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At least 55 records · Page 3

Advances In Understanding Global Water Cycle With Advent of GPM Mission

During the coming decade, the internationally organized Global Precipitation Measurement (GPM) Mission will take an important step in creating a global precipitation observing system from space based on an international fleet of satellites operated as a constellation. One perspective for understanding the nature of GPM is that it will be a hierarchical system of datastreams beginning with very high caliber combined dual frequency radar/passive microwave (PMW) rain-radiometer retrievals, to high caliber PMW rain-radiometer only retrievals, and then on to blends of the former datastreams with additional lower-caliber PMW-based and IR-based rain retrievals. Within the context of the now emerging global water & energy cycle (GWEC) programs of a number of research agencies throughout the world, GPM serves as a centerpiece space mission for improving our understanding of the Earth's water cycle from a global measurement perspective and on down to regional scales and below. One of the salient problems within our current understanding of the global water and energy cycle is determining whether a change in the rate of the water cycle is accompanying changes in climate, e.g., climate warming. As there are a number of ways in which to define a rate-change of the global water cycle, it is not entirely clear as to what constitutes such a determination. This paper first presents an overview of the GPM Mission and how its overriding scientific objectives for climate, weather, and hydrology flow from the anticipated improvements that are being planned for the constellation-based measuring system. Next, the paper shows how the GPM observations can be used within the framework of the oceanic and continental water budget equations to determine whether a given perturbation in precipitation is indicative of an actual rate change in the water cycle, consistent with required responses in water storage and/or water flux transport processes, or whether it is simply part of the natural variability of a fixed rate cycle.

Smith, Eric A.

Cardiovascular effects of microgravity: evolution of understanding

The understanding of cardiovascular effects of spaceflight has evolved throughout the course of the American manned spaceflight program. Originally descriptive in nature, the present understanding is based on empiric measurements of vascular volume, cardiac output, vascular reflexes, and peripheral and central autonomic control. More detailed understanding of cardiovascular effects has allowed us to separate those symptoms from symptoms caused by musculoskeletal or neurovestibular abnormalities.

Non-programmatic

Measurements Required to Understand the Lunar Dust Environment and Transport Mechanism

Going back to the lunar surface offers an opportunity to understand the dust environment and associated transport mechanisms. This talk will explore what measurements are required to understand and characterize the dust-plasma environment in which robotic and human activities will be conducted. The understanding gained with the measurements can be used to make informed decisions on engineering solutions and follow-on investigations. Particular focus will be placed on required measurements of the size, spatial and charge distribution of the suspended lunar regolith.

Spann, James F., Jr.

Understanding the Scalability of Bayesian Network Inference Using Clique Tree Growth Curves

One of the main approaches to performing computation in Bayesian networks (BNs) is clique tree clustering and propagation. The clique tree approach consists of propagation in a clique tree compiled from a Bayesian network, and while it was introduced in the 1980s, there is still a lack of understanding of how clique tree computation time depends on variations in BN size and structure. In this article, we improve this understanding by developing an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN s non-root nodes to the number of root nodes, and (ii) the expected number of moral edges in their moral graphs. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for the total size of each set. For the special case of bipartite BNs, there are two sets and two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, where random bipartite BNs generated using the BPART algorithm are studied, we systematically increase the out-degree of the root nodes in bipartite Bayesian networks, by increasing the number of leaf nodes. Surprisingly, root clique growth is well-approximated by Gompertz growth curves, an S-shaped family of curves that has previously been used to describe growth processes in biology, medicine, and neuroscience. We believe that this research improves the understanding of the scaling behavior of clique tree clustering for a certain class of Bayesian networks; presents an aid for trade-off studies of clique tree clustering using growth curves; and ultimately provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms.

Mengshoel, Ole J.

Mercury's Weather-Beaten Surface: Understanding Mercury in the Context of Lunar and Asteroidal Space Weathering Studies

Mercury's regolith, derived from the crustal bedrock, has been altered by a set of space weathering processes. Before we can interpret crustal composition, it is necessary to understand the nature of these surface alterations. The processes that space weather the surface are the same as those that form Mercury's exosphere (micrometeoroid flux and solar wind interactions) and are moderated by the local space environment and the presence of a global magnetic field. To comprehend how space weathering acts on Mercury's regolith, an understanding is needed of how contributing processes act as an interactive system. As no direct information (e.g., from returned samples) is available about how the system of space weathering affects Mercury's regolith, we use as a basis for comparison the current understanding of these same processes on lunar and asteroidal regoliths as well as laboratory simulations. These comparisons suggest that Mercury's regolith is overturned more frequently (though the characteristic surface time for a grain is unknown even relative to the lunar case), more than an order of magnitude more melt and vapor per unit time and unit area is produced by impact processes than on the Moon (creating a higher glass content via grain coatings and agglutinates), the degree of surface irradiation is comparable to or greater than that on the Moon, and photon irradiation is up to an order of magnitude greater (creating amorphous grain rims, chemically reducing the upper layers of grains to produce nanometer scale particles of metallic iron, and depleting surface grains in volatile elements and alkali metals). The processes that chemically reduce the surface and produce nanometer-scale particles on Mercury are suggested to be more effective than similar processes on the Moon. Estimated abundances of nanometer-scale particles can account for Mercury's dark surface relative to that of the Moon without requiring macroscopic grains of opaque minerals. The presence of nanometer-scale particles may also account for Mercury's relatively featureless visible-near-infrared reflectance spectra. Characteristics of material returned from asteroid 25143 Itokawa demonstrate that this nanometer-scale material need not be pure iron, raising the possibility that the nanometer-scale material on Mercury may have a composition different from iron metal [such as (Fe,Mg)S]. The expected depletion of volatiles and particularly alkali metals from solar-wind interaction processes are inconsistent with the detection of sodium, potassium, and sulfur within the regolith. One plausible explanation invokes a larger fine fraction (grain size less than 45 micron) and more radiation-damaged grains than in the lunar surface material to create a regolith that is a more efficient reservoir for these volatiles. By this view the volatile elements detected are present not only within the grain structures, but also as adsorbates within the regolith and deposits on the surfaces of the regolith grains. The comparisons with findings from the Moon and asteroids provide a basis for predicting how compositional modifications induced by space weathering have affected Mercury's surface composition.

Weathering

Protecting the Health of Astronauts: Enhancing Occupational Health Monitoring and Surveillance for Former NASA Astronauts to Understand Long-Term Outcomes of Spaceflight-Related Exposures

The astronaut community is unique, and may be disproportionately exposed to occupational hazards not commonly seen in other communities. The extent to which the demands of the astronaut occupation and exposure to spaceflight-related hazards affect the health of the astronaut population over the life course is not completely known. A better understanding of the individual, population, and mission impacts of astronaut occupational exposures is critical to providing clinical care, targeting occupational surveillance efforts, and planning for future space exploration. The ability to characterize the risk of latent health conditions is a significant component of this understanding. Provision of health screening services to active and former astronauts ensures individual, mission, and community health and safety. Currently, the NASA-Johnson Space Center (JSC) Flight Medicine Clinic (FMC) provides extensive medical monitoring to active astronauts throughout their careers. Upon retirement, astronauts may voluntarily return to the JSC FMC for an annual preventive exam. However, current retiree monitoring includes only selected screening tests, representing an opportunity for augmentation. The potential long-term health effects of spaceflight demand an expanded framework of testing for former astronauts. The need is two-fold: screening tests widely recommended for other aging populations are necessary to rule out conditions resulting from the natural aging process (e.g., colonoscopy, mammography); and expanded monitoring will increase NASA's ability to better characterize conditions resulting from astronaut occupational exposures. To meet this need, NASA has begun an extensive exploration of the overall approach, cost, and policy implications of e an Astronaut Occupational Health program to include expanded medical monitoring of former NASA astronauts. Increasing the breadth of monitoring services will ultimately enrich the existing evidence base of occupational health risks to astronauts. Such an expansion would therefore improve the understanding of the health of the astronaut population as a whole, and the ability to identify, mitigate, and manage such risks in preparation for deep space exploration missions.

Rossi, Meredith

The Sustainability of Habitability on Terrestrial Planets: Insights, Questions, and Needed Measurements from Mars for Understanding the Evolution of Earth-Like Worlds

What allows a planet to be both within a potentially habitable zone and sustain habitability over long geologic time? With the advent of exoplanetary astronomy and the ongoing discovery of terrestrial-type planets around other stars, our own solar system becomes a key testing ground for ideas about what factors control planetary evolution. Mars provides the solar systems longest record of the interplay of the physical and chemical processes relevant to habitability on an accessible rocky planet with an atmosphere and hydrosphere. Here we review current understanding and update the timeline of key processes in early Mars history. We then draw on knowledge of exoplanets and the other solar system terrestrial planets to identify six broad questions of high importance to the development and sustaining of habitability (unprioritized): (1) Is small planetary size fatal? (2) How do magnetic fields influence atmospheric evolution? (3) To what extent does starting composition dictate subsequent evolution, including redox processes and the availability of water and organics? (4) Does early impact bombardment have a net deleterious or beneficial influence? (5) How do planetary climates respond to stellar evolution, e.g., sustaining early liquid water in spite of a faint young Sun? (6) How important are the timescales of climate forcing and their dynamical drivers? Finally, we suggest crucial types of Mars measurements (unprioritized) to address these questions: (1) in situ petrology at multiple units/sites; (2) continued quantification of volatile reservoirs and new isotopic measurements of H, C, N, O, S, Cl, and noble gases in rocks that sample multiple stratigraphic sections; (3) radiometric age dating of units in stratigraphic sections and from key volcanic and impact units; (4) higher-resolution measurements of heat flux, subsurface structure, and magnetic field anomalies coupled with absolute age dating. Understanding the evolution of early Mars will feed forward to understanding the factors driving the divergent evolutionary paths of the Earth, Venus, and thousands of small rocky extra solar planets yet to be discovered.

rocky exoplanets

Exoplanet Biosignatures: Understanding Oxygen as a Biosignature in the Context of Its Environment

Here we review how environmental context can be used to interpret whether O 2 is a biosignature in extrasolar planetary observations. This paper builds on the overview of current biosignature research discussed in Schwieterman et al. (2017), and provides an in-depth, interdisciplinary example of biosignature identification and observation that serves as a basis for the development of the general framework for biosignature assessment described in Catling et al., (2017). O 2 is a potentially strong biosignature that was originally thought to be an unambiguous indicator for life at high-abundance. In exploring O 2 as a biosignature, we describe the coevolution of life with the early Earth's environment, and how the interplay of sources and sinks in the planetary environment may have resulted in suppression of O 2 release into the atmosphere for several billion years, a false negative for biologically generated O 2 . False positives may also be possible, with recent research showing potential mechanisms in exoplanet environments that may generate relatively high abundances of atmospheric O 2 without a biosphere being present. These studies suggest that planetary characteristics that may enhance false negatives should be considered when selecting targets for biosignature searches. Similarly our ability to interpret O 2 observed in an exoplanetary atmosphere is also crucially dependent on environmental context to rule out false positive mechanisms. We describe future photometric, spectroscopic and time-dependent observations of O 2 and the planetary environment that could increase our confidence that any observed O 2 is a biosignature, and help discriminate it from potential false positives. The rich, interdisciplinary study of O 2 illustrates how a synthesis of our understanding of life's evolution and the early Earth, scientific computer modeling of star-planet interactions and predictive observations can enhance our understanding of biosignatures and guide and inform the development of next-generation planet detection and characterization missions. By observing and understanding O 2 in its planetary context we can increase our confidence in the remote detection of life, and provide a model for biosignature development for other proposed biosignatures.

Victoria S Meadows

Using Simulated Micrometeoroid Impacts to Understand the Progressive Space Weathering of the Surface of Mercury

The surfaces of airless bodies such as Mercury are continually modified by space weathering, which is driven by micrometeoroid impacts and solar wind irradiation. Space weathering alters the chemical composition, microstructure, and spectral properties of surface regolith. In lunar and ordinarychondritic style space weathering, these processes affect the reflectance properties by darkening (lowering of reflectance), reddening (increasing reflectance with increasing wavelength), and attenuation of characteristic absorption features. These optical changes are driven by the production of nanophase Febearing particles (npFe). While our understanding of these alteration processes has largely been based on data from the Moon and near-Earth S-type asteroids, the space weathering environment at Mercury is much more extreme. The surface of Mercury experiences a more intense solar wind flux and higher velocity micrometeoroid impacts than its planetary counterparts at 1 AU. Additionally, the composition of Mercury’s surface varies significantly from that of the Moon. Most notably, a very low albedo unit has been identified on Mercury’s surface, known as the low reflectance material (LRM). This unit is enriched with up to 4 wt.% carbon, likely in the form of graphite, over the local mean. In addition, the surface concentration of Fe across Mercury’s surface is low (<2 wt.%) compared to the Moon. Our understanding of how these low-Fe and carbon phases are altered as a result of space weathering processes is limited. Since Fe plays a critical role in the development of space weathering features on other airless surfaces (e.g., npFe), its limited availability on Mercury may strongly affect the space weathering features in surface materials. In order to understand how space weathering affects the chemical, microstructural, and optical properties of the surface of Mercury, we can simulate these processes in the laboratory [7]. Here we used pulsed laser irradiation to simulate the short duration, high temperature events associated with micrometeoroid impacts. We used forsteritic olivine, likely present on the Mercurian surface, with varying FeO contents, each mixed with graphite, in our experiments. We then performed reflectance spectroscopy and electron microscopy to investigate the spectral, chemical, and microstructural changes in these samples.

Thompson, Michelle S.

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

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

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

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

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

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

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]

Understanding the Active Site Structures and Achieving Catalytic Activity Tuning of Atomically Dispersed FeN 4 Sites for Oxygen Reduction Reaction

Atomically dispersed Fe–—N—C catalysts with high oxygen reduction reaction (ORR) activity have attracted great attention since the last decade. Due to comparable ORR activity and low material cost, they are promising platinum group metal (PGM)-free catalysts that can replace the commercialized Pt/C materials; furthermore, it can facilitate the efficiency of the fuel cell technologies and mitigate dependence on fossil fuels. Great advancements have been made to experimentally optimize the synthesis approach of the Fe–—N—C catalysts, enhance the ORR activity, and improve the catalyst stability. Similarly, recent theoretical studies also provide enriched understanding of the active site structures, properties, and reaction mechanisms. In this review, discussions are made upon utilizing combined experimental and computational spectroscopy to reveal the active site structures, employing mechanistic studies to investigate reaction thermodynamics and kinetics, as well as developing scaling relationships to assist the design and development of future PGM-free catalyst materials. Furthermore, recent advances in studying Fe–—N—C catalysts utilizing electrified surface models and explicit solvation models are also discussed. Not only can these aspects improve the accuracy of theoretical simulation and predictions but also deepen the understanding of the catalyst properties and reaction mechanisms under the effect of surface charges and solvent molecules.

Fe single-atom catalysts

Spatial analysis of cell patterning to aid genetic and phenotypic understanding of grass stomatal density: A case study in maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

59 BASIC BIOLOGICAL SCIENCES