation for noble gases in a molten salt solution to a single functional form using van der Waals radius of the gas and temperature of the system. This functional form is then used to perform a multiple regression method to find two parameters corresponding to the surface energy and volume energy. These two parameters are consistent between all combinations of noble gas and molten salt.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

$\mathcal{g}$ modes of neutron stars with hadron-to-quark crossover transitions

Here we perform the first study of the principal core g-mode oscillation in hybrid stars containing quark matter, utilizing a crossover model for the hadron-to-quark transition inspired by lattice QCD. The ensuing results are compared with our recent findings of g-mode frequencies in hybrid stars with a first-order phase transition using Gibbs constructions. We find that models using Gibbs construction yield g-mode amplitudes and the associated gravitational energy radiated that dominate over those of the chosen crossover model owing to the distinct behaviors of the equilibrium and adiabatic sound speeds in the various models. Based on our results, we conclude that were g modes to be detected in upgraded LIGO and Virgo detectors it would indicate a first-order phase transition akin to a Gibbs construction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Influence of Proton Activity Gaps between Electrodes on Open-Circuit Potential of H 2 /H 2 and H 2 /Air Cells

Polymer -electrolyte-fuel-cell open-circuit voltages (OCVs) are exactly defined by equation (1), where cathode and anode proton activities [(aH+)cathode and (aH+)anode, respectively] usually are identical, so the third term in the right-hand side of equation (2) is ignored. OCV=E0+RT/2F*ln(a1/2 O2*(a2 H+)cathode/aH2O)-RT/2F*ln((a2 H+)anode/aH2) (1) =E0+RT/2F*ln(a1/2 O2*aH2/aH2O)+RT/2F*ln((a2 H+)cathode/(a2 H+)anode) (2) Water vapor pressure is a colligative property that fundamentally correlates to electrolyte concentrations in aqueous solutions. Proton activity is a function of acid concentration, such as pH, when electrolytes are acids. In polymer-electrolyte membranes, water vapor pressure and acid concentration are understood as relative humidity (RH) and water uptake (λ), respectively, where λ represents number of water molecules per sulfonic acid molecule. Several investigations have reported the relationship between RH and λ, meaning that proton activities and associated water uptakes are intimately related to RH. In actual fuel cell operation, cathode RH is determined by ambient-atmosphere and/or humidifier RH(s), and anode RH depends on hydrogen-circulator RH. Therefore, RH is not always identical at both electrodes, and the difference between electrode RHs is considerable during dry operation of polymer electrolyte fuel cells. Therefore, the third term in the right-hand side of equation (2) may be significant for dry operation. We measured OCVs when hydrogen was supplied to both electrodes at 80°C. One electrode (A) was fixed at 30% RH, while RH at the other electrode (B) was varied (0, 5, 10, 20, and 30%). Measured OCVs varied from 0 to 75 mV. For fuel cell tests, electrode A was supplied with hydrogen at 30% RH; electrode B, oxygen at 0, 5, 10, 20, and 30% RH. OCVs deviated from that measured when RH at electrode B was 30%, increasing from 0 to 60 mV with decreasing RH at electrode B. Results are also shown in Figure 1. Proton activities of both electrodes were thermodynamically calculated. The Gibbs–Duhem relation was applied to obtain molar Gibbs free energies of water and sulfonic acid, and proton activity coefficient was calculated using the Gibbs free energy of sulfonic acid and the relationship between RH and λ1–4, assuming that protons and sulfonic anions show identical ionic-activity coefficients. OCVs were estimated using the third term in the right-hand side of equation (2). Results are shown in Figure 1. Fuel-cell current–voltage performance was poor when RHs at the anode and cathode were 30 and 20%, respectively. To determine kinetic current, we measured the oxygen-reduction reaction (ORR) using a rotating-disk electrode (RDE) in concentrated-acid aqueous solutions, which modeled catalyst-layer ionomers. Kinetic currents decreased with acid concentrations. References T. A. Zawodzinski, Jr., C. Derouin, S. Radzinski, R. J. Sherman, V. T. Smith, T. E. Springer and S. Gottesfeld , J. Electrochem. Soc., 140,1041 (1993) P. K. Das and A. Z. Weber, Proceedings of the ASME 2013 11th Fuel Cell Science, Engineering and Technology Conference, Fuel Cell 18010 (2013) V. A. Sethuraman, J. W. Weidner, A. T. Haug, S. Motupally,b and L. V. Protsailo, J. Electrochem. Soc., 155, B50 (2008) A. Kusoglu and A. Z. Weber, Chem. Rev., 117, 987 (2017) Figure 1

Yoshida, Toshihiko↗

Adsorption of furan, hexanoic acid, and alkanes in a hierarchical zeolite at reaction conditions: Insights from molecular simulations

Hierarchical zeolites containing both micropores and mesopores are valuable catalysts for facilitating reactions of large molecules. Furan acylation by fatty acids is a promising reaction for valorizing biomass, and the self-pillared pentasil (SPP) zeolite was found to perform particularly well for this reaction. To better understand the distribution of molecules in hierarchical zeolites at the elevated temperature (T = 523 K) and the elevated pressure (p >1 bar) associated with typical reaction conditions, unary and binary adsorption were predicted using Monte Carlo simulations in the isothermal–isobaric Gibbs ensemble. Adsorption of six species (furan, hexanoic acid, -hexane, -decane, -tetradecane, and 3,6-diethyloctane) was investigated from vapor, liquid, and supercritical phases, and loadings into the micropores, onto the mesopore surface, and in the mesopore interior of SPP were obtained. As pressure increases, -alkanes fill the micropores before loading the surface and then the interior of the mesopore, while furan and hexanoic acid adsorb strongly to the mesopore surface due to hydrogen bonding interactions with surface silanols. Hydrogen bonding interactions also draw hexanoic acid molecules in the micropore region toward the pore mouths, so their carboxylic acid group forms H-bonds with silanols, while the alkyl tails interact with the micropore walls. Mesopore condensation is observed for molecules below their critical point, and occurs when the Gibbs free energy of transfer into the mesopore interior and onto the mesopore surface converge. When hexanoic acid adsorption occurs in the presence of alkane solvents, then the selectivity and spatial distribution of hexanoic acid in the micropores and on the surface can be tuned by adjusting the fluid pressure and the alkane length and/or branching.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operator-level quantum acceleration of non-logconcave sampling

Sampling from probability distributions of the form 𝝈 ∝ e −𝜷V , where V is a continuous potential, is a fundamental task across physics, chemistry, biology, computer science, and statistics. However, when V is nonconvex, the resulting distribution becomes non-logconcave, and classical methods such as Langevin dynamics often exhibit poor performance. We introduce a quantum algorithm that provably accelerates a broad class of continuous-time sampling dynamics. For Langevin dynamics, our method encodes the target Gibbs measure into the amplitudes of aquantum state, identified as the kernel of a block matrix derived from a factorization of the Witten Laplacian operator. This connection enables Gibbs sampling via singular value thresholding and yields up to a quartic quantum speedup over best-knownclassical Langevin-based methods in the non-logconcave setting. Building on this framework, we further develop the first quantum algorithm that accelerates replica exchange Langevin diffusion, a widely used method for sampling from complex, rugged energy landscapes.

97 MATHEMATICS AND COMPUTING↗

Water chemistry in flume channel and hyporheic zone (i.e., porewater) associated with: “Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry”

Dissolved oxygen (DO), total organic carbon (TOC), total nitrogen (TN), molecular data for organic matter, and biochemical reactions for surface water and porewater (i.e., hyporheic zone) collected from a water recirculating flume located at the University of Texas, Austin. The flume contained real river water from Lower Colorado River(Austin, TX) and clean sand. Hyporheic exchange in the flume was induced through The study aims to understand relationships between aerobic metabolism of organic matter and molecular characteristics of organic matter, such as thermodynamic signature and nitrogen content, through the extent of the hyporheic zone at 10 cm- resolution, and through time. During the experiment, organic matter (dry leaves) was added to the flume and removed after 24 hours. The water samples were collected before the addition of leaves, at the time of removal of leaves, and at hour 72. The water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) and total organic carbon (TOC) and total nitrogen (TN) analysis. Dissolved oxygen content throughout the surface water and the hyporheic zone of the flume was measured with a large planar optode. This data package is associated with the publication ’ Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry’ published in Environmental Science and Technology (Turețcaia et al., 2023 https://doi.org/10.1021/acs.est.3c04765). The dataset is comprised of five folders (1) Diss_O2_pic, (2) input_files (3) output_files; (4) python_code; and (5) R_code . Diss_O2_pic contains siximages of dissolved oxygen distribution in a bedform at hours 0, 24, and 72 of the experiment conducted in a large recirculation flume. Images are in separate R and G channels (i.e., RGB). The input_files contains (1) a csv file with FTICR peaks identified within each sample, (2) a csv file with molecular information pertinent to FTICR data with Gibbs free energy calculations adjusted for environmental temperature, (3) a csv file containing concentrations of non-purgeable organic carbon measured throughout the experiment , (4) a csv file containing concentrations of total nitrogen measured throughout the experiment, (5) a csv file containing total biochemical reactions (i.e., transformations) identified in the dataset, (6) a csv containing transformation profiles, and (7) a csv file containing transformations with formulas, and (8) a jpg file with schematic representation of locations for sample collection. The output_files contains (1) and xlsx file containing percent biochemical reactions containing nitrogen identified across all 39 sample, (2) a csv file of merged FTICR data and molecular information files, (3) a csv files containing average Gibbs free energy within sampling domains and at each sampling location, (4) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 0, (5) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 24, (6) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 72, (7) a csv file with percent chemical classes identified across sampling locations at hour 0, (8) a csv file with percent chemical classes identified across sampling locations at hour 24, (9) a csv file with percent chemical classes identified across sampling locations at hour 72, and (10) a csv file containing percent nitrogen containing biochemical reactions identified across sampling locations at hours 0, 24, and 72. The python_code contains seven ipynb files which are Jupyter Notebooks used for data analysis and figures generation. The R_code contains 3 R files with R code used for data analysis and figures generation. This data package contains the processed data used in the associated manuscript. This data has not been previously published.

54 ENVIRONMENTAL SCIENCES↗

Equilipy: a python package for calculating phase equilibria

The CALPHAD (CALculation of PHAse Diagram) approach (Nigel Saunders & Miodownik, 1998) provides predictions for thermodynamically stable phases in multicomponent-multiphase materials across a wide range of temperatures. Consequently, the CALPHAD calculations became an essential tool in materials and process design (Luo, 2015). Such design tasks frequently require navigating a high-dimensional space due to multiple components involved in the system. This increasing complexity demands high-throughput CALPHAD calculations, especially in the rapidly evolving field of alloy design. In response to the need, we developed Equilipy an open-source Python package designed for calculating phase equilibria of multicomponent-multiphase systems. Equilipy is specifically tailored for high-throughput CALPHAD calculations, offering parallel computations across multiple processors and nodes with the given NPT input conditions namely elemental compositions (N), pressure (P), and temperature (T). Equilipy utilizes the program structure and Gibbs energy functions from the Fortran-based program, Thermochimica (Piro et al., 2013), with incorporating a new Gibbs energy minimization algorithm. This algorithm, originally developed by Capitani and Brown in 1987 (Capitani & Brown, 1987), has been revised and implemented to enhance the stability and performance of calculations. The Fortran codes are precompiled and interfaced with Python via F2PY, ensuring high computation speed. Benchmark tests shown in Figure 1 demonstrate that Equilipy’s computation speed is comparable to those of established commercial software, TC-Python and PanPython. This result highlights its efficiency and potential applications in various scientific and industrial fields.

97 MATHEMATICS AND COMPUTING↗

Design and Synthesis of PtPdNiCoMn High‐Entropy Alloy Electrocatalyst for Enhanced Alkaline Hydrogen Evolution Reaction: A Theoretically Supported Predictive Design Approach

Electrocatalytic hydrogen generation requires a multifunctional electrocatalyst with abundant active sites to drive multielectron transfer reactions. High entropy alloys (HEA) are five or more-elements with high configurational entropy are considered unique materials for next-generation electrocatalysts. Here, in this work, based on new screening guidelines for catalyst selections that combine density-functional theory calculated Gibbs formation-enthalpy with bond length and electronegativity variance, a novel HEA electrocatalyst consisting of five elements, namely, Pt, Pd, Ni, Co, and Mn has been designed. By simple room temperature electrodeposition, the designed catalyst is prepared and its hydrogen evolution reaction (HER) is explored and validated through experimental and theoretical approaches. The HEA demonstrated a superior HER activity with an overpotential of 22.6 mV at -10 mA cm -2 which outperforms Pt/C commercial catalyst. No evident degradation of the material is detected even after 100 hours of continuous operation under high current density. Moreover, the HEA has shown exceptional performance in harsh electrolyte conditions such as in simulated seawater and actual seawater. Remarkably, the density-functional theory calculated Gibbs formation-enthalpy is small (≈0 eV) compared to Pt/C placing the new HEA near the apex of Trasatti's model of Volcano plot, which is also suggestive of superior HER activity.

36 MATERIALS SCIENCE↗

Towards the Accurate Thermodynamic Characterization of Enzyme Reaction Mechanisms

We employed QM/MM molecular dynamics (MD) simulations to characterize the rate-limiting step of the glycosylation reaction of pancreatic α-amylase with combined DFT/molecular dynamics methods (PBE/def2-SVP : AMBER). Upon careful choice of four starting active site conformations based on thorough reactivity criteria, Gibbs energy profiles were calculated with umbrella sampling simulations within a statistical convergence of 1 -2 kcal · mol -1 . Nevertheless, Gibbs activation barriers and reaction energies still varied from 11.0 to 16.8 kcal · mol -1 and -6.3 to +3.8 kcal · mol -1 depending on the starting conformations, showing that despite significant state-of-the-art QM/MM MD sampling (0.5 ns/profile) the result still depends on the starting structure. In conclusion, the results supported the one step dissociative mechanism of Asp197 glycosylation preceded by an acid-base reaction by the Glu233, which are qualitatively similar to those from multi-PES QM/MM studies, and thus support the use of the latter to determine enzyme reaction mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of the Al-rich part of the Al-Cu phase diagram using cluster expansion and statistical mechanics

In this work, the thermodynamic properties of α-Al and other phases (GP zones, θ'', θ' and θ) in the Al-rich part of the Al-Cu system have been obtained by means of the cluster expansion formalism in combination with statistical mechanics. This information was used to build the Al-rich part of the Al-Cu phase-diagram taking into account vibrational entropic contributions for θ', as those of the other phases were negligible. The simulation predictions of the phase boundaries between α-Al and either θ'', θ' or θ phases as a function of temperature are in good agreement with experimental data and extend the phase boundaries to a wider temperature range. The DFT calculations reveal the presence of a number of metastable Guinier-Preston-zone type configurations that may coexist with α-Al and θ'' at low temperatures. They also demonstrate that θ' is the stable phase below 550K but it is replaced by θ above this temperature due to the vibrational entropic contribution to the Gibbs energy of θ'. This work shows how the combination of cluster expansion and statistical mechanics can be used to expand our knowledge of the phase diagram of metallic alloys and to provide Gibbs free energies of different phases that can be used as input in mesoscale simulations of precipitation.

36 MATERIALS SCIENCE↗

Machine learning enabled discovery of superhard and ultrahard carbon polymorphs

The demand for multifunctional materials has motivated the move from near-equilibrium materials to metastable i.e. out-of-equilibrium phases that can meet several desired target properties. The search for such metastable phases with exotic properties is non-trivial and often serendipitous. Inverse design approaches based on evolutionary search have been powerful tools, but such traditional searches have focused on identifying primarily stable and metastable materials with the lowest enthalpy. The inverse design of materials, with a focus on a desired property such as, for example, hardness is a challenging task because of the expensive computational cost involved in sampling multiple structures. The recent advances in machine learning have brought new powerful AI techniques to the forefront which can potentially revolutionize the inverse design and discovery of materials, especially metastable phases capable of meeting multifunctionality. Here, in this work, we develop and apply an automated reinforcement learning workflow for inverse design that integrates first principles physics and atomistic simulations with machine learning (ML), and high-performance computing to allow rapid exploration of the superhard and ultrahard metastable phases of Carbon. We demonstrate an automatic machine learning based inverse design workflow to map new undiscovered metastable states ranging from near equilibrium to those far-from-equilibrium that satisfy multiple property objectives, specifically bulk moduli, shear moduli and hardness. We create a comprehensive library of carbon stable and metastable phases with varying hardness and subsequently shortlist 10 top performing candidate carbon structures, including two newly reported phases, based on their hardness and characterize their temperature dependent mechanical properties. A neural network model is built using featurization of allotropes of carbon to predict the quasi-harmonic Gibbs free energies. The Gibbs free energies of the top performing phases are analyzed to get an estimate of the experimental synthesizability of these superhard and ultrahard carbon phases. In general, we show using machine learning based inverse design approaches how hitherto inaccessible metastable states can be identified and potentially synthesized to meet the demand for multifunctional materials.

Balasubramanian, Karthik [Univ. of Illinois, Chica↗

The solubility of La hydroxide and stability of La 3+ and La hydroxyl complexes at acidic to mildly acidic pH from 25 to 250 °C

The mobility of rare earth elements (REE) in natural hydrothermal systems can be assessed using geochemical modeling, which requires reliable thermodynamic data of relevant aqueous species. In this study, we evaluate the controls of pH and temperature on La speciation and the role of hydroxyl complexes in REE transport at hydrothermal conditions. Batch-type hydrothermal solubility experiments were conducted using synthetic La hydroxide powders equilibrated in perchloric acid-based aqueous solutions at temperatures between 150 and 250 °C and starting pH of 2 to 5. The La hydroxide solubility is retrograde with temperature and displays a strong pH dependence with a decrease in La concentrations from acidic to mildly acidic pH spanning between 3 and 5 orders of magnitude (e.g. log La molality of –2.5 to –7.2 at 250 °C). Thermodynamic optimizations using GEMSFITS allow to retrieve the standard partial molal Gibbs energies for the La 3+ aqua ion and the formation constants for the La hydroxyl species (i.e., LaOH 2+ , La(OH) 2 + , La(OH) 3 0 ) between 25 and 250 °C. A comparison between the experimentally derived thermodynamic properties with the calculated values from the Helgeson-Kirkham-Flowers equation of state parameters indicates an increased divergence with temperature. Discrepancies in standard partial molal Gibbs energies range between ~ 1 – 12 kJ/mol and result in a predicted La hydroxide solubility differing by up to 3 orders of magnitude at 250 °C. Speciation calculations indicate a higher stability of La 3+ and LaOH 2+ over the other La hydroxyl species in the studied pH range of 3.4 to 6. Here, the optimized thermodynamic properties for La aqueous species have important implications for modeling the solubility of REE minerals such as monazite and the mobility of REE in hydrothermal systems.

58 GEOSCIENCES↗

The low-temperature heat capacity and thermodynamic properties of greigite (Fe 3 S 4 )

Heat capacity measurements provide important insights into the energetic, thermodynamic, and magnetic properties of materials. Herein we report the heat capacity of greigite (Fe 3 S 4 ) from 1.8 to 300 K. Greigite is a magnetic spinel mineral and through a ferromagnetic magnon term, C fsw = B fsw T 3/2 , ferrimagnetic ordering is observed in the low-temperature heat capacity. Using a set of theoretical fits of the experimental data, we calculate the thermodynamic functions, including the standard entropy ($Δ_{0}^{T}$S m °). Greigite is important in iron sulfide formation and reaction pathways in environmental, ore-forming, and technological settings and previous work has measured enthalpies $ΔH_{r}°$ of formation and decomposition to neighboring phases. In this work, the stability of greigite relative to the elements is demonstrated with a negative Gibbs energy ($ΔG_{r}°$) of formation and the stability relative to decomposition products of pyrrhotite (FeS 1.092 ) and pyrite (FeS 2 ) is demonstrated with a positive Gibbs energy ($ΔG_{r}°$) of decomposition. Values of the standard thermodynamic functions C p,m °, $Δ_{0}^{T}$S m °, $Δ_{0}^{T}$H m °, and Φ m ° are tabulated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermodynamic properties and superconductivity of natural carrollite (CuCo 2 S 4 )

The thermodynamic properties of natural carrollite with a formula Cu 0.92 Co 2.07 S 4 are studied using low temperature heat capacity and high temperature oxidative solution calorimetry. The standard thermodynamic functions at 298.15 K are: C p,m °, S m °, H m °, and Φ m ° are 158.48 J∙K −1 ∙mol −1 , 176.33 J∙K −1 ∙mol −1 , 28.40 kJ∙mol −1 , and 81.07 kJ∙mol −1 with an estimated error of 1%. The enthalpies (Δ f H), entropies (Δ f S), and Gibbs energies of formation (Δ f G) from elements at 298.15 K are: −344.46 ± 12.87 kJ∙mol −1 , −45.22 ± 1.81 J∙K −1 ∙mol −1 , and −331.14 ± 1.89 J∙K −1 ∙mol −1 . The stability of carrollite relative to the elements is demonstrated with a negative Gibbs energy (ΔG r °) of formation for several temperatures between 0 and 300 K. Furthermore, a superconductivity transition, which has been observed previously for synthetic carrollite, is confirmed by both the low temperature heat capacity and magnetization measurements.

Chemistry↗

Thermodynamic evaluation and modeling of the CeF 3 -LaF 3 -LiF-NaF system

The thermodynamic properties of the LiF-NaF-CeF 3 -LaF 3 pseudo-quaternary system have been evaluated, and models for the relevant phases have been revised or newly developed. The solid solubility of NaF in LaF 3 and CeF 3 was described in the model based on reported phase-equilibria observations and results from density functional theory calculations. The Gibbs energy functions for the NaCeF 4 and NaLaF 4 phases have been updated with recently reported thermochemical measurements. The Gibbs energy functions and model relations for the LiF-NaF-LaF 3 and LiF-NaF-CeF 3 pseudo-ternary systems were successfully optimized based on thermochemical properties and phase equilibria observations.

CALPHAD↗