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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data-Driven Tailoring Optimization of Thermoset Polymers Using Ultrasonics and Machine Learning

Thermoset polymers are highly demanded for their structural robustness, thermal stability, and chemical resistance. Tailoring the properties of these polymers for high-performance applications is often preferred to designing brand-new polymers. However, the traditional destructive techniques used to characterize their properties as a function of manufacturing parameters are expensive and time-consuming. A novel non-destructive, data-driven method leveraging ultrasonics and machine learning techniques to tailor the properties of thermosets as a function of the manufacturing parameters is demonstrated. Thermoset epoxy samples with varying curing temperatures (15–40 °C) and curing agent amounts (±40%) were manufactured and tested. Their curing kinetics were monitored by determining the sound speed in the material in real time, while the longitudinal modulus of the samples was determined post-cure. Machine learning models were developed using a k-nearest neighbors algorithm. These models were implemented to predict the curing and final elastic properties using the manufacturing parameters, i.e., stoichiometry and curing temperature, and vice versa. Understanding and modeling how these parameters affect the cure kinetics and final properties will allow for efficient and reliable optimization of thermoset tailoring and manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Generation and Study of Am(IV) by Temperature-Controlled Electron Pulse Radiolysis

Used nuclear fuel (UNF) separation techniques that strive to separate radiotoxic americium (Am) from trivalent lanthanide fission products through oxidation state control have increased research efforts surrounding Am(V) and Am(VI). However, equivalent knowledge of the tetravalent state, Am(IV), has remained elusive, particularly in conditions more representative of UNF reprocessing, i.e., in concentrated nitric acid (HNO3). With this in mind, we have used electron pulse radiolysis to study the radiation-induced redox reaction of Am(III) with the oxidizing nitrate radical (NO3?) in 6 M HNO3: Am(III) + NO3? ? Am(IV) + NO3? . These experiments enabled us to observe the growth and decay of Am(IV) in a concentrated acidic solution for the first time. The transient Am(IV) species was found to have a lifetime of ~16 µs?sufficiently long-lived to play a critical mechanistic role in UNF reprocessing systems. Additionally, we performed the first-ever temperature-dependent kinetics study of an actinide element, elucidating unprecedented Arrhenius and Eyring activation parameters for the reaction of Am(III) with NO3?. This new knowledge provides much-needed molecular-level insights into the radiation-induced behavior of Am.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Internally Catalyzed Hydrogen Atom Transfer (I-CHAT)—A New Class of Reactions in Combustion Chemistry

The current paradigm of low-T combustion and autoignition of hydrocarbons is based on the sequential two-step oxygenation of fuel radicals. The key chain-branching occurs when the second oxygenation adduct (OOQOOH) is isomerized releasing an OH radical and a key ketohydroperoxide (KHP) intermediate. The subsequent homolytic dissociation of relatively weak O–O bonds in KHP generates two more radicals in the oxidation chain leading to ignition. Based on the recently introduced intramolecular “catalytic hydrogen atom transfer” mechanism (J. Phys. Chem. 2024, 128, 2169), abbreviated here as I-CHAT, we have identified a novel unimolecular decomposition channel for KHPs to form their classical isomers—enol hydroperoxides (EHP). The uncertainty in the contribution of enols is typically due to the high computed barriers for conventional (“direct”) keto–enol tautomerization. Remarkably, the I-CHAT dramatically reduces such barriers. The novel mechanism can be regarded as an intramolecular version of the intermolecular relay transfer of H-atoms mediated by an external molecule following the general classification of such processes (Catal. Rev.-Sci. Eng. 2014, 56, 403). Here, we present a detailed mechanistic and kinetic analysis of the I-CHAT-facilitated pathways applied to n-hexane, n-heptane, and n-pentane models as prototype molecules for gasoline, diesel, and hybrid rocket fuels. We particularly examined the formation kinetics and subsequent dissociation of the γ-enol-hydroperoxide isomer of the most abundant pentane-derived isomer γ-C5-KHP observed experimentally. To gain molecular-level insight into the I-CHAT catalysis, we have also explored the role of the internal catalyst moieties using truncated models. All applied models demonstrated a significant reduction in the isomerization barriers, primarily due to the decreased ring strain in transition states. In addition, the longer-range and sequential H-migration processes were also identified and illustrated via a combined double keto–enol conversion of heptane-2,6-diketo-4-hydroperoxide as a potential chain-branching model. To assess the possible impact of the I-CHAT channels on global fuel combustion characteristics, we performed a detailed kinetic analysis of the isomerization and decomposition of γ-C5-KHP comparing I-CHAT with key alternative reactions—direct dissociation and Korcek channels. Calculated rate parameters were implemented into a modified version of the n-pentane kinetic model developed earlier using RMG automated model generation tools (ACS Omega, 2023, 8, 4908). Simulations of ignition delay times revealed the significant effect of the new pathways, suggesting an important role of the I-CHAT pathways in the low-T combustion of large alkanes.

Biochemistry & Molecular Biology↗
DOE OSTI2025

Pyridine Catalysis of Anhydride Hydrolysis within Carbodiimide‐Driven Reaction Networks

Carbodiimide-fueled reaction networks offer a versatile platform for nonequilibrium chemical systems. Typically, the carbodiimide converts a carboxylic acid to its anhydride, called “activation,” which subsequently undergoes hydrolysis, called “deactivation.” Here, we investigate pyridines with variable nucleophilicity as catalysts to control deactivation (pyridine, 4-methylpyridine, 4-methoxypyridine, and 4-dimethylaminopyridine). Reactions have been monitored by NMR spectroscopy. Although this reaction network is simple, determination of well-defined rate constants from kinetic modeling is challenging because of correlation between the parameters. This issue can be addressed by analyzing the anhydride hydrolysis independently. The rate of attack of the pyridines on the anhydride follows expected nucleophilicity trends, although this is offset by increased protonation of more-nucleophilic pyridines at typical pH's. The optimized parameters can be used to model the full carbodiimide-driven process, although the presence of the common carbodiimide EDC has unanticipated effects on the anhydride hydrolysis rate. The results offer context for controlling carbodiimide-fueled reaction networks through the choice of suitable catalysts and pH.

Anhydrides↗
DOE OSTI2024

Probabilistic and maximum entropy modeling of chemical reaction systems: Characteristics and comparisons to mass action kinetic models

We demonstrate and characterize a first-principles approach to modeling the mass action dynamics of metabolism. Starting from a basic definition of entropy expressed as a multinomial probability density using Boltzmann probabilities with standard chemical potentials, we derive and compare the free energy dissipation and the entropy production rates. We express the relation between entropy production and the chemical master equation for modeling metabolism, which unifies chemical kinetics and chemical thermodynamics. Because prediction uncertainty with respect to parameter variability is frequently a concern with mass action models utilizing rate constants, we compare and contrast the maximum entropy model, which has its own set of rate parameters, to a population of standard mass action models in which the rate constants are randomly chosen. We show that a maximum entropy model is characterized by a high probability of free energy dissipation rate and likewise entropy production rate, relative to other models. We then characterize the variability of the maximum entropy model predictions with respect to uncertainties in parameters (standard free energies of formation) and with respect to ionic strengths typically found in a cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Degradation of performance in ICF implosions due to Rayleigh–Taylor instabilities: A Hamiltonian perspective

The Rayleigh–Taylor instability (RTI) is an ubiquitous phenomenon that occurs in inertial-confinement-fusion (ICF) implosions and is recognized as an important limiting factor of ICF performance. To analytically understand the RTI dynamics and its impact on ICF capsule implosions, we develop a first-principle variational theory that describes an imploding spherical shell undergoing RTI. The model is based on a thin-shell approximation and includes the dynamical coupling between the imploding spherical shell and an adiabatically compressed fluid within its interior. Using a quasilinear analysis, we study the degradation trends of key ICF performance metrics (e.g., stagnation pressure, residual kinetic energy, and areal density) as functions of initial RTI parameters (e.g., the initial amplitude and Legendre mode), as well as the 1D implosion characteristics (e.g., the convergence ratio). We compare analytical results from the theory against nonlinear results obtained by numerically integrating the governing equations of this reduced model. Our findings emphasize the need to incorporate polar flows in the calculation of residual kinetic energy and demonstrate that higher convergence ratios in ICF implosions lead to significantly greater degradation of key performance metrics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

DRDMannTurb: A Python package for scalable, data-driven synthetic turbulence

Synthetic turbulence models (STMs) are used in wind engineering to generate realistic flow fields and are employed as inputs to industrial wind simulations. Examples include prescribing inlet conditions in large eddy simulations that model loads on wind turbines and tall buildings. We are interested in STMs capable of generating fluctuations based on prescribed second-moment statistics since such models can simulate environmental conditions that closely resemble on-site observations. To this end, the widely used Mann model (see Mann, 1994, 1998) is the inspiration for DRDMannTurb. The Mann model is described by three physical parameters: a magnitude parameter influencing the global variance of the wind field and corresponding to the Kolmogorov constant multiplied by the rate of viscous dissipation of the turbulent kinetic energy to the two-thirds, αϵ 2/3 , a turbulence length scale parameter L, and a nondimensional parameter Γ related to the lifetime of the eddies. A number of studies, as well as international standards (e.g., those by the International Electrotechnical Commission (IEC)), include recommended values for these three parameters with the goal of standardizing wind simulations according to observed energy spectra. Yet, having only three parameters, the Mann model faces limitations in accurately representing the diversity of observable spectra. This Python package enables users to extend the Mann model and more accurately fit field measurements through flexible neural network models of the eddy lifetime function. Following Keith et al. (2021), we refer to this class of models as Deep Rapid Distortion (DRD) models. DRDMannTurb also includes a general module implementing an efficient method for synthetic turbulence generation based on a domain decomposition technique. This technique is also described in Keith et al. (2021).

17 WIND ENERGY↗
DOE OSTI2025

Transient kinetic insights into selective propene oxidation over industrial bismuth molybdate catalysts

Selective oxidation of propene to acrolein over industrial multicomponent bismuth molybdate (BMO) catalysts significantly depends on reaction conditions that include operating parameters and catalyst state. Here, this work investigates selective propene oxidation in the intrinsic kinetic paradigm of Temporal Analysis of Products (TAP) reactor by systematically varying catalyst redox state, temperature, and oxygen-to-propene feed ratio. A 93 % propene conversion with an acrolein yield of 80 % is achieved at elevated temperatures (450 °C) on oxidized catalysts under oxygen-rich conditions (O 2 :C 3 H 6 = 10). However, these conditions diminish acrolein-to-CO 2 selectivity due to enhanced total oxidation to CO 2 . In contrast, a reduced catalyst state, moderate temperature (350 °C), and lower oxygen feed (O 2 :C 3 H 6 = 1) nearly doubles the acrolein to-CO 2 selectivity, albeit at a lower acrolein yield (33 %). Transient kinetic studies together with a kinetic model that simplify the major product formation pathways in lumped non-elementary forms reveal that the availability of surface oxygen species plays a pivotal role in governing reaction pathways. Additionally, density functional theory (DFT) calculations on pure BMO catalysts inform the role of surface redox states on propene and oxygen activation barriers. Lattice oxygen at acrolein-selective sites drives both acrolein and CO 2 formation, while adsorbed oxygen at activation sites favors unselective CO 2 generation. This work establishes a critical relationship between transient product selectivity and surface oxygen availability, which is strongly influenced by catalyst redox state, feed ratio, and reaction temperature. These insights underscore the importance of dynamic reactor operation strategies and offer a foundation for designing next-generation propene oxidation processes with tunable acrolein selectivity.

42 - ENGINEERING↗
DOE OSTI2026

Modeling Radiolysis and Chemical Reactions during Dry Storage of Aluminum-clad Spent Nuclear Fuel

After aluminum-clad spent nuclear fuel (ASNF) is removed from the reactor, it is initially stored in spent fuel pools, which are specially designed water-filled basins that provide temporary cooling to reduce the temperature of the fuel assemblies and provide radiation shielding. ASNF continues to generate heat due to the radioactive decay of elements within the fuel, which persists for many years post-shutdown as the residual radioactive products decay into more stable elements. During the wet storage period, an oxyhydroxide layer composed of boehmite/bayerite forms on the surfaces of the aluminum cladding from exposure to water in the pools. Road-ready packaging for long-term disposition of the ASNF involves dry storage in helium backfilled DOE standard canisters (DSCs). When the ASNF is removed from water storage and dried, most of the water is removed, but some physisorbed and chemisorbed water remains in the oxyhydroxide layers. This residual water can produce hydrogen when exposed to radiation from the ASNF during dry storage. Predicting hydrogen accumulation over time in the DSCs is critical for long-term storage considerations. Previous modeling efforts have developed coupled computational fluid dynamics (CFD)-chemical models to simulate temperature, pressure, and gas phase concentrations within the DSCs. These models use the thermal field predicted by CFD as input to a radiolysis model for the gas phase and the surface oxyhydroxide layer chemistry. Given the long storage period of the DSCs and the impracticality of long-term experiments, a simulation-based approach is necessary to assess chemical evolution within the canisters. This study advances the development of a modeling framework designed to simulate the chemical evolution of spent fuel canisters. Both thermal and radiation-driven reactions are considered, with radiation kinetics quantified using G-values. Sensitivity analysis identifies key parameters influencing species composition. Reaction pathway diagrams offer insight into dominant species formation routes, enabling more effective comparisons between model predictions and experimental observations, particularly regarding the production of hydrogen. Results show that the model predicts significant hydrogen gas production with minimal oxygen generation, primarily due to hydrogen formation via boehmite pathways. These findings underscore the importance of accurately characterizing surface-bound species and radiolysis kinetics. A deeper understanding of these mechanisms is critical for evaluating the long-term safety of nuclear waste storage.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2025

Polaron catastrophe within quantum acoustics

The quantum acoustic framework has recently emerged as a nonperturbative, coherent approach to electron–lattice interactions, uncovering rich physics often obscured by perturbative methods with incoherent scattering events. Here, we model the strongly coupled dynamics of electrons and acoustic lattice vibrations within this framework, representing lattice vibrations as coherent states and electrons as quantum wave packets, in a manner distinctively different from tight-binding or discrete hopping-based approaches. We derive and numerically implement electron backaction on the lattice, providing both visual and quantitative insights into electron wave packet evolution and the formation of acoustic polarons. We investigate polaron binding energies across varying material parameters and compute key observables—including mean square displacement, kinetic energy, potential energy, and vibrational energy—over time. Our findings reveal the conditions that favor polaron formation, which is enhanced by low temperatures, high deformation potential constants, slow sound velocities, and high effective masses. Additionally, we explore the impact of external electric and magnetic fields, showing that while polaron formation remains robust under moderate fields, it is weakly suppressed at higher field strengths. These results deepen our understanding of polaron dynamics and pave the way for future studies into nontrivial transport behavior in quantum materials.

Science & Technology - Other Topics↗
DOE OSTI2025

Assessing the numerical stability of physics models to equilibrium variation through database comparisons on DIII-D

High fidelity kinetic equilibria are crucial for tokamak modeling and analysis. Manual workflows for constructing kinetic equilibria are time consuming and subject to user error, motivating development of automated equilibrium reconstruction tools to provide accurate and consistent reconstructions for downstream physics analysis. These automated tools also provide access to kinetic equilibria at large database scales, which enables the quantification of general uncertainties arising from equilibrium reconstruction techniques. In this paper, we compare a large database of DIII-D kinetic equilibria generated manually by physics experts to equilibria from automated kinetic reconstruction tools, assessing the impact of reconstruction method on equilibrium parameters and resulting magnetohydrodynamic stability calculations. We find agreement among scalar parameters, whereas profile quantities, such as the bootstrap current, show larger disagreements. We analyze ideal kink and classical tearing stability with DCON and STRIDE respectively, finding that the kink stability calculation is generally more robust than the tearing index Δ' calculation. We find that in 90% of cases, both kink stability classifications are unchanged between the manual expert and automated kinetic equilibria.

CAKE↗
DOE OSTI2025

Measurement of post-disruption runaway electron kinetic energy and pitch angle during final loss instability in DIII-D

Post-disruption runaway electron (RE) kinetic energy K and pitch angle sin$\vartheta$ are critical parameters for determining resulting first wall material damage during wall strikes, but are very challenging to measure experimentally. During the final loss instability, confined RE K and sin$\vartheta$ are reconstructed during center-post wall strikes for both high impurity (high-Z) and low impurity (low-Z) plasmas by combining soft x-ray, hard x-ray, synchrotron emission, and total radiated power measurements. Deconfined (wall impacting) RE sin$\vartheta$ is then reconstructed for these shots by using time-decay analysis of infra-red imaging. Additionally, deconfined RE K and sin$\vartheta$ are reconstructed for a low-Z downward loss shot by analyzing resulting damage to a sacrificial graphite dome limiter. The damage analysis uses multi-step modeling simulating plasma instability, RE loss orbits, energy deposition, and finally material expansion (MARS-F, KORC, GEANT-4, and finally COMSOL). Overall, mean kinetic energies are found to be in the range $\langle$$K$$\rangle$ $≈ 3-4$ MeV for confined REs. KORC simulations indicate that the final loss instability process does not change individual RE kinetic energy K. In conclusion, confined RE pitch angles are found to be fairly low initially pre-instability, $\langle$sin$\vartheta$$\rangle$ $≈ 0.1 – 0.2$, but appear to increase roughly 2x, to $\langle$sin$\vartheta$$\rangle$ $≈ 0.3 – 0.4$ for both confined and deconfined REs during instability onset in the low-Z case; this increase is not observed in the high-Z case.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A deep learning approach to fast analysis of collective Thomson scattering spectra

Fast analysis of collective Thomson scattering ion acoustic wave features using a deep convolutional neural network model is presented. The network was trained from spectra to predict the plasma parameters, including ion velocities, population fractions, and ion and electron temperatures. A fully kinetic particle-in-cell simulation was used to model a laboratory astrophysics experiment and simulate a diagnostic image of the ion acoustic wave feature. Network predictions were compared with Bayesian inference of the plasma model parameters for both the simulated and experimentally measured images. Both approaches were fairly accurate predicting the simulated image and the network predictions matched a good portion of the Bayesian results for the experimentally measured image. The Bayesian approach is more robust to noise and motivates future work to train deep learning models with realistic noise. The advantage of the deep learning model is making thousands of predictions in a few hundred milliseconds, compared to a few seconds to minutes per prediction for the optimization and Bayesian approaches presented here. The results demonstrate promising capabilities of deep learning models to analyze Thomson data orders of magnitude faster than conventional methods when using the neural network for standalone analysis. If more rigorous analysis is needed, neural network predictions can be used to quickly initialize other optimization methods and increase chances of success. This is especially useful when the dataset becomes very large or highly dimensional and manually refining initial conditions for the entire dataset are no longer tractable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Ohm’s Law, the Reconnection Rate, and Energy Conversion in Collisionless Magnetic Reconnection

Magnetic reconnection is a ubiquitous plasma process that transforms magnetic energy into particle energy during eruptive events throughout the universe. Reconnection not only converts energy during solar flares and geomagnetic substorms that drive space weather near Earth, but it may also play critical roles in the high energy emissions from the magnetospheres of neutron stars and black holes. In this review article, we focus on collisionless plasmas that are most relevant to reconnection in many space and astrophysical plasmas. Guided by first-principles kinetic simulations and spaceborne in-situ observations, we highlight the most recent progress in understanding this fundamental plasma process. We start by discussing the non-ideal electric field in the generalized Ohm’s law that breaks the frozen-in flux condition in ideal magnetohydrodynamics and allows magnetic reconnection to occur. We point out that this same reconnection electric field also plays an important role in sustaining the current and pressure in the current sheet and then discuss the determination of its magnitude (i.e., the reconnection rate), based on force balance and energy conservation. This approach to determining the reconnection rate is applied to kinetic current sheets with a wide variety of magnetic geometries, parameters, and background conditions. We also briefly review the key diagnostics and modeling of energy conversion around the reconnection diffusion region, seeking insights from recently developed theories. Finally, future prospects and open questions are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Customizable Aperture Geometry in Metal–Organic Frameworks for Kinetic Hydrocarbon Separation

Precise control of aperture dimensions is crucial in adsorptive separations of hydrocarbons, as it directly affects key parameters such as selectivity, capacity, diffusion, and recyclability. The development of metal–organic frameworks (MOFs) has enabled the fine-tuning of local pore environments to address important hydrocarbon separations. However, customizing the aperture geometry to tune the kinetic separation performance remains challenging. Here, we deploy a mixed-linker synthesis strategy, combining long and short linkers on fcu net Zr-MOFs with equilateral triangular apertures to construct isoreticular multivariate MOFs, NU-415 and NU-416, with tailored isosceles triangular apertures suitable for the separation of hexane isomers. Sorption, liquid batch separation, and X-ray diffraction measurements demonstrate significantly improved selectivity, capacity, stability, and recyclability of NU-415 and NU-416 compared with Zr-muconate and MOF-801. Notably, both NU-415 and NU-416 achieve uptake capacities of 2.2 mmol g –1 in 1 min with an n-hexane to 2,2-dimethylbutane selectivity over 200 in an equimolar ternary mixture at ambient conditions, comparable to leading reported materials. Mechanistic studies confirm that separation performance is predominantly governed by significant kinetic differences rather than by thermodynamics. Furthermore, the successful customization of aperture geometry not only enables superior linear to monobranched hexane selectivity in NU-415 but also demonstrates the mixed-linker synthesis strategy as a promising solution for precise and predictable pore architecture control in MOFs.

Adsorption↗
DOE OSTI2024

Influence of porous aluminosilicate grain size materials in experimental and modelling Cs + adsorption kinetics and wastewater column process

This paper focuses on the influence of the grain size of a geopolymer based adsorbent on its Cs + adsorption performances both in batch and fixed-bed process. The geopolymer phase was used as a binder to support NaY zeolite particle in a 20 wt% charged porous composite with 160 m 2 .g –1 of porous surface area. These samples were shaped with three grain sizes (50 /100/500 µm) to remove 80–90 mg/g of Cs + in batch and column operations. After their microstructural and porous characterizations, their efficiency and adsorption characteristics were investigated through adsorption isotherms and kinetic in the two processes. While the grain size has no influence on the maximal extraction capacity of the adsorbent, it strongly affects the sorption kinetic. By coupling experimental data and a modelling approach, the complex sorption mechanism was highlighted, suggesting a new insight of the contaminant sorption kinetic. Then, comparison of batch and column adsorption experiments illustrates the detailed explanation of various process parameters for column study. The results show challenges for fixed-bed column utilization by the choice of the appropriate grain size as a compromise between the material sorption kinetic and hydrodynamic considerations. Furthermore, this is of high importance to more accurately optimize the design of column adsorption to assess the transport of Cs+ in multi-porous tailored grain size materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Adsorption of terbium (III) on DGA and LN resins: Thermodynamics, isotherms, and kinetics

Two commercially available extraction chromatography (EXC) resins containing N,N,N’,N’-tetra-n-octyldiglycolamide (DGA Resin, Normal, 50 – 100 μm) and Bis(2-ethylhexyl) phosphate (LN Resin, 100 – 150 μm) were used as adsorbents to study fundamental adsorption properties such as thermodynamic values, equilibrium isotherms, and kinetic uptake models for terbium(III) adsorption. Weight distribution ratios (D w ) for terbium on DGA and LN resins were measured using a [ 160 Tb]Tb 3+ radiometric tracer in nitric acid as a function of acidity, temperature, initial analyte concentration, and equilibrium time. The D w values showed increasing binding affinity for DGA resin at high nitric acid concentrations and decreasing binding affinity for LN resins. Thermodynamic studies for DGA and LN resins revealed that the Gibbs free energy (ΔG) increased consistently with temperature. To model equilibrium data, increasingly higher parameter equilibrium isotherm models (Henry (1) < Langmuir, Freundlich (2) < Redlich-Peterson (3) < Fritz-Schluender (4)) were compared on their root mean squared errors (RMSE) and adjusted determination coefficients to determine the most applicable model. In all cases, the empirical four-parameter Fritz-Schluender isotherm demonstrated a superior fit. Similar comparisons for reaction-based kinetic models (Pseudo-first-order < Pseudo-second-order < Pseudo-n-order) revealed that the higher-order PNO model yielded a superior fit of kinetic data for both resins. Furthermore, in some cases, adsorption isotherms and kinetic models could also be modeled by a lower-order model with minimal change in error parameters. Weber-Morris plots revealed that two linear sections are observed for each resin, where the first linear segment is attributed to fast (film diffusion) adsorption of terbium, followed by slower intraparticle diffusion of terbium through the pores as the rate-limiting step. Based on the Weber-Morris plot, both film and intraparticle diffusion are involved in controlling the kinetic rate of adsorption for DGA and LN resins.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

TRANSP-TGLF core predictive modeling of the JET DT baseline scenario

In recent years, an intense modeling activity has been focused on preparing and analyzing the second JET Deuterium–Tritium (D–T) experimental campaign DTE2. Among the numerous scientific outcomes of this campaign was the unique opportunity to test and validate the state of the art of modeling tools with fusion-relevant DT plasmas using the full metallic ITER-like wall in different scenarios. This work reports on the core predictive modeling of plasma density, electron and ion temperatures (n e , T e , T i ) performed using TRANSP (Pankin et al 2025 Comput. Phys. Commun. 312 109611) coupled with Trapped Gyro-Landau Fluid (TGLF)-SAT2 (Kinsey et al 2008 Phys. Plasmas 15 055908), (Staebler et al 2021 Nucl. Fusion 61 116007) for the JET D–T baseline scenario (I p = 3.5 MA, q 95 = 3, β N < 2, with pellet pacing) (Garzotti et al 2025 Plasma Phys. Control. Fusion 67 075011). The sensitivity to different input parameters, as the $\vec{E}$ x $\vec{B}$ shear parameterization and the values of the kinetic quantities at the boundary of the prediction domain (ρ = 0.85) has been assessed, identifying the confidence interval of the prediction results. In particular, the dependence of the electron density profile on the particle source parameters has been studied, identifying the ionization source as the main cause for the density gradient under-prediction obtained by TRANSP-TGLF, reported in (Hyun-Tae et al 2023 Nucl. Fusion 63 112004).

JET↗