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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 343 records · Page 19

Thermodynamic investigation of the NaCl-KCl salt system from 25 to 950 °C

NaCl-KCl molten salt system has been proposed as a primary component of several promising heat transfer eutectics and fuel host for Generation IV molten salt reactors (MSR). In this work, several key thermodynamic parameters, including high temperature enthalpies, isobaric heat capacities (C p ) and molar enthalpies of mixing (ΔH mix ), of the NaCl -KCl system (NaCl, 75mol% NaCl – 25mol% KCl, 51mol% NaCl – 49mol% KCl, 25mol% NaCl – 75mol% KCl, and KCl) were measured by high temperature drop calorimetry (HTDC) utilizing laser sealed nickel and aluminum crucibles. Salts were checked for phase purity by X-ray diffraction (XRD), and water content by Karl Fischer coulometric titrimetry and thermogravimetric analysis (TGA). Thermo-mechanical analysis (TMA) utilizing custom-built boron nitride (BN) crucibles was employed to determine temperatures of phase transitions (solid $\rightarrow$ liquid) for the salts and plotted against the pseudobinary phase diagram for the NaCl-KCl system. Small deviations (3-10 %) were found among C p values obtained from HTDC, differential scanning calorimetry (DSC), and NIST, comparable to the average uncertainty based on two standard deviations of measured data that are ~6% for DSC and ~3% for HTDC. Additionally, the measured enthalpies and C p values of mixed NaCl-KCl salts (e.g., 51mol% NaCl – 49mol% KCl eutectic) were shown to behave as statistical mixtures of its pure endmembers, consistent with ΔH mix = ~ 0 kJ/mol at 800 °C, and a regular interaction parameter of Ω = 1.20 ± 0.76 kJ/mol. In conclusion, this study represents a step towards improved accuracy and precision in determinations of thermodynamic parameters of molten salts by using DSC, TMA, and HTDC, in completion of the Molten Salt Thermal Properties Database (MSTDB).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures

Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.

Thermodynamics↗

Hydrothermal solution calorimetry in acidic aqueous solutions and revisiting the standard partial molal thermodynamic properties of Nd 3+ from 25 to 300 °C

The mobility of rare earth elements (REE) can be predicted in aqueous fluids using geochemical modeling but the accuracy of these models strongly depends on the availability of robust thermodynamic properties for the REE aqueous species. The REE 3+ aqua ions are important in the derivation of the formation constants of all the major REE complexes including the chloride, sulfate, and fluoride species which predominate in many hydrothermal-magmatic systems. However, the thermodynamic properties of the REE 3+ aqua ions are still commonly derived from the Helgeson-Kirkham-Flowers (HKF) equation of state parameters tabulated several decades ago. The standard state thermodynamic properties at reference conditions (25 °C and 1bar) and their extrapolations to high temperature need to be verified, if not revised, based on hydrothermal experiments. In this study, the enthalpy of solution was measured for synthetic Nd hydroxide from 25 to 150 ºC to retrieve the standard partial molal thermodynamic properties of Nd 3+ as a function of temperature. The experiments were conducted in aqueous perchloric acid based solutions with starting pH of 2 and varying ionic strength (0.01 to 0.09 mol/kg NaClO 4 ). The standard partial molal enthalpy of formation (Δ f H°) of Nd 3+ derived from the experimental study displays differences of up to 10 kJ/mol compared to the enthalpy values derived from the HKF equation of state in the studied temperature range. These inaccuracies are resolved by adjusting the standard partial molal Gibbs energy of formation (Δ f G°) of Nd 3+ at 25 °C and 1 bar from -672.0 to -679.7 kJ/mol. The heat capacity function (C p °) derived between 25 and 150 ºC can be described by: C p ° = a 0 + a 1 ·T + a 2 ·T -2 , with a 0 = 1256, a 1 = -2.68, a 2 = -55.56·10 6 and T in Kelvin. A set of recommended thermodynamic properties is provided for the Nd 3+ aqua ions and corrections are provided for the chloride and fluoride species to remain internally consistent with the experimentally derived properties. These results allow predicting accurately the solubility of monazite between 25 and 300 ºC. Before these corrections, the properties for the Nd 3+ aqua ions derived from the HKF parameters resulted in up to ~1.5 orders of magnitude lower monazite solubility than determined experimentally. Here, a revision of the REE +3 aqua ions properties is necessary to accurately predict the mobility of REE in hydrothermal acidic solutions.

58 GEOSCIENCES↗

Equilibrium-gated pattern formation: How molecular dissociation thermodynamics drive emergent behavior in dissipative polymeric systems

Emergent patterns in biological systems arise through dissipative processes that balance reaction and transport phenomena, producing highly functional properties from self-regulating mechanisms. Synthetic fabrication, by contrast, often relies on user-controlled, multistep methods that lack the self-organizing capabilities of natural systems. Inspired by nature, we sought chemical systems that integrate strongly coupled reaction and transport phenomena, identifying frontal ring-opening metathesis polymerization (FROMP) as a method capable of creating diverse forms and functions through reactive processing. By employing discrete molecular initiators, FROMP allows precise control of key reaction steps—inhibition, initiation, and propagation. Using an integrated computational and experimental framework, we uncover how near-equilibrium inhibition dynamics, coupled with far-from-equilibrium reaction kinetics, drive pattern formation in frontally polymerized synthetic materials. We propose the concept of equilibrium-gated pattern formation, demonstrating how initiator chemistry can be tuned to achieve programmable macroscale properties. Our study reveals a surprising insight: Emergent behavior in FROMP systems arises from the inhibition-dominated regime of resin composition, expanding prior observations that such behavior is confined to a narrow compositional space near the boundary between front quenching and uniform front propagation. We identify a broader compositional window, far from the quenching regime, where emergent behavior reliably manifests. This expanded design space significantly enhances the operational flexibility of reactive systems and their capacity for self-organization. Furthermore, these insights provide a roadmap for designing bioinspired materials with self-organizing capabilities, unlocking possibilities in synthetic manufacturing.

Architected Polymers↗

Computer program for thermodynamic analysis of open cycle multishaft power system with multiple reheat and intercool

A computer program to analyze power systems having any number of shafts up to a maximum of five is presented. On each shaft there can be as many as five compressors and five turbines, along with any specified number of intervening intercoolers and reheaters. A recuperator can be included. Turbine coolant flow can be accounted for. Any fuel consisting entirely of hydrogen and/or carbon can be used. The program is valid for maximum temperatures up to about 2000 K (3600 R). The system description, the analysis method, a detailed explanation of program input and output including an illustrative example, a dictionary of program variables, and the program listing are explained.

Glassman, A. J.↗

Early chemical history of the solar system

By using equilibrium thermodynamics, the sequence of condensation of mineral phases from a cooling nebula of solar composition has been calculated. The theoretical models suggest that the chemistry and mineralogy of Ca-Al-rich inclusions in C2 and C3 chondrites were established during condensation at temperatures above 1300 K. Fractionation of such inclusions is necessary to account for the refractory element depletions of ordinary and enstatite chondrites relative to the carbonaceous chondrites. The metal-silicate fractionation in ordinary chondrites took place in the nebula at a temperature below 1000 K and at .00001 atm total pressure. The volatile element depletion of C2 and C3 chondrites relative to C1 chondrites took place during chondrule formation: the most volatile elements are depleted in ordinary chondrites because they accreted before these elements were totally condensed.

Grossman, L.↗

Impact and collisional processes in the solar system

The mechanical and thermodynamic aspects of shock impact cratering and accretionary processes on solid planets and satellites are being investigated experimentally. The recently proposed model of Melosh, describing the physics controlling the size and velocity of only lightly shocked spalled ejecta surrounding the crushed rock region of an impact crater, was studied at the Ames gun facility. Spall velocity measurements using lead and aluminum bullets were conducted. In addition, shock temperatures of silicates and volatile-bearing minerals were measured using radiative techniques. Finally impact devolatilization of minerals and accretion of planetary atmospheres were examined. Measurements of the release isentropes of CaCO3 were carried out. The effect on the water budgets of planets of reactions which occur when metallic iron (which would be present in chondritic material) is introduced into a simple accretion model is under investigation.

Ahrens, T. J.↗

Impact and Collisional Processes in the Solar System

The mechanical and thermodynamic aspects of shock impact cratering and accretionary processes on solid planets and satellites are being investigated experimentally. The recently proposed model of Melosh, describing the physics controlling the size and velocity of only lightly shocked spalled ejecta surrounding the crushed rock region of an impact crater, was studied at the Ames gun facility. Spall velocity measurements using lead and aluminum bullets were conducted. In addition, shock temperatures of silicates and volatile bearing minerals were measured using radiative techniques. Finally impact devolatilization of minerals and accretion of planetary atmospheres were examined. Measurements of the release isentropes of CaCO3 were carried out. The effect on the water budgets of planets of reactions which occur when metallic iron (which would be present in chondritic material) is introduced into a simple accretion model is under investigation.

Ahrens, T. J.↗

Generative Thermodynamic Computing

Here, we introduce a generative modeling framework for thermodynamic computing, in which structured data are synthesized from noise by the natural time evolution of a physical system governed by Langevin dynamics. While conventional diffusion models use neural networks to perform denoising, here the information needed to generate structure from noise is encoded by the dynamics of a thermodynamic system. Training proceeds by maximizing the probability with which the computer generates the reverse of a noising trajectory, which ensures that the computer generates data with minimal heat emission. We demonstrate this framework within a digital simulation of a thermodynamic computer. If realized in analog hardware, such a system would function as a generative model that produces structured samples without the need for artificially injected noise or active control of denoising.

Whitelam, Stephen [Lawrence Berkeley National Labo↗

Environmental Thermodynamic Effects on Future Changes of Mesoscale Convective Systems and Isolated Deep Convection Over the US: A Case Study

Mesoscale convective systems (MCSs) and isolated deep convection (IDC) significantly influence local weather conditions and the hydrological cycle across the United States. Their future changes under warming is critical to the society. However, the exact impacts of thermodynamic environmental changes on them are difficult to resolve using climate model simulations which integrate both dynamic and thermodynamic factors. This study explores a theoretical modeling approach to isolate environmental thermodynamic effects on their future changes through a case study. For a 50-day period during the 2020 summer, a pair of convection-permitting model simulations indicate contrasting changes in MCSs and IDC between inland and coastal regions under pseudo global warming. Driven by the thermodynamic environments of these simulations, a single-column parcel model indicates a decrease in the frequency of IDC occurrences, along with increases in duration and precipitation amount under warming, attributable to rising most unstable convective available potential energy (MUCAPE), convective inhibition (MUCIN), and precipitable water (PW). A multi-column parcel model reveals contrasting changes in the frequency and mean area of MCSs between inland and coastal regions, underscoring the increase in mean MUCIN over inland regions and increases in mean MUCAPE and PW over coastal regions. The increase in mean MCS area over inland regions is linked to the interplay between accelerated gust fronts and enhanced subsidence strength, which is further traced to the unchanged mean MUCIN but increased mean MUCAPE in large-scale environments. In conclusion, these case study results suggest a major role of thermodynamic environmental changes in controlling characteristics of MCSs and IDC under warming.

Mesoscale convective system↗

Unsupervised discovery of extreme weather events using universal representations of emergent organization

Spontaneous self-organization is ubiquitous in systems far from thermodynamic equilibrium. While organized structures that emerge dominate transport properties, universal representations that identify and describe these key objects remain elusive. Here, we introduce a theoretically grounded framework for describing emergent organization that, via data-driven algorithms, is constructive in practice. Its building blocks are spacetime lightcones that embody how information propagates across a system through local interactions. We show that predictive equivalence classes of lightcones—local causal states—capture organized behaviors in complex spatiotemporal systems. Employing an unsupervised physics-informed machine learning algorithm and a high-performance computing implementation, we demonstrate automatically discovering organized structures in two real-world domain science problems. We show that local causal states identify vortices and track their power-law decay behavior in two-dimensional fluid turbulence. We then show how to detect and track familiar extreme weather events—hurricanes and atmospheric rivers—and discover other novel structures associated with precipitation extremes in high-resolution climate data at the grid-cell level.

Rupe, Adam [Pacific Northwest National Laboratory ↗