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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 19 records

Ultrasonic Testing (UT) Reference Standard for Additive Manufacturing Quality Control

Many additive manufacturing (AM) reference standards for build quality verification concentrate primarily on external features. In contrast, EPRI proposes a pair of AM reference blocks that feature only internal and embedded forms. This report presents, collates, and discusses quantitative nondestructive evaluation (NDE) results from various techniques, including visual testing (VT), radiographic testing (RT), conventional ultrasonic testing (UT), and full matrix capture/total focusing method (FMC/TFM) scanning. The blocks are intended, as part of a larger series of blocks, to evaluate build quality and the relative performance of different NDE techniques in detecting various features. The limits of detectability and the closeness of the as-built shape to the intended form for certain features are quantified, facilitating direct comparison. Upon analysis of the results of this testing, it was found that FMC/TFM was consistently superior in detection, followed by conventional UT, then VT, and lastly RT.

36 MATERIALS SCIENCE↗

Ultrasonic Testing (UT) and Computed Tomography (CT) Comparative Scanning of Proposed Additive Manufacturing Reference Standard

This report presents qualitative results of ultrasonic full matrix capture/total focusing method (FMC/TFM) scanning of two series of blocks, additively manufactured by powder bed fusion, containing a variety of internal features and structures that would not be achievable by conventional manufacturing techniques. The purpose of the first series of additively manufactured (AM) blocks was to explore the possibility of building calibration blocks for FMC/TFM ultrasonic testing (UT). It was confirmed that AM is a suitable candidate for generation of unusual and novel reflector forms, such as rotating slots, purposely embedded voids, and tapering holes, and that FMC/TFM was very capable of characterizing them. The intended use of the second series of AM blocks was as UT reference blocks to characterize the AM process quality or the interrogating UT technique. The larger block in this series was scanned from multiple faces, using multiple UT methods (conventional UT and FMC/TFM) and X-ray computed tomography for comparative purposes. The performance of each method was quantified by a metric corresponding to the detection limit of each feature, and the quantitative results are discussed.

36 MATERIALS SCIENCE↗

Cooperative Research and Development Agreement between National Energy Technology Laboratory and Electric Power Research Institute (EPRI) [Abstract]

Carbon dioxide (CO 2 ) capture from flue gas generated by fossil fuel-fired power plants has been proposed as an efficient approach to limit CO 2 emissions to the atmosphere. Due to the high cyclic CO 2 sorption capacity, well-tuned adsorption chemistry and non-volatility, solid sorbents are widely studied for CO 2 capture processes such as pressure swing adsorption (PSA) and temperature swing adsorption (TSA). Realistic applications of traditional solid sorbent systems face many challenges since moisture and heat management are problematic and solid-solid heat exchange is inefficient. Recently, a novel solid sorbent system, the sorbent polymer composite (SPC), has been developed to overcome those challenges in an energy-saving CO 2 capture process using TSA membrane contactors. A SPC material is comprised of a powdered solid sorbent embedded into a hydrophobic and porous polymer matrix. It allows gases to permeate through and achieve full contact with the sorbents while rejecting water moisture in the CO 2 capture process. In this collaborative research, NETL will conduct performance testing of a novel SPC material and EPRI will conduct a cost analysis based on that performance data.

20 FOSSIL-FUELED POWER PLANTS↗

Capturing electronic decoherence in quantum-classical dynamics using the ring-polymer-surface-hopping–density-matrix approach

Simulations of coupled electronic and nuclear dynamics in molecules can be quite challenging due to the involved interplay of the many degrees of freedom. Because a full quantum treatment of both electrons and nuclei is computationally very demanding, it is generally restricted to model systems or rather small molecules and short timescales. Mixed quantum-classical dynamics methods such as Tully's fewest switches surface hopping (FSSH) can be used to overcome this limitation. However, FSSH is known to poorly describe electronic coherences and decoherence phenomena. Here, we present an approach that combines FSSH with ring-polymer molecular dynamics (RPMD) in a specific way that aims to alleviate the coherence problem. Termed the ring-polymer-surface-hopping–density-matrix approach, this method uses an electronic density-matrix formulation to calculate surface hopping rates. Additionally, this incorporates decoherence effects into FSSH in a natural way by taking into account the spatial spreading of the ring polymer that mimics the width of a nuclear wave packet in each RPMD trajectory. By applying our method to Tully's one-dimensional model system, we demonstrate that this method captures a crucial decoherence mechanism that is missing in FSSH. Furthermore, our method turns out to be superior at describing electronic coherences compared with earlier attempts at combining RPMD and FSSH.

74 ATOMIC AND MOLECULAR PHYSICS↗

Role of Coulomb interaction in the phase formation of fcc Ce: Correlation matrix renormalization theory

The effect of electronic Coulomb interaction on the phase formation of fcc Ce lattice is investigated by full ab initio calculations without adjustable Coulomb U and J parameters using the Gutzwiller wavefunction-based correlation matrix renormalization theory (CMRT). Its total energy and pressure as a function of volume agree reasonably well with existing DFT+Gutzwiller calculations and experiments, indicating correct capture of electronic correlation and screening effects within the CMRT formalism. Here, a stable phase is found in line with the experimental α-Ce phase, and a lurking phase is identified supposedly linked with the experimental γ-Ce phase. A criterion based on the local 4f electron charge fluctuation is introduced to confirm the distinct electronic correlation natures of both phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Power capture and power take-off load of a self-balanced dual-flap oscillating surge wave energy converter

Wave energy converters are an important part of future renewable energy infrastructure. Predicting their power matrix, capture width ratio, and power take-off loads at a targeted site is required for performance assessment before deployment. Because their testing is very expensive, numerical modeling and simulations play a significant role in those assessments. Linear potential flow theory has limited accuracy under large amplitude wave forcing. More accurate predictions can be obtained by using higher-fidelity models, which are computationally expensive. We present a framework for multi-fidelity numerical simulations to determine the hydrodynamic response, wave capture capability, and power take-off load of a full-scale dual-flap oscillating surge wave energy converter. This design exploits out-of-phase motion by setting the distance between the flaps to half the wavelength of the most occurring wave. The simulations are validated using a 1:10 model experiments in a wave tank. Based on these validations, it was determined that Euler simulations provide an acceptable prediction with 90% reduction in computational time with only 11% error. Utilizing Euler simulations at full-scale, the results demonstrate that the annual electrical energy output is 1.79 GWh under regular wave conditions. Here, one significant improvement over single-flap designs is the capture width ratio which exceeds unity.

16 TIDAL AND WAVE POWER↗

3D TRISO particle-explicit compact meshing

The TRI-structural ISOtropic (TRISO) layered fuel particle is a robust nuclear fuel form offering enhanced safety and performance for advanced reactor concepts, including high-temperature gas-cooled reactors and other Generation IV designs. These poppy-seed-sized particles are embedded in a graphite matrix to form fuel elements that must withstand elevated temperatures and high burn-up levels. The heterogeneous nature of these fuel elements — comprising thousands of randomly distributed TRISO particles — produces complex stress fields and thermal gradients that one- and two-dimensional models cannot accurately capture. While three-dimensional modeling has improved predictions of dimensional changes, internal pressure buildup, and fission product transport under irradiation, current approaches rely on homogenized material properties that are known to have considerable divergence from experimental observations. This work presents a methodology for optimized random packing of TRISO fuel compacts and full three-dimensional mesh generation within the BISON fuel performance code, with each particle coating layer individually discretized. The resulting mesh was demonstrated through heat conduction simulations under representative in-reactor operating conditions, showing strong agreement with expected behavior. This capability enables detailed analysis of particle-to-particle interactions, matrix cracking mechanisms, and the statistical distribution of coating layer failures — all of which directly govern fuel performance and safety margins.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Machine Learning Surrogates of a Fuel Matrix Degradation Process Model for Performance Assessment of a Nuclear Waste Repository

Spent nuclear fuel repository simulations are currently not able to incorporate detailed fuel matrix degradation (FMD) process models due to their computational cost, especially when large numbers of waste packages breach. The current paper uses machine learning to develop artificial neural network and k-nearest neighbor regression surrogate models that approximate the detailed FMD process model while being computationally much faster to evaluate. Further, using fuel cask temperature, dose rate, and the environmental concentrations of CO 3 2- , O 2 , Fe 2+ , and H 2 as inputs, these surrogates show good agreement with the FMD process model predictions of the UO 2 degradation rate for conditions within the range of the training data. A demonstration in a full-scale shale repository reference case simulation shows that the incorporation of the surrogate models captures local and temporal environmental effects on fuel degradation rates while retaining good computational efficiency.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators

The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable. Classical equation-free (EF) approaches rely on fine-scale simulators treated as black-box timesteppers. However, repeated simulations for steady-state computation, linearization, and control design are often computationally prohibitive, or the microscopic timestepper may not even be available, leaving us with data as the only resource. We propose a data-driven alternative that uses local neural operators, trained on spatiotemporal microscopic/mesoscopic data, to obtain efficient short-time solution operators. These surrogates are employed within Krylov subspace methods to compute coarse steady and unsteady-states, while also providing Jacobian information in a matrix-free manner. Krylov-Arnoldi iterations then approximate the dominant eigenspectrum, yielding reduced models that capture the open-loop slow dynamics without explicit Jacobian assembly. Both discrete-time Linear Quadratic Regulator (dLQR) and pole-placement (PP) controllers are based on this reduced system and lifted back to the full nonlinear dynamics, thereby closing the feedback loop.

93B52, 93C20, 47N70, 65J15, 65M32, 68T07, 68T20, 6↗

Neutron Capture and Transmission Measurements and Evaluation of 54 Fe at the RPI LINAC [Slides]

This presentation covers neutron capture and transmission measurements and evaluation of 54 Fe (Iron) at the Rensselaer Polytechnic Insitute (RPI) Linear Accelerator (LINAC). Presentation conclusions find that 54 Fe is near its conclusion, covariance matrix generation is needed for both experiments before data is made available and released (Completion by April 2023). RPI will be conducting a full Resolved Resonance Region (RRR) evaluation following release of data (Completion by September 2023). Additionally, the neutron beam imager shows promise in providing an easy way to align samples in the most intense part of the neutron beam and there will be a new evaluation that will offer improvements in crit safety, shielding, and stellar applications.

07 ISOTOPE AND RADIATION SOURCES↗

Assessing the National Off-Cycle Benefits of 2-Layer HVAC Technology Using Dynamometer Testing and a National Simulation Framework

Some CO2-reducing technologies have real-world benefits not captured by regulatory testing methods. This paper documents a two-layer heating, ventilation, and air-conditioning (HVAC) system that facilitates faster engine warmup through strategic increased air recirculation. The performance of this technology was assessed on a 2020 Hyundai Sonata. Empirical performance of the technology was obtained through dynamometer tests at Argonne National Laboratory. Performance of the vehicle across multiple cycles and cell ambient temperatures with the two-layer technology active and inactive indicated fuel consumption reduction in nearly all cases. A thermally sensitive powertrain model, the National Renewable Energy Laboratory's FASTSim Hot, was calibrated and validated against vehicle testing data. The developed model included the engine, cabin, and HVAC system controls. Validation of component thermal models and engine efficiency ensured accurate thermal dynamics, fuel consumption, and two-layer benefit. The real-world benefit of the two-layer technology was calculated by simulating the validated powertrain model across a representative test matrix comparing performance with and without the two-layer system. Simulation across the test matrix revealed a real-world representative benefit of 0.0835%. Analysis of test matrix results at the regional level revealed the most benefit in cold climates and rural regions. Mean results across cycle length sensitivity simulations revealed a larger real-world benefit of 0.0872%. These benefit values can be considered a more accurate assessment of real-world technology performance. Future work is planned to explore the requisite number of drive cycles to ensure the full technology benefit is captured.

2-layer↗

FEED Study of CarbonCapture Inc DAC and CarbonCure Utilization Technologies Using United States Steel’s Gary Works Plant Waste Heat (Final Report)

The University of Illinois at Urbana-Champaign (UIUC) led this project to produce a front-end engineering design (FEED) study of an advanced Direct Air Capture and Utilization System (DACUS) system that can remove a minimum of 5,000 tonnes/yr net of carbon dioxide from air (based on cradle-to-gate LCA) and utilizing the CO 2 to produce low carbon intensity ready mix concrete. The designed system, if built, would be larger than any currently existing Direct Air Capture (DAC) collector in the U.S. Such carbon capture technologies are critical to meeting the goals of the DOE’s program to accelerate climate-critical technology. In addition to the power sector, industrial facilities for the manufacture of steel and cement/concrete are among the major sources of anthropogenic CO 2 . DAC is a promising new technology for reducing CO 2 , a potent greenhouse gas, in the atmosphere but is expensive, in part due to the energy required to adsorb and desorb captured CO 2 during cycles. By integrating CarbonCapture Inc. (CCI) DAC modules at United States Steel's Gary Works (USS) and utilizing the site's waste heat, energy, and location this project evaluates the feasibility of utilizing the captured CO 2 and the logistics of transportation. CarbonCapture Inc. has developed an innovative DAC system using novel adsorbents to cost-effectively capture CO 2 . The captured, liquified gas will be trucked to ready-mix concrete plants within the region, the closest of which is approximately 3.5 miles away, where CarbonCure will inject it into concrete during the mixing process at the facilities. The carbon dioxide reacts with concrete, mineralizing into calcium carbonate (CaCO 3 ), permanently locking the greenhouse gas into the matrix of the building material. This FEED study demonstrated a full CO 2 value chain for DACUS from industrial facilities. It also provided a means for Visage Energy Corp. (Visage) to assess the impact of this holistic approach on job creation, regional economic impact, and environmental justice. The project team also included Sargent & Lundy (S&L) to provide the constructability review and costing of the integration of the DAC with the steel plant. Ecotek Engineering USA, LLC designed the outside battery limit (OSBL) infrastructure to connect the DAC and the plant. Activities performed during the project included: (1) Project Management Plan; (2) Technology Maturation Plan (TMP); (3) Initial Workforce Readiness Plan; (4) Workforce Readiness Plan; (5) Front-End Engineering Design (FEED) Study; (6) Project Design Basis; (7) Hazards and Operability (HAZOP) Study; (8) Constructability Review; (9) Project Cost Assessment; (10) Logistics Analysis of CO 2 Transportation to the Utilization Site; (11) Business Case Analysis; (12) Life Cycle Analysis (LCA); (13) Environmental Health and Safety (EH&S) Analysis; (14) Environmental Justice Analysis; and (15) Economic Revitalization and Job Creation Outcomes Analysis. This report provides a summary of the outcomes and results of the project, which was performed between Oct. 1, 2022, through Sept. 30, 2024.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Spin-phonon dispersion in magnetic materials

Microscopic coupling between the electron spin and the lattice vibration is responsible for an array of exotic properties from morphic effects in simple non magnets to magnetodielectric coupling in multiferroic spinels and hematites. Traditionally, a single spin–phonon coupling constant is used to characterize how effectively the lattice can affect the spin, but it is hardly enough to capture novel electromagnetic behaviors to the full extent. Here, we introduce a concept of spin–phonon dispersion to project the spin moment change along the phonon crystal momentum direction, so the entire spin change can be mapped out. Different from the phonon dispersion, the spin–phonon dispersion has both positive and negative frequency branches even in the equilibrium ground state, which correspond to the spin enhancement and spin reduction, respectively. Our study of bcc Fe and hcp Co reveals that the spin force matrix, that is, the second-order spatial derivative of spin moment, is similar to the vibrational force matrix, but its diagonal elements are smaller than the off-diagonal ones. This leads to the distinctive spin–phonon dispersion. Furthermore, the concept of spin–phonon dispersion expands the traditional Elliott-Yafet theory in nonmagnetic materials to the entire Brillouin zone in magnetic materials, thus opening the door to excited states in systems such as CoF 2 and NiO, where a strong spin-lattice coupling is detected in the THz regime.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Influence of Markovianity and self-consistency on time-resolved spectral functions of driven quantum systems

We present a systematic comparison of the real-time Dyson expansion (RTDE) with established nonequilibrium Green's function (GF) approaches for simulating driven, interacting quantum systems. Focusing on density matrix dynamics, time-off-diagonal GFs, and time-resolved photoemission spectra, we benchmark RTDE against fully self-consistent Kadanoff-Baym equation (KBE) calculations, the generalized Kadanoff-Baym ansatz, and exact diagonalization for small systems using second-order many-body perturbation theory. Using a driven two-band Hubbard model, we show that mean-field single-particle density matrix trajectories provide a reliable baseline for RTDE across a broad range of interaction strengths and excited-carrier populations. Further, RTDE accurately captures correlation effects in the GFs, including long-lived oscillations and revivals that are strongly suppressed by the overdamping inherent to self-consistent KBE schemes. As a consequence, RTDE resolves rich nonequilibrium spectral structure in time-resolved photoemission, such as interaction- and population-dependent quasiparticle splittings and band gap renormalization, which are largely washed out in self-consistent approaches yet are present in exact solutions. Furthermore, our results demonstrate that RTDE bridges the gap between mean-field propagation and full two-time KBE simulations, retaining favorable linear scaling while capturing essential dynamical correlations relevant for ultrafast spectroscopy.

Electronic structure↗

Scalar Breit interaction for molecular calculations

Variational treatment of the Dirac–Coulomb–Gaunt or Dirac–Coulomb–Breit two-electron interaction at the Dirac–Hartree–Fock level is the starting point of high-accuracy four-component calculations of atomic and molecular systems. In this work, we introduce, for the first time, the scalar Hamiltonians derived from the Dirac–Coulomb–Gaunt and Dirac–Coulomb–Breit operators based on spin separation in the Pauli quaternion basis. While the widely used spin-free Dirac–Coulomb Hamiltonian includes only the direct Coulomb and exchange terms that resemble nonrelativistic two-electron interactions, the scalar Gaunt operator adds a scalar spin–spin term. The spin separation of the gauge operator gives rise to an additional scalar orbit-orbit interaction in the scalar Breit Hamiltonian. Benchmark calculations of Au n (n = 2–8) show that the scalar Dirac–Coulomb–Breit Hamiltonian can capture 99.99% of the total energy with only 10% of the computational cost when real-valued arithmetic is used, compared to the full Dirac–Coulomb–Breit Hamiltonian. In conclusion, the scalar relativistic formulation developed in this work lays the theoretical foundation for the development of high-accuracy, low-cost correlated variational relativistic many-body theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A matrix completion algorithm for efficient calculation of quantum and variational effects in chemical reactions

This work examines the viability of matrix completion methods as cost-effective alternatives to full nuclear Hessians for calculating quantum and variational effects in chemical reactions. The harmonic variety-based matrix completion (HVMC) algorithm, developed in a previous study (https://doi.org/10.1063/5.0018326), exploits the low-rank character of the polynomial expansion of potential energy to recover, using a small sample, vibrational frequencies (square roots of nuclear Hessian eigenvalues) constituting the reaction path. Furthermore, these frequencies are essential for calculating rate coefficients using variational transition state theory with multidimensional tunneling (VTST-MT). HVMC performance is examined for four SN2 reactions and five hydrogen transfer reactions, with each H-transfer reaction consisting of at least one vibrational mode strongly coupled to the reaction coordinate. HVMC is robust and captures zero-point energies, vibrational free energies, zero-curvature tunneling, and adiabatic ground state and free energy barriers as well as their positions on the reaction coordinate. For medium to large reactions involving H-transfer, with the exception of the most complex Ir catalysis system, less than 35% of total eigenvalue information is necessary for accurate recovery of key VTST-MT observables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Three-dimensional high-content imaging of unstained soft tissue with subcellular resolution using a laboratory-based X-ray microscope

With increasing interest in studying biological systems across spatial scales—from centimeters down to nanometers—histology continues to be the gold standard for tissue imaging at cellular resolution, providing an essential bridge between macroscopic and nanoscopic analysis. However, its inherently destructive and two-dimensional nature limits its ability to capture the full three-dimensional complexity of tissue architecture. Here, we show that phase-contrast X-ray microscopy can enable three-dimensional virtual histology with subcellular resolution. This technique provides direct quantification of electron density without restrictive assumptions, allowing for direct characterization of cellular nuclei in a standard laboratory setting. By combining high spatial resolution and soft tissue contrast, with automated segmentation of cell nuclei, we demonstrated virtual Hematoxylin and Eosin (H&E) staining using machine learning-based style transfer, yielding volumetric datasets compatible with existing histopathological analysis tools. Furthermore, by integrating electron density and the sensitivity to nanometric features of the dark field contrast channel, we achieve stain-free, high-content imaging capable of distinguishing nuclei and extracellular matrix.

3D virtual histology↗

Predicting Fluid Flow Regime, Permeability, and Diffusivity in Mudrocks from Multiscale Pore Characterisation

In geoenergy applications, mudrocks prevent fluids to leak from temporary (H 2 , CH 4 ) or permanent (CO 2 , radioactive waste) storage/disposal sites and serve as a source and reservoir for unconventional oil and gas. Understanding transport properties integrated with dominant fluid flow mechanisms in mudrocks is essential to better predict the performance of mudrocks within these applications. In this study, small-angle neutron scattering (SANS) experiments were conducted on 71 samples from 13 different sets of mudrocks across the globe to capture the pore structure of nearly the full pore size spectrum (2 nm–5 μm). We develop fractal models to predict transport properties (permeability and diffusivity) based on the SANS-derived pore size distributions. The results indicate that transport phenomena in mudrocks are intrinsically pore size-dependent. Depending on hydrostatic pore pressures, transition flow develops in micropores, slip flow in meso- and macropores, and continuum flow in larger macropores. Fluid flow regimes progress towards larger pore sizes during reservoir depletion or smaller pore sizes during fluid storage, so when pressure is decreased or increased, respectively. Capturing the heterogeneity of mudrocks by considering fractal dimension and tortuosity fractal dimension for defined pore size ranges, fractal models integrate apparent permeability with slip flow, Darcy permeability with continuum flow, and gas diffusivity with diffusion flow in the matrix. This new model of pore size-dependent transport and integrated transport properties using fractal models yields a systematic approach that can also inform multiscale multi-physics models to better understand fluid flow and transport phenomena in mudrocks on the reservoir and basin scale.

36 MATERIALS SCIENCE↗