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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Regularizing INR with Diffusion Prior for Self-Supervised 3D Reconstruction OF Neutron Computed Tomography Data

Recently, generative diffusion priors have made huge strides as inverse problem solvers, including the ability to be adapted for inference on out-of-distribution data. Concurrently, implicit neural representations (INRs) have emerged as fast and lightweight inverse imaging solvers that are amenable to hybrid approaches that combine learned priors with traditional inverse problem formulations. In this paper, we present a diffusive computed tomography (CT) inversion framework for regularizing INRs called Diffusive INR (DINR), designed to enable high-quality reconstruction from sparse-view neutron CT. Pretrained purely on synthetic data, DINR is evaluated on simulated and experimentally obtained observations of concrete microstructures, where traditional reconstruction methods suffer substantial degradation when the number of views is reduced. Our approach delivers superior performance, reduces reconstruction artifacts, and achieves gains in PSNR and SSIM, enabling accurate micro-structural characterization even under extreme data limitations compared to state-of-the-art sparse-view reconstruction techniques.

Hossain, Maliha [ORNL]↗
DOE OSTI2019

Spatiotemporal light control with active metasurfaces

Optical metasurfaces have provided us with extraordinary ways to control light by spatially structuring materials. The space-time duality in Maxwell’s equations suggests that additional structuring of metasurfaces in the time domain can even further expand their impact on the field of optics. Advances toward this goal critically rely on the development of new materials and nanostructures that exhibit very large and fast changes in their optical properties in response to external stimuli. New physics is also emerging as ultrafast tuning of metasurfaces is becoming possible, including wavelength shifts that emulate the Doppler effect, Lorentz nonreciprocity, time-reversed optical behavior, and negative refraction. The large-scale manufacturing of dynamic flat optics has the potential to revolutionize many emerging technologies that require active wavefront shaping with lightweight, compact, and power-efficient components.

Science & Technology - Other Topics↗
DOE OSTI2023

Di-CNN: Domain-Knowledge-Informed Convolutional Neural Network for Manufacturing Quality Prediction

In manufacturing, convolutional neural networks (CNNs) are widely used on image sensor data for data-driven process monitoring and quality prediction. However, as purely data-driven models, CNNs do not integrate physical measures or practical considerations into the model structure or training procedure. Consequently, CNNs’ prediction accuracy can be limited, and model outputs may be hard to interpret practically. This study aims to leverage manufacturing domain knowledge to improve the accuracy and interpretability of CNNs in quality prediction. A novel CNN model, named Di-CNN, was developed that learns from both design-stage information (such as working condition and operational mode) and real-time sensor data, and adaptively weighs these data sources during model training. It exploits domain knowledge to guide model training, thus improving prediction accuracy and model interpretability. A case study on resistance spot welding, a popular lightweight metal-joining process for automotive manufacturing, compared the performance of (1) a Di-CNN with adaptive weights (the proposed model), (2) a Di-CNN without adaptive weights, and (3) a conventional CNN. The quality prediction results were measured with the mean squared error (MSE) over sixfold cross-validation. Model (1) achieved a mean MSE of 6.8866 and a median MSE of 6.1916, Model (2) achieved 13.6171 and 13.1343, and Model (3) achieved 27.2935 and 25.6117, demonstrating the superior performance of the proposed model.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Ionic Conductive and Highly-Stable Interface for Alkali Metal Anodes

Alkali metals are regarded as the most promising candidates for advanced anode for the next-generation batteries due to their high specific capacity, low electrochemical potential, and lightweight. However, critical problems of the alkali metal anodes, especially dendrite formation and interface stabilization, remain challenging to overcome. The solid electrolyte interphase (SEI) is a key factor affecting Li and Na deposition behavior and electrochemical performances. Herein, a facile and universal approach is successfully developed to fabricate ionic conductive interfaces for Li and Na metal anodes by modified atomic layer deposition (ALD). In this process, the Li metal (or Na metal) plays the role of Li (or Na) source without any additional Li (or Na) precursor during ALD. Moreover, the key questions about the influence of ALD deposition temperature on the compositions and structure of the coatings are addressed. The optimized ionic conductive coatings have significantly improved the electrochemical performances. In addition, the electrochemical phase-field model is performed to prove that the ionic conductive coating is very effective in promoting uniform electrodeposition. Further, this approach is universal and can be potentially applied to other different metal anodes. At the same time, it can be extended to other types of coatings or other deposition techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Flexible transparent conducting electrodes unexpectedly influence MAPbI 3 film morphology and perovskite solar cell performance

Fabricating perovskite solar cells (PSCs) on plastic substrates will enable cost-effective manufacturing of lightweight and portable energy systems. Here, we study the influence of flexible transparent conductive electrodes (TCEs) on the methylammonium lead iodide (MAPbI3) film morphology and PSC performance. Three types of TCEs on polyethylene terephthalate (PET) are compared: a custom-made AgNWs/indium zinc oxide hybrid TCE and two commercial substrates with indium tin oxide (ITO) or metal/insulator/metal (MIM) as the TCE. Using the same p-i-n architecture and hole transport layer (HTL), we find that PSCs fabricated on the hybrid TCE show better performance and stability compared to those made on commercial TCEs. The PSC performance enhancement is attributed to the superior structural and optical properties of MAPbI3 film deposited on the hybrid TCE, which is explained by the surface energy difference of the HTL. While it is anticipated that solar cell performance can be affected by TCEs’ transmittance and sheet resistance as they determine light absorption and carrier transport, respectively, our finding of TCE influencing the morphology and crystallinity of MAPbI3 film, and hence PSC performance, is unexpected.

14 SOLAR ENERGY↗
DOE OSTI2025

ATcT — Active Thermochemical Tables Python Interface

SF-25-140 atct is a lightweight, Python client for the ATcT v1 API that enables programmatic access to high-accuracy thermochemical data and turnkey reaction-enthalpy analysis. The package implements full v1 endpoint coverage (species lookup by ATcT ID, name, formula, SMILES, InChI, CAS RN; covariance queries; health checks) with robust error handling, retries, and environment-based configuration for local/production endpoints. Beyond data retrieval, atct provides rigorously implemented reaction calculators that propagate uncertainties via either (i) a conventional independent-errors method (0 K or 298.15 K) or (ii) covariance-aware propagation using provided covariances at 298.15 K. Typed data classes ensure transparent, reproducible data structures and carry ATcT Thermochemical Network (TN) version identifiers for provenance. Dual import paths and comprehensive examples facilitate integration into research pipelines, enabling reproducible thermochemical calculations, automated validation, and downstream method development.

Bross, DavidHamilton [Argonne National Laboratory ↗
DOE OSTI2024

Enabling Ultra-Compact, Lightweight, Efficient, and Reliable 6.6 kW On-Board Bi-Directional Electric Vehicle Charger with Advanced Topology and Control

The research explored new topologies, control methods, mechanical integration, and thermal management methods for electric vehicle (EV) on-board chargers. The team investigated capacitor-based power conversion, leveraging the high energy densities inherent to capacitive energy storage compared to inductive methods. The proposed topologies simultaneously enabled high power density and high efficiency of the design. The proposed architecture was demonstrated in a 6.6 kW bi-directional charger prototype. The research pursued several directions to improve system performance. Innovative topologies were studied for both the main power conversion stage as well as the single-phase twice-line-frequency energy buffer. To ensure robust and efficient operation, new control methods were developed to integrate these two subsystems. To achieve high power density in the full system solution, the mechanical structure of the charger is highly optimized to maximally fill the converter box volume. In parallel with the mechanical design effort, the converter was packaged with high-performance cooling methods which removed heat from key areas of power dissipation in the converter. The thermal management system was optimized to minimize its weight and volume, ultimately motivating the design of a custom additively manufactured cold-plate. The full system achieves a peak power of 7 kW with less than 0.3% total harmonic distortion (THD) and greater than 0.994 power factor in power factor correction (PFC) operation, corresponding to a total box-volume power density of 47.9 kW/L and gravimetric power density of 24.6 W/g. The system achieves a peak efficiency of 98.9%, with 97.9% efficiency at maximum power.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Weakly supervised anomaly detection in the Milky Way

ABSTRACT Large-scale astrophysics data sets present an opportunity for new machine learning techniques to identify regions of interest that might otherwise be overlooked by traditional searches. To this end, we demonstrate how Classification Without Labels (CWoLa), a weakly supervised anomaly detection method, can help identify cold stellar streams within the more than one billion Milky Way stars observed by the Gaia satellite. CWoLa operates without the use of labelled streams or knowledge of astrophysical principles. Instead, it uses a classifier to distinguish between mixed samples for which the proportions of signal and background samples are unknown. As a proof of concept, we demonstrate that this computationally lightweight strategy is able to detect both simulated streams and the known stream GD-1 in data. Originally designed for high-energy collider physics, this technique may have broad applicability within astrophysics as well as other domains interested in identifying localized anomalies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Development of Integrated Die Casting Process for Large Thin-Wall Magnesium Applications

The purpose of this project was to develop a process and product which would utilize magnesium die casting and result in energy savings when compared to the baseline steel product. The specific product chosen was a side door inner panel for a mid-size car. The scope of the project included: re-design of major structural parts of the door, design and build of the tooling required to make the parts, making of parts, assembly of doors, and testing (both physical and simulation) of doors. Additional work was done on alloy development, vacuum die casting, and overcasting, all in order to improve the performance of the doors and reduce cost. The project achieved the following objectives: 1. Demonstrated ability to design a large thin-wall magnesium die casting. 2. Demonstrated ability to manufacture a large thin-wall magnesium die casting in AM60 alloy. 3. Tested via simulations and/or physical tests the mechanical behavior and corrosion behavior of magnesium die castings and/or lightweight experimental automotive side doors which incorporate a large, thin-wall, powder coated, magnesium die casting. Under some load cases, the results revealed cracking of the casting, which can be addressed with re-design and better material models for CAE analysis. No corrosion of the magnesium panel was observed. 4. Using life cycle analysis models, compared the energy consumption and global warming potential of the lightweight door with those of a conventional steel door, both during manufacture and in service. Compared to a steel door, the lightweight door requires more energy to manufacture but less energy during operation (i.e., fuel consumption when driving vehicle). Similarly, compared to a steel door, the lightweight door has higher global warming potential (GWP) during manufacture, but lower GWP during operation. 5. Compared the conventional magnesium die casting process with the “super-vacuum” die casting process. Results achieved with cast tensile bars suggest some improvement in tensile properties with vacuum casting. Plant trials with large castings revealed cavity fill issues attributed to cooling and partial solidification of metal in the shot sleeve while waiting for vacuum to be established in the die cavity. 6. Developed age-hardenable Mg-based alloys as potential alternatives to the AM60 and AZ91 alloys typically used in automotive applications. Mg-7%Al-based alloys having Sn or Sn+Si additions exhibited significant age hardening, but more work is needed to demonstrate significant improvement in tensile properties. Corrosion behavior of these alloys is between those of AM60 and AZ91 alloys. 7. Evaluated the die casting of magnesium directly onto either steel or aluminum tubes as a potential process to make large lightweight subassemblies. Samples were free of gross defects, but additional work is needed to increase the interfacial shear strength. Overall, the project demonstrated that an automotive door-in-white design incorporating a die cast magnesium inner panel and a stamped aluminum outer panel can achieve approximately 50% mass reduction compared to the stamped steel baseline door-in-white. This leads to reduced energy consumption when driving the vehicle, which should more than offset the increased embedded energy of manufacture associated with the lighter metals. However, additional design work would be needed in order to meet the mechanical performance required of a door. Development of high-strength, high-ductility magnesium alloy castings would help make this technology more attractive for potential use in the side doors on automobiles. Also, increased use of recycled magnesium and aluminum would reduce the embedded energy and greenhouse gas emissions associated with the manufacture of this type of lightweight door. Commercialization planning of the type of lightweight door technology addressed in this project would be contingent upon the doors meeting all technical performance requirements of the car maker. The specific lightweight door developed in this project didn’t meet some of those requirements, but a preliminary business case study was conducted anyhow. This study considered the ratio of cost increase to mass decrease when the lightweight door is compared to a baseline steel door. The ratio was found to be in an acceptable range for some vehicle programs, especially if the number of such vehicles to be produced is equal to or slightly less than the estimated 250,000-shot life of the die set. This would allow for the investment in the dies to be spread across many parts and thereby help minimize the cost increase.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

High Velocity Joining of Multi-material Stacks Containing 3rd Generation Advanced High-Strength Stainless Steel and Aluminum Extrusion and Casting (Abstract)

Advanced lightweight materials, including multi-phase steels, aluminum extrusions and aluminum castings, have increasingly replaced mild steel to meet original equipment manufacturer (OEM) demand for increased fuel economy and crash-safety requirements. Third Generation (Gen 3) AHSS provides a superior combination of strength and ductility for crash energy management components in the vehicle body-in-white (BIW). Aluminum extrusions are widely used for bumper, door rocker panel, cradle and battery frame applications. Aluminum castings are increasingly being used in electric vehicles to provide part consolidation, weight saving and increased driving range. Rocker panels are, for example, an important component of the battery electric vehicle (BEV) body structure. The rocker panel serves several purposes, including structural support, crash resistance, protection for the vehicle's underbody and battery tray, and contributing to the overall aesthetics. In order to reduce weight, rocker panels are usually constructed using outer panels consisting of 3rd generation advanced high strength steels (AHSS) and an inner multicell aluminum extrusion structure for energy absorption which protects the batteries in a crash event. It is well known, however, that these material combinations provide significant challenges for joining and are susceptible to liquid metal embrittlement and loss of strength. The overall goal is to find a solution that addresses these challenges in order to produce multi-material vehicle components with reduced weight and minimal galvanic and recyclability issues. The approach being proposed here is to utilize a novel high velocity (HiVe) riveting and clinching technique recently demonstrated by Pacific Northwest National Laboratory (PNNL) to join (2T/3T) sheets of aluminum alloys and steel. This process will not only address the aforementioned challenges but also help significantly reduce the joining cycle time. This work will also demonstrate use of HiVe assemblies to be retrofitted to existing body-shop robots thus having minimal impact to existing body shop operations.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Strong and electrically conductive graphene-based composite fibers and laminates

In this study, graphene is an ideal candidate for lightweight, high-strength composite materials given its superior mechanical properties (specific strength of 130 GPa and stiffness of 1 TPa). To date, easily scalable graphene-like materials in a form of separated flakes (exfoliated graphene, graphene oxide, and reduced graphene oxide) have been investigated as candidates for large-scale applications such as material reinforcement. These graphene-like materials do not fully exhibit all the capabilities of graphene in composite materials. In this study, we show that macro (2 inch × 2 inch) graphene laminates and fibers can be produced using large continuous sheets of single-layer graphene grown by chemical vapor deposition. The resulting composite structures have potential to outperform the current state-of-the-art composite materials in both mechanical properties and electrical conductivities (>8 S/cm with only 0.13% volumetric graphene loading and 5 × 10 3 S/cm for pure graphene fibers) with estimated graphene contributions of >10 GPa in strength and 1 TPa in stiffness.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Additive Manufacturing of Self‐Sensing Carbon Fiber Composites

Carbon fiber-reinforced polymer (CFRP) composites have gained substantial attention across various industries owing to their exceptional mechanical properties and lightweight nature. The emergence of additive manufacturing technologies brings new opportunities to the industry, offering advantages such as design freedom, rapid prototyping, and customization. However, the fabrication of CFRP composites through 3D printing techniques poses challenges pertaining to low resolution and limitations in complex geometry realization. This work introduces digital light processing printing as a versatile, high-resolution method ideal for CFRP composite fabrication. Furthermore, the development and characterization of CFRP are focused on and the manipulation of mechanical properties through variations in matrix resins and fiber loadings is investigated, showcasing the versatility of CFRP composites for tailored applications. Additionally, the integration of self-sensing capabilities in CFRP structures is explored, which opens up opportunities for applications in smart components for automotive and structural health monitoring.

carbon fiber composites↗
DOE OSTI2024

Dissimilar material joining of densified superwood to aluminum by adhesive bonding

Abstract Superwood is a densified wood product that shows promise as a lightweight and renewable alternative for metallic materials. In order for this high-performance new material to be used in multi-material products, it must be able to be joined with other major materials. For example, joining superwood to aluminum would provide a key enabling technology for its use in automotive components since aluminum is presently a major lightweight material for such applications. In this paper, a methacrylate-based adhesive has been identified to provide high lap shear strength (7.5 MPa) for aluminum-to-superwood joints. The aluminum-to-superwood samples were prepared with different amounts of pre-polishing to create openings to the pores in the superwood so adhesive could penetrate into them and create a mechanical interlock, in addition to the hydrogen/chemical bonding at the surface between the methyl methacrylate (MMA) in methacrylate-based adhesive and the cellulose in superwood. For aluminum samples, a thin layer (typically a few nanometers) of oxide film on the surfaces provides hydrogen/chemical bond to MMA structure in the adhesive layer. The failure strength of the superwood-to-aluminum joint sample is about 50% higher than that of natural wood to natural wood joint sample and comparable to that of aluminum-to-aluminum joint sample.

Automation & Control Systems↗
DOE OSTI2025

An Open-source Llm Enhanced-tool Specialized In Helping Moose Related Problems And Tasks

MOOSEenger is an open-source, terminal-first chat application for the MOOSE ecosystem that couples specialized parsing of MOOSE documentation and “.i” input files with retrieval-augmented generation to deliver grounded answers about multiphysics modeling and workflows. It includes dedicated readers for MOOSE-style HTML and a pyhit-based parser that uses the MOOSE syntax tree to preserve block structure and attach retrieval metadata. A data-ingestion pipeline performs semantic chunking into atomic facts and stores them hierarchically in a local Chroma vector database that maintains parent–child relationships across documents; the system can ingest directories, individual files, and single-page web content, and it provides CRUD operations (insert, update, delete) to manage the corpus. At query time, relevant chunks are embedded, retrieved, and fused into the model context, with interactive features such as token streaming, persistent chat history, and dynamic RAG (retrieval triggered by user input or intermediate model output). Deployment is flexible: MOOSEenger runs with local Ollama models or remote Hugging Face/OpenAI backends—typically coordinating generation, lightweight tagging/summarization, and embeddings across three models—and it also supports a server mode and integration with the VS Code Continue interface.

Li, Mengnan [Idaho National Laboratory (INL), Idah↗
DOE OSTI2024

Parameter extraction approaches for compact modeling of thermoelectric modules

Thermoelectric (TE) cooling has experienced rapid advancements with the foundational understanding of TE materials. TE modules, compact and lightweight devices, have become the prevalent approach for implementing TE technologies. Accurately quantifying TE physical parameters (Seebeck coefficient α, thermal conductivity κ, and thermal resistance ρ) is challenging due to the dynamic temperature changes in operation. Furthermore, extracting lumped property parameters is crucial for designing energy systems using TE modules. Existing research has several limitations, such as lack of comparative analysis between prevalent formulae, reliance on potentially inaccurate vendor-supplied data, disregard for fundamental assumptions, and absence of empirical measurements. Further, this study addresses these gaps by conducting TE material characterization, comparing three existing formulae using vendor datasheets, designing a laboratory test facility for model validation and refinement, and outlining a structured data extraction procedure. The study's novelty lies in multiple key contributions: (1) a detailed comparative analysis of existing formulae for extracting TE property parameter; (2) executing experimental work in a laboratory setting to validate the model and elucidate its limitations; (3) highlighting potential risks; (4) clarifying possible assumptions from both material and engineering perspectives; and (5) considering temperature differential impacts. This comprehensive approach addresses the current research gaps and provides valuable insights into the design and application of TE modules in various energy systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Controlling N speciation in solution synthesis of N-doped carbon materials

Carbon-based materials, such as graphite and its functionalized/doped derivatives, are promising lightweight layered materials for hydrogen activation and storage. Their propensity to control the thermodynamics of hydrogen binding and the kinetics of hydrogen mobility strongly depends on the speciation and the arrangement of dopants. In this study, we demonstrate precise control over dopant speciation and clustering in nitrogen-containing layered carbon materials during hydrothermal synthesis. Through extensive spectroscopic characterization and first principles simulations, we demonstrate that the formation of N-motifs can be controlled by the choice of precursor and synthesis temperature. The distinct three-dimensional architecture and porosity in graphene oxide and carbon nitride-derived materials furnish a synthetic pathway for precise control over the local and global structure of nitrogen-doped carbon materials and their activity toward the activation of molecular hydrogen.

Byun, Mi Yeon [Pacific Northwest National Laborato↗
DOE OSTI2016

Decoupling antennas in printed technology using elliptical metasurface cloaks

In this paper, we extend the idea of reducing the electromagnetic interactions between transmitting radiators to the case of widely used planar antennas in printed technology based on the concept of mantle cloaking. Here, we show that how lightweight elliptical metasurface cloaks can be engineered to restore the intrinsic properties of printed antennas with strip inclusions. In order to present the novel approach, we consider two microstrip-fed monopole antennas resonating at slightly different frequencies cloaked by confocal elliptical metasurfaces formed by arrays of sub-wavelength periodic elements, partially embedded in the substrate. The presence of the metasurfaces leads to the drastic suppression of mutual near-field and far-field couplings between the antennas, and thus, their radiation patterns are restored as if they were isolated. Moreover, it is worth noting that this approach is not limited to printed radiators and can be applied to other planar structures as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Photo-Curing 3D Printing of Thermosetting Sacrificial Tooling for Fabricating Fiber-Reinforced Hollow Composites

Carbon fiber-reinforced hollow composites play a vital role in lightweighting modern cars and aircrafts. Fabrication of such hollow composites with seamless internal finish requires sacrificial tooling that can be used under pressure and high temperature. For the very first time, high performance sacrificial tooling that can be used to fabricate fiber-reinforced hollow composites is produced using photocuring 3D printing technology. This is achieved by developing UV-curable resins containing highly soluble yet hydrolysable acetal acrylate cross-linker and hydrophilic 4-acryloylmorpholine monomer. It is found that the cross-linker content greatly affects the printing speed. Further, the widely adopted UV post-curing method is found to have negligible impact on improving the thermal-mechanical properties of printed structures. Additionally, after thermal post-treatment, printed sacrificial tooling exhibits a heat deflection temperature of 112 °C at 0.455 MPa and an average coefficient of linear thermal expansion of 59 ppm °C -1 between 30 and 100 °C. As a result, printed tooling enables fabrication of carbon fiber-reinforced hollow composites with complex geometry, which shows a tensile strength of 802 MPa and an elastic modulus of 50.2 GPa.

36 MATERIALS SCIENCE↗