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At least 1,657 records · Page 92

QED: A Powerful Query Equivalence Decider for SQL

Checking query equivalence is of great significance in database systems. Prior work in automated query equivalence checking sets the first steps in formally modeling and reasoning about query optimization rules, but only supports a limited number of query features. In this paper, we present Qed, a new framework for query equivalence checking based on bag semantics. Qed uses a new formalism called Q-expressions that models queries using different normal forms for efficient equivalence checking, and models features such as integrity constraints and NULLs in a principled way unlike prior work. Our formalism also allows us to define a new query fragment that encompasses many real-world queries with a complete equivalence checking algorithm, assuming a complete first-order theory solver. Empirically, Qed can verify 299 out of 444 query pairs extracted from the Calcite framework and 979 out of 1287 query pairs extracted from CockroachDB, which is more than 2× the number of cases proven by prior state-of-the-art solver.

Computer Science↗

On-Orbit Quantitative Real-Time Gene Expression Analysis Using the Wetlab-2 System

NASA Ames Research Center's WetLab-2 Project enables on-orbit quantitative Reverse Transcriptase PCR (qRT-PCR) analysis without the need for sample return. The WetLab-2 system is capable of processing sample types ranging from microbial cultures to animal tissues dissected on-orbit. The project developed a RNA preparation module that can lyse cells and extract RNA of sufficient quality and quantity for use as templates in qRT-PCR reactions. Our protocol has the advantage of using non-toxic chemicals and does not require alcohols or other organics. The resulting RNA is dispensed into reaction tubes that contain all lyophilized reagents needed to perform qRT-PCR reactions. System operations require simple and limited crew actions including syringe pushes, valve turns and pipette dispenses. The project selected the Cepheid SmartCycler (TradeMark), a Commercial-Off-The-Shelf (COTS) qRT-PCR unit, because of its advantages including rugged modular design, low power consumption, rapid thermal ramp times and four-color multiplex detection. Single tube multiplex assays can be used to normalize for RNA concentration and integrity, and to study multiple genes of interest in each module. The WetLab-2 system can downlink data from the ISS to the ground after a completed run and uplink new thermal cycling programs. The ability to conduct qRT-PCR and generate results on-orbit is an important step towards utilizing the ISS as a National Laboratory facility. Specifically, the ability to get on-orbit data will provide investigators with the opportunity to adjust experimental parameters in real time without the need for sample return and re-flight. On orbit gene expression analysis can also eliminate the confounding effects on gene expression of reentry stresses and shock acting on live cells and organisms or the concern of RNA degradation of fixed samples and provide on-orbit gene expression benchmarking prior to sample return. Finally, the system can also be used for analysis of air, surface, water, and clinical samples to monitor environmental pathogens and crew health. The validation flight of the WetLab-2 system using E. coli bacteria and mouse liver launched on SpaceX-7 in June 2015 and will remain on the ISS National Laboratory.

ISS tools↗

NASA Earth Systems Digital Twins (ESDT)

"Similarly to artificial intelligence, which is now revolutionizing many aspects of our daily lives, Earth system digital twin technologies have the potential to revolutionize the way Earth Science research will be conducted in the future, and how results and knowledge from this research will provide information to support decision making and yield impactful societal benefits. An Earth System Digital Twin or ESDT is a dynamic and interactive information system that first provides a digital replica of the past and current states of the Earth or Earth system as accurately and timely as possible; second, allows for computing forecasts of future states under nominal assumptions and based on the current replica; and third, offers the capability to investigate many hypothetical scenarios under varying impact assumptions. In other words, an ESDT provides the integrated What-Now, What-Next, and What-If pictures of the Earth or Earth system, by continuously ingesting newly observed data and by leveraging multiple interconnected models, machine learning as well advanced computing and visualization capabilities. Digital twins have been developed in engineering since 2002, but the interest in digital twins for the Earth domain is more recent and stems from the convergence of several developments: - The huge amount of diverse data that has now been collected continuously for more than 50 years, and that is becoming more and more difficult to access, understand, and utilize. - At the same time, because of climate change and its impacts the information produced by all of this data is becoming of interest to many new non-traditional users for analyzing and predicting various phenomena. - Because of advances in computational and visualization capabilities and the parallel unprecedented development of machine learning (ML), extracting relevant information from these large amounts of data and running complex models faster has become possible. As a result, it is becoming necessary and possible to build intuitive and interactive frameworks that will enable users with various skill levels and/or organizational hierarchy levels to easily access large amounts of targeted information along with the relevant tools and models (Earth system and human activity models), to support them in analyzing and visualizing this information, to help them understand interactions among models, to visualize the potential outcomes of various impacts, and to support decision or policy making. The full power of digital twins is that, through an integrated representation and standardized tools and software technologies, the same digital replica can address the needs of multiple users at various resolutions (spatial and temporal) and for various applications (science, economic, policy, etc.) – “from farmer to scientist”. With all these interests at stake, the challenges of building optimal digital twins are many and complex. The first challenge is to determine if a Digital Twin should be global or local, and multi-domain or thematic. For example, some domains such as Climate or Weather will require a global Digital Twin or Digital Twin capabilities while science areas such as Biodiversity might be more local. We can also envision that multiple thematic ESDTs, e.g., Air Quality, Wildfires, Hydrology could be federated or provide input to other ESDTs, either on a regional level or to a more global ESDT. Overall, we can imagine a future “web” of Digital Twins co-existing in a hierarchy or in a network, and capable of being connected or federated depending on the needs. This last point brings up the very important challenge of interoperability, including standards and protocols that will need to be built into these systems from the beginning. Each individual digital twin would have full flexibility in internal construction but would need standards-based interfaces (input and output) or hooks to make it compatible with others. Another challenge when building digital twins will be to decide how to organize each digital replica. Based on the applications targeted by the DT under implementation, various amounts and types of raw data, Analysis Ready Data (ARD) and information will need to be incorporated. Depending on the required latencies and needs of the users, various solutions can be considered, including Data Cubes, Data Lakes, pointers, or computing information on demand. We envision that each ESDT will choose a solution adapted to its specific objectives. Another important challenge is the type(s) of visualization that will be used, as well as the level of interactivity and refresh rate that will be required. Again, this will depend on the objectives of the ESDT, but also on the various users’ needs. In most cases, several types of visualizations and human interfaces will need to be offered depending on the projected users of that system. In parallel to the challenges highlighted above, there are also many tools and technologies that will need to be developed or improved for all types of digital twins. Among those are improved machine learning technologies, for example providing explainability, but also ML techniques for causality and providing a better integration of physics models. Additionally, reliable uncertainty quantification methods will be needed for all ESDT components, from validating data fusion and assimilation to assessing the accuracy of ML models and weighing the values of decisions supported by those systems. This presentation introduces the ESDT concept, presents several ESDT use cases, and a proposed ESDT architecture framework, as well as various technologies being developed by the Advanced Information Systems Technology (AIST) Program."

Earth Science Remote Sensing; Information Systems↗

Facile Fabrication of Self‐Assembly Functionalized Polythiophene Hole Transporting Layer for High Performance Perovskite Solar Cells

Abstract Crystallinity and crystal orientation have a predominant impact on a materials’ semiconducting properties, thus it is essential to manipulate the microstructure arrangements for desired semiconducting device performance. Here, ultra‐uniform hole‐transporting material (HTM) by self‐assembling COOH‐functionalized P3HT (P3HT‐COOH) is fabricated, on which near single crystal quality perovskite thin film can be grown. In particular, the self‐assembly approach facilitates the P3HT‐COOH molecules to form an ordered and homogeneous monolayer on top of the indium tin oxide (ITO) electrode facilitate the perovskite crystalline film growth with high quality and preferred orientations. After detailed spectroscopy and device characterizations, it is found that the carboxylic acid anchoring groups can down‐shift the work function and passivate the ITO surface, retarding the interface carrier recombination. As a result, the device made with the self‐assembled HTM show high open‐circuit voltage over 1.10 V and extend the lifetime over 4,300 h when storing at 30% relative humidity. Moreover, the cell works efficiently under much reduced light power, making it useful as power source under dim‐light conditions. The demonstration suggests a new facile way of fabricating monolayer HTM for high efficiency perovskite devices, as well as the interconnecting layer needed for tandem cell.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Lumley's PODT definition of large eddies and a trio of numerical procedures

Lumley's 1967 Moscow paper provided, for the first time, a completely rational definition of the physically-useful term 'large eddy', popular for a half-century. The numerical procedures based upon his results are: (1) PODT (Proper Orthogonal Decomposition Theorem), which extracts the Large Eddy structure of stochastic processes from physical or computer simulation two-point covariances, and 2) LEIM (Large-Eddy Interaction Model), a predictive scheme for the dynamical large eddies based upon higher order turbulence modeling. Earlier Lumley's work (1964) forms the basis for the final member of the triad of numerical procedures: this predicts the global neutral modes of turbulence which have surprising agreement with both structural eigenmodes and those obtained from the dynamical equations. The ultimate goal of improved engineering design tools for turbulence may be near at hand, partly due to the power and storage of 'supermicrocomputer' workstations finally becoming adequate for the demanding numerics of these procedures.

Payne, Fred R.↗

Squeezing Every Last 'Bit' of Information from Enceladus Mass Spectrometry

Potential opportunities to return to Enceladus in Discovery and Flagship class missions inspire development of next-generation instruments and creative approaches to sample collection, sample analysis, and data analysis and transmission strategies. Mass spectrometers (MS) are ideally suited to future Enceladus missions due to their analytical power in identifying a range of molecular and ionic compositions – including complex organics – and potentially astrobiologically-important features such as isotope ratios, chirality, and enantiomeric excess. However, long communication delays from Enceladus and limited bandwidth limits the data transmission from these higher-data-volume instruments, likely delaying mission-related response to new data. We explore the utility of data science and machine learning (ML) on isotope ratio (IR)MS data collected from laboratory analogs of Enceladus to: 1) process data quickly for rapid ground-based analyses, 2) understand if compositional and biosignature information could be extracted from IRMS data, and 3) evaluate whether onboard ML techniques could improve sample analysis, cadence, and transmission prioritization. Laboratory analogs analyzed isotopes of volatile CO2 that interacted with seawaters of varying composition, and include both abiotic and biotic (microbially-influenced) experiments. Enceladus’s alkaline oceans promote speciation of carbon into multiple forms (e.g., H2CO3 / CO2, HCO3-, and CO32-), each of which could be isotopically fractionated by abiotic or biotic reactions. Large (>2‰) changes in carbon isotopes (δ13C) are observed from some biotic experiments inoculated with complex microbial ecosystems relative to the abiotic seawaters. ML training and classification suggests that microbial samples can be distinguished from abiotic samples, yet that a broad range of microbial experiments are necessary to train ML models to cover a range of complexities including disequilibria, and isotopic and compositional fractionation.

geochemistry↗

A New Era of H-O-C-S Magma Solubility Modeling: Better, Faster, Stronger

H 2 O, CO 2 , and S are the most abundant volatiles in magmatic systems and are critical to understanding magma storage, phase equilibria, and volcanic eruptions. Models that consider all three of these components, however, may not allow for critical examination and adjustment of assumptions underlying the model, or provide benchmark testing or extensible interfaces. Thus, understanding why models produce different results can be challenging. We have gathered authors of established (D-Compress) and recent (VolFe, EVo, Sulfur_X, MAGEC) H-O-C-S volatile solubility models to work together to understand how and why our models diverge. We present a series of benchmark basalt degassing scenarios revealing that often understated model assumptions such as fO 2 buffer equations, fO 2 -Fe 3+ /ΣFe relationships, and even major element normalization routines have outsized effects on model results. All models consider S 2- and S 6+ melt species but with different approaches to sulfate/sulfide capacities, partition coefficients, and species fugacities, leading to divergence in the evolution of modeled gas compositions, melt S and Fe speciation, and fO 2 , with the extent of divergence depending on melt composition. Such scenarios enable meaningful intercomparison of existing models and lay the groundwork for a user-friendly yet powerful solubility modeling framework. Given our wealth of existing solubility literature, we suggest that the field of magmatic volatiles should focus now on the creation of modern tools and the modular implementation of existing model equations or methods, and that the evaluation of code usability, transparency, and benchmarking should be codified pillars of the peer-review process. As an example of such an endeavor, we present early work coupling these sulfur solubility models with VESIcal, an extensible and rigorously tested python library containing seven existing H 2 O-CO 2 solubility models. VESIcal includes the ability to extract, edit, and even interchange assumptions underlying any model. For example, users may combine or swap separately published H 2 O, CO 2 , and S models, as well as underlying model choices, such as Equations of State and redox models.

volatiles in magmas↗

Reflection and Timing Study of the Transient Black Hole X-Ray Binary MAXI J1803-298 with NuSTAR

The transient black hole X-ray binary MAXI J1803−298 was discovered on 2021 May 1, as it went into outburst from a quiescent state. As the source rose in flux it showed periodic absorption dips and fit the timing and spectral characteristics of a hard-state accreting black hole. We report on the results of a Target-of-Opportunity observation with NuSTAR obtained near the peak outburst flux beginning on 2021 May 13, after the source had transitioned into an intermediate state. MAXI J1803−298 is variable across the observation, which we investigate by extracting spectral and timing products separately for different levels of flux throughout the observation. Our timing analysis reveals two distinct potential quasiperiodic oscillations (QPOs) which are not harmonically related at 5.4 ± 0.2 Hz and 9.4 ± 0.3 Hz, present only during periods of lower flux. With clear relativistic reflection signatures detected in the source spectrum, we applied several different reflection models to the spectra of MAXI J1803−298. Here we report our results, utilizing high-density reflection models to constrain the disk geometry, and assess changes in the spectrum dependent on the source flux. With a standard broken power-law emissivity, we find a near-maximal spin for the black hole, and we are able to constrain the inclination of the accretion disk at 75° ± 2°, which is expected for a source that has shown periodic absorption dips. We also significantly detect a narrow absorption feature at 6.91 ± 0.06 keV with an equivalent width between 4 and 9 eV, which we interpret as the signature of a disk wind.

Benjamin M. Coughenour↗

Multiparameter optical fiber sensing for energy infrastructure through nanoscale light–matter interactions: From hardware to software, science to commercial opportunities

Monitoring of energy infrastructure through robust yet economical sensing platforms is becoming an area of increased importance, with ubiquitous applications including the electrical grid, natural gas and oil transportation pipelines, H2 infrastructure (storage and transportation), carbon storage, power generation, and subsurface environments. Plasmonic and functional nanomaterial enabled fiber optic sensors show excellent promise for a wide range of sensing applications due to their versatility to be engineered for specific analytes of interest while retaining inherent advantages of the optical fiber sensor platform. Through the design of novel sensing layers, the optical transduction mechanism and wavelength dependence can also be tailored for ease of integration with low-cost interrogation systems enabling an inexpensive yet highly functional optical fiber sensing platform. In addition, recent advances in artificial intelligence and machine learning theoretical methods have been leveraged to simultaneously extract multiple parameters through multi-wavelength interrogation such that unique wavelengths can also serve as unique sensing elements, analogous to electronic nose sensor technologies. The concept of an optical fiber based “photonic nose” via multiple interrogation wavelengths and/or sensor nodes offers a compelling platform technology to realize multiparameter speciation of chemical analytes within complex gas mixtures. In this Perspective, we further generalize the notion of multiparameter sensing through the novel “photonic nervous system” concept based upon low-cost, functionalized optical fiber sensor probes monitoring a variety of distinct analyte classes (physical, chemical, electromagnetic, etc.) simultaneously to provide broad situational awareness via integrated sensors.

Su, Yang-Duan (ORCID:0000000214820902)↗

A Harmonics Interferometric Doppler Sensor With a Neon Lamp Detector

A cost-effective harmonic interferometric Doppler sensor has been developed to obtain both amplitude and phase of the micro-Doppler signatures of moving objects. A phase chopper is used to generate the harmonics of the interferometry signal. For cost-effectiveness, a Gunn diode source is used for signal generation and a neon lamp is employed as a broadband detector. An advanced signal processing algorithm has been developed to extract both amplitude and phase Doppler signatures. A prototype has been built to demonstrate the effectiveness of the harmonic interferometric Doppler sensor at 35 GHz, with Doppler objects such as human hand and metal objects. In addition, the broadband detection capability of the neon lamp allows the Doppler sensor to work up to the millimeter-wave regime and potentially beyond the terahertz (THz) wave regime. Due to the ruggedness of the neon lamp detector, it is expected that the Doppler sensor has important applications of sensing and wireless communication in harsh environment such as high-temperature, high-power and radioactive conditions.

Doppler sensor↗

A hollow cathode neutralizer for a 30-cm diameter bombardment thruster

Recent improvements in overall thrustor performance have imposed new constraints on neutralizer performance. The use of compensated grid extraction system requires a re-evaluation of neutralizer position. In addition a suitable control logic for the neutralizer has proven difficult. A series of tests were conducted to determine what effect neutralizer cathode geometry has on performance. The parameters investigated included orifice diameter and length, and cathode diameter. Similar tests investigated open and enclosed keeper geometries. Neutralizer position tests with compensated grids suggest positions approximately 10 cm from the accelerator and radially out of the beam envelope should result in satisfactory performance and long life. Finally operation at keeper currents of 1.5 amp has resulted in lower total neutralizer power, the elimination of tip heater power, and suitable closed loop control of the neutralizer vaporizer.

Bechtel, R. T.↗

Lunar base siting

As with any planetary body, the lunar surface is quite heterogeneous. There are widely dispersed sites of particular interest for known and potential resource availability, selenology, and lunar observatories. Discriminating characteristics include solar illumination, view of earth, local topography, engineering properties of the regolith and certain geological features, and local mineralogy and petrology. Space vehicle arrival and departure trajectories constitute a minor consideration. Over time, a variety of base sites will be developed serving different purposes. Resource-driven sites may see the fastest growth during the first decades of lunar development, but selection of the most favorable sites is likely to be driven by suitability for a combination of activities. As on earth, later development may be driven by geographical advantages of surface transportation routes. With the availability of near-constant sunlight for power generation, as well as permanently shadowed areas at cryogenic temperatures, polar sites are attractive because they require substantially less earth-launched mass and lower equipment complexity for an initial permanent base. Discovery of accessible volatiles reservoirs, either in the form of polar permafrost or gas reservoirs at other locations, would dramatically increase the attractiveness of any site from a logistical support and selenological point of view. Amid such speculation, no reliable evidence of such volatiles exist. More reliable evidence exists for areas of certain mineral concentrations, such as ilmenite, which could form a feedstock for some proposed resource extraction schemes. While tentative selections of advantageous base sites are made, new data from lunar polar orbiters and the Galileo polar flybys would be very helpful.

Staehle, Robert L.↗

Feasibility Investigation for Performing Fireball Temperature Tests

NASA Johnson Space Center White Sands Test Facility (WSTF) was requested by the Launch Abort Subpanel and the Power Systems Subpanel of the Interagency Nuclear Safety Review Panel to investigate the feasibility of using spectroscopic techniques to measure propellant fireball gas temperatures. This report outlines the modeling and experimental approaches and results of this investigation. Descriptions of the theoretical particle temperature and mass effusion models are presented along with the results of the survivability of small plutonium dioxide (less than or equal to 1000 microns diameter) particles entrained in various propellant fireball scenarios. The experimental test systems used to measure the hydroxide radical, water, and particle graybody spectral emissions and absorptions are discussed. Spectral results along with temperatures extracted by analyzing the spectral features are presented for the flames investigated in the laboratory environment. Methods of implementing spectroscopic measurements for future testing using the WSTF Large-scale Hydrogen/Oxygen Explosion Facility are discussed, and the accuracy expected for these measurements is estimated from laboratory measurements.

Tapphorn, Ralph M.↗

Modeling a Sodium Heat Pipe Experiment at SPHERE Using Sockeye

The Single Primary Heat Extraction and Rejection Emulator (SPHERE) facility at Idaho Na- tional Laboratory was recently utilized to generate data for the startup and steady operation of a high-performance, sodium heat pipe over the course of 1000 hours, as a test of detrimental, long-term effects of heat pipe operation. The setup consists of a single, sodium heat pipe enclosed in a stainless-steel vacuum chamber, heated radiatively via a cylindrical ceramic fiber heater configuration and cooled via a water-cooled calorimeter. Measurements include temperatures at several axial locations along the outer surface of the heat pipe, the power provided to the heaters, and the heat removal rate of the calorimeter. In this work, this data is utilized to validate heat pipe models in the heat pipe application Sockeye, which is based upon the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Sockeye provides various heat pipe models at an engineering scale appropriate for the multiphysics simulation of microreactors, which may feature several hundred heat pipes. This work details models of this experiment in SPHERE using various heat pipe models with Sockeye, including heat conduction-based models and compressible flow models of the heat pipe interior. These models are compared to the experimental data to assess the accuracy of several aspects of heat pipe modeling, including frozen startup, the effect of non-condensable gases, and the coupling of the heat pipe to its environment.

97 - MATHEMATICS AND COMPUTING↗

Modeling a Sodium Heat Pipe Experiment at SPHERE Using Sockeye

The Single Primary Heat Extraction and Rejection Emulator (SPHERE) facility at Idaho National Laboratory was recently utilized to generate data for the startup and steady operation of a high-performance, sodium heat pipe over the course of 1,000 hours to test the detrimental, long-term effects of heat pipe operation. The setup consisted of a single, sodium heat pipe enclosed in a stainless-steel vacuum chamber, heated radiatively via a cylindrical ceramic-fiber heater configuration and cooled via a water-cooled calorimeter. Measurements included temperatures at several axial locations along the outer surface of the heat pipe, the power provided to the heaters, and the heat removal rate of the calorimeter. In this work, we use this data to validate heat pipe models in Sockeye, a heat pipe application based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Sockeye provides various heat pipe models at an engineering scale appropriate for the multiphysics simulation of microreactors, which may feature several hundred heat pipes. This work details models of this experiment at SPHERE using various heat pipe models with Sockeye, including heat-conduction-based and compressible flow models of the heat pipe interior.

97 - MATHEMATICS AND COMPUTING↗

TRANSENSOR: Transformer Real-time Assessment INtelligent System with Embedded Network of Sensors and Optical Readout. Final Report

Utilities across the world are wrestling with evolving market dynamics, population growth and climate change. Distributed Energy Resources (DERs) such as solar photovoltaics, distributed generators and energy storage systems are becoming important parts of the U.S. energy mix. These factors are driving an increasing need for low-cost grid asset monitoring. Aside from being costly, traditional utility monitoring systems are not sufficiently robust and do not provide real-time visibility into the condition of grid assets such as transformers. Lack of accurate real-time measurements on performance has resulted in the use of lagging indicators, such as oil sample analysis. To address this need, an innovative embedded optical sensing technology, Transformer Real-time Assessment Intelligent System (TRANSENSOR) was developed, validated and demonstrated in this project. To date, TRANSENSOR has focused on transformers but is extendable to other grid assets. In addition to the technology being embedded into new transformers during manufacturing, a retrofit configuration that can be installed on existing transformers in the field was also developed. It is anticipated that the ability to retrofit existing transformers will help accelerate adoption of the underlying TRANSENSOR technology. Phase 1 of the project focused on laboratory development and qualification of the technology. Following iterations and exploration of relevant optical sensing modalities and multiplexed configurations of interest for the transformer environment, an effective candidate configuration was agreed upon, down-selected and custom-designed for embedding into General Electric (GE) network transformers. Two new GE 500 kilovolt ampere (kVA), 27 kilovolt (kV) distribution network transformers were built with embedded fiber-optic (FO) sensors and successfully qualified per industry standards at GE’s Shreveport, Louisiana facility during Phase 1 of the project. Following the successful completion of Phase 1, the team proceeded to Phase 2, which focused on a field demonstration of the technology. Over Phase 2, the first new GE transformer built with embedded fiber-optic sensors was installed in an above-ground cage and connected to the grid at Con Edison’s Astoria facility. A second transformer equipped with TRANSENSOR was installed in an underground vault. Additionally, an older (1982 year model) GE transformer in an above-ground cage was retrofitted with fiber- optic sensors and reconnected to the grid at ConEd’s facility. Analysis of data acquired from the sensors showed interesting correlations with transformer loading. Additionally, key events such as transformer low-voltage network connection, primary-side energizing, and a pressure loss event from an oil sampling were detected by the TRANSENSOR system. Online data processing/feature extraction algorithms for the second transformer in the underground vault detected key features and event alerts that were transmitted through a wireless 4G connection. The remote deployment concept showed promising results with data collection running for a total of 8 months across the three (3) GE transformers instrumented for the Phase 2 field demonstration. This sets the stage well for further development and commercialization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Disorder Dynamics in Battery Nanoparticles During Phase Transitions Revealed by Operando Single-Particle Diffraction

Structural and ion-ordering phase transitions limit the viability of sodium-ion intercalation materials in grid scale battery storage by reducing their lifetime. However, the combination of phenomena in nanoparticulate electrodes creates complex behavior that is difficult to investigate, especially on the single-nanoparticle scale under operating conditions. In this work, operando single-particle X-ray diffraction (oSP-XRD) is used to observe single-particle rotation, interlayer spacing, and layer misorientation in a functional sodium-ion battery. oSP-XRD is applied to Na 2/3 [Ni 1/3 Mn 2/3 ]O 2 , an archetypal P2-type sodium-ion-positive electrode material with the notorious P2-O2 phase transition induced by sodium (de)intercalation. Here, it is found that during sodium extraction, the misorientation of crystalline layers inside individual particles increases before the layers suddenly align just prior to the P2-O2 transition. The increase in the long-range order coincides with an additional voltage plateau signifying a phase transition prior to the P2-O2 transition. To explain the layer alignment, a model for the phase evolution is proposed that includes a transition from localized to correlated Jahn-Teller distortions. The model is anticipated to guide further characterization and engineering of sodium-ion intercalation materials with P2-O2 type transitions. oSP-XRD, therefore, opens a powerful avenue for revealing complex phase behavior in heterogeneous nanoparticulate systems.

25 ENERGY STORAGE↗

Constituent Data Replacement Tool

The purpose of this tool is to estimate key parameters that may be missing in public wastewater composition datasets. The tool can be applied to develop complete treatment and critical mineral extraction profiles for leachate, produced water and other aqueous waste streams. The tool applies machine learning algorithms to replace missing data in a user’s water data set that are adjusted based on user preferences for options including algorithm type, number of features, and classification variables. The tool can use the user’s data alone or combine user data with the NEWTS USGS Produced Water Database for more robust training. This research was funded by the U.S. Department of Energy’s Office Fossil Energy and Carbon Management (FECM) through National Energy Technology Laboratory’s ongoing research under the Water Management for Power System Field Work Proposal, DE-FECM 1022428 and Critical Minerals Field Work Proposal, DE-FECM 1022420.

Aqueous Chemistry↗