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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 235 records · Page 13

Atomic protein structure refinement using all-atom graph representations and SE(3)-equivariant graph transformer

Abstract Motivation The state-of-art protein structure prediction methods such as AlphaFold are being widely used to predict structures of uncharacterized proteins in biomedical research. There is a significant need to further improve the quality and nativeness of the predicted structures to enhance their usability. In this work, we develop ATOMRefine, a deep learning-based, end-to-end, all-atom protein structural model refinement method. It uses a SE(3)-equivariant graph transformer network to directly refine protein atomic coordinates in a predicted tertiary structure represented as a molecular graph. Results The method is first trained and tested on the structural models in AlphaFoldDB whose experimental structures are known, and then blindly tested on 69 CASP14 regular targets and 7 CASP14 refinement targets. ATOMRefine improves the quality of both backbone atoms and all-atom conformation of the initial structural models generated by AlphaFold. It also performs better than two state-of-the-art refinement methods in multiple evaluation metrics including an all-atom model quality score—the MolProbity score based on the analysis of all-atom contacts, bond length, atom clashes, torsion angles, and side-chain rotamers. As ATOMRefine can refine a protein structure quickly, it provides a viable, fast solution for improving protein geometry and fixing structural errors of predicted structures through direct coordinate refinement. Availability and implementation The source code of ATOMRefine is available in the GitHub repository (https://github.com/BioinfoMachineLearning/ATOMRefine). All the required data for training and testing are available at https://doi.org/10.5281/zenodo.6944368.

59 BASIC BIOLOGICAL SCIENCES↗

Creating and Probing Large Gap 2D Topological Insulators for Quantum Computing (Final Report)

Research under this award focused on experimental and theoretical efforts in developing and characterizing 2D topological insulators (TIs). Key areas of investigation included materials synthesis, device fabrication and characterization, and theoretical advancements. The team synthesized ZrTe 5 , a material with potential for TI phases. Additionally, the team pursued the synthesis of elemental thin films like Indene and Bismuthene, known for their large TI gaps. Indene was successfully stabilized on SiC. Another approach involved stacking and twisting transition metal dichalcogenides (TMDs) to engineer desired TI band structures. On the theoretical front, advancements made under this award predicted remarkable topological properties in twisted WSe2 bilayers, motivating experimental efforts to realize these states. Regarding device fabrication and characterization, significant progress was made in reducing contact resistance, crucial for reliable transport measurements. Contactless Pulsed Tunneling Spectroscopy (CPTS) was employed to study the electronic properties of WTe 2 and WSe 2 . However, challenges in device fabrication and electrode material selection hampered efforts to obtain desired spectra. Ancillary work, utilizing pulsed electrical methods, on the study of sliding ferroelectrics yielded impactful results demonstrating high speed operation and lack of degradation of devices after many billions of cycles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A constitutive model for sheared dense fiber suspensions

Here we propose a constitutive model to predict the viscosity of fiber suspensions, which undergoes shear thinning, at various volume fractions, aspect ratios, and shear stresses/rates. We calibrate the model using the data from direct numerical simulation and prove the accuracy by predicting experimental measurements from the literature. We use a friction coefficient decreasing with the normal load between the fibers to quantitatively reproduce the experimentally observed shear thinning in fiber suspensions. In this model, the effective normal contact force, which is directly proportional to the bulk shear stress, determines the effective friction coefficient. A rise in the shear stress reduces the effective friction coefficient in the suspension. As a result, the jamming volume fraction increases with the shear stress, resulting in a shear thinning in the suspension viscosity. Moreover, we extend the model to quantify the effects of fiber volume fraction and aspect ratio in the suspension. We calibrate this model using the data from numerical simulations for the rate-controlled shear flow. Once calibrated, we show that the model can be used to predict the relative viscosity for different volume fractions, shear stresses, and aspect ratios. The model predictions are in excellent agreement with the available experimental measurements from the literature. The findings of this study can potentially be used to tune the fiber size and volume fraction for designing the suspension rheology in various applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evaporation from thin porous Coatings: Pore size effects and predictive equation for homogeneous coatings

Evaporation of small water droplets on solids is hindered because surface tension pulls the droplet into a spherical cap that has a small perimeter. Our solution is to coat a solid with a very thin, porous layer into which the droplet flows to create a large-area disk with concomitant high rate of evaporation. We investigate evaporation by varying factors that have not been previously considered: pore size and distribution, contact angle, temperature, and relative humidity (RH). A larger pore size resulted in faster evaporation, which we explain through faster transport within the coating. Even faster evaporation occurred for a bilayer structure with small particles on the air side and larger particles on the solid side. Further, the water advancing contact angle had an insignificant effect in the range from < 10° through to 60°. Our results for different pore sizes, temperature, humidity, and contact angle all collapse onto a single curve when appropriately normalized. This validates an equation that can be used for the evaporation from a homogeneous coating that depends only one empirical factor and the droplet volume. Since the volume is often user-controlled, we envisage that this equation can be used to predict evaporation and guide design of fast-drying coatings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modelling the limiter ramp-up of WEST for addressing the future challenges of ITER

This paper presents a joint experimental and numerical investigation into the physics of long limited plasma ramp-up in tokamaks with tungsten (W) first walls, a critical phase for ITER operation. The comparison between the average plasma quantities simulated using the SolEdge-HDG code and the measurements taken during three successive WEST discharges after boronisation shows how challenging it is to predict this phase. While simulations reproduce the general trends at the midplane, with reasonable match in density profiles, they consistently underestimate core temperatures possibly due to too large perpendicular heat conductivity. On the contrary, at the high field side (HFS) limiter, simulations overestimate the measured quantities, and highlights the limitation of using Bohm boundary conditions at grazing magnetic angles. Experimental measurements reveal that the boron layer is rapidly eroded, on a timescale comparable to a single ITER discharge. The subsequent transition from a boron-coated to a tungsten wall increases recycling and significantly degrades the core plasma, reducing the electron temperature by nearly half due to W contamination, despite wall parameters remaining stable. Furthermore, comparisons with Langmuir probes, bolometry, reflectometry, and spectroscopy indicate that the experimental far scrape-Off layer (SOL) is significantly wider than simulated. This wide SOL implies that boron erosion extends along the entire HFS limiter rather than being confined to the contact point. This work highlights some characteristics of the plasma during this phase of the discharge and emphasizes the current modelling issues that need to be resolved in order to obtain reliable predictions concerning the ITER ramp-up.

ITER↗

The molten salt tritium transport experiment: A pumped fluoride salt loop for hydrogen isotope experimentation

Molten salt reactors (MSRs) and fusion reactors propose to use molten salts as coolants and breeder blanket materials, respectively. Tritium, however, poses safety concerns in both reactor types due to its ability to permeate through reactor materials and potential for environmental release. This manuscript addresses the tritium transport phenomena in molten salts and presents the design and analysis of the Molten Salt Tritium Transport Experiment (MSTTE). MSTTE is a forced-convection fluoride salt loop intended to measure hydrogen isotope permeation through structural materials in a flowing salt system. In the first phase, MSTTE will use FLiNaK salt and deuterium as surrogates for FLiBe and tritium, with future plans to utilize tritium and FLiBe. MSTTE couples a Copenhagen Atomics pumped salt loop with an external test section that introduces hydrogen isotopes into the loop and measures transport phenomena. The Hydrogen Injection System (HIS) controls hydrogen isotope introduction into the molten salt loop. Here, the permeation test section measures the permeation rate through stainless steel tubing in contact with flowing salt. Computational fluid dynamics (CFD) analysis ensures fully developed salt flow in the permeation test section. MSTTE is modeled with MELCOR-TMAP to predict the permeation rate as a function of experimental variables such as source term, salt flow rate, and salt temperature. Results indicate that the source term is the only parameter with a significant effect on the permeation rate. Pressure drop analysis suggests that the loop should operate below 200 LPM to maintain a pressure drop below 200 kPa. Additionally, finite-element analysis assesses thermal stress during loop operation to ensure the experiment's safe design. MSTTE will provide semi-integral data on tritium transport phenomena in molten salts and serve as a testbed for advancing molten salt technology.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeling the hydrodynamic impact on the tool influence function during hemispherical subaperture optical polishing

To fabricate high-precision and accurate optics relative to the optical design surface, a high level of deterministic control of material removal (i.e., the tool influence function, TIF) during subaperture tool polishing is required. In this study, a detailed analysis of the pressure distribution, which is a key component of the TIF, has been performed using finite element analysis to couple together solid mechanics and fluid dynamics. Modeling experimental parameters of recently published work reveals that, when considering tool deformation, which in turn influences the fluid film thickness between the tool and workpiece, the effective pressure profile has a flat-top distribution. This flat-top pressure profile differs from the parabolic pressure distributions predicted by Hertzian mechanics. Furthermore, the shear contribution is shown here to be a key contributor to material removal, inducing the removal at the periphery of the contact edge and even outside the generally accepted contact area. Finally, the simulated fluid velocities provide evidence of mixed-mode contact polishing, supporting recent experimental findings that also suggest that onset of hydroplaning contributions lead to material removal drop-off.

36 MATERIALS SCIENCE↗

Discrete-Element and Material-Point Method (DEM and MPM) Based Solvers for Sustainable Technologies

We present the use of discrete element method (DEM) and material point method (MPM) in three relevant green technology applications that include biomass feedstock handling, lithium-ion battery manufacturing, and high-pressure reverse osmosis. Our open-source DEM and MPM solvers are developed using performance portable grid and particle management library, AMReX, thus enabling superior performance on NVIDIA and AMD GPUs with > 100 million particles. Our DEM solver resolves the motion of individual particles in a granular system and includes a bonded sphere method for modeling non-spherical particles along with Hertzian and liquid bridge-based contact models. We simulate highly variable biomass feedstock flows in large-scale hoppers for biofuel production and electrode calendering in battery manufacturing using DEM. Our simulations predict flow blockage in large scale biomass hoppers and electrode microstructure variations, thus providing valuable information for biofuel and battery manufacturers, respectively. The second half of the talk will be on MPM and its application towards pore resolved simulations of reverse osmosis membranes under compressive loads. We present a validation study of our MPM simulations with membrane microscopy imaging thus providing useful insights on membrane stability under high pressure conditions. We also present a spectral stability analysis of using linear hat, quadratic and cubic spline basis in MPM indicating regions of numerical stability.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗

LEAKAGE CHARACTERISTICS OF A STEPPED BALANCE PISTON LABYRINTH SEAL IN SUPERCRITICAL CO2

In an integrally geared compressor, there is a net thrust load on the pinion shaft from gear loads and aerodynamic forces. The net thrust on the pinion is resolved with either a thrust bearing or a thrust collar (rider ring). As the pressure increases, this increases the aerodynamic force proportionally. In highpressure systems this can overwhelm the thrust bearing or thrust collar if thrust is mismanaged. In a recent test program for an sCO2 integrally geared compander (compressor/turbine), a balance piston was created on the opposite end of the turbine to provide an equalizing thrust; while this is not novel, the balance piston provided a test apparatus for measuring the leakage on a 20 tooth stepped labyrinth seal operating at pressures in excess of 250 bar (3600 psi). The stepped balance piston seal is a 20 tooth tooth-onrotor balance piston seal. This type of seal was selected since it was predicted to have substantially less leakage than a comparably sized straight through labyrinth seal. Comparisons between the two designs will be made, showing that the leakage of the stepped balance piston seal is considerably lower. The tooth clearance on the seal was selected to be 30 mils radial. While this seems large, a stack-up tolerance assessment showed that this magnitude of clearance was appropriate to prevent rotor stator contact. During the testing campaign, data was recorded showing the leakage across this stepped balance piston seal at pressures in excess of 250 bar (3600 psi) with a pressure ratio of 2. This leakage data was measured, and will be compared to leakage data predicted with CFD. Two measurement methods are presented for the stepped balance piston seal: an orifice plate and valve. The predicted seal leakage from a straight through seal was four times that of the predicted stepped labyrinth seal. The measured flow from the stepped seal was on the same order as the CFD prediction and offered adequate rotordynamic performance

wilkes, jason↗

Enhancing high-fidelity nonlinear solver with reduced order model

Abstract We propose the use of reduced order modeling (ROM) to reduce the computational cost and improve the convergence rate of nonlinear solvers of full order models (FOM) for solving partial differential equations. In this study, a novel ROM-assisted approach is developed to improve the computational efficiency of FOM nonlinear solvers by using ROM’s prediction as an initial guess. We hypothesize that the nonlinear solver will take fewer steps to the converged solutions with an initial guess that is closer to the real solutions. To evaluate our approach, four physical problems with varying degrees of nonlinearity in flow and mechanics have been tested: Richards’ equation of water flow in heterogeneous porous media, a contact problem in a hyperelastic material, two-phase flow in layered porous media, and fracture propagation in a homogeneous material. Overall, our approach maintains the FOM’s accuracy while speeding up nonlinear solver by 18–73% (through suitable ROM-assisted FOMs). More importantly, the proximity of ROM’s prediction to the solution space leads to the improved convergence of FOMs that would have otherwise diverged with default initial guesses. We demonstrate that the ROM’s accuracy can impact the computational efficiency with more accurate ROM solutions, resulting in a better cost reduction. We also illustrate that this approach could be used in many FOM discretizations (e.g., finite volume, finite element, or a combination of those). Since our ROMs are data-driven and non-intrusive, the proposed procedure can easily lend itself to any nonlinear physics-based problem.

97 MATHEMATICS AND COMPUTING↗

Separation of volatile organic contaminants from water using a direct-contact dehumidifier: An experimental study and modeling

A packed-bed, direct-contact dehumidifier (PB-DCD) has been developed to selectively condense water from a gaseous mixture of organic contaminants. In this process, hot air is humidified by mixing with wastewater vapor in a static mixer and is dehumidified by subcooled fresh water passing through the PB-DCD in a counter-current configuration. The goal of this study is to understand the relationship between various operating parameters and how they affect separation of isopropyl alcohol (IPA) from the gaseous mixture with the purpose of expanding the investigation to other contaminants in the future. The process has been successfully used to separate IPA from wastewater. Different parameters including the concentration of IPA in water, feed temperature, air-to-vapor ratio, and cooling-water-to-vapor mass ratio, as well as residence time were examined to determine their influence on contaminant separation and clean water recovery rate. The Buckingham Pi theorem was applied to reduce the number of studying variables by generating non-dimensional groups. Experiments were performed to determine the relationship between the non-dimensional parameters and model mass transfer in the system. Mass transfer coefficients for multicomponent gaseous mixture condensation in a packed-bed direct contact condenser column are calculated and a modified correlation of mass transfer is developed. The parameters of the mass transfer model are obtained from operating conditions of the PB-DCD, stream conditions and thermodynamic properties. A modified Sherwood correlation is developed to predict IPA separation from a gaseous mixture consisting of air, water, and IPA. The modified Sherwood correlation is applied to successfully predict the Sherwood number with a mean absolute error equal to 6.6 %. According to the experimental results, the maximum IPA separation achieved was 76.3 %, which corresponds to a water recovery rate of 58.7 %.

42 ENGINEERING↗

Prediction and Experimental Verification of Electrolyte Solvation Structure from an OMol25-Trained Interatomic Potential

A molecular-level understanding of electrolyte solvation structure and ion–ion correlations is critical to developing next-generation battery chemistries. Atomistic simulation capabilities with sufficient accuracy, speed, and transferability to deliver reliable structural insights while avoiding arduous system-specific reparameterization are thus highly desirable. Machine learning interatomic potentials (MLIPs) trained on large, chemically diverse data sets are revolutionizing computational chemistry, enabling molecular dynamics simulations of battery electrolytes with near-DFT accuracy over 10,000× faster than DFT. While previous MLIP training data sets with suitable elemental coverage for electrolytes have been based on inorganic materials, the Open Molecules 2025 (OMol25) data set provides large-scale molecular DFT MLIP training data with broad elemental coverage and specifically samples tens of millions of electrolyte configurations. Here, we integrate computational modeling with experimental validation to systematically assess the ability of large-scale MLIPs pretrained on materials data or on OMol25 to accurately resolve nanoscale structural organization and ion-solvation characteristics in Na-ion battery electrolytes across diverse physicochemical conditions and compositional regimes. We find that the OMol25-trained Universal Model of Atoms (UMA-OMol) predicts experimentally measured densities and X-ray structure factors in substantially better agreement compared to state-of-the-art models trained only on inorganic materials data. Using UMA-OMol, we further analyze systematic trends in solvation structure as a function of cation identity, anion chemistry, salt concentration, and solvent topology. We observe that increasing system temperature amplifies the heterogeneity within the solvation environment, perturbing cation–solvent interactions and promoting the formation of contact ion pairs (CIPs). Moreover, subtle variations in the solvent topology of glyme-based electrolytes cause pronounced changes in ion correlations and solvation structure. The experimental agreement and microscopic insights shown here position OMol25-trained MLIPs as a practical route to predictive, high-throughput electrolyte simulations beyond the limits of classical force fields and direct DFT molecular dynamics, serving as a powerful tool for accelerating the design of next-generation Na-ion battery electrolytes and beyond.

MLIPs↗

Irradiation Vehicles for Evaluating SiC/SiC Cladding Bowing Under Neutron Flux Gradients

Silicon carbide fiber–reinforced silicon carbide matrix (SiC/SiC) composites are among the most promising candidates for long term accident-tolerant nuclear fuel cladding. A key challenge related to their deployment is lateral bowing caused by differential radiation-induced swelling under dose or temperature gradients, which could obstruct coolant flow or interfere with control rod/blade movements. Although previous modeling efforts have predicted bowing behavior in light-water reactor (LWR) environments, experimental validation remains limited, especially at prototypic LWR temperatures. This study addresses that gap by irradiating six reduced-length SiC/SiC cladding tubes (~600 mm) in the High Flux Isotope Reactor (HFIR) at ~300°C, which is representative of LWR conditions. The tubes will be housed in a sealed vessel with an inert gas gap to maintain target temperatures and prevent direct coolant contact. Arranged in three pairs, each set will receive a different radiation dose (low, medium, high), with the central pair receiving ~0.1 displacements per atom (dpa)—the expected dose for peak bowing. The experiment will determine the dose-dependent bowing behavior and validate predictive finite element models. In this work, the tubes are freely suspended from pins to allow for unconstrained bowing; however, we present a concept for introducing localized constraints to represent grid spacer effects. Post-irradiation examination will include swelling measurements and profilometry to assess bowing and compare the results with model predictions. This work aims to confirm the conditions under which maximum bowing occurs so as to improve the reliability of SiC/SiC performance models in nuclear applications.

Russell, Nick [ORNL] (ORCID:0000000296099820)↗

Potentiometric Studies on Ion-Transport Selectivity in Charged Gold Nanotubes

Under ideal conditions, nanotubes with a fixed negative tube-wall charge will reject anions and transport-only cations. Because many proposed nanofluidic devices are optimized in this ideally cation-permselective state, it is important to know the experimental conditions that produce ideal responses. A parameter called Ccrit, the highest salt concentration in a contacting solution that still produces ideal cation permselectivity, is of particular importance. Pioneering potentiometric studies on gold nanotubes were interpreted using an electrostatic model that states that Ccrit should occur when the Debye length in the contacting salt solution becomes equivalent to the tube radius. Since this “double-layer overlap model” (DLOM), treats all same-charge ions as identical point charges, it predicts that all same-charged cations should produce the same Ccrit. However, the effect of cation on Ccrit in gold nanotubes was never investigated. This knowledge gap has become important because recent studies with a polymeric cation-permselective nanopore membrane showed that DLOM failed for every cation studied. To resolve this issue, we conducted potentiometric studies on the effect of salt cation on Ccrit for a 10 nm diameter gold nanotube membrane. Ccrit for all cations studied were, within experimental error, the same and identical, with values predicted by DLOM. The reason DLOM prevailed for the gold nanotubes but failed for the polymeric nanopores stems from the chemical difference between the fixed negative charges of these two membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Lattice Boltzmann Method for Predicting Porous Transport Layer Performance During Electrolysis

Electrolysis, the splitting of water into oxygen and hydrogen using electricity, is a sustainable way to produce green hydrogen for energy storage. In polymer electrolyte membrane (PEM) water electrolysis, water is brought into contact with charged catalyst layers and electrochemically separated into oxygen and hydrogen. The hydrogen product formed at the cathode is carried through the catalyst layer for eventual collection, while the oxygen by-product formed at the anode is removed from the surface via a multiphase interaction with circulating water and a solid porous transport layer (PTL). The design of this PTL aids in the detachment and advection of the oxygen by-product and thereby plays a role in the overall efficacy of the catalyst. In this presentation, we present our initial results modeling this multiphase system using a single-component, multiphase lattice Boltzmann method. We use the Shan-Chen model describing inter-particle forces to capture both the cohesion of the water (liquid) and oxygen (gas) phases and their interaction with the PTL (solid) (Shan and Chen, 1993). We use a Carnahan-Starling equation of state to model the effective density governing these inter-particle interactions which allows us to model this relatively high density ratio system (Carnahan and Starling, 1969). With these simulations, we show that the geometry and heterogeneity of the PTL geometry plays a large role in its ability to move oxygen away from the catalyst layer and the resulting bubble structures that are formed within the PTL. The current work demonstrates these effects using synthesized PTL geometries and 2D physics, which will be extended to experimentally-imaged PTL sections and 3D algorithms in the near future.

Boltzmann↗

Metastability and Long-Term Degradation in CIGS Devices: Effect of Alkali Treatments, Back Contact and Emitter Layers

Thin-film solar cell technologies often suffer from metastable and long-term performance degradation, which may or may not be reversible. The presence of the transient or degradation issues pose challenges for energy-yield prediction in the field for these technologies. Cu(In,Ga)(S,Se) 2 solar cells are a promising thin-film technology, however, the underlying mechanisms of instability in these devices are not well understood. The most common mechanism of metastability in CIGS solar cells has been speculated to be the configuration changes of (VSe-VCu) divacancy complex. However, the role of metastability in light soaking behavior and the effect of alkali treatments and buffer layers is not understood. The goal of the current project is to understand the effect of alkali treatments and buffer materials on metastability and light soaking behavior and develop a device model to simulate experimental results. Input parameters are taken from literature or derived from first-principle calculations, and are fine-tuned through validation experiments.

14 SOLAR ENERGY↗

Tool-workpiece stick-slip conditions and their effects on torque and heat generation rate in the friction stir welding

Friction stir welding (FSW) has found increased applications in automotive and aerospace industries due to its advantages of solid-state bonding, no fusion and melting, and versatility in various working conditions and material combinations. However, the relationship among processing parameters, material properties, and bonding extent and fidelity remains largely empirical, primarily because of the lack of the mechanistic understanding of the tool-workpiece frictional behavior that affects our subsequent understanding of microstructural evolution and interface bonding formation. While the tool-workpiece stick-slip condition is believed to dictate the resulting torque and heat generation rate during the welding process, it remains rare and elusive to conduct a quantitative experimental measurement of such interfacial field. On the other hand, numerical simulations based on Computational Fluid Dynamics (CFD) rely on ad hoc assumptions of interfacial pressure and shear-stress conditions, but predictions can only be validated via the medium- and far-range temperature field which is known to be insensitive to the interfacial frictional behavior. This work first presents a comparison among two CFD-based simulation methodologies and the Coupled Eulerian Lagrangian (CEL) model in finite element method, the last of which uses the Coulomb friction so that the stick-slip is naturally developed. Based on the Hill-Bower similarity relationship in the contact analysis, an analytical model is developed here to prove why a constant stick-slip fraction will be developed in the steady state, to correlate the stick-slip fraction to processing parameters such as the tool spin rate, and further to derive dimensionless functions for torque and heat-generation-rate predictions. Pros and cons of various numerical approaches in predicting stick-slip are discussed, and our analytical model has been found to agree well with our numerical simulation and literature experimental results. These analyses provide the critical strain-rate and temperature fields that are needed for the bonding analysis in our future work.

36 MATERIALS SCIENCE↗

Modeling Marangoni Convection using a Velocity-Time Relationship

The Waste Treatment and Immobilization Plant (WTP) at the U.S. Department of Energy’s (DOE’s) Handford site is designed to treat 56 million gallons of radioactive waste through vitrification. The melting vessels physical and chemical integrity is essential to maintain, as failure has a high safety and financial penalty. Monofrax® K-3 refractory, the material widely used for the melting vessel, undergoes significant corrosion over time, concentrated at the triple-point junction between the gaseous atmosphere, refractory, and glass melt, producing a characteristic neck-like profile that significantly limits refractory service life. Accurate prediction of the corrosion within the melter can be used to prevent this and extend the lifetime of the melters. A computational fluid dynamics (CFD) model was previously developed, and predicted subsurface refractory corrosion, but failed to predict the neck-line profile observed experimentally. To address this limitation, the glass-melt meniscus geometry at the glass-refractory interface was estimated from experimentally measured neck profiles and wettability experiments. A curve was fitted to the neck profile to identify the triple point location, and the meniscus shape was characterized by a contact angle of 1°. A velocity profile accounting for Marangoni convection-driven corrosion was derived from the estimated meniscus geometry. Surface tension measurements from LORPM14R1 glasses of varying composition were coupled with K-3 coupon dissolution rates to establish a surface tension–time relationship. This analytical velocity-time model was integrated into the existing CFD framework to improve prediction of the neck corrosion profile. Work was done in a computational setting with national collaboration, resulting in professional development through presentational and technical writing growth.

36 - MATERIALS SCIENCE↗