Results for “Monte Carlo simulation” — Page 31

NASA NTRS2026

A Modular Conjugate Heat Transfer Optimization Framework for Thermal Management of Electric Aircraft

Conjugate heat transfer (CHT) analysis and optimization is a powerful method for improving thermal management, as it simultaneously resolves the temperature distribution in both fluid and solid domains. This paper presents a modular, discrete adjoint-based CHT optimization capability integrated within the OpenMDAO/MPhys framework. A unique feature of the proposed framework is its flexibility to extend to multidisciplinary optimization, including aero-structural-thermal applications. The fluid domain is modeled using a finite-volume Computational Fluid Dynamics (CFD) solver, and the solid domain with a conduction heat transfer solver. A mixed Neumann-Dirichlet boundary condition is developed to enable full submersion of the solid geometry within the fluid domain, while ensuring consistent temperature and heat flux coupling at the CHT interface. Gradient-based optimization is performed; the gradients are efficiently computed using the discrete adjoint solvers implemented in DAFoam. To demonstrate the method, this paper considers two cases related to electric aircraft thermal management: a U-bend heat exchanger and an actively cooled battery pack. The U-bend case aims to minimize pressure loss while maximizing heat flux by changing the pipe geometry. The optimized design reduces pressure loss by 52.7% and increases total heat flux by 2.3%. In the battery pack case, a 3-by-3 cell configuration is cooled by ambient airflow, with constant heat generation prescribed in the cells. The battery casing shape serves as the design variable, and the objective function is a weighted sum of pressure loss and pack weight, subject to a maximum temperature constraint. The optimized design achieves a 44.6% reduction in pressure loss and a 1.5% reduction in weight, while satisfying the thermal constraint. To ensure the reliability of the optimized designs, this study validates coarse-mesh, steady-state predictions against fine-mesh unsteady simulations, demonstrating consistency within acceptable errors. This work demonstrates the potential of the developed framework to enable rapid, high-fidelity design of thermal management systems for electric aircraft.

heat transfer↗

DOE OSTI2026

Reduction of baseplate distortion during directed energy deposition using compliant features

Distortion in additive manufacturing (AM) remains a barrier to its adoption in precision industries. Baseplate warpage is one such issue which compromises the feasibility of post-process precision machining. The restriction to thermal contraction of the deposited part, imposed by the baseplate, generates bending moments, that in turn causes warpage. A novel distortion mitigation strategy using baseplates with integrated compliant features, which enables thermal contraction of the build is presented. Six unique design concepts are evaluated, including a solid reference, using two deposition geometries. A laser, hot-wire, directed energy deposition (DED) process is used to deposit a symmetric cylindrical part (C-part) and a T-shaped asymmetric part (T-part). Flatness deviation of baseplates is measured using structured light 3D scanning. Measurements reveal a reduction in net flatness deviation of 58.8% for the C-part and 40.9% for the T-part, compared to the solid reference. While most designs yielded reductions exceeding 30% and 20% for the C- and T-parts, respectively, one configuration resulted in increased deviation. Finite element (FE) simulations are performed to elucidate the underlying mechanisms affecting distortion of compliant baseplates during DED. Despite variations between predictions and measurements, agreement in the general trend is observed. It also revealed that initial flatness errors in baseplates significantly affect its deviation during deposition. Predictions indicate that compliant features significantly affect the thermal distribution as well as the evolution of flatness deviation in the baseplate during deposition. Notably, one design exhibited a reduction in distortion during cooling, following its initial increase during deposition. FE predictions show a maximum reduction of 60.9% and 38.8% in net flatness deviation for the C- and T-parts, respectively. The performance of compliant baseplates is found to be governed by both its the thermal and mechanical characteristics, which are crucial factors to be considered during design.

Mathews, Ritin [ORNL] (ORCID:0000000301440828)↗

DOE OSTI2026

SAM Code Enhancements for Fission Product Tracking of Noble Gases and Metals in MSRs

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

Mui, Travis (ORCID:0000000303736470)↗

DOE OSTI2026

Systematic Construction of Time-Dependent Hamiltonians for Microwave-Driven Josephson Circuits

Time-dependent electromagnetic drives are fundamental for controlling complex quantum systems, including superconducting Josephson circuits. In these devices, accurate time-dependent Hamiltonian models are imperative for predicting their dynamics and designing high-fidelity quantum operations. Existing numerical methods, such as black-box quantization (BBQ) and energy-participation ratio (EPR), excel at modeling the static Hamiltonians of Josephson circuits. However, these techniques do not fully capture the behavior of driven circuits stimulated by external microwave drives, nor do they include a generalized approach to account for the inevitable noise and dissipation that enter through microwave ports. Here, we introduce numerical techniques that leverage classical microwave simulations, efficiently executable in finite-element solvers, to obtain the time-dependent Hamiltonian of microwave-driven superconducting circuits with arbitrary geometries under charge, flux, or mixed electromagnetic modulation. Importantly, our techniques do not rely on a lumped-element description of the superconducting circuit, in contrast to previous approaches to tackling this problem. We demonstrate the versatility of our approach by characterizing the driven properties of realistic circuit devices in complex electromagnetic environments, including coherent dynamics due to charge and flux modulation, as well as drive-induced relaxation and dephasing. Our techniques offer a powerful toolbox for optimizing circuit designs and advancing practical applications in superconducting quantum computing.

Lu, Yao [Yale U.; Yale U. (main); Fermilab] (ORCID↗

NASA NTRSDate not supplied

Battery Evaluation Profiles for X-57 and Future Urban Electric Aircraft

Battery energy density is one of the most critical design parameters for sizing all-electric aircraft, however it’s easily overestimated. Establishing the effective, usable energy density is confused by varying degrees of margin needed to account for structural and thermal management between different cell chemistry and pack designs. Therefore, a better methodology is needed to fairly compare emerging battery technologies for electric aircraft. Currently, there is a loss of critical information when vehicle trade studies are performed using “nominal” published cell-level performance metrics. Aircraft power demands rarely match these nominal power profiles, and aircraft designers lack the ability to accurately simulate the battery performance and temperature off-nominally unless the battery chemistry is well established. Conversely, battery suppliers have no generalized reference cases to publish more realistic performance metrics. This can lead to poor assumptions, such as aircraft studies assuming a fixed discharge efficiency of a battery, when in reality the usable energy in a pack is dependent on the power and thermal profile. Information needed to properly assess weight penalties for thermal management is also typically poorly characterized when assessing candidate batteries. This paper serves to better inform battery development, and similarly, provide aircraft designers with more realistic assumptions for applying knockdown margins in their designs. Detailed power and thermal performance estimates are provided, which provide a starting point for sizing power and thermal budgets using experimentally derived battery models. Results show that the X-57 battery-to-shaft efficiency is 77.3% for a particular optimized mission. Considering a 25% reserve on the battery capacity, this means that only roughly half of the original 55.3kWh ‘nominal’ pack energy can be converted to useful work during a mission. Further estimates on a clean-sheet VTOL optimization show an average 82.7% battery-to-shaft efficiency, using 98% peak efficiency inverters and 97.4% peak efficiency motors. Although higher battery efficiencies are possible, the resulting weight penalty negates improvement in vehicle performance. These trade-offs and resulting power profiles are provided as a starting point to better assess future battery designs.

Battery↗

NASA NTRS2022

Optical properties of morphologically complex black carbon aerosols: Effects of coatings

Optical properties are computed for fractal-like aggregate black carbon (BC) aerosols coated with different substances. Two models are used for these aerosols: (i) the coated aggregate model (model I), where coating is added to the voids and surroundings of BC fractal-like aggregates; and (ii) the closed-cell aggregate model (model II), where coating is added concentrically to each monomer of BC fractal-like aggregates. Our results favor choosing the coated aggregate model (model I) to simulate scattering and absorption by coated BC aerosols because this model is morphologically more realistic, and because this model yields mass absorption cross section (MAC) and backscattering linear depolarization ratio (LDR) values that are consistent with field measurements. Moreover the corresponding computed degree of linear polarization (DoLP) and LDR values are very sensitive to changes in the coating volume fraction (fvol) and the coating refractive index (m). With the same absorbing BC core, the MAC value increases steadily with increasing fvol and m values. For example, using a density of 1.8 g/cm 3 and BC refractive index 1.95 + i0.79, the calculated MAC values for uncoated BC aggregates range from 6.2 to 6.8 m 2 /g at 0.55 µm. When coating material is applied to the BC aggregates, the calculated MAC values for model I particles increase to between 9.8 and 13.2 m 2 /g (depending on m) when fvol = 87.5%. The backscattering LDR values also tend to increase with the increasing m values for the shapes and sizes considered in our study. For model I particles, the backscattering LDR values span a wide range of 4.2–27.8% at a wavelength of 0.35 µm at fvol = 87.5% when m increases from 1.33 to 1.55. Our results are relevant to analyses of polarimetric and lidar observations of smoke particles, especially when these particles undergo hygroscopic growth.

Black carbon aerosols↗

DOE OSTI2026

Direct observation of diamond formation in a shock-compressed high explosive

Understanding the formation timescale and structure of carbonaceous reaction products is critical for modeling the high-pressure equation-of-state of organic materials. We use the National Ignition Facility to shock-compress polycrystalline TATB (C 6 H 6 N 6 O 6 ) samples to ~70–130 GPa and ~4000–5500 K, employing in situ nanosecond X-ray diffraction to probe reaction products and velocimetry to measure transmitted compression wave profiles. Our diffraction data is consistent with the formation of diamond over timescales less than ~60 ns. This represents carbon condensation from a molecular explosive on timescales three times faster than previously reported and the earliest observation of diamond produced from reacting TATB. Reactive flow simulations with explicit chemistry reproduce the observed temporal structure within wave profiles to inform the distribution of P-T states. These findings provide direct evidence of ultrafast diamond formation in a reactive system at extreme conditions and provide new constraints for models of shock and detonation chemistry.

Clarke, Samantha M. [Lawrence Livermore National L↗

DOE OSTI2026

Adsorption, charge transfer and a coverage-driven transition of alkali metals on rutile TiO 2 (110)

The interaction of alkali metals with metal oxide surfaces is central to tuning surface reactivity in heterogeneous catalysis and photocatalysis. Here we present a comprehensive DFT+U study of the adsorption of alkali metals (Li, Na, K, Rb, Cs) on the (110) surface of rutile TiO 2 . At low coverage (θ = 1/8), all alkali metals bind preferentially to bridging oxygen sites with adsorption energies in the range −4.06 to −3.33 eV, transferring nearly one full electron (0.92–0.99 |e|) to the substrate and inducing Ti 4+ → Ti 3+ reduction. The excess charge localizes preferentially at subsurface Ti sites in the form of small polarons. Diffusion barriers indicate facile motion along bridging-oxygen rows, whereas inter-row hopping is strongly hindered. Coverage effects were examined systematically for potassium: adsorption energy and charge transfer per K atom decrease monotonically with increasing θ. Strikingly, a sharp energy discontinuity occurs between θ = 4/8 and θ = 5/8 (ΔE ≈ 1 eV per atom), which we identify as a coverage-driven structural transition arising from steric packing constraints and enhanced K–K electrostatic repulsion once every (1×1) surface cell is occupied. This structural transition perfectly correlates with a dramatic drop in the work function down to an ultra-low minimum of 0.84 eV at θ=5/8, followed by a metallization- driven recovery at higher coverages. Ab initio molecular dynamics simulations confirm zigzag K arrangements at moderate coverage (θ = 1/3), while at high coverage (θ = 2/3) short-range K–K correlations emerge without long-range order. These results provide atomistic insight into the structure–activity relationships underlying alkali promotion effects on oxide-supported catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Structure of Self-Generated Magnetic Fields in Laser-Solid Interaction from Proton Tomography

Self-generated magnetic fields in laser-solid interactions are experimentally characterized to reveal the 3D location and local field strength, rather than path-integrated quantities, using multi-view proton radiography and tomographic inversion. We infer magnetic fields that extend several millimeters off the target into the hot, rarefied corona, sufficient to strongly magnetize the plasma (Ω e τ e ≫ 1). The data are compared to MHD simulations incorporating recent improvements in modeling magnetic field generation and transport; the volume-averaged coronal field strength and magnetic flux agree to within 25% using a model with magnetic re-localization of transport, although the near-target morphology is not reproduced. This work demonstrates tomographic proton radiography as a valuable tool for investigating magnetic fields in laser-produced plasmas.

High-energy-density plasmas↗

NASA NTRSDate not supplied

Performance of a Regenerative Fuel Cell System for the Lunar Surface

Regenerative fuel cells (RFCs) are an attractive energy storage solution for lunar missions as a technology capable of providing a higher specific energy (i.e., W∙h/kg) than state-of-the-art packaged Li-ion battery systems. An RFC consists of the (1 & 2) electrochemical stacks (chemical to electrical energy conversion to supply electricity to an external load, i.e. the fuel cell reaction, and electrical to chemical energy conversion of supplied electrical power to dissociate water into hydrogen and oxygen gases, i.e. water electrolysis), (3) fluidic conditioning, (4) reactant storage, (5) avionics, (6) power management and distribution (PMAD), and (7) thermal management. NASA’s Glenn Research Center has designed, assembled, and tested a breadboard RFC sys-tem capable of operating autonomously for multiple simulated lunar day/night cycles in a laboratory environment. The system is comprised of a non-flow through proton exchange membrane (PEM) fuel cell stack and a liquid-anode feed PEM electrolyzer (EZ) stack designed to electrochemically compress the reactants at balanced pressures up to 12.4 MPa (1800 psia). The fluidic conditioning, avionics, PMAD, and thermal management sub-systems are largely comprised of commercial-off-the-shelf components for this system-level development effort. The hardware is controlled by a CubeSat space processor running an operational program based on core flight architecture that can control the RFC hardware autonomously through a state machine with fault monitoring. The testing results highlighted here were completed with the system in an open-loop configuration such that reactants generated through water electrolysis were vented while gas cylinders supplied fuel cell operation. The breadboard operated autonomously, but there were five unplanned transitions to a safe state that required a manual restart after reviewing the data, determining a root cause, and implementing a solution. Four of the transitions were caused by the thermal management subsystem and the fifth was caused by a water management control issue in the EZ sub-system. The RFC system operated for over 550 hours with the final cycle being slightly abbreviated due to reasons unrelated to system performance.

Kerrigan Cain↗

NASA NTRSDate not supplied

Performance of a Regenerative Fuel Cell System for the Lunar Surface

Regenerative fuel cells (RFCs) are an attractive energy storage solution for lunar missions as a technology capable of providing a higher specific energy (i.e., W∙h/kg) than state-of-the-art packaged Li-ion battery systems. An RFC consists of the (1 & 2) electrochemical stacks (chemical to electrical energy conversion to supply electricity to an external load, i.e. the fuel cell reaction, and electrical to chemical energy conversion of supplied electrical power to dissociate water into hydrogen and oxygen gases, i.e. water electrolysis), (3) fluidic conditioning, (4) reactant storage, (5) avionics, (6) power management and distribution (PMAD), and (7) thermal management. NASA’s Glenn Research Center has designed, assembled, and tested a breadboard RFC sys-tem capable of operating autonomously for multiple simulated lunar day/night cycles in a laboratory environment. The system is comprised of a non-flow through proton exchange membrane (PEM) fuel cell stack and a liquid-anode feed PEM electrolyzer (EZ) stack designed to electrochemically compress the reactants at balanced pressures up to 12.4 MPa (1800 psia). The fluidic conditioning, avionics, PMAD, and thermal management sub-systems are largely comprised of commercial-off-the-shelf components for this system-level development effort. The hardware is controlled by a CubeSat space processor running an operational program based on core flight architecture that can control the RFC hardware autonomously through a state machine with fault monitoring. The testing results highlighted here were completed with the system in an open-loop configuration such that reactants generated through water electrolysis were vented while gas cylinders supplied fuel cell operation. The breadboard operated autonomously, but there were five unplanned transitions to a safe state that required a manual restart after reviewing the data, determining a root cause, and implementing a solution. Four of the transitions were caused by the thermal management subsystem and the fifth was caused by a water management control issue in the EZ sub-system. The RFC system operated for over 550 hours with the final cycle being slightly abbreviated due to reasons unrelated to system performance.

Kerrigan Cain↗

DOE OSTI2024

Cosmic neutrino decoupling and its observable imprints: insights from entropic-dual transport

Abstract Very different processes characterize the decoupling of neutrinos to form the cosmic neutrino background (CνB) and the much later decoupling of photons from thermal equilibrium to form the cosmic microwave background (CMB). The CνB emerges from the fuzzy, energy-dependent neutrinosphere and encodes the physics operating in the early universe in the temperature rangeT∼ 10 MeV toT∼ 10 keV. This is the epoch where beyond Standard Model (BSM) physics, especially in the neutrino sector, may be influential in setting the light element abundances, the necessarily distorted fossil neutrino energy spectra, and other light particle energy density contributions. Here we use techniques honed in extensive CMB studies to analyze the CνB as calculated in detailed neutrino energy transport and nuclear reaction simulations of the protracted weak decoupling and primordial nucleosynthesis epochs. Our moment method, relative entropy, and differential visibility approach can leverage future high precision CMB and light element primordial abundance measurements to provide new insights into the CνB and any BSM physics it encodes. We demonstrate that the evolution of the energy spectrum of the CνB throughout the weak decoupling epoch is accurately captured in the Standard Model by only three parameters per species, a non-trivial conclusion given the deviation from thermal equilibrium and the impact of the decrease of electron-positron pairs. Furthermore, we can interpret each of the three parameters as physical characteristics of a non-equilibrium system. Though the treatment presented here makes some simplifying assumptions including ignoring neutrino flavor oscillations, the success of our compact description within the Standard Model motivates its use also in BSM scenarios. We further demonstrate how observations of primordial light element abundances can be used to place constraints on the CνB energy spectrum, deriving response functions that can be applied for general deviations from a thermal spectrum. Combined with the description of those deviations that we develop here, our methods provide a convenient and powerful framework to constrain the impact of BSM physics on the CνB.

Astronomy & Astrophysics↗

DOE OSTI2024

Alignments in the orientation of radio jets from AGN and their host galaxies

It is well established that active galactic nuclei (AGNs) play an important role in the evolution of galaxies. These AGNs can be linked to the accretion processes onto massive black holes and past merger events in their host galaxies, which may lead to different alignments of the jets with respect to the host galaxies. This paper presents a study of the position angle (PA) differences between radio and optical images of radio-AGNs based on the second data release (DR2) of the Low Frequency Array (LOFAR) Two-Meter Sky Survey (LoTSS), theKarl G. JanskyVery Large Array Faint Images of the Radio Sky at Twenty-Centimeters Survey (FIRST), the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, and the Sloan Digital Sky Survey (SDSS). We assessed PA measurement biases in the data and classified the radio-AGNs based on the radio luminosity and infrared colour from the Wide-field Infrared Survey Explorer (WISE). This resulted in the largest sample of radio AGNs with reliable radio and optical PA measurements published to date, with a total of 3682 AGNs. The PA difference (dPA) distributions for the radio-AGN sample show a prominent minor-axis alignment tendency. Based on some simple assumptions, we simulated the projection effect to estimate the intrinsic jet-galaxy alignment. The observed dPA distribution can be well described by a two-component jet-alignment model in which one component is more aligned with the minor axis of the host galaxy than the other. The fitting results indicate that the jet alignment is dependent on radio luminosity and the shape of the host galaxies, with the jets being more likely to be aligned with the minor axis of the galaxy for lower radio luminosity and for optically more elongated radio-AGNs. The minor-axis alignment of the entire sample may suggest a coherent accretion model present in most AGN host galaxies, while a considerable number of luminous radio-AGNs with massive host galaxies might have undergone accretion – according to the chaotic model – or past merger events.

Astronomy & Astrophysics↗

DOE OSTI2026

The Role of Nuclear Data Sensitivities in Prompt α-Eigenvalue Predictions of Delayed Critical Benchmarks

Alpha (α) eigenvalues, which describe the logarithmic time derivative of the neutron population in a multiplying system, are integral to time-dependent behavior and diagnostic applications. However, uncertainties in the evaluated nuclear data can significantly impact the accuracy of transport simulations for such quantities. This work explores the use of machine learning models to predict two key outputs, α-eigenvalues and keff bias, using input features derived from α-eigenvalue sensitivities to nuclear data. The criticality safety benchmark models used in this study come from the International Handbook of Evaluated Criticality Safety Benchmark Experiments. Three models, random forest, XGBoost, and NGBoost, are trained on both energy-resolved and energy-summed α sensitivities. For the α-eigenvalue bias prediction, NGBoost achieved the highest R 2 (0.9476) using energy-resolved features, while XGBoost performed best using summed sensitivities. In contrast, when predicting the keff bias, all the models showed moderate predictive capability (best R 2 ≈ 0.72), as the mapping from the static α-sensitivities to the static keff bias was less direct. SHAP (SHapley Additive exPlanations) analysis was used to interpret the model predictions. Across both prediction tasks, the features associated with neutron capture [H-1 (n, γ)], uranium scattering reactions (such as 235 U elastic/inelastic), and actinide capture/fission reactions (such as 239 Pu and 234 U) were consistently identified as the most impactful. This highlights the key role of specific nuclear reactions and energy ranges in shaping both time-dependent and steady-state criticality behavior. These results demonstrated that α-sensitivities, despite being computed for time-dependent metrics, can provide valuable insights for predicting both α-eigenvalues and the keff bias. Moreover, machine learning models offer a promising pathway for uncovering important nuclear data dependencies and guiding future data evaluation efforts.

Nuclear data↗

NASA NTRSDate not supplied

Battery Evaluation Profiles for X-57 and Future Urban Electric Aircraft

Battery energy density is one of the most critical design parameters for sizing all-electric aircraft, however it’s easily overestimated. Establishing the effective, usable energy density is confused by varying degrees of margin needed to account for structural and thermal management between different cell chemistry and pack designs. Therefore, a better methodology is needed to fairly compare emerging battery technologies for electric aircraft. Currently, there is a loss of critical information when vehicle trade studies are performed using “nominal” published cell-level performance metrics. Aircraft power demands rarely match these nominal power profiles, and aircraft designers lack the ability to accurately simulate the battery performance and temperature off-nominally unless the battery chemistry is well established. Conversely, battery suppliers have no generalized reference cases to publish more realistic performance metrics. This can lead to poor assumptions, such as aircraft studies assuming a fixed discharge efficiency of a battery, when in reality the usable energy in a pack is dependent on the power and thermal profile. Information needed to properly assess weight penalties for thermal management is also typically poorly characterized when assessing candidate batteries. This paper serves to better inform battery development, and similarly, provide aircraft designers with more realistic assumptions for applying knockdown margins in their designs. Detailed power and thermal performance estimates are provided, which provide a starting point for sizing power and thermal budgets using experimentally derived battery models. Results show that the X-57 battery-to-shaft efficiency is 77.3% for a particular optimized mission. Considering a 25% reserve on the battery capacity, this means that only roughly half of the original 55.3kWh ‘nominal’ pack energy can be converted to useful work during a mission. Further estimates on a clean-sheet VTOL optimization show an average 82.7% battery-to-shaft efficiency, using 98% peak efficiency inverters and 97.4% peak efficiency motors. Although higher battery efficiencies are possible, the resulting weight penalty negates improvement in vehicle performance. These trade-offs and resulting power profiles are provided as a starting point to better assess future battery designs.

Battery Electric Aircraft↗

DOE OSTI2023

Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models

Abstract We present 307 type Ia supernova (SN) light curves from the first 4 yr of the Transiting Exoplanet Survey Satellite mission. We use this sample to characterize the shapes of the early-time light curves, measure the rise times from first light to peak, and search for companion star interactions. Using simulations, we show that light curves must have noise <10% of the peak flux to avoid biases in the early-time light-curve shape, restricting our quantitative analysis to 74 light curves. We find that the mean power-law index t β 1 of the early-time light curves isβ 1 = 1.93 ± 0.57, and the mean rise time to peak is 15.7 ± 3.5 days. The underlying population distribution forβ 1 may instead consist of a Gaussian component with mean 2.29, width 0.34, and a long tail extending to values less than 1.0. We find that the data can rarely distinguish between models with and without companion interaction models. Nevertheless, we find three high-quality light curves that tentatively prefer the addition of a companion interaction model, but the statistical evidence for the companion interactions is not robust. We also find two SNe that disfavor the addition of a companion interaction model to a curved power-law model. Taking the 74 SNe together, we calculate 3σupper limits on the presence of companion signatures to control for orientation effects that can hide companions in individual light curves. Our results rule out common progenitor systems with companions having Roche lobe radii >31R ⊙ (separations >5.7 × 10 12 cm, 99.9% confidence level) and disfavor companions having Roche lobe radii >10R ⊙ (separations >1.9 × 10 12 cm, 95% confidence level). Lastly, we discuss the implications of our results for the intrinsic fraction of single degenerate progenitor systems.

Astronomy & Astrophysics↗

DOE OSTI2025

From Pollutant Removal to Renewable Energy: MoS2-Enhanced P25-Graphene Photocatalysts for Malathion Degradation and H2 Evolution

The widespread presence of pesticides—especially malathion—in aquatic environments presents a major obstacle to conventional remediation strategies, while the ongoing global energy crisis underscores the urgency of developing renewable energy sources such as hydrogen. In this context, photocatalytic water splitting emerges as a promising approach, though its practical application remains limited by poor charge carrier dynamics and insufficient visible-light utilization. Herein, we report the design and evaluation of a series of TiO2-based ternary nanocomposites comprising commercial P25 TiO2, reduced graphene oxide (rGO), and molybdenum disulfide (MoS2), with MoS2 loadings ranging from 1% to 10% by weight. The photocatalysts were fabricated via a two-step method: hydrothermal integration of rGO into P25 followed by solution-phase self-assembly of exfoliated MoS2 nanosheets. The composites were systematically characterized using X-ray diffraction (XRD), Raman spectroscopy, transmission electron microscopy (TEM), UV-Vis diffuse reflectance spectroscopy (DRS), and photoluminescence (PL) spectroscopy. Photocatalytic activity was assessed through two key applications: the degradation of malathion (20 mg/L) under simulated solar irradiation and hydrogen evolution from water in the presence of sacrificial agents. Quantification was performed using UV-Vis spectroscopy, gas chromatography–mass spectrometry (GC-MS), and thermal conductivity detection (GC-TCD). Results showed that the integration of rGO significantly enhanced surface area and charge mobility, while MoS2 served as an effective co-catalyst, promoting interfacial charge separation and acting as an active site for hydrogen evolution. Nearly complete malathion degradation (~100%) was achieved within two hours, and hydrogen production reached up to 6000 µmol g−1 h−1 under optimal MoS2 loading. Notably, photocatalytic performance declined with higher MoS2 content due to recombination effects. Overall, this work demonstrates the synergistic enhancement provided by rGO and MoS2 in a stable P25-based system and underscores the viability of such ternary nanocomposites for addressing both environmental remediation and sustainable energy conversion challenges.

Chemistry↗

DOE OSTI2026

Reduced instability growth and improved radiation trapping with optimized shock timing in double-shell inertial confinement fusion capsules

The double shell is a volume-burn inertial confinement fusion concept consisting of two concentric shells: a low-Z outer shell that collides with and transfers momentum to a high-Z inner shell which compresses and heats the thermonuclear fuel. The increased number of capsule interfaces and severe hydrodynamic instability of the high-density pusher during its acceleration phase provide challenges to the success of the double shell. Two-dimensional radiation-hydrodynamics simulations predict the hydrodynamic instability growth on the outer surface of the pusher can be greatly reduced through appropriate timing of two shocks that cross this interface. One of these shocks, unique to multi-shell designs, arises from radiation-driven ablation of the inner shell ahead of the main shock, the second shock of concern. The shock timing is optimized by increasing the thickness of a low-Z tamper layer exterior to the pusher, resulting in only minimal changes to the implosion timing. Reducing the instability growth on the outer surface of the high-Z pusher can dramatically decrease the modulations that feedthrough to the pusher inner surface, improving the efficacy of radiation trapping in the thermonuclear fuel and increasing the predicted thermonuclear yield by ≳20×.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗