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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Glucocorticoids activate the ATP-ubiquitin-dependent proteolytic system in skeletal muscle during fasting

Glucocorticoids are essential for the increase in protein breakdown in skeletal muscle normally seen during fasting. To determine which proteolytic pathway(s) are activated upon fasting, leg muscles from fed and fasted normal rats were incubated under conditions that block or activate different proteolytic systems. After food deprivation (1 day), the nonlysosomal ATP-dependent process increased by 250%, as shown in experiments involving depletion of muscle ATP. Also, the maximal capacity of the lysosomal process increased 60-100%, but no changes occurred in the Ca(2+)-dependent or the residual energy-independent proteolytic processes. In muscles from fasted normal and adrenalectomized (ADX) rats, the protein breakdown sensitive to inhibitors of the lysosomal or Ca(2+)-dependent pathways did not differ. However, the ATP-dependent process was 30% slower in muscles from fasted ADX rats. Administering dexamethasone to these animals or incubating their muscles with dexamethasone reversed this defect. During fasting, when the ATP-dependent process rises, muscles show a two- to threefold increase in levels of ubiquitin (Ub) mRNA. However, muscles of ADX animals failed to show this response. Injecting dexamethasone into the fasted ADX animals increased muscle Ub mRNA within 6 h. Thus glucocorticoids activate the ATP-Ub-dependent proteolytic pathway in fasting apparently by enhancing the expression of components of this system such as Ub.

Non-NASA Center↗
NASA NTRS2011

Developing Tests of Visual Dependency

Astronauts develop neural adaptive responses to microgravity during space flight. Consequently these adaptive responses cause maladaptive disturbances in balance and gait function when astronauts return to Earth and are re-exposed to gravity. Current research in the Neuroscience Laboratories at NASA-JSC is focused on understanding how exposure to space flight produces post-flight disturbances in balance and gait control and developing training programs designed to facilitate the rapid recovery of functional mobility after space flight. In concert with these disturbances, astronauts also often report an increase in their visual dependency during space flight. To better understand this phenomenon, studies were conducted with specially designed training programs focusing on visual dependency with the aim to understand and enhance subjects ability to rapidly adapt to novel sensory situations. The Rod and Frame test (RFT) was used first to assess an individual s visual dependency, using a variety of testing techniques. Once assessed, subjects were asked to perform two novel tasks under transformation (both the Pegboard and Cube Construction tasks). Results indicate that head position cues and initial visual test conditions had no effect on an individual s visual dependency scores. Subjects were also able to adapt to the manual tasks after several trials. Individual visual dependency correlated with ability to adapt manual to a novel visual distortion only for the cube task. Subjects with higher visual dependency showed decreased ability to adapt to this task. Ultimately, it was revealed that the RFT may serve as an effective prediction tool to produce individualized adaptability training prescriptions that target the specific sensory profile of each crewmember.

Kindrat, Alexandra N.↗
NASA NTRS2012

Spectral Line Parameters Including Temperature Dependences of Self- and Air-Broadening in the 2 (left arrow) 0 Band of CO at 2.3 micrometers

Temperature dependences of pressure-broadened half-width and pressure-induced shift coefficients along with accurate positions and intensities have been determined for transitions in the 2<--0 band of C-12 O-16 from analyzing high-resolution and high signal-to-noise spectra recorded with two different Fourier transform spectrometers. A total of 28 spectra, 16 self-broadened and 12 air-broadened, recorded using high- purity (greater than or equal to 99.5% C-12-enriched) CO samples and CO diluted with dry air(research grade) at different temperatures and pressures, were analyzed simultaneously to maximize the accuracy of the retrieved parameters. The sample temperatures ranged from 150 to 298K and the total pressures varied between 5 and 700 Torr. A multispectrum nonlinear least squares spectrum fitting technique was used to adjust the rovibrational constants (G, B, D, etc.) and intensity parameters (including Herman-Wallis coefficients), rather than determining individual line positions and intensities. Self-and air-broadened Lorentz half-width coefficients, their temperature dependence exponents, self- and air-pressure-induced shift coefficients, their temperature dependences, self- and air-line mixing coefficients, their temperature dependences and speed dependence have been retrieved from the analysis. Speed-dependent line shapes with line mixing employing off-diagonal relaxation matrix element formalism were needed to minimize the fit residuals. This study presents a precise and complete set of spectral line parameters that consistently reproduce the spectrum of carbon monoxide over terrestrial atmospheric conditions.

Devi, V. Malathy↗
NASA NTRS2013

Assessing the Temperature Dependence of Narrow-Band Raman Water Vapor Lidar Measurements: A Practical Approach

Narrow-band detection of the Raman water vapor spectrum using the lidar technique introduces a concern over the temperature dependence of the Raman spectrum. Various groups have addressed this issue either by trying to minimize the temperature dependence to the point where it can be ignored or by correcting for whatever degree of temperature dependence exists. The traditional technique for performing either of these entails accurately measuring both the laser output wavelength and the water vapor spectral passband with combined uncertainty of approximately 0.01 nm. However, uncertainty in interference filter center wavelengths and laser output wavelengths can be this large or larger. These combined uncertainties translate into uncertainties in the magnitude of the temperature dependence of the Raman lidar water vapor measurement of 3% or more. We present here an alternate approach for accurately determining the temperature dependence of the Raman lidar water vapor measurement. This alternate approach entails acquiring sequential atmospheric profiles using the lidar while scanning the channel passband across portions of the Raman water vapor Q-branch. This scanning is accomplished either by tilt-tuning an interference filter or by scanning the output of a spectrometer. Through this process a peak in the transmitted intensity can be discerned in a manner that defines the spectral location of the channel passband with respect to the laser output wavelength to much higher accuracy than that achieved with standard laboratory techniques. Given the peak of the water vapor signal intensity curve, determined using the techniques described here, and an approximate knowledge of atmospheric temperature, the temperature dependence of a given Raman lidar profile can be determined with accuracy of 0.5% or better. A Mathematica notebook that demonstrates the calculations used here is available from the lead author.

Raman lidar↗
NASA NTRS2019

Application of a Temperature-Dependent Load Prediction Method to a RUAG Six-Component Block-Type Balance

Temperature-dependent data of a RUAG six-component block-type balance was analyzed to assess the accuracy of two load prediction methods for temperature-dependent balance data. The supplied data was prepared for the analysis by splitting it into calibration and check load data subsets. The first calibration data subset was obtained at a temperature of 294 Kelvin. The second calibration data subset was obtained at a temperature of 315 Kelvin. A subset of 38 points was extracted from the second data set and used as check loads so that the accuracy of the two load prediction methods could be tested. First, the Iterative Method in combination with an extended independent and dependent variable set was used for the balance load prediction. This approach fits electrical outputs as a function of loads and the temperature and, afterwards, constructs a load iteration scheme from the regression coefficients so that loads can be predicted from outputs and the temperature during a wind tunnel test. The Non-Iterative Method was also used for the load prediction. This alternate method can more easily be implemented in a data system as loads are directly fitted as a function of electrical outputs and the temperature. Analysis results for the axial force are only discussed in the paper as similar results were obtained for the other five load components. Results for both methods clearly show that the cross-product term constructed from either a primary gage load or a primary gage output and the temperature explains the majority of the temperature-dependent part of the predicted balance load. This term models the temperature dependent nature of the gage sensitivity. Therefore, it is recommended to apply primary gage loadings at different temperatures during a balance calibration whenever temperature effects need to be described. These loadings will contain information about the temperature-dependent nature of the gage sensitivities that can be quantified by related cross-product terms in regression models of the data.

strain-gage balance↗
NASA NTRSDate not supplied

PACE OCI Short-Wave Infrared Detection Assembly frequency-dependent linearity characterization and uncertainty analysis

The Ocean Color Instrument (OCI), the primary payload of the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE)observatory, will collect data to monitor the health of Earth’s oceans and atmosphere. The Short-Wave Infrared(SWIR) Detection Assembly (SDA) was built and characterized by the Utah State University Space DynamicsLaboratory (SDL) and is a subsystem of OCI. The SDA measures seven bands centered at 940, 1038, 1250, 1378,1615, 2130, and 2260 nm, with standard- and high-gain varieties for the 1250 and 1615 nm bands, resulting in nine total detection configurations in the SWIR. The delivery of high-quality science data is critically dependent upon accurately characterizing the linearity of the SDA. Two metrology techniques were employed to measure the linearity and characterize the frequency-dependent linearity uncertainty of the system. The first technique used superposition linearity measurements to determine the DC linearity, and the second technique involved an oscillating small-signal response at seven frequencies to determine the frequency-dependent linearity. Discrepancies between the DC and frequency-dependent linearities constrain the uncertainty between the two. Examining the difference between these two methods for all SDA channels, we find most channels experience an uncertainty below0.2% with a worst-case measurement uncertainty of 0.31%. Averaging SDA channels with similar detectors, optical filters, and electronics to simulate the flight-like data products yields a worst-case frequency-dependence linearity uncertainty of 0.12%, demonstrating minimal frequency dependence, implying an excellent linearity knowledge.Detailed performance knowledge, including linearity performance, verifies data quality and builds confidence in the success of the PACE mission.

PACE↗
DOE OSTI2020

Extracting dependencies between network assets using deep learning

A network analysis tool receives network flow information and uses deep learning—machine learning that models high-level abstractions in the network flow information—to identify dependencies between network assets. Based on the identified dependencies, the network analysis tool can discover functional relationships between network assets. For example, a network analysis tool receives network flow information, identifies dependencies between multiple network assets based on evaluation of the network flow information, and outputs results of the identification of the dependencies. When evaluating the network flow information, the network analysis tool can pre-process the network flow information to produce input vectors, use deep learning to extract patterns in the input vectors, and then determine dependencies based on the extracted patterns. The network analysis tool can repeat this process so as to update an assessment of the dependencies between network assets on a near real-time basis.

Carroll, Thomas E.↗
DOE OSTI2021

Energy Dependence in the Neutrino Scattering Data of MINERvA

As we prepare for lower neutrino energy beams where physics is highly energy-dependent, it is important to isolate factors that can contribute largely to these low energy neutrino experiments. The world of neutrino oscillation experiments uses a wide range of energies: from 0.7 GeV beam of T2K and MicroBooNE, 2 GeV beam of NOvA, to the 0.6 to 6.0 GeV beam produced by DUNE in the future. MINERvA’s data are currently the best place to test the upper end of the range for DUNE and can be extrapolated into both DUNE’s and NOvA’s oscillation maximum. The goal of the research is to constrain energy dependence in the neutrino scattering experiment using data from MINERvA and then determine what factors contribute to the observed energy dependence. The research is divided into two parts. First, I will analyze different theoretical models in different channels of interaction, such as the quasi-elastic and delta resonance channels, in terms of neutrino energy dependence. The goal is to study the models at the level of the structure functions, which emphasizes the W2 structure function (the C function for QE) dominates the MINERvA data, but the W3 is increasingly important for NOvA and DUNE. The second half of the research is data-driven and focuses on the different detectors and systematic effects. An experimental effect, the angle acceptance, is larger than the structure function effects. However, it is a detector geometry effect and is well measured and well modeled. Other effects such as the muon energy scale are small and localized. Additionally, the research will determine if the MINERvA GENIE model correctly predicts all of the energy dependence seen in the data, and identify the remaining unmodeled energy dependence between the MINERvA data and its best simulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Energy Dependence Analysis of Neutrino-Nucleus Interactions in Scintillator for MINERvA

This thesis is on the intrinsic energy dependence in neutrino-nucleus interaction models, especially quasielastic scattering and 2p2h process, and the implications for understanding data from MINERvA, NOvA, and DUNE. Neutrino-nucleus interactions are modeled using fve structure functions, W1, W2, W3, W4 and W5, and each structure function contributes diferently to the energy dependence once it enters the cross-section calculations. The energy independent term in the calculations contains only W2 and the next lower order term (of the order 1/E) contains W3 also. In this thesis, we show that W2 is good enough to describe MINERvA data and energy dependence coming from the cross-section directly is small. However, W3 will be signifcant for lower energy experiments such as NOvA and DUNE (especially at and below the oscillation maximum). We have also developed a method to extract structure functions directly from MINERvA data though we find that systematic uncertainties present in the data are too big to successfully determine 1/E Term. In addition to this, we have applied muon angle cuts on MINERvA data and MC, which have their own energy dependent effects. An apparent energy dependent discrepancy comes from known shortcomings especially in the pion production model. Finally, because the energy dependence analysis has similarities to the low-$\nu$ method, we have evaluated discrepancies between the data and MC in light of diferent fux constraint techniques. The results suggest including MINERvA s low-$\nu$ method constraint is an improvement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Phase-field modeling of rate-dependent fluid-driven fracture initiation and propagation

The rate-dependent behavior associated with deformation and fracturing of materials, such as natural rocks, poses significant challenges for modeling. In addition to the complications of the viscoelastic response, the speed of fracture propagation reflects micromechanical mechanisms in the fracture process zone(FPZ). In order to represent these complicated behaviors, a thermodynamically consistent, rate-dependent fracture model is required. Based on rigorous thermodynamic principles, we derive a rate-dependent phase-field mechanical model coupled with single-phase fluid flow in both the matrix and the fracture. The model is guaranteed to satisfy energy conservation during fracture propagation. Here, the system of equations is solved using the introduced solution procedure and a novel preconditioner that accounts for the complex fluid-structure interaction. The proposed phase-field model is tested against several benchmark problems on solid-fluid coupling, fluid-driven fracture propagation and rate-dependent viscoelastic deformation. The model serves as a strong basis for investigating rate-dependent fracturing experiments and for making predictions of material behaviors under new conditions.

42 ENGINEERING↗
DOE OSTI2020

Resiliency-based restoration optimization for dependent network systems against cascading failures

Due to the increasing importance of large-scale and complex network systems and the potential for massive cascading failures in these real-world systems, modeling of system resiliency and optimization of restoration strategies to mitigate system performance loss caused by diverse disruptions is of significant interest among researchers and practitioners. Although society has experienced many incidents that demonstrate the influence of cascading failures aggravated by dependencies inside network systems, existing resiliency-based restoration optimization research rarely if ever jointly considers the impact of system dependencies on cascading failures. In this paper, different restoration prioritization strategies are applied to network systems subject to cascading failures that take into account system dependencies. By conducting case studies on synthetic networks and the U.S. airport network system, the effects of restoration strategies are evaluated using a system resiliency metric and two system performance measurements. Furthermore, the influence of system dependency characteristics and the interplay between them and restoration strategies on system resiliency regarding cascading failures are also investigated. This work demonstrates the distinct effects of restoration prioritization actions against cascading failures to mitigate the performance loss in network systems with different properties. It also provides insights about restoration improvement by considering dependency impacts to effectively reduce the intensity and extent of cascading failures.

42 ENGINEERING↗
DOE OSTI2021

Competitive Exclusion and Metabolic Dependency among Microorganisms Structure the Cellulose Economy of an Agricultural Soil

Microorganisms that degrade cellulose utilize extracellular reactions that yield free by-products which can promote interactions with noncellulolytic organisms. We hypothesized that these interactions determine the ecological and physiological traits governing the fate of cellulosic carbon (C) in soil. We performed comparative genomics with genome bins from a shotgun metagenomic-stable isotope probing experiment to characterize the attributes of cellulolytic and noncellulolytic taxa accessing 13 C from cellulose. We hypothesized that cellulolytic taxa would exhibit competitive traits that limit access, while noncellulolytic taxa would display greater metabolic dependency, such as signatures of adaptive gene loss. We tested our hypotheses by evaluating genomic traits indicative of competitive exclusion or metabolic dependency, such as antibiotic production, growth rate, surface attachment, biomass degrading potential, and auxotrophy. The most 13 C-enriched taxa were cellulolytic Cellvibrio (Gammaproteobacteria) and Chaetomium (Ascomycota), which exhibited a strategy of self-sufficiency (prototrophy), rapid growth, and competitive exclusion via antibiotic production. Auxotrophy was more prevalent in cellulolytic Actinobacteria than in cellulolytic Proteobacteria, demonstrating differences in dependency among cellulose degraders. Noncellulolytic taxa that accessed 13 C from cellulose (Planctomycetales, Verrucomicrobia, and Vampirovibrionales) were also more dependent, as indicated by patterns of auxotrophy and 13 C labeling (i.e., partial labeling or labeling at later stages). Major 13 C-labeled cellulolytic microbes (e.g., Sorangium, Actinomycetales, Rhizobiales, and Caulobacteraceae) possessed adaptations for surface colonization (e.g., gliding motility, hyphae, attachment structures) signifying the importance of surface ecology in decomposing particulate organic matter. Our results demonstrated that access to cellulosic C was accompanied by ecological trade-offs characterized by differing degrees of metabolic dependency and competitive exclusion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Probing the Boundary between Classical and Quantum Mechanics by Analyzing the Energy Dependence of Single-Electron Scattering Events at the Nanoscale

The relation between the energy-dependent particle and wave descriptions of electron–matter interactions on the nanoscale was analyzed by measuring the delocalization of an evanescent field from energy-filtered amplitude images of sample/vacuum interfaces with a special aberration-corrected electron microscope. The spatial field extension coincided with the energy-dependent self-coherence length of propagating wave packets that obeyed the time-dependent Schrödinger equation, and underwent a Goos–Hänchen shift. The findings support the view that wave packets are created by self-interferences during coherent–inelastic Coulomb interactions with a decoherence phase close to Δφ = 0.5 rad. Due to a strictly reciprocal dependence on energy, the wave packets shrink below atomic dimensions for electron energy losses beyond 1000 eV, and thus appear particle-like. Consequently, our observations inevitably include pulse-like wave propagations that stimulate structural dynamics in nanomaterials at any electron energy loss, which can be exploited to unravel time-dependent structure–function relationships on the nanoscale.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Approach to Dependence Assessment in Human Reliability Analysis: Application of Lag and Linger Effects

Dependence assessment refers to an approach used in human reliability analysis (HRA) to adjust a human error probability (HEP) for the following action by considering the impact of the preceding action. It has been known to significantly affect the overall results of probabilistic safety assessment (PSA). If the dependence assessment is not adequate, the result could be unconvincing for explaining the operator failures in the context of PSA. To date, several methods and some recent research have identified suggestions for treating dependence issues in HRA; however, these are still exclusively based on the intrinsic approach of the Technique for Human Error Rate Prediction (THERP), an HRA method. THERP inevitably has a challenge with the subjectivity of expert evaluation as well as the requirement for PSA and HRA expertise with resource-intensive and time-consuming processes. This paper suggests an approach to dependence assessment that could not only minimize the influence of expert judgment, but also saves time to perform the analysis with reasonable manpower. It modifies existing HRA methods with considering lag and linger effects to apply dependence effects for them. Based on a representative HRA method, i.e., Standardized Plant Analysis Risk - HRA (SPAR-H), guidance for how to apply lag and linger effects for the HRA method is suggested. Then, an investigation is carried out to compare quantification results of the revised HRA method with that of the original approach based on experimental data.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2019

Determination of the solar angular dependence of the NOAA-20 VIIRS solar diffuser BRDF change factor

When fully illuminated by the Sun, the solar diffuser (SD) onboard of the NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) instrument provides a radiance source to allow for radiometric calibration of the VIIRS’s reflective solar bands (RSBs). Once on-orbit, due to solar bombardment and the space environment, the SD’s bidirectional reflectance distribution function (BRDF) changes its value. The change is denoted by a factor, known as the H-factor, that is time and wavelength dependent, as well as both incident and out-going angle dependent. Here, we use regular on-orbit solar diffuser stability monitor (SDSM) data to determine the solar angular dependence for the H-factor along the SD-to-SDSM direction. We compare the dependence with that for the VIIRS on the Suomi National Polar-orbiting Partnership satellite and apply the dependence ratio to obtain the N20 VIIRS SD H-factor along the SD-telescope direction.

N20 VIIRS↗
DOE OSTI2021

Potential dependent spectroelectrochemistry of electrofluorogenic dyes on indium–tin oxide

Indium-tin oxide (ITO) is used in a variety of applications due to its electrical conductivity and optical transparency. Moreover, ITO-coated glass is a common working electrode for spectroelectrochemistry. Thus, the ITO substrates should exhibit well-understood spectroscopic characteristics. Here, we report anomalous potential-dependent luminescence emission from three structurally dissimilar electrofluorogenic probe on ITO-coated glass. The three probes, flavin mononucleotide, resorufin, and Nile blue, show the expected fluorescence modulation between their oxidized, emissive forms and their reduced, nonfluorescent forms at low laser irradiance and/or high concentrations. However, at high irradiance and/or low concentration, the emission intensity increases at reducing potentials, contrary to expectations. In addition, a strong interplay between probe molecule concentration and laser irradiance is observed. We attribute the anomalous behavior to a combination of (1) irradiance-dependent ITO carrier dynamics, and (2) interaction of the fluorescent probe with ITO at reducing potentials resulting in a charge transfer state with altered emission behavior. Thus, the potential- and irradiance-dependent behavior of ITO and the resulting charge transfer state may not only interfere with the observation of potential-dependent fluorescence from redox probes but can completely reverse the polarity of the potential-dependent luminescence, especially at high irradiance and low concentration.

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

Multistage distributionally robust mixed-integer programming with decision-dependent moment-based ambiguity sets

We study multistage distributionally robust mixed-integer programs under endogenous uncertainty, where the probability distribution of stage-wise uncertainty depends on the decisions made in previous stages. We first consider two ambiguity sets defined by decision-dependent bounds on the first and second moments of uncertain parameters and by mean and covariance matrix that exactly match decision-dependent empirical ones, respectively. For both sets, we show that the subproblem in each stage can be recast as a mixed-integer linear program (MILP). Moreover, we extend the general moment-based ambiguity set in to the multistage decision-dependent setting, and derive mixed-integer semidefinite programming (MISDP) reformulations of stage-wise subproblems. We develop methods for attaining lower and upper bounds of the optimal objective value of the multistage MISDPs, and approximate them using a series of MILPs. We deploy the Stochastic Dual Dynamic integer Programming (SDDiP) method for solving the problem under the three ambiguity sets with risk-neutral or risk-averse objective functions, and conduct numerical studies on multistage facility-location instances having diverse sizes under different parameter and uncertainty settings. Furthermore, our results show that the SDDiP quickly finds optimal solutions for moderate-sized instances under the first two ambiguity sets, and also finds good approximate bounds for the multistage MISDPs derived under the third ambiguity set. We also demonstrate the efficacy of incorporating decision-dependent distributional ambiguity in multistage decision-making processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Mutual Diffusion Coefficients of Na 2 SO 4 at C = 0.02989 mol·dm -3 and 298.15 K by Using Rayleigh Interferometry with Free Diffusion Boundary Conditions: Experimental Test of the Effect of the C 3/2 Concentration Dependence of Refractive Index at Low Concentration

Rayleigh interferometry is one of the most precise and accurate methods for the experimental determination of the mutual diffusion coefficients of both electrolytes and non-electrolytes in liquid solutions. For binary solutions at moderate and high concentrations where the concentration dependences of both diffusion coefficient and refractive index can be assumed to be linear or almost linear and the concentration difference ΔC between a pair of solutions undergoing free diffusion is not large compared to their average concentration, and by using proper combinations of the interference fringe positions as they vary with time, under these conditions diffusion coefficients are obtained that are independent of the size of ΔC. However, this situation becomes more complicated at low concentrations for electrolyte solutions where the concentration dependences of both the diffusion coefficient and refractive index are non-linear, with C 1/2 dependence for the diffusion coefficient and C 3/2 dependence for the refractive index. As a test of these effects on calculated mutual diffusion of electrolyte solutions at low concentrations as measured by Rayleigh interferometry, apparent mutual diffusion coefficients D v,a (volume-fixed reference frame) were measured for fixed average concentrations C=(0.02989 ± 0.00001) mol·dm –3 of Na 2 SO 4 (aq) at 298.15 K while varying ΔC/C from 0.66673 to 2, a threefold variation. The dependence of the diffusion coefficient on ΔC/C was found to be linear, yielding D v = 1.041 6 × 10 –9 m 2 ·s –1 for an infinitely small concentration difference between the diffusing solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗