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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Understanding interfacial crystallization dynamics on carbon fiber reinforced polypropylene composite manufacturing

Reinforcing polymers with discontinuous fibers improves mechanical properties, such as strength and stiffness, and in some cases achieve isotropic properties, rendering them suitable for various engineering applications. Matrix materials are generally highly engineered thermosets (e.g. crosslinked epoxies), bonded to the fiber periphery by proprietary surface and sizing chemistries. Semicrystalline thermoplastic matrices are less utilized due to poor fiber-matrix bonding resulting in inefficient interfacial load-transfer in reinforced composites. However, flexibility with melt-processing or molding conditions can be leveraged to promote non-covalent interfacial bonding between matrix and fiber via crystallization of the matrix onto fiber surface. In the present study, we utilize a co-mingle chopped carbon and isotactic polypropylene fibers to form isotropic composites, tailoring interfacial immobilized matrix or interphase morphology to optimize performance through precise control of thermal processing/molding windows. Calorimetry and optical microscopy were employed to investigate the impact of carbon fiber at various volume fractions (10, 20, and 30 %) on isotactic polypropylene crystallization and mechanical performance. Variations in mechanical properties correspond to the structural evolution of the interfacial region and are correlated to underlying microstructural attributes using wide-angle X-ray scattering, thermal analysis, and low-field nuclear magnetic resonance spectroscopy. These results provide a practical framework for the manufacturing of thermoplastic matrix composites. In conclusion, the results presented provide a guide for the strategic optimization of interphase design, showcasing tailorable tensile strengths which outperform any isotactic polypropylene carbon fiber composites previously reported in literature.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine learning approaches for intentional materials engineering

In this article, the development of nanoporous metals and metallic composites through dealloying processes presents significant opportunities in materials engineering. However, designing multicomponent precursor alloys and establishing corresponding processing methods that yield predictable compositions and nanostructures remain a complex challenge. This article explores how machine learning (ML)-augmented computational and experimental methodologies can tackle these challenges by predicting precursor alloy compositions, final nanoporous structures, and mechanical properties, while integrating ML-enabled autonomous experimentation for material design and quantification. We highlight recent advancements in applying ML to nanostructured materials design via dealloying and discuss how techniques from other nanomaterial designs can be adapted for improved control over morphological and compositional outcomes in nanoporous and nanocomposite materials. Furthermore, we explore the role of ML in autonomous synchrotron x-ray experimentation, enabling real-time feedback between modeling and experimental setups. ML-driven approaches to microstructure characterization and mechanical property prediction are also examined, with a focus on modeling and advanced imaging techniques such as three-dimensional nanotomography. Finally, this article outlines future directions for ML-enhanced materials science, emphasizing the exploration of high-dimensional parameter spaces and the incorporation of materials kinetics into processing and property evaluation, ultimately advancing the design of nanoporous structures and materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2021

CFD Analysis of RLUOB Zone 1 HEPA Filter Plenum and Testing Manifolds

The purpose of this computational fluid dynamics (CFD) analysis is to ensure that Camfil Farr’s upstream and downstream injection and sampling manifolds can meet or exceed the requirements outlined in the ASME AG-1 1997 a(2000) Code on Nuclear Air and Gas Treatment for the testing of HEPA and adsorbent filters. This paper will present a numerical simulation of airflow in the Radiological Laboratory Utility Office Building (RLUOB) zone 1 HEPA filter plenum and testing manifolds using the commercial CFD software ANSYS FLUENT 2020R1. The CFD analysis focuses on the investigation of the air flow distribution and air-aerosol mixing uniformity. The evaluation was done for all steps of the modeling process: grid generation, physics setup, simulation, and post-processing. The mass flow rate in each section of the zone 1 injection and sampling manifolds is also reported.

42 ENGINEERING↗
DOE OSTI2023

Efficient turbine engine using integrated ammonia fuel processing

A gas turbine engine includes a core engine that includes a core flow path where air is compressed in a compressor section, communicated to a combustor section, mixed with an ammonia based fuel and ignited to generate a high energy combusted gas flow that is expanded through a turbine section. The turbine section is mechanically coupled to drive the compressor section. An ammonia flow path communicates an ammonia flow to the combustor section. A cracking device is disposed in the ammonia flow path. The cracking device is configured to decompose the ammonia flow into a fuel flow containing hydrogen (H2). At least one heat exchanger is upstream of the cracking device that provides thermal communication between the ammonia flow and a working fluid flow such that the ammonia fluid flow accepts thermal energy from the working fluid flow.

Smith, Lance L.↗
DOE OSTI2022

Exploiting Machine Learning in Multiscale Modelling of Materials

Recent developments in efficient machine learning algorithms have spurred significant interest in the materials community. The inherently complex and multiscale problems in Materials Science and Engineering pose a formidable challenge. The present scenario of machine learning research in Materials Science has a clear lacunae, where efficient algorithms are being developed as a separate endeavour, while such methods are being applied as ‘black-box’ models by others. The present article aims to discuss pertinent issues related to the development and application of machine learning algorithms for various aspects of multiscale materials modelling. The authors present an overview of machine learning of equivariant properties, machine learning-aided statistical mechanics, the incorporation of ab initio approaches in multiscale models of materials processing and application of machine learning in uncertainty quantification. In addition to the above, the applicability of Bayesian approach for multiscale modelling will be discussed. Critical issues related to the multiscale materials modelling are also discussed.

42 ENGINEERING↗
DOE OSTI2020

Unraveling the Nature of Excellent Potassium Storage in Small-Molecule Se@Peapod-Like N-Doped Carbon Nanofibers

The potassium-selenium (K-Se) battery is considered as an alternative solution for stationary energy storage because of abundant resource of K. However, the detailed mechanism of the energy storage process is yet to be unraveled. In this work, the findings in probing the working mechanism of the K-ion storage in Se cathode are reported using both experimental and computational approaches. A flexible K-Se battery is prepared by employing the small-molecule Se embedded in freestanding N -doped porous carbon nanofibers thin film (Se@NPCFs) as cathode. The reaction mechanisms are elucidated by identifying the existence of short-chain molecular Se encapsulated inside the microporous host, which transforms to K 2 Se by a two-step conversion reaction via an "all-solid-state" electrochemical process in the carbonate electrolyte system. Through the whole reaction, the generation of polyselenides (K 2 Se n , 3 ≤ n ≤ 8) is effectively suppressed by electrochemical reaction dominated by Se-2 molecules, thus significantly enhancing the utilization of Se and effecting the voltage platform of the K-Se battery. This work offers a practical pathway to optimize the K-Se battery performance through structure engineering and manipulation of selenium chemistry for the formation of selective species and reveal its internal reaction mechanism in the carbonate electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2022

Deep Learning‐Assisted Automated Single Cell Electroporation Platform for Effective Genetic Manipulation of Hard‐to‐Transfect Cells

Abstract Genome engineering of cells using CRISPR/Cas systems has opened new avenues for pharmacological screening and investigating the molecular mechanisms of disease. A critical step in many such studies is the intracellular delivery of the gene editing machinery and the subsequent manipulation of cells. However, these workflows often involve processes such as bulk electroporation for intracellular delivery and fluorescence activated cell sorting for cell isolation that can be harsh to sensitive cell types such as human‐induced pluripotent stem cells (hiPSCs). This often leads to poor viability and low overall efficacy, requiring the use of large starting samples. In this work, a fully automated version of the nanofountain probe electroporation (NFP‐E) system, a nanopipette‐based single‐cell electroporation method is presented that provides superior cell viability and efficiency compared to traditional methods. The automated system utilizes a deep convolutional network to identify cell locations and a cell‐nanopipette contact algorithm to position the nanopipette over each cell for the application of electroporation pulses. The automated NFP‐E is combined with microconfinement arrays for cell isolation to demonstrate a workflow that can be used for CRISPR/Cas9 gene editing and cell tracking with potential applications in screening studies and isogenic cell line generation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Graphene oxide gluing layer enabling macroscale tribology applications of pristine graphene

In recent studies of two-dimensional (2D) nanomaterial-based solid lubricants, the importance of durability has been emerging for real engineering-scale applications. To achieve this, a transfer layer formation is essential to prevent the wear of the mechanical systems. However, it has been challenging for pristine graphene (PG) to induce a material transfer due to chemical inertness. In this study, we suggest an easy-to-process strategy to promote the huge material transfer of the PG onto the counterpart contacting material. We utilized graphene oxide (GO) as a gluing layer between the PG film and the counterpart contact surface to realize the superior tribological performance. The high interaction energy of the GO from its functional groups makes a contribution to the material transfer of PG, which is unveiled by a systematic analysis of the counterpart contact surface and the wear track. The huge solid transfer layer not only makes a wear-resistant contact interface between the transfer layer and the underlying film by densification and oxidation, but also reduces surface interaction energies, finally resulting in a significant improvement in durability.

graphene oxide (GO)↗
DOE OSTI2022

Numerical simulation of falling film sensible heat transfer over round horizontal tubes

Numerical simulations are performed to explore the heat transfer characteristics of falling films over horizontal round tubes with uniform heat flux imposed for a range of Reynolds numbers spanning the droplet, jet, and sheet regimes. Simulations results agree well with available experimental measurements. The study analyzes the local as well as average heat transfer behavior under the different flow modes. The numerical results show that the local Nusselt number (Nu) distribution depends on the flow features in each mode and varies substantially in all directions for the respective mode. In the droplet mode, the Nu value varies significantly as the droplet impinges and the remnant liquid-bridge retracts (peak instantaneous Nu near 6), followed by wave propagation over the tube surface with peak Nu around 0.25. For the jet modes, the local maximum in the heat transfer occurs off-center to the impingement location with magnitudes of peak Nu = 3.1 for the inline jet mode and Nu = 2.7 for the staggered jet mode, while on the rest of the tube surface, it has an inverse relation with the liquid film thickness. Substantial variations in the heat transfer value are also recorded in the middle of the two impinging jets with Nu = 0.95 in the inline jet mode where the neighboring jets do not interact, and Nu = 0.60 in the crest region of the staggered jet mode where the neighboring jets interact with each other. In the sheet mode, the Nu was seen to depend on the thickness of the liquid waves traversing over the tube surface. Lower Nu values were recorded beneath the crest location of the liquid waves, which increases (1.4–11.6% depending on circumferential location) abruptly in magnitude at the advancing fronts of the waves. The temperature distribution in the liquid film in each of the modes was examined to evaluate the mechanism of heat transfer process. This study also compares the local heat transfer coefficient distribution with the analytical heat transfer models derived to predict heat transfer performance over horizontal tube surfaces.

42 ENGINEERING↗
DOE OSTI2020

Extreme shear-deformation-induced modification of defect structures and hierarchical microstructure in an Al–Si alloy

Abstract Extreme shear deformation is used for several material processing methods and is unavoidable in many engineering applications in which two surfaces are in relative motion against each other while in physical contact. The mechanistic understanding of the microstructural evolution of multi-phase metallic alloys under extreme shear deformation is still in its infancy. Here, we highlight the influence of shear deformation on the microstructural hierarchy and mechanical properties of a binary as-cast Al-4 at.% Si alloy. Shear-deformation-induced grain refinement, multiscale fragmentation of the eutectic Si-lamellae, and metastable solute saturated phases with distinctive defect structures led to a two-fold increase in the flow stresses determined by micropillar compression testing. These results highlight that shear deformation can achieve non-equilibrium microstructures with enhanced mechanical properties in Al–Si alloys. The experimental and computational insights obtained here are especially crucial for developing predictive models for microstructural evolution of metals under extreme shear deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Correlating energy density induced residual stress, porosity, and mechanical property variations in directed energy deposition using neutron diffraction and imaging techniques

In a directed energy deposition (DED) process, the energy density deposited into the materials drives the structure and properties. The energy density is influenced by several printing parameters, such as laser power, hatch spacing, scanning speed, etc. In this study, 316L stainless steels samples were fabricated with varying hatch spacing aiming to induce variations in sample microstructure and properties. A combination of techniques including engineering neutron diffraction, neutron computed tomography, and tensile testing, were employed to correlate the structure and macroscopic properties. Porosity was predominantly observed at the bottom of the deposited materials and was effectively reduced by decreased hatch spacing. Correlatively, compressive residual stress was observed at the bottom of the specimens, while internal stress is largely determined by the hatch spacing. The residual stress in general decreases as the hatch spacing decreases. The maximum ultimate tensile strength (UTS) was found to increase from 517.4 to 528.6 MPa with a strain increased from 0.847 to 0.897 as the hatch spacing decreased from 0.45 to 0.42 mm. However, further increase in energy density by reducing the hatch spacing resulted in a significant decrease in UTS (as low as 452 MPa). This work provides new insights from bulk non-destructive techniques into correlating energy density induced residual stress, porosity, and mechanical property variations in directed energy deposition.

316L stainless steel↗
DOE OSTI2025

Aldehyde cool-flame chemistry explains a missing source of organic acids

Combustion emission is a significant source of organic acids, impacting atmospheric chemistry and climate. Their formation mechanisms, however, remain poorly understood, leading to underestimation in kinetic models. We investigate the cool-flame oxidation of key combustion intermediates—C 1 –C 4 aldehydes and benzaldehyde. Using in-situ synchrotron vacuum ultraviolet photoionization mass spectrometry, we observe the direct conversion of aldehydes to organic acids, a process enhanced by HO 2 radicals. Quantum chemistry calculations reveal that the reaction of RC(O)O 2 with HO 2 on the singlet potential energy surface contributes to organic acids. Incorporating this pathway into a kinetic model significantly improves organic acid prediction. Despite the high-temperature nature of engine combustion, significant spatial and temporal inhomogeneities (e.g., near-wall regions and crevice volumes) lead to localized cool-flame conditions, facilitating organic acid formation and emission. Elucidating the acid formation under cool-flame conditions provides a critical mechanism for accurately modelling anthropogenic organic acid emissions and developing mitigation strategies.

SVUV-PIMS↗
DOE OSTI2020

Anomalous Auger Recombination in PbSe

Using first-principles approaches we find that the Auger recombination in PbSe is anomalous in three distinct ways. First, the direct Auger coefficient is 4 orders of magnitude lower than that of other semiconductors with similar band gaps, a result that can be attributed to the lack of involvement of a heavy-hole band. Second, phonon-assisted indirect Auger recombination prevails, contrary to the common belief that direct Auger is dominant in narrow-gap semiconductors. Third, an unexpectedly weak temperature dependence of the Auger coefficient is observed, which we can now attribute to the indirect nature of the Auger process. The widely accepted explanation of this behavior in terms of an unusual temperature dependence of the band gap is only a secondary effect. Furthermore, our results elucidate the mechanisms underlying the anomalous Auger recombination in IV-VI semiconductors in general, which is critical for understanding and engineering carrier transport.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Computational design of high-entropy rare earth aluminum garnets for advanced thermal and environmental barrier coatings

To enhance the protection of Ni-based superalloys in gas turbine engines’ high-temperature environments, it’s crucial to develop advanced thermal/environmental barrier coating (T/EBC) materials with a balanced combination of thermal and mechanical properties. This optimization is essential to safeguard against chemical and thermal challenges. Here, in this study, we harness the power of density functional theory (DFT) in conjunction with combinatorial chemistry methodologies to engineer high-performance high-entropy rare earth disilicates of the RE 3 Al 5 O 12 family (where RE denotes Y, Gd, Er, and Yb). These materials are meticulously designed to exhibit superior phase stability, a targeted coefficient of thermal expansion (CTE), low lattice thermal conductivity, and robust mechanical properties. The determination of CTE values is accomplished through phonon calculations at various volume settings within the quasi-harmonic approximation, while lattice thermal conductivities are rigorously assessed employing the Debye-Callaway model, accounting for three distinct phonon processes. Our findings highlight the remarkable attributes of the solid solution (Y 1/4 Gd 1/4 Er 1/4 Yb 1/4 ) 3 Al 5 O 12 , which displays a reduction in lattice thermal conductivity compared to its individual constituents while maintaining a favorable range of CTE values. The novel T/EBC material, distinguished by their multifaceted functionalities, are poised to use in substantial enhancements in the performance of engines.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sustainable conversion of biomass to rationally designed lithium-ion battery graphite

The carbon net negative conversion of bio-char, the low value byproduct of pyrolysis bio-oil production from biomass, to high value, very high purity, highly crystalline flake graphite agglomerates with rationally designed shape and size tailored for lithium-ion battery energy storage material is reported. The process is highly efficient, 0.41 g/Wh; the energy content of its co-product of the process, bio-oil, exceeds that needed to power the process. It is shown that the shape of the starting material is retained during the transformation, allowing the ultimate morphology of the graphite agglomerates to be engineered from relatively malleable biomass. In contrast to commercial graphite production, the process can be performed at small scale with low equipment costs, enabling individual research laboratories to produce Li-ion grade graphite with customizable shape, size and porosity for Si/graphite composite and other graphite involved anodes. The mechanism of the graphitization of bio-char, a “non-graphitizable” carbon, is explored, suggesting the molten metal catalyst is absorbed into the pore structure, transported through and transforming the largely immobile biochar. Finally, the transformation of biomass to rationally designed graphite morphologies with Li-ion anode performance that closely mimic commercial shaped graphite is demonstrated.

09 BIOMASS FUELS↗
DOE OSTI2024

Capabilities Development at the University of Texas at El Paso for Hydrogen Generation Research and Education

Gasification-based systems have recently received much attention due to their capability of converting wastes into useful fuels. The gasification of biomass, municipal solid waste (MSW), plastics, and other sustainable resources has shown promise in hydrogen production. When coupled to a CCU or CCS unit, these systems have the potential to achieve carbon neutrality or carbon-negative emissions. In addition, these systems have an edge over conventional incineration or landfill systems by reducing greenhouse gas emissions and recovering useful energy. However, the gasification of MSW and other wastes is still in its early stages. In particular, co-gasification of wastes with biomass has significant unknowns in optimizing the reaction kinetics, operability, design and performance improvements. Currently, Supercritical Water Gasifiers (SCWG) and Plasma Gasifiers are the major systems that are capable of producing high hydrogen amounts from Biomass and MSW, respectively. However, both systems have high capital and operating costs, adversely affecting efficiency and the hydrogen production cost. Additionally, due to lower temperatures, SCWGs are prone to tar formation and fouling in the heat exchangers. Hence, there is a need to look for alternative solutions for MSW and biomass gasifications, particularly in co-gasification. The current effort aims to develop a strategic plan to establish a sustainable gasification facility for hydrogen research at the University of Texas at El (UTEP). A major part of this effort involves an extensive literature survey to identify technological gaps and potential areas of interest. Several concepts were developed in accordance with the current demands from the literature survey. Based on the concepts, a center-wide capability assessment was conducted to measure the current capacity and feasibility of establishing hydrogen research. Afterward, a strategic research plan was developed, and a list of required resources was made for the expansion of hydrogen research at UTEP. In addition, successful partnerships with the local county and the city were developed to pursue hydrogen research. The strategic goal setting and planning of UTEP Aerospace Center resulted in securing $2.5 million in external support to expand the hydrogen research during the project performance period. In addition, during the project period, a course in Hydrogen Energy Systems was developed to expand the energy curriculum at the UTEP Aerospace and Mechanical Engineering Department. The course focused on hydrogen production, storage, supply and delivery and application. The cross-listed course was offered at both undergraduate and graduate levels during the Spring 2024 semester and had 27 enrolled students. Moreover, the students supported under this award were trained in gasification process modeling, CAD, CFD and FEA during the project period. The training enabled the students to move into new projects to support gasification design, integrated gasification combined cycle process plant analysis, gasifier structural and operational analysis, and digitally threading the systems.

08 HYDROGEN↗
DOE OSTI2024

Development of a Novel DIW-PuSL Printer: The xPuSL Project

During my internship at Lawrence Livermore National Laboratory, I contributed to the xPuSL project. The xPuSL project aimed to revolutionize multi-material 3D printing by combining DIW and PuSL techniques to produce complex geometries with functional materials. My role encompassed process engineering, control systems, experimentation, and CAD design, leading to a streamlined workflow from CAD models to xPuSL prints.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Low-Cost, Scalable Sorbents with Balanced Capacity-Kinetics-Thermodynamics for H2 Storage

The goal of this project is to utilize cutting-edge materials science, chemistry, and process engineering to demonstrate the feasibility of a new class of scalable sorbents with unprecedented balance of capacity-kinetics-thermodynamics for H 2 storage in fossil fuel power plants . The core fabrication leverages the unique exotic properties (e.g., high H 2 affinity, ultrahigh surface area, and exceptional thermal, mechanical and chemical stability) of the emerging 2D materials i.e. hexagonal boron nitride (hBN) followed by strategic coupling with alkali metals (Li, Na) dopants and optimal interlayer distance to deliver a stable, long-term energy storage for the grid. Figure 1 shows how this technology works.

08 HYDROGEN↗