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The Death of Airmanship: The Urgent Need to Understand Pilot Skills and Knowledge

Aviation awards a special name—airmanship—for the quality of being highly competent in foundational piloting skills, which seem to comprise primarily judgment, decision making, stick-and-rudder skills, and a bit of intuition. The term, which has a mystical quality, has historically resisted analysis; airmanship is acquired solely through experience. The graying of the Boomers and the extreme turbulence of the last few years in commercial aviation have led to a significant loss of those pilots who started out in simpler, round-dial airplanes and made a tortured transition to glass. Those pilots were comfortable disengaging the autopilot at any time, and more importantly, they continued to stay mentally engaged with flight and systems management even as automation continued to encroach on traditional pilot roles. As an industry, we need to prepare for the loss of these pilots by understanding the elements of airmanship and finding a way to replace the competency. The goal is to eliminate “airmanship” by understanding it...by demystifying it. Human factors/cognitive engineering offers tools and methods to develop a system interface that supports skilled performance from the human/technology team. In this presentation, I will talk about my efforts to understand the elements of skilled performance so that they can be trained, or supported by the interface in a seamless manner Specific topics will include the limits of SOP, monitoring for flight path management, alerting non-normals, and autoflight/mode confusion.

pilot skills↗
NASA NTRS2022

Directed Acyclic Graphs: A Tool for Understanding the NASA Human Spaceflight System Risks - Human System Risk Board

For over a decade, the National Aeronautics and Space Administration (NASA) has tracked and configuration-managed approximately 30 risks to astronaut health and performance that occur before, during and after spaceflight. The Human System Risk Board (HSRB), a Health and Medical Technical Authority (HMTA) Board at NASA Johnson Space Center, is the entity responsible for identifying, assessing, analyzing, and monitoring the official understanding of the risk or risk posture for each of the Human System Risks and determining – based on evaluation of the available evidence – when that risk posture changes. The ultimate purpose of tracking and researching these risks is to find ways to reduce the risk that astronaut crews face during spaceflight. Historically, research, development and operations relevant to one risk have been conducted in isolation from other risks; these individual risk ‘silos’ enabled initial characterization of each specific risk. In spaceflight however, the impact of exposure to risk for astronaut crews is cumulative, and not independent of exposures or other risks, as all the adverse effects of the spaceflight environment begin at launch, continue throughout the duration of the mission and in some cases across the lifetime of the crews. In January of 2020, the HSRB at NASA embarked on a pilot project designed to assess the potential value of causal diagramming as a tool to facilitate understanding of these cumulative and interdependent effects as applied within Human System Risk management. This process uses directed acyclic graphs as a means of formalizing a shared mental model of the causal flow of risk among Risk Board stakeholders. Initially this model was to improve communication among those stakeholders, but the potential value exceeds communication alone. The causal diagrams are formulated as directed acyclic graphs (DAGs) to function as a type of knowledge graph for reference for the board and its stakeholders. This document is a sister document to NASA/TM 20220006812 Directed Acyclic Graph Guidance Documentation (1). In that document, the basic guidance for creating and standardizing directed acyclic graphs as tools for cross-risk analysis is provided. This document contains the initial configuration managed DAGs that were created as a result of applying those principles. These initial versions were accepted by the HSRB in January of 2022. Each of the Human System Risks are represented by a DAG that has been reviewed by the larger Human Health and Performance community at NASA including life scientists, physical scientists, physicians, nurses, pharmacists, exercise specialists and more. These results show the starting point for Human System Risk DAGs as shared mental models and communication aids across the boundaries of the various expertise needed to understand and mitigate the human risks in spaceflight. Because they are a starting point, each of these DAGs can be expected to change over time as new or refined evidence becomes available. The process for updating these DAGs can be found in the JSC-66705 Human System Risk Management Plan (2) that is publicly available on the NASA Technical Reports Server.

Erik L. Antonsen↗
NASA NTRS2022

Understanding Structure in Line-Driven Stellar Winds Using Ultraviolet Spectropolarimetry in the Time Domain

The most massive stars are thought to lose a significant fraction of their mass in a steady wind during the main-sequence and blue supergiant phases. This in turn sets the stage for their further evolution and eventual supernova, and preconditions the surrounding medium for all following events, with consequences for ISM energization, chemical enrichment, and dust formation. Understanding these processes requires accurate observational constraints on the mass-loss rates of the most luminous stars, which can also be used to test theories of stellar wind driving. In the past, mass-loss rates have been characterized via collisional emission processes such as optical Hα and free-free radio emission, but these so-called “density squared” diagnostics require correction in the presence of widespread clumping. Recent observational and theoretical evidence points to the likelihood of a ubiquitously high level of such clumping in hot-star winds, but quantifying its effects requires a deeper understanding of the complex dynamics of radiatively driven winds and their stochastic instabilities. Furthermore, large-scale structures initiating in surface anisotropies and propagating throughout the wind can also affect wind driving and alter mass-loss diagnostics. Time series spectroscopy of high resonance-line opacity in the UV, capable of high resolution and high signal-to-noise, are required to better understand these complex dynamics, and more accurately determine mass-loss rates. The proposed Polstar mission (Scowen et al. 2022, this volume) provides the necessary resolution at the Sobolev (∼10 km s −1 ) or sound-speed (∼20 km s −1 ) scale, for over three dozen bright galactic massive stars with signal-to noise an order of magnitude above that of the celebrated MEGA campaign (Massa et al. 1995) of the International Ultraviolet Explorer (IUE), via continuous observations that track propagating structures through the winds in real time. Supporting geometric constraints are provided by the polarimetric capabilities present in all the datasets of such a mission.

Polstar – NASA MIDEX↗
DOE OSTI2018

Plutonium: Advancing our Understanding to Support Sustainable Nuclear Fuel Cycles

With Global energy needs increasing, real energy solutions to meet demands now, are needed. Fossil fuels are not an ideal candidate to meet these needs because of their negative impact on the environment. Renewables such as wind and solar have huge potential, but still need major technological advancements (particularly in the area of battery storage) before they can effectively meet growing world needs. The best option for meeting large energy needs without a large carbon footprint is nuclear energy. Of course, nuclear energy can face a fair amount of opposition and concern. However, through modern engineering and science many of these concerns can now be addressed. Many safety concerns can be met by engineering advancements, but perhaps the biggest area of concern is what to do with the used nuclear fuel after it is removed from the reactor. Currently the United States (and several other countries) utilize an open fuel cycle, meaning fuel is only used once and then discarded. It should be noted that fuel coming out of a reactor has utilized approximately 1% of the total energy that could be produced by the uranium in the fuel rod. The answer here is to close the fuel cycle and recycle the nuclear materials. By reprocessing used nuclear fuel, all the U can be repurposed without requiring disposal. The various fission products can be removed and either discarded (hugely reduced waste volume) or more reasonably, utilized in specialty reactors to make more energy or needed research/medical isotopes. While reprocessing technology is currently advanced enough to meet energy needs, completing research to improve and better understand these techniques is still needed. Better understanding behavior of fission products is one area of important research. Despite it being discovered over 75 years ago, plutonium is still an exciting element to study because of the complex solution chemistry it exhibits. In aqueous solutions Pu can exist simultaneously in multiple oxidation states, including 3+, 4+, and 6+. It also readily forms a variety of metal-ligand complexes depending on solution pH and available ligands. Understanding of the behavior of Pu in solution remains an important area of research today, with relevance to developing sustainable nuclear fuel cycles, minimizing its impact on the environment, and detecting and preventing the spread of nuclear weapons technology.

Lines, Amanda M.↗
DOE OSTI2019

Extreme Fast Charging of Lithium-Ion Battery: Understanding Bottlenecks and Safety Issues

Currently, graphite-based lithium-ion battery (LIB) packs in the electric vehicle (EV) domain can accommodate a charging rate up to 2C, which translates into a 0.5 to 1h recharge time [1-2]. Reducing the recharge time down to 10-15 min range would reduce the gap between the internal combustion engine’s refueling time and EV’s recharge time. Minimizing this gap is seen as attractive to consumers and would eventually enhance the adoption of EVs [1-3]. Significant research activity has been going on globally to understand the scientific limitations associated with high rate charging [4-6]. Extreme fast charging (XFC) of Li-ion batteries can create LIB life and safety issues [1, 7]. Among the issues are shortened battery life and enhanced safety concerns due to potential short creation by Li dendrites [1-2]. The detection and monitoring of Li plating onset and evolution over aging is a significant challenge. In-operando detection schemes to understand the dynamics of Li plating and the role that aging has on Li plating are vital to enable fast charging of specific energy cells. A key to the effort would be understanding the interplay between materials, electrode structure, and use conditions. This presentation will discuss the key bottlenecks of aggressive fast charging (~10 min). In particular, how extreme fast charging impacts individual battery components as well as the overall battery’s performance, life, and safety will be presented in light of experimental results and analysis. The effectiveness and challenges of in-operando electrochemical detection methods in aggressive charging conditions shall also be discussed. References [1] S. Ahmed, I. Bloom, A. N. Jansen, T. R. Tanim, E. J. Dufek, A. Pesaran, A. Burnham, R. B. Carlson, F. Dias, K. Hardy,M. Keyser, C. Kreuzer, A. Markel, A. Meintz, C. Michelbacher, M. Mohanpurkar, P. A. Nelson, D. C. Robertson, D. Scoffield,M. Shirk, T. Stephens, R. Vijayagopal, J. Zhang, Enabling fast charging–A battery technology gap assessment, J Power Sources,367 (2017), 250-262 [2] T.R. Tanim, M. G. Shirk, R. L. Bewley, E. J. Dufek, B. Y. Liaw, Fast charge implications: Pack and cell analysis and comparison,, J Power Sources, 381 (2018) 56-65 [3] N. Lutsey, S. Searle, S. Chambliss, and A. Bandivadekar, Assessment of leading electric vehicle promotion activities inUnited States cities, International Council on Clean Transportation, July 2015 [4] C. Michelbacher, S. Ahmed, I. Bloom, A. Burnham, B. Carlson, F. Dias, E. J. Dufek, A. N Jansen, M. Keyser, A. Markel,A. Meintz, M. Mohanpurkar, A. Pesaran, D. Scoffield, M. Shirk, T. Stephens, T. R. Tanim, R. Vijayagopal, J. Zhang, Enablingfast charging–Introduction and overview, J Power Sources, [5] E-Mobility: New Possibilities with 800-volt charging, Porsche newsroom, https://newsroom.porsche.com/en/technology/porsche-engineering-e-power-electromobility-800-volt-charging-12720.html(accessed Sep 2017) [6] Charging interface initiative e.V. - Industry statement on future charging infrastructure, available at: http://www.charinev.org/fileadmin/Downloads/Papers_and_Regulations/CharIN_industry_statement.pdf(accessed June 2017) [7] T. Waldmann, B. Hogg,M. Kasper, S. Grolleau, C. Couceiro, K. Trad, B. P. Matadi and M. Wohlfahrt-Mehrens, Interplay ofOperational Parameters on Lithium Deposition in Lithium-Ion Cells: Systematic Measurements with Reconstructed 3-ElectrodePouch Full Cells, J. Electrochem. Soc. 163 (7) (2016) A1232-A1238

25 ENERGY STORAGE↗
DOE OSTI2020

Lithium Metal Electrode — Understanding Its Unique Characteristics and Functions

Lithium metal electrode (LME) is attractive for the next generation of commercial high-energy rechargeable lithium battery (RLB) design and development. As a light element with a very reducing electrochemical potential, Li metal certainly has the unique characteristics that also present challenges for its application in RLBs. To overcome technical barriers with LME such as the dendrite formation that causes uneven current distributions, excessive SEI formation that consumes Li inventory, and formation of inactive Li metal in granular forms that induces safety hazards, more fundamental understanding of the unique characteristics of LME and its impact on functions in performance in RLBs is critical. Here, we present some recent work based on temporally-correlated reactive molecular dynamics simulations to understand the Li deposition and the associated nucleation and growth process on the LME or graphitic electrode surfaces. Such a study provides some intriguing perspectives on how Li reacts with electrolytes on LME and conventional graphitic electrodes in the RLB operation. Such an insight could help improving our strategy to deal with LME problems and provide functional improvements for LME’s application in RLBs. This presentation is dedicated to Professor Robert Huggins for his life-long teaching of the fundamentals on solid state ionics and its implications in understanding the electrochemical behavior of Li in RLB applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Beginner's Guide to Understanding Power System Model Results for Long-Term Resource Plans

This presentation summarizes a recently published beginner's guide for understanding power system model results for long-term resource plans. This guide is designed to improve decision-making in the electricity planning process by strengthening dialogue between system planners and relevant stakeholders. It focuses on interpreting scenario results generated by power system planning models. These results are often used to inform integrated resource plans, which are long-term plans for a utility to meet future electricity requirements. Whether you are a state utility commissioner, commission staff, part of a state energy office, an intervenor in the planning process, or another stakeholder, this guide is designed to help you better weigh in on the modeling methods or interpret the model results to improve decision-making. This guide can enhance your understanding to ask the right questions, which can enable better understanding of results and key assumptions, data, and methods.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

A Modelling Framework for Understanding the Impacts of Radioactive and Chemo-toxic Waste Disposals - 18199

In order to assess the compliance of a radioactive waste disposal facility against regulatory requirements, it is usual to develop a numerical model that provides estimates of quantities such as effective dose, radiological risk and environmental concentrations at times in the future after disposal of the wastes. An important aspect of a safety case based on the results of the numerical assessment model is to develop understanding and confidence in the results. This understanding includes determining why the magnitudes of the results are as they are, determining the key controlling parameters on the model outputs, providing confidence that the model outputs are credible, providing an alternative and complementary modelling approach, undertaking sensitivity analyses and facilitating communication of the safety case results with stakeholders. In this paper we present a modelling approach that addresses these issues for a wide range of disposal concepts. The approach captures the key processes that affect contaminant migration and transport, and uses analytical solutions to provide insight and understanding about the behaviour of a disposal system. The approach has been tested against a wide range of concepts for LLW, ILW, HLW and SF. In all cases, agreement with the results from numerical assessment models is found to be very good, with estimates of peak radiological risk and other metrics within a factor of two or better, compared with those from numerical assessment models. This agreement is achieved for assessment results that can potentially span many orders of magnitude. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Understanding Line Losses and Transformer Losses in Rural Isolated Distribution Systems: Preprint

Rural, isolated power systems in the mainland U.S. and in states like Alaska and Hawaii are powered by assets like diesel generators. These rural, isolated power systems also cannot operate at the higher band of medium voltage (like 69kV). They are primarily in the 12 to 14 kV range to keep the cost of the distribution investments lower. Because of this mid-band medium voltage range, the line losses and distribution transformers losses consume significant diesel consumption (almost 10 percent of the peak load). This work considers one such power system powering an isolated system and presents key findings online losses, and transformer losses. Understanding and documenting the impacts is critical for these communities operating their power systems and take actions to reduce expensive diesel consumption. In this paper, we will present one such typical grid and model it in electromagnetic transients (EMT) domain. We used the tower structure, under ground cabling installation to develop high fidelity models of lines. We also used high fidelity models of distribution transformers to present the no-load losses and full load loses. We will also present technical solutions available commercially off-the-shelf to reduce these losses and reduce diesel consumption. This work will be a primer for communities to understand the technical challenges and to understand the possible solution available to solve such challenges for rural, isolated power system operators.

blackstart↗
DOE OSTI2024

Distribution Transformer Demand: Understanding Demand Segmentation, Drivers, and Management Through 2050

The National Renewable Energy Laboratory (NREL) has been working closely with the U.S. Department of Energy's Office of Electricity (OE) to understand the critical drivers and potential means of managing distribution transformer demand through 2050. This effort has consulted with utility representative organizations and transformer manufacturers to understand the problem, characterized the in-service assets, and modeled future demand. Distribution transformers, or service transformers, range from 10 to 5,000 kilovolt-amperes (kVA), have a high-side voltage of less than 34.5 kilovolts, and have step-down power delivery for customer end use. This research will help the manufacturing sector understand production requirements and better inform utility strategies for managing their demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Understanding Fission Gas Bubble Distribution and Zirconium Redistribution in Neutron-irradiated U-Zr Metallic Fuel Using Machine Learning

U-10wt.% Zr (U-10Zr) based metallic fuel is the leading candidate for next-generation sodium cooled fast reactor in United States. Currently, Idaho National Laboratory (INL) has been the leading national laboratory for research, development, and demonstration (RD&D) on metallic fuel. Advanced post-irradiation characterization will help to understand fuel microstructure and property change during irradiation, benefiting fuel qualification for commercial application. Characterization capabilities ranging from sub-nanometer to micrometer, such as scanning electron microscopy (SEM), focused ion beam (FIB) sampling, transmission electron microscopy (TEM) characterization, and local thermal conductivity microscopy (TCM), have been utilized recently on irradiated U-10Zr fuel samples to gain a better understanding of nuclear fuel microstructure and property evolution inside a reactor. The FIB/SEM coupled with energy dispersive X-ray spectroscopy (EDS) can capture the essential information to achieve better understanding of fuel behaviors. Inside a nuclear reactor, the phase and microstructure of U-10Zr is constantly changing under neutron bombardment. For example, the gaseous fission product atoms have a limited solubility inside fuel matrix and tend to precipitate out in bubble form, which not only contribute to fuel thermal conductivity degradation but also provide a shortcut for movement of fission products, i.e. lanthanides. The resultant deposition of lanthanides at the cladding inner surface will potentially trigger a chemical reaction/interaction between nuclear fuel and cladding at reactor operational conditions, threatening fuel integrity and safety. FIB/SEM coupled with EDS can provide the fission bubble information as well as probe into phase separation or Zr redistribution, which is fundamental to predict the fuel performance. With high velocity image data generating method, such as FIB/SEM, an automatic way to extract the microstructural information quantitively can better serve the needs from post irradiation characterization. A trained machine learning model, named Decision Tree, is employed to generate a bubble classifier and to categorize bubbles into three categories: isolated bubble, connected without lanthanides, and connected with lanthanides bubbles[3]. This work presents a showcase of this approach on six regions of a fuel cross-section along the radial temperature gradient. We obtained distributions of bubble categories and porosity rates along the six regions. Moreover, a secondary phase U-Zr2 was determined and found on regions 5 and 6. The secondary phase fraction was increasing from 15.61% in region 5 to 34.79% in region 6 based on this approach . This quantitative data offers insights into the lanthanide migration and potentially thermal conductivity degradation. This information from machine learning will be fed into fuel design code for better prediction of fuel performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗
DOE OSTI2017

Understanding the mechanisms of radiation belt dropouts observed by Van Allen Probes

To achieve a better understanding of the dominant loss mechanisms for the rapid dropouts of radiation belt electrons, three distinct radiation belt dropout events observed by Van Allen Probes are comprehensively investigated. For each event, observations of the pitch angle distribution of electron fluxes and electromagnetic ion cyclotron (EMIC) waves are analyzed to determine the effects of atmospheric precipitation loss due to pitch angle scattering induced by EMIC waves. Last closed drift shells (LCDS) and magnetopause standoff position are obtained to evaluate the effects of magnetopause shadowing loss. Evolution of electron phase space density (PSD) versus L* profiles and the μ and K (first and second adiabatic invariants) dependence of the electron PSD drops are calculated to further analyze the dominant loss mechanisms at different L*. Here, our findings suggest that these radiation belt dropouts can be classified into distinct classes in terms of dominant loss mechanisms: magnetopause shadowing dominant, EMIC wave scattering dominant, and combination of both mechanisms. Different from previous understanding, our results show that magnetopause shadowing can deplete electrons at L* < 4, while EMIC waves can efficiently scatter electrons at L* > 4. Compared to the magnetopause standoff position, it is more reliable to use LCDS to evaluate the impact of magnetopause shadowing. Finally, the evolution of electron PSD versus L* profile and the μ, K dependence of electron PSD drops can provide critical and credible clues regarding the mechanisms responsible for electron losses at different L* over the outer radiation belt.

58 GEOSCIENCES↗
DOE OSTI2025

What's on the menu? Examining native apex‐ and invasive meso‐predator diets to understand impacts on ecosystems

Abstract Understanding how carnivores impact ecological communities is essential for guiding effective management actions and conserving biodiversity. Quantifying predators' diets, including prey selectivity, allows for the assessment of the relative effects native and invasive predators may have on prey populations. In Australia, populations of a native, terrestrial apex predator, the dingo Canis dingo/C. familiaris , and introduced and invasive subordinate mesopredators, the European red fox Vulpes vulpes and feral cat Felis catus , co‐occur, but there is limited understanding of their relative impacts on native and invasive prey in different ecosystems. To assess the possible effects of dingoes, foxes and cats on prey, we examined their diet and prey selectivity across a ~10,000 km 2 semi‐arid mallee ecosystem. Using macroscopic scat analysis, we identified strong dietary niche separation. Larger‐bodied dingoes primarily consumed large marsupial herbivores, whereas foxes and cats primarily consumed smaller prey, including introduced and native rodents and birds. Foxes had the broadest diet, and the greatest dietary overlap with cats ( = 0.81), compared with dingoes ( = 0.50) or between dingoes and cats ( = 0.36). Livestock were identified in 2% of dingo and 7% of fox scats. Cats and foxes consumed more than 15 times the volume of small native mammals compared with dingoes, including threatened species such as fat‐tailed dunnarts Sminthopsis crassicaudata . Cats and foxes also selectively consumed small mammals relative to their estimated availability and consumed fewer large mammals. In contrast, dingoes consumed fewer birds and more echidnas relative to their availability. Our results suggest limited intraguild competition within this semi‐arid ecosystem, as dingoes are primarily exerting top‐down pressure on large herbivores, whereas invasive mesopredators are disproportionately impacting smaller prey, including threatened native mammals. Practical implication . Our findings suggest that ongoing conservation management of dingoes, red foxes and feral cats must consider the variation in diets, impacts on prey and ecological roles of these different predator species, and avoid indiscriminate lethal control methods. Quantifying actual, rather than assumed, impacts of predators on threatened native species, large herbivores and livestock is essential to achieve effective and integrated ecosystem management.

Mason, Rachel T. [School of Life and Environmental↗
DOE OSTI2019

Molecular Level Understanding of the Interactions Between Reaction Intermediates of Li–S Energy Storage Systems and Ether Solvents

The lithium–sulfur energy storage system has the potential to deliver high energy density for grid and transportation applications. Lithium polysulfides (LiPS) formed during the chemical transformation of elemental sulfur can be reactive toward commonly used ether solvents. In this chapter, using density functional theory calculations, we address kinetic and thermodynamic feasibilities of LiPS reactions with various ether molecules (linear and cyclic) and fluorine-substituted ether molecules to understand their long-term chemical stability as solvents or cosolvents. These a priori computations indicate that the most reactive intermediates that initiate a likely degradation reaction of ether solvent molecules are Li2S2, Li2S3, Li2S4, and S2 2−. The lowest computed activation barriers (ΔH ‡) for the CO bond cleavage of dimethoxy ethane (DME) by shorter chain polysulfides or sulfide anions are in the range of ∼27–35 kcal mol−1, suggesting extremely slow kinetics for a polysulfide-induced ether solvent degradation. Calculations are extended to nine more linear and cyclic ether solvent molecules including the glymes, tetrahydrofuran (THF), and dioxolane (DOL). Computations suggest that the solvent stability is higher for shorter chain linear ethers compared to longer chain linear ethers and cyclic ethers. In addition to the 10 ether solvent candidates, simulations were also performed to understand the kinetic stability of 16 fluorinated DME molecules – a model for fluorinated ether species. Computations show that the introduction of one or more CF bond(s) in linear ether molecules enables nucleophilic attack by the polysulfide species, especially toward the polar CF/CO bonds. The CO bond stability of the fluoroether molecule was also compromised by the presence of the highly electron-withdrawing “−F” functional group. In general, in this chapter, utilizing the predictive power of first principle simulations, the LiPS reactivity toward ether solvent molecules was simulated and likely reactions that cause degradation are discussed. These studies also provide guidelines for the design of electrolyte systems with longer term chemical stability.

Assary, Rajeev S.↗
DOE OSTI2018

The Progress of Li-S Batteries-Understanding of the Sulfur Redox Mechanism: Dissolved Polysulfide Ions in the Electrolytes

Rechargeable lithium–sulfur batteries have aroused great attention in recent years. Thousands of research articles are published, and among these publications, the majority are dedicated to improving the battery's performance through chemically and physically modifying the sulfur electrode, electrolytes, separator, and lithium anode. However, the single most important aspect, understanding the sulfur redox mechanism, is sparse and overwhelmed by the huge volume of work done on improving the battery's performance. Besides the intrinsic complexity of the sulfur redox chemistry, the most challenging task is to find an effective analytical technique for the quantitative and qualitative determination of the dissolved and solid polysulfides, including elemental sulfur. In this paper, the recent important research aiming to understand the redox mechanism of the sulfur electrode is reviewed in light of the unique analytical techniques used in the research. The review re–affirms the complexity of the sulfur redox chemistry and lays the background for the future mechanistic research for Li–S batteries.

25 ENERGY STORAGE↗
DOE OSTI2026

Understanding Depolymerization and Repolymerization Toward Repurposing Polymer Waste Into Valuable Chemicals & Materials

The versatility of synthetic polymers has led to their continual and escalating production that has accompanied mismanagement at their end-of-life. Exploring and understanding complementary avenues to repurpose plastic waste beyond traditional mechanical recycling can unlock new opportunities in providing feedstock flexibility, securing supply chains, recovering valuable materials, and enabling new valorization paths. Chemical recycling allows for the return to monomers, tailored oligomers, and polymers, even from mixed states of post-consumer waste plastics. This review article summarizes our research team's efforts on elucidating key insights surrounding plastic depolymerization and repolymerization into valorized products. We revealed organocatalyst design rules lead to highly effective and selective deconstruction of condensation polymers. The intricacies of tailoring the reaction environment to produce products of specific lengths and desired functionalities transform low-value waste feedstocks into high-performance materials with embedded circularity. Other types of polymers, including polyolefins and polyakenamers, have also been designed and converted into valuable products. There remain opportunities for further developments such as low-energy and precision depolymerization, adoption of cutting-edge small molecule transformation to access functionalized polymer scaffolds typically inaccessible otherwise, as well as precision design and understanding through the aid of advanced tools.

Galan, Nick [ORNL]↗
DOE OSTI2018

Fundamental Understanding and Material Challenges in Rechargeable Nonaqueous Li-O 2 Batteries: Recent Progress and Perspective

Energy storage challenges have triggered growing interest in various battery technologies and electrocatalysis. As a particularly promising variety, the Li–O 2 battery with an extremely high energy density is of great significance, offering tremendous opportunities to improve cell performance via understanding catalytic mechanisms and the exploration of new materials. Furthermore, focus on nonaqueous electrolyte–based Li–O 2 batteries has markedly intensified since there could be a higher probability of commercialization, compared to that of solid–state or aqueous electrolytes. The recent advancements of the nonaqueous Li–O 2 battery in terms of fundamental understanding and material challenges, including electrolyte stability, water effect, and noncarbon cathode materials are summarized in this review. Further, the current status of water impact on discharge products, possible mechanisms, and parasitic reactions in nonaqueous electrolytes are reviewed for the first time. The key challenges of noncarbon oxygen electrode materials, such as noble metals and metal oxide–based cathodes, transition metals, transition metal compounds (carbides, oxides) based cathodes as well as noncarbon supported catalysts are discussed. In conclusion, this review concludes with a perspective on future research directions for nonaqueous Li–O 2 batteries.

25 ENERGY STORAGE↗