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At least 1,531 records · Page 85
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NASA NTRS2007

Overview of the Results of the Organics PET Study of the Cometary Samples from Comet Wild 2 by the Stardust Mission

STARDUST is the first mission designed to bring samples back to Earth from a known comet. The captured samples were successfully returned to Earth on 15 Jan 2006, after which they were subjected to a preliminary examination by a number of teams of scientists from around the world. This abstract describes the efforts of the Organics Preliminary Examination Team (PET). More detailed discussions of specific analyses of the samples can be found in other papers presented at this meeting by individual members of the Organics PET (see the author list above for team members). The studied Wild 2 gas and dust samples were collected by impact onto aerogel tiles and Al foils when the spacecraft flew through the coma of 81P/Wild 2 on 2 Jan 2004 at a relative velocity of approx.6.1 kilometers per second. After recovery of the Sample Return Capsule (SRC) on 15 Jan 2006, the aerogel collector trays were removed in a clean room at JSC. After documentation of the collection, selected aerogel tiles and aluminum foils were removed and aerogel and cometary samples extracted for study.

Sandford, S. A.↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided many statistics on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution possible for capturing cloud initiation and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool, strategies to identify development stages from cloud tracks, and preliminary results that document cumulus lifecycle properties from satellite. The application of AHI 0.5-km reflectance has both strengths and limitations when attempting to track lifecycles of the smallest resolvable clouds. We show that by aggregating cloud tracks from a few case studies of CAMP2EX, we can discern differences in cloud lifetime and development according to ensembles selected from areas of interest. The results demonstrate an ability to quantify lifetimes and assess rates of change in cloud characteristics that are likely controlled by the surrounding environment and meteorology.

Cloud Tracking↗
NASA NTRS2015

The Far-Ultraviolet Spectra of "Cool" PG1159 Stars

We present a comprehensive study of Far Ultraviolet Spectroscopic Explorer (FUSE) spectra (912-1190 A) of two members of the PG1159 spectral class, which consists of hydrogen-deficient (pre-) white dwarfs with effective temperatures in the range T(sub eff) = 75000-200000 K. As two representatives of the cooler objects, we have selected PG1707+427 (T(sub eff) = 85000 K) and PG1424+535 (T(sub eff) = 110000 K), complementing a previous study of the hotter prototype PG1159-035 (T(sub eff) = 140000 K). The helium-dominated atmospheres are strongly enriched in carbon and oxygen, therefore, their spectra are dominated by lines from C III-IV and O III-VI, many of which were never observed before in hot stars. In addition, lines of many other metals (N, F, Ne, Si, P, S, Ar, Fe) are detectable, demonstrating that observations in this spectral region are most rewarding when compared to the near-ultraviolet and optical wavelength bands. We perform abundance analyses of these species and derive upper limits for several undetected light and heavy metals including iron-group and trans-iron elements. The results are compared to predictions of stellar evolution models for neutron-capture nucleosynthesis and good agreement is found.

Werner, K.↗
DOE OSTI2021

Geothermal Representation in Power System Models

Power system models generally fail to capture the range of characteristics geothermal resources provide and the value they potentially contribute to decarbonization and reliability of future electricity grids as firm, dispatchable, non-combustion power resources. This study reviews the results of power system modeling efforts to investigate geothermal deployment potential in the United States, including the U.S. DOE GeoVision analysis and ongoing modeling and analysis efforts to support planning and development of future grids with 100% renewable energy in California. Several themes are identified that could be implemented immediately to improve the accuracy of geothermal representation in power system models: consistency of model inputs, modeling of baseload and dispatchable geothermal resources, accurate valuation of grid services, improved representation of capacity factor, use of contemporary LCOE estimates, improved understanding of the evolution of geothermal value, and use of accurate resource potential constraints. Many of the models reviewed produced significantly different amounts of geothermal resource selection - even when modeling the same region and time period. This highlights the variability of inputs and assumptions among models, so creating a consistent set of geothermal inputs is a first step toward more accurate representation of geothermal in models. Research opportunities are identified that could help improve geothermal data inputs in modeling efforts, including analyses of historical data, sensitivity to model inputs, and comparative value of geothermal generators as baseload or dispatchable resources. Outcomes of such research can inform the geothermal community about how best to guide geothermal development toward wider deployment in support of future electricity grids through improved understanding of the evolution of geothermal value over time and the characteristics that contribute to that value.

capacity expansion models↗
NASA NTRS2002

Peptides at Membrane Surfaces and their Role in Prebiotic Evolution

Protocells had to transport ions and organic matter across membranes separating the interior of the cell from the environment, capture and utilize energy and transduce environmental signals. In a series of detailed, molecular-level computer simulations we show how these peptides in contact with membranes can acquire ordered structures and functions. We have investigated the stability of a simple alpha-helical peptide containing Leucine (L) and Serine (S) of the form (LSLLLSL)3 in a model membrane system. The parallel in-plane state is the most stable configuration. The transmembrane state is metastable, and about 15 kcal/mol is required to insert the peptide into the membrane. We investigated dimes of both (LSLLLSL)3 and glycophorin A, and show how the free energy of helix association can, at least partially, offset the free energy of insertion. We have also investigated the transmembrane pore of the influenza M2 protein. This aggregate of four identical alpha-helices, each built of 25 amino acids, forms an efficient and selective voltage-gated proton channel. Our simulations explain the gating mechanism, which can involve strands of hydrogen-bonded water through the pore or proton transfer through tautomerization of protein residues. The channel can be re-engineered to act as a simple proton pump.

Pohorille, Andrew↗
DOE OSTI2020

Balancing Water Sustainability and Productivity Objectives in Microalgae Cultivation: Siting Open Ponds by Considering Seasonal Water-Stress Impact Using AWARE-US

Microalgae have great potential as an energy crop. Scaling-up algal biofuel production in the United States (US) should be done with careful attention to water stress. This study evaluates the regional and seasonal water-stress impact of potential algae-pond deployments in the US. Three site-selection strategies focusing on biomass yield, water-use efficiency (WUE), and water-stress impact, respectively, are applied and compared to meet a US algae biomass production target of 30 million metric tons/yr ash-free dry weight, which converts to 20.8 billion L renewable diesel, via hydrothermal liquefaction. Ranking algae ponds based on biomass yield leads to freshwater consumption of 2.66 km3/yr, resulting in the highest water-stress impact (39.1 US equivalent km3). Under the WUE scenario, water consumption is reduced by 81%, but biomass yield is reduced by 12%. In contrast, adding a water-stress constraint to the biomass-yield ranking reduces water consumption by 50% and water-stress impact by 97%, with a small yield reduction (1.7%). Results show that pond location has a significant effect on water stress and that water stress is not proportional to water consumption or yield. Furthermore, capturing seasonal water patterns is critical for planning because sites in water-abundant regions can have short-term but significant water-stress impacts.

algae, Biofuel, water scarcity footprint, hydrothe↗
NASA NTRS1992

Self-organization via active exploration in robotic applications

We describe a neural network based robotic system. Unlike traditional robotic systems, our approach focussed on non-stationary problems. We indicate that self-organization capability is necessary for any system to operate successfully in a non-stationary environment. We suggest that self-organization should be based on an active exploration process. We investigated neural architectures having novelty sensitivity, selective attention, reinforcement learning, habit formation, flexible criteria categorization properties and analyzed the resulting behavior (consisting of an intelligent initiation of exploration) by computer simulations. While various computer vision researchers acknowledged recently the importance of active processes (Swain and Stricker, 1991), the proposed approaches within the new framework still suffer from a lack of self-organization (Aloimonos and Bandyopadhyay, 1987; Bajcsy, 1988). A self-organizing, neural network based robot (MAVIN) has been recently proposed (Baloch and Waxman, 1991). This robot has the capability of position, size rotation invariant pattern categorization, recognition and pavlovian conditioning. Our robot does not have initially invariant processing properties. The reason for this is the emphasis we put on active exploration. We maintain the point of view that such invariant properties emerge from an internalization of exploratory sensory-motor activity. Rather than coding the equilibria of such mental capabilities, we are seeking to capture its dynamics to understand on the one hand how the emergence of such invariances is possible and on the other hand the dynamics that lead to these invariances. The second point is crucial for an adaptive robot to acquire new invariances in non-stationary environments, as demonstrated by the inverting glass experiments of Helmholtz. We will introduce Pavlovian conditioning circuits in our future work for the precise objective of achieving the generation, coordination, and internalization of sequence of actions.

Ogmen, H.↗
DOE OSTI2026

Neural network potentials with effective charge separation for non-equilibrium dynamics of ionic solids: a ZnO case study

Developing neural network potentials (NNPs) accurate under non-equilibrium dynamics is challenging, as such systems require extensive sampling beyond equilibrium phases. Here we construct high-fidelity NNPs for zinc oxide (ZnO), a polymorphic ionic solid, using density functional theory (DFT) reference data. To efficiently capture transitional configurations, we combine enhanced-sampling molecular dynamics with empirical potentials, data distillation, and pretraining on short-range atomic energies (A-Train), followed by transfer learning with DFT-relabeled datasets. This hierarchical approach improves transferability across polymorphs and stress states. We further introduce effective charge separation, treating long-range Coulombic terms analytically while short-range residual interactions are learned by the NNP. The optimal effective charges fall in the range 0.5–1.0 q e , consistent with dielectric-screened values derived from formal charges but distinct from Bader estimates. Motivated by this observation, we propose a simple data-driven protocol in which effective charges are optimized by comparing DFT reference energies with explicit Coulomb calculations, without additional NNP training. This strategy improves accuracy and transferability in DFT-level predictions of energies, forces, and stress. Together, these results provide a practical charge-selection framework for robust NNP development in ionic solids, enabling reliable simulation of polymorphic phase transformations and non-equilibrium dynamics.

Chemistry↗
DOE OSTI2023

Electrochemical Reduction of Flue Gas Carbon Dioxide to Commercially Viable C2-C4 Products (Final Report)

This is the final scientific/technical report for a DOE project focused on the electrochemical conversion of CO 2 in non-aqueous solvents to novel products. Electrochemical reduction of CO 2 provides an attractive route to produce valuable fuels and chemicals that can simultaneously lower greenhouse gas emissions when powered by renewable electricity. While recent technological advances have shown the feasibility of industrial CO 2 electroreduction, many challenges remain to improve this technology and expand the list of economically viable products. The vast majority of electrochemical CO 2 reduction research has been conducted in aqueous media under neutral to alkaline conditions, leading to commonly reported products including carbon monoxide, formic acid, methane, methanol, ethylene, acetic acid, and ethanol. In comparison, non-aqueous media for CO 2 reduction has been underexplored but represents a possible avenue to yield new products and improved operating conditions. The aim of the project was to convert waste CO 2 in the form of flue gas to a multicarbon C2 - C4 chemical product in a reactor designed to achieve economically competitive values of current density and selectivity. The project strived to advance the technology readiness of an electrochemical CO 2 reduction process in alcohol solvents from the proof-of-concept stage to a device capable of meeting performance metrics for commercial viability. In the initial plan, the University of Louisville researchers were to focus on investigating the electrochemical process and improving the faradaic efficiency for novel C2 – C4 species, while also working on a parallel effort to build a practical electrolysis reactor to markedly increase the CO 2 reduction current density. The reactor development effort also aimed to engineer a dual-electrolyte feed strategy with non-aqueous catholyte and aqueous anolyte to promote water oxidation as the coupling anodic half-reaction to enable a sustainable and economical overall process. At the outset, the University of North Dakota was to investigate the feasibility of operating directly from coal-derived flue gas without separate capture and purification. The research team sought to determine impurity effects and test mitigation strategies, as well as engineer the gaseous feed system for high reactor tolerance to lower CO 2 concentration. In the last half year of the project, the focus was planned to shift to integrating the advances in the catalysis, electrochemical conditions, reactor design, and flue gas compatibility into a fully functional device and improve it for maximum current density and faradaic efficiency for C2 – C4 species. Knowledge of the full system components, constraints, and maximum performance was then to be used as the basis for a thorough technoeconomic analysis (TEA) and life cycle analysis (LCA) at the end of the project.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2003

Membrane-Based Functions in the Origin of Cellular Life

How simple membrane peptides performed such essential proto-cellular functions as transport of ions and organic matter across membranes separating the interior of the cell from the environment, capture and utilization of energy, and transduction of environmental signals, is a key question in protobiological evolution. On the basis of detailed, molecular-level computer simulations we investigate how these peptides insert into membranes, self-assemble into higher-order structures and acquire functions. We have studied the insertion of an a-helical peptide containing leucine (L) and serine (S) of the form (LSLLLSL)S into a model membrane. The transmembrane state is metastable, and approximately 15 kcal/mol is required to insert the peptide into the membrane. Investigations of dimers formed by (LSLLLSL)S and glycophorin A demonstrate how the favorable free energy of helix association can offset the unfavorable free energy of insertion, leading to self- assembly of peptide helices in the membrane. An example of a self-assembled structure is the tetrameric transmembrane pore of the influenza virus M2 protein, which is an efficient and selective voltage-gated proton channel. Our simulations explain the gating mechanism and provide guidelines how to reengineering the channel to act as a simple proton pump. In general, emergence of integral membrane proteins appears to be quite feasible and may be easier to envision than the emergence of water-soluble proteins.

Wilson, Michael A.↗
NASA NTRS2017

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗
DOE OSTI2026

Insights into mixing of non-isothermal multi-polymer melts for complex plastics recycling

Catalytic recycling or upcycling of plastics is often limited not by catalyst performance, but by transport, arising from highly viscous, non-Newtonian polymer melts. In this work, we develop a reactor-scale framework that integrates rheological measurements, constitutive modeling, computational fluid dynamics (CFD), and experiments to quantify mixing, heat transfer, and dispersion in surrogate hydrocarbon melts representing mixed plastics systems. Temperature- and shear rate-dependent viscosity of low-density polyethylene (LDPE) and high-density polyethylene (HDPE) is measured to create two surrogate polymers (PLD and PHD) that capture the dominant shear-thinning flow behavior while neglecting strong elastic effects, enabling tractable simulation of non-isothermal, polymer-melt mixing using a Carreau-Arrhenius generalized Newtonian framework. Three-dimensional CFD simulations are employed to evaluate impeller performance in PLD using mixing time, cavern volume, thermal uniformity, and interfacial area for regimes in which viscoelastic effects are not dominant. We show that magnetic stir bars commonly used in lab-scale studies produce large thermal gradients (~60 °C) and poor mixing, even under idealized power delivery and polymer flow conditions. In contrast, close-clearance anchor impellers achieve near-isothermal operation, reduce mixing times by up to 5×, and provide >90% active circulation volume. We further demonstrate that, at low pseudo-Deborah number (De*), motor power requirements can be predicted directly from shear rate-dependent rheology using the Carreau-Arrhenius framework, enabling rational selection of operating conditions. Extension to surrogate immiscible multi-polymer systems based on PLD and PHD shows that interfacial area is highly sensitive to operating conditions and impeller design, with coaxial anchor-turbine configurations enhancing dispersion by up to 4 × .

Close-clearance impellers↗
NASA NTRS1999

The Mars Pathfinder Mission and Science Results

Mars Pathfinder, the first low-cost, quick Discovery class mission to be completed, successfully landed on the surface of Mars on July 4, 1997, deployed and navigated a small rover, and collected data from 3 science instruments and 10 technology experiments. The mission operated on Mars for 3 months and returned 2.3 Gbits of new data, including over 16,500 lander and 550 rover images, 16 chemical analyses of rocks and soil, and 8.5 million individual temperature, pressure and wind measurements. The rover traversed 100 m clockwise around the lander, exploring about 200 square meters of the surface. The mission captured the imagination of the public, and garnered front page headlines during the first week. A total of about 566 million internet "hits" were registered during the first month of the mission, with 47 million "hits" on July 8th alone, making the Pathfinder landing by far the largest internet event in history at the time. Pathfinder was the first mission to deploy a rover on Mars. It carried a chemical analysis instrument, to characterize the rocks and soils in a landing area over hundreds of square meters on Mars, which provided a calibration point or "ground truth" for orbital remote sensing observations. The combination of spectral imaging of the landing area by the lander camera, chemical analyses aboard the rover, and close-up imaging of colors, textures and fabrics with the rover cameras offered the potential of identifying rocks (petrology and mineralogy). With this payload, a landing site in Ares Vallis was selected because it appeared acceptably safe and offered the prospect of analyzing a variety of rock types expected to be deposited by catastrophic floods, which enabled addressing first-order scientific questions such as differentiation of the crust, the development of weathering products, and the nature of the early Martian environment and its subsequent evolution. The 3 instruments and rover allowed seven areas of scientific investigation: the geology and geomorphology of the surface, mineralogy and geochemistry of rocks and soils, physical properties of surface materials, magnetic properties of airborne dust, atmospheric science including aerosols, and rotational and orbital dynamics of Mars. Scientists were assembled into 7 Science Operations Groups that were responsible for requesting measurements by the 3 instruments, rover and engineering subsystems for carrying out their scientific investigations and for analyzing the data and reporting on their findings. The spacecraft was launched on December 4, 1996 and had a 7 month cruise to Mars, with four trajectory correction maneuvers. The vehicle entered the atmosphere directly following cruise stage separation. Parachute deployment, heatshield and lander separation, radar ground acquisition, airbag inflation and rocket ignition all occurred before landing at 2:58 AM true local solar time (9:56:55 AM PDT). The lander bounced at least 15 times up to 12 in high without airbag rupture, demonstrating the robustness of this landing system. Reconstruction of the final landing sequence indicates that the parachute/backshel1/1ander was tilted due to a northwest directed wind and wind shear, which resulted in the lander bouncing about I km to the northwest and initially downhill about 20 m from where the solid rockets fired. Two anomalously bright spots located in the lander scene are likely the heatshield, which continued in a ballistic trajectory about 2 km downrange (west southwest), and the backshell/parachute, which stayed nearer to where the rockets fired. Unconnected disturbed soil patches in the scene indicate that the final few bounces of the lander were from the east-southeast and were followed by a gentle roll to the west before coming to rest on the base petal. The location of the lander away from where the solid rockets fired and considerations of the exhaust products used to inflate the airbags and their fate, indicate that the Pathfinder landing system is one of the cleanest designed leaving the local area essentially contaminant free. The radio signal from the low-=gain antenna was received at 11:34 AM PDT indicating a successful landing.

Golombek, M. P.↗
NASA NTRS2013

Daily MODIS 500 m Reflectance Anisotropy Direct Broadcast (DB) Products for Monitoring Vegetation Phenology Dynamics

Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily MODIS 500 m reflectance anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on short time scales, are less well served by remote sensing challenges and lack of anisotropy correction in satellite data sources. The daily MODIS 500 m reflectance anisotropy product is employed to retrieve daily vegetation indices (VI) of a 1 year period for an almond orchard in California and for a winter wheat field in northeast China, as well as a 2 year period for a deciduous forest region in New Hampshire, USA. Compared with the ground records from these regions, the VI trajectories derived from the cloud-free and atmospherically corrected MODIS Nadir BRDF (bidirectional reflectance distribution function) adjusted reflectance (NBAR) capture not only the detailed footprint and principal attributes of the phenological events (such as flowering and blooming) but also the substantial inter-annual variability. This study demonstrates the utility of the daily 500 m MODIS reflectance anisotropy DB product to provide daily VI for monitoring and detecting changes of the natural vegetation phenology as exemplified by study regions comprising winter wheat, almond trees, and deciduous forest.

Vegetation↗
DOE OSTI2020

Diversity in Photoprotection and Energy Balancing in Terrestrial and Aquatic Phototrophs

The evolution of oxygenic photosynthesis enabled organisms to use sunlight as an energy source, allowing them to colonize new niches. At the same time, life (as we know it) places severe constraints on photosynthesis. For example, the initial reactions of photosynthesis involve highly energetic intermediates that, if not controlled, can generate highly toxic side products (especially reactive oxygen species, ROS), that can damage other essential components of the organisms it powers. Photosynthesis must therefore be tightly regulated to balance the need for efficient energy conversion with the necessity of avoiding photodamage (Gust D, Kramer D, Moore A, Moore T, Vermaas W, Mater Res Bull 33:383–389, 2008). A related constraint on photosynthesis is the need to precisely balance how much energy is stored in ATP and NADPH to precisely meet biochemical demands. If this balancing does not occur, the system will fail, leading to photodamage (Kramer DM, Evans JR, Plant Physiol 155:70–78, 2011). Consideration of these requirements is essential for efforts to improve the efficiency of photosynthesis by introducing CO 2 concentrating mechanisms, altering metabolism or biosynthetic pathways to shunt energy to alternative products (Kramer DM, Evans JR, Plant Physiol 155:70–78, 2011). These balancing processes must be extremely robust to contend with the rapid and unpredictable fluctuations in environmental conditions and metabolic demands that occur in nature. A large body of work has come from model systems, especially terrestrial higher plants and the green alga Chlamydomonas reinhardtii, leading to a model for the regulation of light reactions that involves 1) sensing of the pH gradient component of the thylakoid proton motive force (pmf), and 2) the redox state of the plastoquinone- and stromal pools. Over the short term, these sensors trigger regulation of light capture by altering the activity of ATP synthase leading to adjustments in lumen pH, which fine tunes light capture through nonphotochemical quenching (NPQ) and control of electron flow by adjusting the rate of PQH 2 oxidation at the b 6 f complex. Simultaneously, this system controls the balance of ATP/NADPH by adjusting electron flux to linear and cyclic electron flow pathways to balance ATP/NADPH. This integrated “pmf paradigm” model explains much of the existing data on plants and green algae, but may not extend to other diverse organisms. This review considers how advances in our understanding of photosynthesis over the past 7–8 years, particularly in the discoveries of diverse biochemical/biophysical mechanisms in aquatic photosynthetic species, affects the view of energy balance, including the shunting of electrons to O 2 through the flavodiiron proteins (FLV), the plastid terminal oxidase, the dissipation of electric field by ion movements, and the activation of alternative electron sinks. Furthermore, we will introduce the basic model that has been developed for higher plant chloroplasts, then contrast these with selected aquatic systems, focusing on how the differences impact the needs to re-balance both energy input and its partitioning into energy currencies.

Kanazawa, Atsuko↗
DOE OSTI2025

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - Simulated Wave

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production using a single, simulated wave energy conversion device. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel Hydrogen. While the unit supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. For the wave energy, NLR used a wave energy converter model from PacWave. These devices can be equipped with accumulators and pressure relief values to smooth the power output by storing and releasing hydraulic energy. Using a peak power output of 10 MW, the model created two 25-minute profiles: one with and one without the accumulators and pressure relief valves. To down select the profile data from the native resolution of 20 Hz to 1 Hz, NLR took the mean of every 20 data points. NLR experimented with two simulated wave energy power plants: one that peaks at 10 MW, and one that peaks at 5 MW. These profiles were scaled for the physical 1.25 MW electrolyzer by multiplying the original profiles by one eighth and one quarter, respectively. The first profile matches the capacity rating of eight of the 1.25 MW electrolyzers, while the second matches four electrolyzers. Finally, NLR experimented with two settings for the electrolyzer power supply minimum and maximum current ramp rates (gain and slew): 200 and 400 amperes per second. The simulated profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wave electrolysis experiment and is formatted as follows: {technology}-{accumulator?}_{number of 1.25 MW electrolyzers connected}-{electrolyzer ramp rate in amperes/second} For instance, “wavePacWave-Noacc_4-400.zip” represents the 25 minute-long experiment using the PacWave’s wave energy converter model, equipped with no accumulator, connected to four 1.25-MW electrolyzers with their power supplies set to a maximum current ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power. An experiment, labeled “characterization_200.zip”, demonstrates the MC250 electrolyzer steady-state response with 30 minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all wave profiles combined into one dataset labeled "combined_wave_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis.

08 HYDROGEN↗
NASA NTRS2001

Evaluation Criteria for Solid Waste Processing Research and Technology Development

A preliminary list of criteria is proposed for evaluation of solid waste processing technologies for research and technology development (R&TD) in the Advanced Life Support (ALS) Program. Completion of the proposed list by current and prospective ALS technology developers, with regard to specific missions of interest, may enable identification of appropriate technologies (or lack thereof) and guide future development efforts for the ALS Program solid waste processing area. An attempt is made to include criteria that capture information about the technology of interest as well as its system-wide impacts. Some of the criteria in the list are mission-independent, while the majority are mission-specific. In order for technology developers to respond to mission-specific criteria, critical information must be available on the quantity, composition and state of the waste stream, the wast processing requirements, as well as top-level mission scenario information (e.g. safety, resource recovery, planetary protection issues, and ESM equivalencies). The technology readiness level (TRL) determines the degree to which a technology developer is able to accurately report on the list of criteria. Thus, a criteria-specific minimum TRL for mandatory reporting has been identified for each criterion in the list. Although this list has been developed to define criteria that are needed to direct funding of solid waste processing technologies, this list processes significant overlap in criteria required for technology selection for inclusion in specific tests or missions. Additionally, this approach to technology evaluation may be adapted to other ALS subsystems.

Levri, Julie A.↗
NASA NTRSDate not supplied

Europa Luminescence Microscope

The Europa Luminescence Microscope (ELM) is an automated fluorescence and dark-field mi-croscope designed to meet key objectives defined in the NASA Europa Lander Study Report, includ-ing the identification and characterization of morphological biosignatures. ELM’s heritage stems from a 2U cubesat fluorescence microscope, the Fluorescence Analysis for In-situ Research (FLAIR) im-ager, designed and built at NASA Ames Research Center, for the autonomous study of microbial bi-ology in low Earth orbit. For the ELM implementation, a sample is autonomously manipulated with a microfluidic system using in-line filter sets to capture successively smaller particles on 10, 1.0, and 0.1 µm pore-size filters for imaging. For darkfield imaging, ELM uses ultraviolet and visible light to image organic and inorganic structures with submicron resolution. The ability to detect structural and chemical biosignatures as small as 0.2 µm in size is achieved by imaging native fluorescence and us-ing fluorescence microscopy stains to identify key molecular and structural indicators of microbial life (proteins, lipids, nucleic acids). To excite fluorescence, ELM uses LEDs with wavelengths centered near 265, 370, 470, and 530 nm and five emission bands. The use of multiple excitation and emission wavelengths for native fluorescence imaging not only enables the detection of different molecular species, but also their rough classification. Excitation at 265 nm allows for the detection of smaller polyaromatic hydrocarbons (PAHs; 1-5 rings), aromatic amino acids, and proteins with little to no interference from mineral fluorescence, given proper emission band selection. 370 and 470 nm light excites increasingly larger PAH structures (e.g., coronene) and larger aromatic biomolecules that may be present (e.g., protective pigments). Similarly, inorganic fluorescence can be characterized and sep-arated from organic fluorescence, allowing the recognition and in some cases classification, of miner-als and other abiotic particles. ELM is based upon work supported by the NASA COLDTech and ICEE-2 programs.

Microscope↗