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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A highly stable Cu(OH) 2 -Poly(vinyl alcohol) nanocomposite membrane for dramatically enhanced direct borohydride fuel cell performance

Nano-additive aggregation, limited performance, and unclear modification mechanisms are the main obstacles in developing nanocomposite anion exchange membranes (AEMs). In this work, for the first time, an effective and highly stable Poly(vinyl alcohol) (PVA)-based AEMs with dispersive Cu(OH)$_2$ nanoclusters (Cu-AEMs) are prepared by a simple and eco-friendly three-step method: ‘CuCl$_2$ doping-casting-KOH immersing’. The doped Cu$^{2+}$ ions chemically combine with OH- ions to form anionic conductive Cu(OH)2 nanoclusters intermediated by attaching resins. The PVA skeletons wrap around Cu(OH)$_2$ while the hydroxyl groups expose to bulk water, forming Cu(OH)$_2$-PVA complex, which avoids nano-additive aggregation, increases anionic channels, and strengthens additive-matrix connection. A direct borohydride fuel cell using Cu-AEM with 0.56 wt % CuCl$_2$ possess the highest power density of 403.3 mW cm$^{-2}$ at 60 °C and a life span of over 200 h. The high-performance and durability come from the unique structure of Cu(OH)$_2$ nanoclusters-PVA complex. ‘Vehicle’ theory is considered to be the dominant mechanism for enhancing such nanocomposite Cu-AEMs. This work demonstrates a new concept for preparing the stable AEMs toward high-performance fuel cells. The synthetic chemistry involved can be broadly extended for fabricating versatile AEMs.

25 ENERGY STORAGE↗
DOE OSTI2020

Modulating electrode utilization in lithium-ion cells with silicon-bearing anodes

The stability of silicon-containing anodes can, in principle, be extended by constraining these electrodes to limited states of lithiation. Partial utilization of the anode lessens the volume changes experienced by silicon particles during cycling, which can mitigate mechanisms of performance degradation. In full-cells, anode utilization can be modulated by adjusting the relative capacities of the negative and positive electrodes - the N/P ratio. Here, we examine how the N/P ratio affects the long-term stability of Si-based full-cells, and investigate how this parameter would impact the cost and energy of realistic Li-ion cells. Here, we show that, for some configurations, cell failure due to rapid anode degradation can only by avoided at higher N/P ratios. The price of this enhanced stability is accelerated impedance rise at the cathode. Surprisingly, when electrode expansion is taken into account, increasing N/P ratio can actually increase the specific energy and energy density of silicon-rich Li-ion cells.

25 ENERGY STORAGE↗
DOE OSTI2022

A three-dimensional pore-scale model for redox flow battery electrode design analysis

A three-dimensional (3-D) pore-scale model has been developed to construct multiscale fibrous electrodes for redox flow batteries (RFB). New designs, such as biporous electrodes modify electrode structures by creating secondary pores on single carbon fiber to reduce internal battery resistance. Existing pore-scale models only resolve electrodes to the single carbon fiber scale and cannot incorporate recent multiscale electrode designs into numerical models. Our new model aims to bridge this gap and provide a tool to rapidly screen new electrode configurations. Two multiscale electrodes, laser-perforated and biporous electrodes, were investigated at varying operation conditions with the proposed 3-D pore-scale models. The laser-perforated electrode exhibits a reduced pressure drop, but follows the same permeability correlation compared to the corresponding pristine electrode. For the biporous electrode, the added specific surface area and faster reaction kinetics from the secondary pores are the most influential factors leading to improved battery efficiency. However, operating the biporous electrode in limiting current density conditions should be avoided due to the decreased mass transfer efficiency and a more significant voltage loss. Finally, we believe that our 3-D pore-scale model can accelerate the flow battery electrode design process and provide new insights into electrode geometry optimizations.

25 ENERGY STORAGE↗
DOE OSTI2023

Ethanol-fueled metal supported solid oxide fuel cells with a high entropy alloy internal reforming catalyst

High-performance metal supported solid oxide fuel cells (MS-SOFC) with an integrated high entropy alloy (HEA) internal reforming catalyst (IRC) are demonstrated for transportation applications using ethanol and methanol as fuels. Addition of the HEA IRC dramatically improves cell performance and stability when using ethanol/water blend fuel. Absence of carbon deposition predicted by thermodynamic calculations is confirmed by Raman spectroscopy analysis of posttest anodes. Optimal catalyst processing (deposition technique, loading, firing temperature) and cell operation conditions (flow rates, temperature, fuel compositions) are explored. Infiltrated HEA reforming catalyst provides a highly porous structure and low catalyst loading (6 mg cm –2 ). The designed structure and catalysts achieve small mass transport resistances in the fuel electrode (26.2 s m –1 ) and oxygen electrode (41.6 s m –1 ). The best ethanol concentration (60:40 v% ethanol: water) provides 0.83 W cm –1 at 700 °C, without carbon deposition. The ethanol-fueled MS-SOFC is operated for 500 h, including five thermal cycles. As a result, cell evolution is similar to that reported previously for hydrogen fuel; nickel aggregation and chromia deposition were the major observed changes, and carbon formation can be avoided even after long-term operation.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

High performance porous Si anode enabled by an organic-solvent assisted etching process

Silicon (Si) is a promising anode for the next generation of lithium-ion batteries, but its large volume changes (~300 %) during cycling hindered its practical applications. One method to improve its stability is to etch micron sized Si/SiO 2 particles to form porous Si (p-Si) and accommodate volume changes internally. However, the conventional HF etching method generates excess gas/heat and is difficult to scale up. Herein, we developed an organic-solvent-assisted HF etching process (O-HF) using a mixture of benzene and saturated HF aqueous solution. The organic solvent can be preferentially absorbed on the surface of Si/SiO 2 powder so etching rate of SiO 2 can be controlled to avoid rapid gas/heat generation. This method can also prevent over-etching of Si by minimizing direct contact/react between water and newly exposed Si. Si||NMC622 cells using carbon coated p-Si particles prepared by optimized O-HF etching process demonstrate a capacity retention of 82.0 % after 500 cycles, which is much better than those prepared by conventional HF etching (73.7 %). The thickness of Si anode increases only ~10 % during the initial lithiation, which is comparable with those of graphite anode. In conclusion, the O-HF etching strategy developed in this work can also be applied to the etching of a broad range of materials.

HF etching↗
DOE OSTI2020

Application of Koopman operator for model-based control of fracture propagation and proppant transport in hydraulic fracturing operation

This work explores the application of the recently developed Koopman operator approach for model identification and feedback control of a hydraulic fracturing process. Controlling fracture propagation and proppant transport with precision is a challenge due in large part to the difficulty of constructing approximate models that accurately capture the characteristic moving boundary and highly-coupled dynamics exhibited by the process. Koopman operator theory is particularly attractive here as it offers a way to explicitly construct linear representations for even highly nonlinear dynamics. The method is data-driven and relies on lifting the states to an infinite-dimensional space of functions called observables where the dynamics are governed by a linear Koopman operator. Here this work considers two problems: (a) fracture geometry control, and (b) proppant concentration control. In both cases, an approximate linear model of the corresponding dynamics is constructed and used to design a model predictive controller (MPC). The manuscript shows that in the case of highly nonlinear dynamics, as observed in the proppant concentration, use of canonical functions in the observable basis fails. In such cases, a priori system knowledge can be leveraged to choose the required basis. The numerical experiments demonstrate that the Koopman linear model shows excellent agreement with the real system and successfully achieves the desired target values maximizing the oil and gas productivity. Additionally, due to its linear structure, the Koopman models allow convex MPC formulations that avoid any issues associated with nonlinear optimization.

42 ENGINEERING↗
DOE OSTI2022

SAFE-OCC: A novelty detection framework for Convolutional Neural Network sensors and its application in process control

Herein we present a novelty detection framework for Convolutional Neural Network (CNN) sensors that we call Sensor-Activated Feature Extraction One-Class Classification (SAFE-OCC). We show that this framework enables the safe use of computer vision sensors in process control architectures. Emergent control applications use CNN models to map visual data to a state signal that can be interpreted by the controller. Incorporating such sensors introduces a significant system operation vulnerability because CNN sensors can exhibit high prediction errors when exposed to novel (abnormal) visual data. Unfortunately, identifying such novelties in real-time is nontrivial. To address this issue, the SAFE-OCC framework leverages the convolutional blocks of the CNN to create an effective feature space to conduct novelty detection using a desired one-class classification technique. This approach engenders a feature space that directly corresponds to that used by the CNN sensor and avoids the need to derive an independent latent space. We demonstrate the effectiveness of SAFE-OCC via simulated control environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Longitudinal proteomics analysis in the immediate microenvironment of islet allografts during progression of rejection

The applicability and benefits of pancreatic islet transplantation are limited due to various issues including the need to avoid immune-mediated rejection. In the present study, we used our experimental platform of allogeneic islet transplant in the anterior chamber of the eye (ACE-platform) to longitudinally monitor the progress of rejection in mice and obtain aqueous humor samples representative of the microenvironment of the graft for accurately-timed proteomic analyses. LC-MS/MS-based proteomics performed on such mass-limited samples (~5 μL) identified a total of 1296 proteins. Various analyses revealed distinct protein patterns associated with the mounting of the inflammatory and immune responses and their evolution with the progression of the rejection. Pathway analyses indicated predominant changes in cytotoxic functions, cell movement, and innate and adaptive immune responses. Furthermore, network prediction analyses revealed transition from humoral to cellular immune response and exacerbation of pro-inflammatory signaling. One of the proteins identified by this localized proteomics as a candidate biomarker of islet rejection, Cystatin 3, was further validated by ELISA in the aqueous humor. This study provides (1) experimental evidence demonstrating the feasibility of longitudinal localized proteomics using small aqueous humor samples and (2) proof-of-concept for the discovery of biomarkers of impending immune attack from the immediate local microenvironment of ACE-transplanted islets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A variance deconvolution estimator for efficient uncertainty quantification in Monte Carlo radiation transport applications

Monte Carlo simulations are at the heart of many high-fidelity simulations and analyses for radiation transport systems. As is the case with any complex computational model, it is important to propagate sources of input uncertainty and characterize how they affect model output. Unfortunately, uncertainty quantification (UQ) is made difficult by the stochastic variability that Monte Carlo transport solvers introduce. The standard method to avoid corrupting the UQ statistics with the transport solver noise is to increase the number of particle histories, resulting in very high computational costs. In this contribution, we propose and analyze a sampling estimator based on the law of total variance to compute UQ variance even in the presence of residual noise from Monte Carlo transport calculations. Here, we rigorously derive the statistical properties of the new variance estimator, compare its performance to that of the standard method, and demonstrate its use on neutral particle transport model problems involving both attenuation and scattering physics. We illustrate, both analytically and numerically, the estimator’s statistical performance as a function of available computational budget and the distribution of that budget between UQ samples and particle histories. We show analytically and corroborate numerically that the new estimator is unbiased, unlike the standard approach, and is more accurate and precise than the standard estimator for the same computational budget.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Impact of organic acids on extraction of rare earth elements: Mechanisms and optimization

Organic acids are increasingly recognized as an environmentally friendly and efficient selective leaching agent of critical minerals. However, their impact on subsequent extraction processes remains unclear. This study investigates the extraction behavior of rare earth elements (REEs), representative of critical minerals, in the presence of various organic acids, including citric acid, maleic acid, malonic acid, DL-malic acid, L(+)-tartaric acid, and L-ascorbic acid. The results show that organic acids slightly reduce the extraction of REEs but greatly increase the extraction of aluminum (Al³⁺), making it harder to separate REEs from other elements. To avoid this, it is best to keep organic acid concentrations as low as possible in practical applications. However, by optimizing extraction conditions, these negative effects can be minimized. Specifically, adjusting the contact time between solutions allows for efficient REE extraction while limiting unwanted aluminum extraction. Among the acids tested, malonic acid and L(+)-tartaric acid were found to be the most effective for selectively extracting REEs. Mechanistically, organic acids are likely to form complexes with REEs and D2EHPA during extraction, except for Y (III), offering practical guidelines for optimizing REE recovery. Beyond extraction, this study also highlights a way to recover organic acids by precipitating REEs from stripping solutions using oxalic acid, which adds both environmental and economic benefits. Furthermore, these findings provide useful insights for optimizing REE recovery and offer a reference for extracting other critical minerals from solutions containing organic acids.

D2EHPA↗
DOE OSTI2022

Metallic support films reduce optical heating in cryogenic correlative light and electron tomography

Super-resolved cryogenic correlative light and electron tomography is an emerging method that provides both the single-molecule sensitivity and specificity of fluorescence imaging, and the molecular scale resolution and detailed cellular context of tomography, all in vitrified cells preserved in their native hydrated state. Technical hurdles that limit these correlative experiments need to be overcome for the full potential of this approach to be realized. Chief among these is sample heating due to optical excitation which leads to devitrification, a phase transition from amorphous to crystalline ice. Here, in this work, we show that much of this heating is due to the material properties of the support film of the electron microscopy grid, specifically the absorptivity and thermal conductivity. We demonstrate through experiment and simulation that the properties of the standard holey carbon electron microscopy grid lead to substantial heating under optical excitation. In order to avoid devitrification, optical excitation intensities must be kept orders of magnitude lower than the intensities commonly employed in room temperature super-resolution experiments. We further show that the use of metallic films, either holey gold grids, or custom made holey silver grids, alleviate much of this heating. For example, the holey silver grids permit 20× the optical intensities used on the standard holey carbon grids. Super-resolution correlative experiments conducted on holey silver grids under these increased optical excitation intensities have a corresponding increase in the rate of single-molecule fluorescence localizations. This results in an increased density of localizations and improved correlative imaging without deleterious effects from sample heating.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Engineering the beat phenomenon of quasi-Rayleigh waves for regions with minimal Surface Acoustic Wave (SAW) amplitude

Surface Acoustic Waves (SAW) are prevalent in a variety of scientific fields. Typically, the ability to manipulate these surface waves has a significant impact on the efficacy of any SAW-based device. In this paper, we present a simple method for designing localized regions that have minimal SAW amplitude. These localized regions have valley-like drops in SAW amplitude and are achieved by using the spatial beat phenomenon of quasi-Rayleigh waves. Controlling the beat phenomenon allows us to manipulate where and how these localized regions appear in the waveguide. In particular, the localized regions can be designed to have variable widths and can be positioned consecutively due to minimal wave scattering. The design methodology and physics are described in detail, and several supplementary simulations are provided to demonstrate the efficacy of the proposed method. Finally, we briefly discuss how the proposed approach could potentially be exploited to implement a localized high-pass filter and enables SAW wave propagation that avoids surface obstacles.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Local modeling for FRF estimation with noisy input measurements

The frequency response function (FRF) is an essential means by which dynamic systems are qualified. In recent years, local modeling approaches have been extensively researched and shown to significantly outperform traditional FRF estimators. However, the standard local modeling approach assumes a perfectly-known system input, which results in biased FRF estimates in the presence of input noise. This paper derives a simple adjustment that can be used to improve FRF estimation for systems subjected to random excitation with noisy input data. This improvement can be implemented with little modification to standard local modeling algorithms and with little additional computational burden. The adjustment is coupled with a model selection procedure to avoid underfitting and overfitting. In conclusion, the methods presented in this paper are validated on a simulation, and they are shown to reduce bias due to input noise.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Large-Eddy Simulation of a wind turbine using a Filtered Actuator Line Model

When dealing with multirotor devices such as quadcopters or wind farms, the cost of blade-resolved large-eddy simulation (LES) becomes prohibitive. Combining LES with a family of lower-fidelity models, called actuator line models (ALMs), has grown in popularity in the past decade. ALM replaces full blade resolution with an array of actuator points or lines parameterized by aerodynamic lift/drag polar plots along the blades. Body forces computed based on these actuator points are then projected onto the LES flow mesh, mimicking the effect of rotating blades on the flow. However, the optimal projection radius and the associated LES grid size is often too restrictive for multirotor simulations. Recently, a new tip-correction-based filtered ALM (F-ALM) was proposed by Martinez-Tossas and Meneveau (2019), which allows coarser-than-optimal grids by avoiding the associated overprediction of thrust. In this work, F-ALM is implemented into a high-order, in-house LES code to simulate National Renewable Energy Laboratory Phase VI wind turbine. It is then followed by a comparison between the baseline ALM and the newly implemented F-ALM in terms of instantaneous and time-averaged flow fields and blade loads, revealing the advantages of F-ALM in preventing the overprediction of power on coarse grids. Finally, this encourages accurate and affordable simulations of multirotor devices in the future.

17 WIND ENERGY↗
DOE OSTI2025

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite↗
DOE OSTI2022

On the high-temperature stability of the Al 8 Cu 3 Ce intermetallic in an additively manufactured Al-Cu-Ce-Zr alloy

High-temperature resistant eutectic Al alloys are crucial materials for lightweight and energy efficient design in the automotive and aviation industries. Additive manufacturing offers a pathway to refine eutectic microstructures and develop novel alloys with superior high-temperature strength. High-volume fraction intermetallic Al-Cu-Ce alloys have been developed to deliver high-temperature strength in combination with reduced hot-tearing susceptibility. Zr is added to provide additional strengthening via nanoscale Al 3 Zr precipitation, and to stabilize and avoid coarsening of the Al 8 Cu 3 Ce phase. However, the detailed interaction between Zr and Al 8 Cu 3 Ce remains unexplored. In this work, we show with synchrotron X-ray diffraction that laser powder bed fusion fabricated Al-Cu-Ce and Al-Cu-Ce-Zr alloys contain predominantly the Al 8 Cu 3 Ce intermetallic in the as-fabricated condition. Heat treatment of the Al-Cu-Ce alloy results in the Al 8 Cu 3 Ce → Al 8 Cu 4 Ce phase transformation. In the Al-Cu-Ce-Zr alloy, minor fractions of (Al,Cu,Si) 4 Ce and Al 2 Cu-θ are found in the as-fabricated condition, while Al 8 Cu 3 Ce remains stable during heat treatment. Atom probe microscopy quantifies intermetallic stoichiometries and reveals how Zr is enriched at the Al-matrix/Al 8 Cu 3 Ce interface acting as a diffusion barrier against solute exchange. Calibrated thermodynamic modeling underpins this as a kinetic effect. Here, a qualitative microstructural model summarizes, how Zr stabilizes Al 8 Cu 3 Ce against phase transformations and coarsening.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling deformation and failure in AlSi-polyester abradable sealcoating material using microstructure-based finite element simulation

A plasma-sprayed aluminum-silicon (AlSi)/polyester coating is applied in modern gas turbine engines as an abradable sealcoating to maintain tight clearances between the rotating blades and the static casing. While running the engine, the rotating blades “rub” with the abradable coating, which results in extreme strain rate (up to 10 6 ) dynamics and a high-temperature environment. Due to the difficulty of collecting direct measurements, predictive computational models are important for analyzing the deformation and failure of the abradable material, to help meet the design target of avoiding damage to the blade tip and maintaining high fuel efficiency. In this research, a microstructure-based finite element (FE) computational model was developed to capture the complex mechanical behavior of the AlSi/polyester microstructure. The model is based on a virtual representative-volume-element (RVE) of a metal-polymer microstructure, reconstructed from x-ray computed tomography. It models the plastic deformation of, and damage to, each AlSi and polyester constituents, as well as the failure at their interface. The model was calibrated and validated with uniaxial tension and compression experiments, conducted at two temperatures (298 K and 533 K) at an applied strain rate of 10 3 - 10 4 s -1 . The material exhibited strongly asymmetric tension-compression behavior and a sensitivity to temperature, which was well captured by the model. The model was further applied to investigate changes in mechanical behavior due to variations in constituents’ volume fractions, which provides guidance to the microstructural design of AlSi/polyester abradable materials. The model is expected to facilitate the development of improved abradable materials by bypassing the conventional trial-and-error approach and extensive testing requirements.

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

Bonding of vanadium- and Iron-based alloys as interlayers for plasma-facing and structural materials in fusion systems

Vanadium alloys and FeCrAl were investigated as interlayers between tungsten and reduced activation ferritic martensitic steel for fusion system components to avoid formation of intermetallic phase at operating temperatures between 550 and 1100 °C, while maintaining a body centered cubic phase throughout the interface. Physical and mechanical properties need to be graded between tungsten and steel, but recent results showed a significant hardness increase at the FeCrAl to vanadium alloy interface. Here, a sintered sample of these alloys was annealed for extended time, and the microstructure was investigated to provide a better understanding of the phenomena. A comparison with an additively manufactured interface of the same material is provided. An unexpected L2 1 intermetallic phase formation has been revealed using microscopy and synchrotron techniques and will inform future additive manufacturing approaches of the interface. A Cr layer interface as a preliminary solution was proposed between the Vanadium alloy and FeCrAl alloy interface.

Additive manufacturing↗