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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Derivation of physical equations for high-speed laser welding using large language models

It is challenging to formulate complex physical phenomena that occur in a manufacturing process, particularly when the available data are limited, rendering conventional data-driven approaches ineffective. This study aims to predict humping onset in high-speed laser welding by introducing a novel framework, namely text-to-equations generative pre-trained transformer (T2EGPT). This method leverages the capabilities of large language models (LLMs), in combination with sparse experimental data and enriched literature data, to derive an interpretable and generalizable equation for predicting humping initiation. By capturing key correlations among physical parameters, T2EGPT generates a compact and dimensionless expression that accurately predicts hump formation. The equation reveals that humping arises from the interplay between inertia-driven backward melt flow and capillary-driven surface stabilization, where inertial forces drive molten metal backward and capillary forces resist surface deformation. Furthermore, compared to traditional data-driven models, T2EGPT demonstrates enhanced predictive accuracy and cross-material transferability. More broadly, this study highlights the potential of LLMs to integrate textual information with data-driven discovery, enabling the extraction of physical laws in data-scarce scientific domains.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Machine learning based prediction of airflow maldistribution in air-to-refrigerant heat exchangers

Flow maldistribution is a common challenge in heat exchanger (HX) design and particularly important for air-to-refrigerant geometries where capacity losses can approach 65%. This has a major impact on central air conditioning systems, as compact duct design motivates the use of A-type HXs which are known to be affected by airflow maldistribution. Because velocity profiles are difficult to predict, components are often oversized leading to increased material cost, system footprint, and refrigerant charge. Several studies detail airflow maldistribution for individual HXs and packages, but findings cannot always be extrapolated to new designs. In this work, a machine learning (ML) based flow profile prediction framework is developed and applied to two common package configurations: (i) A-type and (ii) U-type HXs, across a broad range of HX geometries and flow rates. Porous media CFD simulations are validated against independent data for both package types as well as comprehensive in house measurements for a finless geometry with shape optimized non-round tubes, which validates the framework for new heat transfer surfaces. The ML models are trained on the porous media CFD simulations, predicting volumetric flow rate (VFR) within 1.1% and 1.9% with maximum relative L 2 norm errors of 0.48 and 0.65, respectively, while also delivering 10 5 speed up factor compared to full porous media CFD. HX level simulations show an up to 9% reduction in heat transfer from flow maldistribution, with greater losses occurring at smaller half apex angles. This framework enables rapid and highly accurate prediction of airflow maldistribution induced capacity degradation.

42 ENGINEERING↗
DOE OSTI2024

Evaluation of methods for characterizing the fine particulate matter emissions from aircraft and other diffusion flame combustion aerosol sources

The U. S. Environmental Protection Agency in collaboration with the U. S. Air Force Arnold Engineering Development Complex conducted the VAriable Response In Aircraft nvPM Testing (VARIAnT) 3 and 4 test campaigns to compare nvPM emissions measurements from a variety of diffusion flame combustion aerosol sources (DFCASs), including a Cummins diesel engine, a diesel powered generator, two gas turbine start carts, a J85-GE-5 turbojet engine burning multiple fuels, and a Mini-CAST soot generator. The VARIAnT research program has conducted four test campaigns to date with the VARIAnT 3 and 4 test campaigns focusing on BC mass instrument performance, use of gas turbine engine sources for BC mass instrument calibration, and the characterization of the aerosols produced from the combustion sources. Results from both campaigns revealed agreement of about 20% between the AVL Micro-Soot Sensor, the Cavity Attenuated Phase Shift (CAPS PMSSA) monitor and the thermal-optical reference method for elemental carbon (EC), independent of the calibration source used. For the Artium LII-300, the measured mass concentrations in VARIAnT3 fall within 18% and in VARIAnT4 fall within 32% of the reference EC mass concentration when calibrated on a combustor rig in VARIAnT3 and on a LGT-60 start cart in VARIAnT4, respectively. It was also found that the three mass instrument types (MSS, CAPS PMSSA, and LII-300) can exhibit different BC to reference EC ratios depending on the emission source that appear to correlate to particle geometric mean mobility diameter, morphology, or some other parameter associated with particle geometric mean diameter (GMD) with the LII-300 showing a slightly stronger apparent trend with GMD. Systematic differences in LII-300 measured mass concentrations have been reduced by calibrating with a turbine combustion source (combustor or turbine engine). With respect to the particle size measurements made, the sizing instruments (TSI SMPS, TSI EEPS, and Cambustion DMS 500) were found to be in general agreement in terms of size distributions and concentrations with some exceptions. Teflon filter measurements of the total aerosol mass produced by the various DFCASs differed from the reference EC, BC, and integrated particle sized distribution measured aerosol masses. The Teflon filter measured mass was 30 to 40% greater than the reference EC and 50 to 60% greater than the BC mass for the J85 in both test campaigns. The measurements of particle size distributions and single particle analysis by miniSPLAT indicated the presence of large particles (>100 nm) having more compact morphologies, higher effective density, and a composition dominated by OC and ash. This increased large particle fraction is also associated with higher values of single scattering albedo measured by the CAPS PMSSA instrument and higher OC/EC measurements. These measurements indicate gas turbine engine emissions can be a more heterogeneous mix of particle types beyond the original E31 assumption that it is mainly composed of black carbon.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Multiple-charging effects on the CCN activity and hygroscopicity of surrogate black carbon particles

Accurate measurements of cloud condensation nuclei (CCN) activity and hygroscopicity of black carbon (BC)-containing particles are particularly important because of the positive climate forcing from these particles. Such measurements are typically conducted on particles selected by a Differential Mobility Analyzer (DMA), which in addition to singly charged particles transmits multiply charged larger particles that have the same electrical mobility. These larger particles activate at lower supersaturations than the singly charged particles, biasing measurements and resulting in overestimation of CCN activity and hygroscopicity parameter (κ). Here, we measure the CCN activity and determine κ for different BC surrogates with electrical mobility diameters from 100 to 200 nm selected 1) only by electrical mobility with a DMA, and 2) by both electrical mobility and mass using a DMA and a Centrifugal Particle Mass Analyzer (CPMA), thus allowing selection of only singly charged particles. We demonstrate the use of the DMA-CPMA system in resolving biases caused by multiply charged particles, and we show that the effect of multiple charging on the CCN activity of the BC particles is strongly influenced by morphology dispersion, i.e., the variability due to the range of morphologies of particles that have the same electrical mobility and mass. Finally, our findings show that electrical mobility-based methods alone are unlikely to lead to accurate results in measurements of CCN activation and hygroscopicity of BC particles, even for those with a more compact morphology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Correlation of optical properties with particle size, morphology, and polymorph of fine- and nano-particle formulations of titanium dioxide powders

Titanium dioxide (TiO 2 ) particulates are known to exhibit different visible and infrared optical properties compared to the bulk material, showing strong dependence on particle size, crystal structure, and morphology. In this study, the optical properties, sizes, and morphologies of TiO 2 particles from two different sources (nano and fine powders) having a) nominally different particle sizes and b) various crystal polymorph mixture fractions are compared using a combination of single particle mass spectrometry, optical spectroscopies, and aerosol characterization methods. The nano sample was found to be largely particles of the anatase polymorph (88% by mass), while the fine sample was found to consist largely of rutile particles (95% by mass). Two distinct particle morphologies (fractal and compact) were found in each powder sample and could be identified and separated in-situ based on particle aerodynamic properties. The attenuation of near-infrared, visible and ultraviolet light by TiO 2 particles shows strong dependence on particle morphology. Furthermore, while the fine particles were found to have larger near-infrared (675–800 nm) extinction coefficients by mass than the nanoparticles, the reverse was true in the ultraviolet and visible regions (370–675 nm). However, for polydisperse particles with different sizes and shapes, the optical behaviors are not straightforward to directly correlate to a combination of physical parameters.

Lockwood, Schuyler P. [Pacific Northwest National ↗
DOE OSTI2025

Unlocking hidden information in sparse small-angle neutron scattering measurements

Hypothesis Small-Angle Neutron Scattering (SANS) is a powerful technique for studying soft matter systems such as colloids, polymers, and lyotropic phases, providing nanoscale structural insights. However, its effectiveness is limited by low neutron flux, leading to long acquisition times and noisy data. Here, we hypothesize that Bayesian statistical inference using Gaussian Process Regression (GPR) can reconstruct high-fidelity scattering data from sparse measurements by leveraging intensity smoothness and continuity. Experiments and Simulations The method was benchmarked computationally and validated through SANS experiments on various soft matter systems, including wormlike micelles, colloidal suspensions, polymeric structures, and lyotropic phases. GPR-based inference was applied to both experimental and synthetic data to evaluate its effectiveness in noise reduction and intensity reconstruction. Findings GPR significantly enhances SANS data quality and therefore reducing measurement times by up to two orders of magnitude. This cost-effective approach maximizes experimental efficiency, enabling high-throughput studies and real-time monitoring of dynamic systems. It is particularly beneficial for weakly scattering and time-sensitive studies. Beyond SANS, this framework applies to other low-SNR techniques, including laboratory-based small-angle X-ray scattering and various dynamical scattering methods. Furthermore, it offers transformative potential for compact neutron sources, enhancing their viability for structural analysis in resource-limited settings.

Small angle neutron scattering↗
DOE OSTI2026

Quantitative SANS and multi-model analysis of spacer-dependent micellization of urea-based gemini surfactants

The micellization behavior of urea-based cationic gemini surfactants was investigated using small-angle neutron scattering (SANS) with multi-model form factor analysis. A homologous series of surfactants with urea group included in the hydrophobic tail and polymethylene spacers consisting of two to ten methylene units was analyzed using three form factor models: a core–shell ellipsoid and two variants of homogeneous ellipsoids. The results from all models show a consistent trend of the micelle structures, confirming that the spacer length critically influences micellar geometry, aggregation number, and hydration. The surfactant with four CH 2 groups in the spacer formed the largest micelles with the highest aggregation number, while longer spacers led to progressively smaller, more compact aggregates. The shell hydration—quantified as the volume fraction of heavy water within the hydrophilic region—decreased systematically with increasing spacer length due to enhanced hydrophobicity of the headgroup-spacer region. Intermicellar interactions, modeled as screened Coulomb interaction using the rescaled mean spherical approximation (RMSA), revealed the strongest electrostatic repulsion for the case of four methylene groups in the spacer, corresponding to the highest micellar charge and largest interparticle spacing. The observed spacer-dependent trends were robust across all modeling approaches, demonstrating that the spacer length serves as a key structural determinant of self-assembly in this type of urea-based gemini systems. These findings provide insight into the design of gemini surfactants with tailored aggregation behavior for applications in drug delivery, nanostructure templating, and solubilization technologies.

Core–shell ellipsoid model↗
DOE OSTI2024

A high-order, localized-artificial-diffusivity method for Eulerian simulation of multi-material elastic-plastic deformation with strain hardening

A high-order method for Eulerian simulation of material undergoing large elastic–plastic deformation is developed. Thermodynamically consistent hyperelastic constitutive relations are assumed, facilitating the treatment of solids, liquids, and gases in a unified manner. Here, the method enables the simulation of multi-material interactions using a diffuse interface approach. Numerical capturing of material interfaces, shock waves, contact surfaces, and elastic-plastic strain discontinuities using high-order compact-difference schemes is assisted by Localized Artificial Diffusivity (LAD). In the new setting involving elastic–plastic deformation, the previously established terms for the artificial properties are verified to effectively regularize normal shocks. Additional LAD terms are introduced to the elastic and plastic kinematic equations to regularize shear shocks and other strain discontinuities, improving solution stability. Other important features of the method that improve robustness include the numerical treatment of compatibility terms in the kinematic equations, and the treatment of rotation. Particular emphasis is focused toward new advancements of the methods for plastic-deformation integration and the associated strain hardening of the material, including rate-dependent plasticity. The method is demonstrated on a variety of test problems, including 1-D impacts, a variant of the Shu-Osher problem, a Taylor impact, and a Richtmyer-Meshkov instability between two elastic–plastic solids with strain hardening.

42 ENGINEERING↗
DOE OSTI2024

A fully implicit, asymptotic-preserving, semi-Lagrangian algorithm for the time dependent anisotropic heat transport equation

In this paper, we extend the operator-split asymptotic-preserving, semi-Lagrangian algorithm for time dependent anisotropic heat transport equation proposed in Chacón et al. (2014) [18] to use a fully implicit time integration with backward differentiation formulas. The proposed implicit method can deal with arbitrary heat-transport anisotropy ratios $\mathcal{X}$∥ /$ \mathcal{X}$⟂ $\ggg$ 1 (with $\mathcal{X}$∥, $ \mathcal{X}$⟂ the parallel and perpendicular heat diffusivities, respectively) in complicated magnetic field topologies in an accurate and efficient manner. Further, the implicit algorithm is second-order accurate temporally and demonstrates an accurate treatment at boundary layers (e.g., island separatrices), which was not ensured by the operator-split implementation. The condition number of the resulting algebraic system is independent of the anisotropy ratio, and is inverted with preconditioned GMRES. We propose a simple preconditioner that renders the finite-dimensional linear operator compact, resulting in mesh-independent convergence rates for topologically simple magnetic fields, and convergence rates scaling as ~ (NΔt) 1/4 (with N the total mesh size and Δt the timestep) in topologically complex magnetic-field configurations. We demonstrate the accuracy and performance of the approach with test problems of varying complexity, including an analytically tractable boundary-layer problem in a straight magnetic field, and a topologically complex magnetic field featuring magnetic islands with extreme anisotropy ratios $\mathcal{X}$∥ /$ \mathcal{X}$⟂ = 10 10 ) .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

An extension of the localized artificial diffusivity method for immiscible and high density ratio flows

The localized artificial diffusivity (LAD) method is widely regarded as the preferred multi-material regularization scheme for the compact finite difference method, because it is conservative, easy to implement, and generally robust for a wide range of multi-material problems. However, traditional LAD methods face significant challenges when applied to flows with large density ratios and when maintaining thermodynamic equilibrium across material interfaces. These limitations arise from the formulation of the artificial diffusivity flux and the reliance on enthalpy diffusion for interface regularization. Additionally, traditional LAD methods struggle to ensure stability under large density ratio conditions, fail to maintain a finite interface thickness, and are therefore unsuitable for modeling immiscible interfaces. Here, in this work, we discuss the origins of these issues in traditional LAD methods and propose modifications which enable the simulation of large density ratio and immiscible flows. The proposed method targets the artificial diffusion fluxes at gradients and ringing in the volume fraction, rather than the mass fraction in traditional methods, to consistently regularize large density ratio interfaces. Furthermore, the proposed method introduces an artificial bulk density diffusion term to enforce equilibrium conditions across interfaces. To address the challenge of modeling immiscible flows, a conservative diffuse interface term is incorporated into the formulation to ensure a finite interface thickness. Specific consideration is taken in the design of the method to ensure that these crucial properties are maintained for N -material flows. The effectiveness of the proposed method is demonstrated through a series of canonical test cases, and its accuracy is validated by comparison with experimental data on micro-bubble collapse in water. These results highlight the method’s robustness and its ability to overcome the limitations of traditional LAD approaches.

Artificial diffusivity↗
DOE OSTI2026

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗
DOE OSTI2025

How do substituted phenyl-based cations affect the structure-property-stability relationship of low-dimensional perovskites?

Incorporating organic bulky cations in the precursor or post-treatment to achieve two-dimensional/three-dimensional (2D/3D) heterojunction is an effective strategy for enhancing the stability of perovskite materials. However, the issue of insufficient charge transport in 2D perovskites limits their development, and the fundamental mechanism of out-of-plane carrier transport remains unclear. This study designed and synthesized seven organic phenyl-core cations, differentiated at the 1- and 1,4-positions, and identified the impacts on the corresponding properties of the 2D crystalline perovskite. Shorter cations facilitated a more compact arrangement of adjacent inorganic layers, aligning to favor charge transport along the vertical direction. In addition, introducing high electronegativity led to increased intermolecular interactions, resulting in enhanced structural stability and improved phenyl ring π-orbital overlap and interlayer electron coupling, yielding efficient charge transport. Resilience to thermal stressing of the perovskite was strongly correlated with the carbon chain length of the spacer cations. Here, the increase in cation length and the reduction in the rigidity of the amino-terminal both aided in the dispersion of thermal stress in the inorganic framework. Additional hydrogen bonding also contributed to mitigating structural disorder.

14 SOLAR ENERGY↗
DOE OSTI2024

Pressureless sintering of lithium hydride

Lithium Hydride is a material of growing importance for addressing technological challenges related to nuclear fusion, long-term human space travel, and thermal energy storage. Pressureless sintering provides a straightforward, scalable approach to produce dense LiH parts of all sizes and shapes. Pressed LiH green compacts were sintered at heating rates from 2.5 to 20 °C/min to 650 °C, yielding densities up to 96 ± 1.4 %, with densification initiating at 500 °C. Here, a validated master sintering curve was constructed with a sintering apparent activation energy of 135 kJ/mol. X-ray diffraction and simultaneous thermal analysis revealed Li 2 O formation from 300 – 550 °C and decomposition of LiH into Li metal at 550 °C, each reflected as deviations in the master sintering curve. Computed tomography after thermal treatment to 550 °C showed the formation of corrosion products, and after thermal treatment to 650 °C LiH reduction to Li most significantly at exposed surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enhancing low-temperature sintering in the MgO-LiF system: Mechanistic insights

In the present article, we provide compelling evidence that minor (1 wt%) additions of micron and nanometre-sized LiF particles in MgO decompose leading to free Li diffusing into MgO surfaces enhancing vacancy production during direct current sintering. The addition of nanometre-sized LiF particles leads to a > 500 °C reduction in the sintering temperature and over 99 % theoretical density of final consolidated compacts. Correlating differential scanning calorimetry with in-situ x-ray diffraction, together with Schottky calculations, post sintering electron microscopy and laser induced breakdown spectroscopy, we uncover critical insights into this impressive reduction in sintering temperature. Our quantitative analysis reveals that MgO and LiF interact at low temperatures with the diffusion of Li into the surface of MgO particles due to the intrinsic structural disorder of the LiF and MgO crystallites. Nanometre-sized LiF particles were found to react the most at low temperatures due to their increased structural disorder. Our multimodal characterization points to a Li-promoted densification and sintering mechanism. This impressive reduction in sintering temperature can be harnessed to promote low-temperature fabrication of MgO-based composites for technological applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fast-rate joining of thermoplastic composites using integrated additive manufacturing and compression molding process

The integration of additive manufacturing (AM) technology with compression molding (CM), has emerged as a high-performance composite manufacturing technology in recent years. In the AM-CM process, quickly deposited AM preform on a mold undergoes a rapid compaction cycle to fabricate structurally robust composite parts due to highly controlled fiber alignment (from AM) and reduced porosity (from CM). Currently, AMCM-based part size is limited by the size of the mold volume, thus posing a challenge to manufacture scalable parts. Here, this work focuses on joining techniques developed to enable fast rate joining of short fiber-reinforced thermoplastic composite parts using the AM-CM process. Acrylonitrile butadiene styrene resin reinforced with 20 wt% short carbon fiber composites was printed onto a flat mold and pressed under a hydraulic press. Fabricated panels were joined by the (a) mechanical impression at the joining interface and (b) over-molded continuous carbon fiber (CCF) sheet. Tensile tests were performed to characterize the joining strength of both mechanical impression-based joints and CCF over molded joints. Among the mechanical impression-based joints, a U-shape channel allowed the fibers to flow between two joint parts, and 280 % increased mechanical properties were observed. The continuous carbon fiber-based over molded joint CCF showed 350 % increase in tensile strength compared to the butt joints.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Optimized manufacturing process for multilayer two-dimensional focusing mirrors in laboratory X-ray applications

Recent advances in laboratory X-ray applications require high-performance optical components that achieve exceptional imaging resolution and beam uniformity within compact experimental setups. Montel mirrors have become a preferred solution due to their unique dual-reflection focusing mechanism and a space-efficient design. Here, in this study, we present an effective manufacturing process for producing Montel mirrors tailored to focus laboratory X-ray beams. The mirrors were fabricated from single-crystal silicon substrates, chosen for their high mechanical stability and compatibility with precision polishing techniques. Our approach begins with the integration of a deterministic chemo-mechanical polishing (CMP)-based pre-shaping step followed by ion beam figuring (IBF), significantly improving manufacturing efficiency. Subsequently, our custom-developed advanced metrology and IBF techniques were employed for fabricating an off-axis, elliptical cylinder Montel mirror system with a 6-mrad total slope, with stringent optical specifications. While post-IBF processes, including multilayer coating, dicing, and gluing, introduced minor surface errors, yet their impact on performance remained negligible. The Montel mirrors manufactured with the optimized process exhibited significantly improved beam uniformity and a reduced focal spot size. These findings validate our approach as a viable solution for high-precision Montel mirror fabrication and facilitate further advancements in laboratory X-ray applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimizing Bendability and Hardness of Age-Hardenable Aluminum Sheets through Local Thermo-Mechanical Processing

This paper introduces a novel thermo-mechanical process to modify the local mechanical properties of 6xxx aluminum (Al-Mg-Si-Cu) alloy sheets. In this process, two pairs of rollers travel along the length of a sheet while locally bending and unbending it so that the final shape and thickness of the sheet remains unchanged. Room temperature bending/unbending (B/U) produces a deformation gradient through thickness and local hardening in both T4 and T6 sheets (with 41% and 18% greater Vickers hardness, respectively). High temperature bending/unbending performed at ~ 500°C via induction heating, produces significant improvements in local formability as measured by bend testing. Formability levels equivalent to the as-received T4 temper are achieved within the processed zones of T6 sheets with bend angles of ~ 150°, without disturbing the T6 temper in the remainder of the sheet. Finite element simulations and characterization explained the mechanical property improvements and the heterogenous microstructure with weakened Cube texture. Due to its similarity with the roller hemming process, and its compact dimensions, the apparatus developed for B/U has the potential for seamless integration with roller hemming robots to selectively process high strength aluminum sheet materials within mass-production settings.

Efe, Mert [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2024

Synchrotron micro-computed tomography analysis of neutron-irradiated U-Mo fuel

The three-dimensional (3D) microstructure of neutron-irradiated uranium-10 wt.% molybdenum (U-10Mo) fuel with a burn-up of 9.8 × 10 21 fissions/cm 3 was characterized using a novel, multi-modal synchrotron micro-computed tomography approach combining propagation-based phase-contrast enhanced and absorption contrast techniques. The porosity development, porosity interconnectedness, swelling, composition, local thickness of the zirconium (Zr) diffusion barrier, and the influence of the fuel–cladding interaction on the local composition and pore morphology, were uniquely determined in 3D. Two cuboids were produced using a focused ion beam-scanning electron microscope at the Zr diffusion barrier–fuel interface and in the bulk fuel. The bulk fuel sample swelled by 53.3 [+9.7/−3.1]%, while the fuel near the Zr–fuel interface swelled by 63.3 [+14.7/−7.2]%. The average local thickness of the Zr diffusion barrier decreased by 53 %, compared to the expected pre-irradiated thickness. Four pore morphology regions were identified initiating parallel to the fuel–Zr interaction region: (1) an interaction layer of suppressed porosity, (2) a layer of elongated and interconnected porosity, (3) a transition zone of low porosity, and (4) a layer of unoriented porosity representative of the bulk fuel behavior. The increase in porosity near the diffusion barrier corresponded to a higher U concentration compared to that in the bulk fuel. The interconnected porosity in the fuel near the diffusion barrier was extensive and oriented parallel to the diffusion barrier, while the bulk fuel had more compact and isolated pore networks. The interaction layer, despite having suppressed porosity, was nearly 100 wt.% U. Porosity suppression at the diffusion barrier corresponds to the expected reduction in radiation-driven diffusion of Xe at the interface despite the anticipated increase in fission product nucleation originating from a higher U concentration. In conclusion, the novel 3D insights of the porosity, swelling, and compositional variations characterized herein can improve the fidelity of fuel performance codes for proliferation-resistant fuels for research and test reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗