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At least 451 records · Page 25

Simulation of Particulate Transport for Delivery of Solid Amendments into the Subsurface: FY24 Status Report

For particulate-based amendments to be viable for field-scale remediation at the Hanford Site (e.g., 200 DV-1 Operable Unit), particles need to be delivered a sufficient radial distance from an injection well and retained at concentrations high enough for effective treatment. An accurate description of the particle radius of influence (ROI) is critical for developing an overall remediation strategy. However, field-scale particle simulations are currently limited due to insufficient simulation capabilities and a lack of experimental data to validate and parameterize particle transport models. To help build toward field-scale deployment, this fiscal year (FY) we have (1) developed a pre screening tool to estimate particle transport, (2) implemented particle transport models within PFLOTRAN, and (3) conducted preliminary estimations of particle ROI. While field-scale numerical simulations will ultimately be necessary before remedy design and field implementation, we have developed a pre-screening tool that offers valuable estimations of expected particle injectability and ROI in a 1-D system. The advantage of the tool is that it does not require extensive laboratory experiments and instead makes predictions based solely on routine laboratory measurements. This tool can assist in down-selection and decision-making by identifying which particle amendment systems are worth pursuing in future laboratory experiments, such as 1-D column tests and beyond. With any system, scaling up from the lab to the field presents challenges. Currently, there is no field data available for model calibration or validation. However, the theoretical particle models being developed herein are the best tools available to guide progress toward field deployment. To help bridge this gap and verify model predictions, larger-scale lab experiments are being proposed. To advance simulation capabilities, six particle transport models are being integrated into the reactive transport simulator PFLOTRAN. These include colloid filtration theory (CFT) and five additional particle transport models (M1-M5). Each model, from M1 to M5, progressively incorporates additional particle transport and retention processes. Ultimately, the simplest model capable of accurately describing 1-D column data will be selected and parameterized. During FY24, the CFT and M1 model have been fully implemented within PFLOTRAN. Using an existing 1 D column experiment, the two currently implemented particle transport models (CFT and M1), and associated parameters, were fit to this experiment. While simpler model formulations are helpful for estimations, these formulations could not fully describe particle transport and retention behavior in the previous 1-D column experiment. Thus, additional complexities will need to be considered, which will be accounted for in the M2-M5 model formulations. Additionally, because a viscous, shear thinning fluid was required to keep particles in suspension, considerations for flow will also need to also be accounted for. Therefore, a new immiscible two-phase flow mode is currently being implemented in PFLOTRAN. With some modifications, this new flow module could also support simulation of non-Newtonian liquid amendments, foams, and emulsions. We also estimated the expected ROI of solid amendments using 1-D simulations. The average predicted ROI was approximately 15 ft for micron-sized zero valent iron (mZVI) suspended in xanthan gum (XG). Using the pre screening tool and ROI estimates, additional amendment-delivery laboratory characterization and experiments are proposed. The results from additional experiments can be used to validate and parametrize particulate transport model formulations, which will ultimately provide predictive capabilities for field amendment-delivery systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Applying Costs, Risks and Values Evaluation (CRAVE) methodology to Engineering Support Request (ESR) prioritization

Given limited budget, the problem of prioritization among Engineering Support Requests (ESR's) with varied sizes, shapes, and colors is a difficult one. At the Kennedy Space Center (KSC), the recently developed 4-Matrix (4-M) method represents a step in the right direction as it attempts to combine the traditional criteria of technical merits only with the new concern for cost-effectiveness. However, the 4-M method was not adequately successful in the actual prioritization of ESRs for the fiscal year 1995 (FY95). This research identifies a number of design issues that should help us to develop better methods. It emphasizes that given the variety and diversity of ESR's one should not expect that a single method could help in the assessment of all ESR's. One conclusion is that a methodology such as Costs, Risks, and Values Evaluation (CRAVE) should be adopted. It also is clear that the development of methods such as 4-M requires input not only from engineers with technical expertise in ESR's but also from personnel with adequate background in the theory and practice of cost-effectiveness analysis. At KSC, ESR prioritization is one part of the Ground Support Working Teams (GSWT) Integration Process. It was discovered that the more important barriers to the incorporation of cost-effectiveness considerations in ESR prioritization lie in this process. The culture of integration, and the corresponding structure of review by a committee of peers, is not conducive to the analysis and confrontation necessary in the assessment and prioritization of ESR's. Without assistance from appropriately trained analysts charged with the responsibility to analyze and be confrontational about each ESR, the GSWT steering committee will continue to make its decisions based on incomplete understanding, inconsistent numbers, and at times, colored facts. The current organizational separation of the prioritization and the funding processes is also identified as an important barrier to the pursuit of cost-effectiveness. Perhaps the greatest barrier is that, at the working level, KSC's culture is so preoccupied with technical concerns that it seems almost oblivious to any cost concerns, let alone cost-effectiveness concerns. It is recommended that we must urgently begin to change that culture and seek a better balance between these two concerns.

Joglekar, Prafulla N.↗

Spatial non-locality of electronic correlations beyond GW approximation

The question of spatial locality of electronic correlations beyond GW approximation is one of the central issues of the famous combination of GW and dynamical mean field theory, GW+DMFT. In this study, the above question is addressed directly (for the first time) by performing calculations with and without assumption of locality of the corresponding diagrams. For this purpose we use sc(GW+G3W2) approach where the higher order part (G3W2) is evaluated with fully momentum dependent Green's function G and screened interaction W and with "local" variant, where the single site approximation is assumed for both G and W. For all three materials studied in this work (NiO, α-Ce, LiFeAs), we have found the spatial non-locality effects to be strong. For NiO and LiFeAs they, in fact, are decisive for the proper evaluation of vertex corrections. The results of this study have direct impact on our understanding of approximations made in practical implementations of GW+DMFT method, where all diagrams beyond GW (DMFT part) are assumed to be local. Taking into account the fact that the first diagrams beyond GW represent the most important contribution also in GW+DMFT calculations, we conclude that the basic assumption of GW+DMFT, namely the locality of diagrams evaluated in the DMFT part, is not as good as it is believed to be.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Effect of Ice Formations on Propeller Performance

Measurements of propeller efficiency loss due to ice formation are supplemented by an analysis to establish the magnitude of efficiency losses to be anticipated during flight in icing conditions. The measurements were made during flight in natural icing conditions; whereas the analysis consisted of an investIgation of changes in blade-section aerodynamic characteristics caused by ice formation and the resulting propeller efficiency changes. Agreement in the order of magnitude of eff 1- ciency losses to be expected is obtained between measured and analytical results. The results indicate that, in general, efficiency losses can be expected to be less than 10 percent; whereas maximum losses, which will be encountered only rarely, may be as high as 15 or 20 percent. Reported. losses larger than 15 or 20 percent, based on reductions in airplane performance, probably are due to ice accretions on other parts of the airplane. Blade-element theory is used in the analytical treatment, and calculations are made to show the degree to which the aerodynamic characteristics of a blade section. must be altered to produce various propeller efficiency losses. The effects of ice accretions on airfoil-section characteristics at subcritical speeds and their influence on drag-divergence Mach number are examined, and. the attendant maximum efficiency losses are computed. The effect of kinetic heating on the radial extent of ice formation is considered, and its influence on required length of blade heating shoes is discussed. It is demonstrated how the efficiency loss resulting from an icing encounter is influenced by the decisions of the pilot in adjusting the engine and propeller controls.

Neel, C. B., Jr.↗

Baryon Number Violation Search

Understanding the fundamental forces and symmetries of nature has long been a central goal of particle physics. While the Standard Model (SM) provides a successful framework, it does not guarantee the conservation of baryon number B or lepton number L, thus motivating searches for their violation. Proton decay, a fundamental process violating B, has been at the forefront of experimental searches for decades.The discovery of the weak neutral current in 1973 unified the electromagnetic and weak forces and inspired the creation of Grand Unified Theories (GUTs) that also unify the strong force. In 1974, the first-ever GUT, proposed by Georgi and Glashow, naturally predicted proton decay. This prediction led to an experimental push to validate these theories, and a large underground detector boom was born. Initially designed for proton decay searches, these detectors later proved invaluable to neutrino physics.Although no evidence for proton decay has yet been observed, next-generation large detectors, such as the Deep Underground Neutrino Experiment (DUNE), offer the opportunity to improve on current experimental limits. Utilizing its Liquid Argon Time Projection Chamber (LArTPC) technology, DUNE is positioned to probe rare processes such as proton decay with increased sensitivity.This thesis presents a sensitivity study for the dominant proton decay mode predicted by Supersymmetric GUTs, p → K+ν, utilizing machine learning approaches. Two methods are explored in this thesis: a Boosted Decision Tree (BDT) analysis and a Graphical Neural Network (GNN) analysis with NuGraph. A lifetime limit of 5.36 ± 0.69 × 1033 years for 400 kt-yrs is found using the BDT, while the GNN achieves a lifetime limit of 6.19±1.26×1033 years for 400-kt-yrs. The NuGraph result offers better sensitivity compared to the current limit set by Super-Kamiokande of 5.90 × 1033 while the BDT result offers a slightly lower sensitivity.Additionally, this thesis discusses cross-section work, a first-ever foray into proton decay and atmospheric neutrinos in a vertical drift (VD) DUNE detector, and extensive hardware contributions to the DUNE Far Detector (FD) 1 Module-0, ProtoDUNE-2, which serves as a testbed for the final detector design and installation.

Stokes, Tyler D. [Louisiana State U.] (ORCID:00000↗

Tactical Versus Strategic Behavior: General Aviation Piloting in Convective Weather Scenarios

We commonly describe environments and behavioral responses to environmental conditions as 'tactical' and 'strategic.' However theoretical research defining relevant environmental characteristics is rare, as are empirical investigations that would inform such theory. This paper discusses General Aviation (GA) pilots' descriptions of tactical/strategic conditions with respect to weather flying, and evaluates their ratings along a tactical/strategic scale in response to real convective weather scenarios experienced during a flight experiment with different weather information cues. Perceived risk was significantly associated with ratings for all experimental conditions. In addition, environmental characteristics were found to be predictive of ratings for Traditional IMC (instrument meteorological conditions), i.e., aural weather information only, and Traditional VMC (visual meteorological conditions), i.e., aural information and an external view. The paper also presents subjects' comments regarding use of Graphical Weather Information Systems (GWISs) to support tactical and strategic weather flying decisions and concludes with implications for the design and use of GWISs.

Latorella, Kara A.↗

Redox Defect Thermochemistry of FeAl 2 O 4 Hercynite in Water Splitting from First-Principles Methods

Solar thermochemical hydrogen (STCH) production is a promising route to produce fuels from sunlight via high-temperature water splitting. However, efficient and technologically viable implementations of this process only allow a narrow window of thermodynamic boundary conditions that can be used to cycle the system, thus limiting the design space for suitable metal oxide redox mediators. An oxygen defect redox mechanism can contribute a favorable reduction entropy to expand this window, and computational evaluation of materials with high oxygen defect entropies could play a pivotal role in guiding the discovery and design of suitable oxides. This study employs first-principles calculations to investigate the redox mediating defect mechanism of the STCH candidate material, hercynite (FeAl 2 O 4 ). We compare the results of total energy calculations from density functional theory (DFT) with beyond-DFT approaches, including hybrid functionals and the random phase approximation, which are among the most advanced methods currently feasible for supercell defect calculations. Using the predicted formation energies, we perform thermodynamic modeling of FeAl2O4 reduction and oxidation via free energy minimization that incorporates ideal gas, configurational, and vibrational entropy contributions evaluated within the quasi-harmonic approximation. Special attention is devoted to understanding interactions among co-existing defects, such as the association of pairs and complexes of O vacancies and cation antisite defects, and the effect of mutually compensating defect charges. Our results corroborate the notion that the details of defect interactions can be decisive for the viability of hydrogen production within the desirable STCH process window.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy↗

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy↗

Consideration of Collision "Consequence" in Satellite Conjunction Assessment and Risk Analysis

Classic risk management theory requires the assessment of both likelihood and consequence of deleterious events. Satellite conjunction risk assessment has produced a highly-developed theory for assessing collision likelihood but holds a completely static solution for collision consequence, treating all potential collisions as essentially equally worrisome. This may be true for the survival of the protected asset, but the amount of debris produced by the potential collision, and therefore the degree to which the orbital corridor may be compromised, can vary greatly among satellite conjunctions. This study leverages present work on satellite collision modeling to develop a method by which it can be estimated, to a particular confidence level, whether a particular collision is likely to produce a relatively large or relatively small amount of resultant debris and how this datum might alter conjunction remediation decisions. The more general question of orbital corridor protection is also addressed, and a preliminary framework presented by which both collision likelihood and consequence can be jointly considered in the risk assessment process.

Hejduk, M.↗

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES): Workshop Report

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail. Current U.S. Department of Energy (DOE) projects such as LES ARM Symbiotic Simulation and Observation Activity (LASSO) are leading the way in conducting routine LES, building large, public databases that are accessible for data science, sensitivity studies, and training for machine learning. LES will also become more routine as it becomes more accessible for individual researchers to address their scientific questions of interest. Scientific questions addressed by LES over the next 10 years are likely to include cloud organization and aggregation; aerosol cloud interactions and atmospheric chemistry (including geo-engineering); urban-scale LES; atmospheric extreme events, ranging from small-scale severe weather to wildfires; and ocean-wave-atmosphere interactions. Further LES-related research will likely grow significantly in areas related to societal impact studies of air quality and extreme weather events, applications to renewable energy forecasting and resource assessment, and aid in decision-making processes. The growth in the use of LES in atmospheric science research will drive the need for better physical process representations (e.g., cloud aerosol microphysics, radiation, and atmospheric chemistry) at the scales resolved by LES. To date, many of the process representations used by LES have been taken directly from coarser-resolution models. Promising methods for LES process representations include superdroplet and quadrature methods for microphysics, 3D approaches for radiation, and better representation of chemistry and aerosol processes. At LES resolution, land-atmosphere interactions for complex terrains, land cover/types, biogeochemistry, and plant canopy models are needed as an improvement beyond traditional and widely used Monin-Obuhkov similarity theory.

54 ENVIRONMENTAL SCIENCES↗

Geoscience Laser Altimetry System (GLAS) Loop Heat Pipe Anomaly and On Orbit Testing

The Geoscience Laser Altimetry System (GLAS) is the sole instrument on the ICESat Satellite. On day 230 of 2003, the GLAS Component Loop Heat Pipe (CLHP) entered a slow circulation mode that resulted in the main electronics box reaching its hot safing temperature, after which the entire instrument was turned off. The CLHP had a propylene working fluid and was actively temperature controlled via a heater on the compensation chamber. The slow circulation mode happened right after a planned propulsive yaw maneuver with the spacecraft. It took several days to recover the CLHP and ensure that it was still operational. The recovery occurred after the entire instrument was cooled to survival temperatures and the CLHP compensation chamber cycled on a survival heater. There are several theories as to why this slow circulation mode exhibited itself, including: accumulation of Non-Condensible Gas (NCG), the secondary wick being under designed or improperly implemented, or an expanded (post-launch) leak across the primary wick. Each of these is discussed in turn, and the secondary wick performance is identified as the most likely source of the anomalous behavior. After the anomaly, the CLHP was controlled to colder temperatures to improve its performance (as the surface tension increases with lower temperature, as does the volume of liquid in the compensation chamber) and only precursor pulses occurred later in the mission. After GLAS s last laser failed, in late 2009, a decision was made to conduct engineering tests of both LHPs to try and duplicate this flight anomaly. The engineering tests consisted of control setpoint changes, sink changes, and one similar propulsive Yaw maneuver. The only test that showed any similar anomaly precursors on the CLHP was the propulsive maneuver followed by a setpoint increase. The ICESat Satellite was placed in a decaying orbit and ended its mission on August 30, 2010 in Barents Sea.

Baker, Charles↗

Machine Learning Modeling Pipeline for Extracting Nuclear Proliferation Events of Interest from Open Data Sources (U)

In FY2020, the Savannah River National Laboratory (SRNL) and the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Polytechnic Institute and State University entered a collaboration funded by Department of Energy’s (DOE) Office of Defense Nuclear Nonproliferation Research and Development. The project’s mission was to take the first steps toward developing a demonstration prototype system that uses multiple machine learning and data analytics methods on largescale open data sources to identify new, developing, and/or undeclared nuclear programs. Given the SRNL team’s on-site perspective of events culminating in the DOE’s decision to pursue the Savannah River Plutonium Processing Facility (SRPPF), the team targeted the identification of events and indicators in retrospective datasets that pointed to the activity of “fissile core fabrication at the Savannah River Site” prior to the official announcement in May of 2018. A preliminary modeling pipeline was developed in FY20 that showed the datasets contained adequate signal for continuation of efforts. In FY21, a modular demonstration prototype modeling pipeline has continued in development for two text-based data sources: a broad internet archive (Webhose Ltd.) and a decahose Twitter database (i.e., a global sampling of one in every ten Tweets). The techniques that have been developed rely on graph theory and anomaly detection to identify contextual shifts in key words and phrases at various points in time such that indicators of events of interest could be identified and subsequently, events could be extracted from the corpuses. The foundational concept behind the approaches is that contextual shifts in key words and phrases can act as indicators of events of interest. Both datasets have proven successful in extracting events of interest related to pit production at the Savannah River Site prior to the official announcement. In addition, the pipelines have generated a wide range of events broadly summarized as: the awarding of DOE contracts at major sites, DOE investments in various programs, accidents at DOE national laboratories, speculations about the fate of pit production in the DOE complex, domestic and international shipments and receipts of nuclear materials at DOE sites, termination of non-proliferation agreements with Russia, termination of MOX, new weapons development approvals/testing, nuclear posture reviews, major DOE cleanup/production milestones, political opinions, and nuclear watch groups’ opinions, among many others.

97 MATHEMATICS AND COMPUTING↗

Survey on stochastic distribution systems: A full probability density function control theory with potential applications

Complex systems seen either in general engineering practice or economics are subjected to ever increased uncertainties that are mostly represented as random variables or parameters, and the characteristics of random variables are represented by their probability density functions (PDFs). Controlling their PDFs means to shape their stochastic distributions and in general it would provide a full treatment for system analysis and operational control and optimization. This leads to the development of stochastic distribution control (SDC) systems theory in the past decades, where the original aim of the controller design is to realize a shape control of the distributions of certain random variables in their PDFs sense for some engineering processes. Indeed, once the PDFs of these random variables or parameters are used to describe their distribution characters, the control task is to obtain control signals so that the output PDFs of stochastic systems are made to follow their target PDFs. The subject of SDC was initially originated for non-Gaussian stochastic control systems design but has found a wide spectrum of applications in general systems in terms of data-driven modeling, analysis, signal processing (filtering), data mining via multivariable statistics, decision-making (optimization) for systems subjected to uncertainties and even in economics. In this context, SDC constitutes an effective primer tool for complex system analysis, control and operational optimizations. In this review paper, a detailed survey of the developments on the research of SDC systems will be made together with their wide spectrum applications and future perspectives.

42 ENGINEERING↗

A method for determining optimal electric range by considering electric vehicle lightweighting on perceived ownership cost

The limited driving range due to high costs and low energy densities of batteries constraints the battery electric vehicle (BEV) market growth. Lightweighting in theory can reduce energy consumption rate and extend the driving range. The knowledge gap is to quantitatively link the cost-effectiveness of light-weight technologies with range extension and consumer acceptance of BEVs. In this study, a physics-based energy consumption model of BEVs is constructed and associated with a statistics-based model on the basis of travel surveys. A perceived cost of ownership (PCO) is then developed by adding intangible costs to traditional total cost of ownership models. We estimate, at the disaggregate vehicle model and driver level and the aggregate market level, 1) the extended range due to lightweighting for a given battery size; and 2) the optimal electric range based on lightweighting decisions. The cost-effectiveness of lightweighting for BEV range extension is found to vary with income-dependent daily range limitation value, driving patterns and lightweighting technology costs. In general, adopting lightweighting in BEVs is more cost-effective for consumers with higher daily limitation value, as well as for those with higher driving intensity or suitable daily driving patterns. When the lightweighting involves a higher vehicle production cost, less lightweighting could reduce the overall PCO for BEV owners. 4 of the selected top ten BEV models are found to benefit from additional 2.09%–4.45% lightweighting. Finally, the method built in this study can guide automakers in planning R&D investments in battery and lightweighting technologies.

33 ADVANCED PROPULSION SYSTEMS↗

Resolving Graphite‐Electrolyte Interphase of Lithium‐Ion Batteries using Air‐Tight Ambient Mass Spectrometry

Abstract The formation of a stable solid electrolyte interphase (SEI) at graphite electrode is necessary for lithium‐ion batteries (LIB) to prevent excessive degradation of electrolytes. Until now, the exact organic composition of SEI has not been decisively determined with lithium ethylene mono‐carbonate (LEMC) being one of the debated components. An air‐tight ambient mass spectrometry (MS) platform is developed to directly characterize the air‐sensitive organic components present in SEI. Ionization occurs via a solvent‐free field‐induced process at atmospheric pressure. Our experimental data, based on tandem MS analysis, revealed LEMC to be the major organic component in SEI. This result resolves a long‐standing mystery surrounding the composition of native SEI in LIB, where no trace of the other debated compound, lithium ethylene dicarbonate, was detected. The energetics of fragmentation of LEMC and the corresponding stabilities of various ionic species detected during the air‐tight ambient MS analysis were calculated using density functional theory (DFT). Our findings confirmed favorable protonation energies and suggested the molecular structures for many of the detected species. Solvent (i. e., ethylene carbonate)‐induced stabilization effects observed during the ionization process were also confirmed by DFT. The reported study encourages the routine use of ambient mass spectrometry to characterize both anodic and cathodic electrodes of all battery types as well as to study other air‐sensitive materials in their native state.

25 ENERGY STORAGE↗

Electrochemical techniques and mechanisms for the corrosion of metals and alloys in sub- and supercritical aqueous systems

Corrosion has become a decisive factor hindering supercritical water technologies' long-cycle, safe implementation. Electrochemical experiments performed in supercritical aqueous systems can capture essential, real-time information about the micro/nanoscale processes of corrosion and their kinetics. As a starting point, this paper first summarizes the critical chemical properties of supercritical aqueous systems and analyzes their role in determining the duality of corrosion mechanisms (whether electrochemical or chemical micro-processes predominate). Next, it reviews the available electrochemical techniques such as pH sensors, electrochemical noise measurements, and related applications for quantitatively elaborating the corrosion issues in supercritical aqueous systems. With thick and heavy colors, a series of mechanistic models, such as the mixed potential model and the coupled environment models were introduced from the fundamental theories to the related applications, which have been applied widely in ambient and subcritical aqueous systems and exhibit great values and potential to be employed in high-density supercritical water environments. The passivity, depassivation, and passivity breakdown of metals and alloys in terms of the Point Defect Model (PDM) were also successfully implemented and discussed. Further, the newly built SCW_PDM describes the film growth kinetics at the atomic level of metals and alloys in supercritical water and is being developed to quantitatively analyze and resolve a series of corrosion issues such as the passivity breakdown and the stress corrosion cracking that occur in supercritical aqueous systems. This review is helpful by promoting the development of the electrochemical corrosion theory in supercritical aqueous systems and by identifying corrosion prevention and control methods for the safe implementation of relevant supercritical water technologies.

36 MATERIALS SCIENCE↗

Insights into the electronic origin of enhancing the catalytic activity of Co 3 O 4 for oxygen evolution by single atom ruthenium

The surface electronic structure of transition-metal oxide catalysts plays a decisive role in binding the intermediates of the oxygen evolution reaction (OER) to the oxide surface, in turn influencing the catalytic activity of these materials. However, the approaches to modulating the electronic structure of surface metal ions are rare and far behind the demands. Here, we report a surface single atom decoration for adjusting the surface electronic structure of Co 3 O 4 , leading to enhanced electrocatalytic activity for OER, in which the isolated Ru single atoms were uniformly deposited on the surface of Co 3 O 4 by an atomic layer deposition technology. As the OER catalyst, the as-made catalysts have exhibited a significantly enhanced catalytic activity (with increasing to 95.5 times) and a dramatically decreased overpotential. The density functional theory calculations reveal that the single-atom Ru acts as a promotor to adjust the 3d electronic structure of adjacent Co atoms and to tune the binding energy between intermediates and activity sites, finally leading to enhanced catalytic activity.

36 MATERIALS SCIENCE↗