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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 253 records · Page 14

Optimizing the Smoothness and Thickness Uniformity of Thin-Film Parylene-N Vapor-Deposited Coatings for Inertial Confinement Fusion Experiments

Polymer coatings with submicrometer smoothness and constant thickness are a required component in a variety of inertial confinement fusion experiments. Smoothness is important for minimizing Rayleigh-Taylor-driven hydrodynamic instabilities, and uniform thickness is important for uniform shock propagation and shell convergence, both of which are critical phenomena that affect the experiment. The preferred polymer coating method is to vapor deposit the parylene-N polymer because it provides nominally smooth conformal coatings. As the coating thickness exceeds 5 µm, however, dome-shaped nodular growth defects develop and the thickness will vary by up to 17% over a distance of 3 cm. This study presents a deterministic method for achieving uniform film thicknesses with ±2% variability over 3 cm and a predictive method to control the thickness to within 5% of the desired value. A coating smoothness of ∼50 nm rms, measured over 40 000 µm 2 , was achieved by adding additional surfaces near the substrates. This additional area improved the thickness uniformity, an effect that is attributed to the low sticking coefficient of the parylene monomer.

chemical vapor deposition (CVD)↗

Ink-based laser powder bed fusion of barium titanate

Barium titanate (BTO) is a lead-free functional ceramic that is widely used in sensors, transducers, and actuators. The increasing demand for complex geometries and quick design iterations motivates the use of additive manufacturing techniques. Laser powder bed fusion (L-PBF) additive manufacturing technique enables the net-shape or near-net-shape fabrication of metals and alloys. Ceramic L-PBF remains challenging due to their high melting temperature. Here, to address this challenge, a nanoparticle ink feedstock was incorporated into the L-PBF process to allow low power melting of BTO. Key print parameters (i.e. laser power, scanning speed, and hatching spacing) were optimized to fabricate millimeter-scale BTO parts. The printed BTO samples possessed an inhomogeneous equiaxed-columnar-cellular microstructure. Semiconducting current-voltage behavior was observed in as-printed samples, which was attributed to the creation of oxygen vacancies. The piezoelectric d 33 coefficient was measured to be 4.6 pC/N.

Dielectrics↗

Controlled Synthesis of SnO 2 Nanocrystals with Tunable Band Gaps

Tin(IV) oxide nanocrystals (SnO 2 NCs) have significant potential in various applications, with their performance closely related to their band gap. The band gap is influenced by the size and shape of the NCs, which can be precisely controlled by adjusting reaction conditions. In this study, we present deliberately designed synthesis protocols to produce high-quality SnO 2 NCs with tunable band gaps using different methods. Key factors affecting the synthesis include control of the oxidizing agent, reaction temperature, solvent selection, and reaction time optimization. The resulting NCs were characterized by using TEM, XRD, XPS, and optical spectroscopy. Notably, SnO 2 NCs synthesized by controlling the oxidizing agent (air injection) in a hot organic solution were smaller in size and exhibited abundant oxygen vacancies. In contrast, extending the reaction time or using ethanol as a solvent in hydrothermal systems facilitated larger spherical or rod-like SnO 2 NCs with fewer oxygen vacancies. Further analysis of the band gap and valence band maximum energy revealed that the abundant vacancies in SnO 2 NCs synthesized with the air-controlled hot organic solution method resulted in a narrower band gap and an upshifted valence band. These synthetic strategies illustrate the potential for deliberately designing SnO 2 NCs with optimized electronic structures for various applications.

band gap↗

Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing

In this paper, we propose a method to perform empirical analysis of the loss landscape of machine learning (ML) models. The method is applied to two ML models for scientific sensing, which necessitates quantization to be deployed and are subject to noise and perturbations due to experimental conditions. Our method allows assessing the robustness of ML models to such effects as a function of quantization precision and under different regularization techniques -- two crucial concerns that remained underexplored so far. By investigating the interplay between performance, efficiency, and robustness by means of loss landscape analysis, we both established a strong correlation between gently-shaped landscapes and robustness to input and weight perturbations and observed other intriguing and non-obvious phenomena. Our method allows a systematic exploration of such trade-offs a priori, i.e., without training and testing multiple models, leading to more efficient development workflows. This work also highlights the importance of incorporating robustness into the Pareto optimization of ML models, enabling more reliable and adaptive scientific sensing systems.

Baldi, Tommaso [Pisa, Scuola Normale Superiore]↗

Exploring the Origins of Anti-Ambipolarity in BBL Polymer: Links to Redox Chemistry, Electronic Structure, and Structural Dynamics

We examine the intrinsic physical-chemical properties of the conjugated ladder-type polymer poly(benzimidazobenzophenanthroline) (BBL) in response to electron transfer. We aim at explaining the origin of the anti-ambipolar behavior behind the observed BBL nonlinear response associated with specific device architectures. To elucidate this point, we use theory and computation based on first principles, including density functional theory optimizations, ab initio molecular dynamics, time-dependent DFT, and Marcus-theory analysis. Our results reveal that this redox response is not simply monotonic but follows an alternating odd/even pattern in which gap narrowing and reopening occur sequentially before near-gapless behavior emerges at high charging. Converging theoretical evidence in this work demonstrates that bell shaped conductivity in BBL originates in its fundamental electronic structure and supramolecular organization.

FOS: Physical sciences↗

Optimal intrinsic alignment estimators in the presence of redshift-space distortions

We present estimators for quantifying intrinsic alignments in large spectroscopic surveys that efficiently capture line-of-sight (LOS) information while being relatively insensitive to redshift-space distortions (RSD). We demonstrate that changing the LOS integration range, pimax, as a function of transverse separation outperforms the conventional choice of a single pimax value. This is further improved by replacing the flat pimax cut with a LOS weighting based on shape projection and RSD. Although these estimators incorporate additional LOS information, they are projected correlations that exhibit signal-to-noise ratios comparable to 3D correlation functions, such as the IA quadrupole. Using simulations from Abacus Summit, we evaluate these estimators and provide recommended pimax values and weights for projected separations of 1 - 100 Mpc/h. These will improve measurements of intrinsic alignments in large cosmological surveys and the constraints they provide for both weak lensing and direct cosmological applications.

cosmology↗

Droplet bioprinting of acellular and cell-laden structures at high-resolutions

Advances in digital light projection(DLP) based (bio) printers have made printing of intricate structures at high resolution possible using a wide range of photosensitive bioinks. A typical setup of a DLP bioprinter includes a vat or reservoir filled with liquid bioink, which presents challenges in terms of cost associated with bioink synthesis, high waste, and gravity-induced cell settling, contaminations, or variation in bioink viscosity during the printing process. Here, we report a vat-free, low-volume, waste-free droplet bioprinting method capable of rapidly printing 3D soft structures at high resolution using model bioinks and model cells. A multiphase many-body dissipative particle dynamics model was developed to simulate the dynamic process of droplet-based DLP printing and elucidate the roles of surface wettability and bioink viscosity. Process variables such as light intensity, photo-initiator concentration, and bioink formulations were optimized to print 3D soft structures (∼0.4–3 kPa) with a typical layer thickness of 50 µm, an XY resolution of 38 ± 1.5 μm and Z resolution of 237 ± 5.4 µm. To demonstrate its versatility, droplet bioprinting was used to print a range of acellular 3D structures such as a lattice cube, a Mayan pyramid, a heart-shaped structure, and a microfluidic chip with endothelialized channels. Droplet bioprinting, performed using model C3H/10T1/2 cells, exhibited high viability (90%) and cell spreading. Additionally, microfluidic devices with internal channel networks lined with endothelial cells showed robust monolayer formation while osteoblast-laden constructs showed mineral deposition upon osteogenic induction. Overall, droplet bioprinting could be a low-cost, no-waste, easy-to-use, method to make customized bioprinted constructs for a range of biomedical applications.

DLP↗

Demonstration of a tandem lens for producing shaped laser-ionized plasmas for plasma wakefield acceleration

We demonstrate a tandem lens optical setup, comprising two diffractive optics, that focuses a high-power ultrafast laser with a shaped on-axis intensity profile, producing a meter-long Bessel focus. The intended use of the optical setup is to produce a laser-ionized plasma source for plasma wakefield acceleration. By controlling the on-axis intensity, the density profile of the plasma ramps at the entrance and exit of the plasma can be tailored to optimize the matching of the electron beam into the plasma. In addition to demonstrating the optical system, we describe the algorithm used to calculate the lens phases and present detailed calculations of the lenses’ expected performance.

Ariniello, Robert [SLAC National Accelerator Labor↗

Surrogate-driven Variance-based Sensitivity Analysis of Thermal Storage Tanks in Integrated Energy Systems

Sensitivity analysis and uncertainty quantification are essential steps for enhancing the accuracy of computational models by identifying and mitigating uncertainties. This study focuses on these steps for the Thermal Energy Delivery System at Idaho National Laboratory, specifically targeting the thermocline tank. Using a Modelica/Dymola simulation model, the study perturbed various design parameters and boundary conditions, including shape factor, porosity, outlet temperature, inlet mass flow rate, and system pressure, to predict and quantify uncertainty in the tank’s ax- ial temperature. A dataset of over 1,000 simulations was generated, and surrogate models were developed using the pyMAISE (Michigan Artificial Intelligence Standard Environment) library, which is an Automatic Machine Learning library for nuclear engineering applications. The optimal model, a feedforward neural network with two hidden layers, achieved an R2 score above 0.99 and a mean absolute error below 1 Kelvin. Sensitivity analyses using Sobol indices and Fourier amplitude sensitivity testing methods on this surrogate model revealed that the inlet mass flow rate at initial timestamps and porosity significantly impacts predicted temperatures across all sensors and time steps.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DEM simulation of the compression of crushable sand: does the initial particle shape matter?

Advances in DEM modeling, combined with high-resolution X-ray tomography, opened the way for computer models based on virtual replicas of the particles which preserve nearly all facets of their geometry. This leads to simulation advantages, but also high computational costs. Here we tackle a question stemming from this trend: how accurate should particle models be to ensure accuracy? We address this question for the case of the compression of crushable sand. LS-DEM was used to generate three models of Ottawa sand (exact replicas, ellipsoids, and spheres) from digital images of its grains. Compression-induced crushing was simulated for all sets by tracking evolving size and shape distribution. The results confirm that exact replicas provide the closest match of the measurements. However, intermediate degrees of rendering (e.g. ellipsoids preserving volume and aspect ratio of the real grains) led to satisfactory results only marginally different from those of exact replicas. In conclusion, these findings provide an example of the protocols that may be followed to identify the optimal degree of particle approximation which should be regarded as mandatory to achieve a conscious, sustainable use of computational resources.

58 GEOSCIENCES↗

Ni-Rich Li[Ni x MnyCo 1– x – y ]O 2 Single Crystals as Superior Fast Charge Cathodes for Lithium-Ion Batteries

The utilization of single-crystal (SC) Li[Ni x MnyCo 1-x-y ]O 2 (NMC) cathodes has facilitated unparalleled performance in commercial high-energy lithium-ion batteries (LIBs). In the current study, we evaluate the application of SC cathodes in fast charge (FC)-LIBs where particle cracking is a predominant failure mechanism. Ni-rich SC-NMC samples with various compositions, sizes, and shapes are synthesized and investigated for their influence on FC performance. We reveal the necessity of utilizing smaller SCs (<1 μm) as larger sizes (>2 μm) experience significant particle-level lithium concentration gradients under FC conditions. To improve lithium transport and minimize side reactivities, we strategically expose the (104) crystal facets on the surface. Exceptional performance was observed on an optimized SC-LiNi 0.80 Mn 0.05 Co 0.15 O 2 , delivering a discharge capacity of 165 mAh/g even after 150 cycles at 6C charge. Our study not only demonstrates the promise of SC-NMC but also provides the key insights for the design and optimization of advanced cathodes for FC-LIBs.

25 ENERGY STORAGE↗

Neutrino oscillation prospects with a dual-baseline beam from BNL to SNOLAB and SURF

The Electron-Ion Collider (EIC) is a next-generation accelerator primarily designed to study the internal structure of nucleons through high-precision electron-hadron collisions. In this work, we explore the feasibility of employing a 1 MW fraction of the EIC proton beam to generate a high-intensity GeV-scale neutrino beam for long-baseline oscillation studies. We have simulated proton-target interactions and optimize the resulting neutrino fluxes for water-based liquid scintillator (WbLS) detectors located at distinct baselines of 900 km and at 2900 km. Oscillation analyses performed with GLoBES show that extended baselines allow access to multiple oscillation maxima, significantly enhancing sensitivity to leptonic CP violation. The study also examines the interplay between matter effects and the intrinsic CP violating phase in shaping observable asymmetries. We note that simplified systematics and no backgrounds are used in this analysis to establish the baseline physics potential. These results suggest that the EIC proton beam could provide a novel and complementary source for precision neutrino physics, extending the scientific reach of the EIC program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Optimizing Transportation Networks for E-Waste Reverse Logistics: A Multi-Modal Cost Allocation and Pricing Strategy

The exponential growth of electronic waste (e-waste) poses critical challenges for sustainable reverse logistics and transportation network optimization. This study develops a dual-channel transportation framework for e-waste logistics that integrates dynamic freight pricing, cost allocation mechanisms, and game-theoretic coordination. The model captures interactions between centralized hubs and distributed processing networks, accounting for freight rate elasticity, volume allocation, and capacity constraints. Using Stackelberg game theory and cost-sharing strategies, the framework optimizes transportation efficiency and profit distribution across logistics channels. Numerical simulations show that the dual-channel structure increases centralized hub profit by 226.8% compared to baseline single-channel operations, while boosting total transported volume by 1.2% and nearly doubling freight collector profit under cost-sharing. Scenario analyses across regional infrastructures reveal that network density, policy incentives, and logistics costs shape routing efficiency and profit allocation. These findings suggest that coordinated strategies combining dynamic pricing, targeted infrastructure investment, and strategic cost allocation are needed to design efficient, resilient, and regionally adaptable e-waste transportation systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

BEACON—automated aberration correction for scanning transmission electron microscopy using Bayesian optimization

Aberration correction is an important aspect of modern high-resolution scanning transmission electron microscopy. Most methods of aligning aberration correctors require specialized sample regions and are unsuitable for fine-tuning aberrations without interrupting on-going experiments. Here, we present an automated method of correcting first- and second-order aberrations called BEACON, which uses Bayesian optimization of the normalized image variance to efficiently determine the optimal corrector settings. We demonstrate its use on gold nanoparticles and a hafnium dioxide thin film showing its versatility in nano- and atomic-scale experiments. BEACON can correct all first- and second-order aberrations simultaneously to achieve an initial alignment and first- and second-order aberrations independently for fine alignment. Ptychographic reconstructions are used to demonstrate an improvement in probe shape and a reduction in the target aberration.

techniques and instrumentation↗

Processability and Material Behavior of NiTi Shape Memory Alloys Using Wire Laser-Directed Energy Deposition (WL-DED)

Utilizing additive manufacturing (AM) techniques with shape memory alloys (SMAs) like NiTi shows great promise for fabricating highly flexible and functionally superior 3D metallic structures. Compared to methods relying on powder feedstocks, wire-based additive manufacturing processes provide a viable alternative, addressing challenges such as chemical composition instability, material availability, higher feedstock costs, and limitations on part size while simplifying process development. This study presented a novel approach by thoroughly assessing the printability of Ni-rich Ni55.94Ti (Wt. %) SMA using the wire laser-directed energy deposition (WL-DED) technique, addressing the existing knowledge gap regarding the laser wire-feed metal additive manufacturing of NiTi alloys. For the first time, the impact of processing parameters—specifically laser power (400–1000 W) and transverse speed (300–900 mm/min)—on single-track fabrication using NiTi wires in the WL-DED process was examined. An optimal range of process parameters was determined to achieve high-quality prints with minimal defects, such as wire dripping, stubbing, and overfilling. Building upon these findings, we printed five distinct cubes, demonstrating the feasibility of producing nearly porosity-free specimens. Notably, this study investigated the effect of energy density on the printed part density, impurity pick-up, transformation temperature, and hardness of the manufactured NiTi cubes. The results from the cube study demonstrated that varying energy densities (46.66–70 J/mm3) significantly affected the quality of the deposits. Lower to intermediate energy densities achieved high relative densities (>99%) and favorable phase transformation temperatures. In contrast, higher energy densities led to instability in melt pool shape, increased porosity, and discrepancies in phase transformation temperatures. These findings highlighted the critical role of precise parameter control in achieving functional NiTi parts and offer valuable insights for advancing AM techniques in fabricating larger high-quality NiTi components. Additionally, our research highlighted important considerations for civil engineering applications, particularly in the development of seismic dampers for energy dissipation in structures, offering a promising solution for enhancing structural performance and energy management in critical infrastructure.

Dabbaghi, Hediyeh↗

Linking Plant and Microbial Traits to Soil Carbon for Reliable and Resilient Bioenergy Systems

Bioenergy systems in the United States offer a dual opportunity to supply renewable feedstocks while enhancing ecosystem services such as hydrologic regulation, erosion control, and soil carbon (C) storage. National assessments highlight the potential to grow perennial energy crops to improve soil function and ecosystem resilience. Realizing this potential requires understanding the ecological mechanisms that govern how C is added, transformed, and stabilized in soils. Plant traits determine the quantity, depth, and chemistry of organic inputs, while microbial processes—including carbon use efficiency, necromass formation, and trophic interactions—mediate their transformation and partitioning among soil carbon pools. These biological pathways are shaped by soil physical and chemical properties, including aggregation, texture, and mineralogy, and by environmental drivers such as temperature, moisture, and disturbance, leading to context-dependent outcomes across landscapes. Management practices that diversify feedstocks, minimize disturbance, and maintain soil cover can promote both biomass production and C retention, while microbial amendments and rhizosphere engineering offer emerging, but often context-dependent, tools to optimize plant–microbe interactions. Trade-offs between biomass yield and soil carbon storage may arise when systems favor rapid aboveground productivity at the expense of belowground inputs and microbial processing, underscoring the importance of trait combinations that support both functions. Advances in monitoring, reporting, and verification—spanning precision agriculture, remote sensing, and biosensing—are improving predictive capacity through microbial-explicit process models and model–experiment (ModEx) frameworks. By connecting soil, plant, and microbial processes with advances in modeling and biosensing, this review outlines research priorities focused on trait-based parameterization and ModEx integration. These priorities will support the design of bioenergy systems that are both reliable and resilient, enhancing renewable energy production and ecosystem sustainability.

bioenergy systems↗

Thermal Management System of an Outer-Rotor-Motor-Based Traction Drive With Integrated Power Electronics in its Central Cavity

Increasing power densities of electric vehicle traction drive systems necessitates combining the electric motor and the power electronics into one unit. A compact, integrated traction drive unit with fewer components also drives production costs down, enabling wider adoption of electric vehicles. However, the integration of power electronics in the electric machine is associated with challenges of designing an effective thermal management solution for the combined traction drive system. This paper focuses on the thermal management approach selected for Oak Ridge National Laboratory’s outer-rotor-motor-based integrated traction drive and evaluates its potential performance. The outer-rotor-motor configuration provided an opportunity for integration of the six-phase inverter in the available space in the central cavity of the internal stator. A cylindrical inverter enclosure with integrated coolant (water-ethylene glycol) channels in its walls was designed to enable heat removal from the power electronics. Numerical thermal-fluid modeling and initial channel/fin optimization results for the cylindrical heat sink are presented here. As permanent magnets are integrated in a high-speed (20 000 RPM) outer rotor, forced air convection provides cooling for the magnets. The magnets were segmented axially to mitigate the eddy current losses. Heat generated in the stator windings and laminations is removed by water-ethylene glycol coolant circulating in interpolar T-shape ceramic heat exchangers inserted between windings. General design concepts and numerical thermal-fluid simulations illustrating the electric motor thermal management solution are also presented.

Kekelia, Bidzina↗

From Detector Layout to Signal Analysis: Geometry Optimization and Neutron-Gamma Tagging in Plastic Scintillator Detectors

Neutrinos are elementary particles with many properties still unknown. Their masses so far have only upper and lower limits. Still, due to neutrino oscillations, it is clear that they are not massless, as stated by the Standard Model of Elementary Particles. Neutrinos are also present in the Universe in vast amounts, but they rarely interact with the surrounding matter. Their abundance makes them very interesting for many theories beyond the Standard Model, e.g., dark matter searches and CP symmetry violation in the leptonic sector, which could be (partially) responsible for the observed matter-antimatter asymmetry in today's Universe.\\ The Deep Underground Neutrino Experiment (DUNE) is a next-generation accelerator-based neutrino oscillation experiment that will study neutrinos with unprecedented precision and may answer many open questions. DUNE uses a powerful neutrino beam from Fermilab. It consists of a Near Detector (ND) complex to measure neutrinos before oscillat ion, and a Far Detector (FD) complex $1300\ \mathrm{km}$ away to measure them after oscillation. As part of the ND complex, measurements are also possible with different angles to the neutrino beam. This enables excellent control of systematic uncertainties of e.g., neutrino cross section measurements.\\ One detector in the near detector complex is The Muon Spectrometer (TMS), an extension of a Liquid Argon (LAr) detector that measures the charge and momentum of muons produced in neutrino interactions within the LAr. The design of this detector, which consists of alternating layers of steel and plastic scintillator bars, must be optimized for the expected muon energies.\\ In this thesis, a study of the optimal module orientation plan is presented, which is necessary for the physics performance of the near detector complex and, by extension, DUNE. As part of this study, the event reconstruction was also developed and improved. Simulated muons are then reconstructed, and the performan ce of different module orientation plans is tested.\\ As a second part, a study of neutron and gamma tagging using a Pulse Shape Discriminating (PSD) plastic scintillator is presented. The properties of this material allow particle differentiation based on the temporal distribution of emitted light. A novel approach to using the individual light signals was successfully tested using data from a small, local test setup.

Nehm, Asa [Mainz U.]↗