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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 19 records

Delayed leaf greening involves a major shift in the expression of cytosolic and mitochondrial ribosomes to plastid ribosomes in the highly phosphorus-use-efficient Hakea prostrata (Proteaceae)

Abstract Background and aims Hakea prostrata (Proteaceae) is a highly phosphorus-use-efficient plant native to southwest Australia. It maintains a high photosynthetic rate at low leaf phosphorus (P) and exhibits delayed leaf greening, a convergent adaptation that increases nutrient-use efficiency. This study aimed to provide broad physiological and gene expression profiles across leaf development, uncovering pathways leading from young leaves as nutrient sinks to mature leaves as low-nutrient, energy-transducing sources. Methods To explore gene expression underlying delayed greening, we analysed a de novo transcriptome for H. prostrata across five stages of leaf development. Photosynthesis and respiration rates, and foliar pigment, P and nitrogen (N) concentrations were determined, including the division of P into five biochemical fractions. Key results Transcripts encoding functions associated with leaf structure generally decreased in abundance across leaf development, concomitant with decreases in foliar concentrations of 85% for anthocyanins, 90% for P and 70% for N. The expression of genes associated with photosynthetic function increased during or after leaf expansion, in parallel with increases in photosynthetic pigments and activity, much later in leaf development than in species that do not have delayed greening. As leaves developed, transcript abundance for cytosolic and mitochondrial ribosomal proteins generally declined, whilst transcripts for chloroplast ribosomal proteins increased. Conclusions There was a much longer temporal separation of leaf cell growth from chloroplast development in H. prostrata than is found in species that lack delayed greening. Transcriptome-guided analysis of leaf development in H. prostrata provided insight into delayed greening as a nutrient-saving strategy in severely phosphorus-impoverished landscapes.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of salinity on morphology, growth, and pigment profiles of Scenedesmus obliquus HTB1 under ambient air and elevated CO 2 (10 %) conditions

Certain microalgal species, such as Scenedesmus obliquus strain HTB1, thrive under high CO 2 concentrations, making them promising for carbon sequestration to mitigate climate change. Isolated from the Baltimore Inner Harbor, HTB1 grows faster with 10 % CO 2 than with ambient air. To investigate its responses to salinity and elevated CO 2 , two experiments were conducted. In the first, HTB1 was cultured at seven different salinities (0, 17.5, 20, 22.5, 25, 27.5, and 30 ppt) (parts per thousand) under ambient air. Higher salinity caused cell shrinkage, color changes from green to pale white, reduced pigments like zeaxanthin, lutein, and chlorophyll b, but increased canthaxanthin. Growth declined significantly above 22.5 ppt. The second experiment compared HTB1's response to salinity (0, 10, 20 ppt) under air and 10 % CO 2 . Cultures under 10 % CO 2 showed minimal color changes, while those under air shifted from green to brown, with salinity having less inhibitory effects on growth under elevated CO 2 . Interestingly, lutein and canthaxanthin levels rose with salinity in 10 % CO 2 . These findings indicate that elevated CO 2 mitigates salt stress in HTB1, reducing its impact on growth and promoting adaptive pigment changes. This study sheds light on how salinity and CO 2 interact to influence HTB1's morphology, growth, and pigment composition, enhancing our understanding of its resilience and potential applications.

20 FOSSIL-FUELED POWER PLANTS↗

Shifting from Fossil Fuel Reliance to Green Energy Sovereignty: Ute Mountain Ute Tribe

Self-determination has been an on-going effort for Native American people and gained much traction with the passing of The Energy Policy Act of 2005, which included the Indian Tribal Energy Development and Self-Determination Act. Congress passed this act to assist Native American tribes and Alaska Native villages with planning, development, and assistance to achieve their energy goals. The Ute Mountain Ute Tribe (UMUT) has relied on oil and natural gas for economic support the last 70 years. Burning fossil fuels, along with oil and gas development, decreases the quality of air and leads to increased greenhouse gas emissions. Subsequently, the burning of fossil fuels to produce energy is now more costly than many renewable energy sources, including solar photovoltaic (PV) systems. Environmental stewardship, along with the need to maintain revenue generation, has led UMUT’s efforts to achieve energy self-determinism employing PV and exploring other technology. In the past, the tribe completed a 1 megawatt PV project near Towaoc, Colorado, which serves as a case study on the tribe’s energy goals: a future where renewables will dominate their energy landscape. This paper explores UMUT’s past and on-going efforts toward energy independence and how it relates to the broader landscape of Native American energy sovereignty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Giant defect emission enhancement from ZnO nanowires through desulfurization process

Zinc oxide (ZnO) is a stable, direct bandgap semiconductor emitting in the UV with a multitude of technical applications. It is well known that ZnO emission can be shifted into the green for visible light applications through the introduction of defects. However, generating consistent and efficient green emission through this process is challenging, particularly given that the chemical or atomic origin of the green emission in ZnO is still under debate. In this work we present a new method, for which we coin term desulfurization, for creating green emitting ZnO with significantly enhanced quantum efficiency. Solution grown ZnO nanowires are partially converted to ZnS, then desulfurized back to ZnO, resulting in a highly controlled concentration of oxygen defects as determined by X-ray photoelectron spectroscopy and electron paramagnetic resonance. Using this controlled placement of oxygen vacancies we observe a greater than 40-fold enhancement of integrated emission intensity and explore the nature of this enhancement through low temperature photoluminescence experiments.

36 MATERIALS SCIENCE↗

Interplay of Topography, Fire History, and Climate on Interior Alaska Boreal Forest Vegetation Dynamics in the 21st Century: A Landsat Time-Series Analysis

This study investigates vegetation dynamics in boreal forests of Interior Alaska, focusing on topography, fire history, and climate influences. The study area includes Bonanza Creek Experimental Forest (BCEF) and surrounding region, categorized by topography (upland, floodplain, lowland) and fire history. Using Mann–Kendall trend and Theil–Sen slope analyses on Landsat-derived spectral metrics: Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR), we observed a shift from browning to greening trends, particularly in historically burned areas. The photosynthetic activity in burned upland converged with unburned areas ~30 years post-fire, coincident with a shift towards deciduous dominance during post-fire succession. Normalized Difference Moisture Index (NDMI) trends revealed a significant increase in vegetation moisture content across all topographies. We introduce Effective Seasonal Precipitation Index (ESPI), which combines prior-year annual precipitation with current-year spring snow depth. Its positive correlation with NDMI highlights its potential for monitoring vegetation moisture dynamics at the landscape scale. Furthermore, by correlating dendrochronology-based climate indices, we found strong correlation between NDMI and normalized Supplemental Precipitation Index (nSPI), across topographies. Overall, this research provides critical insights into how climate and fire influence interior boreal vegetation, highlighting the effects of increased precipitation, and topography on shaping differential vegetation responses across the landscape.

Google Earth Engine↗

Chemically sensitive fluorescence imaging of colliding microdroplets

Here, we present a simple optical capability for generating spatially resolved chemical concentration maps of mixing fluids using a chemically sensitive dye, 1-hydroxy-3,6,8-pyrenetrisulfonic acid, detected by planar laser induced fluorescence. To demonstrate an application of this capability, we investigate the collision and mixing of a pair of microdroplets in air. The two microdroplets are composed of different fluids, methanol and water, with the dye initially in the methanol droplet. When the droplets collide and mixing process develops, the fluorescence of the dye shifts from blue to green as the solvent environment changes. A series of spectral-temporal images of the collision and subsequent mixing are recorded, from which we extract the distribution of the two intermixing droplet species reflected in the spatially resolved dye spectra. Images reveal material transfer between droplets in both coalescing and non-coalescing droplet collisions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An integrated integral projection model ( IPM 2 ) to disentangle size‐structured harvest and natural mortality

Abstract Body size is one of the most important traits governing individual‐level demographic rates and modulating population‐level processes. Multiple size‐dependent demographic rates can simultaneously change population structure, so distinguishing their individual contributions to overall population dynamics remains a challenge. Disentangling size‐dependent harvest rates from other demographic rates is critical for assessing the impact of removal on populations of invasive species. Inference about invasive populations can be difficult, however, as observations are often collected opportunistically as part of removal programs, rather than experimentally designed. Yet accurate inference is essential for understanding the feasibility of population suppression and optimising management decisions. We develop an integrated integral projection model (IPM 2 ) that leverages the strengths of the integrated population model and integral projection model to enable inference about complex, size‐structured demographic rates from imperfect observations. We apply the IPM 2 in the context of invasive European green crab ( Carcinus maenas ), a species for which individual body size strongly regulates both the observation‐generating process and latent, population dynamics. The IPM 2 facilitates the distinct estimation of green crab size‐structured harvest and natural mortality rates, parameters for which no explicit data is collected and that are unidentifiable in component datasets of the integrated population model. The model represents how the green crab population changes over time, providing the first estimates of size‐structured abundance of this high‐priority species. By forecasting the stable size distribution and equilibrium population size under varying removal efforts, we demonstrate that extremely high levels of removal effort can reduce the equilibrium green crab population size. Yet these high mortality rates also shift the stable size distribution and increase the equilibrium abundance of smaller crabs, since size‐selective removal alters intraspecific interactions. The ecological outcome of this shift in size structure will be variable, as green crab size modulates only some of its interactions with other species. These results highlight the value of the IPM 2 framework for inferring complex population dynamics with information needs that outpace information in individual observational datasets, providing a path forward for accurate assessment of conservation programs.

Keller, Abigail G. [Department of Environment Scie↗

XANES analysis of phosphate glasses melted with Tb 4 O 7 and SnO: evaluating the impact of valence states on structural, thermal, and luminescent properties

Barium phosphate glasses were prepared with 0.5 mol% Tb 4 O 7 added alongside SnO up to 5 mol% with the purpose of evaluating the resulting terbium and tin oxidation states and their impact on glass structural, thermal, and luminescent properties. In this work, following material synthesis by melt-quenching, the composition-structure–property investigation was pursued encompassing measurements by X-ray diffraction (XRD), X-ray absorption near-edge spectroscopy (XANES), Raman spectroscopy, differential scanning calorimetry (DSC), dilatometry, and photoluminescence (PL) spectroscopy. While XRD confirmed the amorphous nature of the glasses, results from XANES indicated that terbium occurs as terbium(III) with a predisposition for tin to exist as tin(IV) which decreased at high SnO content. The structural as well as the thermal properties appeared to be mostly impacted by the presence of tin(IV). Specifically, glass depolymerization was indicated to be induced by Sn 4+ ions, and their concentration was observed to correlate with glass transition and softening temperatures. On the other hand, the tin(II) remnants were observed to exert an impact on the luminescent properties shifting light emission from the green towards the blue-green (cyan). It is indicated that Tb 4 O 7 reacting to produce Tb 2 O 3 supports the oxidation of tin(II) to tin(IV) which in turn dominates the physical properties. However, this was somewhat circumvented at the highest SnO content wherein tin(IV) appeared to be lower.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology

Abstract. Vegetation phenology plays a key role in controlling the seasonality of ecosystem processes that modulate carbon, water and energy fluxes between the biosphere and atmosphere. Accurate modelling of vegetation phenology in the interplay of Earth's surface and the atmosphere is thus crucial to understand how the coupled system will respond to and shape climatic changes. Phenology is controlled by meteorological conditions at different timescales: on the one hand, changes in key meteorological variables (temperature, water, radiation) can have immediate effects on the vegetation development; on the other hand, phenological changes can be driven by past environmental conditions, known as memory effects. However, the processes governing meteorological memory effects on phenology are not completely understood, resulting in their limited performance of vegetation phenology represented in land surface models. A deep learning model, specifically a long short-term memory network (LSTM), has the potential to capture and model the meteorological memory effects on vegetation phenology. Here, we apply the LSTM to model the vegetation phenology using meteorological drivers and high-temporal-resolution canopy greenness observations through digital repeat photography by the PhenoCam network. We compare a multiple linear regression model, a no-memory-effect LSTM model and a full-memory-effect LSTM model to predict the whole seasonal greenness trajectory and the corresponding phenological transition dates across 50 sites and 317 site years during 2009–2018, covering deciduous broadleaf forests, evergreen needleleaf forests and grasslands. Results show that the deep learning model outperforms the multiple linear regression model, and the full-memory-effect LSTM model performs better than the no-memory-effect model for all three plant function types (median R2 of 0.878, 0.957 and 0.955 for broadleaf forests, evergreen needleleaf forests and grasslands). We also find that the full-memory-effect LSTM model is capable of predicting the seasonal dynamic variations of canopy greenness and reproducing trends in shifting phenological transition dates. We also performed a sensitivity analysis of the full-memory-effect LSTM model to assess its plausibility, revealing its coherence with established knowledge of vegetation phenology sensitivity to meteorological conditions, particularly changes in temperature. Our study highlights that (1) multi-variate meteorological memory effects play a crucial role in vegetation phenology, and (2) deep learning opens up new avenues for improving the representation of vegetation phenological processes in land surface models via a hybrid modelling approach.

Geology↗

Exploring the Structural Behavior of Hydrophilic Diglycolamide Complexes with the Lanthanides and Actinides

In the ongoing effort to meet the anticipated rise in energy demand while maintaining the full-scale abandonment of natural gas and coal, a substantial shift in our considerations of green energy is required through the wider adoption of nuclear power. However, the advantages of nuclear power are hindered by the challenges of safely managing nuclear waste. Hydrophilic diglycolamides (DGA) ligands have been explored for use as stripping agents in various lanthanide and actinide partitioning processes. Additionally, the separation of lanthanide fission products and transplutonic actinides can serve multifaceted advantages in that the separation neutron poisoning rare earth element (REE) fission products from minor actinides from used nuclear fuel (UNF) can be mutually beneficial to the fundamental research behind REE separations and UNF separations. With this in mind, understanding the bonding differences between the Ln3+ and An3+ ions as a function of DGA structure, such as varying the alkyl groups on each of the amide functional groups, has an influence on the molecule’s selectivity and solubility and whose changes in molecular architecture also impact the radiolytic behavior of these molecules. As such, crystal structures of (Y3+, La-Lu3+, excl. Pm, Pu3+/4+, Am3+, Bk3+, and Cf3+) with hydrophilic diglycolamides show the systematic progression, and changes in coordination habits, as a function of a f-element ions. These coordination complexes see a consistent decrease in bond lengths and changes in the coordination environment while traversing across the f-elements, owing to the effects of the lanthanide contraction as well as local geometry around the metal centers. Direct comparisons of lanthanide with actinide DGA structures display both striking similarities in coordination with earlier actinides of Pu and Am, while later actinides of Bk and Cf display a complete breakdown of these observed trends. This work has also presented the rare opportunity to study homoleptic DGA compounds across multiple oxidation states have provided insight into their nuanced differences in structural chemistry.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Experimental warming differentially affects vegetative and reproductive phenology of tundra plants

Rapid climate warming is altering Arctic and alpine tundra ecosystem structure and function, including shifts in plant phenology. While the advancement of green up and flowering are well-documented, it remains unclear whether all phenophases, particularly those later in the season, will shift in unison or respond divergently to warming. Here, we present the largest synthesis to our knowledge of experimental warming effects on tundra plant phenology from the International Tundra Experiment. We examine the effect of warming on a suite of season-wide plant phenophases. Results challenge the expectation that all phenophases will advance in unison to warming. Instead, we find that experimental warming caused: (1) larger phenological shifts in reproductive versus vegetative phenophases and (2) advanced reproductive phenophases and green up but delayed leaf senescence which translated to a lengthening of the growing season by approximately 3%. Patterns were consistent across sites, plant species and over time. The advancement of reproductive seasons and lengthening of growing seasons may have significant consequences for trophic interactions and ecosystem function across the tundra.

54 ENVIRONMENTAL SCIENCES↗

Multiple horizontal gene transfer events have shaped plant glycosyl hydrolase diversity and function

Plant glycosyl hydrolases (GHs) play a crucial role in selectively breaking down carbohydrates and glycoconjugates during various cellular processes, such as reserve mobilization, pathogen defense, and modification/disassembly of the cell wall. In this study, we examined the distribution of GH genes in the Archaeplastida supergroup, which encompasses red algae, glaucophytes, and green plants. We identified that the GH repertoire expanded from a few tens of genes in early archaeplastidians to over 400 genes in modern angiosperms, spanning 40 GH families in land plants. Our findings reveal that major evolutionary transitions were accompanied by significant changes in the GH repertoire. Specifically, we identified at least 23 GH families acquired by green plants through multiple horizontal gene transfer events, primarily from bacteria and fungi. We found a significant shift in the subcellular localization of GH activity during green plant evolution, with a marked increase in extracellular-targeted GH proteins associated with the diversification of plant cell wall polysaccharides and defense mechanisms against pathogens. In conclusion, our study sheds light on the macroevolutionary processes that have shaped the GH repertoire in plants, highlighting the acquisition of GH families through horizontal transfer and the role of GHs in plant adaptation and defense mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

The SuperCam Instrument Suite on the NASA Mars 2020 Rover: Body Unit and Combined System Tests

The SuperCam instrument suite provides the Mars 2020 rover, Perseverance, with a number of versatile remote-sensing techniques that can be used at long distance as well as within the robotic-arm workspace. These include laser-induced breakdown spectroscopy (LIBS), remote time-resolved Raman and luminescence spectroscopies, and visible and infrared (VISIR; separately referred to as VIS and IR) reflectance spectroscopy. A remote micro-imager (RMI) provides high-resolution color context imaging, and a microphone can be used as a stand-alone tool for environmental studies or to determine physical properties of rocks and soils from shock waves of laser-produced plasmas. SuperCam is built in three parts: The mast unit (MU), consisting of the laser, telescope, RMI, IR spectrometer, and associated electronics, is described in a companion paper. The on-board calibration targets are described in another companion paper. Here we describe SuperCam’s body unit (BU) and testing of the integrated instrument. The BU, mounted inside the rover body, receives light from the MU via a 5.8 m optical fiber. The light is split into three wavelength bands by a demultiplexer, and is routed via fiber bundles to three optical spectrometers, two of which (UV and violet; 245–340 and 385–465 nm) are crossed Czerny-Turner reflection spectrometers, nearly identical to their counterparts on ChemCam. The third is a high-efficiency transmission spectrometer containing an optical intensifier capable of gating exposures to 100 ns or longer, with variable delay times relative to the laser pulse. This spectrometer covers 535–853 nm ( $105\text{--}7070~\text{cm}^{-1}$ Raman shift relative to the 532 nm green laser beam) with $12~\text{cm}^{-1}$ full-width at half-maximum peak resolution in the Raman fingerprint region. The BU electronics boards interface with the rover and control the instrument, returning data to the rover. Thermal systems maintain a warm temperature during cruise to Mars to avoid contamination on the optics, and cool the detectors during operations on Mars.Results obtained with the integrated instrument demonstrate its capabilities for LIBS, for which a library of 332 standards was developed. Examples of Raman and VISIR spectroscopy are shown, demonstrating clear mineral identification with both techniques. Luminescence spectra demonstrate the utility of having both spectral and temporal dimensions. Finally, RMI and microphone tests on the rover demonstrate the capabilities of these subsystems as well.

47 OTHER INSTRUMENTATION↗

Status and Trends in the U.S. Voluntary Power Market: 2023 Data

Voluntary green power, for this report, refers to renewable energy procurement by retail electricity customers above what is otherwise provided by load-serving entities. This report is part of an annual series of reports synthesizing trends in the U.S. voluntary green power market. In 2023, about 9.7 million retail electricity customers procured about 319 million megawatt-hours (MWh) of voluntary green power (Figure ES-1), representing a 17% increase over sales in 2022. Estimated voluntary green power market sales represented about 44% of non-hydropower renewable energy sales and about 8% of all U.S. retail electricity sales in 2023. Most of the remainder of U.S. renewable energy sales reflects renewable energy procured by load-serving entities to comply with state renewable energy mandates, also known as compliance-based procurement. The U.S. voluntary green power market is undergoing a clear shift toward long-term contracts, driven primarily by increasingly ambitious corporate renewable energy procurement targets.

2023↗

Robust fluorescent calcium coordination polymers as Cu 2+ sensors with high sensitivity and fast response

A three-dimensional (3D) and highly fluorescent calcium-based coordination polymer (Ca-CP) has been synthesized and structurally characterized. Furthermore, built on a strongly fluorescent (FL) chromophore ligand, [Ca(H 2 tcbpe)(H 2 O) 2 ] (1) (H 4 tcbpe = 4',4''',4''''',4'''''''-(ethene-1,1,2,2-tetrayl)tetrakis(([1,1'-biphenyl]-4-carboxylic acid))) is highly luminescent. Photoluminescence (PL) studies indicate that 1 undergoes a bathochromic shift in emission energy from blue to green color upon outgassing or under mechanic force. Notably, 1 exhibits selective FL sensing for Cu 2+ ions with a detection limit (LOD) of 0.064 ppm, far below the U.S. WHO and EPA standard for drinking water. Detailed investigation of the sensing mechanism reveals that uncoordinated COO– groups in 1 play a major role in recognizing Cu 2+ ions.

36 MATERIALS SCIENCE↗