Search NASA⌕ Search

SEARCH · Search NASA

Results for “Advanced composites”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Extending PETSc's Composable Hierarchical Solvers (Final Technical Report)

This report documents research activities conducted at CU Boulder as part of Extending PETSc’s Composable Hierarchical Solvers, which has been part of a collaboration with Argonne National Laboratory (separate award). Our work has focused on performance-portable end-to-end GPU solvers demonstrated via exemplary applications in nonlinear fluid and structural mechanics. We describe advances in algorithmic composition and analysis in the context of these applications, but the implementations are fully documented and decoupled, and in use by other projects. We believe the vertical integration achieved through collaboration with ECP’s CEED and the PSAAP center at CU was necessary to take risks with data structures and algorithms.

42 ENGINEERING↗
DOE OSTI2025

Joining Study for Formed Plate Heat Exchangers (Final Report)

Plate heat exchangers (PHEs) have been used in numerous industrial applications, such as HVAC systems, power generation, transportation and manufacturing. The performance of plate heat exchangers is frequently undermined by corrosion, fouling, and scaling. These phenomena not only diminish heat transfer efficiency but also lead to increased operational costs, maintenance demands, and reduced equipment lifespan. In this project, the team addressed the widespread challenges of corrosion, fouling, and scaling, and explored alternative material solutions. While commonly used materials like stainless steel and titanium offer notable benefits, they can still experience corrosion under certain operating conditions. The advancement of new materials and surface engineering technologies, such as advanced coating, ceramics, composites materials, and high entropy alloys are promising for can help solve these issues, enable longer lifetime and high performance of plate heat exchangers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Using simulation to study solid oxide cell degradation

Slides of the presentation given by Harry Abernathy from the National Energy Technology Laboratory at the 2023 International Conference and Expo on Advanced Ceramics and Composites. The presentation was an overview of NETL's solid oxide cell performance degradation modeling, including a demonstration of the impact of microstructural analysis methods on the resulting degradation simulations.

Abernathy, Harry↗
DOE OSTI2024

Developing higher performing solid oxide cells through simulation

Presentation given by NETL solid oxide cell (SOC) group leader Harry Abernathy reviewing NETL's SOC modeling capabilities for an invited talk at the 48th International Conference and Expo on Advanced Ceramics and Composites January 28 - February 2, 2024.

Abernathy, Harry↗
DOE OSTI2025

Development of a Representative Molten Chloride Fast Reactor Model to Assess the Impact of Nuclear Data

The SCALE code system was employed to conduct a preliminary investigation of nuclear data impacts for a fast spectrum molten chloride salt reactor. A computationally effective depletion model that is representative of the reactor system was successfully developed and used to conduct fuel depletion simulations. Development of this model draws from the SLICE method that was developed at Oak Ridge National Laboratory to enable generation of fuel compositions for an advanced reactor core at equilibrium operation. Eigenvalue uncertainty calculations using the ENDF/B-VII.1 nuclear data library were performed for the reactor in the fresh fuel state and an irradiated fuel state. It was determined that the primary driver of eigenvalue uncertainty was the uncertainty in the 235U (n, 𝛾) cross section. Uncertainty calculation results from this study were compared to results available for a different fast system, a sodium-cooled fast reactor, to confirm similarities and identify differences with respect to nuclear data impacts between the two fast advanced reactor systems.

Hirji, Rakim [Georgia Institute of Technology]↗
DOE OSTI2020

Recent advancements of plant-based natural fiber–reinforced composites and their applications

Demands for reducing energy consumption and environmental impacts are the major driving factors for the development of natural fiber–reinforced composites (NFRCs) in many sectors. Compared with synthesized fiber, natural fiber provides several advantages in terms of biodegradability, light weight, low price, life-cycle superiority, and satisfactory mechanical properties. However, the inherent features of plant-based natural fibers have presented challenges to the development and application of NFRCs, such as variable fiber quality, limited mechanical properties, water absorption, low thermal stability, incompatibility with hydrophobic matrices, and propensity to agglomeration. Substantial research has recently been conducted to address these challenges for improved performance of NFRCs and their applications. This article reviews the recent advancements of plant-based NFRCs, focusing on strategies and breakthroughs in enhancing the NFRCs’ performance, including fiber modification, fiber hybridization, lignocellulosic fillers incorporation, conventional processing techniques, additive manufacturing (3D printing), and new fiber source exploration. In conclusion, the sustainability of plant-based NFRCs using life-cycle assessment and the burgeoning applications of NFRCs with emphasis on the automotive industry are also discussed.

3D reinforcement↗
DOE OSTI2024

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Additively Manufactured Graded Composite Transition Joints for Dissimilar Metal Weldments in Advanced Ultra-Supercritical Power Plant (Final Technical Report)

In this project, we successfully achieved all the goals we proposed: ① Code Development; ② Transition Joint Design; ③ Lab-scale GCTJ Testing Piece Development; ④ Heat Treatment; ⑤ Welding of DMW; ⑥ Mechanical Characterization; ⑦ Corrosion; ⑧ Fabrication of Prototype GCTJ; ⑨In-field Test in SWRI and ⑩Tech-economic Analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predicting path-dependent diffusion barrier spectra in vast compositional space of multi-principal element alloys via convolutional neural networks

The emergent multi-principal element alloys (MPEAs) provide a vast compositional space to search for novel materials for technological advances. How to screen promising compositions from such an ample design space for targeted properties is a grand challenge. In this report, we demonstrate the state-of-the-art deep learning technology—convolutional neural network (CNN)—in predicting path-dependent vacancy migration energy barrier spectra, which are critical to diffusion behavior and many high-temperature properties, in the hyperdimensional composition space of MPEAs. The developed CNN model, fully capturing local chemical features surrounding each vacancy, accurately and efficiently predicts migration energy barrier of MPEAs with different degrees of chemical short-range order and at any unseen compositions. By varying the size of the local region encapsulating vacancy in the CNN model, we reveal that the length scale influencing vacancy migration is surprisingly extensive, up to its six nearest neighboring shells. The efforts of the CNN model make it promising for developing a database of diffusion barriers for various MPEA systems, which would have profound implications for accelerating alloy screening and discovering new compositions with desirable properties.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Ultrafast Nanoimaging of Carrier Funneling in Composition-Graded Semiconductor Nanowires

Recent advances in bandgap engineering of low-dimensional semiconductors have enabled high-efficiency carrier transport in miniaturized electronic and optoelectronic devices. The physical properties and functionalities of these materials are governed by complex carrier dynamics coupled with multiple transport mechanisms in tailored band structures. Here, we report ultrafast nanoimaging of carrier funneling and recombination in composition-grade CdSxSe1-x nanowires using pump-probe near-field nanoscopy. Leveraging the high resolution of this technique in both space and time, we resolve nanoscale local carrier dynamics along composition-graded nanowires, revealing the local variation of composition-dependent carrier mobilities and lifetimes that significantly differ from their uniform composition counterparts. Furthermore, we demonstrate a length-dependent behavior wherein shorter nanowires exhibit enhanced funneling effects, accelerating carrier transport by up to 33%. Our findings provide direct visualization of nanoscale carrier transport while supporting an effective approach for investigating complex carrier interactions in inhomogeneous semiconductor nanostructures, with implications for optimizing next-generation optoelectronic devices.

Yang, Rundi↗
DOE OSTI2025

Advanced polymer impregnation and pyrolysis (PIP) of SiOC-based ceramic matrix composites (CMCs)

Silicon carbide (SiC) ceramic matrix composites (CMCs) are valued for their high-temperature properties, making them ideal for harsh environments. However, conventional polymer impregnation and pyrolysis (C-PIP) often result in porous composites and require numerous cycles for densification. This study introduces the advanced PIP (A-PIP) method using a crosslinked polycarbosiloxane (PCS) precursor to enhance densification efficiency. Five SiC CMCs were fabricated using C-PIP and A-PIP, with variations in fiber reinforcement and fiber coatings. A-PIP achieved up to 19 % higher density and 78 % lower porosity in 79–86 % less processing time compared to C-PIP. Moreover, SiC-SiOC composites with boron nitride-coated fibers showed significant improvements in tensile strength (11 MPa to 134 MPa) and strain at maximum strength (0.01–0.11 %), underscoring the role of weak fiber-matrix interfaces. In conclusion, these results demonstrate A-PIP's potential to produce dense, low-porosity SiC CMCs more efficiently, significantly reducing manufacturing time and costs.

36 MATERIALS SCIENCE↗