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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Uncovering the Cu-driven electrochemical mechanism of transition metal chalcogenides based electrodes

Transition-metal chalcogenides (TMCs) have emerged as attractive anode materials for rechargeable batteries due to their excellent performance and abundant resources. In this work, for the first time, we disclose a unique copper (Cu)-driven conversion process in TMC-based battery systems that involves classic Cu current collector and is considered to be an “activation process”. According to state-of-the-art characterization techniques, Cu was evidenced to gradually replace the transition-metal elements in TMCs to be the active material during cycling. Based on this unique Cu-driven conversion mechanism, we used a facile method to design a new type of sulfur-based battery that presents excellent performance: a reversible capacity of 1.045 mAh cm -2 after 700 cycles at 2Ag -1 , and a good rate capability up to a capacity of 0.33 mAh cm -2 at 20 A g - 1. Lastly, with respect to the large family of TMC compounds, this study introduces a new direction for the design of high-performance energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Thermodynamic and Kinetic Mechanisms Governing the Synthesis of Nickel-Poor Cathodes

A deeper understanding of the thermodynamics and kinetics governing the lithiation and layering mechanisms of NMC cathode materials (LiNixMnyCozO 2 , where x + y + z = 1) offers valuable insights for enhancing synthesis methods and improving cathode performance. By employing atomistic and mesoscale approaches informed by in situ powder X-ray diffraction (PXRD) experiments, critical parameters for comprehending lithiation and layering processes and reaction rates were identified. The mesoscale approach captured the evolution of the phases and crystallite size observed in the in situ PXRD, revealing the differences in reaction rates with the use of different lithium salts and starting precursors. Ab initio molecular dynamics (AIMD) underscored the importance of vacancies and structural defects in promoting ion mobility and facilitating the nucleation of a layered domain. This nucleation disrupts the symmetry of disordered phases, ultimately creating a strained phase that serves as a buffer between layered and disordered regions. The lithiation and layering processes reflect a dynamic balance between the thermodynamic drive for a low-energy layered structure and the kinetic of diffusion, which is influenced by temperature and lithium vacancy concentration. Overall, reaction mechanisms are driven by the inherent defects of the intermediate phase that differ for NMC cathode materials. The lithium salts impact the rates of lithiation and layering, with a much slower process for Li 2 CO 3 .

25 ENERGY STORAGE↗
DOE OSTI2017

Speeding up N -body simulations of modified gravity: chameleon screening models

We describe and demonstrate the potential of a new and very efficient method for simulating certain classes of modified gravity theories, such as the widely studied f ( R ) gravity models. High resolution simulations for such models are currently very slow due to the highly nonlinear partial differential equation that needs to be solved exactly to predict the modified gravitational force. This nonlinearity is partly inherent, but is also exacerbated by the specific numerical algorithm used, which employs a variable redefinition to prevent numerical instabilities. The standard Newton-Gauss-Seidel iterative method used to tackle this problem has a poor convergence rate. Our new method not only avoids this, but also allows the discretised equation to be written in a form that is analytically solvable. We show that this new method greatly improves the performance and efficiency of f ( R ) simulations. For example, a test simulation with 512{sup 3} particles in a box of size 512 Mpc/ h is now 5 times faster than before, while a Millennium-resolution simulation for f ( R ) gravity is estimated to be more than 20 times faster than with the old method. Our new implementation will be particularly useful for running very high resolution, large-sized simulations which, to date, are only possible for the standard model, and also makes it feasible to run large numbers of lower resolution simulations for covariance analyses. We hope that the method will bring us to a new era for precision cosmological tests of gravity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Security proof of practical quantum key distribution with detection-efficiency mismatch

Quantum key distribution (QKD) protocols with threshold detectors are driving high-performance QKD demonstrations. The corresponding security proofs usually assume that all physical detectors have the same detection efficiency. However, the efficiencies of the detectors used in practice might show a mismatch depending on the manufacturing and setup of these detectors. A mismatch can also be induced as the different spatial-temporal modes of an incoming signal might couple differently to a detector. Here we develop a method that allows to provide security proofs without the usual assumption. Our method can take the detection-efficiency mismatch into account without having to restrict the attack strategy of the adversary. Especially, we do not rely on any photon-number cutoff of incoming signals such that our security proof is directly applicable to practical situations. We illustrate our method for a receiver that is designed for polarization encoding and is sensitive to a number of spatial-temporal modes. In our detector model, the absence of quantum interference between any pair of spatial-temporal modes is assumed. For a QKD protocol with this detector model, we can perform a security proof with characterized efficiency mismatch and without photon-number cutoff assumption. Our method also shows that in the absence of efficiency mismatch in our detector model, the key rate increases if the loss due to detection inefficiency is assumed to be outside of the adversary's control, as compared to the view where for a security proof this loss is attributed to the action of the adversary.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

DuraMAT: Building a Consortium to Accelerate the Photovoltaic Module Reliability Learning Cycle

Durable and reliable photovoltaic (PV) modules are critical to enabling an efficient transition to sustainable energy generation. The rate at which new module designs and materials are developed and deployed currently outpaces the rate at which we can identify failure mechanisms and understand degradation rates. Increasing the service life of PV modules, and our ability to predict performance over time, requires more durable materials and designs, better durability testing, more extensive material characterization, robust modeling, and methods to cross-examine historical performance data to extract meaningful results. This is a multidisciplinary challenge that requires expertise from a broad range of fields and, therefore, benefits significantly from a collaborative approach. In this Perspective, we outline the approach taken by the Durable Module Materials Consortium (DuraMAT), present a few case studies where our approach was successful, and provide an outlook on where this approach might be applied as the PV technology landscape continues to rapidly evolve. Published by the American Physical Society 2024

14 SOLAR ENERGY↗
DOE OSTI2025

Probabilistic Resilience-Oriented Assessment Approach for Transmission Networks Under Wildfires

The rising threat of wildfires poses significant challenges to power transmission networks, particularly in areas prone to such disasters. Traditional approaches for wildfire risk assessment neglect some potential wildfire scenarios. Here, this paper introduces a probabilistic resilience-oriented assessment approach for power transmission networks to address this gap. Initially, a probabilistic wildfire model is developed to capture uncertainties in ignition, intensity, and fire spread. Next, a spatiotemporal fragility model is constructed to assess the impact of wildfires on transmission corridors, incorporating Thermal Aging (TA) and Dynamic Thermal Rate (DTR) change. Finally, a comprehensive resilience metric is defined to evaluate system performance, leveraging the fragility model to determine component and system-level resilience. The approach employs a combinatorial enumeration method to generate potential wildfire scenarios, enhanced by an impact-increment-based state enumeration (IISE) method for computational efficiency. The proposed method provides critical insights for identifying system vulnerabilities and developing robust strategies to protect transmission networks from wildfires. The efficacy of this approach is validated through extensive scenarios of the RTS-GMLC system across Southern California, Nevada and Arizona.

Vahedi, Soroush [Univ. of Connecticut, Storrs, CT ↗
DOE OSTI2020

Development of an Encoding Method on an Co-simulation Platform for Mitigating the Impact of Unreliable Communication

This report presents a hardware-in-the-loop (HIL) based modeling approach for simulating impacts of unreliable communication on the performance of centralized volt-var control and for developing an encoding method to mitigate the impacts. First, an asynchronous real-time HIL simulation platform is introduced to enable multi-rate co-simulation of a distribution system with many inverter-based distributed energy resources (DERs). The distribution system is modeled by milliseconds phasor-based models and the DERs are modeled by micro-seconds power electronic models. Communication connections between a centralized volt-var controller (modeled externally to the HIL testbed) and smart inverters are built by implementing Modbus links and the Long Term Evolution network. On this co-simulation platform, an enhanced, augmented Lagrangian multiplier based encoded data recovery (EALM-EDR) algorithm for mitigating the impact of unreliable communication is developed and validated. Simulation results demonstrate the efficacy of using the HIL-based co-simulation platform as a power grid digital twin for developing algorithms that coordinate a large number of heterogeneous control systems through wired and wireless communication links.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

On Transfer Learning Of Neural Networks Using Bi-Fidelity Data For Uncertainty Propagation

Due to their high degree of expressiveness, neural networks have recently been used as surrogate models for mapping inputs of an engineering system to outputs of interest. Once trained, neural networks are computationally inexpensive to evaluate and remove the need for repeated evaluations of computationally expensive models in uncertainty quantification applications. However, given the highly parameterized construction of neural networks, especially deep neural networks, accurate training often requires large amounts of simulation data that may not be available in the case of computationally expensive systems. In this paper, to alleviate this issue for uncertainty propagation, we explore the application of transfer learning techniques using training data generated from both high- and low-fidelity models. We explore two strategies for coupling these two datasets during the training procedure, namely, the standard transfer learning and the bi-fidelity-weighted learning. In the former approach, a neural network model mapping the inputs to the outputs of interest is trained based on the low-fidelity data. The high-fidelity data are then used to adapt the parameters of the upper layer(s) of the low-fidelity network, or train a simpler neural network to map the output of the low-fidelity network to that of the high-fidelity model. In the latter approach, the entire low-fidelity network parameters are updated using data generated via a Gaussian process model trained with a small high-fidelity dataset. The parameter updates are performed via a variant of stochastic gradient descent with learning rates given by the Gaussian process model. Using three numerical examples, we illustrate the utility of these bi-fidelity transfer learning methods where we focus on accuracy improvement achieved by transfer learning over standard training approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Study of Helium Irradiation Effect on Al6061 Alloy Fabricated by Additive Friction Stir Deposition

Additive friction stir deposition (AFS-D) is considered a productive method of additive manufacturing (AM) due to its ability to produce dense mechanical parts at a faster deposition rate compared to other AM methods. Al6061 alloy finds extensive application in aerospace and nuclear engineering; nevertheless, exposure to radiation or high-energy particles over time tends to deteriorate their mechanical performance. However, the effect of radiation on the components manufactured using the AFS-D method is still unexamined. In this work, samples from the as-fabricated Al6061 alloy, by AFS-D, and the Al6061 feedstock rod were irradiated with He+ ions to 10 dpa at ambient temperature. The microstructural and mechanical changes induced by irradiation of He+ were examined using a scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), transmission electron microscopy (TEM), and nanoindentation. This study demonstrates that, at 10 dpa of irradiation damage, the feedstock Al6061 produced a bigger size of He bubbles than the AFS-D Al6061. Nanoindentation analysis revealed that both the feedstock Al6061 and AFS-D Al6061 samples have experienced radiation-induced hardening. These studies provide a valuable understanding of the microstructural and mechanical performance of AFS-D materials in radiation environments, offering essential data for the selection of materials and processing methods for potential application in aerospace and nuclear engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Two-DoF Model-Informed Controller Gain Tuning for Several Floating Wind Platforms

Much effort has recently been put into the development of collective blade pitch controllers for floating offshore wind turbines, with the aim of overcoming negative damping issues that arise with traditional control methods. One proposed approach to this challenge involves using a two-degree-of-freedom model to inform the gain schedule of a nacelle velocity feedback term in an otherwise conventional proportional-integral controller. The model uses tower-top fore-aft and rotor angular displacements, and is used to calculate a nacelle velocity feedback gain that results in a specified increase in platform pitch damping. Earlier performance evaluations of this tuning method were favorable, suggesting its potential as an easy way for researchers to obtain an adequate controller. This paper expands on those previous results by examining the performance of the tuning method relative to baseline controllers for several hull configurations, and for several prescribed increases in platform pitch damping. Simulations were run in OpenFAST for several load cases above rated wind speed and show results consistent with trends in the earlier study. The tuning method is thus shown to be adaptable to many different types of hulls, making it useful for the evaluation of prototype designs.

artificial intelligence↗
DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Development of a Module for Performance Shaping Factors

Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) in communication with a variety of methods and tools. In this paper, how we have developed one of the HUNTER modules, the individual module for evaluating performance shaping factors (PSFs), is introduced. The PSF refers to any factor that influences human performance such as workload or complexity. It has been used for highlighting human errors and adjusting the error probabilities in the existing HRA. We consider the eight PSFs suggested in the Standardized Plant Analysis Risk-HRA (SPAR-H) method, which is the representative HRA method widely used in the nuclear field. To support our dynamic modeling using the eight SPAR-H PSFs, we reviewed human performance literature and developed data-based mathematical models to rate and quantify PSFs in the context of dynamic HRA. We also design the individual module composed of the two functions: 1) the PSF qualification function that automatically or manually evaluates a PSF level, and 2) the PSF quantification function that dynamically or statically determines the PSF multiplier values and integrate them to adjust human error probabilities (HEPs). How each function works with the SPAR-H PSFs and how the PSFs adjust the HEPs are investigated through literature and discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Impact of electrode porosity architecture on electrochemical performances of 1 mm-thick LiFePO4 binder-free Li-ion electrodes fabricated by Spark Plasma Sintering

Thick electrodes with high active material loadings have been intensively studied over the last couple of decades in pursuit of achieving high energy density systems. To optimize and enhance the electrochemical performance of such electrodes, one has to control the pore morphology by, for example, varying the pore size and shape, and the level of porosity. In the present work, the fabrication of thick binder-free LiFePO4 (LFP) electrodes with two different pore sizes (12 and 20 mu m) and porosities (21 vol% and 44 vol%) using Spark Plasma Sintering (SPS) and templating approach is reported. The well-controlled porous architecture inside the thick electrodes is realized by fine-tuning experimental parameters. The impact of porosity architecture on electrochemical performance is quantified and correlated with the 3D tortuosity values determined from both micro-computed tomography and electrochemical impedance-based experimental methods. Based on the micro-computed tomography data analysis, estimated tortuosity values along X, Y, and Z axes reveal an anisotropic effect perpendicularly to the SPS compression axis (Z-direction). This is particularly profoundly observed in the samples with larger pores (20 mu m). The correlation between morphological properties and the rate capability performance is established indicating that the capacity loss happens mainly due to the Li-ion diffusion limitations.

Cathode material↗
DOE OSTI2019

High water recovery and improved thermodynamic efficiency for capacitive deionization using variable flowrate operation

Water recovery is a measure of the amount of treated water produced relative to the total amount of water processed through the system, and is an important performance metric for any desalination method. Conventional operating methods for desalination using capacitive deionization (CDI) have so far limited water recovery to be about 50%. To improve water recovery for CDI, we introduce a new operating scheme based on a variable (in time) flow rate wherein a low flow rate during discharge is used to produce a brine volume which is significantly less than the volume of diluent produced. We demonstrate experimentally and study systematically this novel variable flowrate operating scheme in the framework of both constant current and constant voltage charge-discharge modes. We show that the variable flowrate operation can increase water recovery for CDI to very high values of ~90% and can improve thermodynamic efficiency by about 2- to 3-fold compared to conventional constant flowrate operation. Importantly, this is achieved with minimal performance reductions in salt removal, energy consumption, and volume throughput. Our work highlights that water recovery can be readily improved for CDI at very minimal additional cost using simple flow control schemes.

42 ENGINEERING↗
DOE OSTI2022

Anderson acceleration stability in NDA-accelerated k-eigenvalue problems

Anderson acceleration (AA) has been used to improve the stability and convergence rate of multiphysics iterative methods for reactor analysis. Most applications studied assume a tightly converged solution for the different physics problems, and AA is usually applied to state variables like temperature, density, and heat generation rate. In this paper, we study the theoretical performance of AA in NDA-accelerated k-eigenvalue problems. The problems and algorithms studied are simplified from the coupled iteration scheme adopted by MPACT and many other high-fidelity whole-core reactor codes. Compared to previous analyses of AA for these iteration schemes, we study the case with a partially converged neutronics solution and possibly partially converged nonlinear diffusion acceleration (NDA)/coarse mesh finite difference (CMFD) solutions. We observe that the performance of the iteration scheme with AA is very sensitive to the initial guess and is affected by the partially converged CMFD solutions. When the NDA solution is fully converged, using AA cannot achieve the optimal convergence rate in large-sized problems. Conversely, if the NDA solution is partially converged, the iteration scheme with AA can diverge or converge extremely slowly. It is found that the loss of robustness for AA is due to the fact that it is applied to the iterative subspace of state variables rather than the fundamental unknowns of the governing equations. To improve the robustness, the scalar flux should also be considered in the implementation of AA. After considering the residuals of flux, we observe that the stability is regardless of the partial convergence of NDA solutions. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Synthesizing Highly Crystalline Graphite Powder from Bulk Polyethylene Waste for Lithium-Ion Battery Anodes

Upcycling plastic waste into graphite can potentially be used, in conjunction with other methods, to manage existing waste materials and diversify graphite supply chains. However, synthesizing large quantities of crystalline graphite powder from plastic waste, particularly polyethylene (PE), remains a challenge because PE decomposes into light gases during thermal processing and simple methods do not exist at any appreciable size scale to address this challenge. In this work, a method is developed for air processing bulk forms of PE waste to create stable carbon char that does not readily decompose during high-temperature processing. This method employs solid additives in the form of salts, which are combined with the PE melt during air processing to increase the effective surface area of the melt and improve the oxygen-driven chemistry that stabilizes PE for high-temperature processing. After removal of the solid salt additives from the PE-derived char, it is converted into a highly crystalline bulk graphite powder using an Fe-based catalytic process. The PE-derived graphite anode in a lithium-ion coin cell showed a specific capacity of 345 mAh/g at 0.05C with an initial Coulombic efficiency of 87% and reversible capacity retention of ~100% at different current rates. It also showed a specific capacity of up to 313 mAh/g at 0.5 discharge/charge cycles per hour (0.5C) and Coulombic efficiency of 99.9% after 250 cycles, indicating excellent electrochemical performance as an anode material for lithium-ion batteries. This method illustrates that there are opportunities for upcycling large quantities of PE waste to produce graphite powders suitable for use in LIBs.

25 ENERGY STORAGE↗
DOE OSTI2022

Carbon nanofibers (CNFs) dispersed in ultra-high performance concrete (UHPC): Mechanical property, workability and permeability investigation

This paper presents experimental data on the effect of carbon nano-fiber (CNF) dispersion on mechanical behavior, workability, and permeability of ultra-high-performance concrete containing CNF (UHPC-CNF). The addition of CNFs in concrete has been shown to provide improved performance. However, an inhomogeneous distribution of CNFs in the cement matrix can result in no impact or decreased mechanical performance. Due to the van der Waal's forces and hydrophobic surface properties of the CNFs, good dispersion in mix fluids and cement paste is challenging. Experimental studies of UHPC-CNF with different dispersion methods are provided. Further mixing with optimized UHPC paste allowed for the investigation of the optimal dosage of CNFs, impact on porosity, compressive strength, flexural strength, hydration rate, and slump. Scanning electron microscopy (SEM) analysis visually revealed the effect of dispersion. Our results indicate that shear mixing and subsequent ultrasonic dispersion with chemical surfactants can provide a well-dispersion liquid admixture of CNFs resulting in high mechanical performance of UHPC-CNFs composites. The water permeability and chloride resistance of optimized UHPC-CNFs composites were further evaluated with the wicking test and ponding test to reveal improved performance for these properties as well.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Effect of Noninvasive Follicular Thyroid Neoplasm with Papillary-Like Nuclear Features (NIFTP) on Malignancy Rates in Thyroid Nodules: How to Counsel Patients on Extent of Surgery

Purpose: To investigate the impact of the nomenclature change to “noninvasive follicular thyroid neoplasm with papillary-like nuclear features” (NIFTP) on reported malignancy rates following thyroidectomy. Methods: Retrospective cohort study of patients with thyroid nodules sampled preoperatively with fine-needle aspiration (FNA) and subsequently removed at one tertiary-care hospital from 4/2016 to 2/2017. Surgical procedure, anatomic pathology, thyroid cytopathology classification, and demographic characteristics were recorded. Results: Thyroidectomy was performed in 353 patients. Twenty-six patients (7.3%) had NIFTP on anatomic pathology. Preoperative FNA demonstrated atypia of undetermined significance (AUS/Bethesda III) in 13 (50%), suspicious for malignancy (SUS/Bethesda V) in 6 (23%), suspicious for follicular neoplasm (SFN/Bethesda IV) in 4 (15%), benign/Bethesda I in 2 (8%), and malignant/Bethesda VI in 1 (4%). Invasive malignancy rates across cytologic categories changed as follows: benign (n = 74) from 4 to 1%, AUS (n = 85) from 33 to 18% (p < 0.05), SFN (n = 58) from 29 to 22%, SUS (n = 33) from 91 to 73% (p < 0.05), and malignant (n = 99) from 99 to 98%. Overall decrease in invasive malignancy was 7.3% for the entire population and 13.1% for indeterminate preoperative FNA cytology (Bethesda III–V). Among 26 NIFTP patients, 17 had thyroid lobectomy (TL) and 9 underwent total thyroidectomy (TT). Eight of the nine patients with TT could have been definitively treated with TL, an 89% decrease. Conclusions: The NIFTP nomenclature change led to an overall decrease in the malignancy rate at our institution, especially for Bethesda III–V categories. Patients may be counseled toward more conservative surgical options if NIFTP is in the differential.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Influence of Ink Formulation and Drying Conditions on Ionomer Distribution in High-Performance Roll-to-Roll-Coated Gas-Diffusion Electrodes

To enable mass production of fuel cell membrane electrode assemblies (MEAs) catalyst layers production will require continuous roll-to-roll (R2R) coating processes. Gas diffusion electrodes (GDEs) are advantageous for mass production because the catalyst layer can be directely coated on the microporous layer of the gas diffusion media without the need for a decal-transfer process. It is known that the water-to-alcohol ratio in the catalyst ink influences the interactions of the ionomer with the catalyst leading to different distributions of ionomer in spray-coated catalyst layers. It is also known that during drying of colloidal mixtures, like fuel cell inks, factors such as drying rate, particle size, and agglomeration influence how the materials distribute themselves throughout the thickness of the dired film. Thus far there have only been limited studies to understand how process conditions such as ink formulation and drying temperature influence the distribution of ionomer and catalyst coated using scalable methods. This understanding is especially important for GDEs since it is known that having a sufficient amount of ionomer at the catalyst layer-membrane interface is critical for high performance. In this study we have focused on determining how the ratio of water to 1-propanol in the catalyst ink ink and drying temperature influence the distribution of ionomer throughout the thickness of the catalyst layer. Using a combination of Kelvin probe and x-ray photoelectron spectroscopy we show that an ionomer-rich surface is promoted by a higher drying rate and a water-rich catalyst ink. In contrast, a 1-propanol catalyst ink leads to a lower concentration of ionomer on the top surface. Using x-ray computed tomography, we are able to characterize the ionomer distribution throughout the thickness of the layer. We find that, in addition to promoting an ionomer-rich top surface, water-rich inks lead to a more homogenous distribution of ionomer, whereas a 1-propanol-rich ink leads to a more irregular distribution. It is found that MEA performance is improved by selecting conditions and ink formulations that promote ionomer enrichment at the top surface to facilitate a good interface with the membrane. MEAs prepared with a 75 wt% water catalyst ink with a 0.9 I/C have equivalent performance to spray-coated GDEs. Critically, these R2R-coated GDEs do not need an additional ionomer overlayer like the spray-coated GDEs do, reducing the number of processing steps in a manufacturing setting. This work shows that with the appropriate selection of materials, ink formulation, and processing conditions gas-diffusion electrodes are a viable pathway for fuel cell manufacturing.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗