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DOE OSTI2020

Proton-coupled electron transfer across benzimidazole bridges in bioinspired proton wires

Designing molecular platforms for controlling proton and electron movement in artificial photosynthetic systems is crucial to efficient catalysis and solar energy conversion. The transfer of both protons and electrons during a reaction is known as proton-coupled electron transfer (PCET) and is used by nature in myriad ways to provide low overpotential pathways for redox reactions and redox leveling, as well as to generate bioenergetic proton currents. Herein, we describe theoretical and electrochemical studies of a series of bioinspired benzimidazole-phenol (BIP) derivatives and a series of dibenzimidazole-phenol (BI 2 P) analogs with each series bearing the same set of terminal proton-accepting (TPA) groups. The set of TPAs spans more than 6 pK a units. These compounds have been designed to explore the role of the bridging benzimidazole(s) in a one-electron oxidation process coupled to intramolecular proton translocation across either two (the BIP series) or three (the BI 2 P series) acid/base sites. These molecular constructs feature an electrochemically active phenol connected to the TPA group through a benzimidazole-based bridge, which together with the phenol and TPA group form a covalent framework supporting a Grotthuss-type hydrogen-bonded network. Infrared spectroelectrochemistry demonstrates that upon oxidation of the phenol, protons translocate across this well-defined hydrogen-bonded network to a TPA group. The experimental data show the benzimidazole bridges are non-innocent participants in the PCET process in that the addition of each benzimidazole unit lowers the redox potential of the phenoxyl radical/phenol couple by 60 mV, regardless of the nature of the TPA group. Using a series of hypothetical thermodynamic steps, density functional theory calculations correctly predicted the dependence of the redox potential of the phenoxyl radical/phenol couple on the nature of the final protonated species and provided insight into the thermodynamic role of dibenzimidazole units in the PCET process. This information is crucial for developing molecular “dry proton wires” with these moieties, which can transfer protons via a Grotthuss-type mechanism over long distances without the intervention of water molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1985

Thermodynamics of clathrate hydrate at low and high pressures with application to the outer solar system

The thermodynamic stability of clathrate hydrate is calculated to predict the formation conditions corresponding to a range of solar system parameters. The calculations were performed using the statistical mechanical theory developed by van der Waals and Platteeuw (1959) and existing experimental data concerning clathrate hydrate and its components. Dissociation pressures and partition functions (Langmuir constants) are predicted at low pressure for CO clathrate (hydrate) using the properties of chemicals similar to CO. It is argued that nonsolar but well constrained noble gas abundances may be measurable by the Galileo spacecraft in the Jovian atmosphere if the observed carbon enhancement is due to bombardment of the atmosphere by clathrate-bearing planetesimals sometime after planetary formation. The noble gas abundances of the Jovian satellite Titan are predicted, assuming that most of the methane in Titan is accreted as clathrate. It is suggested that under thermodynamically appropriate conditions, complete clathration of water ice could have occurred in high-pressure nebulas around giant planets, but probably not in the outer solar nebula. The stability of clathrate in other pressure ranges is also discussed.

Lunine, J. I.↗

NASA NTRS1986

Non-solar noble gas abundances in the atmosphere of Jupiter

Lunine, Jonathan I.↗

DOE OSTI2023

Optimized thermodynamic properties of REE aqueous species (REE 3+ and REEOH 2+ ) and experimental database for modeling the solubility of REE phosphate minerals (monazite, xenotime, and rhabdophane) from 25 to 300 °C

Rare earth elements (REE) are critical elements found in monazite, xenotime, and hydrated REE phosphates which typically form in hydrothermal mineral deposits. Accurate predictions of the solubility of these REE phosphates and the speciation of REE in aqueous fluids are both key to understanding the controls on the transport, fractionation, and deposition of REE in natural systems. Previous monazite and xenotime solubility experiments indicate the presence of large discrepancies between experimentally derived solubility constants versus calculated solubilities by combining different data sources for the thermodynamic properties of minerals and aqueous species at hydrothermal conditions. In this study, these discrepancies were resolved by using the program GEMSFITS to optimize the standard partial molal Gibbs energy of formation (Δ f G° 298 ) of REE aqueous species (REE 3+ and REE hydroxyl complexes) at 298.15 K and 1 bar while keeping the thermodynamic properties fixed for the REE phosphates. A comprehensive experimental database was compiled using solubility data available between 25 and 300 °C. The latter permits conducting thermodynamic parameter optimization of Δ f G° 298 for REE aqueous species. Optimal matching of the rhabdophane solubility data between 25 and 100 °C requires modifying the Δ f G° 298 values of REE 3+ by 1–6 kJ/mol, whereas matching of the monazite solubility data between 100 and 300 °C requires modifying the Δ f G° 298 values of both REE 3+ and REEOH 2+ by ~15–31 kJ/mol and ~2–10 kJ/mol, respectively. For xenotime, adjustments of Δ f G° 298 values by 1–26 kJ/mol are only necessary for the REE 3+ species. The optimizations indicate that the solubility of monazite in acidic solutions is controlled by the light (L)REE 3+ species at <150 °C and the LREEOH 2+ species at >150 °C, whereas the solubility of xenotime is controlled by the heavy (H)REE 3+ species between 25 and 300 °C. Based on the optimization results, we conclude that the revised Helgeson-Kirkham-Flowers equation of state does not reliably predict the thermodynamic properties of REE 3+ , REEOH 2+ , and likely other REE hydroxyl species at hydrothermal conditions. We therefore provide an experimental database (ThermoExp_REE) as a basic framework for future updates, extensions with other ligands, and optimizations as new experimental REE data become available. As a result, the optimized thermodynamic properties of aqueous species and minerals are available open access to accurately predict the solubility of REE phosphates in fluid-rock systems.

58 GEOSCIENCES↗

DOE OSTI2024

Thermodynamic driving forces in contact electrification between polymeric materials

Abstract Contact electrification, or contact charging, refers to the process of static charge accumulation after rubbing, or even simple touching, of two materials. Despite its relevance in static electricity, various natural phenomena, and numerous technologies, contact charging remains poorly understood. For insulating materials, even the species of charge carrier may be unknown, and the direction of charge-transfer lacks firm molecular-level explanation. Here, we use all-atom molecular dynamics simulations to investigate whether thermodynamics can explain contact charging between insulating polymers. Based on prior work suggesting that water-ions, such as hydronium and hydroxide ions, are potential charge carriers, we predict preferred directions of charge-transfer between polymer surfaces according to the free energy of water-ions within water droplets on such surfaces. Broad agreement between our predictions and experimental triboelectric series indicate that thermodynamically driven ion-transfer likely influences contact charging of polymers. Furthermore, simulation analyses reveal how specific interactions of water and water-ions proximate to the polymer-water interface explain observed trends. This study establishes relevance of thermodynamic driving forces in contact charging of insulators with new evidence informed by molecular-level interactions. These insights have direct implications for future mechanistic studies and applications of contact charging involving polymeric materials.

36 MATERIALS SCIENCE↗

NASA NTRS2014

Liquid Oxygen Thermodynamic Vent System Testing with Helium Pressurization

This report presents the results of several thermodynamic vent system (TVS) tests with liquid oxygen plus a test with liquid nitrogen. In all tests, the liquid was heated above its normal boiling point to 111 K for oxygen and 100 K for nitrogen. The elevated temperature was representative of tank conditions for a candidate lunar lander ascent stage. An initial test series was conducted with saturated oxygen liquid and vapor at 0.6 MPa. The initial series was followed by tests where the test tank was pressurized with gaseous helium to 1.4 to 1.6 MPa. For these tests, the helium mole fraction in the ullage was quite high, about 0.57 to 0.62. TVS behavior is different when helium is present than when helium is absent. The tank pressure becomes the sum of the vapor pressure and the partial pressure of helium. Therefore, tank pressure depends not only on temperature, as is the case for a pure liquid-vapor system, but also on helium density (i.e., the mass of helium divided by the ullage volume). Thus, properly controlling TVS operation is more challenging with helium pressurization than without helium pressurization. When helium was present, the liquid temperature would rise with each successive TVS cycle if tank pressure was kept within a constant control band. Alternatively, if the liquid temperature was maintained within a constant TVS control band, the tank pressure would drop with each TVS cycle. The final test series, which was conducted with liquid nitrogen pressurized with helium, demonstrated simultaneous pressure and temperature control during TVS operation. The simultaneous control was achieved by systematic injection of additional helium during each TVS cycle. Adding helium maintained the helium partial pressure as the liquid volume decreased because of TVS operation. The TVS demonstrations with liquid oxygen pressurized with helium were conducted with three different fluid-mixer configurations-a submerged axial jet mixer, a pair of spray hoops in the tank ullage, and combined use of the axial jet and spray hoops. A submerged liquid pump and compact heat exchanger located inside the test tank were used with all the mixer configurations. The initial series without helium and the final series with liquid nitrogen both used the axial jet mixer. The axial jet configuration successfully demonstrated the ability to control tank pressure; but in the normal-gravity environment, the temperature in the upper tank region (ullage and unwetted wall) was not controlled. The spray hoops and axial jet combination also successfully demonstrated pressure control as well as temperature control of the entire tank and contents. The spray-hoops-only configuration was not expected to be a reliable means of tank mixing because there was no direct means to produce liquid circulation. However, surprisingly good results also were obtained with the sprayhoops- only configuration (i.e., performance metrics such as cycle-averaged vent flowrate were similar to those obtained with the other configurations). A simple thermodynamic model was developed that correctly predicted the TVS behavior (temperature rise or pressure drop per TVS cycle) when helium was present in the ullage. The model predictions were correlated over a range of input parameters. The correlations show that temperature rise or pressure drop per cycle was proportional to both helium mole fraction and tank heat input. The response also depended on the tank fill fraction: the temperature rise or pressure drop (per TVS cycle) increased as the ullage volume decreased.

Thermodynamic vent system↗

DOE OSTI2025

Evaluation of New Additions to OLI Software in Predicting Mercuric and Mercurous Species in Liquid Waste Operations

Speciation of mercury during the pretreatment steps of tank waste processing is critical to successful mercury removal prior to vitrification during Liquid Waste Operations (LWO) at SRS. OLI software has been used to predict mercury speciation and activity throughout LWO. The OLI software operates based on a thermodynamic framework called the Mixed Solvent Electrolyte (MSE) framework. The MSE framework allows prediction in theoretically infinitely dilute to concentrated mixtures (e.g., purely solute solutions). Before modification to the MSE framework databanks, certain critical mercury species were missing in the MSE databank, and some thermodynamic data needed to be updated for the OLI software to accurately predict mercury chemical species in SRS waste tanks. To better reflect streams across LWO, new mercury species were integrated into the MSE database. To evaluate the changes to the OLI MSE framework per the Technical Task Request (TTR) and the Task Technical and Quality Assurance Plan (TTQAP), waste stream compositions from Tanks 38, 43, and Tank 50 decontaminated salt solution (DSS) were used as model inputs. Models were developed and executed using both the old and new databases. Compositional analyses from caustic Tank 50 DSS and caustic Tanks 38 and 43 were used as the input streams. These streams represent the most comprehensive chemical data sets where both mercury and tank constituents were measured together. Results for Tank 50 DSS predict HgO as the predominant species in both databases. Both methyl and dimethyl Hg species are present when the new database is ‘on’ and are not predicted with the new database turned ‘off’. The new database predicts a greater amount of HgO and a greater fraction of it in the solid phase. Pourbaix diagrams (potential vs. pH) generated for each Tank 50 DSS were identical regardless of which database was used. Elemental Hg and HgO were predicted in the water stable region under basic conditions. Tanks 38 and 43 follow similar trends as the Tank 50 DSS models. Unlike Tanks 38 and 50 DSS, the Tank 43 Pourbaix plot shows a region of stability for an aqueous HgOHCO3 - species between approximately pH 7-11. In all streams, when MeHg+ is included in the inputs, the new database predicts aqueous MeHgOH as the dominant species. If elemental or dimethyl mercury is in the waste stream, the new database model predicts they are unchanged and remain in those states and quantities. Additionally, the total mercury values are reported for both the measured input data and the OLI output data for all considered tanks. The summary indicates that the percentage error between the measured and calculated values is less than 1% in all cases The reconciliations and generation of the Pourbaix diagrams for Tank 50 DSS took approximately ten times longer with the new database ‘on’. In addition, over the course of that time, models with the new database ‘on’ were more likely to crash or display an error. Some modest performance improvements were noted when modeling with an i7 processor versus an i5. An example error is found in Appendix A. Furthermore, Appendix B provides V&V for two chemical systems analyzed with the OLI software, results were satisfactory. It is recommended to utilize the new databases (i.e., HCO.ddb and SR-Hg.ddb) in future Savannah River Mission Completion applications of OLI to represent pseudo steady-state. Furthermore, the integration and utilization of the new databases (i.e., HCO.ddb and SR-Hg.ddb) in modeling applications (e.g., Aspen) is also recommended.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Predicting phase behavior in high entropy and chemically complex alloys

The interest in high entropy alloys and other metallic compounds with four or more elements at near-equiatomic ratios has drawn attention to the ability to rapidly predict phase behavior of these complex materials, particularly where existing thermodynamic data are lacking. In this paper, we discuss aspects of this from the point of view of predicting without utilizing (or fitting) experimental data. Of particular interest are heuristic approaches that provide prediction of single-phase compositions, more rigorous approaches that tackle the thermodynamics from a more fundamental point of view, and simulation approaches that provide further insight into the behaviors. This paper covers cases of all three of these, in order to examine the strengths and weaknesses of each approach, and to indicate directions where these may be utilized and improved upon. Of particular interest is moving beyond “which composition may form a solid solution,” to recognizing the importance of underlying thermodynamic realities that affect the temperature- and composition-dependent transformations of these materials.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Degenerate parametric down-conversion facilitated by exciton-plasmon polariton states in a nonlinear plasmonic cavity

Abstract We study the effect of degenerate parametric down-conversion (DPDC) in an ensemble of two-level quantum emitters (QEs) coupled via near-field interactions to a single surface plasmon (SP) mode of a nonlinear plasmonic cavity. For this purpose, we develop a quantum driven-dissipative model capturing non-equilibrium dynamics of the system in which incoherently pumped QEs have transition frequency tuned near the second-harmonic response of the SPs. Considering the strong coupling regime, i.e. the SP-QE interaction rate exceeds system dissipation rates, we find a critical SP-QE coupling attributed to the phase transition between normal and lasing steady states. Examining fluctuations above the system’s steady states, we predict new elementary excitations, namely, the exciton-plasmon polaritons formed by the two-SP quanta and single-exciton states of QEs. The contribution of two-SP quanta results in the linear scaling of the SP-QE interaction rate with the number of QEs,  o , as opposed to the  o -scaling known for the Dicke and Tavis–Cummings models. We further examine how SP-QE interaction scaling affects the polariton dispersions and power spectra in the vicinity of the critical coupling. For this purpose, we compare the calculation results assuming a finite ensemble of QEs and the model thermodynamic limit. The calculated power spectra predict an interplay of coherent photon emission by QEs near the second-harmonic frequency and correlated photon-pair emission at the fundamental frequency by the SPs (i.e. the photonic DPDC effect).

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

First-principles equation of state of CHON resin for inertial confinement fusion applications

A wide-range (0 to 1044.0 g/ cm 3 and 0 to 10 9 K) equation-of-state (EOS) table for a CH 1.72 O 0.37 N 0.086 quaternary compound has been constructed based on density-functional theory (DFT) molecular-dynamics (MD) calculations using a combination of Kohn-Sham DFT MD, orbital-free DFT MD, and numerical extrapolation. The first-principles EOS data are compared with predictions of simple models, including the fully ionized ideal gas and the Fermi-degenerate electron gas models, to chart their temperature-density conditions of applicability. The shock Hugoniot, thermodynamic properties, and bulk sound velocities are predicted based on the EOS table and compared to those of C-H compounds. The Hugoniot results show the maximum compression ratio of the C-H-O-N resin is larger than that of CH polystyrene due to the existence of oxygen and nitrogen; while the other properties are similar between CHON and CH. Radiation hydrodynamic simulations have been performed using the table for inertial confinement fusion targets with a CHON ablator and compared with a similar design with CH. Here, the simulations show CHON outperforms CH as the ablator for laser-direct-drive target designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Simulation of a rapid compression machine for evaluation of ignition chemistry and soot formation using gasoline/ethanol blends

Due to the projected decline of demand for gasoline in light duty engines and the advent of ethanol as a green fuel, the use of gasoline/ethanol blend fuels in heavy duty applications are being investigated as they are projected to have lower cost and lower lifecycle green house gas (GHG) emissions. In heavy duty engines, the primary mode of combustion is mixing controlled combustion where wide range of mixture conditions (equivalence ratio) exist. Soot emissions of these fuels in richer conditions are not well understood. The goal of this research is to evaluate some commercially available soot modeling codes for the particulate matter emissions from gasoline/ethanol fuel blends, especially at fuel rich conditions. A Rapid Compression Machine (RCM) is modeled in a three-dimensional numerical simulation using CONVERGE computational software using a reduced chemical kinetic mechanism with SAGE chemistry solver and a RANS k-ϵturbulence model with a sector model including the creviced piston. The creviced piston is used in the experimental setup to reduce boundary layer effects and to maintain a homogeneous core in the reaction cylinder. Computational fluid dynamics simulations are conducted for different gasoline-ethanol fuel blends from E10 (10% ethanol v/v) to E100. The fuel blend is modeled as a surrogate mixture of toluene, iso-octane, n-heptane for gasoline content, and ethanol. The computational results were validated against experimental results using pressure measurements and laser extinction diagnostics. Different soot models are investigated to evaluate their capability of predicting the sooting tendencies of fuel blends, especially in richer conditions experienced during mixing-controlled combustion. The experimental combustion characteristics such as the ignition delay of different blends of fuel are reasonably well predicted. The Particulate Size Mimic (PSM) model accurately predicts the soot generation characteristics of the different fuels, but the Hiroyasu-NSC model falls short in this regard. For accurate prediction of soot with the PSM model, the thermodynamic conditions during combustion must be accurately modeled. While the current computational modeling tools can produce accurate results for the prediction of particulate matter emissions, there is much work to be done in improving our understanding of the underlying fundamental processes.

Energy & Fuels↗

DOE OSTI2023

Evaluation of PBL Parameterization Schemes in WRF Model Predictions during the Dry Season of the Central Amazon Basin

Planetary Boundary Layer (PBL) parameterization schemes are employed to handle subgrid-scale processes on atmospheric models, playing a key role in accurately representing the atmosphere. Recent studies have shown that PBL schemes are particularly fundamental to the depiction of PBL height (PBLH), especially over the Amazon. In the present study, we investigated the performance of PBL schemes on the representation of meteorological variables, turbulent fluxes, PBL vertical structures, and PBLH over the central Amazon basin under dry conditions, taking advantage of observations from the Observations and Modeling of the Green Ocean Amazon campaign (GoAmazon2014/5) for validation and evaluation. Numerical experiments were carried out within the WRF model using eight PBL schemes for two dry periods from 2014 (typical year) and 2015 (El-Niño year), and results from the 1-km resolution domain were directly compared to hourly in situ observations. In general, all PBL schemes present good performance to reproduce meteorological variables, with nonlocal (local) PBL schemes producing better performance in the 2014 (2015) study period. All PBL schemes in general overestimate (>100%) daytime turbulent fluxes. Thermodynamic (daytime) vertical structures are better predicted than mechanical (nocturnal) ones. The local MYNN2.5 scheme showed the overall best performance for PBLH prediction, mainly at night.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

Computing Thermodynamics Of Cryostorage Tanks In Orbit

No-vent filling, boiloff, and other phenomena predicted. Cryogenic On-Orbit Liquid Analytical Tool (COOLANT) computer program developed to analyze thermodynamic processes required in maintaining and utilizing cryogen depot tank in microgravity environment. Code contains four major analysis modules, tank-geometry module, and data base of properties of fluids and other materials. COOLANT is modular, so algorithms and data bases upgraded and expanded as required. Written in FORTRAN 77.

Brown, N.↗

DOE OSTI2025

Implications of reduced-complexity aerosol thermodynamics on organic aerosol mass concentration and composition over North America

Atmospheric organic aerosol (OA) mass concentrations can be affected by water uptake through its impact on the gas–particle partitioning of semi-volatile compounds. Current chemical transport models (CTMs) neglect this process. We have implemented the Binary Activity Thermodynamics model coupled to a volatility basis set partitioning scheme in the GEOS-Chem CTM, providing an efficient reduced-complexity OA model that predicts relative-humidity-dependent mixing and partitioning thermodynamics, while limiting the impact on computational efficiency. We provide a quantitative assessment of this water-sensitive OA treatment, focusing on a subdomain over North America. The updated OA scheme predicts a spatiotemporal mean enhancement in surface-level OA mass concentration of 145 % for January 2019 and 76 % for July 2019 compared to GEOS-Chem's most advanced OA scheme. The temporal mean surface-level OA organic mass concentration can increase by up to ∼590 % for January 2019 and ∼280 % for July 2019, with the greatest enhancements occurring over the ocean. The updated OA scheme also quantifies the OA-associated water content. The simulations show how different OA precursors and related OA surrogates contribute and respond to water uptake, including that due to changes in temperature and relative humidity over the diurnal cycle in selected winter and summer months. These results are independent of future CTM improvements involving updates to chemical reaction schemes and emission inventories. Our water-sensitive OA scheme allows for a better representation of the seasonal and regional variations in OA mass concentration in CTMs.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Open-source Numerical Modeling of Solidification Cracking Susceptibility: Application to Refractory Alloy Systems

Introduction. Alloys such as aluminum, nickel-base, and austenitic stainless steels are susceptible to solidification cracking during welding and 3D printing. Compositional optimization is one method used to effectively mitigate solidification cracking of those alloy systems. With the surge in hypersonic and in-space propulsion activities, refractory metals (Nb, Mo, Ta, W, and Re) and their alloy derivatives are increasing in importance due to their extreme high melting point and retention of high-temperature strength; however, their chemistry was most typically optimized to promote ductility during mechanical operations such as drawing and forming. Welding of such alloys has been a challenge due to a number of issues including solidification cracking, atmospheric contamination (O, C, and N), as well as a shift in ductile-to-brittle transition to higher temperature following grain growth induced by welding. Compositional optimization of refractory alloys for solidification cracking resistance in particular is desirable as their usage increases with the advent of advanced manufacturing methods such as 3D printing. This work evaluates the effect of compositional variation in refractory metal systems on the solidification cracking susceptibility with the goals of optimizing existing alloys and joining process techniques, and formulating new alloys with increased solidification cracking resistance. Experimental Procedures. A python code was developed in a Jupyter notebook environment (Michael and Sowards, 2023) to facilitate the calculation of crack susceptibility index proposed by Kou (2015). Composition is entered as a single point, or as a 1-D or 2-D array. The notebook calls pycalphad (Otis and Liu, 2017 and Bocklund et al, 2020) to calculate the evolution of fraction solid as a function of temperature (under either Scheil or equilibrium assumptions) and then evaluates steepness of the fraction solid curve near the terminal stage of solidification to predict solidification cracking resistance. Open source thermodynamic databases available at online repositories are used (van de Walle). The process is setup in an automated fashion to generate plots that show variation in solidification cracking susceptibility according to composition on 1-D line plots or 2-D contour plots. The Jupyter notebook and crack susceptibility algorithm was also integrated with a widely used commercial CALPHAD code for validation and alloy exploration. Results and Discussion. The crack susceptibility model was first validated against a series of refractory alloy compositions evaluated in past work which utilized a specialized Varestraint test built inside a vacuum chamber environment (Lessman and Gold, 1971). The alloys tested in the Varestraint apparatus included T-111 (Ta-8W-2Hf), ASTAR-811C (Ta-8W-1Re-0.7Hf-0.025C), FS-85 (Nb-27Ta-10W-1Zr), T-222 (Ta-9.6W-2.4Hf-0.01C), Ta-10W, B-66 (Nb-5Mo-5V-1Zr), and SCb-291 (Nb-10W-10Ta). The initial test of the model showed a strong correlation with empirical Varestraint data, i.e., a Spearman rank correlation between model predictions and hot cracking measurements was observed to be greater than 0.8. Following the validation, a set of refractory metal binary mixtures was investigated to evaluate sensitivity of Nb, Mo, W, and Ta to C, N, and O content. A series of plots were produced that suggest ppmw ranges of C, N, and O where solidification cracking increases significantly and reaches a maximum. Also comparative ranking of each primary refractory metal to each interstitial was produced. For example C produces greater cracking response in Mo whereas O produces greater cracking response in Ta and Nb. Such compositional values have utility in setting limits on pickup of these interstitial elements during welding and printing rather than using a one-size-fits-all approach. Furthermore, the results have use in determining additive powder recycling requirements, which is especially pertinent for refractory metal powders due to their high cost compared to conventional alloys. Another application created thousands of hypothetical alloys within the nominal specified composition range of two widely used refractory alloys C103 (Nb-10Hf-1Ti) and TZM (Mo-0.5Ti-0.1Zr). The cracking index was calculated for the alloys and results were fed into machine learning regression techniques including Multiple Linear Regression, Ridge Regression, and Lasso Regression to determine relative potency each alloying element had on computed solidification cracking index. A series of linear equations were produced that relate composition of C103 and TZM to solidification cracking index. The crack susceptibility of C103 for example is described by an equation of the form: cracking index ~ O + 0.667*C + 0.635*N + 0.00037*Ta – 0.0008*Hf (in wt.%) From that equation, it is clear that O has strong propensity to induce solidification cracking. Interestingly, Hf is shown to reduce calculated cracking response. Finally, realizing the potential of this method to discover new refractory alloy formulations across the period table that have low solidification cracking sensitivity, the code was applied to new untested alloy systems including W-Zr-C, W-Ta-C, and others. Conclusions. In summary, an open source numerical method has been developed using Python code to calculate Kou’s crack susceptibility index. The method was applied to refractory metals which are inherently difficult to study from a weldability testing standpoint since inert shielding gas is not sufficient and welding is typically done in vacuum, especially in light of findings presented here where oxygen has profound influence on solidification cracking. This work revealed the effect of compositional variations on a series of refractory metals and showed the framework defined here will be useful in 1) the development of new alloys that have improved weldability and 3D printability, 2) placing compositional limits on existing alloys, and 3) ensuring adequate controls of manufacturing processes such as 3D printing where powder reuse is critical. Keywords. pycalphad; Python; refractory metals; solidification cracking. References. B. Bocklund et. al. (2020) http://doi.org/10.5281/zenodo.3630657. S. Kou. (2015) https://doi.org/10.1016/j.actamat.2015.01.034. G.G. Lessmann and R.E. Gold. Welding Journal, issue 1, pp. 1-s – 8-s (1971). F.N. Michael and J.W. Sowards. NASA/TM-20230002218 (2023). R. Otis and Z.-K. Liu. (2017) http://doi.org/10.5334/jors.140. A. Van de Wallle et. al. (2018) https://doi.org/10.1016/j.calphad.2018.04.003.

pycalphad↗

DOE OSTI2024

Additively manufactured Ni-20Cr to V functionally graded material: Computational predictions and experimental verification of phase formations

Throughout this work, a database for the Cr-Ni-V system was constructed by modeling the binary Cr-V and ternary Cr-Ni-V systems using the CALPHAD approach aided by density functional theory (DFT)-based first-principles calculations and ab initio molecular dynamics (AIMD) simulations. To validate this new database, a functionally graded material (FGM) using Ni-20Cr and elemental V was fabricated using directed energy deposition additive manufacturing (DED AM) and experimentally characterized. The deposited Ni-20Cr was pure fcc phase, while increasing the amount of V across the gradient resulted in the formation of sigma phase, followed by the bcc phase. The experimentally measured phase data was compared with computational predictions made using a Cr-Ni-V thermodynamic database from the literature as well as the database developed in the present work. The newly developed database was shown to better predict the experimentally observed phases due to its accurate modeling of binary systems within the database and the ternary liquid phase, which is critical for accurate Scheil calculations.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Deep energy-pressure regression for a thermodynamically consistent EOS model

Abstract In this paper, we aim to explore novel machine learning (ML) techniques to facilitate and accelerate the construction of universal equation-Of-State (EOS) models with a high accuracy while ensuring important thermodynamic consistency. When applying ML to fit a universal EOS model, there are two key requirements: (1) a high prediction accuracy to ensure precise estimation of relevant physics properties and (2) physical interpretability to support important physics-related downstream applications. We first identify a set of fundamental challenges from the accuracy perspective, including an extremely wide range of input/output space and highly sparse training data. We demonstrate that while a neural network (NN) model may fit the EOS data well, the black-box nature makes it difficult to provide physically interpretable results, leading to weak accountability of prediction results outside the training range and lack of guarantee to meet important thermodynamic consistency constraints. To this end, we propose a principled deep regression model that can be trained following a meta-learning style to predict the desired quantities with a high accuracy using scarce training data. We further introduce a uniquely designed kernel-based regularizer for accurate uncertainty quantification. An ensemble technique is leveraged to battle model overfitting with improved prediction stability. Auto-differentiation is conducted to verify that necessary thermodynamic consistency conditions are maintained. Our evaluation results show an excellent fit of the EOS table and the predicted values are ready to use for important physics-related tasks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

A First–Principles–Based Sub–Lattice Formalism for Predicting Off–Stoichiometry in Materials for Solar Thermochemical Applications: The Example of Ceria

Theoretical models that reliably can predict off-stoichiometry in materials via accurate descriptions of underlying thermodynamics are crucial for energy applications. For example, transition-metal and rare-earth oxides that can tolerate a large number of oxygen vacancies, such as CeO 2 and doped CeO 2 , can split water and carbon dioxide via a two-step, oxide-based solar thermochemical (STC) cycle. The search for new STC materials with a performance superior to that of state-of-the-art CeO 2 can benefit from predictions accurately describing the thermodynamics of oxygen vacancies. The sub-lattice formalism, a common tool used to fit experimental data and build temperature-composition phase diagrams, can be useful in this context. Here, sub-lattice models are derived solely from zero-temperature quantum mechanics calculations to estimate fairly accurate temperature- and oxygen-partial-pressure-dependent off-stoichiometries in CeO 2 and Zr-doped CeO 2 . Physical motivations for deriving some of the “excess” sub-lattice model parameters directly from quantum mechanical calculations, instead of fitting to minimize deviations from experimental and/or theoretical data, are identified. As a result, important limitations and approximations of the approach used are specified and extensions to multi-cation oxides are also suggested to help identify novel candidates for water and carbon dioxide splitting and related applications.

08 HYDROGEN↗