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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 199 records · Page 11

Identifying Suitable Front Contacts for High‐Efficiency Cd(Se,Te) Solar Cells on Space‐Qualified Cover Glass

Deployment of photovoltaics in space requires devices that combine high-efficiency, low areal mass, and resilience to harsh environments. Historically, high-efficiency multijunction III–V materials have dominated space power systems; however, their high cost and limited manufacturing throughput motivate the exploration of scalable alternatives. While CdTe-based thin-film photovoltaics offer an attractive option, their performance on non-conventional substrates can suffer from front contact instability under higher-temperature processing. Here, the role of front contact chemistry in limiting cell performance is investigated using CdTe-based devices fabricated on 150 μm thick Ceria-doped space-qualified 0214 Corning glass. A matrix of four transparent conducting oxides (TCOs: CTO, AZO, ITO, IZO) combined with two n-type emitters (MZO, IGO) reveals chemical stability at the front interface—rather than absorber composition alone—governs recombination losses, voltage deficits, and device reproducibility. Chemically stable front contact combinations suppress elemental diffusion and interfacial degradation, resulting in significantly improved carrier lifetimes and junction quality. These insights are validated through record-certified Cd(Se,Te) cell efficiencies of 18.4% under AM1.5G and 16.2% under AM0 illumination on ultra-thin glass. Beyond CdTe, this work provides a general framework for the rational selection of TCO/emitter interfaces in superstrate thin-film photovoltaics, including emerging technologies like metal halide perovskites, while enabling high-efficiency, lightweight photovoltaics for space applications.

14 SOLAR ENERGY↗

N -Terminal Octylated Peptoid Hydrogels as 3D-Printable Cell Scaffolds and Proteolytically Robust Cargo Depots

Supramolecular hydrogels that mimic the extracellular matrix (ECM) represent promising materials for tissue engineering and drug delivery. However, conventional hydrogels formed via the self-assembly of natural or synthetic building blocks often face a trade-off between biological functionality and biochemical stability, limiting their utility in long-term or protease-rich environments. Peptoids, a class of peptide-inspired, sequence-defined polymers, offer a compelling alternative due to their exceptional proteolytic resistance and bioactivity. Despite this potential, the development of supramolecular peptoid hydrogels has been hindered by the absence of backbone hydrogen bond donors, which limits long-range ordering necessary for efficient hydrogel formation. This work describes a short peptoid functionalized at the N-terminus with an octyl chain that readily self-assembles into hydrogels. Hydrophobic interactions among pendant octyl groups promote directional peptoid packing into highly ordered nanosheets, which interconnect to form a porous hydrogel network. These hydrogels exhibit tunable viscoelasticity, shear-thinning, and self-healing properties, enabling their use as inks for extrusion-based 3D printing. They support NIH-3T3 fibroblast adhesion, spreading, and proliferation, maintaining greater than 95% cell viability over 4 days. Moreover, the hydrogels retain their macroscopic integrity under protease-rich conditions, enabling sustained cargo release and uniform cellular uptake. Together, this study demonstrates a class of supramolecular peptoid hydrogelators that integrate biocompatibility, 3D printability, and proteolytic stability, providing a versatile platform for ECMmimetic scaffolds in regenerative medicine and long-term therapeutic delivery.

cargo delivery↗

The impact and mitigation of broad-absorption-line quasars in Lyman α forest correlations

ABSTRACT Correlations in and with the flux transmission of the Lyman α (Ly α) forest in the spectra of high-redshift quasars are powerful cosmological tools, yet these measurements can be compromised if the intrinsic quasar continuum is significantly uncertain. One particularly problematic case is broad-absorption-line (BAL) quasars, which exhibit blueshifted absorption associated with many spectral features that are consistent with outflows of up to ∼0.1c. As these absorption features can both fall in the forest region and be difficult to distinguish from Ly α absorption, cosmological analyses eliminate the ∼12–16 per cent of quasars that exhibit BALs. In this paper, we explore an alternate approach that includes BALs in the Ly α autocorrelation function, with the exception of the expected locations of the BAL absorption troughs. This procedure returns over 95 per cent of the path-length that is lost by the exclusion of BALs, as well as increasing the density of sightlines. We show that including BAL quasars reduces the fractional uncertainty in the covariance matrix and correlation function by 12 per cent and does not significantly change the shape of the correlation function relative to analyses that exclude BAL quasars. We also evaluate different definitions of BALs, masking strategies, and potential differences in the quasar continuum in the forest region for BALs with different amounts of absorption.

79 ASTRONOMY AND ASTROPHYSICS↗

Matrix element corrections in the PYTHIA8 parton shower in the context of matched simulations at next-to-leading order

We discuss the role of matrix element corrections (MEC) to parton showers in the context of MC@NLO-type matchings for processes that feature unstable resonances, where MEC are liable to result in double-counting issues, and are thus generally not employed. By working with PYTHIA8 , we show that disabling all MEC is actually unnecessary in computations based on the narrow-width approximation, and we propose alternative MEC settings which, while still avoiding double counting, allow one to include hard-recoil effects in the simulations of resonance decays. We illustrate our findings by considering $t\overline{t}$ production at the LHC, and by comparing MadGraph5-aMC@NLO predictions with those of POWHEG-BOX and standalone PYTHIA8 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Enhancing ACPF Analysis: Integrating Newton-Raphson Method with Gradient Descent and Computational Graphs

This paper presents a new method for enhancing Alternating Current Power Flow (ACPF) analysis. The method integrates the Newton-Raphson (NR) method with Enhanced-Gradient Descent (GD) and computational graphs. The integration of renewable energy sources in power systems introduces variability and unpredictability, and this method addresses these challenges. It leverages the robustness of NR for accurate approximations and the flexibility of GD for handling variable conditions, all without requiring Jacobian matrix inversion. Furthermore, computational graphs provide a structured and visual framework that simplifies and systematizes the application of these methods. The goal of this fusion is to overcome the limitations of traditional ACPF methods and improve the resilience, adaptability, and efficiency of modern power grid analyses. We validate the effectiveness of our advanced algorithm through comprehensive testing on established IEEE benchmark systems. Furthermore, our findings demonstrate that our approach not only speeds up the convergence process but also ensures consistent performance across diverse system states, representing a significant advancement in power flow computation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Water Treatment: Are Membranes the Panacea?

Alongside the rising global water demand, continued stress on current water supplies has sparked interest in using nontraditional source waters for energy, agriculture, industry, and domestic needs. Membrane technologies have emerged as one of the most promising approaches to achieve water security, but implementation of membrane processes for increasingly complex waters remains a challenge. The technical feasibility of membrane processes replacing conventional treatment of alternative water supplies (e.g., wastewater, seawater, and produced water) is considered in the context of typical and emerging water quality goals. This review considers the effectiveness of current technologies (both conventional and membrane based), as well as the potential for recent advancements in membrane research to achieve these water quality goals. We envision the future of water treatment to integrate advanced membranes (e.g., mixed-matrix membranes, block copolymers) into smart treatment trains that achieve several goals, including fit-for-purpose water generation, resource recovery, and energy conservation.

catalysis (heterogeneous)↗

Flax–Reinforced Vitrimer Epoxy Composites Produced via RTM

Composite laminates were produced by RTM using similar glass and flax fabrics and both vitrimer epoxy and aerospace-grade epoxy, both formulated for liquid molding. Tensile and flexural properties were measured and compared, revealing that the vitrimer composites exhibited equivalent performance in flexural strength and tensile modulus, but slightly lower performance in tensile strength relative to reference epoxy composites. In general, glass–fiber composites outperformed flax–fiber composites in tension. However, both glass and flax–fiber composites yielded roughly equivalent flexural strength and tensile modulus-to-weight ratios. Flax fabrics were recovered from composites by matrix dissolution, and a second-life laminate showed full retention of the mechanical properties relative to those produced from fresh flax. Finally, a demonstration of re-forming was undertaken, showing that simple press-forming can be used to modify the composite shape. However, re-forming to a flat configuration resulted in local fiber damage and a decrease in mechanical properties. An alternative forming method was demonstrated that resulted in less fiber damage, indicating that further refinements might lead to a viable forming and re-forming process.

Martinez, Patricio (ORCID:0000000225884389)↗

Dielectric and Structural Properties of the Hybrid Material Polyvinylidene Fluoride-Bacterial Nanocellulose-Based Composite

In the search for environmentally friendly materials with a wide range of properties, polymer composites have emerged as a promising alternative due to their multifunctional properties. This study focuses on the synthesis of composite materials consisting of four components: bacterial nanocellulose (BNC) modified with magnetic Fe 3 O 4 , and a mixture of BaTiO 3 (BT) and polyvinylidene fluoride (PVDF). The BT powder was mechanically activated prior to mixing with PVDF. The influence of BT mechanical activation and BNC with magnetic particles on the PVDF matrix was investigated. The obtained composite films’ structural characteristics, morphology, and dielectric properties are presented. This research provides insights into the relationship between mechanical activation of the filler and structural and dielectric properties in the PVDF/BT/BNC/Fe 3 O 4 system, creating the way for the development of materials with a wide range of diverse properties that support the concept of green technologies.

36 MATERIALS SCIENCE↗

Alternative Hanford ETF Grout Evaluation Report

The Hanford Effluent Treatment Facility (ETF) ammonia tolerant grout waste form was developed by the Vitreous State Laboratory (VSL) to stabilize ammonium and thereby prevent emission of ammonia vapor during processing of a final cementitious waste form. This ETF evaporator bottom waste is a concentrated sodium sulfate aqueous solution that also contains dissolved ammonium. The VSL waste form was produced in a two-step process in which struvite (MgNH 4 PO 4.6 H 2 O) is precipitated and then the resulting slurry is solidified in a cementitious matrix. SRNL researchers were tasked to evaluate the effect of compositional and struvite stability in simulated ETF evaporator brine. In 2022 to 2023, samples prepared by SRNL experienced significant expansion (up to 20 volume %) which was not observed by VSL.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Fast Gaussian Process Estimation for Large-Scale In Situ Inference using Convolutional Neural Networks

Exascale computing will bring with it significant I/O limitations. One foreseeable consequence of such restrictions is that the user can save only a small fraction of complex simulation data to disk for subsequent analysis. An alternative is to fit statistical models to data in situ, that is, inside the simulation as it runs. This option requires extremely fast statistical estimation to avoid slowing down the simulation. Gaussian processes (GPs) have state-of-the-art predictive performance for modeling spatial data. However, standard estimation methods for GPs scale quite poorly to large data sets as parameter estimation requires inverting a covariance matrix to the size of the data set. In the presented work, we use a convolutional neural network (CNN) to predict the GP parameters for a spatial data set, from a simulation or otherwise, rather than optimize the parameters directly. Here, our presented case study models spatial data from E3SM, the Department of Energy’s Exascale climate model. The CNN is trained on synthetic data simulated from GP models with known parameters and then applied to data from the climate simulation. In the presented examples, the neural network scheme produces parameter estimates that compare well with standard methods such as maximum likelihood estimation in predictive performance but is obtained four orders of magnitude faster.

big data↗

Data Associated with "Identifying Suitable Front Contacts for High-Efficiency Cd(Se,Te) Solar Cells on Space-Qualified Cover Glass"

This is data associated with the publication " Identifying Suitable Front Contacts for High-Efficiency Cd(Se,Te) Solar Cells on Space-Qualified Cover Glass " by Aesha P. Patel, Ryan Muzzio, Matthew R. Young, Robert Morrissey, Suresh Chaulagain, B. Edward Sartor, Prabodika N. Kaluarachchi, Christian Velez, Joshua A. Brown, Joel N. Duenow, Stephen Glynn, Michael J. Heben, Zhaoning Song, Nikolas J. Podraza, Adam B. Phillips, Randy J. Ellingson, Matthew O. Reese. All data associated with each figure in the manuscript and supplementary should be available in this dataset. A readme file is also included to provide some guidance. Abstract: Deployment of photovoltaics in space requires devices that combine high-efficiency, low areal mass, and resilience to harsh environments. Historically, high-efficiency multijunction III–V materials have dominated space power systems; however, their high cost and limited manufacturing throughput motivate the exploration of scalable alternatives. While CdTe-based thin-film photovoltaics offer an attractive option, their performance on non-conventional substrates can suffer from front-contact instability under higher-temperature processing. Here, the role of front-contact chemistry in limiting cell performance is investigated using CdTe-based devices fabricated on 150 μm thick Ceria-doped space-qualified 0214 Corning glass. A matrix of four transparent conducting oxides (TCOs: CTO, AZO, ITO, IZO) combined with two n-type emitters (MZO, IGO) reveals chemical stability at the front interface—rather than absorber composition alone—governs recombination losses, voltage deficits, and device reproducibility. Chemically stable front-contact combinations suppress elemental diffusion and interfacial degradation, resulting in significantly improved carrier lifetimes and junction quality. These insights are validated through record-certified Cd(Se,Te) cell efficiencies of 18.4% under AM1.5G and 16.2% under AM0 illumination on ultra-thin glass. Beyond CdTe, this work provides a general framework for the rational selection of TCO/emitter interfaces in superstrate thin-film photovoltaics, including emerging technologies like metal halide perovskites, while enabling high-efficiency, lightweight photovoltaics for space applications.

14 SOLAR ENERGY↗

Spinon continuum in the Heisenberg quantum chain compound Sr 2 ⁢V 3 ⁢O 9

Magnetic excitations in the spin chain candidate Sr 2 ⁢V 3 ⁢O 9 have been investigated by inelastic neutron scattering on a single crystal sample. A spinon continuum with a bandwidth of ~22 meV is observed along the chain formed by alternating magnetic V 4+ and nonmagnetic V 5+ ions, which reveals the importance of the orbital degree of freedom in determining the chain axis as identified by prior electronic structure calculations. Incipient magnetic Bragg peaks due to weak ferromagnetic interchain couplings emerge when approaching the magnetic transition at T N ~ 5.3 K, while the excitations remain gapless within the instrumental resolution. Comparisons to the Bethe ansatz, density matrix renormalization group calculations, and effective field theories confirm Sr 2 ⁢V 3 ⁢O 9 as a host of weakly coupled S = 1/2 chains dominated by antiferromagnetic intrachain interactions of ~7.1(1) meV.

1-dimensional spin chains↗

Designing Ti-6Al-4V microstructure for strain delocalization using neural networks

Abstract The deformation behavior of Ti-6Al-4V titanium alloy is significantly influenced by slip localized within crystallographic slip bands. Experimental observations reveal that intense slip bands in Ti-6Al-4V form at strains well below the macroscopic yield strain and may serially propagate across grain boundaries, resulting in long-range localization that percolates through the microstructure. These connected, localized slip bands serve as potential sites for crack initiation. Although slip localization in Ti-6Al-4V is known to be influenced by various factors, an investigation of optimal microstructures that limit localization remains lacking. In this work, we develop a novel strategy that integrates an explicit slip band crystal plasticity technique, graph networks, and neural network models to identify Ti-6Al-4V microstructures that reduce the propensity for strain localization. Simulations are conducted on a dataset of 3D polycrystals, each represented as a graph to account for grain neighborhood and connectivity. The results are then used to train neural network surrogate models that accurately predict localization-based properties of a polycrystal, given its microstructure. These properties include the ratio of slip accumulated in the band to that in the matrix, fraction of total applied strain accommodated by slip bands, and spatial connectivity of slip bands throughout the microstructure. The initial dataset is enriched by synthetic data generated by the surrogate models, and a grid search optimization is subsequently performed to find optimal microstructures. Describing a 3D polycrystal with only a few features and a combination of graph and neural network models offer robustness compared to the alternative approaches without compromising accuracy. We show that while each material property is optimized through a unique microstructure solution, elongated grain shape emerges as a recurring feature among all optimal microstructures. This finding suggests that designing microstructures with elongated grains could potentially mitigate strain localization without compromising strength.

Ahmadikia, Behnam↗

Low-energy cross-section measurement of the B 10 ( α , n ) N 13 reaction and its impact on neutron production in first-generation stars

Nucleosynthesis in the first generation of massive stars offers a unique setting to explore the creation of the first heavier nuclei in an environment free of impurities from earlier stellar generations. In later generations of massive stars, hydrogen burning occurs predominantly through the CNO cycles, but without the carbon, nitrogen, and oxygen to catalyze the reaction sequence, first stars would have to rely on the inefficient pp chains for their energy production. Observations of second and third generation stars show pronounced abundances of carbon and oxygen isotopes, which suggests a rapid conversion of the primordial abundances to heavier elements. While the triple-alpha-process primarily facilitates this conversion, there are alternative reaction sequences, such as 2 H(α,γ) 6 Li(α,γ) 10 B(α,n) 13 N, that may play a significant role. To study such alternate reaction pathways for production of carbon and heavier nuclei, a number of new measurements are needed. In this work, new measurements are reported for the 10 B(α,n) 13 N reaction, extending the cross section down to 575 keV incident α-particle energy. The measurements were made using a state-of-the-art deuterated liquid scintillator and a spectrum unfolding technique. An R-matrix analysis was performed in order to facilitate a comparison of the underlying nuclear structure with the reaction measurements. An unexpected upturn is observed in the low-energy S factor that indicates the presence of a new low-energy resonance. Finally, a revised reaction rate is determined that takes into account the present data as well as other previous measurements from the literature that were previously neglected.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Low-rank Tensor Completion for PMU Data Recovery

This paper proposes a tensor completion method for the recovery of missing phasor measurement unit (PMU) measurements. Tensor completion as the general case of matrix completion has attracted increasing attention in recent years. The imputation accuracy for the existing matrix completion methods may be significantly reduced when there are consecutive data losses across multiple data channels. To tackle this issue, we explore the multi-way characteristics of PMU measurements by using a tensor model. We leverage the low-rank property of the PMU measurements and formulate the missing PMU data recovery problem as a low-rank tensor completion problem. An efficient algorithm based on alternating direction method of multipliers (ADMM) is developed to solve the tensor completion problem. The experiments using the real PMU dataset show that the proposed method exhibits better imputation accuracy compared with the conventional data recovery methods.

Ghasemkhani, Amir↗

Reactor Performance and Safety Characteristics of Beryllium-Based Composite Moderators as Replacements for Graphite in mHTGRs

Here, this study evaluates beryllium-based two-phase composite moderators as an alternative to graphite in an evaluation of reactor performance and safety characteristics. Historically, modular high-temperature gas-cooled reactors (mHTGRs) use graphite as a moderator because of its high moderating ratio and reasonable thermal properties; however, graphite has unfavorable properties under irradiation, which can require component replacement and a significant radioactive waste burden. In this assessment, we explore advanced moderators comprised of magnesium oxide (MgO) as the host matrix and beryllium metal and/or beryllium oxide (Be and/or BeO) as the entrained moderating phase. For the reactor performance and thermal-hydraulic safety analysis, the core design model of the General Atomics mHTGR-350 was used to demonstrate the feasibility of a “drop-in” replacement of graphite using the beryllium-based moderators. We employed the neutronics code Serpent to analyze the moderating behavior of the composite moderators with comparisons drawn to graphite. We performed a scoping analysis of accidents for mHTGRs using RELAP to show that these moderators do not present impediments to safety and are expected to stay within temperature limits. Measured thermophysical properties of the composite moderators are used in the thermal-hydraulic assessments. Our analysis reveals that the two-phase composite MgO-matrix beryllium-based moderators are a suitable replacement for graphite.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data

We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, used in 2024 analyses. We find only a few percent differences between the mock sample covariance matrix and our results, which can be expected given the approximate nature of the mocks, although we do identify discrepancies between the shot-noise properties of the DESI fiber assignment algorithm and the faster approximation (emulator) used in the mocks. Importantly, we find a close agreement (≤ 8% relative differences) in the projected errorbars for distance scale parameters for the baryon acoustic oscillation measurements. This confirms our method as an attractive alternative to simulation-based covariance matrices, especially for non-standard models or galaxy sample selections, making it particularly relevant to the broad current and future analyses of DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗

Enhancing photoionization rate calculations in low-temperature plasmas using spectral methods

Photoionization plays a central role in the development of streamer discharges and other non-equilibrium plasma phenomena. It creates seed electrons, which are essential for positive streamer propagation, allowing the ionization front to move forward. Because of this, accurate modeling of photoionization is very important for predicting streamer behavior and plasma evolution. The photoionization process in air (N 2 – O 2 mixture) is often described by the Zheleznyak model (1982). This model is usually solved through Helmholtz-type equations that approximate the Zheleznyak photoionization model (Zheleznyak et al. 1982) as Partial Differential Equations (PDEs). Conventional numerical methods, such as the Finite Difference Method (FDM) or Finite Volume Method (FVM), are widely used to solve these equations. Although they are prevalent, the computational cost of these methods due to their need for matrix operations and iterative solver is demanding. To address this challenge, this work develops a spectral solver based on the Fast Fourier Transform (FFT) combined with Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) to calculate the photoionization rate efficiently in an axisymmetric cylindrical domain. This method naturally satisfies the boundary conditions used in the model and converts the PDE into algebraic ones in spectral space. Thus, avoids the need for iterative matrix solvers. When compared with FDM results, it is demonstrated that the new solver not only maintains accuracy, but also reduces the computational cost, showing a performance increase of approximately 100 compared to FDM over a wide range of problem sizes. The method is parallelized using Message Passing Interface (MPI) and has been integrated into a fluid plasma model for streamer simulation. Here, this FFT-based approach provides a fast and reliable alternative for calculating photoionization in fluid models, helping large-scale plasma simulations run faster and efficiently, and allows higher-resolution simulation without extra computational cost.

Axisymmetric system↗