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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

E-modulus evolution and its relation to solids formation of pastes from commercial cements

Models for early age E-modulus evolution of cement pastes are available in the literature, but their validation is limited. This paper provides correlated measurements of early age evolution of E-modulus and hydration of pastes from five commercial cements differing in limestone content. A recently developed methodology allowed continuous monitoring of E-modulus from the time of casting. The methodology is a variant of classic resonant frequency methods, which are based on determination of the first resonant frequency of a composite beam containing the material. The hydration kinetics - and thus the rate of formation of solids - was determined using chemical shrinkage measurements. For the cements studied similar relationships between E-modulus and chemical shrinkage were observed for comparable water-to-binder ratio. For commercial cements it is suggested to model the E-modulus evolution based on the amount of binder reacted, instead of the degree of hydration.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Gradient boosting machine for modeling the energy consumption of commercial buildings

Accurate savings estimations are important to promote energy efficiency projects and demonstrate their cost-effectiveness. The increasing presence of advanced metering infrastructure (AMI) in commercial buildings has resulted in a rising availability of high frequency interval data. These data can be used for a variety of energy efficiency applications such as demand response, fault detection and diagnosis, and heating, ventilation, and air conditioning (HVAC) optimization. This large amount of data has also opened the door to the use of advanced statistical learning models, which hold promise for providing accurate building baseline energy consumption predictions, and thus accurate saving estimations. The gradient boosting machine is a powerful machine learning algorithm that is gaining considerable traction in a wide range of data driven applications, such as ecology, computer vision, and biology. In the present work an energy consumption baseline modeling method based on a gradient boosting machine was proposed. To assess the performance of this method, a recently published testing procedure was used on a large dataset of 410 commercial buildings. The model training periods were varied and several prediction accuracy metrics were used to evaluate the model's performance. The results show that using the gradient boosting machine model improved the R-squared prediction accuracy and the CV(RMSE) in more than 80 percent of the cases, when compared to an industry best practice model that is based on piecewise linear regression, and to a random forest algorithm.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Commercial building HVAC demand flexibility with model predictive control: Field demonstration and literature insights

Model Predictive Control (MPC) for building Heating Ventilation and Air Conditioning (HVAC) systems is beginning to gain traction in the market, with a few controls companies incorporating it into their product offerings. However, it remains difficult to assess whether the energy cost savings are enough to justify the cost of MPC implementation for a particular building, given the limited number of reported demonstrations. For small commercial and residential buildings with relatively uniform systems, standardized approaches can help lower implementation costs. In contrast, for large buildings or district systems, the potential magnitude of cost savings could justify more customized solutions. Estimating the cost-effectiveness of MPC becomes more challenging for medium and large commercial buildings, where a one-size-fits-all solution may not be suitable, and the potential energy cost savings may be insufficient to justify a customized solution. To make MPC technology more appealing, incorporating additional value streams beyond energy efficiency alone can significantly increase its attractiveness. One such revenue stream is demand flexibility, in response to dynamic electricity prices, where MPC can leverage the thermal mass of the building to shift the load and support the grid. Building on an extensive literature review of MPC field studies focused on cost savings and demand flexibility, this paper presents the results of implementing MPC control in a large office building HVAC system in Berkeley, CA. Four different dynamic electricity price profiles were integrated into the MPC objective function to shift building demand while maintaining comfort, and field testing was performed with each price profile across four seasons. The results show potential for 40–65 % demand decrease percentage and up to 61 % annual cost savings compared to the existing rule-based control strategy, under the tested dynamic price scenarios. This paper also presents a sensitivity analysis on the cost savings with respect to the price profile variability, discusses the implementation effort for the price-responsive MPC, and compares the cost savings found in this study to those found in literature on the basis of dynamic price variability, or so-called Electricity Price Relative Standard Deviation.

Zanetti, Ettore↗
DOE OSTI2026

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗
DOE OSTI2022

Near isothermal compressed air energy storage system in residential and commercial buildings: Techno-economic analysis

Electrical energy storage systems offer a wide range of options to efficiently manage our power supply infrastructure. Energy and environmental security via renewable resources and energy storage devices will also play a critical role in addressing the supply-demand challenges. A novel energy efficient storage system based on near isothermal compressed air energy storage concept, named as Ground-Level Integrated Diverse Energy Storage (GLIDES) is analyzed for integration with residential and commercial buildings. Additionally, the influence of different configurational aspects on key performance and cost attributes is presented in this study. GLIDES modules in the range of 0.5 kWh–15 kWh configurations were considered for residential buildings whereas 25 kW h–500 kW h modules were considered for commercial buildings. Detailed cost and performance analysis of the GLIDES module proved them to be an effective resource in lowering the peak energy demand and corresponding utility bills.

25 ENERGY STORAGE↗
DOE OSTI2018

UV-filters and musk fragrances in seafood commercialized in Europe Union: Occurrence, risk and exposure assessment

Highlights: • Largest survey on UV-Fs and musks in seafood commercialized in Europe. • Farmed seabream showed the highest average concentration of UV-Fs. • Wild mackerel showed the highest average concentration of polycyclic musks. • UV-Fs and musks in raw samples were far below the estimated toxicological reference value. In the framework of the FP7 ECsafeSeafood project, 62 seafood samples commercialized in Europe Union from several representative species – mackerel, tuna, salmon, seabream, cod, monkfish, crab, shrimp, octopus, perch and plaice – were analysed for residues of 21 personal care products (PCPs), including 11 UV-filters (UV-Fs) and 10 musk fragrances (musks). PCPs analysis were performed by Quick, Easy, Cheap, Effective Rugged, Safe (QuEChERS), combined with liquid-liquid extraction (LLE) or dispersive solid-phase extraction (dSPE), followed by gas chromatography-tandem mass spectrometry (GC-MS/MS). The results showed the presence in a wide range of samples of nine out of eleven UV-Fs compounds analysed, namely 2-ethylhexyl salicylate (EHS), 2-ethylhexyl,4-methoxycinnamate (EHMC), 4-methylbenzylidenecamphor (4-MBC), benzophenone-1 (BP1), benzophenone-3 (BP3), isoamyl-4-methoxycinnamate (IMC), 2,2′-dihydroxy-4,4′-dimethoxybenzophenone (DHMB), homosalate (HS), and octocrylene (OC), whereas galaxolide (HHCB), galaxolide lactone (HHCB-lactone), and tonalide (AHTN) were the most found musks. The potential risks to human health associated with the exposure to eight of the more prevalent PCPs – EHS, EHMC, 4-MBC, BP1, BP3, IMC, HHCB, and AHTN - through seafood consumption were assessed for consumers from five European countries (Belgium, Ireland, Italy, Portugal and Spain). Results showed that the human exposure to UV-Fs and musks estimated from the concentration values found in seafood and the daily consumption of concerned seafood species, were far below toxicological reference values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Degradation and Modeling of Large-Format Commercial Lithium-Ion Cells as a Function of Chemistry, Design, and Aging Conditions

Demand for large-format (>10 Ah) lithium-ion batteries has increased substantially in recent years, due to the growth of both electric vehicle and stationary energy storage markets. The economics of these applications is sensitive to the lifetime of the batteries, and end-of-life can either be due to energy or power limitations. Despite this, there is little information from cell manufacturers on the sensitivity of cell degradation to environmental conditions or battery use. This work reports accelerated aging test data from four commercial large-format lithium-ion batteries from three manufacturers, with varying design (thickness, casings, ...), chemistry (lithium-iron-phosphate (LFP) or lithium-nickel-manganese-cobalt-oxide positive electrodes (NMC), with graphite (Gr) negative electrodes), and capacity (50 to 250 Amp hours). The tested LFP|Gr cell is found to be relatively insensitive to cycling conditions like temperature or voltage window, while NMC|Gr cells have varying sensitivity. Degradation trends are further investigated by training predictive models: simple polynomial trend lines, a semi-empirical reduced-order model, and an empirical reduced-order model identified using machine-learning based on symbolic regression. Calendar and cycle life are simulated over a variety of conditions to directly compare the various batteries. Cell size and thickness are found to substantially impact sensitivity to temperature during cycle aging, while electrode chemistry impacts depth-of-discharge sensitivity. Real-world battery lifetime is evaluated by simulating residential energy storage and commercial frequency containment reserve systems in several U.S. climate regions. Predicted lifetime across cell types varies from 7 years to 20+ years, though all cells are predicted to have at least 10 year life in certain conditions.

battery lifetime↗
DOE OSTI2024

Comprehensive evaluation of commercially scalable atomic-layer-deposited alumina coating impact on full cell battery performance across varied test conditions

Atomic Layer Deposition (ALD) has emerged as a strategic enhancement method for lithium-ion battery (LIB) materials offering potential benefits and durability benefits for industrial battery production. However, the translation from laboratory achievements to commercial-scale applications has been limited. Here, this study aims to bridge this gap by comprehensively evaluating the effects of commercially scalable Al 2 O 3 ALD coatings using full pouch cell performance as a means to assess the ALD impact. We utilized large-scale slot-die coating techniques to ensure consistent electrode quality and tested four configurations of pouch cells to analyze the individual effects of ALD coating on anode and cathode electroactive materials. Our extensive testing matrix included long-term cycling, fast discharge, fast charge, leakage current, and high voltage tests. While at lower C-rates (<~1C), the influence of Al 2 O 3 coatings on cell performance is not significant. Fast charging conditions reveal that the anode ALD coating significantly enhances performance via a passivating effect, while on the cathode, it is detrimental, potentially due to increased resistance of the thin interfacial layer formed during the ALD processing. Leakage current and high-voltage tests show that the application of ALD coatings on either anode or cathode effectively minimizes side reactions at the electrode-electrolyte interface. Additionally, ALD coatings significantly mitigate concentrated and localized lithium plating on the anodes. These insights provide a valuable understanding of the potential of ALD technologies in LIB manufacturing to tailor cell performance, paving the way for safer, more efficient, and cost-effective battery solutions.

25 ENERGY STORAGE↗
DOE OSTI2013

Northern pike bycatch in an inland commercial hoop net fishery: effects of water temperature and net tending frequency on injury, physiology, and survival

In lakes and rivers of eastern Ontario (Canada) commercial fishers use hoop nets to target a variety of fishes, but incidentally capture non-target (i.e., bycatch) gamefish species such as northern pike (Esox lucius). Little is known about the consequences of bycatch in inland commercial fisheries, making it difficult to identify regulatory options. Regulations that limit fishing during warmer periods and that require frequent net tending have been proposed as possible strategies to reduce bycatch mortality. Using northern pike as a model, we conducted experiments during two thermal periods (mid-April: 14.45 ± 0.32 °C, and late May: 17.17 ± 0.08 °C) where fish were retained in nets for 2 d and 6 d. A ‘0 d’ control group consisted of northern pike that were angled, immediately sampled and released. We evaluated injury, physiological status and mortality after the prescribed net retention period and for the surviving fish used radio telemetry with manual tracking to monitor delayed post-release mortality. Our experiments revealed that injury levels, in-net mortality, and post-release mortality tended to increase with net set duration and at higher temperatures. Pike exhibited signs of chronic stress and starvation following retention, particularly at higher temperatures. Total mortality rates were negligible for the 2 d holding period at 14 °C, 14% for 6 d holding at 14 °C, 21% for 2 d holding at 17 °C, and 58% for 6 d holding at 17 °C. No mortality was observed in control fish. Collectively, these data reveal that frequent net tending, particularly at warmer temperatures, may be useful for conserving gamefish populations captured as bycatch in inland hoop net fisheries.

discards↗
DOE OSTI2015

Verification of a solvent optimization approach for postcombustion CO 2 capture using commercial alkanolamines

This work verified a phase equilibrium approach for optimization of conceptual solvents by using process simulations of commercial solvents N-methyl-diethanolamine (MDEA) and 2-amino-2-methyl-1-propanol (AMP) aqueous solution, for a conventional absorption/desorption based postcombustion CO 2 capture process. The simulated total heat/total equivalent work for the investigated tertiary/hindered amines has the same trends as those based on the phase equilibrium approach for conceptual solvents with the same heat of reactions. Moreover, the simulated CO 2 working capacities for the commercial solvents agree well with those obtained with the phase equilibrium approach for the corresponding conceptual solvents, verifying the phase equilibrium approach. Finally, results of parametric tests using the AMP aqueous solution illustrate that there is an optimal lean loading for the lean solution and an optimal temperature for the stripper inlet solvent to achieve the least total equivalent work/total heat.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Risk-based Post Injection Site Care and Monitoring for Commercial-Scale Carbon Storage: Reevaluation of the FutureGen 2.0 Site using NRAP-Open-IAM and DREAM

Modeling was conducted to assess the effectiveness of the NRAP toolset, specifically NRAP-IAM-CS v2 and DREAM, to determine a risk-based PISC period and optimized monitoring network for a commercial-scale CO2 storage project. Realizations from NRAP-IAM-CS v2 revealed that leakage rates of both CO2 and brine were small, on the order of 10-5 kg/s, and occurred primarily during the injection phase in the Ironton-Galesville, the thief zone immediately overlying the injection reservoir. Using this information to design an optimized monitoring well network eliminated one of the two originally planned above zone monitoring wells, resulting a substantial cost reduction for the project. Perhaps the most significant finding from this effort is that NRAP-IAM-CS v2 can be used to define a risk-based, and substantially shorter, PISC period for the site. NRAP-IAM-CS v2 realizations indicate that the majority of risk of endagerment to USDWs decreases within the first 5 years after CO2 injection ends. Doubling this timeframe would still lead to a net PISC period reduction of 40-years and an operational cost reduction in excess of $50M for the project. This study serves as a first-of-its-kind effort to apply NRAP tools to evaluate components of a commercial-scale Class VI UIC permit and provides a foundation for broader application and adoption by the CCS community.

system model, integrated assessment, reservoir, aq↗
DOE OSTI2016

Multi-institutional Validation Study of Commercially Available Deformable Image Registration Software for Thoracic Images

Purpose: To assess the accuracy of the commercially available deformable image registration (DIR) software for thoracic images at multiple institutions. Methods and Materials: Thoracic 4-dimensional (4D) CT images of 10 patients with esophageal or lung cancer were used. Datasets for these patients were provided by DIR-lab ( (dir-lab.com)) and included a coordinate list of anatomic landmarks (300 bronchial bifurcations) that had been manually identified. Deformable image registration was performed between the peak-inhale and -exhale images. Deformable image registration error was determined by calculating the difference at each landmark point between the displacement calculated by DIR software and that calculated by the landmark. Results: Eleven institutions participated in this study: 4 used RayStation (RaySearch Laboratories, Stockholm, Sweden), 5 used MIM Software (Cleveland, OH), and 3 used Velocity (Varian Medical Systems, Palo Alto, CA). The ranges of the average absolute registration errors over all cases were as follows: 0.48 to 1.51 mm (right-left), 0.53 to 2.86 mm (anterior-posterior), 0.85 to 4.46 mm (superior-inferior), and 1.26 to 6.20 mm (3-dimensional). For each DIR software package, the average 3-dimensional registration error (range) was as follows: RayStation, 3.28 mm (1.26-3.91 mm); MIM Software, 3.29 mm (2.17-3.61 mm); and Velocity, 5.01 mm (4.02-6.20 mm). These results demonstrate that there was moderate variation among institutions, although the DIR software was the same. Conclusions: We evaluated the commercially available DIR software using thoracic 4D-CT images from multiple centers. Our results demonstrated that DIR accuracy differed among institutions because it was dependent on both the DIR software and procedure. Our results could be helpful for establishing prospective clinical trials and for the widespread use of DIR software. In addition, for clinical care, we should try to find the optimal DIR procedure using thoracic 4D-CT data.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Mechanical properties of neutron-irradiated model and commercial FeCrAl alloys

The development and understanding of the mechanical properties of neutron-irradiated FeCrAl alloys is increasingly a critical need as these alloys continue to become more mature for nuclear reactor applications. This study focuses on the mechanical properties of model FeCrAl alloys and of a commercial FeCrAl alloy neutron-irradiated to up to 13.8 displacements per atom (dpa) at irradiation temperatures between 320 and 382 °C. Tensile tests were completed at room temperature and at 320 °C, and a subset of fractured tensile specimens was examined by scanning electron microscopy. Results showed typical radiation hardening and embrittlement indicative of high chromium ferritic alloys with strong chromium composition dependencies at lower doses. At and above 7.0 dpa, the mechanical properties saturated for both the commercial and model FeCrAl alloys, although brittle cleavage fracture was observed at the highest dose in the model FeCrAl alloy with the highest chromium content (18 wt %). Finally, the results suggest the composition and microstructure of FeCrAl alloys plays a critical role in the mechanical response of FeCrAl alloys irradiated near temperatures relevant to light water reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Post-irradiation examination of commercial tantalum alloys following neutron irradiation

Post irradiation examination of two commercial tantalum alloys (based on Ta-8 %W) revealed significant irradiation hardening following neutron irradiation in the High Flux Isotope Reactor at Oak Ridge National Laboratory. Tensile samples of commercial Ta alloys T-111 and ASTAR-811C were irradiated to a total neutron fluence (E > 0.1 MeV) in the range (2–4)x10 21 n/cm 2 (0.39–0.75 dpa) at an irradiation temperature near 900 °C. Tensile testing conducted at room temperature and at 800 °C revealed significant irradiation hardening under all test conditions. Samples that were tensile tested at room temperature exhibited brittle failure, whereas ductility was maintained for elevated temperature testing. The irradiation hardening and embrittlement noted for both alloys was attributed to irradiation-induced dislocation loop formation as confirmed through scanning transmission electron microscopy analysis. Corresponding energy dispersive x-ray spectroscopy revealed radiation-induced segregation of Hf in these loop populations. This Hf enrichment is shown to result in eventual co-precipitation of elongated (Hf,O)-rich precipitates along the dislocation loops. Further, these results show that irradiation hardening is enhanced via irradiation-enhanced precipitation at elevated irradiation temperatures. Consequently, the minimum recommended operating temperature window for Ta alloys should be increased to account for observed hardening/embrittlement at irradiation temperatures as high as 900 °C (1,173 K).

36 MATERIALS SCIENCE↗
DOE OSTI2011

Evaluation of commercial lithium-ion cells based on composite positive electrode for plug-in hybrid electric vehicle applications. Part I: Initial characterizations

Evaluating commercial Li-ion batteries presents some unique benefits. One of them is to use cells made from established fabrication process and form factor, such as those offered by the 18650 cylindrical configuration, to provide a common platform to investigate and understand performance deficiency and aging mechanism of target chemistry. Such an approach shall afford us to derive relevant information without influence from processing or form factor variability that may skew our understanding on cell-level issues. A series of 1.9 Ah 18650 lithium ion cells developed by a commercial source using a composite positive electrode comprising (LiMn1/3Ni1/3Co1/3O2 + LiMn2O4) is being used as a platform for the investigation of certain key issues, particularly path-dependent aging and degradation in future plug-in hybrid electric vehicle (PHEV) applications, under the US Department of Energy's Applied Battery Research (ABR) program. Here we report in Part I the initial characterizations of the cell performance and Part II some aspects of cell degradation in 2C cycle aging. The initial characterizations, including cell-to-cell variability, are essential for life cycle performance characterization in the second part of the report when cell-aging phenomena are discussed. Due to the composite nature of the positive electrode, the features (or signature) derived from the incremental capacity (IC) of the cell appear rather complex. In this work, the method to index the observed IC peaks is discussed. Being able to index the IC signature in details is critical for analyzing and identifying degradation mechanism later in the cycle aging study.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Failure statistics for commercial lithium ion batteries: A study of 24 pouch cells

There are relatively few publications that assess capacity decline in enough commercial cells to quantify cell-to-cell variation, but those that do show a surprisingly wide variability. Capacity curves cross each other often, a challenge for efforts to measure the state of health and predict the remaining useful life (RUL) of individual cells. We analyze capacity fade statistics for 24 commercial pouch cells, providing an estimate for the time to 5% failure. Our data indicate that RUL predictions based on remaining capacity or internal resistance are accurate only once the cells have already sorted themselves into “better” and “worse” ones. Analysis of our failure data, using maximum likelihood techniques, provide uniformly good fits for a variety of definitions of failure with normal and with 2- and 3-parameter Weibull probability density functions, but we argue against using a 3-parameter Weibull function for our data. pdf fitting parameters appear to converge after about 15 failures, although business objectives should ultimately determine whether data from a given number of batteries provides sufficient confidence to end lifecycle testing. Increased efforts to make batteries with more consistent lifetimes should lead to improvements in battery cost and safety.

25 ENERGY STORAGE↗
DOE OSTI2011

Influence of cooling rate on the development of multiple generations of {gamma}' precipitates in a commercial nickel base superalloy

The compositional and microstructural evolution of different generations of {gamma}' precipitates during the continuous cooling of a commercial nickel base superalloy, Rene88DT, has been characterized by three dimensional atom probe tomography coupled with energy-filtered transmission electron microscopy studies. After solutionizing in the single {gamma} phase field, continuous cooling at a very high rate results in a monomodal size distribution of {gamma}' precipitates with a high nucleation density and non-equilibrium compositions. In contrast, a relatively slower cooling rate ({approx} 24 deg. C/min) results in a multi-modal size distribution of {gamma}' precipitates with the larger first generation primary precipitates exhibiting close to equilibrium composition, along with the smaller scale secondary {gamma}' precipitates, exhibiting non-equilibrium composition (excess of Co and Cr, depleted in Al and Ti). The composition of the {gamma} matrix near these precipitates also exhibits similar trends with the composition being closer to equilibrium near the primary precipitates as compared to the secondary precipitates. - Highlights: {yields} Effect of cooling rate on the precipitation of {gamma}' particles in commercial nickel base superalloy. {yields} Couples EFTEM and 3DAP studies to determine the composition and morphology of {gamma}' precipitates. {yields} Determination of near and far field compositional variations within the gamma matrix leading to subsequent precipitation.

36 MATERIALS SCIENCE↗