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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 55 records · Page 3

A lightweight and metal-free current collector for battery anode applications

The requirement for high energy density batteries is driving the development of high-capacity electrode materials while reducing the amount of inactive battery components such as separators, binders, and current collectors. Though current collectors are an inactive component, they are still required for successful working of a battery cell. Conventional current collectors include aluminum foil for cathode and copper foil for anode. Copper foil is quite heavy (8.7 mg/cm 2 ) for 10μm thickness. Therefore, there is a need for a lightweight current collector for anode applications. In this work, a metal-free current collector comprised of aligned carbon fiber (CFs) layer filled with carbon nanotubes (CNTs) mixed in polymer (P) is developed to be used as a current collector for anodes. Further, anodes coated on the CF-CNT-P showed lower charge transfer resistance and improved rate capability compared with the anodes fabricated on conventional copper foil-based current collectors. The CF-CNT-P are lighter (≈1.5 mg/cm 2 ) than the commonly used copper foil (8.7 mg/cm 2 ), which will increase the gravimetric energy density.

25 ENERGY STORAGE↗

Thermal shock resistance of lightweight cements developed for geothermal conditions

Cements are a critical component in well construction, as they act to prevent well fluid and gas escape, prevent corrosion of the casing, and strengthen the wellbore to prevent deformation. Under the high temperature/pressure conditions common in geothermal systems, the injection of cold water for energy production is expected to induce cyclic damage to the borehole cement through the rapid temperature fluctuations. These “thermal shocks” are expected to cause casing shrinkage, annulus formation, and cement tensile stresses. To understand the effect of cold water injection on the wellbore environment, a set of rock-cement-steel samples were created to simulate the structure of a geothermal well. Lightweight thermally-insulating cement blends were tested under thermal shock conditions in this study. In each test, the samples were pressurized to an effective pressure of ~3.5 MPa and placed at high temperatures. Thermal shocks were performed by injecting cold water (~10-15 °C) through the samples at a constant rate while keeping the samples at high temperatures until the sample temperature stopped decreasing and deformation ceased. Eight thermal shock tests were conducted with each sample – two at 100 °C and six at 200 °C. Post-tests analysis was then conducted by cutting open each sample to examine the damage in each component of the simulated wellbore. Experimental results suggest that all samples experienced similar degrees of axial and lateral contraction during cold water injection, but for the most part this contraction is recoverable when injection halts. Post-test analysis revealed that fly ash cenosphere pre-treatment had the best effect on improving thermal shock resistance in the cement blends. Thermomechanical modeling of likely stress paths experienced by the cements during heating/cooling cycles shows that elasto-plastic cement constitutive behavior results in most plastic strain occurring during the initial heating steps, with mostly elastic strain occurring during the thermal shock cycles. In conclusion, this agrees with experimental evidence, suggesting that cement damage from shocking occurs via other mechanisms such as chemical alteration, corrosion, and fatigue.

36 MATERIALS SCIENCE↗

A lightweight Fe–Mn–Al–C austenitic steel with ultra-high strength and ductility fabricated via laser powder bed fusion

Lightweight Fe–Mn–Al–C steels have become a topic of significant interest for the defense and automotive industries. These alloys can maintain high strength and ductility while also reducing weight in structural applications. Conventionally processed Fe–Mn–Al–C austenitic steels with high Al content (~9 wt%) demonstrate greater than 1.5 GPa strength with 35% elongation. Several recent studies have demonstrated success in fabricating steel parts using laser powder bed fusion (L-PBF) additive manufacturing (AM), which can generate near-net-shape components with complex geometries and is capable of local microstructural control. However, studies on L-PBF processing of Fe–Mn–Al–C alloys have focused on low Al content (<5 wt%) compositional regimes representing alloys that undergo transformation-induced plasticity (TRIP) and twinning-induced plasticity (TWIP). Here, in this study, we present the effects of L-PBF processing on the microstructure and mechanical properties of an Fe–30Mn–9Al–1Si-0.5Mo-0.9C austenitic steel. A process optimization framework is employed to determine an ideal L-PBF processing space that will result in >99% density parts. Implementing this framework resulted in near-fully dense specimens fabricated over a broad range of process parameters. Additionally, two bi-directional scan rotation strategies (90° and 67°) were applied to understand their effects on texture and anisotropy in this material. As-printed specimens displayed considerable work-hardening characteristics with average strengths of up to 1.3 GPa and 36% elongation in the build direction. However, solidification microcracks oriented in the build direction resulted in anisotropy in tensile strength and ductility resulting in average strengths of 1.1 GPa and 20% elongation perpendicular to the build direction. The successful L-PBF fabrication of Fe–30Mn–9Al–1Si-0.5Mo-0.9C presented here is expected to open new avenues for weight reduction in structural applications with a high degree of control over part topology.

36 MATERIALS SCIENCE↗

Stiff and strong, lightweight bi-material sandwich plate-lattices with enhanced energy absorption

Plate-based lattices are predicted to reach theoretical Hashin–Shtrikman and Suquet upper bounds on stiffness and strength. However, simultaneously attaining high energy absorption in these plate-lattices still remains elusive, which is critical for many structural applications such as shock wave absorber and protective devices. In this article, we present bi-material isotropic cubic + octet sandwich plate-lattices composed of carbon fiber-reinforced polymer (stiff) skins and elastomeric (soft) core. This bi-material configuration enhances their energy absorption capability while retaining stretching-dominated behavior. We investigate their mechanical properties through an analytical model and finite element simulations. Our results show that they achieve enhanced energy absorption approximately 2–2.8 times higher than their homogeneous counterparts while marginally compromising their stiffness and strength. When compared to previously reported materials, these materials achieve superior strength-energy absorption characteristics, making them an excellent candidate for stiff and strong, lightweight energy absorbing applications.

36 MATERIALS SCIENCE↗

Advanced Lightweight HiE PMDD Generator for WTGs

Preliminary designs of advanced lightweight permanent magnet direct drive generators for offshore and “tall wind” onshore applications utilizing funding from DOE/EERE/WETO were developed by WEG, RTX, NREL and supporting partners. This work significantly reduces tower head mass, increases efficiency, reduces the rare earth content of the generator, and leads to additional turbine system benefits that improve competitiveness, such as the use of taller towers onshore and less expensive foundations (“hull”) for floating offshore. The end result is an approximately 10% reduction of LCOE in both cases, which could significantly improve competitiveness and support the EERE/DOE goal of promoting US manufacturing.

17 WIND ENERGY↗

Functionally Designed Ultra-Lightweight Carbon Fiber Reinforced Thermoplastic Composites Door Assembly (Final Scientific/Technical Report)

This is the final technical report for a project that developed an ultra-lightweight carbon fiber reinforced thermoplastics composite door assembly for a mid-size SUV. The project was able achieve a weight reduction of at least 42.5% while maintaining or exceeding the fit, function, safety, stiffness, and crash performance requirements of the current baseline door. Additionally, the target cost was set at less than $5 per pound of weight saved. To accomplish these goals, the project team employed a systems approach that involves redesigning the door assembly, exploring novel materials, optimizing the design, and utilizing advanced manufacturing technologies.

42 ENGINEERING↗

Predictor-corrector models for lightweight massive machine-type communications in Industry 4.0

Future Industry 4.0 scenarios are characterized by seamless integration between computational and physical processes. To achieve this objective, dense platforms made of small sensing nodes and other resource constraint devices are ubiquitously deployed. All these devices have a limited number of computational resources, just enough to perform the simple operation they are in charge of. The remaining operations are delegated to powerful gateways that manage sensing nodes, but resources are never unlimited, and as more and more devices are deployed on Industry 4.0 platforms, gateways present more problems to handle massive machine-type communications. Although the problems are diverse, those related to security are especially critical. To enable sensing nodes to establish secure communications, several semiconductor companies are currently promoting a new generation of devices based on Physical Unclonable Functions, whose usage grows every year in many real industrial scenarios. Those hardware devices do not consume any computational resource but force the gateway to keep large key-value catalogues for each individual node. In this context, memory usage is not scalable and processing delays increase exponentially with each new node on the platform. In this paper, we address this challenge through predictor-corrector models, representing the key-value catalogues. Models are mathematically complex, but we argue that they consume less computational resources than current approaches. The lightweight models are based on complex functions managed as Laurent series, cubic spline interpolations, and Boolean functions also developed as series. Unknown parameters in these models are predicted, and eventually corrected to calculate the output value for each given key. The initial parameters are based on the Kane Yee formula. An experimental analysis and a performance evaluation are provided in the experimental section, showing that the proposed approach causes a significant reduction in the resource consumption.

97 MATHEMATICS AND COMPUTING↗

Hydrophobic Lightweight Cement with Thermal Shock Resistance and Thermal Insulating Properties for Energy-Storage Geothermal Well Systems

This study assessed the possibility of using polymethylhydrosiloxane (PMHS)-treated fly ash cenospheres (FCS) for formulating a thermally insulating and thermal shock (TS)-resistant cementitious blend with calcium aluminate cement. To prevent FCS degradation in an alkaline cement environment at high temperatures, the cenospheres were pre-treated with sodium metasilicate to form silanol and aluminol groups on their surface. These groups participated in a dehydrogenation reaction with the functional ≡Si–H groups within PMHS with the formation of siloxane oxygen-linked M-FCS (M: Al or Si). At high hydrothermal temperatures of 175 and 250 °C, some Si–O–Si and SiCH 3 bonds ruptured, causing depolymerization of the polymer at the FCS surface and hydroxylation of the raptured sites with the formation of silanol groups. Repolymerization through self-condensation between the silanol groups followed, resulting in the transformation of siloxane to low crosslinked silicon-like polymer as a repolymerization-induced product (RIP) without carbon. The RIP provided adequate protection of FCS from pozzolanic reactions (PR), which was confirmed by the decline in zeolites as the products of PR of FCS. Cements with PMHS-treated FCS withstood both hydrothermal and thermal temperature of 250 °C in TS tests, and they also showed improved compressive strength, toughness, and water repellency as well as decreased thermal conductivity. The lubricating properties of PMHS increased the fluidity of lightweight slurries.

15 GEOTHERMAL ENERGY↗

Macroscale Fabrication of Lightweight and Strong Porous Carbon Foams through Template-Coating Pair Design

Manufacturing of low-density-high-strength carbon foams can benefit the construction, transportation, and packaging industries. One successful route to lightweight and mechanically strong carbon foams involves pyrolysis of polymeric architectures, which is inevitably accompanied by drastic volumetric shrinkage (usually >98%). As such, a challenge of these materials lies in maintaining bulk dimensions of building struts that span orders of magnitude difference in length scale from centimeters to nanometers. Here, this work demonstrates fabrication of macroscale low-density-high-strength carbon foams that feature exceptional dimensional stability through pyrolysis of robust template-coating pairs. The template serves as the architectural blueprint and contains strength-imparting properties (e.g., high node density and small strut dimensions); it is composed of a low char-yielding porous polystyrene backbone with a high carbonization-onset temperature. The coating serves to imprint and transcribe the template architecture into pyrolytic carbon; it is composed of a high char-yielding conjugated polymer with a relatively low carbonization-onset temperature. The designed carbonization mismatch enables structural inheritance, while the decomposition mismatch affords hollow struts, minimizing density. The carbons synthesized through this new framework exhibit remarkable dimensional stability (≈80% dimension retention; ≈50% volume retention) and some of the highest specific strengths (≈0.13 GPa g -1 cm 3 ) among reported carbon foams derived from porous polymer templates.

36 MATERIALS SCIENCE↗

Lightweight Software Process Improvement Using Productivity and Sustainability Improvement Planning (PSIP)

Productivity and Sustainability Improvement Planning (PSIP) is a lightweight, iterative workflow that allows software development teams to identify development bottlenecks and track progress to overcome them. In this paper, we present an overview of PSIP and how it compares to other software process improvement (SPI) methodologies, and provide two case studies that describe how the use of PSIP led to successful improvements in team effectiveness and efficiency.

Heroux, Michael A.↗

Smart manufacturing approach to manufacture bulk nanocrystalline aluminum for lightweight applications

In this research, a smart manufacturing approach was used to enhance the mechanical properties of aluminum (Al) for lightweight applications. The smart manufacturing involved cryomilling of Al powders with and without 5 wt.% magnesium (Mg) powders for varying durations followed by a high-pressure cold spray (HPCS) additive manufacturing process to prepare bulk components. The morphological changes, crystallite size, and composition of the cryomilled powders and cold sprayed (CS’ed) components were examined using scanning electron microscopy (SEM), x-ray diffraction (XRD), and transmission electron microscopy (TEM) techniques. The results showed that the crystallite size reduces with an increase in cryomilling time and the addition of Mg dopant. To test the mechanical properties of the bulk CS’ed components, microhardness tests were performed using a Vickers microhardness tester. Uniaxial tensile tests were also carried out to ascertain the material’s tensile properties. The mechanical testing results showed great improvement in the hardness and tensile strength of CS’ed Al–Mg samples as compared to pure Al samples. Subsequently, fractography analysis of the tensile failed samples was carried out to determine the nature of the failure. Here, the research article also discusses the inherent mechanisms for the improvement in mechanical properties of smart manufactured components as a result of Mg doping and cryomilling.

36 MATERIALS SCIENCE↗

Doping Effects on the Ductility of a Lightweight Refractory High-Entropy Alloy: Grain Boundary and Bulk Lattice Aspects

Doping elements in small amounts often segregate to grain boundaries (GBs) in alloys and can significantly impact mechanical properties and performance. Refractory high-entropy alloys (RHEAs) are known for their poor ductility, especially at low temperatures. Promoting GB cohesion through segregation can be an effective approach to mitigate embrittlement. Here, in this study, first-principles density functional theory (DFT) calculations were performed to examine the effects of important interstitial dopants (O, B, C, and N) and substitutional dopants (Cr, Y, La, and Ce) on the Σ5(310) [001] tilt GB of a lightweight RHEA Nb 32.5 Ti 27.5 Mo 22.5 Ta 12.5 Hf 2.5 Zr 2.5 . The DFT calculations reveal that certain dopants, such as B, C, Cr, N, and Y, exhibit favorable GB strengthening effects by improving bonding interactions with the bulk alloy. The impact of doping on the ductility parameter of the bulk lattice, defined as the ratio of surface energy to unstable stacking fault energy for the {110} <111> slip system, was also studied; and the results show that doping reduces the intrinsic ductility of the alloy, decreasing the D-parameter from 2.90 to 2.55, depending on the specific dopant. The present findings provide a foundational understanding at atomic level of the effect of representative dopants on mechanical properties of RHEAs and can be used to guide future alloy design for improved mechanical properties.

deformation charge density↗

Parametric and sensitivity analysis of a PCM-integrated wall for optimal thermal load modulation in lightweight buildings

Load modulation in buildings is becoming increasingly important due to growing disparity in energy demand during peak and off-peak hours. Integrating phase change material (PCM) in building envelopes and using a controlled precooling strategy can provide substantial thermal load modulation; however, it may greatly increase the total energy use. Previous studies have employed PCM in building envelopes primarily for energy savings and, to some extent, peak load shedding and shifting. However, the load modulation capacity of a PCM-integrated envelope has not been well explored in the literature. In this study, we perform an extensive parametric and sensitivity analysis on PCM-integrated lightweight building walls and examine the combinatory effects of various PCM parameters on thermal load modulation and wall-related heat gains in buildings. Using numerical simulations, we investigate eight PCM parameters: PCM location in the wall, transition temperature, thickness, latent heat, transition range, density, specific heat, and thermal conductivity. Here, we evaluate their impact and relative importance to achieve maximum load modulation in buildings without compromising occupants’ thermal comfort or total energy use. The results show that the optimized PCM proposed in this study can completely invert the transient heat gain profile of the wall, providing up to 70% reduction of wall-related heat gain during peak hours without a major increase in the cumulative heat gain.

42 ENGINEERING↗

A deep learning and finite element approach for exploration of inverse structure–property designs of lightweight hybrid composites

Hybrid composites have important applications, such as high-performance and lightweight materials in aerospace and automotive industries. Hybrid composites utilize the synergy of diverse fillers to achieve desired material properties, but usually have more complicated microstructures. While topology optimization can optimize a particular property, designing hybrid composites for customized mechanical performances, e.g. full-range stress–strain curve, remains challenging. Here, a computational framework that integrated finite element analysis (FEA) and artificial intelligence (AI) methods of Conditional Generative Adversarial Networks (cGAN) deep learning and transfer learning was developed to establish inverse structure–property relationships and design tailor-made hybrid composites. Based on FEA-generated datasets of hybrid fiber-particle–matrix microstructures and their corresponding full-range stress–strain curves, a cGAN architecture was trained to generate tailored microstructures and establish structure–property relationships. Similarity in microstructural features and well-matched stress–strain curves based on the AI-generated composites were achieved. In conclusion, transfer learning was used to expand the pre-trained model for designing different materials systems.

Hybrid composites↗

A lightweight method for evaluating in situ workflow efficiency

Performance evaluation is crucial to understanding the behavior of scientific workflows. In this study, we target an emerging type of workflow, called in situ workflows. These workflows tightly couple components such as simulation and analysis to improve overall workflow performance. To understand the tradeoffs of various configurable parameters for coupling these heterogeneous tasks, namely simulation stride, and component placement, separately monitoring each component is insufficient to gain insights into the entire workflow behavior. Through an analysis of the state-of-the-art research, we propose a lightweight metric, derived from a defined in situ step, for assessing resource usage efficiency of an in situ workflow execution. By applying this metric to a synthetic workflow, which is parameterized to emulate behaviors of a molecular dynamics simulation, we explore two possible scenarios (Idle Simulation and Idle Analyzer) for the characterization of in situ workflow execution. In addition to preliminary results from a recently published study [11], we further exploit the proposed metric to evaluate a practical in situ workflow with a real molecular dynamics application, i.e., GROMACS. Here, experimental results show that the in transit placement (analytics on dedicated nodes) sustains a higher frequency for performing in situ analysis compared to the helper-core configuration (analytics co-allocated with simulation).

97 MATHEMATICS AND COMPUTING↗

Silicon Dioxide Deposited Using Atmospheric Pressure Plasma Chemical Vapor Deposition for Improved Adhesion and Water Intrusion Resistance for Lightweight Manufacturing

This work aims to demonstrate the barrier coating, and adhesion promoting properties of silica-based coatings deposited using an atmospheric pressure plasma torch (APPT). This is achieved by applying an industrial grade adhesive to silica thin films deposited, on the surfaces to be joined, using atmospheric pressure plasma chemical vapor deposition (APP-CVD), to make single joint lap shear samples of different metal combinations commonly found in lightweight manufacturing such as aluminum and magnesium as well as steel. To deposit these thin films, two separate silicon based organic precursors, hexamethyldisiloxane (HMDSO), and tetraehylorthosilicate (TEOS), are used. Here, samples are bonded using DuPont Betamate 1486 adhesive, and the lap shear results for these films are compared to the lap shear results of a chemically cleaned control using the same adhesive. The APPT uses a microwave power supply and gas mixtures of N 2 and Ar. The adhesion of the films are tested using lap shear, and elevated temperature water soaks are conducted on the joints as well to simulate environmental exposure. Lap shear results from samples with silica thin films max shear stress are 25%-115% increase compared to control samples depending on material. After exposure to water soak the max shear strength of the joints decreased by less than 15%, which demonstrates the films capabilities as a water barrier. Film morphology is examined using Scanning Electron Microscopy (SEM), and the film’s composition and approximate thickness are obtained using Rutherford Backscattering Spectroscopy (RBS).

36 MATERIALS SCIENCE↗

High-strength, lightweight nano-architected silica

Continuous nanolattices are an emerging class of mechanical metamaterials that are highly attractive due to their superior strength-to-weight ratios, which originate from their spatial architectures and nanoscale-sized elements possessing near-theoretical strength. Rational design of frameworks remains challenging below 50 nm because of limited methods to arrange small elements into complex architectures. Here, we fabricate silica frameworks with ~4- to 20-nm-thick elements using self-assembly and silica templating of DNA origami nanolattices and perform in situ micro-compression testing to examine the mechanical properties. We observe strong effects of lattice dimensions on yield strength (σ $\mathcal{y}$ ) and failure mode. Silica nanolattices are found to exhibit yield strengths higher than those of any known engineering materials with similar mass density. The robust coordination of the nanothin and strong silica elements leads to the combination of lightweight and high-strength framework materials offering an effective strategy for the fabrication of nanoarchitected materials with superior mechanical properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

PET-FBA: A lightweight enzyme allocation and thermodynamics-constrained flux analysis approach to explore Escherichia coli metabolic adaptation to intracellular acidification

Escherichia coli employs diverse strategies to adapt to acidic environments that disrupt enzyme activity and the thermodynamic feasibility of essential reactions. To understand the impact of pH stress on cell metabolism, we present the PET-FBA (pH-, Enzyme protein allocation-, and Thermodynamics-constrained Flux Balance Analysis) framework. PET-FBA extends genome-scale modeling by integrating enzyme protein costs and reaction Gibbs free energy changes. Additionally, by incorporating pH-dependent enzyme kinetics in response to intracellular acidification, this framework enables the simulation of E. coli's metabolic adjustments across varying external pH levels. The model's accuracy is validated by comparing in silico growth simulations with experimental measurements under both anaerobic and aerobic conditions, as well as in silico gene knockouts of essential genes. By explicitly incorporating pH effects, our model accurately replicates the metabolic shift towards lactate production as the primary fermentation product at low pH in anaerobic conditions. This shift is only predicted when enzyme kinetics are dynamically adjusted as a function of pH. Further analysis revealed that this shift can be attributed to the reduced protein efficiency of the acetyl-CoA branch compared to lactate dehydrogenase under acidic stress, which then becomes crucial for maintaining NAD regeneration and cell growth at low pH. Furthermore, we identified strategies for enhancing cell growth under acidic anaerobic conditions by improving the enzyme activity of lactate dehydrogenase and pyruvate formate lyase, which increases NAD production efficiency and reduces enzyme protein allocation costs. Designed as a lightweight yet versatile framework, PET-FBA enables efficient genome-scale metabolic analysis. Using E. coli as a model system, our framework provides a systematic approach to understanding metabolic responses to environmental stress, pinpointing key metabolic bottlenecks, and identifying potential targets for strain optimization.

42 ENGINEERING↗