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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Tailoring the rheological properties of high protein suspension by thermal-mechanical treatment

The viscoelasticity of concentrated protein suspensions associates closely with the mixing efficiency and cleaning frequency of facility during high-protein food development. This study investigated the effects of thermal-mechanical treatment on the viscoelasticity of milk protein isolate (MPI) suspensions and their underlying mechanisms to develop protein ingredient with low viscoelasticity. MPI suspensions (20%) were treated at 25, 50 and 85°C for 10-60 min under constant shear (100 s -1 ), followed by storage at 4°C. The viscosity (η) of MPI suspension treated at 50°C and 85°C was similar to 1-10% as those treated at 25 ° C. After four days of storage at 4°C, η showed the least value in 50°C-treated samples compared to those at 25 ° C and 85 ° C. The η and storage modulus (G') was decreased with prolonged treatment at 25 and 50°C, whereas opposite trend was found in 85°C treated samples. Differential scanning calorimetry found proteins in 50°C treated samples had smaller enthalpy than those in the control and 25°C treated samples. Protein surface hydrophobicity was increased slightly from 25°C to 50°C, but remarkably in 85°C treated samples. Ultra-small angle x-ray scattering showed the radius of gyration (R-g) of casein micelle was similar to 38 nm at 25°C and 50°C treated samples but increased to similar to 44 nm 85°C treated samples with reduced compactness. A new sphere-like structure with R-g of 18 nm was generated in 85°C treated samples. These findings suggested modulating temperature during thermal-mechanical treatment is essential to alter protein structures and morphology for desirable rheological properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Feature review of photovoltaic modeling software utilizing blind performance assessment

While confidence in photovoltaic (PV) modeling software has always been essential, the rapid pace of new PV plant developments makes accuracy and credibility more critical than ever. Independent assessments, particularly through blind modeling comparisons, are therefore necessary to ensure unbiased benchmarking across PV modeling software. Previous studies have been limited by a narrow range of models compared, anonymized results, or system size. This study presents results from the first-ever onymous blind modeling comparison, evaluated using both lab- and utility-scale fixed-tilt, monofacial, south-facing systems at sub-hourly time intervals. Seven commercially used PV software tools were compared: 3E SynaptiQ, PlantPredict, PVsyst, RatedPower, SAM, SolarFarmer, and Solargis Evaluate. Predictions were submitted directly by software representatives, providing unique insights into each software’s implementation and resulting prediction behavior. Notable features, including plane-of-array (POA) transposition model, module temperature model, shading model, and performance model were analyzed and compared. Four summary tables compile these features of the software, serving as a resource to help users understand the methodological differences and select the most suitable software for their applications. The software tools show deviations from mean error in annual yield up to 2.5 % in the lab-scale system, increasing to 6.0 % for the utility-scale system. These differences arise from a combination of user decisions and the inherent behavior of the software, indicating the need for continuous and rigorous validation of modeling methods using these software tools against complex, real-world systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Suggested Modifications for Bifacial Capacity Testing

Capacity tests such as those described in ASTM 2848 and IEC 61724-2 are widely used during the contracting and acceptance testing of photovoltaic systems. With the increasing deployment of bifacial photovoltaic modules, there is a need to develop a standardized approach to capacity test these systems. Although variability and bias error were inherently higher for the measured capacity of bifacial systems, they could be reduced to a level consistent with the monofacial reference system by appropriate incorporation of rear irradiance—either measured or modeled. Three field installations provided bifacial system capacity that was measured with a mean bias error and standard deviation within 1% over the 2–10-month observation period. Capacity test accuracy could be improved further by using the measured back-of-module temperature and the IEC 61724-2 test method for well curated systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2024

Artificial Replication of Field Soiling Losses on PV Modules

In this paper, we experimentally demonstrate an improved replication of field soiling losses using an indoor artificial soiling chamber and tests on anti-soiling coated PV modules and coupons. The primary focus is to use site-specific soil collected from module surface and replicate the natural soiling processes including dust concentration in the air, slow and gradual dust accumulation and sedimentation on the module surface during the dominant soiling season of the site of interest. The experiments were conducted on two sample sets having different anti-soiling properties. The first set contains commercial modules with two different surface properties retrieved after three years of exposure from a single PV plant in a mid-Atlantic location; the other set contain glass coupons with three different coating materials that were installed and exposed over 4 months, at Lemoore, California. Major field-representative factors considered here for the close replication in the chamber include: the use of dust collected from modules surfaces at the outdoor sites to give the same dust chemistry; dust particle size distribution and concentration; the charge size of dust (< 0.15 g per injection); field humidity, and module temperature. The effectiveness of antisoiling coatings (or surface properties) for both sample sets were ranked in the artificial testing and were found to be closely matching with the field rank orders of the respective sites and sample sets. This paper provides the rank ordering results to objectively demonstrate the replication of field soiling losses in the artificial soiling chamber.

artificial soiling↗
DOE OSTI2024

An experimentally validated electro-thermal EV battery pack model incorporating cycle-life aging and cell-to-cell variations

Lithium-ion batteries are used in a wide variety of applications. To meet the power and energy demands of these applications battery packs are composed of hundreds to thousands of cells. The electrical and thermal interactions between cells introduce additional complexity in the pack dynamics. To capture these effects, a battery pack model composed of 192 cells based on a first-generation (2012) Nissan Leaf battery pack is developed in MATLAB/Simulink/Simscape. Here, with this model, we simulate the electrical dynamics (using a first-order equivalent-circuit model), the thermal dynamics (using a first-order lumped-parameter thermal model), and the aging dynamics (using a semi-empirical severity factor-based model) of every cell in the pack and we also create a pack thermal model that explicitly captures the heat exchange between the modules, and the cells contained within, during operation. The models are calibrated and validated, both at the cell and pack level, with experimental data. Two different case studies of this pack model are investigated. In the first case study, an initial, normally-distributed, cell-to-cell capacity variation is introduced and its effect on the pack voltage and module temperatures is studied. In the second case study, we deliberately insert cells with lower than nominal capacity into the pack and we investigate how this type of initial cell-to-cell capacity variation affects the pack’s ability to deliver energy over time. Finally, we also study how parallel-connected cells can reduce the effects of cell-to-cell variations at the expense of increased aging of the pack overall.

25 ENERGY STORAGE↗
DOE OSTI2022

Liquid fragility maximum in lithium borate glass‐forming melts related to the local structure

Abstract The structure of liquid lithium pyroborate, Li 4 B 2 O 5 ( J = Li/B = 2), has been measured over a wide temperature range by high‐energy X‐ray diffraction, and compared to that of its glass and borate liquids of other compositions. The results indicate a gradual increase in tetrahedral boron fraction from 3(1)% to 6(1)% during cooling from T = 1271(15) to 721(8) K, consistent with the larger N 4 = 10(1)% found for the glass, and literature 11 B nuclear magnetic resonance measurements. van't Hoff analysis based on a simple boron isomerization reaction BØ 3 O 2 – ⇌ BØO 2 2– yields Δ H = 13(1) kJ mol –1 and Δ S = 40(1) J mol –1 K –1 for the boron coordination change from 4 to 3, which are, respectively, smaller and larger than found for singly charged isomers for J ≤ 1. With these, we extend our model for N 4 ( J , T ), nonbridging oxygen fraction f nbr ( J , T ), configurational heat capacity , and entropy S conf ( J , T ) contributions up to J = 3. A maximum is revealed in at J = 1, and shown semi‐quantitatively to lead to a corresponding maximum in fragility contribution, akin to that observed in the total fragilities by temperature‐modulated differential scanning calorimetry. Lithium is bound to 4.6(2) oxygen in the pyroborate liquid, with 2.7(1) bonds centered around 1.946(8) Å and 1.9(1) around 2.42(1) Å. In the glass, n LiO = 5.4(4), the increase being due to an increase in the number of short Li–O bonds.

36 MATERIALS SCIENCE↗
DOE OSTI2024

PV Performance Modeling and Stakeholder Engagement (Final Technical Report)

This core capability project’s objective is to increase the value of photovoltaic (PV) performance models by improving their functionality, demonstrating, and quantifying their validity, and offering a wide range of stakeholder engagement opportunities. In FY22-24, we developed new and improved modeling algorithms and functions to represent PV performance more accurately in a variety of environments and conditions. The “Model parameter toolkit” was developed and includes functions to translate between different module temperature models, incidence angle modifier models, and single-diode models. A new modeling capability named “PV Atlas” was also developed leveraging Sandia’s High Performance Computing resources. This capability allows us to investigate several questions and provide climate-specific best practices and geographic data files; all these are hosted on an interactive website on Sandia’s GitHub and can be used for training, system optimization, or to provide best practices for uncertainty reduction. For model validation, we published high-quality PV performance, and weather data; these data are well documented, filtered, and processed for quality and include examples on how to run PV simulations. We also developed well documented, standardized methods for validating PV models and ran independent model validation and 2 blind modeling intercomparisons engaging with 49 organizations from 17 countries. We co-led and contributed to a growing, well documented and maintained suite of open-source functions for PV modeling (i.e., the pvlib-python) and we outreached to the PV modeling stakeholders via the PVPMC workshops and web resources. In addition, this project supported US representation and leadership for the International Energy Agency (IEA) PVPS Task 13; specifically, members of our team led and supported 3 subtasks on: 1) Best practices for the optimization of bifacial photovoltaic tracking, 2) Extreme weather events and their multiple impact on PV power plants: Risks, failure mechanisms and mitigation strategies, and 3) Best practice guidelines for the use of economic and technical Key Performance Indicators (KPIs). This project resulted in the publications of 14 peer reviewed journal papers, 37 conference presentations, 6 SAND reports, 5 public datasets and 6 new webpages on the PVPMC website. It supported the release of 13 pvlib-python versions where 28 enhancements were from this PV Performance Modeling project. We co-organized 5 PVPMC workshops in FY22-24 with the participation of 214 unique institutions and around 700 participants. The PVPMC website was redesigned, and its reliability was improved; it receives over 50,000 visitors/year from 202 unique countries.

14 SOLAR ENERGY↗
DOE OSTI2023

PV Performance Modeling - Data and Resources

The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. This dataset includes seven MS-Excel sheets with instructions, notes and all necessary data (weather, irradiance, temperature, power) used for the data analysis of the blind modeling comparison. The hourly data represent six different systems from Albuquerque, NM and Roskilde, Denmark over a period of one year. These data are useful for PV performance model validation studies.

14 SOLAR ENERGY↗
DOE OSTI2020

Scanning tunneling thermometer

Various examples are provided related to scanning tunneling thermometers and scanning tunneling microscopy (STM) techniques. In one example, a method includes simultaneously measuring conductance and thermopower of a nanostructure by toggling between: applying a time modulated voltage to a nanostructure disposed on an interconnect structure, the time modulated voltage applied at a probe tip positioned over the nanostructure, while measuring a resulting current at a contact of the interconnect structure; and applying a time modulated temperature signal to the nanostructure at the probe tip, while measuring current through a calibrated thermoresistor in series with the probe tip. In another example, a device includes an interconnect structure with connections to a first reservoir and a second reservoir; and a scanning tunneling probe in contact with a probe reservoir. Electrical measurements are simultaneously obtained for temperature and voltage applied to a nanostructure between the reservoirs.

Chinivaranahalli Shastry, Abhay Shankar↗
DOE OSTI2022

Scanning tunneling thermometer

Various examples are provided related to scanning tunneling thermometers and scanning tunneling microscopy (STM) techniques. In one example, a method includes simultaneously measuring conductance and thermopower of a nanostructure by toggling between: applying a time modulated voltage to a nanostructure disposed on an interconnect structure, the time modulated voltage applied at a probe tip positioned over the nanostructure, while measuring a resulting current at a contact of the interconnect structure; and applying a time modulated temperature signal to the nanostructure at the probe tip, while measuring current through a calibrated thermoresistor in series with the probe tip. In another example, a device includes an interconnect structure with connections to a first reservoir and a second reservoir; and a scanning tunneling probe in contact with a probe reservoir. Electrical measurements are simultaneously obtained for temperature and voltage applied to a nanostructure between the reservoirs.

Chinivaranahalli Shastry, Abhay Shankar↗
DOE OSTI2023

Potential Vorticity Dynamics Explain How Extratropical Oceans and the Arctic Modulate Wintertime Land–Temperature Variations

Temperature variations across the continental northern hemisphere at the interdecadal scale are thought to be remotely modulated by oceanic internal climate variability and the Arctic. Nevertheless, further elucidating the dynamics is essential for clarifying ongoing debates. We show that potential vorticity (PV) dynamics provide a concise explanation for these teleconnections. Our findings demonstrate that extratropical oceans and the Arctic can remotely modulate the wintertime continental temperature variations by stimulating PV anomalies, which are constrained by climatological PV gradients and jet streams. A causal explanation includes anomalous temperature and precipitation over oceans and the Arctic inducing local PV anomalies via diabatic heating. Subsequently, meridional and downstream advection distributes the anomalous PV to remote land regions where the climatological PV gradients are strong, that is, involving PV fronts, as well as jet streams; therefore, PV fronts and jet streams jointly indicate land regions that are largely and frequently impacted. However, land can also modulate other regions through the same mechanism when variations over land occur in advance. Clear causality depends on which factor is independent, while interactions among those regions may convolute the causality, thereby causing further debates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Cold-Starting All-Solid-State Batteries from Room Temperature by Thermally Modulated Current Collector in Sub-Minute

All-solid-state batteries (ASSBs) show great potential as high-energy and high-power energy storage devices but their attainable energy/power density at room temperature is severely reduced because of the sluggish kinetics of lithium-ion transport. Here we first reported a thermally modulated current collector (TMCC), which can rapidly cold-start ASSBs from room temperature to operating temperatures (70–90 °C) in less than one minute, and simultaneously enhance the transient peak power density by 15-fold compared to one without heating. This TMCC is prepared by integrating a uniform, ultrathin (~200 nm) nickel layer as a thermal modulator within an ultralight polymer-based current collector. By isolating the thermal modulator from the ion/electron pathway of ASSBs, it can provide fast, stable heat control yet does not interfere with regular battery operation. Moreover, this ultrathin (13.2 μm) TMCC effectively shortens the heat transfer pathway, minimizes heat losses, and mitigates the formation of local hot spots. The simulated heating energy consumption can be as low as ~3.94% of total battery energy. This TMCC design with good tunability opens new frontiers towards smart energy storage devices in the future from the current collector perspective.

25 ENERGY STORAGE↗
DOE OSTI2023

Land surface dynamics and meteorological forcings modulate land surface temperature characteristics

This study examines the effect of land cover, vegetation health, climatic forcings, elevation heat loads, and terrain characteristics (LVCET) on land surface temperature (LST) distribution over West Africa (WA). We employ fourteen machine-learning models, which preserve nonlinear relationships, to downscale LST and other predictands while preserving the geographical variability of WA. Our results showed that the random forest model performs best in downscaling predictands. This is important for the sub-region since it has limited access to mainframes to power multiplex machine-learning algorithms. In contrast to the northern regions, the southern regions consistently exhibit healthy vegetation. Also, areas with unhealthy vegetation coincide with hot LST clusters. The positive Normalized Difference Vegetation Index (NDVI) trends in the Sahel underscore rainfall recovery and subsequent Sahelian greening. The southwesterly winds cause the upwelling of cold waters, lowering LST in southern WA and highlighting the cooling influence of water bodies on LST. Identifying regions with elevated LST is paramount for prioritizing greening initiatives, and our study underscores the importance of considering LVCET factors in urban planning. Topographic slope-facing angles, heat loads, and diurnal anisotropic heat all contribute to variations in LST, emphasizing the need for a holistic approach when designing resilient and sustainable landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

CsbZIP2-miR9748-CsNPF4.4 Module Mediates High Temperature Tolerance of Cucumber Through Jasmonic Acid Pathway

High temperature stress seriously affects the growth of cucumber seedlings, and even leads to a decline in yield and quality. miRNAs have been shown to be involved in regulating the response to stress in plants, but little is known about its effects on cucumber high temperature stress tolerance. Here, we found that high temperature stress induced the expression of miR9748 in cucumber. Overexpression of cucumber miR9748 in Arabidopsis improved high temperature tolerance. Transcriptome analysis revealed that miR9748 might mediate high temperature tolerance through plant hormone signal pathway. 5′ RNA ligase-mediated rapid amplification of cDNA ends (5′ RLM-RACE) and transient transformation technology demonstrated that CsNPF4.4 was the target gene of miR9748. CsNPF4.4 overexpression plants decreased high temperature tolerance accompanied by reducing the content of jasmonic acid (JA), but alleviated by foliar application of methyl jasmonate, indicating that CsNPF4.4 negatively regulated high temperature stress tolerance through inhibition JA signal pathway. Furthermore, high temperature stress also increased the expression level of CsbZIP2 . Yeast one-hybrid and dual-luciferase assays showed that CsbZIP2 directly bound to the promoter of MIR9748 to induce its expression. Taken together, our results indicated that CsbZIP2 directly regulated miR9748 expression to cleave CsNPF4.4 to mediate high temperature tolerance through JA pathway.

Li, Lan↗
DOE OSTI2026

Testing and Modeling of Subscale Ice-on-Coil Module as Low Temperature Reservoir for sCO2 based Pumped Thermal Energy Storage Systems

Echogen tested approximately 10 kWthsubscale IOC system in their lab in Akron, OH for studying the feasibility, endurance and performance impact of the technology on PTES system. This paper discusses the test loop setup, testing and results from this sub-scale IOC testing. Along with testing, the project team also developed sub-scale IOC transient model. The paper discusses this transient model development and its validation against the test data.

Avadhanula, Vamshi Krishna [Echogen Power Systems ↗
DOE OSTI2022

Disentangling the mechanism of temperature and water vapor modulation on ozone under a warming climate

Temperature and water vapor have been considered as important factors affecting ozone concentrations, however, their synergistic effect on ozone, as well as its response to a warming climate remains unclear. Here, numerical experiments with different combinations of climate and emissions highlighted opposite changes of annual ozone over the contiguous U.S. under scenarios with high vs. low ozone precursor emissions in the future with warming. Comparing the occurrence of heat waves on higher vs. lower ozone days, we found significant suppression of the heat wave exacerbation of ozone by anthropogenic emissions reductions. Variations of ozone with temperature (T) and water vapor (Q) over the western U.S. and southeastern U.S. in the simulations are clearly revealed through the construction of an O 3 -T-Q diagram. Based on the diagram, we further identified a T-dominant regime at higher temperatures where ozone increases with temperature increase, and a Q-dominant regime at lower temperatures where ozone decreases with temperature increase due to the negative effect of water vapor. With larger anthropogenic emission reductions, ozone may increase at a lower rate with temperature in the T-dominant regime, or even decrease with temperature in the Q-dominant regime. Our results show that with large emission reductions, substantial ozone pollution due to warming and increasing heat waves may be counteracted by water vapor, partly turning the ‘climate penalty’ on ozone into ‘climate benefit’. Hence controlling anthropogenic emissions may be an increasingly important strategy in a warmer and wetter climate to improve air quality and public health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A New Approach to Indoor Characterization of PV Module Energy Yield Parameters

Temperature and solar irradiance are among the most relevant parameters that affect the energy yield of photovoltaic cells and modules. A rise in the module temperature leads to a significant decrease in the open circuit voltage and a small increase in the short circuit current. Here we use a new tool to determine temperature coefficients as well as to assess power rating of multi c-Si, mono c-Si, CdTe, and CIGS-based PV modules in controlled indoor conditions per IEC 60891 and IEC 61853-1. We use the tool to explore how nonuniformities in module temperature affect the accuracy of the temperature coefficients.

14 SOLAR ENERGY↗
DOE OSTI2021

Thermal model to quantify the impact of sub-bandgap reflectance on operating temperature of fielded PV modules

Minimizing module heating is an effective way to increase the lifetime energy output of photovoltaic systems. Maximizing the reflection of light that is unusable for energy conversion is one of the most promising ways to reduce the operating temperature of fielded modules. We derive a model based on a steady-state energy balance to quantify the temperature benefit of cell or module optical modifications aimed at improving reflection of light with photon energies below the photovoltaic cell bandgap energy. This more detailed model is then simplified so that, from outdoor measured data, temperature differences arising from reflectance can be isolated from those arising from irradiance, wind speed, and module standard-test-condition efficiency.

14 SOLAR ENERGY↗