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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

New Deformation Mechanisms in Nanocrystalline Nano-porous Small Scale Metals as Defined by Kinetically-driven Microstructures

This report describes recent advances in the design and fabrication of nanostructured metallic pillars with hierarchical microstructures using a novel nanoscale additive manufacturing approach. Through a hydrogel-infusion-based two-photon lithography (TPL) method, we successfully fabricated 3D nickel nanopillars exhibiting both nanocrystalline and nanoporous features. The resulting “bamboo-like” internal architecture comprises 30–50 nm grains and voids with similarly scaled pores. These geometrically tunable pillars, with diameters ranging from ~130 to 550 nm, serve as an ideal platform for probing deformation mechanisms in structurally heterogeneous metals at the nanoscale.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A probabilistic graphical model foundation for enabling predictive digital twins at scale

A unifying mathematical formulation is needed to move from one-off digital twins built through custom implementations to robust digital twin implementations at scale. This work proposes a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset. We create an abstraction of the asset–twin system as a set of coupled dynamical systems, evolving over time through their respective state spaces and interacting via observed data and control inputs. The formal definition of this coupled system as a probabilistic graphical model enables us to draw upon well-established theory and methods from Bayesian statistics, dynamical systems and control theory. The declarative and general nature of the proposed digital twin model make it rigorous yet flexible, enabling its application at scale in a diverse range of application areas. Here, we demonstrate how the model is instantiated to enable a structural digital twin of an unmanned aerial vehicle (UAV). The digital twin is calibrated using experimental data from a physical UAV asset. Its use in dynamic decision-making is then illustrated in a synthetic example where the UAV undergoes an in-flight damage event and the digital twin is dynamically updated using sensor data. The graphical model foundation ensures that the digital twin calibration and updating process is principled, unified and able to scale to an entire fleet of digital twins.

42 ENGINEERING↗
DOE OSTI2020

Predicting Microstructural Void Nucleation in Discontinuous Fiber Composites through Coupled in-situ X-ray Tomography Experiments and Simulations

Composite materials have become widely used in engineering applications, in order to reduce the overall weight of structures while retaining their required strength. In this work, a composite material consisting of discontinuous glass fibers in a polypropylene matrix is studied at the microstructural level through coupled experiments and simulations, in order to uncover the mechanisms that cause damage to initiate in the microstructure under macroscopic tension. Specifically, we show how hydrostatic stresses in the matrix can be used as a metric to explain and predict the exact location of microvoid nucleation that occurs during damage initiation within the composite’s microstructure. Furthermore, this work provides evidence that hydrostatic stresses in the matrix can lead to coupled microvoid nucleation and early fiber breakage, and that small fragments of fibers can play an important role in the process of microvoid nucleation. These results significantly improve our understanding of the mechanics that drive the initiation of damage in the complex microstructures of discontinuous fiber reinforced thermoplastics, while also allowing scientists and engineers to predict the microstructural damage behavior of these composites at sub-fiber resolution and with high accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Aerodynamic Data Fusion Toward the Digital Twin Paradigm

This paper considers the fusion of two aerodynamic data sets originating from differing types of physical or computer experiments. This paper specifically addresses the fusion of 1) noisy and in-complete fields from wind-tunnel measurements and 2) deterministic but biased fields from numerical simulations. These two data sources are fused in order to estimate the true field that best matches measured quantities that serve as the ground truth. For example, two sources of pressure fields about an aircraft are fused based on measured forces and moments from a wind-tunnel experiment. A fundamental challenge in this problem is that the true field is unknown and cannot be estimated with 100% certainty. A Bayesian framework is employed to infer the true fields conditioned on measured quantities of interest; essentially a statistical correction to the data is performed. The fused data may then be used to construct more accurate surrogate models suitable for early stages of aerospace design. An extension of the proper orthogonal decomposition with constraints is also introduced to solve the same problem. In this work, both methods are demonstrated on fusing the pressure distributions for flow past the RAE2822 airfoil and the Common Research Model wing at transonic conditions. Comparison of both methods reveals that the Bayesian method is more robust when data are scarce and capable of also accounting for uncertainties in the data. Furthermore, given adequate data, the proper-orthogonal-decomposition-based and Bayesian approaches lead to surprisingly similar results.

42 ENGINEERING↗
DOE OSTI2021

In-Situ Calibrated Digital Process Twin Models for Resource Efficient Manufacturing

The chief objective of manufacturing process improvement efforts is to significantly minimize process resources such as time, cost, waste, and consumed energy while improving product quality and process productivity. This paper presents a novel physics-informed optimization approach based on artificial intelligence (AI) to generate digital process twins (DPTs). The utility of the DPT approach is demonstrated in the case of finish machining of aerospace components made from gamma titanium aluminide alloy (γ-TiAl). This particular component has been plagued with persistent quality defects, including surface and sub-surface cracks, which adversely affect resource efficiency. Previous process improvement efforts have been restricted to anecdotal post-mortem investigation and empirical modeling, which fail to address the fundamental issue of how and when cracks occur during cutting. In this work, the integration of in-situ process characterization with modular physics-based models is presented, and machine learning algorithms are used to create a DPT capable of reducing environmental and energy impacts while significantly increasing yield and profitability. Based on the preliminary results presented here, we report an improvement in the overall embodied energy efficiency of over 84%, 93% in process queuing time, 2% in scrap cost, and 93% in queuing cost has been realized for γ-TiAl machining using our novel approach.

42 ENGINEERING↗
DOE OSTI2025

Rheology improvement for silicon nitride and resin slurries for vat photopolymerization printing and sintering

This work presents the formulation, rheological characterization, and sintering of silicon nitride (Si₃N₄) slurries for vat photopolymerization (VPP) using digital light processing (DLP). Bimodal Si₃N₄ powder was dispersed into commercial photopolymer resin using two different dispersants with opposing effects on surface charge, resulting in varied slurry stability and flow behavior. Slurries were engineered to exhibit shear-thinning behavior suitable for VPP, and their flow properties were quantified using a power-law fluid model. The formulations achieved cure depths of approximately 40 µm and enabled printing of green bodies. Post-processing included thermal debinding and liquid-phase sintering, yielding primarily β-Si₃N₄ with a minor Y-Si-Al-O-N glass phase. The sintered parts reached ~85% of theoretical density and demonstrated a flexural strength of ~330 MPa. Microstructural analysis revealed closed porosity along with some defects related to powder agglomeration and interlayer adhesion. These findings provide insights into slurry formulation strategies for additive manufacturing of high-performance non-oxide ceramics.

Aerospace engineering↗
DOE OSTI2025

Multiple‐Repeated Plasma Surface Treatments for Significantly Improving Bonding Performance of Metal‐Carbon‐Fiber‐Reinforced Thermoplastic Polymer Dissimilar Adhesive Joints

This work investigates how multiple‐repeated plasma surface treatments can significantly enhance adhesively bonded metal‐carbon‐fiber‐reinforced thermoplastic polymer (CFRTP) dissimilar joints, a topic that has been rarely investigated compared to other parameters during the plasma treatment process. By conducting double cantilever beam tests on adhesively bonded AA6061‐carbon‐fiber‐reinforced polyphthalamide (CFRPPA) dissimilar joints, it is shown that the average Mode I specific fracture energy after 20 repetitions of the same plasma treatment, using processing parameters without noticeably changing surface roughness, can be improved and saturated up to almost 2000% compared to non‐treated joints and almost 240% compared to a single plasma treatment commonly used in the literature. The improvement can be attributed to the enhanced chemical bonding at the CFRPPA‐adhesive interface. This study is important for achieving strong bonding performance of CFRTP‐related structural joints using multiple plasma treatments, a simple and effective method.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Physicochemical properties of digital light processing 3D-Printed alumina and mullite ceramics

Alumina ceramics fabricated using conventional techniques such as uniaxial pressing or injection molding are popular due to their low density, excellent insulation, and mechanical properties. However, these methods often limit the fabrication of complex geometries with high dimensional accuracy due to tooling constraints and limited design freedom. To overcome these limitations, this study employed Digital Light Processing (DLP) additive manufacturing (AM), which enables the production of precise structures. In addition, the optimization of sintering parameters to enhance the densification and performance of alumina and mullite ceramics was investigated, with a specific focus on how varying sintering temperatures and hold times affect part shrinkage, geometric accuracy, and material integrity. Flexural strength of both alumina and mullite specimens was clearly influenced by the way the layers was stacked. When layers were arranged across the direction of the applied load (Z = 4; XZ), the strength was higher than when they were stacked along the same direction as the load (Z = 3; XY). Weibull analysis based on these results showed high modulus values across all samples, indicating good reliability in the flexural strength measurements. This reliability, combined with the clear influence of sintering parameters, highlights how processing conditions effect the material properties and mechanical performance of parts produced through DLP additive manufacturing. In conclusion, these findings open new avenues for ceramic AM across various applications, enhancing the potential for innovation in fields such as aerospace, biomedical engineering, and energy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

SEEMS: A Single Event Effects and Muon Spectroscopy facility at the Spallation Neutron Source

This study outlines a concept that would leverage the existing proton accelerator at the Spallation Neutron Source (SNS) of Oak Ridge National Laboratory to enable transformative science via one world-class facility serving two missions: Single Event Effects (SEE) and Muon Spectroscopy (μSR). The μSR portion would deliver the world’s highest flux and highest resolution pulsed muon beams for material characterization purposes, with precision and capabilities well beyond comparable facilities. The SEE capabilities deliver neutron, proton, and muon beams for aerospace industries that are facing an impending challenge to certify equipment for safe and reliable behavior under bombardment from atmospheric radiation originating from cosmic and solar rays. With negligible impact on the primary neutron scattering mission of the SNS, the proposed facility will have enormous benefits for both science and industry. Herein, we have designated this facility “SEEMS.”

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

The ATTO-Campina site: A new observatory for tropical convection and gas-aerosol-cloud-precipitation interactions in the Amazon

We present results from ATTO-Campina, a new permanent observational site in central Amazon, about 4 km from the ATTO towers. Operational since 2020, ATTO-Campina characterizes atmospheric, cloud and rainfall properties through remote sensing. The goal is to provide continuous, complementary measurements to the ATTO towers, addressing the rainforest’s complex gas-aerosol-cloud-precipitation dynamics. Using a 3.5-year dataset, we classified convective clouds into three types: shallow cumulus (ShCu), congestus (Con) or (Deep) clouds. The shallow-to-deep transition takes about three hours, starting with ShCu formation at 11:00 local time. The accumulated rainfall peak follows at about 16:00. Only weak downdrafts are present in the upper troposphere where previous studies indicate new particle formation (NPF) occurrence. Strong downdrafts are mostly limited to heights below 5 km. Con and Deep convective days have higher concentrations of ultrafine aerosol and lower concentrations of accumulation-mode particles compared to ShCu. Convective clouds also significantly modify gas mixing ratios. Deep convective clouds are associated with high near-surface O3, consistent with downward transport from the midtroposphere. Our results showcase the added detail achieved by integrating data from the ATTO towers and ATTO-Campina sites. Together, these sites support better understanding of interconnected gas-aerosol-cloud-precipitation processes in the Amazon and their evolution under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

High-Efficiency, Low-Cost III-V Solar Cells by Dynamic Hydride Vapor Phase Epitaxy Coupled with Rapid, Polishing-Free Wafer Reuse through Orientation-Optimized (110) Spalling

We demonstrated (110) GaAs solar cells grown by D-HVPE with equivalent performance and material quality relative to (100) devices. Also, we developed a procedure for repeatable wafer-scale spalling of (110) GaAs. Spalled surfaces were free of the facets founds in (100) GaAs spalling, the large arrest lines found in (100) Ge spalling, and surface features greater than 3 µm in peak-to-valley height, which can otherwise degrade the efficiency of regrown III-V devices. A sub-µm step-terrace morphology was discovered on the post-spall wafer surface, resulting from the restricted cleavage system of GaAs, but we developed understanding of the factors that determine the resulting morphology, enabling ample opportunity for optimization of morphologies suitable for device growth and spall depth waste minimization on (110) GaAs. Lastly, we demonstrated a device grown on a previously spalled surface with only 8% relative efficiency difference to a cell grown on a new unspalled wafer. Significant optimization of the substrate regrowth conditions are required to enable higher efficiency, but these results highlight the promise of (110)-oriented devices coupled with substrate reuse by spalling as a pathway for low-cost III-V photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2023

Multidisciplinary design optimization in Architecture, Engineering, and Construction: a detailed review and call for collaboration

The design of buildings has become a complex and multidisciplinary problem involving multiple conflicting objectives as architects and designers address competing technical, economic, environmental, and societal concerns. This has been driving research in Architecture, Engineering, and Construction (AEC) toward rigorous multidisciplinary decision-making frameworks that generate and evaluate numerous design alternatives using multi-objective optimization in concert with simulation and analysis models of varying fidelity and computational expense. While such frameworks are well known and widely employed in the aerospace and systems engineering domains, efforts by design professionals and researchers in the AEC field are scattered at best. In this paper, we provide a detailed review of recent developments in optimization frameworks in the AEC field and subsequently highlight how such developments are largely compartmentalized into separate domains such as structural, energy, daylighting, and other performance factors. Herein, we further discuss the technical challenges involved in concurrent coupled multidisciplinary design optimization (MDO) in the AEC field such as interoperability issues between Building Information Modeling (BIM) environments, analysis/simulation tools, and optimization frameworks. We conclude by outlining research needed for more unified modeling and simulation-based optimization frameworks to aid in complex and multidisciplinary building design processes. We also highlight the need for the identification and development of multi-fidelity simulation tools for use across multiple design phases. As such, this paper contributes a novel roadmap to leverage aerospace and systems engineering research in MDO into the field of AEC, along with a call for researchers in the MDO community to seek collaborations in AEC field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗