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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Streaming Large-Scale Microscopy Data to a Supercomputing Facility

Data management is a critical component of modern experimental workflows. As data generation rates increase, transferring data from acquisition servers to processing servers via conventional file-based methods is becoming increasingly impractical. The 4D Camera at the National Center for Electron Microscopy generates data at a nominal rate of 480 Gbit s -1 (87,000 frames s -1 ⁠), producing a 700 GB dataset in 15 s. To address the challenges associated with storing and processing such quantities of data, we developed a streaming workflow that utilizes a high-speed network to connect the 4D Camera’s data acquisition system to supercomputing nodes at the National Energy Research Scientific Computing Center, bypassing intermediate file storage entirely. In this work, we demonstrate the effectiveness of our streaming pipeline in a production setting through an hour-long experiment that generated over 10 TB of raw data, yielding high-quality datasets suitable for advanced analyses. Additionally, we compare the efficacy of this streaming workflow against the conventional file-transfer workflow by conducting a postmortem analysis on historical data from experiments performed by real users. Our findings show that the streaming workflow significantly improves data turnaround time, enables real-time decision-making, and minimizes the potential for human error by eliminating manual user interactions.

4D-STEM↗
DOE OSTI2020

U.S. Department of Energy Free-Air CO 2 Enrichment Experiments: FACE Results, Lessons, and Legacy

In the 1970s, growing concern about potential long-range consequences of carbon dioxide (CO 2 ) emissions from the combustion of fossil fuels prompted the U.S. Department of Energy (DOE) to begin developing a CO 2 research program. The goal was to obtain the scientific information needed to reduce uncertainty and develop a knowledgebase for decision-making. At its start in 1980, this program had three components: the global carbon cycle, climate effects, and vegetation effects. The vegetation effects component recognized that increased atmospheric CO 2 could be a potential benefit to vegetation and crops because CO 2 is an essential resource for plant growth. In addition to increasing crop yield, program developers and researchers recognized that this fertilizer effect could also result in greater storage of fossil fuel CO 2 by forests. Initial experiments were small in scale and scope and focused on the photosynthesis, physiology, and water use of crop plants, but the focus shifted toward responses of plants in natural systems, as needed for connections to the global carbon cycle. Program research investigated CO 2 interactions with other environmental variables, emphasizing field research whenever possible and recognizing that exposure to elevated CO 2 concentrations under realistic field conditions should lead to better predictions of plant response. Whole-ecosystem field experiments were instituted in low-stature ecosystems, but experiments to address forest responses necessarily relied on tree seedlings or saplings in open-top chambers (OTCs) and not within intact forest ecosystems. The need for larger-scale, longer-duration experiments in each of the world’s six major biomes (tundra, boreal forest, temperate forest, tropical forest, grassland, and desert) became clear, and for these experiments, free-air CO 2 exposure facilities were necessary. This report summarizes the objectives and main results of DOE-sponsored experiments employing such facilities, along with the outcomes from research on ecosystem responses using field chambers (see Fig. ES.1, p. x). Additionally, this report highlights the many successes of DOE CO 2 enrichment studies and considers the lessons learned that can be used to guide future initiatives.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

WHONDRS-GUI: a web application for global survey of surface water metabolites

Background The Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) is a consortium that aims to understand complex hydrologic, biogeochemical, and microbial connections within river corridors experiencing perturbations such as dam operations, floods, and droughts. For one ongoing WHONDRS sampling campaign, surface water metabolite and microbiome samples are collected through a global survey to generate knowledge across diverse river corridors. Metabolomics analysis and a suite of geochemical analyses have been performed for collected samples through the Environmental Molecular Sciences Laboratory (EMSL). The obtained knowledge and data package inform mechanistic and data-driven models to enhance predictions of outcomes of hydrologic perturbations and watershed function, one of the most critical components in model-data integration. To support efforts of the multi-domain integration and make the ever-growing data package more accessible for researchers across the world, a Shiny/R Graphical User Interface (GUI) called WHONDRS-GUI was created. Results The web application can be run on any modern web browser without any programming or operational system requirements, thus providing an open, well-structured, discoverable dataset for WHONDRS. Together with a context-aware dynamic user interface, the WHONDRS-GUI has functionality for searching, compiling, integrating, visualizing and exporting different data types that can easily be used by the community. The web application and data package are available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1484811 , which enables users to simultaneously obtain access to the data and code and to subsequently run the web app locally. The WHONDRS-GUI is also available for online use at Shiny Server ( https://xmlin.shinyapps.io/whondrs/ ).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Optimization of WAAM Process to Produce AUSC Components with Increased Service Life

Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Study of CC2p0$\pi$ Event Topologies in the MicroBooNE Detector

The precise measurement of neutrino oscillation parameters is a critical component of understanding neutrino oscillations. As future accelerator neutrino experiments will utilize 40 Ar as the target nucleus it is important to understand the influence that nuclear effects have on neutrino-nucleon cross-sections. Processes that lead to 2 particle-2 hole (2p2h) states are of particular interest, such as Meson Exchange Currents (MEC) and Short Range Nucleon-Nucleon Correlations. In the MicroBooNE detector, a charged-current interaction that produced a 2p2h state would create a 3 track topology with 1 muon and 2 protons connected to a single interaction vertex (CC2p0$\pi$). We present here a study of MicroBooNE’s potential sensitivity to a variety of MEC models as well as CC2p0$\pi$ events selected from a combination of data collected from the first 3 years of running of the MicroBooNE experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Genomic adaptations of the green alga Dunaliella salina to life under high salinity

Life in high salinity environments poses challenges to cells in a variety of ways: maintenance of ion homeostasis and nutrient acquisition, often while concomitantly enduring saturating irradiances. Dunaliella salina has an exceptional ability to thrive even in saturated brine solutions. This ability has made it a model organism for studying responses to abiotic stress factors. Here we describe the occurrence of unique gene families, expansion of gene families, or gene losses that might be linked to osmoadaptive strategies. We discovered multiple unique genes coding for several of the homologous superfamily of the Ser-Thr-rich glycosyl-phosphatidyl-inositol-anchored membrane family and of the glycolipid 2-alpha-mannosyltransferase family, suggesting that such components on the cell surface are essential to life in high salt. Gene expansion was found in families that participate in sensing of abiotic stress and signal transduction in plants. One example is the patched family of the Sonic Hedgehog receptor proteins, supporting a previous hypothesis that plasma membrane sterols are important for sensing changes in salinities in D. salina. We also investigated genome-based capabilities regarding glycerol metabolism and present an extensive map for core carbon metabolism. We postulate that a second broader glycerol cycle exists that also connects to photorespiration, thus extending the previously described glycerol cycle. Further genome-based analysis of isoprenoid and carotenoid metabolism revealed duplications of genes for 1-deoxy-D-xylulose-5-phosphate synthase (DXS) and phytoene synthase (PSY), with the second gene copy of each enzyme being clustered together. Moreover, we identified two genes predicted to code for a prokaryotic-type phytoene desaturase (CRTI), indicating that D. salina may have eukaryotic and prokaryotic elements comprising its carotenoid biosynthesis pathways. In brief, our genomic data provide the basis for further gene discoveries regarding sensing abiotic stress, the metabolism of this halophilic alga, and its potential in biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Utah FORGE 2-2439v2: Characterizing In-Situ Stress with Laboratory Modelling and Field Measurements - 2024 Annual Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project by The University of Pittsburgh, presented by Andrew Bunger. The project characterizes the stress in the Utah FORGE EGS reservoir using three methods: Method 1: Demonstrate complimentary laboratory rock-core stress estimation combined with Machine Learning approach for measuring in-situ stress from field sonic log data; Method 2: Complete field based in-situ measurement (mini-frac); and Method 3: Develop a mechanics-based method for connection near wellbore stress measurements to stresses away from the well-bore. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 14, 2024.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

NSTX-U National Research Program: White Paper in Response to Call from FESAC Sub-Committee

Both scientific and technical innovation is needed for the realization of an attractive engineering solution for a timely and cost-effective Pilot Plant, the design and construction of which is the overarching recommendation of the FESAC Long Range Plan, and the 2021 NASEM Pilot Plant reports, which underpin the Bold Decadal Vision. The two most significant plasma physics gaps to close for a Compact Pilot Plant (CPP) are core confinement improvement and heat flux mitigation, neither of which have been closed in an integrated fashion for any planned fusion power production device. High core confinement and stability are essential for producing majority self-driven plasmas in CPPs with reduced size and auxiliary heating power requirements, with an improvement in confinement being the major driver for cost reduction of a CPP. The National Spherical Tokamak Experiment - Upgrade (NSTX-U) is a unique low aspect ratio research facility that will address the fundamental challenge of developing the science and technology basis for a CPP design that integrates high core and edge confinement with the ability to mitigate very high incident heat fluxes. NSTX-U capabilities will enable the high performance, already achieved on NSTX, to extend into physics regimes much closer to those anticipated in Spherical Tokamak (ST)-based CPPs. These confinement and stability properties will be assessed by a full complement of diagnostics and analysis tools, which will also aid in the development of the underlying theory and predictive models needed for further optimization. Both conventional and transformative heat flux mitigation methods, such as liquid lithium plasma-facing components, will be developed and tested in-situ in NSTX-U at incident heat fluxes of ~100 MW/m 2 , and will inform plans and reduce risk for a subsequent major upgrade to the device to fully heated, high-Z wall and full liquid lithium divertor capability, a technology that potentially could then be implemented on any magnetic confinement device at any aspect ratio. NSTX-U research is fully complementary to programs performed on other STs, nationally and internationally. Furthermore, NSTX-U research has a direct connection to the private sector by informing design choices for future power production facilities being developed by these companies. The NSTX-U program will operate as a national User Facility, with collaborating researchers, engineers, and graduate students from 19 outside institutions, and open to participation and experiments led by researchers from both public and private entities. The research program will advance workforce development through training of young scientists, engineers, and technicians, and it will also serve for further diagnostic innovation, especially for high heat flux and high-Z wall environments, and implementation of advanced artificial intelligence (AI) for plasma and heat flux control.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A Visual Understanding of Circular Dichroism Spectroscopy

Mapping chemical and structural properties to electronic and magnetic responses is critical to many applications such as quantum information science, where the precise storage and transmission of unique information is paramount. Specifically, constructing molecules and materials that provide strong polarized responses at tunable frequencies and with large anisotropies is key to optical processing of quantum information. Chiral molecules provide chiroptical response to circularly polarized light, making them attractive for quantum information science and other applications related to sensing, polarized photodetectors, and spintronics. Predicting a molecular design, a priori, with large anisotropies to circularly polarized light is challenging due to the complex interplay between electric and magnetic components of the optical response. In this work, we explore a visual representation of the electronic chiroptical response by decomposing the rotary strength into its constituent components. Here, we make use of the intuitive electronic oscillator framework to develop classical intuition regarding the rotary strength and its constituents. We explore three model chemical systems that exhibit local and global chirality. Our analysis reveals that local chirality necessarily exhibits competition between the local chiral center and chirality induced in other fragments of the molecule, resulting in both unexpected nonmonotonic trends and sign flips in chemically adjacent geometries. Furthermore, we can visually distinguish between local and global chirality via examination of the transition chiral tensor. Interestingly, we make strong connections to ferromagnetic and antiferromagnetic spin systems in that chiroptically inactive transitions exhibit antiferromagnetic-like alternating orbital patterns while active transitions show domain formation in an ferromagnetic-like alignment that produces a net chiroptical response.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantifying and visualizing the microscopic degrees of freedom of grain boundaries in the Wigner–Seitz cell of the displacement-shift-complete lattice

Here we introduce a grain boundary (GB) translation vector, t ws , to describe and quantify the domain of the microscopic degrees of freedom of GBs. It has long been recognized that for fixed macroscopic degrees of freedom of a GB there exists a large multiplicity of states characterized by different relative grain translations. More recently another degree of freedom, [n], the number of GB atoms, has emerged and is now recognized as an equally important component of GB structural multiplicity. In this work, we show that all GB microstates can be uniquely characterized by their value of t ws , which is located within the Wigner–Seitz (WS) cell of the Displacement-Shift-Complete lattice (DSCL) of the GB. The GB translation vector captures information about both the translation state and the number of GB atoms. We show that the density of GB microstates inside the WS cell of the DSCL is not uniform and can form clusters that correspond to different GB phases. Further, the vectors connecting the centers of the clusters correspond to the Burgers vectors of GB phase junctions, which can be predicted without building the junctions. Using t ws , we quantify GB excess shear and argue that it is defined up to a DSCL vector, which has implications for thermodynamic equilibrium conditions. Additionally, this work generalizes the definition of the number of GB atoms [n] to asymmetric boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Domain architecture and catalysis of the Staphylococcus aureus fatty acid kinase

Fatty acid kinase (Fak) is a two-component enzyme that generates acyl-phosphate for phospholipid synthesis. Fak consists of a kinase domain protein (FakA) that phosphorylates a fatty acid enveloped by a fatty acid binding protein (FakB). The structural basis for FakB function has been established, but little is known about FakA. Here, we used limited proteolysis to define three separate FakA domains: the amino terminal FakA_N, the central FakA_L, and the carboxy terminal FakA_C. The isolated domains lack kinase activity, but activity is restored when FakA_N and FakA_L are present individually or connected as FakA_NL. The X-ray structure of the monomeric FakA_N captures the product complex with ADP and two Mg 2+ ions bound at the nucleotide site. The FakA_L domain encodes the dimerization interface along with conserved catalytic residues Cys240, His282, and His284. AlphaFold analysis of FakA_L predicts the catalytic residues are spatially clustered and pointing away from the dimerization surface. Furthermore, the X-ray structure of FakA_C shows that it consists of two subdomains that are structurally related to FakB. Analytical ultracentrifugation demonstrates that FakA_C binds FakB, and site-directed mutagenesis confirms that a positively charged wedge on FakB meshes with a negatively charged groove on FakA_C. Finally, small angle X-ray scattering analysis is consistent with freely rotating FakA_N and FakA_C domains tethered by flexible linkers to FakA_L. These data reveal specific roles for the three independently folded FakA protein domains in substrate binding and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation

We introduce a conditional pseudo-reversible normalizing flow (PR-NF) that directly learns conditional probability distributions from noisy physical models to efficiently quantify both forward and inverse uncertainty propagation. Traditional surrogate modeling approaches approximate only the deterministic component of physical models, requiring separate noise characterization and computationally expensive sampling methods for inverse problems. Here, in this work, we develop the conditional PR-NF model to directly learn and efficiently generate samples from the conditional probability density functions (PDFs). The training process utilizes dataset consisting of input-output pairs without requiring prior knowledge about the noise and the function. Once trained, our model efficiently generates samples from conditional PDFs for any input within the training domain. Moreover, the pseudo-reversibility feature allows for the use of fully connected neural network architectures, which simplifies the implementation and enables theoretical analysis. We provide a rigorous convergence analysis of the conditional PR-NF model, showing its ability to converge to the target conditional PDF using the Kullback−Leibler divergence. To demonstrate the effectiveness of our method, we apply it to several benchmark tests and a real-world geologic carbon storage problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Practical Comparison of Data-Driven Prognostics Methods for Energy Systems

This study explores data-driven prognostics for nuclear power plant (NPP) condensers, focusing on tube fouling. We utilized the Asherah nuclear power plant simulator (ANS) to compare four methods: Random Forest (RF), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory Neural Network (LSTM). By simulating various fouling scenarios in the ANS, we generated data with different degradation rates under transient operations. The models were trained and tested on these data, with performance evaluated visually and numerically including uncertainty assessment. The LSTM model excelled, exhibiting minimal prediction noise and the most accurate remaining useful life estimates across all degradation levels. Its ability to capture long-term dependencies and produce cleaner outputs makes it a strong candidate, although accurate training data across the entire component lifespan are crucial. The RF model emerged as a robust alternative, providing reliable predictions with high confidence. The FCNN and SVR models, while less effective overall, showed potential under specific conditions. FCNN offers a less complex alternative to LSTM and might benefit from larger datasets. SVR excels in precision when the quality of the training data is high. Furthermore, this study highlights the operational benefits of advanced prognostics in the energy sector and emphasizes the need for further research in NPP condenser health management through real-life experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Mixed warm dark matter constraints using Milky Way satellite galaxy counts

Warm dark matter has been strongly constrained in recent years as the sole component of dark matter. However, a less-explored alternative is that dark matter consists of a mixture of warm and cold dark matter (MWDM). In this work, we use observations of Milky Way satellite galaxies to constrain MWDM scenarios where the formation of small-scale structure is suppressed either by generic thermal relic warm dark matter or a sterile neutrino produced through the Shi-Fuller mechanism. To achieve this, we model satellite galaxies by combining numerical simulations with semianalytical models for the subhalo population, and use a galaxy-halo connection model to match galaxies onto dark matter subhalos. By comparing the number of satellites predicted by MWDM models to the observed satellite population from the Dark Energy Survey and Pan-STARRS1, we constrain the fraction of warm dark matter, f WDM , as a function of its mass, m WDM . We exclude dark matter being composed entirely of thermal relic warm dark matter with m WDM ≤ 6.6 keV at a posterior ratio of 10 ∶ 1 , consistent with previous works. However, we find that warm dark matter with smaller mass is allowed when mixed with cold dark matter, and that the f WDM constraints strengthen with decreasing m WDM until they plateau at f WDM ≲ 0.45 for m WDM ≲ 1.5 keV . Likewise, in the case of a sterile neutrino with mass of 7 keV produced through the Shi-Fuller mechanism, we exclude a fraction of f ν s ≲ 0.45 , independent of mixing angle. Our results extend constraints on MWDM to a region of parameter space that has been relatively unconstrained with previous analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Multiscale Electrothermal Design of a Modular Multilevel Converter for Medium-Voltage Grid-Tied Applications

As a key feature of modular multilevel converters (MMCs), a large number of semiconductor devices are employed in the converter and distributed over a stack of submodules. Each submodule has a strict temperature limit that imposes constraints on the operating range of the converter. Different loading conditions/losses in the submodules lead to unavoidable temperature variations inside the MMC, which consequently affect the system-level performance and reliability. This paper is focused on the electrothermal analysis and design of a medium-voltage silicon carbide (SiC)-based MMC system, from submodule power semiconductors to the overall MMC system integration of multiple submodules, for grid-connected applications. Loss calculations are performed to estimate the cooling requirements and aid thermal design at different levels. The performance of a forced-air cooling approach is analyzed within a numerical modeling framework. Maximum temperature of the SiC power modules is predicted using numerical tools. Thermal design of the MMC cabinet with various arrangements of air inlet(s) and outlet(s) is investigated and compared from a cooling performance perspective. A fully resolved model of the arrangement that yields optimal results is developed to accurately predict the temperature profile of the essential components in the submodules.

computational fluid dynamics↗
DOE OSTI2024

Building a Simplistic Automatic Extruder: Instrument Development Opportunities for the Laboratory

This work presents an automatic extruder as a research experience for undergraduate students. The system offers a user-friendly approach to preparing vesicles, such as liposomes or polymersomes, with a defined size and polydispersity properties crucial for research in biology and macromolecules. It comprises two syringe pumps connected by a membrane filter. The setup is controlled by software. Compared to manual extrusion, this automated system provides advantages, such as precisely controlled variables. The project describes a tool to enhance undergraduate learning in science and engineering laboratories. Building an automatic extruder serves as a simplified model of a complex industrial process. It offers a clear advantage: automating a well-understood manual extrusion process. To make this project accessible, it is broken down into three manageable tasks: software development, hardware assembly, and testing procedures. This breakdown describes the software created, the hardware components used, and the testing procedures conducted for this project. All project data, including software code, testing data, and procedures, are freely available online. This allows undergraduate students to not only begin their own projects but also contribute to this educational instrument’s ongoing development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

From photosynthetic electron flow to gene regulation: redox signal transduction in cyanobacteria

In cyanobacteria, the free-living ancestors of chloroplasts, photosynthesis simultaneously sustains growth and generates reactive oxygen species (ROS) that damage proteins, lipids, and DNA when light capture outpaces carbon fixation. Maintaining redox balance, therefore, requires cells to read photosynthetic electron flow as a signal that continuously tunes gene expression and protein activity. This review traces how these redox signals are transduced to transcription machinery through three routes: membrane-localized sensors, cytoplasmic redox sensors downstream of photosystem I, and ROS generated when electron sinks are saturated. Membrane-bound histidine kinases (two-component systems) relay the redox state of the plastoquinone pool to control photosystem remodeling, pigment biosynthesis, and circadian timing. Cytoplasmic one-component regulators, by contrast, sense redox directly through thiol-disulfide switches, glutathionylation, iron-sulfur clusters, and metal-catalyzed oxidation to control photosystem-cofactor, electron-carrier, and transition-metal homeostasis. Because many of these regulators persist in algal and plant chloroplasts, cyanobacteria illuminate principles of redox control across photosynthetic eukaryotes. Post-transcriptional and translational control further shapes redox-dependent gene expression programs through transcript stability, ribosome assembly, and translation initiation, extending redox regulation beyond transcription to every step of protein synthesis and even activity modulation. Finally, we connect redox regulation to photosynthetic physiology, stress resilience, and the rational engineering of cyanobacteria for sustainable bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hydraulic redistribution supplies a major water subsidy and improves water status of understory species in a longleaf pine ecosystem

Hydraulic redistribution (HR) is a common phenomenon in water-limited ecosystems; however, it remains unclear how the volume of water transported via HR compares to other components of the hydrologic budget and how HR influences water availability for understory plant communities. In this study, we investigate the absolute and relative magnitude of HR on a forest water budget and identify potential impacts of this water subsidy to understory plant communities. We scaled tree-level estimates of transpiration and HR of three common tree species naturally occurring in a longleaf pine woodland with plot-level measurements of basal area to determine their magnitude at the stand scale. We trenched plots containing understory vegetation but devoid of mature trees and their connected roots to exclude HR subsidies to understory plant species. We analysed soil water isotopes and assessed leaf water potential (Ψ L ) in trenched and control plots to determine if HR results in mixing of water among soil strata and improves understory plant moisture status. Water inputs from HR were equivalent to >30% of total rainfall for the site during the observation period and ~40% of total tree water uptake, depending on species. A stable isotope mixing model confirmed that soil water within HR-exposed plots was more similar to groundwater, whereas soil water within trenched plots was more similar to precipitation. Exclusion of HR via trenching decreased soil moisture and pre-dawn Ψ L for all understory species. These three lines of evidence suggest that HR from overstory trees redistributes a sizable portion of water from deeper to shallower soil profiles and that this water subsidy enhances understory plant water status.

54 ENVIRONMENTAL SCIENCES↗