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NASA NTRSDate not supplied

Physics and Modeling of Quasi-Steady and Forced Shock Trains

The dual-mode scramjet is a propulsive concept for contemporary hypersonic vehicles promising flight cruise speeds upwards of Mach 5. Despite decades of development and a recent resurgence in interest, such engines are not routinely deployed for commercial or military purposes. Instead, they have been confined to the realm of ground-test research and limited one-off flight test missions. One of the key stumbling blocks on the critical path to deployment of a dual-mode scramjet is the optimal design and stable operation of the isolator, a typically constant area duct that separates the scramjet inlet from the combustor. During ramjet mode at Mach numbers from 3 to 5 and during the transition to scramjet mode at higher Mach numbers, the isolator contains the pseudo-shock. Necessary to meet the back-pressure in the combustor, the pseudo-shock is typically divided into a shock dominated shock train region followed by a turbulence driven mixing region. Fluctuations in combustor pressure due to vehicle maneuvering, throttling, or combustion instabilities drive the shock train to shift streamwise within the isolator. In response to sharp pressure fluctuations, the shock train is unable to stabilize within the isolator, and the scramjet unstarts by ejecting the shock train out the inlet. This work addresses three key gaps in understanding of the isolator pseudo-shock. The phenomenon is studied in three experimental facilities to investigate the quasi-steady and unsteady fluid dynamics of the shock train in fueled and un-fueled test conditions. The strong link between boundary layer morphology and shock train structure is studied in detail and used as a tool to evaluate the state-of-the-art definitions and models of the pseudo-shock. Identifying the limitations of these models, a new process driven flux-conserved pseudo-shock model is proposed. This provides a computationally efficient model grounded in the fluid dynamic mechanisms of the pseudo-shock with better predictive capability than the current state-of-the-art across all facilities tested. The unsteady behavior of the shock train is further investigated to identify and understand two distinct forced dynamic modes: mechanically induced, low-rate forcing and high-rate combustion driven unsteadiness that sheds upstream propagating shocks. The proposed process driven model is found to be effective in the the limiting case of high-rate combustion driven unsteadiness by evaluating the model in a shock stationary reference frame. Further analysis identifies the approximately rigid chain motion of the shock train structure to mechanically induced forcing. The time delay between the onset of forced dynamics is found to saturate to a constant value and maximum shock train speed along the isolator with respect to the perturbation rate of change. The result of this work provides dual-mode scramjet designers with improved tools and physical understanding to develop more efficient, robust, and capable propulsion systems for hypersonic vehicles.

JAXA↗

DOE OSTI2024

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗

NASA NTRS1993

Horizontal stresses induced by vertical processes in planetary lithospheres

Understanding the state of stress in the elastic lithosphere is of fundamental importance for planetary geophysics, as it is the link between the observed geologic structures on the surface and the processes which form and modify these structures. As such, it can provide valuable constraints for the difficult problem of determining interior structure and processes. On the Earth, most large scale, organized deformation can be related to lateral tectonics associated with plate dynamics; however, the tectonics on many extraterrestrial bodies (such as the Moon, Mars, and most of the outer-planet satellites) appears to be primarily vertical in nature, and the horizontal stresses induced by vertical motions and loads are expected to dominate the deformation of their lithospheres. The largest stress contributions from vertical loading come from the flexure of the lithosphere, which induces both bending moments and membrane stresses. We are concerned here only with nonflexural changes in the state of stress induced by processes such as sedimentary and volcanic deposition, erosional denudation, and changes in the thermal gradient that induce uplift or subsidence. This analysis is important both for evaluating stresses for specific regions in which the vertical stress history can be estimated, as well as for applying the proper loading conditions to global stress models. It is also of interest for providing a reference state of stress for interpreting stress measurements in the crust of the Earth.

Banerdt, W. B.↗

NASA NTRS2006

Spectral Analysis Tool 6.2 for Windows

Spectral Analysis Tool 6.2 is the latest version of a computer program that assists in analysis of interference between radio signals of the types most commonly used in Earth/spacecraft radio communications. [An earlier version was reported in Software for Analyzing Earth/Spacecraft Radio Interference (NPO-20422), NASA Tech Briefs, Vol. 25, No. 4 (April 2001), page 52.] SAT 6.2 calculates signal spectra, bandwidths, and interference effects for several families of modulation schemes. Several types of filters can be modeled, and the program calculates and displays signal spectra after filtering by any of the modeled filters. The program accommodates two simultaneous signals: a desired signal and an interferer. The interference-to-signal power ratio can be calculated for the filtered desired and interfering signals. Bandwidth-occupancy and link-budget calculators are included for the user s convenience. SAT 6.2 has a new software structure and provides a new user interface that is both intuitive and convenient. SAT 6.2 incorporates multi-tasking, multi-threaded execution, virtual memory management, and a dynamic link library. SAT 6.2 is designed for use on 32- bit computers employing Microsoft Windows operating systems.

Morgan, Feiming↗

NASA NTRS2001

Linking Science Analysis with Observation Planning: A Full Circle Data Lifecycle

A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations. The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper will examine the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what has been its successes and challenges.

Jones, Jeremy↗

DOE OSTI2023

Response of Ecosystem Productivity to High Vapor Pressure Deficit and Low Soil Moisture: Lessons Learned From the Global Eddy-Covariance Observations

Although there is mounting concern about how high vapor pressure deficit (VPD) and low soil moisture (SM) affect ecosystem productivity, their relative importance is still under debate. Here, we comprehensively quantified the relative impacts of these two factors on ecosystem gross primary production (GPP) using observations from a global network of eddy-covariance towers and two approaches (sensitivity analysis and linear regression model). Both approaches agree that a higher percentage of sites experience GPP reduction from high VPD than from low SM over the growing season. However, the constraint of high VPD and low SM on GPP reduction is tightly linked with climates and plant functional types. Humid and mesic ecosystems including forests and grasslands are dominated by VPD, while the semi-arid and arid ecosystems including shrublands and savannas are dominated by SM. The varying dominant role of these two factors on GPP is closely related to plant stomatal behavior, as predicted by a stomatal conductance model. Additionally, we highlight the non-linear impact of SM on GPP during droughts and the possible underestimation of the SM effects for deep-rooted plants when only using surface-layer SM. Our results shed light on a better understanding of the impacts of VPD and SM on vegetation productivity, with important implications for modeling the response and feedback of ecosystem dynamics to current and future climates.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2001

Linking Science Analysis with Observation Planning: A Full Circle Data Lifecycle

A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations more efficiently, The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper examines the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what have been its successes and challenges.

Grosvenor, Sandy↗

NASA NTRS1994

Linking boundary-layer circulations and surface processes during FIFE89. Part 1: Observational analysis

Surface, aircraft, and satellite observations are analyzed for the 21-day 1989 intensive field campaign of the First ISLSCP Field Experiment (FIFE) to determine the effect of precipitation, vegetation, and soil moisture distributions on the thermal properties of the surface including the heat and moisture fluxes, and the corresponding response in the boundary-layer circulation. Mean and variance properties of the surface variables are first documented at various time and space scales. These calculations are designed to set the stage for Part 2, a modeling study that will focus on how time-space dependent rainfall distribution influences the intensity of the feedback between a vegetated surface and the atmospheric boundary layer. Further analysis shows strongly demarked vegetation and soil moisture gradients extending across the FIFE experimental site that were developed and maintained by the antecedent and ongoing spatial distribution of rainfall over the region. These gradients are shown to have a pronounced influence on the thermodynamic properties of the surface. Furthermore, perturbation surface wind analysis suggests for both short-term steady-state conditions and long-term averaged conditions that the gradient pattern maintained a diurnally oscillating local direct circulation with perturbation vertical velocities of the same order as developing cumulus clouds. Dynamical and scaling considerations suggest that the embedded perturbation circulation is driven by surface heating/cooling gradients and terrain ef fects rather than the manifestation of an inertial oscillation. The implication is that at even relatively small scales (less than 30 km), the differential evolution in vegetation density and soil moisture distribution over a relatively homogenous ecotone can give rise to preferential boundary-layer circulations capable of modifying local-scale horizontal and vertical motions.

Smith, Eric A.↗

DOE OSTI2026

Thiol post-translational modifications modulate allosteric regulation of the OpcA–G6PDH complex through conformational gate control

In cyanobacteria, the redox-sensitive protein OpcA acts as a metabolic switch for G6PDH, enabling rapid adjustment of reducing power generation from glycogen catabolism and thereby precisely regulating carbon flux between anabolic and catabolic pathways. Although redox-sensitive cysteines in OpcA are known to regulate G6PDH, the mechanisms by which redox post-translational modifications (PTMs) on OpcA control G6PDH structure and activity remain unclear. Here, we combine computational modeling with experimental redox proteomics in Synechococcus elongatus PCC 7942 to dissect this mechanism. Experimentally, redox proteome analysis revealed differential redox PTM patterns, particularly on cysteines within the G6PDH-binding site of OpcA. These environmentally sensitive PTM changes at the interface suggest that thiol modifications in this region form a key regulatory node. More broadly, redox proteomics identified site-specific cysteine modifications under light/dark transitions and circadian cycling, linking distinct redox regimes to discrete PTM states. We employed PTM-Psi simulations to show that thiol PTMs near the OpcA–G6PDH interface are critical for allosteric regulation of G6PDH. The thiol PTMs on OpcA affect a putative gate region in G6PDH for substrate ingress and product egress as well as key hydrogen-bond networks within the active site. We infer that PTMs on OpcA tune the conformational landscapes of individual G6PDH subunits toward functionally relevant configurations according to environmental gradients, biasing the enzyme toward catalytically favorable states. Together, our results reveal a molecular mechanism in which thiol PTMs on OpcA modulate G6PDH structure and function through PTM-induced reorganization of conformational dynamics and allosteric communication. These findings demonstrate that PTM-level regulation provides a critical control layer from genotypes to phenotypes that enables cyanobacteria to rapidly adapt to environmental fluctuations through precise metabolic fine-tuning.

Allosteric regulation↗

NASA NTRSDate not supplied

Early Information Parameter-Set Analysis for Satellite Close Approaches using Machine Learning

Understanding orbital mechanics is essential in space flight and navigation applications, and leveraging modern force models for flight path projection remains an important aspect in space mission design and operation. However, force models do not capture all the dynamics or perturbations in the space environment and thus are subject to errors in predicting the state vectors. The further out the predicted miss distance between spacecraft is from the time of closest approach (TCA), the larger the propagated errors in the predicted miss distance at TCA is. The dependency on these force models for spacecraft flight state prediction calls for a more reliable method that can quantify, or even reduce, these propagated errors. With recent advances in the field artificial intelligence, specifically in machine and deep learning algorithms, a model that implements these approaches can improve on the modern force model approach. The goal for this work is to provide an early-information decision-making threshold, in order to prioritize risk assessment implementation, given the ongoing increase of space objects. In analyzing the relationship of several parameters from conjunction data messages(CDMs) and solar information, early information becomes viable in miss distance prediction with unsupervised learning techniques, which learn the parameters that are linked together with miss distance and probability of collision (Pc) variables. Another approach implemented for identifying relationships within CDMs is supervised learning, in which a shallow neural network binary classifier learns to distinguish events with Pc values¡108. These parameters detected in the unsupervised process are then applied to a regression neural network, which predicts the miss distance at TCA for a specific event within a given uncertainty bound. For the regression neural network, a Long Short Term Memory (LSTM) neural network is implemented, which yields memory about each time step in an event. Using an LSTM network, the model learns to predict miss distance within 0.2km of the value measured at TCA. Although there is a limited amount of "close miss" data to train a network, the network learns to associate parameters, like large energy dissipation rates with the secondary object, with an elevated Pc

Brianna I. Robertson↗

NASA NTRS2000

Dynamic Stall Characteristics of Drooped Leading Edge Airfoils

Helicopters in high-speed forward flight usually experience large regions of dynamic stall over the retreating side of the rotor disk. The rapid variations in the lift and pitching moments associated with the stall process can result in vibratory loads, and can cause fatigue and failure of pitch links. In some instances, the large time lag between the aerodynamic forces and the blade motion can trigger stall flutter. A number of techniques for the alleviation of dynamic stall have been proposed and studied by researchers. Passive and active control techniques have both been explored. Passive techniques include the use of high solidity rotors that reduce the lift coefficients of individual blades, leading edge slots and leading edge slats. Active control techniques include steady and unsteady blowing, and dynamically deformable leading edge (DDLE) airfoils. Considerable amount of experimental and numerical data has been collected on the effectiveness of these concepts. One concept that has not received as much attention is the drooped-leading edge airfoil idea. It has been observed in wind tunnel studies and flight tests that drooped leading edge airfoils can have a milder dynamic stall, with a significantly milder load hysteresis. Drooped leading edge airfoils may not, however, be suitable at other conditions, e.g. in hover, or in transonic flow. Work needs to be done on the analysis and design of drooped leading edge airfoils for efficient operation in a variety of flight regimes (hover, dynamic stall, and transonic flow). One concept that is worthy of investigation is the dynamically drooping airfoil, where the leading edge shape is changed roughly once-per-rev to mitigate the dynamic stall.

Sankar, Lakshmi N.↗

DOE OSTI2023

Fusing time-varying mosquito data and continuous mosquito population dynamics models

Climate change is arguably one of the most pressing issues affecting the world today and requires the fusion of disparate data streams to accurately model its impacts. Mosquito populations respond to temperature and precipitation in a nonlinear way, making predicting climate impacts on mosquito-borne diseases an ongoing challenge. Data-driven approaches for accurately modeling mosquito populations are needed for predicting mosquito-borne disease risk under climate change scenarios. Many current models for disease transmission are continuous and autonomous, while mosquito data is discrete and varies both within and between seasons. This study uses an optimization framework to fit a non-autonomous logistic model with periodic net growth rate and carrying capacity parameters for 15 years of daily mosquito time-series data from the Greater Toronto Area of Canada. The resulting parameters accurately capture the inter-annual and intra-seasonal variability of mosquito populations within a single geographic region, and a variance-based sensitivity analysis highlights the influence each parameter has on the peak magnitude and timing of the mosquito season. This method can easily extend to other geographic regions and be integrated into a larger disease transmission model. This method addresses the ongoing challenges of data and model fusion by serving as a link between discrete time-series data and continuous differential equations for mosquito-borne epidemiology models.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Transcriptomic and functional analyses uncover a conserved effector driving genotype-dependent virulence in the Sphaerulina musiva-Populus trichocarpa interaction

The introduction of invasive microbes compromises the structure, biodiversity, and function of naïve ecosystems. Sphaerulina musiva, a hemibiotrophic pathogen that causes leaf spot and stem cankers in Populus species, exemplifies an invasive fungal pathogen spread by human activities. However, the genetic mechanisms of pathogenicity and virulence are poorly understood, impeding mitigation strategies. We utilized RNA sequencing to identify fungal effectors linked to stem canker formation, informing the development of future strategies for effective disease management. Our analysis revealed 70 genes differentially expressed at 2 weeks and 110 genes at 3 weeks between inoculated trees and controls. Notably, the gene with the highest expression at 2 weeks and the second highest at 3 weeks was homologous to Extracellular protein 2 (Ecp2). Complementary genome-wide association studies linked sequence polymorphisms in this locus to phenotypic variation in disease severity. Infiltration of S. musiva Ecp2 into Populus trichocarpa leaves induced necrosis in susceptible genotypes. Gene disruption using a CRISPR-Cas9 RNP system resulted in a genotype-dependent reduction of stem canker and disease severity. Tracing the evolutionary history of this effector across the fungal kingdom, we uncovered clade-specific gene-family expansions and orthologs in new species. These findings raise questions about the function and adaptive significance of these gene families in fungal lifestyles. Our study provides the first tractable target for breeding resistant poplar genotypes, addressing the challenges of managing S. musiva and uncovering mechanisms that drive its virulence, and provides deeper insights into the evolutionary dynamics of a conserved small-secreted protein with a diversity of functions.

Sondreli, Kelsey L [Oregon State University]↗

DOE OSTI2023

A Novel Spatio-Temporal Regime Tracking Method for Impact Simulations

In this proposal, we present a novel method of tracking the rheological regimes activated during impact cratering events that will allow researchers to gain new insights into cratering mechanics. Rheology describes the stress-strain response of rocks to different conditions. Planetary impact cratering events often occur on too large of a scale to be feasibly captured in controlled experiments. Instead, these dynamic events are primarily studied using multi-physics codes equipped with complex material models that enable calculations of the impact event at scale. However, determining which physical processes are required for the problem of interest is challenging. Because the dominant rheological regimes change with space and time during crater formation, it is difficult to link numerical simulations with observable features of craters at the end of the event. The basis of this work is the implementation of numerical flags that track the activation of each rheological regime throughout impact simulations. We demonstrate this with the ‘Rock Model’ implemented in the CTH shock-physics code. We will use this rheology tracking method to ’zoom in’ on a specific region within an event and track the conditions the rock experiences over time. This work will develop community benchmarks to validate and distribute our implemented rheological models. We will focus on improving the melt models used by the planetary impact modeling community by developing an EOS-aware rheological transition from solid to melt. Through analysis of cell and tracer-particle based tracking data, we will study the effects of different rheologies on modeled outcomes, particularly on the volume and distributions of impacts melts. We will also use this method to link observable features with the rheological mechanisms responsible for them. The deliverables (peer-reviewed papers) from the proposed work are (i) tests of the implemented rheologic processes and demonstrations of the tracking flags; (ii) the first calculations of the spatio-temporal evolution of the dominant rheologies during impact cratering events; and (iii) application to delivery of impactor iron during basin-scale impacts.

58 GEOSCIENCES↗

DOE OSTI2023

Twin-screw granulation: Mechanistic understanding of the effect of material properties on key granule quality attributes through the analysis of mixing dynamics and granulation rate mechanisms

This study focuses on understanding the effect of material properties on granule quality attributes through the analysis of mixing dynamics and granulation rate mechanisms. Powder wettability, binder viscosity, and liquid-to-solid (L/S) ratio were the factors that were investigated in this study. Further, the mixing occurring inside the twin-screw granulator (TSG) was quantitatively assessed by obtaining the axial dispersion coefficient from the experimentally measured residence time distribution (RTD) curves. It was observed that the quality of the nuclei fed to the kneading zone significantly affected the mixing dynamics. The quality of nuclei was governed by nucleation kinetics, which in turn was principally affected by the liquid saturation of the nuclei and the ratio of drop penetration time and encounter time, which in turn were affected by the L/S ratio and binder viscosity respectively. The hydrophobicity of the blend mainly affected the extent of nucleation. The type of nuclei entering the kneading zone and mixing dynamics in the TSG also determined whether the granulation growth mechanism was “layering-dominant” or “viscous-dominant”. It was also shown that the resultant granule quality attributes were a reflection of the growth mechanisms. Ultimately, a mechanistic link between material properties, mixing dynamics, granulation rate mechanisms, and granule quality attributes was established.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗

DOE OSTI2021

Excited-State Bond Contraction and Charge Migration in a Platinum Dimer Complex Characterized by X-ray and Optical Transient Absorption Spectroscopy

Interactions between metal centers in dimeric transition metal complexes (TMCs) play important roles in their excited-state energetics and pathways, and, thus, affect their photophysical properties relevant to their applications, e.g., photoluminescent materials and photocatalysis. In this study, we report electronic and nuclear structural dynamics studies of two photoexcited pyrazolate-bridged [Pt(ppy)(µ-R 2 pz)] 2 -type Pt(II) dimers (ppy = 2-phenylpyridine, µ-R 2 pz = 3,5-substituted pyrazolate): [Pt(ppy)(µ-H 2 pz)] 2 (1) and [Pt(NDI-ppy)(µ-Ph 2 pz)] 2 (2, NDI = 1,4,5,8-naphthalenediimide), both of which have distinct ground state Pt-Pt distances. X-ray transient absorption spectroscopy at the Pt L III -edge revealed a new d-orbital vacancy due to the one-electron oxidation of the Pt centers in 1 and 2. However, while a transient Pt-Pt contraction was observed in 2, such an effect was completely absent in 1, demonstrating how the excited states of these complexes are determined by the overlap of the Pt (d z 2 ) orbitals, which is tuned by steric bulk of the pyrazolate R-groups in the 3- and 5-positions. In tandem with analysis of the Pt-Pt distance structural parameter, we observed photoinduced charge separation in 2 featuring a covalently linked NDI acceptor on the ppy ligand. The formation and subsequent decay of the NDI radical anion absorption signals were detected upon photoexcitation using optical transient absorption spectroscopy. The NDI radical anion decayed on the same timescale, hundreds of picoseconds, as that of the d-orbital vacancy signal of the oxidized Pt-Pt core observed in the XTA measurements. The data indicated ultrafast formation of the charge-separated state and subsequent charge recombination to the original Pt(II-II) species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Understanding the dynamics of vacuole trafficking and secretion for enhanced plant storage reserves

Vacuoles are essential in plants and serve roles in both protein and organelle degradation for reutilization and storage of high energy molecules such as storage proteins which are critical for seed germination under normal and stress conditions and impact biomass production and nutrition. In addition, plants secrete many different molecules such as cell wall components, lipids, waxes and others that are important for plant protection, structure and biomass. Vacuole accumulation and secretion are closely linked and highly regulated pathways within the endomembrane trafficking network. We have discovered many drug-like synthetic small molecules that can suppress vacuole trafficking and enhance secretion; other chemicals can enhance vacuole trafficking and suppress secretion. The ability of our compounds to modulate these pathways indicates that these pathways are tightly coupled and highly regulated. Thus, to achieve the goals of enhanced energy reserves or enhanced secretion it is essential to understand how this dynamic is controlled. Bioactive chemicals have provided us unique insight into natural mechanisms controlling the dynamics of vacuole trafficking and secretion that was not possible previously. One such compound, ES2, negatively modulates secretion while enhancing vacuole trafficking. This is the first compound discovered that targets an essential secretory complex known as the exocyst and will reveal important regulatory domains controlling secretion and vacuole trafficking. During the current funding period, we determined the structure of the EXO70A1 in plants and identifying its binding site. To understand the dynamics of vacuole trafficking it is key to have compounds that inhibit vacuole trafficking as well as enhancing it (ES2). We have used sophisticated image analysis to identify another novel compound ES17 that enhances secretion while negatively modulating vacuole trafficking (opposite of ES2). We have already made rapid progress. Our preliminary data indicates that ES17 very specifically targets a late stage of vesicle fusion with the tonoplast which is highly regulated. Thus, ES17 is an ideal compound to dissect the regulation of vacuole targeting dynamics. In addition, we have now synthesized a biotinylated version of ES17 that is fully functional, permitting the use of chemical proteomics to identify the cognate target with a high probability of success. We propose to investigate the ES17 target which can negatively modulate vacuole trafficking and combine this with knowledge of the ES2 target which can promote vacuole trafficking. Dissecting the mechanisms controlling the dynamics of secretion vs vacuole accumulation and the use of synthetic modulators will permit us to understand and regulate trafficking to enhance secretion to the plasma membrane and cell wall or the accumulation of biological energy reserves for increased biomass, nutritional value, stress resistance, and the secretion of specialized plant products.

59 BASIC BIOLOGICAL SCIENCES↗