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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The response of stomatal conductance to seasonal drought in tropical forests

Stomata regulate CO2 uptake for photosynthesis and water loss through transpiration. The approaches used to represent stomatal conductance (gs) in models vary. In particular, current understanding of drivers of the variation in a key parameter in those models, the slope parameter (i.e. a measure of intrinsic plant water-use-efficiency), is still limited, particularly in the tropics. Here we collected diurnal measurements of leaf gas exchange and water potential (?leaf), and a suite of plant traits from the upper canopy of 15 tropical trees in two contrasting Panamanian forests throughout the dry season of the 2016 El Niño. The plant traits included wood density, leaf-mass-per-area (LMA), leaf carboxylation capacity (Vc,max25), leaf water content, the degree of isohydry, and predawn ?leaf. We first investigated how the choice of four commonly used leaf-level gs models with and without the inclusion of ?leaf as an additional predictor variable influence the ability to predict gs, and then explored the abiotic (i.e. month, site-month interaction) and biotic (i.e. tree-species-specific characteristics) drivers of slope parameter variation. Our results show that the inclusion of ?leaf did not improve model performance and that the models that represent the response of gs to vapor pressure deficit performed better than corresponding models that respond to relative humidity. Within each gs model, we found large variation in the slope parameter, and this variation was attributable to the biotic driver, rather than abiotic drivers. We further investigated potential relationships between the slope parameter and the six available plant traits mentioned above, and found that only one trait, LMA, had a significant correlation with the slope parameter (R2=0.66, n=15), highlighting a potential path towards improved model parameterization. This study advances understanding of gs dynamics over seasonal drought, and identifies a practical, trait-based approach to improve modeling of carbon and water exchange in tropical forests.

carbon and water exchange, stomatal conductance mo↗
DOE OSTI2022

Mesophyll conductance response to short-term changes in p CO 2 is related to leaf anatomy and biochemistry in diverse C 4 grasses

Mesophyll CO 2 conductance (g m ) in C 3 species responds to short-term (minutes) changes in environment potentially due to changes in leaf anatomical and biochemical properties and measurement artefacts. Compared with C 3 species, there is less information on g m responses to short-term changes in environmental conditions such as partial pressure of CO 2 (pCO 2 ) across diverse C 4 species and the potential determinants of these responses. Using 16 C 4 grasses we investigated the response of g m to short-term changes in pCO 2 and its relationship with leaf anatomy and biochemistry. In general, g m increased as pCO 2 decreased (statistically significant increase in 12 species), with percentage increases in gm ranging from +13% to +250%. Greater increase in g m at low pCO 2 was observed in species exhibiting relatively thinner mesophyll cell walls along with greater mesophyll surface area exposed to intercellular air spaces, leaf N, photosynthetic capacity and activities of phosphoenolpyruvate carboxylase and Rubisco. Species with greater CO 2 responses of g m were also able to maintain their leaf water-use efficiencies (TE i ) under low CO 2 . Our study advances understanding of CO 2 response of g m in diverse C 4 species, identifies the key leaf traits related to this response and has implications for improving C 4 photosynthetic models and TE i through modification of g m .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Mesophyll conductance and cell wall composition: insights from a meta‐analysis across species

Mesophyll conductance (g m ) plays a critical role in plant photosynthesis by regulating the diffusion of CO 2 from substomatal cavities to the site of carbon fixation within the chloroplasts. Despite its importance, our understanding of the factors influencing g m , particularly the role of cell wall properties, remains incomplete. In this issue of New Phytologist , Roig-Oliver et al. ( 2025 ; pp. 2384–2391) address this knowledge gap through a comprehensive meta-analysis across multiple species from the major clades of land plants. By analyzing trends in g m and two other key physiological parameters – the ratio of pectin to cellulose and hemicellulose in the cell wall by weight (P/(C + H)), and cell wall thickness (T cw ) – their findings reveal strong correlations of gm with the combination of P/(C + H) and T cw , where g m is directly proportional to P/(C + H) and inversely proportional to T cw . This work not only underscores the influence of cell wall composition on CO 2 diffusion but also provides a valuable framework for further experimental and modeling studies. By shedding light on the dynamic properties of cell walls, shaped by both composition and environmental regulation, this study opens new frontiers for understanding and improving photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Increased activity of core photorespiratory enzymes and CO 2 transfer conductances are associated with higher and more optimal photosynthetic rates under elevated temperatures in the extremophile Rhazya stricta

Increase photorespiration and optimising intrinsic water use efficiency are unique challenges to photosynthetic carbon fixation at elevated temperatures. To determine how plants can adapt to facilitate high rates of photorespiration at elevated temperatures while also maintaining water-use efficiency, we performed in-depth gas exchange and biochemical assays of the C 3 extremophile, Rhazya stricta. These results demonstrate that R. stricta supports higher rates of photorespiration under elevated temperatures and that these higher rates of photorespiration correlate with increased activity of key photorespiratory enzymes; phosphoglycolate phosphatase and catalase. The increased photorespiratory enzyme activities may increase the overall capacity of photorespiration by reducing enzymatic bottlenecks and allowing minimal inhibitor accumulation under high photorespiratory rates. Additionally, we found the CO 2 transfer conductances (stomatal and mesophyll) are re-allocated to increase the water-use efficiency in R. stricta but not necessarily the photosynthetic response to temperature. These results suggest important adaptive strategies in R. stricta that maintain photosynthetic rates under elevated temperatures with optimal water loss. The strategies found in R. stricta may inform breeding and engineering efforts in other C 3 species to improve photosynthetic efficiency at high temperatures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Projection-Based Model Reduction for Coupled Conduction—Enclosure Radiation Systems

We report a projection-based reduced order model (pROM) methodology has been developed for transient heat transfer problems involving coupled conduction and enclosure radiation. The approach was demonstrated on two test problems of varying complexity. The reduced order models demonstrated substantial speedups (up to 185×) relative to the full order model with good accuracy (less than 3% L ∞ error). An attractive feature of pROMs is that there is a natural error indicator for the ROM solution: the final residual norm at each time-step of the converged ROM solution. Using example test cases, we discuss how to interpret this error indicator to assess the accuracy of the ROM solution. The approach shows promise for many-query applications, such as uncertainty quantification and optimization. The reduced computational cost of the ROM relative to the full-order model (FOM) can enable the analysis of larger and more complex systems as well as the exploration of larger parameter spaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Specific conductivity, pH, dissolved oxygen, water temperature, alkalinity and sulfide in-situ data; Slate River floodplain, Crested Butte, CO; May 2020-October 2020

This data package includes a time-series of field measurements from May to October 2020 in groundwater and surface water from the Slate River floodplain in Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The data packade includes 6 data files, one for each measured variable: specific conductivity, pH, dissolved oxygen, water temperature, alkalinity and sulfide. All measurements were recorded in the field immediately after water sampling. Groundwater samples were extracted from a network of installed rhizons (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the floodplain. In addition to the data files, there is a terminology file explaining the terms used, a file level metadata file, and a sensor file with metadata about the sensors used.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Specific conductivity, pH, dissolved oxygen, water temperature and alkalinity in-situ data; Slate River floodplain, Crested Butte, CO; March 2021-October 2021

This data package includes a time-series of field measurements from March to October 2021 in groundwater and surface water from the Slate River floodplain in Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The data package includes 5 data files, one for each measured variable: specific conductivity, pH, dissolved oxygen, water temperature and alkalinity. All measurements were recorded in the field immediately after water sampling. Groundwater samples were extracted from a network of installed rhizons (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the floodplain. In addition to the data files, there is a terminology file explaining the terms used, a file level metadata file, and a sensor file with metadata about the sensors used.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Temporal Study 2022-2024: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, Turbidity, Chlorophyll A, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin in Washington, USA

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides periodic (bi-weekly or monthly) in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata collected at six sites across the Yakima River Basin in Washington, USA. Sample and sensor data from previous years (2021-2022) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054, respectively. Related sample data from 2022-2024 are available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2562910. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions This dataset contains a folder of environmental context photographs and videos and (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) field protocols; (6) international generic sample number (IGSN) mapping file; (7) handheld sensor data; and (8) two sensor subfolders. Each sensor subfolder (BarotrollAtm and MantaRiverData) contains a subfolder containing sensor time series data and plots. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL sensor pressure and air temperature data. The MantaRiverData subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and chlorophyll A. All files are .csv, .pdf, .jpg, .jpeg, .mp4, .png, or .mov.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Monitoring accelerated alkali-silica reaction in concrete prisms with petrography and electrical conductivity measurements

We report deterioration of concrete due to alkali-silica reaction (ASR) involves a reaction between alkaline ions in the cement pore solution and non-crystalline silica found in many aggregates. Diagnosing and quantifying deterioration due to ASR in concrete currently requires destructive testing for microscopy examinations. In this paper, electrical conductivity is investigated qualitatively as an alternative non-destructive evaluation (NDE) method of ASR in hardened concrete. The study was performed using an unrestrained set of small concrete prism specimens made with highly reactive small aggregates, and kept in an environmental chamber according to ASTM C1293 standard. In a companion study, destructive petrography and damage rating index (DRI) assessment, and pore solution extraction and analysis were performed on the same set of accelerated ASR specimens. The results show that temporal evolution of nondestructive bulk resistivity is linearly correlated with destructive DRI score.

36 MATERIALS SCIENCE↗
DOE OSTI2021

NETL Electrical Conductivity Relaxation(ECR) Analysis Tool

This application was developed within the solid oxide fuel cell (SOFC) work plan. It calculates the oxygen surface exchange coefficient (k) and oxygen diffusion coefficient (D) for an oxide sample using electrical conductivity relaxation (ECR) data. The tool also produces a heat map showing the associated uncertainty in fitting the ECR data for given pairs of k and D values, so the user can determine the most likely range of k and D values for the tested values. Multiple datasets for the same material can be plotted to decrease uncertainty. The tool can also simulate ECR curves for inputted k and D values and overlay the simulated curves with experimental data for comparison.

electrical conductivity relaxation↗
DOE OSTI2021

Preprocessing for Unintended Conducted Emissions Classification with ResNet

Characterization of Unintended Conducted Emissions (UCE) from electronic devices is important when diagnosing electromagnetic interference, performing nonintrusive load monitoring (NILM) of power systems, and monitoring electronic device health, among other applications. Prior work has demonstrated that UCE analysis can serve as a diagnostic tool for energy efficiency investigations and detailed load analysis. While explaining the feature selection of deep networks with certainty is often not fully comprehensive, or in other applications, quite lacking, additional tools/methods for further corroboration and confirmation can help further the understanding of the researcher. This is true especially in the subject application of the study in this paper. Often the focus of such efforts is the selected features themselves, and there is not as much understanding gained about the noise in the collected data. If selected feature and noise characteristics are known, it can be used to further shape the design of the deep network or associated preprocessing. This is additionally difficult when the available data are limited, as in the case which the authors investigated in this study. Here, the authors present a novel work (which is a proposed complementary portion of the overall solution to the deep network classification explainability problem for this application) by applying a systematic progression of preprocessing and a deep neural network (ResNet architecture) to classify UCE data obtained via current transformers. By using a methodical application of preprocessing techniques prior to a deep classifier, hypotheses can be produced concerning what features the deep network deems important relative to what it perceives as noise. For instance, it is hypothesized in this particular study as a result of execution of the proposed method and periodic inspection of the classifier output that the UCE spectral features are relatively close to each other or to the interferers, as systematically reducing the beta parameter of the Kaiser window produced progressively better classification performance, but only to a point, as going below the Beta of eight produced decreased classifier performance, as well as the hypothesis that further spectral feature resolution was not as important to the classifier as rejection of the leakage from a spectrally distant interference. This can be very important in unpredictable low-FNR applications, where knowing the difference between features and noise is difficult. As a side-benefit, much was learned regarding the best preprocessing to use with the selected deep network for the UCE collected from these low power consumer devices obtained via current transformers. Baseline rectangular windowed FFT preprocessing provided a 62% classification increase versus using raw samples. After performing a more optimal preprocessing, more than 90% classification accuracy was achieved across 18 low-power consumer devices for scenarios in which the in-band features-to-noise ratio (FNR) was very poor.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Thermally Conductive Backsheets (TCB) of PV Modules: Positive Impacts on Performance, Lifetime and LCOE

The operating temperatures of photovoltaic (PV) modules can be impacted by the selection of specific packaging materials, e.g., backsheets and encapsulants. This research focuses on the evaluation of operating temperature reduction of one-cell modules by comparing conventional Tedlar/polyester/Tedlar (TPT) backsheet with novel thermally conductive backsheets (TCBs) materials. A large number of one-cell modules with two TCB types (TCB_A and TCB_B) and baseline TPT type were fabricated and installed in three different climatic conditions of the hot-dry desert in Arizona (high and low wind speed locations) and North Carolina (temperate with low wind speed location). In this study, these two TCBs were compared with conventional TPT backsheet in terms of performance, lifetime and levelized cost of energy (LCOE). The field results were analyzed for thermal performance of TCBs compared to TPT at three sites for two and half years. This study concludes that the thermal and electrical performances of the PV modules can be improved by using TCB_A in hot and dry climate sites and TCB_B at temperate climate sites. Therefore, the lifetime of TCB-based modules is expected to be higher than TPT-based modules. Using backsheet-specific power degradation levels and assuming the same cost for both types of backsheets, the LCOE of modules using TCBs is estimated to be lower than that of TPT.

14 SOLAR ENERGY↗
DOE OSTI2024

An Electrical Resistance Diagnostic for Conductivity Monitoring in Laser Powder Bed Fusion

With the growing interest in metal additive manufacturing using laser powder bed fusion (LPBF), there is a need for advanced in-situ nondestructive evaluation (NDE) methods that can dynamically monitor manufacturing process-related variations, that can be used as a feedback mechanism to further improve the manufacturing process, leading to parts with improved microstructural properties and mechanical properties. Current NDE techniques either lack sensitivity beyond build layer, are costly or time-consuming, or are not compatible for in-situ integration. In this research, we develop an electrical resistance diagnostic for in-situ monitoring of powder fused regions during laser powder bed fusion printing. The technique relies on injecting current into the build plate and detecting voltage differences from conductive variations during printing using a simple, cheap four-point electrode array directly connected to the build plate. A computational model will be utilized to determine sensitivities of the approach, and preliminary experiments will be performed during the printing process to test the overall approach.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Investigation of Failure Modes, Mechanisms and Driving Forces for Electrically Conductive Adhesives as Interconnects in PV Modules

In this work we describe our current progress into investigating the reliability of ECA interconnects for PV modules. Preliminary thermal cycling experiments demonstrated that both cohesive and adhesive failure of the ECA joint are relevant failure modes that result in an increase of the joints electrical resistance. A thorough viscoelastic characterization of the candidate ECA was conducted to enable accurate numerical modeling of the joint’s response to thermal cycling. Combined with critical and subcritical fracture measurements, the numerical model elucidates that an additional fatigue mechanism exists which can result in fracture well below subcritical debonding threshold values. It is also demonstrated that fracture of the ECA is more sensitive to humidity than temperature and subcritical debonding mechanisms do exist which are again more sensitive to humidity.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

In Situ Formation of Li 3 P Layer Enables Fast Li + Conduction across Li/Solid Polymer Electrolyte Interface

Abstract Solid‐state polymer electrolytes provide better flexibility and electrode contact than their ceramic counterparts, making them a worthwhile pursuit for all‐solid‐state lithium‐metal batteries. However, their large Li/solid state electrolyte interfacial resistance, small critical current density, and rapid lithium dendrite growth during cycling still limit their viability. Owing to these restrictions, all‐solid‐state cells with solid polymer electrolytes must be cycled above room‐temperature and with a small current density. These problems can be mitigated with an in situ formed artificial solid electrolyte interphase that rapidly conducts Li + ions. Herein, a Li 3 P layer formed in situ at the Li‐metal/solid polymer electrolyte interphase is reported that significantly reduces the electrode/electrolyte interfacial resistance. Additionally, this layer increases the wettability of the solid polymer by the metallic lithium anode, allowing for the critical current density of lithium symmetric cells to be doubled by homogenizing the current density at the interface. All‐solid‐state Li/Li symmetric cells and Li/LiFePO 4 cells with the Li 3 P layer show improved cycling performance with a high current density.

Wu, Nan↗
DOE OSTI2021

Roadmap for Sustainable Mixed Ionic–Electronic Conducting Membranes

Mixed ionic-electronic conducting (MIEC) membranes have gained growing interest recently for various promising environmental and energy applications, such as H 2 and O 2 production, CO 2 reduction, O 2 and H 2 separation, CO 2 separation, membrane reactors for production of chemicals, cathode development for solid oxide fuel cells, solar-driven evaporation and energy-saving regeneration as well as electrolyzer cells for power-to-X technologies. The purpose of this roadmap, written by international specialists in their fields, is to present a snapshot of the state-of-the-art, and provide opinions on the future challenges and opportunities in this complex multidisciplinary research field. As the fundamentals of using MIEC membranes for various applications become increasingly challenging tasks, particularly in view of the growing interdisciplinary nature of this field, a better understanding of the underlying physical and chemical processes is also crucial to enable the career advancement of the next generation of researchers. As an integrated and combined article, it is hoped that this roadmap, covering all these aspects, will be informative to support further progress in academics as well as in the industry-oriented research toward commercialization of MIEC membranes for different applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ultra-Stretchable, Ionic Conducting, Pressure-Sensitive Adhesive with Dual Role for Stable Li-Metal Batteries

The practical application of lithium (Li) metal battery is impeded by the Li dendrite growth and unstable solid electrolyte interphase (SEI) layer. Herein, an ultra-stretchable and ionic conducting chemically crosslinked pressure-sensitive adhesive (cPSA) synthesized via the copolymerization of 2-ethylhexyl acrylate and acrylic acid with poly(ethyleneglycol)dimethacrylate as crosslinker (short for 70cPSA), is developed as both artificial SEI layer and solid polymer electrolyte (SPE) for stable Li-metal electrode, enabling all-solid-state Li metal batteries with excellent cycling performance. As an artificial SEI layer, the 70cPSA-modified electrodes exhibit excellent electrochemical performance in Li|70cPSA@Cu half cells and 70cPSA@Li|70cPSA@Li symmetric cells. In full cells with LiFePO 4 (LFP) as cathode, the 70cPSA@Li|LFP cell exhibits stable cycling performance over 250 cycles. Utilized as SPE, the all-solid-state Li|SPE|LFP cell delivers excellent cycling stability with a capacity retention of 86% over 500 cycles. With high-voltage LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) as cathode, the Li|SPE|NMC811 cell exhibits a discharge capacity of 124.3 mAh g -1 with a capacity retention of 71% after 200 cycles. Furthermore, the rational design of PSAs and investigation of their dual role for stable and safe Li-metal batteries may shed a light on adhesive polymers for battery applications.

25 ENERGY STORAGE↗