Search NASA⌕ Search

SEARCH · Search NASA

Results for “R2)”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

Solvent for non-aqueous battery

A solvent useful for lithium batteries comprises a compound of Formula (I): (R1)(R2)(R3)Si—R4—O—C(O)—[(O—R5)n—(O—C(O)]m—O—R6—X1. Each of R1 and R2 independently is alkyl; R3 is alkyl, —X2—Si(R7)(R8)(R9), or —CH2—O—C(O)—O—R10; X1 is H or —Si(R11)(R12)(R13); each of R4 and R6 independently is alkylene; each R5 independently is C2 to C6 alkylene; each of R7, R8, R9, and R10 independently is alkyl; X2 is O or alkylene; each of R11 and R12 independently is alkyl; R13 is alkyl or —X3—Si(R14)(R15)(R16); each of R14, R15, and R16 independently is alkyl; X3 is O or alkylene; m is 0 or 1, and n is 1-3; and when m is 0 and R3 is alkyl, X1 is —Si(R11)(R12)(R13). Also described is a method for manufacturing a compound of Formula (II): (R17)(R18)(R19)Si—CH2—O—C(O)—O—R20 where each R17, R18, R19, and R20 is alkyl.

25 ENERGY STORAGE↗

Stable fluorinated alkylated lithium malonatoborate salts for lithium-ion battery applications

The invention is directed in a first aspect to electrolyte salt of the general formula Li+Z−, wherein Z− has the following chemical formula: wherein R1 is an alkyl group (R′) containing at least one and up to twelve carbon atoms, and R2 and R3 are independently selected from fluorine atom, hydrocarbon groups R, alkoxy groups (—OR), and ester groups —OC(O)R, wherein R2 and R3 can optionally interconnect via R functionalities to form a boron-containing ring. The invention is also directed to electrolyte compositions in which the above electrolyte salt is incorporated. The invention is further directed to lithium-ion batteries containing these electrolytes.

Sun, Xiao-Guang↗

High solubility thioether quinones

Substituted hydroquinones and quinones and methods of synthesizing such compounds are disclosed herein. The substituted hydroquinones have the formula: while the substituted quinones have the corresponding oxidized structure (1,4-benzoquinones). One, two, three, or all four of R1, R2, R3 and R4 comprise a thioether moiety and a sulfonate moiety, and wherein each R1, R2, R3 and R4 that does not comprise a thioether and a sulfonate moiety sulfonate moiety is independently a hydrogen, an alkyl or an electron withdrawing group. The substituted hydroquinones and quinones are soluble in water, stable in aqueous acid solutions, and have a high reduction potential in the oxidized form. Accordingly, they can be used as redox mediators in emerging technologies, such as in mediated fuel cells or organic-mediator flow batteries.

Stahl, Shannon S.↗

Lipophilic diglycolamide compounds for extraction of rare earth metals from aqueous solutions

A method for extracting rare earth metals (e.g., lanthanides and/or actinides) from aqueous solution, the method comprising: (i) acidifying an aqueous solution containing said rare earth metals with sulfuric acid to result in an acidified aqueous solution containing 1-12 M concentration of sulfuric acid; and (ii) contacting the acidified aqueous solution with an aqueous-insoluble hydrophobic solution comprising a rare earth extractant molecule dissolved in an aqueous-insoluble hydrophobic solvent to result in extraction of one or more of the rare earth metals into the aqueous hydrophobic solution, wherein the rare earth extractant molecule has the following structure: wherein R1, R2, R3, and R4 are independently selected from hydrocarbon groups containing 1-20 carbon atoms, provided that the total carbon atoms in R1, R2, R3, and R4 is at least 12; and R5 and R6 are independently selected from hydrogen atom and hydrocarbon groups containing 1-3 carbon atoms.

Brigham, Derek↗

WPTO Navigator

Protecting hydroelectric plants from incidents that adversely impact their cyber-physical systems presents unique challenges due to the plants’ widely dispersed geographic locations and varied configurations as well as the relative nascent nature of the cyberattacks targeting these facilities. To help hydroelectric plants better respond to and mitigate cybersecurity incidents, this Department of Energy Water Power Technologies Office Navigator aligns the processes within the National Institute of Standards 800-61r2 Computer Security Incident Handling Guide with the emergency actions within the FEMA 64 Emergency Action Plan Framework. This work is to be used at a hydroelectric plant to quickly understand how the plant responds to a cyber incident in relationship to the actions involved in an emergency action plan involving a hydroelectric plant. In addition to this product, there are three other products meant to be distributed to a hydroelectric plant to assist in their cyber incident response and recovery. The first, a report on the processes of building a R&R flip book based on a large set of existing guidance. The second, a handy flip book meant to be distributed to hydroelectric plants to assist them during a cybersecurity incident occurring on a hydroelectic plant. And the third is a comprehensive set of resources to assist an operator in locating appropriate guidance during the recovery process.

13 HYDRO ENERGY↗

A Well-Defined Bipolar Outflow Shell

We report in this letter the results of a study of the massive bipolar outflow in the central region of the giant molecular cloud Monoceros R2.

bipolar outflow shell extended blue lobe of bipola↗

Accuracy of Tau Positron Emission Tomography as a Prognostic Marker in Preclinical and Prodromal Alzheimer Disease: A Head-to-Head Comparison Against Amyloid Positron Emission Tomography and Magnetic Resonance Imaging

Importance: Tau positron emission tomography (PET) tracers have proven useful for the differential diagnosis of dementia, but their utility for predicting cognitive change is unclear. Objective: To examine the prognostic accuracy of baseline fluorine 18 ( 18 F)-flortaucipir and [18F]RO948 (tau) PET in individuals across the Alzheimer disease (AD) clinical spectrum and to perform a head-to-head comparison against established magnetic resonance imaging (MRI) and amyloid PET markers. Design, setting, and participants: This prognostic study collected data from 8 cohorts in South Korea, Sweden, and the US from June 1, 2014, to February 28, 2021, with a mean (SD) follow-up of 1.9 (0.8) years. A total of 1431 participants were recruited from memory clinics, clinical trials, or cohort studies; 673 were cognitively unimpaired (CU group; 253 [37.6%] positive for amyloid-β [Aβ]), 443 had mild cognitive impairment (MCI group; 271 [61.2%] positive for Aβ), and 315 had a clinical diagnosis of AD dementia (315 [100%] positive for Aβ). Exposures: [ 18 F]Flortaucipir PET in the discovery cohort (n = 1135) or [ 18 F]RO948 PET in the replication cohort (n = 296), T1-weighted MRI (n = 1431), and amyloid PET (n = 1329) at baseline and repeated Mini-Mental State Examination (MMSE) evaluation. Main outcomes and measures: Baseline [ 18 F]flortaucipir/[ 18 F]RO948 PET retention within a temporal region of interest, MRI-based AD-signature cortical thickness, and amyloid PET Centiloids were used to predict changes in MMSE using linear mixed-effects models adjusted for age, sex, education, and cohort. Mediation/interaction analyses tested whether associations between baseline tau PET and cognitive change were mediated by baseline MRI measures and whether age, sex, and APOE genotype modified these associations. Results: Among 1431 participants, the mean (SD) age was 71.2 (8.8) years; 751 (52.5%) were male. Findings for [ 18 F]flortaucipir PET predicted longitudinal changes in MMSE, and effect sizes were stronger than for AD-signature cortical thickness and amyloid PET across all participants (R 2 , 0.35 [tau PET] vs 0.24 [MRI] vs 0.17 [amyloid PET]; P < .001, bootstrapped for difference) in the Aβ-positive MCI group (R2, 0.25 [tau PET] vs 0.15 [MRI] vs 0.07 [amyloid PET]; P < .001, bootstrapped for difference) and in the Aβ-positive CU group (R 2 , 0.16 [tau PET] vs 0.08 [MRI] vs 0.08 [amyloid PET]; P < .001, bootstrapped for difference). These findings were replicated in the [ 18 F]RO948 PET cohort. MRI mediated the association between [ 18 F]flortaucipir PET and MMSE in the groups with AD dementia (33.4% [95% CI, 15.5%-60.0%] of the total effect) and Aβ-positive MCI (13.6% [95% CI, 0.0%-28.0%] of the total effect), but not the Aβ-positive CU group (3.7% [95% CI, -17.5% to 39.0%]; P = .71). Age (t = -2.28; P = .02), but not sex (t = 0.92; P = .36) or APOE genotype (t = 1.06; P = .29) modified the association between baseline [ 18 F]flortaucipir PET and cognitive change, such that older individuals showed faster cognitive decline at similar tau PET levels. Conclusions and relevance: The findings of this prognostic study suggest that tau PET is a promising tool for predicting cognitive change that is superior to amyloid PET and MRI and may support the prognostic process in preclinical and prodromal stages of AD.

59 BASIC BIOLOGICAL SCIENCES↗

A PRACTICAL ELECTRODIALYSIS MODEL FOR ACCELERATING SYSTEM DEVELOPMENT

Empirical optimization of electrodialysis (ED) is dependent on repetitive experiments with incremental adjustments, which is cost prohibitive at scale. While models can reduce the costs associated with optimization and scale-up, existing ED models are limited in application to specific use cases and tend to be developed for the exploration of specific transport phenomena. The field requires a practical system-level model, generalized for the broad range of ED systems. This work presents a modeling framework that enables rapid evaluation of membrane stack design, flow configuration, scale, and operational inputs. Across applications spanning 1 L to 5400 L; use of conventional and bipolar membranes; operation in continuous, batch and fed-batch modes; and feedstocks including seawater, brine, wastewater, and manure hydrolysate, the model achieves a mean R2 of 0.978 for concentration-time profiles and links design choices to techno-economic trade-offs, enabling cost-aware prioritization of system configurations.

Bipolar Membrane↗

Manganese sources and rates impact plant Mn concentrations and soil Mn fractions

Manganese (Mn) is an essential micronutrient for all organisms. In plants, Mn plays a critical role in photosynthesis and as a structural component of enzymes. In soils, Mn exists as different fractions of varying availability to plants. Mn fertilizers can be used to increase Mn availability to plants but are easily converted from a plant-available fraction (exchangeable Mn) to an unavailable fraction (Mn-oxides). Little research has been done in agricultural settings on soil Mn fractions; thus, the objective of this experiment was to study the effect of Mn additions on soil Mn fractions and plant Mn concentration. Here, a greenhouse experiment was conducted by growing soybean (Glycine max) treated with three Mn application rates (recommended or 1×, 10×, and 50×) of two sources (MnSO 4 and Mn ethylenediamine tetraacetic acid [MnEDTA]). Soil Mn fractions (Mehlich-1 extractable, exchangeable, organic-bound, Mn-oxide, residual) were quantified via sequential Mn extraction procedures. Bioavailability was evaluated by measuring soybean leaf Mn concentrations. Both fertilizer types increased available soil Mn fractions. Leaf Mn concentration increased with MnSO 4 50× application at the V3 stage and decreased with MnEDTA addition at the V3 and R2 stages. Mn additions likely resulted in the conversion of Mn into unavailable fractions. This was amplified by higher application rates, where total Mn increased by 18.5%, but available Mn decreased by 4.3% relative to initial soil values. Thus, our study showed that adding Mn to soils does not necessarily increase plant-available Mn.

54 ENVIRONMENTAL SCIENCES↗

Matching high resolution satellite data and flux tower footprints improves their agreement in photosynthesis estimates

Mapping canopy photosynthesis in both high spatial and temporal resolution is essential for carbon cycle monitoring in heterogeneous areas. However, well established satellites in sun-synchronous orbits such as Sentinel-2, Landsat and MODIS can only provide either high spatial or high temporal resolution but not both. Recently established CubeSat satellite constellations have created an opportunity to overcome this resolution trade-off. In particular, Planet Fusion allows full utilization of the CubeSat data resolution and coverage while maintaining high radiometric quality. In this study, we used the Planet Fusion surface reflectance product to calculate daily, 3-m resolution, gap-free maps of the near-infrared radiation reflected from vegetation (NIRvP). We then evaluated the performance of these NIRvP maps for estimating canopy photosynthesis by comparing with data from a flux tower network in Sacramento-San Joaquin Delta, California, USA. Overall, NIRvP maps captured temporal variations in canopy photosynthesis of individual sites, despite changes in water extent in the wetlands and frequent mowing in the crop fields. When combining data from all sites, however, we found that robust agreement between NIRvP maps and canopy photosynthesis could only be achieved when matching NIRvP maps to the flux tower footprints. In this case of matched footprints, NIRvP maps showed considerably better performance than in situ NIRvP in estimating canopy photosynthesis both for daily sum and data around the time of satellite overpass (R2 = 0.78 vs. 0.60, for maps vs. in situ for the satellite overpass time case). This difference in performance was mostly due to the higher degree of consistency in slopes of NIRvP-canopy photosynthesis relationships across the study sites for flux tower footprint-matched maps. Our results show the importance of matching satellite observations to the flux tower footprint and demonstrate the potential of CubeSat constellation imagery to monitor canopy photosynthesis remotely at high spatio-temporal resolution.

54 ENVIRONMENTAL SCIENCES↗

Microwave radiometer, sun-photometer and GNSS multi-comparison of integrated water vapor in Southwestern Europe

This work presents a comparison of integrated water vapor (IWV) data recorded from microwave radiometer (MWR) and sun-photometer (SP) using global navigation satellite system (GNSS) IWV as reference in five mid-latitude sites of Portugal and Spain (2003–2021). A very high correlation is obtained for both instruments (R2 between 0.94 and 0.98), although, while MWR shows a wet bias, SP exhibits a dry one. In addition, a dependence of mean bias error (MBE) and standard deviation (SD) on IWV has been observed, increasing (larger discrepancies) both indices as IWV increases. The solar zenith angle (SZA) dependence is also studied, finding slightly larger discrepancies for the MWR than for SP in comparison with GNSS for very high values of SZA. Finally, a marked seasonal dependence is observed for SP-GNSS differences, modulated by the IWV dependence explained above. In contrast, the seasonal dependence for MWR is quite weaker than it is for SP. Therefore, in spite of the excellent agreement found among the different instruments, it is recommended that: i) the dependence with IWV be studied and corrected to further increase the performance of the instruments, and ii) metadata be used to filter out situations in which the instrument cannot operate properly.

54 ENVIRONMENTAL SCIENCES↗

A high throughput assay to detect enzymatic polyethylene oxidation

Biological plastics deconstruction and upcycling have emerged as sustainable alternatives to traditional recycling technologies for plastics waste. The discovery and engineering of efficient thermostable poly(ethylene terephthalate) (PET) hydrolases have made biological PET recycling possible at scale; however, enzymes for non-PET plastics, which account for approximately 70% of all plastics produced, remain largely undiscovered. To accelerate the discovery of such enzymes, we develop a high-throughput screen to detect initial polymer oxidation, specifically that of the C-H bond to an aldehyde. We test 4-hydrazino-7-nitro-2,1,3-benxoxadiozole hydrazine (NBD-H), which reacts with generated aldehydes to form a fluorescent hydrazone on plasma oxidized low-density polyethylene (LDPE) films. Hydrazone generation correlated well with the area of aldehyde peaks as measured by Fourier Transform Infrared Spectroscopy (FTIR) (R2 = 0.92). Moreover, we demonstrate that the probe reliably identifies LDPE-active dye decolorizing peroxidases (DyPs) that generate aldehydes on LDPE films (1.7 – 3.0 fold change relative to background), serving as an effective screen as demonstrated by receiver operating characteristic area under the curve of 0.95. Furthermore, this assay offers an LDPE oxidation screening platform that can be readily parallelized and automated for accelerated discovery of enzymes involved in polyolefin deconstruction.

biocatalysis↗

Deep learning for drag force modelling in dilute, poly-dispersed particle-laden flows with irregular-shaped particles

Here, this study applies machine learning-based approaches to develop a drag force model for irregular-shaped particles in incompressible flows. The particle-laden flows are studied through an in-house particle-resolved direct numerical simulation (PR-DNS) at low-intermediate Reynolds numbers (Re). We utilize the PR-DNS to obtain drag force coefficients and flow fields of single particles. A variational auto-encoder model is used to obtain latent vectors to represent the geometrical features of the particles, and artificial neural networks (ANN) are developed to predict drag force coefficients and flow fields of the single particles. This study applies a pairwise interaction extended point-particle (PIEP) model to obtain the coefficients assuming the flow fields of neighboring particles can be linearly superposed. The PIEP method shows significant improvement on prediction for a few neighbored particles. In addition, the results reveal R2 scores of 0.56-0.62 and errors of 9.1-10.0 % for the dilute, polydispersed systems with a volume fraction of 0.5 %.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing

This paper presents a physics-informed machine learning (ML) framework to construct reduced-order models (ROMs) for reactive-transport quantities of interest (QoIs) based on high-fidelity numerical simu-lations. QoIs include species decay, product yield, and degree of mixing. The ROMs for QoIs are applied to quantify and understand how the chemical species evolve over time. First, high-resolution datasets for constructing ROMs are generated by solving anisotropic reaction-di?usion equations using a non-negative finite element formulation for di?erent input parameters. The reactive-mixing model input parameters are: time-scale associated with flipping of velocity, spatial-scale controlling small/large vortex structures of velocity, perturbation parameter of the vortex-based velocity, anisotropic dispersion strength/contrast, and molecular diffusion. Second, random forests, F-test, and mutual information criterion are used to evaluate the importance of model inputs/features with respect to QoIs. We observed that anisotropic dispersion strength/contrast is the most important feature and time-scale associated with flipping of velocity is the least important feature. Third, Support Vector Machines (SVM) and Support Vector Regression (SVR) are used to construct ROMs based on the model inputs. The constructed SVR-ROMs are then used to predict scaling of QoIs. We also present estimates and inequalities on the QoIs, which inform that the species decay, mix, and produce in an exponential fashion. These inequalities also inform that a radial basis function is the most suitable kernel for the SVM/SVR models for QoIs. It is observed that R2-score for SVR-ROMs on unseen data is greater than 0.9, implying that the SVR-ROMs are able to predict the reaction-diffusion system state reasonably well. Finally, in terms of the computational cost, the proposed SVM-ROMs are O(107) times faster than running a high-fidelity finite element simulation for evaluating QoIs. This makes the proposed ML-based ROMs attractive for reactive-transport sensing and real-time monitoring applications as they are significantly faster yet reasonably accurate.

Mudunuru, Maruti K.↗

Influence of PRE-emergence herbicides on soybean development, root nodulation and symbiotic nitrogen fixation

We report widespread occurrence of herbicide-resistant weeds has further limited effective POST-emergence herbicide options in soybean (Glycine max (L.) Merr.) leading to an increased adoption of PRE-emergence herbicides. The objective of this study was to investigate the influence of 11 commonly used PRE herbicides on soybean development, root nodulation, and symbiotic N fixation. Soybean plants were grown under greenhouse conditions in pots (10 L; 4 plants per pot) filled with silt loam soil and treated one day after planting with a labeled field rate of imazethapyr, chlorimuron-ethyl, cloransulam-methyl, metribuzin, sulfentrazone, flumioxazin, saflufenacil, acetochlor, S-metolachlor, dimethenamid-P, pyroxasulfone and no herbicide (nontreated control). Sulfentrazone reduced soybean canopy at the VC growth stage but no canopy reduction was observed at the V2 growth stage from any of the herbicide treatments. At the R2 growth stage, herbicides had no effect on soybean development (root and shoot biomass), root nodulation (# nodule per plant, nodule diameter, and nodule biomass) and symbiotic N fixation (acetylene reduction assay and 15 N natural abundance). According to our findings, although PRE herbicides may slightly affect early-season soybean development, the impacts on plant growth, root nodulation, and symbiotic N fixation were negligible. Thus, when sprayed according to the label, the benefits of PRE herbicides for weed control likely outweigh any potential concern regarding soybean development, root nodulation, and N fixation.

54 ENVIRONMENTAL SCIENCES↗

Machine learning models of intermittent operation of RO wellhead water treatment for salinity reduction and nitrate removal

Machine learning models were developed for intermittent multi-mode operation of a wellhead reverse osmosis water purification and desalination system to predict salt passage, nitrate passage, and permeate flux. The models, based on long short-term memory (LSTM) recurrent neural network (RNN) architecture, included an attention mechanism to increase model performance in proximity of the regulatory limit for nitrate. Training and testing of the models for the Startup, Production, Shutdown and Flushing operational modes were based on operational data (consisting of 22 process variables per data sample) acquired every 2–5 s over a six-month period. The significant sets of model input attributes for the different operational modes were assessed via Spearman ranking correlation, Self-Organizing Map (SOM) analysis and feed forward feature selection (FFFS). Although the variability of nitrate passage, salt passage and permeate flux was significant over the four operational modes, prediction performance for the three outcomes were with R2 and Average Absolute Relative Error (AARE) of 0.78–0.95 and 2.96–6.16 %, respectively. Model updates post membrane elements replacement demonstrated similar levels of prediction accuracy. The study results suggest that there is merit in exploring the utility of multi-mode models for sensor fault detection, data imputation, and for potential use in model-predictive control.

Intermittent RO operation↗

Long-term effects of thinning and woody control on longleaf pine plantation development, understory abundance, and tree damage from an ice storm

Longleaf pine (Pinus palustris) plantations have been established across the southeastern United States as the first step in restoring the declining savanna ecosystem, yet their long-term stability and development to open canopied woodlands may depend on early density and vegetation management treatments. Commercial thinning (CT) was applied in 2012 (year 18) to a long-term study of longleaf pine community restoration at the Savannah River Site near Aiken, SC to increase abundance of herb species. Although precommercial thinning (PCT) and woody vegetation control increased herb species cover during the first five years of the study, measurements from years 17 to 22 indicated a continuing decline in their cover since year 9 despite application of CT in year 18. Herb species richness, however, increased from 21 to 43 species per 100 m2 area during the last six years of the study, likely a result of disturbances associated with CT and an ice storm in year 20. Application of PCT in 1994, when the plantations were 8–11 years old, reduced their susceptibility to stem bending and breakage from the ice storm, which occurred 20 years later in 2014. Measured 5 months before the storm, pine height: dbh ratio (HD) averaged 78 and 90 for trees growing with and without PCT, respectively, and stem breakage (% of trees) from the ice storm increased linearly (r2 = 0.53) with HD. Pine mortality from the combined effects of glaze ice and wind differed with (28%) versus without (45%) PCT, indicating that long-term stability of longleaf pine plantations depends on early density management.

54 ENVIRONMENTAL SCIENCES↗

Carbon sequestration and nitrogen and phosphorus accumulation in a freshwater, estuarine marsh: Effects of microtopography and nutrient loads

Wetlands are widely recognized as nutrient sinks for their ability to remove nutrients in runoff and retain them in soils. This is a valuable service, especially in agricultural watersheds, making nutrient removal one of the main goals in many wetland creation and restoration projects. However, incorporating nutrient management considerations requires site-level assessments, the scale at which wetland creation and restoration occur. Here we studied how carbon (C) sequestration, and nitrogen (N) and phosphorus (P) accumulation vary at different microtopographic levels and locations within a freshwater, estuarine marsh on the coast of Lake Erie. We further explored links between C sequestration, and N and P accumulation in recent years, and orthophosphate ($PO_{4}^{3-}$), ammonium ($NH_{4}^{+}$), and nitrate ($NO_{3}^{-}$) concentrations and loads. The rates of C sequestration and N accumulation were relatively lower at spots of intermediate depth and locations closer to the wetland’s main channel. P accumulation was highest at deep spots but did not differ among locations based on distance from the channel. Empirical models showed that nitrate load is the most important variable explaining the variability in C, N, and P sequestration/accumulation (r2 = 0.57, 0.61, and 0.32, respectively) and that the relationship between inorganic nutrient loads and accumulation was negative. Our findings suggest that including microtopographic relief features in wetland creation and design, especially deeper spots, is critical to enhancing wetland ecosystems’ C, N, and P sinking capacity. Also, that upstream nitrate management should be a priority to increase benefits from C sequestration and long-term N and P accumulation.

54 ENVIRONMENTAL SCIENCES↗