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NASA NTRS2014

Exploring NASA OMI Level 2 Data With Visualization

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms, etc.).Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as images, with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data-map sources.

Level 2↗

NASA NTRS2014

Exploring NASA OMI Level 2 Data With Visualization

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms,... etc.). Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as "images", with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data/map sources.

Aura↗

DOE OSTI2020

Experimentally Validated Computational Modeling of Creep and Creep-Cracking for Nuclear Concrete Structures

In a Nuclear Power Plant, one of the most important components is the concrete nuclear reactor cavity, which serves both a structural and protective function as the biological radiation shield. Given that creep has been identified as a major knowledge gap in the assessment of nuclear structures (NUREG/CR-7153), this work helps to further the understanding of creep behavior of massive concrete containment structures for decades to enable safe and long-term operation of these facilities. This project has developed a robust, experimentally validated model to predict creep in nuclear concrete structures for up 60 years using short-term creep data thereby enabling a longer service life of critical facilities and early detection of structural failure. The work presented in this report is a pairing of computational and experimental methods. For the first time, the time temperature superposition (TTS) principle was successfully used to generate a uniaxial creep compliance master curve to predict mortar creep response for up to 22,500 days (nearly 60 years) at a reference temperature of 20°C. These data were used as input into finite element analysis (FEA) codes that use highly realistic random, 3D concrete microstructures from reconstructed coarse limestone aggregates. Finite element analysis performed provides the ability to quickly upscale mortar viscoelastic behavior to long-term concrete creep/relaxation data. A master creep compliance curve, constructed from the TTS principle, spanning 27 years, was used to validate two and a half decades of simulated concrete creep. Concurrently, three different simulated wall specimens were designed to mimic the behavior of post-tensioned concrete nuclear containment facility vessel walls over time as a result of concrete creep. The specimens were designed with different thicknesses, transverse and longitudinal reinforcement ratios, and level of post-tensioning stress. Each specimen contained various instrumentation to measure internal concrete temperature, concrete strain, and post-tensioning strain hourly for over 3 years. The concrete creep model developed in this project, based on the FEA concrete simulations, was applied to simulate the structural-scale experiments of prestressed concrete walls conducted in this project using the Grizzly code. These models can represent the effects of reinforcing and prestressing. Although there are some discrepancies with the experimental data, the model can predict the overall trends of the creep response in these experiments. One of these experimental models was also applied to an extended time to demonstrate how the findings from this study can be used to predict the behavior of actual structures of interest that have been in service for extended periods of time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2007

Overview of TRMM Data Products and Services

November 27, 2007 marks the l0th anniversary of the launch of the Tropical Rainfall Measuring Mission (TRMM) satellite. In anticipation of this anniversary, this paper will present an overview of the various TRMM data products currently available including the standard products, near real-time products, special products, and prototype products. It also will present an easy way to obtain these data. TRMM standard products have been publicly available since a few months after launch in November 1997. TRMM is currently on version 6 of the data product. Version 3 was the "at launch" version. The approval for each of these versions came through the Joint TRMM Science Team. Standard products are divided into 3 categories: single TRMM instrument, Visible Infrared Scanner (VIRS), TRMM Microwave Imager (TMI), and Precipitation Radar (PR); combined TRMM products (PR and TMI); finally TRMM and other satellites (combined, TMI, SSMI, AMSRE, AMSU). The single TRMM instrument products are processed through 4 levels: Level lA, science data packets processed into orbital files; Level 1B and lC, geolocated data at the instrument field of view; Level 2, geolocated, geophysical parameters at the instrument field of view; Level 3, time aggregated, gridded geophysical parameters. These products are available with 24 hours of production through an anonymous ftp account on trmmopen.gsfc.nasa.gov. The TRMM data system started to produce near real-time products at the end of 1999. They are currently available only through a controlled user account. However, approval to get access to this account can be obtained by sending a note to Erich.F.Stoclter@nasa.gov providing the reason for access and contact information including a valid email. TRMM is not restricting access but needs the information to determine the usefulness of near-real time data to the general science community including applications agencies. TRMM near real-time products are swath products up to Level 2 of processing. The oldest data in the swath is generally no older than 120 minutes when it becomes available to the community. The real-time products including a VIRS level lB, a TMI parameter reduced 1B, a TMI level 2 parameter reduced rain product, a PR level 2 surface rain product, and a PR level 2 rain product with 25 vertical levels. Currently, TRMM also produces a gridded 3 hour global merged product from several radiometers including AMSU and from radiometercalibrated IR data. The paper also describes several simple-format gridded text products available fiom the trmmopen.gsfc.nasa.gov anonymous fip server denoted as 3668 products. These products were produced to provide rain estimates from the three TRMM instruments in a universal format (ASCII) that requires very little data format knowledge. The paper goes on to describe prototype L1 radiometer products that apply an early intercalibration approach that provides a starting point to be used for Global Precipitation Measurement mission radiometer products. The paper also provides a brief overview of a precipitation features data product being produced using TRMM products including the Lighting Imaging Sensor (LIS) using an algorithm developed at the University of Utah and distributed by that organization. The paper concludes with some possible changes to products that are planned for the next reprocessing cycle and special services such as geographical subsetting available to the science community.

Stocker, Erich Franz↗

DOE OSTI2015

Fibrillar dimer formation of islet amyloid polypeptides

Amyloid deposits of human islet amyloid polypeptide (hIAPP), a 37-residue hormone co-produced with insulin, have been implicated in the development of type 2 diabetes. Residues 20 – 29 of hIAPP have been proposed to constitute the amyloidogenic core for the aggregation process, yet the segment is mostly unstructured in the mature fibril, according to solid-state NMR data. Here we use molecular simulations combined with bias-exchange metadynamics to characterize the conformational free energies of hIAPP fibrillar dimer and its derivative, pramlintide. We show that residues 20 – 29 are involved in an intermediate that exhibits transient β-sheets, consistent with recent experimental and simulation results. By comparing the aggregation of hIAPP and pramlintide, we illustrate the effects of proline residues on inhibition of the dimerization of IAPP. The mechanistic insights presented here could be useful for development of therapeutic inhibitors of hIAPP amyloid formation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Frustrated Coulombic and Cation Size Effects on Nanoscale Boehmite Aggregation: A Tumbler Small- and Ultra-Small-Angle Neutron Scattering Study

To better understand the effects of solution chemistry on particle aggregation in the complex legacy tank wastes at the Hanford (WA) and Savannah River (SC) sites, we have performed a series of tumbler small- and ultra-small-angle neutron scattering experiments on 20 wt % solid slurries of nanoparticulate aluminum oxyhydroxide (boehmite) with M 1+ nitrates of various concentrations and radii. In this study, the solutes consisted of H, Li, Na, K, and Rb nitrates at 10 –5 , 10 –3 , 10 –1 , 2, and 4 molal (m) concentrations, as well as in pure H 2 O. Synthetic boehmite nanoparticles were used with a size range from ~20 to 30 nm. Tumbler cells were used to keep the solids from settling. Although particles initially form individual rhombohedral platelets, once placed in solution, they quickly form well-bonded stacks, primary aggregates, up to ~1500 Å long, and a second level of aggregates whose concentration and structure vary as a function of cation type and concentration. Aggregation generally increases with increased solute concentration and with cation radius up to a concentration somewhat above 10 –1 m, at which point the trend reverses. Primary aggregates become more rodlike and larger. The Kirkwood-like reversal probably reflects a change from Derjaguin–Landau–Verwey–Overbeek (DLVO)/Debye behavior controlled by surface chemistry to a frustrated Coulombic system controlled by the solution structure. These data suggest that an understanding of the effects of salt concentration and chemistry on nanoparticle aggregate structures provides useful physical insights into the microscopic origin of slurry rheology in the Hanford and Savannah River legacy wastes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Bridging Control and Deployment: A Cross-Layer Analysis of Scalable Building Cluster Control

Building cluster control has emerged as a promising approach for enabling flexible and coordinated operation of distributed building systems, yet its transition from pilot demonstrations to routine grid-interactive operation remains limited. This paper argues that this gap cannot be explained by control algorithms alone. Instead, it arises from interacting barriers in communication infrastructure, data and semantic interoperability, uncertainty management, stakeholder participation, market design, and policy support. Accordingly, the paper reviews both technical and non-technical barriers to building cluster control. Technical challenges include heterogeneous devices and protocols, communication latency and reliability, distributed decision-making, and uncertainty propagation across aggregated loads. Non-technical barriers include user participation, stakeholder coordination, incentive allocation, and data governance. Existing solution approaches are synthesized, including semantic interoperability frameworks, edge and hierarchical communication architectures, distributed and transactive control strategies, uncertainty-aware optimization, policy mechanisms, and market reforms. Based on this analysis, two research directions are identified: testing infrastructures that can evaluate control performance under realistic multi-building conditions, and abstraction methods that allow building clusters to interact with other energy sectors through standardized flexibility representations. Overall, the paper provides a structured review of how building cluster control can move from isolated demonstrations toward reproducible, market-compatible, and grid-relevant implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

Application of Variable Data Rate (VDR) Towards Channel Optimization

Recognizing the vagaries of channel impediments, one way to optimize aggregate channel information throughput is to maintain a constant symbol rate but vary the modulation scheme and/or the codec rate. The CCSDS VCM and ACM standards promulgation relies upon this kind of an approach. We offer a considerably simpler alternative for spacecraft that are not parked in geo-stationary orbit, one that can rely upon conventional spacecraft housekeeping schedules to change spacecraft and ground operations and will minimize the possibility of requiring any spacecraft hardware accommodations to incorporate. We suggest the use of varying the physical symbol rate within the channel to both initiate acquisition earlier in a pass and retain the link longer as the pass tends toward loss of signal. There is nothing new in what we propose, just a recognition of what has been successful in the past and employed in multiple missions. Integrating over the periodicity of orbit repetition, we shall show that any link that is dependent primarily on a varying range from spacecraft to ground only requires a maximum of five symbol rate transitions in order to optimize total information throughput. By applying these symbol rate transitions using almost rigid rules, we anticipate doubling the information throughput for conventional LEO sun-synchronous orbits. We provide other examples as well.

variable data rate↗

NASA NTRSDate not supplied

Application of Variable Data Rate (VDR) Towards Channel Optimization

Variable Data Rate↗

DOE OSTI2022

Real-time deep-learning inversion of seismic full waveform data for CO 2 saturation and uncertainty in geological carbon storage monitoring

Deep-learning inversion has recently drawn attention in geological carbon storage research due to its potential of imaging and monitoring carbon storage in real time, significantly improving efficiency and safety of carbon storage operations. We present a deep-learning full waveform inversion method that after the neural network has been trained can image CO 2 saturation and its uncertainty in real time. Our deep-learning inversion method is based on the U-Net architecture with the neural network trained on pairs of synthetic seismic data and CO 2 saturation models. Accordingly, our training establishes a mapping relationship between seismic data and CO 2 saturation models and once fully trained directly estimates CO 2 saturation as a function of subsurface location. We further quantify uncertainties of CO 2 saturation estimates using the Monte Carlo dropout method and a bootstrap aggregating method. For this proof-of-concept study, the CO 2 training models and data are derived from the Kimberlina 1.2 model, a hypothetical 3D geological carbon storage model that is constructed based on various geological and hydrological data from the Southern San Joaquin Basin, California. We perform deep-learning inversion experiments using noise-free and noisy training and test data sets and compare the results. Our modelling experiments show that (1) the deep-learning inversion can estimate 2D distributions of CO 2 fairly well even in the presence of Gaussian random noise and (2) both CO 2 saturation imaging and uncertainty quantification can be done in real time. Our results suggest that the deep-learning inversion method can serve as a robust real-time monitoring tool for geological carbon storage and/or other time-varying reservoir/aquifer properties that result from injection, extraction, and/or other subsurface transport phenomena.

58 GEOSCIENCES↗

DOE OSTI2019

Peak selection matters in Principal Component Analysis: A case study of syntrophic microbes

In situ liquid time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful technique to address surface characterization of living biofilms in hydrated conditions. Principal component analysis (PCA) is an important tool to process a large amount of data and interpret the information from ToF-SIMS spectra. However, ToF-SIMS data analysis is still a great challenge in complicated bacterial biofilms, because many interference peaks from the medium may result in inaccurate interpretation of ToF-SIMS spectral analysis. In this study, two syntrophic Geobacter populations were investigated using in situ liquid ToF-SIMS to reveal the biofilm surface changes between them as due to direct interspecies electron transfer (DIET). Peak overlay is an effective strategy to eliminate the matrix effects in handling complex ToF-SIMS data and was used to accomplish peak selection in this work. Both all peak and selected peak spectral PCA showed a distinctive separation among different samples. However, medium samples occupied high scores values in all peak PCA compared with the selected peak PCA, suggesting a strong interference from the medium as the matrix effect. Amino acids and lipids contributed significantly in separating all samples in selected peak PCA, which indicated that surface membrane components such as pili and proteins are important in the co-cultured Geobacter community compared to controls such as the single population planktonic cells and biofilms, respectively. Additionally, the spectral PCA results of high intensity and high resolution data obtained from liquid ToF-SIMS were compared. Selected peak PCA obtained nice separation among samples in both data sets; however, the high resolution data showed better separation between co-culture planktonics and co-culture aggregates, confirming that the higher mass accuracy is useful in analysis of microbial samples. Furthermore, amino acid and water cluster as an important media for microbial metabolite were selected for a more focused selected peak PCA comparison. Consistent scores and loadings plots were achieved. In conclusion, we show that peak selection is critical for acquiring effective microbial information and interpretation of syntrophic Geobacter using spectral data from in situ liquid ToF-SIMS.

spectral overlay, peak selection, matrix effect, P↗

DOE OSTI2017

Light Water Reactor Sustainability Program Interrogation of Alkali-Silica Reaction Degraded Concrete Samples using Acoustic and Thermal Techniques to Support Development of a Structural Health Monitoring Framework

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Health monitoring of concrete structures is performed to understand the current condition of a structure based on heterogeneous measurements and then produce high-confidence actionable information regarding structural integrity. This information can then be used to support operational and maintenance decisions. The proposed diagnosis and prognosis framework consists of four elements: health monitoring, data analytics, uncertainty quantification, and prognosis. The objectives of this ongoing research project focuses on health monitoring and data analytics of concrete slab cast, which is cured using four pockets of reactive aggregates: pure silica, wells, placitas, and spratt. A controlled concrete slab with four aggregates is cast at Vanderbilt University in representative conditions to accelerate degradation due to alkali-silica reaction (ASR). Four nondestructive evaluation (NDE) techniques (thermography, mechanical deformation measurements, nonlinear impact resonance-acoustic spectroscopy, and vibro-acoustic modulation) are used to examine the degraded concrete slab. Heterogeneous data from these techniques are analyzed for assessing ASRrelated degradation in concrete samples. In addition, this report discusses thermography assessment of three cement bricks cured under different conditions to accelerate ASR-related degradation. The application of the digital image correlation technique to study ASR-related degradation on a large concrete sample at the University of Tennessee Knoxville is discussed and initial observations are presented in this report. The results from the data analysis of the NDE techniques on concrete slab cured at Vanderbilt University are discussed in detail in this report. The major outcome of the analysis suggests that the nonlinear impact resonance acoustic spectroscopy is able to detect potential degradation in a concrete slab but is unable to locate or isolate the degradation. Alternatively, the vibro-acoustic technique is able to detect degradation and locate the damage in the concrete slab cast. The outcomes supports development of a structural health monitoring framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Extending OpenSHMEM with Aggregation Support for Improved Message Rate Performance

OpenSHMEM is a highly efficient one-sided communication API that implements the PGAS parallel programming model, and is known for its low latency communication operations that can be mapped efficiently to RDMA capabilities of network interconnects. However, applications that use OpenSHMEM can be sensitive to point-to-point message rates, as many-to-many communication patterns can generate large amounts of small messages which tend to overwhelm network hardware that has predominantly been optimised for bandwidth over message rate. Additionally, many important emerging classes of problems such as data analytics are similarly troublesome for the irregular access patterns they employ. Message aggregation strategies have been proven to significantly enhance network performance, but their implementation often involves complex restructuring of user code, making them unwieldy. This paper shows how to combine the best qualities of message aggregation within the communication model of OpenSHMEM such that applications with small and irregular access patterns can improve network performance while maintaining their algorithmic simplicity. We do this by providing a path to a message aggregation framework called conveyors through a minimally intrusive OpenSHMEM extension introducing aggregation contexts that fit more naturally to the OpenSHMEM atomics, gets, and puts model. We test these extensions using four of the bale 3.0 applications which contain essential many-to-many access patterns to show how they can produce performance improvements of up to 65×.

Welch, Aaron↗

DOE OSTI2025

Considerations for Distributed Edge Data Centers and Use of Building Loads to Support Large Interconnections

The rapid expansion of artificial intelligence (AI) and machine learning is driving unprecedented electricity demand from data centers. It is predicted that by 2030, 90% of AI workloads will be inference-based, requiring interconnection of multiple low-latency edge data centers (<20 MW) sited closer to end users - often on already constrained distribution feeders. Although individually small, these loads can aggregate to large loads per feeder, straining infrastructure, creating multi-year interconnection delays, and driving up customer costs. This paper proposes a data center-focused grid-integration framework that combines feeder hosting capacity analysis with building energy efficiency, building load flexibility, and waste heat reuse to expand effective feeder and substation headroom. Such approaches can reduce interconnection delays, lower costs for ratepayers, and accelerate AI-ready infrastructure deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Hydrogen-bonded aggregates in precise acid copolymers

We perform atomistic molecular dynamics simulations of melts of four precise acid copolymers, two poly(ethylene-co-acrylic acid) (PEAA) copolymers, and two poly(ethylene-co-sulfonic acid) (PESA) copolymers. The acid groups are spaced by either 9 or 21 carbons along the polymer backbones. Hydrogen bonding causes the acid groups to form aggregates. These aggregates give rise to a low wavevector peak in the structure factors, in agreement with X-ray scattering data for the PEAA materials. The structure factors for the PESA copolymers are very similar to those for the PEAA copolymers, indicating a similar distance between aggregates which depends on the spacer length but not on the nature of the acid group. The PEAA copolymers are found to form more dimers and other small aggregates than do the PESA copolymers, while the PESA copolymers have both more free acid groups and more large aggregates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

NREL OpenPATH: An Open-Source, Extensible Platform for Instrumenting Travel Behavior Data

NREL OpenPATH is an open-source, extensible platform that allows communities to instrument their own travel behavior data. The platform consists of a smartphone app, server and analysis pipeline, and enables collection of opt-in, multi-modal, end-to-end travel diaries. It makes the aggregate statistics available via a public dashboard, and allows deployers to download and visualize trip and trajectory data through the admin dashboard. It also allows for customization of the initial demographic survey and the trip-level qualitative information collected. Our goal is to provide an easy-to-use tool that can democratize travel behavior data collection by empower communities of all sizes to recruit participants and obtain a holistic picture of their travel patterns. The platform has been used by close to 40 partners, to collect data from thousands of participants. Upon signing a simple MOU, it is currently available for free to universities, non-profits and public agencies in the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Effective Storage of Electrons in Water by the Formation of Highly Reduced Polyoxometalate Clusters

Aqueous solutions of polyoxometalates (POMs) have been shown to have potential as high-capacity energy storage materials due to their potential for multi-electron redox processes, yet the mechanism of reduction and practical limits are currently unknown. Herein, we explore the mechanism of multi-electron redox processes that allow the highly reduced POM clusters of the form {MO 3 } y to absorb y electrons in aqueous solution, focusing mechanistically on the Wells-Dawson structure X 6 [P 2 W 18 O 62 ], which comprises 18 metal centers and can uptake up to 18 electrons reversibly (y = 18) per cluster in aqueous solution when the countercations are lithium. This unconventional redox activity is rationalized by density functional theory, molecular dynamics simulations, UV-vis, electron paramagnetic resonance spectroscopy, and small-angle X-ray scattering spectra. These data point to a new phenomenon showing that cluster protonation and aggregation allow the formation of highly electron-rich meta-stable systems in aqueous solution, which produce H 2 when the solution is diluted. Finally, we show that this understanding is transferrable to other salts of [P 5 W 30 O 110 ] 15- and [P 8 W 48 O 184 ] 40- anions, which can be charged to 23 and 27 electrons per cluster, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Ionic conductivity and dielectric permittivity of PEO-LiClO{sub 4} solid polymer electrolyte plasticized with propylene carbonate

We have studied ionic conductivity and dielectric permittivity of PEO-LiClO{sub 4} solid polymer electrolyte plasticized with propylene carbonate. Differential scanning calorimetry and X-ray diffraction studies confirm minimum volume fraction of crystalline phase for the polymer electrolyte with 40 wt. % propylene carbonate. The ionic conductivity exhibits a maximum for the same composition. The temperature dependence of the ionic conductivity has been well interpreted using Vogel-Tamman-Fulcher equation. Ion-ion interactions in the polymer electrolytes have been studied using Raman spectra and the concentrations of free ions, ion-pairs and ion-aggregates have been determined. The ionic conductivity increases due to the increase of free ions with the increase of propylene carbonate content. But for higher content of propylene carbonate, the ionic conductivity decreases due to the increase of concentrations of ion-pairs and ion-aggregates. To get further insights into the ion dynamics, the experimental data for the complex dielectric permittivity have been studied using Havriliak–Negami function. The variation of relaxation time with temperature obtained from this formalism follows Vogel-Tamman-Fulcher equation similar to the ionic conductivity.

36 MATERIALS SCIENCE↗