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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Green genes from blue greens: challenges and solutions to unlocking the potential of cyanobacteria in drug discovery

Cyanobacteria are prolific producers of biologically active compounds that are important in influencing ecology, behavior of interacting organisms, and as leads in drug discovery efforts. Here we discuss the challenges faced by all natural product researchers, especially those that focus on cyanobacteria, and then describe progress that has been made in these areas. We also propose some solutions, paths forward, and thoughts for consideration on these challenges.

Philmus, Benjamin↗
DOE OSTI2026

Will cities keep getting hotter? The interplay of urban expansion and greening reshapes future urban heat trajectories

Urban heat islands (UHIs) pose growing risks to public health, infrastructure, and resilience. While often assumed to intensify with urban growth, dynamic changes in urban expansion and vegetation greenness complicate UHI trajectories, which remain poorly understood. This study investigated the interplay of urban expansion and greenness change on UHI spatial profile across 36 Chinese megacities during 2003–2018 using multiple satellite products. We introduce a framework that classifies urban areas into four dynamic development pathways based on impervious surface area (ISA) and enhanced vegetation index (EVI) trends: urbanized-greening, urbanized-browning, urbanizing-greening (UingG), and urbanizing-browning (UingB). While most urbanized centers exhibited greening driven by targeted initiatives and urbanizing suburbs showed browning due to vegetation loss, about 30% urban areas showed the reverse pattern, revealing overlooked complexity in urban development. Urban expansion and browning strengthened UHI in suburban areas, whereas greening initiatives mitigated UHI in urban center and mitigated UHI enhancement in suburban areas. Slowed warming in urban centers together with accelerated warming in suburban areas flattened the temperature gradient between urban centers and suburbs. This dynamic expanded the spatial extent of elevated temperatures and reshaped the classic urban-to-rural UHI profile into a flatter form. In UingB areas, UHI intensification was jointly driven by increase in ISA, vegetation loss, and their interaction, while in UingG areas, EVI increases and a negative interaction together offset over half of the warming driven by urban expansion. These findings reveal that UHI evolution is not unidirectional but depends on localized urbanization and greening dynamics, offering pathways for strategic heat mitigation.

greening initiative↗
DOE OSTI2025

Extreme hydroclimates amplify the biophysical effects of advanced green-up in temperate China

Vegetation phenology modulates climate by altering energy and water exchange between the land and atmosphere. However, how extreme hydroclimatic conditions modify these phenology-climate feedbacks is still poorly understood. Here, in this study, we used a land–atmosphere-coupled Weather Research and Forecasting model to explore the impacts of advanced green-up on air temperature under different hydroclimate conditions across temperate China and to Mechanistic analysis elucidate the underlying biophysical mechanisms. By imposing a 14-day earlier green-up in line with recent satellite observations, we found that under mean climate conditions, an earlier leaf-out induces immediate surface cooling of 0.14 °C during green-up and a lagging 0.02 °C warming during senescence averaged for temperate China. Extremely humid conditions amplify the cooling effects to 0.18 °C during green-up, extending this cooling into the senescence period. Conversely, under extremely arid conditions, earlier green-up cools air temperature by 0.09 °C, and amplified senescence warming to 0.16 °C. Mechanism analysis revealed that evapotranspiration-dominated non-radiative processes drive immediate cooling during green-up while radiation and circulation process dominates the delayed but opposite warming/cooling effects during senescence in extremely arid/humid hydroclimates. Given the projected continuation of warming trends and increased frequency of extreme climatic events, it is imperative to incorporate the biophysical effects of vegetation phenology into local climate adaptation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Exploring the exact limits of the real-time equation-of-motion coupled cluster cumulant Green’s functions

In this paper, we analyze the properties of the recently proposed real-time equation-of-motion coupled-cluster (RT-EOM-CC) cumulant Green’s function approach [Rehr et al., J. Chem. Phys. 152, 174113 (2020)]. We specifically focus on identifying the limitations of the original time-dependent coupled cluster (TDCC) ansatz and propose an enhanced double TDCC ansatz, ensuring the exactness in the expansion limit. In addition, we introduce a practical cluster-analysis-based approach for characterizing the peaks in the computed spectral function from the RT-EOM-CC cumulant Green’s function approach, which is particularly useful for the assignments of satellite peaks when many-body effects dominate the spectra. Our preliminary numerical tests focus on reproducing, approximating, and characterizing the exact impurity Green’s function of the three-site and four-site single impurity Anderson models using the RT-EOM-CC cumulant Green’s function approach. The numerical tests allow us to have a direct comparison between the RT-EOM-CC cumulant Green’s function approach and other Green’s function approaches in the numerical exact limit.

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

A Unified Analytical Method Greenness Score ( uAMGS ) Quantifies How Microscopic Imaging Is Greener Than Conventional Liquid Chromatography

Green chemistry is a set of principles for assessing, developing, and implementing methods that are safer, more efficient, and less detrimental to the environment. The analytical method greenness score (AMGS) is one of many metrics that attempt to evaluate traditional liquid chromatography (LC) based on the energy consumption of the instrument and the safety, health risks, and environmental impact of the solvents employed. Unfortunately, in practice, the AMGS is primarily focused on traditional separation methods in the pharmaceutical industry and is not amenable to cutting-edge separation science, including miniaturization. To broaden this scope, the unified Analytical Method Greenness Score (uAMGS) is presented here, which clarifies and expands on the underlying mathematics and incorporates both dimensional and uncertainty analysis, enabling its application to a broader range of analytical techniques. The uAMGS is used to compare the greenness of two distinct methods: single-molecule microscopy (SMM) and high-performance liquid chromatography (HPLC), which were used to collect equivalent data. uAMGS determines that SMM is significantly greener than HPLC due primarily to decreased solvent consumption. Overall, the uAMGS should allow chemists ranging from undergraduates to industrial PhDs to assess the greenness of a wide range of separations.

chemical separations↗
DOE OSTI2025

Leaky ribosomal scanning enables tunable translation of bicistronic ORFs in green algae

Advances in sequencing technology have unveiled examples of nucleus-encoded polycistrons, once considered rare. Exclusively polycistronic transcripts are prevalent in green algae, although the mechanism by which multiple polypeptides are translated from a single transcript is unknown. Here, we used bioinformatic and in vivo mutational analyses to evaluate competing mechanistic models for translation of bicistronic mRNAs in green algae. High-confidence manually curated datasets of bicistronic loci from two divergent green algae, Chlamydomonas reinhardtii and Auxenochlorella protothecoides, revealed a preference for weak Kozak-like sequences for ORF 1 and an underrepresentation of potential initiation codons before the ORF 2 start codon, which are suitable conditions for leaky ribosome scanning to allow ORF 2 translation. We used mutational analysis in A. protothecoides to test the mechanism. In vivo manipulation of the ORF 1 Kozak-like sequence and start codon altered reporter expression at ORF 2, with a weaker Kozak-like sequence enhancing expression and a stronger one diminishing it. A synthetic bicistronic dual reporter demonstrated inversely adjustable activity of green fluorescent protein expressed from ORF 1 and luciferase from ORF 2, depending on the strength of the ORF 1 Kozak-like sequence. Our findings demonstrate that translation of multiple ORFs in green algal bicistronic transcripts is consistent with episodic leaky scanning of ORF 1 to allow translation at ORF 2. This work has implications for the potential functionality of upstream open reading frames (uORFs) found across eukaryotic genomes and for transgene expression in synthetic biology applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The Relationship of Hydrology in the Green River to Colorado Pikeminnow Populations

The Federally listed Colorado Pikeminnow (CP) (Ptychocheilus Lucius) has been declining in the Green River Basin over the last 20 years. Muth et al. (2000) recommended flows and temperatures to benefit endangered fish species downstream of Flaming Gorge Dam on the Green River. The recommendations identified a range of flows during the base flow period (flows that occur after the annual snowmelt runoff period, usually from early summer to the following spring) that were intended to benefit CP. The recommendations indicated that the mean flow for the summer–winter period should be established each year on the basis of anticipated hydrologic conditions, but adjustments could be made if hydrologic conditions change. Flow should gradually decline from peak flow to base flow, with the base flow reached by early to middle summer (depending on hydrologic conditions) and maintained through February. The rate of decline should depend on rates of decline in Yampa River flows and the recommended rates of decline for dam releases. No specific recommendations were made for base flow variation in Reach 1, but variation around the annual mean base flow should be restricted to achieve recommended levels of variation in Reach 2 (middle Green River) (Table 5.5 in Muth et al. 2000). Implementation of the flow and temperature recommendations served as the proposed action for an EIS on Flaming Gorge Dam operations. A Biological Assessment of the impacts on endangered species of implementing the recommendations was prepared and a Biological Opinion that called for development of a study plan to examine the effects of implementation. Projects to address this evaluation were identified in the Green River Study Plan and have been conducted since then. The purpose of the Study Plan was to identify and recommend to the Recovery Program those monitoring or research projects necessary for implementation and evaluation of the flow and temperature recommendations. Those projects included studies to evaluate the anticipated effects of implementing the recommendations (including potential adverse effects identified in the 2006 Biological Opinion) and studies to examine recognized uncertainties of the recommendations. A new recovery program summer base flow study plan was approved in September of 2020 to evaluate stable and elevated summer base flows below Flaming Gorge Dam intended to benefit CP spawning and rearing success. Anecdotal observations suggest CP production may have been higher in years prior to flow restrictions for endangered fish. Based on long-term CP monitoring data in the Green River, Bestgen and Hill (2016) concluded that CP would benefit from higher summer baseflows (1,700-3,000 ft 3 /sec) with flows above or below associated with lower abundance of age-0 CP. Therefore, flexibility in the ROD is currently being utilized to establish higher stable summer base flows in an attempt create more advantageous conditions for spawning and rearing CP. These fish recovery flows are restrictive to WAPA in the summer months, therefore it is necessary to conduct an analysis of historic river data relationships to CP abundance to better understand if the recommended fish flows (elevated and stable base flows) are necessary for fish recovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Optical image analysis for graphene layer detection: Enhanced green channel methodology

Graphene, a material of increasing research interest, requires accurate layer identification due to its sensitivity to layer count. Existing methods for graphene layer number identification are either time-consuming or of low accuracy, with high-accuracy methods often requiring expensive processes. This paper aims to address this challenge by proposing a cost-effective and efficient approach. Specifically, the current work highlights only the green channel—one of the three primary color channels (red, green, blue) that make up an optical image—from images of exfoliated graphene flakes for layer count identification. A linear regression is performed between pixel position and substrate green channel value, and this effect is subtracted from the entire optical image to mitigate background effects. By storing the range of green channel values for each type of flake (monolayer, bilayer, or tri-layer) based on a few images, we establish thresholds for identifying different types of layers in a particular setup. Additionally, our methodology allows for flexible threshold tuning using a single reference image, enabling adjustment to changes in detection setup such as illumination level, magnification, or microscope used. Finally, demonstrating high accuracy and flexibility, this methodology presents a suitable technique for graphene layer number identification without the need for large datasets or expensive instruments.

2D materials↗
DOE OSTI2025

Comprehensive techno-economic and life cycle greenhouse gases analysis of green ammonia production utilizing PV and wind energy: Jordan as a case study

Ammonia (NH 3 ) has emerged as a critical player in the global energy transition due to its potential as a low-carbon fuel. Conventional ammonia production methods, primarily through steam methane reforming, are significant contributors to global CO 2 emissions. This study investigates the potential of green ammonia production in Jordan by leveraging the country's abundant solar photovoltaic and wind energy resources. A comprehensive techno-economic and life cycle greenhouse gas analysis was conducted to compare green ammonia production with conventional grey and blue ammonia pathways. Here, the study utilized spatial mapping to assess renewable energy capacity factors across Jordan and optimized the integration of hybrid PV/wind systems with proton exchange membrane (PEM) electrolyzers. The results indicate that the levelized cost of green ammonia (LCOA) in Jordan varies between 900 USD/kg NH 3 and 2500 USD/kg NH 3 which is significantly higher than grey ammonia (similar to 360 USD/kg NH 3 ). Nevertheless, the carbon intensity of green ammonia production (between 0.1 kg CO 2eq /kg NH 3 and 0.5 kg CO 2eq /kg NH 3 ) is much lower than the grey ammonia (1.8 kg CO 2eq /kg NH 3 ). Finally, the results indicate that considering future reductions in capital costs and advancement in renewable energy systems and PEM electrolyzers as well as the ability to sell the co-product O 2 can reduce the LCOA by up to 92 % and make it competitive with grey ammonia.

Green Ammonia↗
DOE OSTI2024

Persistent global greening over the last four decades using novel long-term vegetation index data with enhanced temporal consistency

Advanced Very High-Resolution Radiometer (AVHRR) satellite observations have provided the longest global daily records from 1980s, but the remaining temporal inconsistency in vegetation index datasets has hindered reliable assessment of vegetation greenness trends. To tackle this, we generated novel global long-term Normalized Difference Vegetation Index (NDVI) and Near-Infrared Reflectance of vegetation (NIRv) datasets derived from AVHRR and Moderate Resolution Imaging Spectroradiometer (MODIS). We addressed residual temporal inconsistency through three-step post processing including cross-sensor calibration among AVHRR sensors, orbital drifting correction for AVHRR sensors, and machine learning-based harmonization between AVHRR and MODIS. After applying each processing step, we confirmed the enhanced temporal consistency in terms of detrended anomaly, trend and interannual variability of NDVI and NIRv at calibration sites. Our refined NDVI and NIRv datasets showed a persistent global greening trend over the last four decades (NDVI: 0.0008 yr -1 ; NIRv: 0.0003 yr -1 ), contrasting with those without the three processing steps that showed rapid greening trends before 2000 (NDVI: 0.0017 yr -1 ; NIRv: 0.0008 yr -1 ) and weakened greening trends after 2000 (NDVI: 0.0004 yr -1 ; NIRv: 0.0001 yr -1 ). These findings highlight the importance of minimizing temporal inconsistency in long-term vegetation index datasets, which can support more reliable trend analysis in global vegetation response to climate changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Earth's record-high greenness and its attributions in 2020

Terrestrial vegetation is a crucial component of Earth's biosphere, regulating global carbon and water cycles and contributing to human welfare. Despite an overall greening trend, terrestrial vegetation exhibits a significant inter-annual variability. The mechanisms driving this variability, particularly those related to climatic and anthropogenic factors, remain poorly understood, which hampers our ability to project the long-term sustainability of ecosystem services. Here, in this work, by leveraging diverse remote sensing measurements, we pinpointed 2020 as a historic landmark, registering as the greenest year in modern satellite records from 2001 to 2020. Using ensemble machine learning and Earth system models, we found this exceptional greening primarily stemmed from consistent growth in boreal and temperate vegetation, attributed to rising CO 2 levels, climate warming, and reforestation efforts, alongside a transient tropical green-up linked to the enhanced rainfall. Contrary to expectations, the COVID-19 pandemic lockdowns had a limited impact on this global greening anomaly. Our findings highlight the resilience and dynamic nature of global vegetation in response to diverse climatic and anthropogenic influences, offering valuable insights for optimizing ecosystem management and informing climate mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Green's Function Wind Turbine Induction Model That Incorporates Complex Inflow Conditions

ABSTRACT In this work, we develop a new analytical turbine induction model that can incorporate complex inflow conditions including cases where the wind velocity and temperature profiles can vary as functions of height. This induction model is derived from the linearized Navier–Stokes and leads to a second‐order ODE that can be solved using a Green's function formulation. The corresponding Green's function for several configurations are found including the infinite domain, semi‐infinite domain with ground plane, and a power law velocity inflow profile. The results of this approach are then compared with simulations of the turbine induction field using the AMR‐Wind CFD solver with a uniformly loaded actuator disk model. These comparisons show that the Green's function approach captures the centerline blockage, three‐dimensional blockage flow field, and streamwise velocity slow down, with very good agreement for lower thrust conditions and at larger distances away from rotor disk. The effects of shear on the turbine blockage were also compared using a power law inflow profile, and we show that this approach matches the CFD predictions for the cases considered.

17 WIND ENERGY↗
DOE OSTI2025

A Green’s function fast multipole method for computation of micromechanical fields in heterogeneous materials

Computation of micromechanical fields in heterogeneous materials is usually performed using either the finite element method or the Green’s function method based on FFTs. The finite element method allows for accurate discretization and for non-periodic boundary conditions but is computationally expensive. On the other hand, the FFT-based method is computationally efficient but requires discretization on a regular grid of hexahedral voxels. In this paper, a Green’s function method allowing for accurate discretization using tetrahedral elements and for non-periodic boundary conditions is proposed. The convolution is computed using the fast multipole method, which provides good accuracy even for low-order expansion due to the fast decay of interactions between elements. The proposed Green’s function fast multipole method is verified by comparison with analytical and FFT-based solutions. Furthermore, the computational time is analyzed and compared to the FFT-based method for non-periodic convolution. Finally, effective properties of an elastic polycrystalline microstructure containing thin intergranular cracks are computed and analyzed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Screening green solvents for multilayer plastic film recycling processes

Multilayer (ML) plastic films are essential packaging materials that help protect products from diverse external factors; however, only 5% of all ML films are recycled in the United States. Solvent-based technologies are a promising alternative for recycling ML films because they enable recovery of constituent polymer resins. For example, the Solvent Targeted Recovery and Precipitation (STRAPTM) process sequentially dissolves and separates polymer components using a series of targeted solvent washes. A crucial design aspect of this process is the impact of selected solvents on human health and on the environment. Here, this work introduces a computational framework that integrates molecular modeling, process modeling, techno-economic analysis (TEA), and life-cycle analysis (LCA) to quickly screen green solvents for solvent-based ML recycling processes. Initial screening for solvents based on selectivity is performed by estimating temperature-dependent solubilities using molecular-scale models. Subsequent screening uses basic estimates of energy use and octanol-water partition coefficients (logP) as key measures of health, safety, and environmental hazards. Detailed process modeling, TEA, and LCA are used on a reduced set of promising solvents identified in early screening steps to more accurately determine how solvent selection and associated operating conditions impact overall economics and environmental impacts. The framework is used for the identification of green solvents (from a database of 1,000 solvents) that separate an industrial ML film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET). Our analysis shows the effectiveness of the framework and reveals fundamental trade-offs between solvent greenness, solubility, and economics. Our work emphasizes the importance of taking a holistic systems view during solvent design and aims to inform the development of new processes for ML film recycling and the identification of new ML films that are easier to recycle.

economics↗
DOE OSTI2024

Identifying Green Solvent Mixtures for Bioproduct Separation Using Bayesian Experimental Design

Liquid–liquid extraction (LLE) is a widely used technique for the separation and purification of liquid-phase products with applications in various industries, including pharmaceuticals, petrochemicals, and renewable chemistry. A critical step in the design of an LLE process is the selection of appropriate solvents. This study presents a new methodology for identifying solvent mixtures for bioproduct separation using Bayesian experimental design (BED). Motivated by the need for environmentally friendly and effective separation methods, we address the challenge of selecting solvent systems that balance separation efficiency, selectivity, and environmental impact while also tackling the difficulty of separating multiple bioproducts using complex solvent systems. Our approach specifically seeks to predict product partition coefficients (log10 Kp values) as thermodynamic parameters underlying solvent selection. The iterative approach integrates Bayesian optimization with experimental measurements to guide solvent selection and leverages COSMO-RS simulations to enhance high-throughput experimentation. Using the design of solvent systems for the separation of lignin-derived aromatic products via centrifugal partition chromatography (CPC) as a case study, we show that within seven iterations/cycles of the methodology, we can identify new mixtures of green solvents that align with CPC design principles. Furthermore, these results demonstrate the efficacy of the BED framework in optimizing green solvent systems for complex separations, highlighting the potential of this method to advance the field of green chemistry and contribute to the development of sustainable industrial processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Geranylgeranylated-chlorophyll-protein complexes in lhl3 mutant of the green alga Chlamydomonas reinhardtii

Chlorophylls a and b (Chl a and b) are involved in light harvesting, photochemical reactions, and electron transfer reactions in plants and green algae. The core complexes of the photosystems (PSI and PSII) associate with Chl a, while the peripheral antenna complexes (LHCI and LHCII) bind Chls a and b. One of the final steps of Chl biosynthesis is the conversion of geranylgeranylated Chls (Chls GG ) to phytylated Chls by geranylgeranyl reductase (GGR). Here, we isolated and characterized a pale green mutant of the green alga Chlamydomonas reinhardtii that was very photosensitive and was unable to grow photoautotrophically. This mutant has a 16-bp deletion in the LHL3 gene, which resulted in the loss of LHL3 and GGR and accumulated only Chls GG . The lhl3 mutant cells grown in the dark accumulated PSII and PSI proteins at 25–50% of WT levels, lacked PSII activity, and retained a decreased PSI activity. The PSII and PSI proteins were depleted to trace amounts in the mutant cells grown in light. In contrast, the accumulation of LHCI and LHCII was unaffected except for LHCA3. Our results suggest that the replacement of Chls with Chls GG strongly affects the structural and functional integrity of PSII and PSI complexes but their associating LHC complexes to a lesser extent. Affinity purification of HA-tagged LHL3 confirmed the formation of a stable LHL3-GGR complex, which is vital for GGR stability. The LHL3-GGR complex contained a small amount of PSI complex assembly factors, suggesting a putative coupling between Chl synthesis and PSI complex assembly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Multiscale Neural Networks for Approximating Green’s Functions

Neural networks (NNs) have been widely used to solve partial differential equations (PDEs) in the applications of physics, biology, and engineering. One effective approach for solving PDEs with a fixed differential operator is learning Green’s functions. However, Green’s functions are notoriously difficult to learn due to their poor regularity, which typically requires larger NNs and longer training times. In this work, we address these challenges by leveraging multiscale NNs to learn Green’s functions. Through theoretical analysis using multiscale Barron space methods and experimental validation, we show that the multiscale approach significantly reduces the necessary NN size and accelerates training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Silicate coprecipitation reduces green rust crystal size and limits dissolution-precipitation during air oxidation

Green rusts (GR) are mixed-valence iron (Fe) hydroxides which form in reducing redox environments like riparian and wetland soils and shallow groundwater. In these environments, silicon (Si) can influence Fe oxides’ chemical and physical properties but its role in GR formation and subsequent oxidative transformation have not been studied starting at initial nucleation. Green rust sulfate [GR(SO 4 )] and green rust carbonate [GR(CO 3 )] were both coprecipitated from salts by base titration in increasing % mol Si (0, 1, 10, and 50). The minerals were characterized before and after rapid (24 h) aqueous air-oxidation by x-ray diffraction (XRD), scanning electron microscopy (SEM), Fe extended x-ray absorption fine structure spectroscopy (EXAFS), and N 2 -BET surface area. Results showed that only GR(SO4) or GR(CO3) was formed at every tested Si concentration. Increasing % mol Si caused decreased plate size and increased surface area in GR(CO3) but not GR(SO4). GR plate basal thickness was not changed at any condition indicating a lack of Si interlayering. Air oxidation of GR(SO4) at all % mol Si contents transformed by dissolution and reprecipitation into lepidocrocite and goethite, favoring ferrihydrite with higher % Si content. Air oxidation of GR(CO3) transformed into magnetite and goethite but increasing Si caused GR to oxidize while retaining its hexagonal plate structure via solid-state oxidation. Our results indicate that Si has the potential to cause GR to form in smaller particles and upon air oxidation, Si can either stabilize the plate structure or alter transformation to ferrihydrite.

36 MATERIALS SCIENCE↗