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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sizing of discontinuous natural fibers: Effect of sizing approach and sizing concentration on composite properties

Natural fiber reinforced composites (NFRCs) are gaining attention in automotive applications as an alternative to glass fiber composites due to their lightweight and renewable sourcing. However, the inherent hydrophilicity of natural fibers leads to poor compatibility with hydrophobic polymers which adversely affects the mechanical properties of the composites and can limit their application to non-structural parts. Sizing is a common approach used for synthetic fibers to improve the interface between fiber and matrix. However, there is limited study on the sizing of natural fibers, and hence the focus of this work. Here, in this study, two different approaches to sizing discontinuous coir fibers were investigated, namely; (1) ex-situ sizing and (2) in-situ sizing. A commercial polypropylene (PP) based sizing agent was used and the effects of varying sizing solution concentrations (1.5, 2.5, and 3.5 wt%) on the properties of the composites was studied. Results showed that composites prepared via the in-situ sizing process had better fiber–matrix adhesion and improved tensile properties compared to ex-situ sized composites. On studying the effect of different sizing concentrations on composite properties, we found that the tensile strength of the composites increased (by ∼ 42 %) up to 2.5 wt% sizing concentration (in solution) and then decreased. However, the impact strength decreased significantly on increasing the sizing content beyond 1.5 wt% (by ∼ 40 %). Additionally, the study was further extended to investigate the effect of sizing on different NFRCs (coir, banana, and cottonized hemp fiber) where effectiveness of sizing was found to be influenced by the fiber surface morphology.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sizing Energy Storage System for Energy Arbitrage in Extreme Fast Charging Station

This paper proposes a non-linear programming (NLP) model to optimally size the energy storage system (ESS) and obtain an optimal energy management for energy arbitrage of an extreme fast charging station (XFCS) for electric vehicles (EVs), with minimized total cost of XFCS operation and ESS investment. Different from most reported work on sizing the ESS for EV charging stations, this paper proposes a pragmatic approach to model the ESS life degradation and accurately count the ESS cycles. Moreover, this work incorporates the peak demand charges in the operational cost of the charging station which are often overlooked in the literature. The proposed model is formulated and solved using AIMMS. Finally, a thorough sensitivity analysis is performed to offer insights into how different input parameters impact the ESS sizing and savings from the energy arbitrage perspective.

25 ENERGY STORAGE↗
DOE OSTI2024

Size Up or Size Down? National Analysis of Heat Pump Sizing and Impacts

Electrification of on-site fossil fuel combustion in buildings is recognized as a key component of achieving global greenhouse gas emissions targets. Air-source heat pumps are an efficient approach for space heating electrification. However, a major barrier to heat pump adoption is the high installation cost relative to furnaces and air conditioners. Because the installation cost of heat pumps - especially cold climate models - is dependent on their size, it is important to understand the distribution of heat pump sizes using different sizing methods and factors that impact heat pump sizing. In this study, we use sub-hourly physics simulations of 550,000 statistically representative dwelling units to analyze the distribution of heat pump size in the U.S. for three different efficiency levels of heat pumps, with and without building insulation and air sealing upgrades. We will present results from the national analysis of different factors affecting heat pump sizing along with the impact of sizing decisions on upgrade costs and operating costs.

electrification↗
DOE OSTI2021

Particle Size Distribution Dynamics Can Help Constrain the Phase State of Secondary Organic Aerosol

Particle phase state is a property of atmospheric aerosols that has important implications for the formation, evolution, and gas/particle partitioning of secondary organic aerosol (SOA). In this work, we use a size-resolved chemistry and microphysics model (SOM-TOMAS), updated to include an explicit treatment of particle phase state, to constrain the bulk diffusion coefficient (Db) of SOA produced from ??- pinene ozonolysis. By leveraging data from laboratory experiments performed in the absence of a seed and under dry conditions, we find that the Db for SOA can be constrained (1-7 ×10-15 cm2 s-1 in these experiments) by simultaneously reproducing the time-varying SOA mass concentrations and the evolution of the particle size distribution. Another version of our model that used the predicted SOA composition to calculate the glass transition temperature, viscosity, and, ultimately, Db (~10-15 cm2 s-1) of the SOA was able to reproduce the mass and size distribution measurements when we included oligomer formation (oligomers accounted for about a fifth of the SOA mass). Our work highlights the potential of a size resolved SOA model to constrain the particle phase state of SOA by utilizing historical measurements of the evolution of the particle size distribution.

He, Yicong↗
DOE OSTI2025

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

X-Ray Diffraction and Electron Microscopy Studies of the Size Effects on Pressure-Induced Phase Transitions in CdS Nanocrystals

In recent years, investigations of the phase transition behavior of semiconducting nanoparticles under high pressure has attracted increasing attention due to their potential applications in sensors, electronics, and optics. However, current understanding of how the size of nanoparticles influences this pressure-dependent property is somewhat lacking. In particular, phase behaviors of semiconducting CdS nanoparticles under high pressure have not been extensively reported. Therefore, in this work, CdS nanoparticles of different sizes are used as a model system to investigate particle size effects on high-pressure-induced phase transition behaviors. In particular, 7.5, 10.6, and 39.7 nm spherical CdS nanoparticles are synthesized and subjected to controlled high pressures up to 15 GPa in a diamond anvil cell. Analysis of all three nanoparticles using in-situ synchrotron wide-angle X-ray scattering (WAXS) data shows that phase transitions from wurtzite to rocksalt occur at higher pressures than for bulk material. Bulk modulus calculations not only show that the wurtzite CdS nanomaterial is more compressible than rocksalt, but also that the compressibility of CdS nanoparticles depends on their particle size. Furthermore, sintering of spherical nanoparticles into nanorods was observed for the 7.5 nm CdS nanoparticles. Our results provide new insights into the fundamental properties of nanoparticles under high pressure that will inform designs of new nanomaterial structures for emerging applications.

Meng, Lingyao↗
DOE OSTI2026

Data for Clumping Index Estimation With 30°-tilted Cameras in Row Crops: Evaluation of Methods and Segment Size Effects

The clumping index (CI) quantifies the spatial distribution of foliage elements and is essential for accurately estimating the plant area index (PAI), canopy radiative transfer, and photosynthesis. Traditionally, the finite-length averaging method (LX), the gap size distribution method (CC), and a combined approach of CC and LX (CLX) have been applied to instruments like TRAC and digital hemispherical photography to estimate CI. However, a comprehensive evaluation of these methods in row crops remains limited, especially regarding the influence of segment size on CI. Meanwhile, digital cameras offer a cost-effective and user-friendly solution for canopy measurements in row crops, yet their application in this context remains underexplored. In this study, we employed a new approach using a 30°-tilted digital camera to estimate CI in corn and soybean fields, applying the LX, CC, and CLX methods. We systematically assessed the performance of these three methods by combining field measurements in real-world fields with simulations using the LESS 3D radiative transfer model. Our results showed that CLX applied to the whole image and 45° segment offered accurate estimation of CI (bias within ±0.1, RMSE < 0.2) and PAI (bias within ±0.4, RMSE < 1) in real-world fields and LESS simulations. The accuracy of the LX method was highly sensitive to segment size, with the best performance observed at the 15° segment (PAI bias within ±0.4). In contrast, the CC method remained stable across different segment sizes, and its performance was generally comparable to that of LX, except at the 15° segment. Across view zenith angles, CI derived from CC generally showed a continuous increase, while those from LX and CLX followed a rising trend at small zenith angles but began to decline at 68°, likely due to an increasing proportion of no-gap segments. Seasonally, LX tended to show decreasing CI during early growth stages but increased as the canopy matured, whereas CC and CLX showed gradually increasing CI before plateauing at peak PAI. The 30°-tilted camera effectively captured CI variations across different angles and growth stages, making it a practical and robust instrument for row crop canopy structure analysis. Applying these CI methods to digital cameras offers a low-cost and accessible CI estimation alternative, improving canopy structure monitoring accuracy in row crops.

Modeling↗
DOE OSTI2021

Introducing the GeoRePORT Resource Size Tool: Reporting on Geothermal Resource Size Estimations Using the Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT): Preprint

The Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT) was developed with funding from the U.S. Department of Energy Geothermal Technologies Office to assist in identifying and pursuing long-term investment strategies through the development of a resource reporting protocol. The assessment protocols used in GeoRePORT allow for comparison of project attributes across locations and geological settings to understand the feasibility of geothermal development. This work introduces the Resource Size Tool, a new feature within the GeoRePORT package that compiles two independent methods for estimating geothermal resource size in terms of energy capacity in MW. Energy production potential for twenty-three case studies was estimated with the Resource Size Tool in order to 1) generate a reasonable range of resource size estimates for a particular geothermal field; 2) illustrate the advantages and limitations of each methodology (such as data input requirements, estimate accuracy and precision, and the appropriate circumstances of use); and 3) test the ability of the resource size tool to provide useful and accurate information for geothermal stakeholders. The tool employs two methods widely used in the geothermal industry: (1) USGS Volumetric and (2) Power Density. Results from our case studies show general overlap between these two methods in terms of resource size estimates; however, they also reveal key differences between the two approaches that should be considered when using such estimates to drive development. First, the two methods rely on different input parameters and therefore one method may be more appropriate and/or accurate for a given project than the other. Second, the Power Density method was found to generate wider ranges of resource size predictions, more consistently aligning with actual power production of the field but with larger scales of error; whereas the USGS Volumetric method predicts narrower ranges but tends to overestimate when compared to current MW production. Future work will refine variables used in the methods with input data from other sections of GeoRePORT and modify uncertainty levels based on the particular datasets used for a given project.

geological↗
DOE OSTI2024

Uncovering the Size-dependent Thermal Solid Transformation of Akaganéite

Investigating the structural evolution and phase transformation of iron oxides is crucial for gaining a deeper understanding of geological changes on diverse planets and preparing oxide materials suitable for industrial applications. In this study, we employed in-situ heating techniques in conjunction with transmission electron microscopy (TEM) observations and ex-situ characterization to thoroughly analyze the thermal solid-phase transformation of akaganéite one-dimensional (1D) nanostructures with varying diameters. Our findings offer compelling evidence for a size-dependent morphology evolution in akaganéite 1D nanostructures, which can be attributed to the transformation from akaganéite to maghemite (?-Fe2O3) and subsequent crystal growth. Specifically, we observed that akaganéite nanorods with a diameter of around 50 nm transformed into hollow polycrystalline maghemite nanorods, which demonstrated remarkable stability without arresting crystal growth under continuous heating. In contrast, smaller akaganéite nanoneedles or nanowires with a diameter ranging from 20 to 8 nm displayed a propensity for forming single-crystal nanoneedles or nanowires through phase transformation and densification. By manipulating the size of the precursors, we have developed a straightforward method for the synthesis of single-crystal and polycrystalline maghemite nanowires through solid-phase transformation. These significant findings provide new insights into the size-dependent structural evolution and phase transformation of iron oxides at the nanoscale.

Wang, Xiang↗
DOE OSTI2024

Quantifying structural errors in cloud condensation nuclei activity from reduced representation of aerosol size distributions

Aerosol effects on clouds and radiation are the dominant contribution to uncertainty in radiative forcing relative to the pre-industrial atmosphere. While previous studies have assessed the impact of parametric uncertainty on modeled forcing, structural errors from the numerical representation of particle distributions have not been well quantified. Here we present a framework for quantifying error in aerosol size distributions and cloud condensation nuclei activity, which we apply to the widely used 4-mode version of the Modal Aerosol Module (MAM4). Box model predictions from the MAM4 are evaluated against the Particle Monte Carlo Model for Simulating Aerosol Interactions and Chemistry (PartMC-MOSAIC), a benchmark model that tracks the evolution of individual particles. We show that size distributions simulated by MAM4 diverge from those simulated by PartMC-MOSAIC after only a few hours of aging by condensation and coagulation in polluted conditions, which leads to large errors in modeled cloud condensation nuclei concentrations. We find that differences between MAM4 and PartMC-MOSAIC are largest under polluted conditions, where the size distribution evolves rapidly though aging by condensation of semi-volatile substances and coagulation among particles. These findings suggest that structural error in modeled aerosol properties contributes to the large inter-model variability in aerosol radiative forcing.

Fierce, Laura M.↗
DOE OSTI2022

Ab-Initio Investigation of Finite Size Effects in Rutile Titania Nanoparticles with Semilocal and Nonlocal Density Functionals

In this work, we employ hybrid and generalized gradient approximation (GGA) level density functional theory (DFT) calculations to investigate the convergence of surface properties and electronic gap of rutile titania nanoparticles with particle size. The surface energies and electronic gaps are calculated for cuboidal particles with minimum dimension ranging from 3.7 Angstrom (24 atoms) to 10.3 Angstrom (384 atoms) using a highly-parallel real-space DFT code to enable hybrid level DFT calculations of larger nanoparticles than are typically practical. We deconvolute the geometric and electronic finite size effects in surface energy, and evaluate the influence of defects on electronic gap and density of states (DOS). The electronic finite size effects in surface energy vanish when the minimum length scale of the nanoparticles becomes greater than 10 Angstrom. We show that this length scale is consistent with a computationally efficient numerical analysis of the characteristic length scale of electronic interactions. The surface energy of nanoparticles having minimum dimension beyond this characteristic length can be approximated using slab calculations that account for the geometric defects. In contrast, the finite size effects on the electronic gap and DOS is highly dependent on the shape and size of these particles. Furthermore, the DOS for cuboidal particles and more realistic particles constructed using the Wulff algorithm reveal that defect states within the electronic gap play a key role in determining the eigen value distribution of nanoparticles and the electronic gap does not converge to the bulk limit for the particle sizes investigated.

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

3D Morphology of Bimodal Porous Copper with Nano-Sized and Micron-Sized Pores to Enhance Transport Properties for Functional Applications

Multiscale porous metals with multiscale porosity from nanometer to micrometer have a high specific surface area and high effective diffusivity for ion transport, thereby enhancing functionalities and extending the applications of porous metals. Herein, the Cu–Fe–Al ternary system was selected as the precursor alloy to construct multiscale, bimodal porous copper by the chemical dealloying method. The effect of the phase composition and initial microstructure of precursor alloys (Al x Fe 75– x Cu 25 , x = 10–60) on the three-dimensional (3D) morphology of multiscale porous metals was systematically investigated, with a goal to precisely control the multiscale porous structure. The four crystal structure phases (body-centered cubic (BCC), face-centered cubic (FCC), CsCl type (B2), and monoclinic) in precursor alloys were analyzed by synchrotron X-ray diffraction refinement. The 3D morphology, feature size distribution, and tortuosity of four representative porous Cu after dealloying Al x Fe 75– x Cu 25 ( x = 10, 30, 50, and 60) precursor alloys were directly visualized and quantified via advanced synchrotron X-ray nanotomography. The relationship between the phases/crystal structures of precursor alloys and their corresponding porous morphology was established: the micron-sized pores in bimodal porous Cu are formed by dissolving the CuFeAl phase with BCC and monoclinic crystal structures, and the nano-sized pores are formed by dealloying the CuFeAl phase with FCC and B2 crystal structures. The size of the nanoporous structure depends on the ratio between the more noble and more active components in the precursor alloy, while the size of the microporous structure depends on the corresponding phase size in the precursor alloy. The tortuosity results showed that the multiscale porous structure with both nanoporosity and microporosity exhibits lower tortuosity, which will enhance transport properties for functional applications.

25 ENERGY STORAGE↗
NASA NTRS2006

Turbulent Size Selection and Concentration of Chondrule-Sized Objects: Reynolds Number Invariance and Implications

It is generally agreed that individual chondrules formed as entities in a gaseous nebula prior to being accumulated into a meteorite parent body, within which they incur various forms of modification before arriving in our labs. While there are major unanswered questions about the properties of the nebula environment in which chondrules formed, the process by which the most primitive meteorites are formed overwhelmingly from chondrules must then be an aspect of "nebula processing". Textures in certain fragments of primitive meteorites might be summarized as being primarily chondrules and clastic, chondrule-sized, fragments of other minerals, each covered with a rim of fine dust with physical and chemical properties which are essentially independent of the composition and mineralogy of the underlying chondrule. This (unfortunately rather rare) texture was called "primary accretionary texture" to reflect their belief that it precedes subsequent stages in which fragmentation, comminution, mixing, heating, and other forms of alteration occur on the parent body(-ies). The size distribution of these chondrules and fragments, and the properties of their dusty rims, are key clues regarding the primary nebula accretion process. Even in the much more abundant meteorites which have clearly suffered internal mixing, abrasion, grinding, and even mineralogical alteration or replacement (due presumably to the collisional growth and heating process itself), key chondrule properties such as mean size and density remain relatively well defined, and well defined rims persist in many cases. It has been our goal to infer the key nebula processes indirectly from the properties of these very earliest primitive meteorites by making use of a theoretical framework in which the nebula possesses a plausible level of isotropic turbulence. We have shown that turbulence has the property of concentrating one particular particle size by orders of magnitude, where the preferentially concentrated size depends primarily on the intensity of the turbulent kinetic energy (represented by the Reynolds number of the nebula). Specifically, the preferentially concentrated particle is that which has a stopping time equal to the turnover time of the smallest eddy. The intensity level of turbulence implied by chondrule sizes can be maintained by even a small fraction of the energy released by the radially evolving disk (it must be noted that the details of how this transfer of energy actually occurs remain obscure, however).

Cuzzi, J. N.↗
DOE OSTI2021

Electronic impact of Ni2P nanoparticle size on hydrogenation rates

Nickle phosphide, Ni2P, nanoparticles supported on SiO2 show a marked volcano shaped size dependence. Kinetic analysis and physicochemical characterization shows the electron density of Ni to increase with increasing Ni2P size, enhancing in turn the H2 adsorption strength. For particles below 15 nm, H adsorbs weakly causing a low surface coverage of H, gradually increasing with particle size. For large particles, hydrogen binds too strongly causing a high coverage but low catalytic activity. The remarkable size dependence of the electronic properties show that Ni2P particle size can be used to fine-tune its activity for hydrogenation.

Ni2P size effect, Electron density, H2 adsorption ↗