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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effect of temperature on capacity fade in silicon-rich anodes

Coin half-cells containing 80 wt% silicon electrodes are assembled and cycled at the similar to C/10 rate in the temperature range of 25-55 degrees C. To the best of our knowledge, this is the first time that the effect of temperature is reported for such high-silicon-containing cells. Two different electrolytes are used in this study, a baseline electrolyte and the baseline electrolyte +10 wt% fluoroethylene carbonate (FEC). Analysis of the capacity vs. cycle count data by curve fitting reveals that the addition of FEC markedly affects the capacity loss mechanism. Without FEC, the kinetic rate law for the capacity loss mechanism can be described as the sum of two logistic growth models. With the addition of FEC, the rate law depends on ln(t). Clearly, the addition of FEC has a profound effect on the mechanism of capacity loss. Interestingly, X-ray photoelectron spectroscopy (XPS) shows that the composition of the solid electrolyte interphase (SEI) layer changes markedly from mostly organic to mostly inorganic in the presence of FEC and how it varies at the different temperatures tested, especially in the absence of FEC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Chemistry Informed Machine Learning-Based Heat Capacity Prediction of Solid Mixed Oxides

Knowing heat capacity is crucial for modeling temperature changes with the absorption and release of heat and for calculating the thermal energy storage capacity of oxide mixtures with energy applications. The current prediction methods (ab initio simulations, computational thermodynamics, and the Neumann–Kopp rule) are computationally expensive, not fully generalizable, or inaccurate. Machine learning has the potential of being fast, accurate, and generalizable, but it has been scarcely used to predict mixture properties, particularly for mixed oxides. Here, we demonstrate a method for the generalizable prediction of heat capacity of solid oxide pseudobinary mixtures using heat capacity data obtained from computational thermodynamics and descriptors from ab initio databases. Further, models trained through this workflow achieved an error (mean absolute error of 0.43 J mol –1 K –1 ) lower than the uncertainty in differential scanning calorimetry measurements, and the workflow can be extended to predict other properties derived from the Gibbs free energy and for higher-order oxide mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Cu Doping Increases Capacity Retention in LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) by Altering the Potential of the Ni-Based Redox Couple and Inhibiting Particle Pulverization

To discern the influence of Cu 2+ as a dopant on both the structural and electrochemical characteristics of LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622), Cu 2+ (aq) was added to the coprecipitation synthesis from the constituent ions. At 5 mol % Cu 2+ , a single-phase Cu-NMC product results, evidenced by an increase in d-spacing along the [003] and [104] directions and a slight increase in the crystal volume of the R–3m hexagonal (rock-salt superstructure) lattice. XRD data and high-resolution TEM imaging support Cu 2+ doping primarily on the transition metal 3b Wyckoff sites. Here, galvanostatic cycling of Cu-NMC shows a reversible gravimetric capacity of 102 mAh/g compared to 136 mAh/g for undoped NMC. Despite the lower capacity, the discharge capacity retention of Cu-NMC is 89% after 100 cycles compared to only 70% for NMC. XPS analysis reveals that this lower capacity is due to an increase in the concentration of Ni 3+ ions at the surface, while XRD data collected at the top and bottom of charge show a smaller decrease in crystalline domain size for Cu-NMC (40.5% decrease) compared to NMC (74.7% decrease), translating to pulverization of the secondary particles.

25 ENERGY STORAGE↗
DOE OSTI2021

EV Hosting Capacity Analysis on Distribution Grids

The increasing trend in electric vehicle (EV) adoption can cause challenges to traditional electric grid operations if utilities are not equipped with tools and methods to effectively manage these fleets. Growing EV charging loads will alter the magnitude and duration of conventional peaks in demand profiles and even significantly shift them, potentially causing operational violations in the distribution grid. This paper presents the development and results of an EV hosting capacity tool to quantify the impacts of injecting large numbers of EV charging loads and to determine the available capacity of existing distribution feeders to continue providing reliable and affordable grid operations. Tools like the hosting capacity analysis would enable utilities to better prepare for grid operations in the near future while exploring the impact and effectiveness of strategies to manage these loads, such as peak pricing and smart charging. This paper evaluates the hosting capacity of some real-world feeders to accommodate EV charging loads, including extreme fast-charging options.

distribution grid↗
DOE OSTI2022

PV Hosting Capacity Estimation: Experiences with Scalable Framework

Hosting capacity is an indication of the amount of solar photovoltaics (PV) that can be hosted in a distribution system without additional changes to infrastructure or oper-ations. This paper presents a framework for estimating the PV hosting capacity at scale. First, we analyze computational, modeling and other key challenges of performing relevant, large-scale simulations, provided along with the experiences and lessons learned. Then, we develop two open-source Python-based software tools to conduct repeatable distribution analyses: the Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations and the Job Automation and Deployment Engine (JADE) for parallelizing jobs on high-performance computing clusters. A case study of hosting capacity estimation for the SMART-DS San Francisco (SFO) 2000+ synthetic feeders, is used to demonstrate the capability of the developed DISCO+JADE framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, which can help them better plan for the overall upgrade costs to integrate more PV in the future. The experiences are shared to aid the tool users and researchers to conduct relevant studies and research.

distributed energy resources↗
DOE OSTI2020

Cut–and–chip harvester material capacity and fuel performance on commercial-scale willow fields for varying ground and crop conditions

Shrub willow (Salix spp.) is capable of producing commercially attractive amounts of biomass in short rotations, but harvesting costs and logistics remain a concern. There is a particular need for information about harvesting operations on larger, commercial short–rotation woody crop systems. Another recent issue on commercial fields in northern New York is commercial growers conducting harvests during the growing season rather than the recommended dormant season when fields may be too wet to harvest. This study evaluated and modeled the in–field performance of a cut–and–chip harvester for almost 700 wagonloads of chips operating in commercial willow fields in a wider array of crop and field conditions than have been previously reported. Analysis indicated that the time of harvest (leaf–on or leaf–off) and whether site conditions were wet or dry affected the harvester's material capacity. Mean material capacity was greatest for leaf–off, dry conditions (71.8 Mg/hr) and lowest for leaf–on harvests, which were similar for wet (30.4 Mg/hr) and dry conditions (29.7 Mg/hr). Mean crop specific fuel consumption ranged between 1.3 and 3.3 L/Mg, but can get considerably higher for standing biomasses below 40 Mg/ha. Wet ground conditions and leaf–on harvests tend to decrease material capacity and increase fuel consumption as the harvester has to divert power to forward movement and material processing. Relationships for material capacity and fuel consumption based on standing biomass, time of harvest and ground conditions will be essential for evaluating and modeling the economic and environmental impacts of commercial–scale willow operations.

09 BIOMASS FUELS↗
DOE OSTI2026

Assessing Photovoltaic Capacity Factor Variability Using Long-Term Satellite Derived Solar Resource Data Under Brazilian Climate

Accurate estimation of photovoltaic (PV) energy yield and its variability is essential for reducing financial risk and supporting reliable system planning for rapidly expanding PV markets. In Brazil, high solar adoption and increasing levels of distributed energy resources are beginning to introduce operational challenges such as curtailment and evolving grid requirements. Understanding how natural variability in solar resource propagates into PV system performance is therefore increasingly important for both project design and grid integration. Modern PV yield assessments commonly rely on multi-year meteorological datasets and probabilistic exceedance metrics (e.g., P50/P90) to quantify energy yield uncertainty for project financing. However, the implications of long-term solar resource variability for PV system design choices and high-adoption grid conditions remain less well characterized for rapidly expanding markets such as Brazil. In particular, understanding how weather-driven variability propagates into PV production distributions and capacity factor expectations is important for evaluating curtailment exposure, deployment strategies, and storage requirements in regions experiencing rapid growth of distributed and utility-scale PV. Seasonal and interannual variability in atmospheric conditions can produce substantial fluctuations in monthly PV energy production, which propagate into uncertainty in annual energy yield and capacity factor expectations. Characterizing this variability using long-term meteorological datasets allows probabilistic estimation of PV system performance and provides improved insight into the range of expected PV energy outcomes. This study explores the use of long-term satellite-derived meteorological data from the National Solar Radiation Database (NSRDB) to evaluate the variability of photovoltaic system performance across multiple locations in Brazil. Using a 27-year dataset (1998-2024), PV system simulations are performed to characterize the distribution of annual and seasonal capacity factors and energy yield outcomes, while propagating key sources of meteorological variability and model uncertainty through the PV modeling chain. The analysis also investigates the sensitivity of PV performance outcomes to key system design assumptions within the PV modeling chain, including tracking configuration and system sizing parameters. The resulting probabilistic performance characterization provides insight into how weather-driven variability influences PV production expectations and capacity factor distributions. These results provide a foundation for evaluating how weather-driven variability interacts with high PV adoption and potential storage or curtailment mitigation strategies.

14 SOLAR ENERGY↗
DOE OSTI2021

Multi-User Capacity for Cyclic Prefix Direct Sequence Spread Spectrum with Linear Detection and Precoding

Cyclic Prefix Direct Sequence Spread Spectrum (CP-DSSS) is a promising solution for futuristic 6G ultra-reliable low latency communications (URLLC) and massive machine type communication (mMTC) applications, where the CP-DSSS waveform would operate as a secondary network at the same frequencies as the primary network but at much lower SNR. In this paper, we show per-user capacity for multi-user scenarios, where simple matched filtering (MF) is performed on the uplink (UL) and time-reversal (TR) precoding is used on the downlink (DL). When operating in the low SNR regime, CP-DSSS achieves per-user capacity near the optimum single-user capacity by using a MF detector at the receiver for the UL. TR precoding converges to the optimal capacity as the number of antennas at the hub/gateway increases. Given the near-optimal performance of MF detection and TR precoding for each of the users, CP-DSSS can be implemented with simple device transceiver structures, reducing per-unit cost for massively deployed 6G networks.

5G and Beyond Communications↗
DOE OSTI2022

PV Hosting Capacity Estimation: Experiences with Scalable Framework; Preprint

Hosting capacity is an indication of the amount of photovoltaics (PV) can be hosted in a distribution system. This paper presents a framework for estimating distributed PV hosting capacity at scale. We first analyze the key challenges of performing relevant large scale simulation including computational and modeling challenges. Then, we develop two python-based software tools in order to conduct repeatable distribution analyses: Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations, and JADE for parallelizing jobs on HPC clusters. A case study of hosting capacity estimation for SMART-DS SFO 2000+ synthetic feeders is used to demonstrate the capability of the developed framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, through which the overall upgrade cost can be better planned in order to integrate more PV in the future.

distributed energy resources↗
DOE OSTI2021

Multicriterion Benefit Evaluation of Deploying New Battery Technology with Increased Capacity at a Generic Nuclear Power

Nuclear power plant (NPP) safety improvements are routinely made by plant licensees and regulators. Examples of plant improvements include accident-tolerant fuel, diverse and flexible coping strategies, passive cooling systems, and increased battery capacity. A combined use of these plant improvements could lead to plant designs with enhanced resilience, allowing NPPs to better cope with both internal and external hazards and keep the plant operating safely, efficiently, and economically. This paper focuses on increased battery capacity and evaluates the potential costs and benefits of deploying batteries with increased capacities at a generic boiling water reactor (BWR) NPP. A multicriterion benefit evaluation methodology is used for the cost-benefit analysis. Ten alternatives for extending battery capacity are developed, including nine alternatives to provide additional direct-current power and one alternative to provide additional alternating-current power. Potential benefits of reducing plant risk are quantified through incorporating the alternatives into loss-of-offsite-power scenarios of the generic BWR probabilistic risk assessment model. Potential costs of implementing the alternatives are qualitatively discussed and ranked. The alternatives are then compared based on their impacts on plant risk and economics.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Multicriterion Benefit Evaluation of Deploying New Battery Technology with Increased Capacity at a Generic Nuclear Power Plant

This presentation is prepared for the DOE LWRS RISA Pathway Stakeholder Engagement Meeting on October 13-14, 2021. Nuclear power plant (NPP) safety improvements are routinely made by plant licensees and regulators. Examples of plant improvements include accident-tolerant fuel, diverse and flexible coping strategies, passive cooling systems, and increased battery capacity. A combined use of these plant improvements could lead to plant designs with enhanced resilience, allowing NPPs to better cope with both internal and external hazards and keep the plant operating safely, efficiently, and economically. This presentation focuses on increased battery capacity and evaluates the potential costs and benefits of deploying batteries with increased capacities at a generic boiling water reactor (BWR) NPP. A multicriterion benefit evaluation methodology is used for the cost-benefit analysis. Ten alternatives for extending battery capacity are developed, including eight alternatives to provide additional direct-current power and one alternative to provide additional alternating-current power. Potential benefits of reducing plant risk are quantified through incorporating the alternatives into loss-of-offsite-power scenarios of the generic BWR probabilistic risk assessment model. Potential costs of implementing the alternatives are qualitatively discussed and ranked. The alternatives are then compared based on their impacts on plant risk and economics.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Soil pH Buffering Capacity, Geochemical Characterization, and Soil Water Retention for Arctic Soils of Seward Peninsula and Utqiagvik, Alaska, 2013-2019

This dataset provides pH titration data and soil pH buffering capacities of 21 Arctic soils that were collected between 2013-2019. Geochemical data including soil organic carbon, carbon:nitrogen ratio, initial pH, and gravimetric water content are also reported. Additional measurements of cation exchange capacity and soil water retention (dry range) are presented for selected soils. A script, developed in R, is also included for a simple biogeochemical simulation that incorporates soil pH buffering capacity. This dataset contains 7 csv files and one R script.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

High Sulfur Loading and Capacity Retention in Bilayer Garnet Sulfurized‐Polyacrylonitrile/Lithium‐Metal Batteries with Gel Polymer Electrolytes

The cubic‐garnet (Li 7 La 3 Zr 2 O 12 , LLZO) lithium–sulfur battery shows great promise in the pursuit of achieving high energy densities. The sulfur used in the cathodes is abundant, inexpensive, and possesses high specific capacity. In addition, LLZO displays excellent chemical stability with Li metal; however, the instabilities in the sulfur cathode/LLZO interface can lead to performance degradation that limits the development of these batteries. Therefore, it is critical to resolve these interfacial challenges to achieve stable cycling. Here, an innovative gel polymer buffer layer to stabilize the sulfur cathode/LLZO interface is created. Employing a thin bilayer LLZO (dense/porous) architecture as a solid electrolyte and significantly high sulfur loading of 5.2 mg cm −2 , stable cycling is achieved with a high initial discharge capacity of 1542 mAh g −1 (discharge current density of 0.87 mA cm −2 ) and an average discharge capacity of 1218 mAh g −1 (discharge current density of 1.74 mA cm −2 ) with 80% capacity retention over 265 cycles, at room temperature (22 °C) and without applied pressure. Achieving such stability with high sulfur loading is a major step in the development of potentially commercial garnet lithium–sulfur batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

A Strategy for Constructing Pore‐Space‐Partitioned MOFs with High Uptake Capacity for C 2 Hydrocarbons and CO 2

Abstract Introduction of pore partition agents into hexagonal channels of MIL‐88 type (acs topology) endows materials with high tunability in gas sorption. Here, we report a strategy to partition acs framework into pacs (partitioned acs) crystalline porous materials (CPM). This strategy is based on insertion of in situ synthesized 4,4′‐dipyridylsulfide (dps) ligands. One third of open metal sites in the acs net are retained in pacs MOFs; two thirds are used for pore‐space partition. The Co 2 V‐pacs MOFs exhibit near or at record high uptake capacities for C 2 H 2 , C 2 H 4 , C 2 H 6 , and CO 2 among MOFs. The storage capacity of C 2 H 2 is 234 cm 3 g −1 (298 K) and 330 cm 3 g −1 (273 K) at 1 atm for CPM‐733‐dps (the Co 2 V‐BDC form, BDC=1,4‐benzenedicarboxylate). These high uptake capacities are accomplished with low heat of adsorption, a feature desirable for low‐energy‐cost adsorbent regeneration. CPM‐733‐dps is stable and shows no loss of C 2 H 2 adsorption capacity following multiple adsorption–desorption cycles.

Wang, Yong↗
DOE OSTI2020

A Strategy for Constructing Pore-Space-Partitioned MOFs with High Uptake Capacity for C 2 Hydrocarbons and CO 2

Introduction of pore partition agents into hexagonal channels of MIL-88 type (acs topology) endows materials with high tunability in gas sorption. Here, we report a strategy to partition acs framework into pacs (partitioned acs) crystalline porous materials (CPM). This strategy is based on insertion of in situ synthesized 4, 4'-dipyridylsulfide (dps) ligands. As a result, one third of open metal sites in the parent acs net are retained in pacs MOFs, while two thirds are used for pore space partition. The newly synthesized Co 2 V-pacs MOFs, with optimized pore space and open metal sites, exhibit near or at record high uptake capacities for C 2 H 2 , C 2 H 4 , C 2 H 6 , and CO 2 among MOFs. For example, the storage capacity of C 2 H 2 is 234 cm 3 /g -1 (298 K) and 330 cm 3 /g -1 (273K) at 1 atm for CPM-733-dps (the Co 2 V-BDC form, BDC=1,4-benzenedicarboxylate), higher than benchmark MOFs such as MOF-74 and all other pacs members. These high uptake capacities are accomplished with low heat of adsorption, a feature desirable for low-energy-cost adsorbent regeneration. CPM-733-dps is stable and shows no loss of C 2 H 2 adsorption capacity following multiple adsorption–desorption cycles.

25 ENERGY STORAGE↗
DOE OSTI2021

Breaking the trade-off between selectivity and adsorption capacity for gas separation

It is generally recognized that porous solids (sorbents) with high selectivity and high adsorption capacity offer potential for energy-efficient gas separations. Unfortunately, there is generally a trade-off between capacity and selectivity, which represents a roadblock to the utility of sorbents in key industrial processes. For example, acetylene (C 2 H 2 ), an important fuel and chemical intermediate, is produced with CO 2 as an impurity, and the similar physicochemical properties of C 2 H 2 and CO 2 mean that most sorbents are poorly selective. Hybrid ultramicroporous materials (HUMs) are candidates for gas separations as they exhibit benchmark selectivity for several key gas pairs. Unfortunately, existing HUMs are handicapped by low capacity. Here, we report a new HUM, SIFSIX-21-Ni, that addresses the trade-off between selectivity and capacity that has plagued sorbents, as its high uptake and high selectivity renders it the new benchmark for C 2 H 2 /CO 2 separation performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Mitigation of rapid capacity decay in silicon-LiNi 0.6 Mn 0.2 Co 0.2 O 2 full batteries

Silicon (Si)-based materials have been considered as the most promising anode materials for high-energy-density lithium-ion batteries because of their higher storage capacity and similar operating voltage, as compared to the commercial graphite (Gr) anode. But the use of Si anodes including silicon-graphite (Si-Gr) blended anodes often leads to rapid capacity decay in Si-Gr/LiNixMnyCo z O 2 (x+y+z=1) full cells, which has been attributed to surface instability of the Si component. In addition to stabilizing the surface, this work investigates the potential of the Si-Gr blended anodes in a full-cell configuration and its impact on the capacity contribution from active components. Using dQ/dV plots of the full cells, a powerful but simple-to-implement differential potential approach is developed to decouple the capacity contribution and degradation from the graphite and silicon components. Data collected from three-electrode cells confirm the results from the differential potential approach, which suggests a voltage slippage to a higher voltage at the blended anode side. Additionally, the voltage slippage causes a reduced utilization of the Gr component and exacerbates side reactions between the Si-Gr anode and carbonate electrolytes. Furthermore, based on these failure mechanisms, we adopted a mitigation strategy to tune the open circuit voltage of the prelithiated anode while stabilizing the surface. As a result, the full cells with the modified Si-Gr anodes (mass loading, 2.5 mAh/cm 2 ) offer a highly reversible full-cell energy density of 390 Wh/kg (based on the mass of both anode and cathode materials in a full cell) with a cycling CE of 99.9% over 200 cycles.

25 ENERGY STORAGE↗
DOE OSTI2023

Unraveling capacity fading in lithium-ion batteries using advanced cyclic tests: A real-world approach

Battery lifespan estimation is essential for effective battery management systems, aiding users and manufacturers in strategic planning. However, accurately estimating battery capacity is complex, owing to diverse capacity fading phenomena tied to factors such as temperature, charge-discharge rate, and rest period duration. In this work, we present an innovative approach that integrates real-world driving behaviors into cyclic testing. Unlike conventional methods that lack rest periods and involve fixed charge-discharge rates, our approach involves 1000 unique test cycles tailored to specific objectives and applications, capturing the nuanced effects of temperature, charge-discharge rate, and rest duration on capacity fading. This yields comprehensive insights into cell-level battery degradation, unveiling growth patterns of the solid electrolyte interface (SEI) layer and lithium plating, influenced by cyclic test parameters. Here, the results yield critical empirical relations for evaluating capacity fading under specific testing conditions.

25 ENERGY STORAGE↗