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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

ADEPT: A Pedagogical Framework for Integrating Agentic AI with Deterministic Scientific Workflows

The integration of Large Language Models (LLMs) into scientific research promises to accelerate discovery, yet a significant gap remains between the dynamic reasoning of Artificial Intelligence (AI) agents and the static, deterministic nature of canonical scientific workflows. This paper introduces ADEPT (Agentic Discovery and Exploration Platform for Tools), a reference architecture and pedagogical framework explicitly designed to bridge this gap. ADEPT's primary mission is to provide a transparent, "glass-box" environment where researchers and engineers can learn to effectively wrap established scientific software (e.g., BLAST, Nextflow pipelines) and compose it into reliable, agent-driven workflows. We describe its modular, multi-server architecture, which leverages the Model Context Protocol (MCP) for tool serving, LangGraph for robust agentic orchestration, and a secure nsjail-based sandbox for safe code execution. By prioritizing architectural clarity, safety, and modularity, ADEPT serves as an extensible blueprint for building trustworthy AI-augmented systems and fosters the collaborative development necessary to responsibly employ agentic AI for science. We provide practical examples of how to adapt and extend this framework, highlighting its utility in workforce development and AI-readiness capabilities across research and development projects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Clean Energy Co-Benefits: Air Quality, Health and Just Energy Transitions

Outdoor air pollution is a leading environmental risk factor and contributes to public health concerns. With assistance from the Department of State, NREL researchers supported the expansion of the Intervention Model for Air Pollution (InMAP) to Global InMAP model. This model offers a new approach to estimating the human health impacts caused by air pollutant emissions and how those impacts are distributed across populations around the world. Further research sponsored by the U.S. Agency for International Development (USAID) and executed by NREL and the University of Minnesota applied the Global InMAP Model for the first time in a study of the effects of renewable electricity deployment on air quality and human health in Southeast Asia. This brief details the inception, application, and novel approach of the Global InMAP model, and more broadly NREL's capabilities for air quality modeling and health effects co-benefits analyses in the context of just energy transitions.

air quality↗
DOE OSTI2024

Identification and characterization of a skin microbiome on Caenorhabditis elegans suggests environmental microbes confer cuticle protection

ABSTRACT In the wild, C. elegans are emersed in environments teeming with a veritable menagerie of microorganisms. The C. elegans cuticular surface serves as a barrier and first point of contact with their microbial environments. In this study, we identify microbes from C. elegans natural habitats that associate with its cuticle, constituting a simple “skin microbiome.” We rear our animals on a modified CeMbio, mCeMbio, a consortium of ecologically relevant microbes. We first combine standard microbiological methods with an adapted micro skin-swabbing tool to describe the skin-resident bacteria on the C. elegans surface. Furthermore, we conduct 16S rRNA gene sequencing studies to identify relative shifts in the proportion of mCeMbio bacteria upon surface-sterilization, implying distinct skin- and gut-microbiomes. We find that some strains of bacteria, including Enterobacter sp. JUb101 , are primarily found on the nematode skin, while others like Stenotrophomonas indicatrix JUb19 and Ochrobactrum vermis MYb71 are predominantly found in the animal’s gut. Finally, we show that this skin microbiome promotes host cuticle integrity in harsh environments. Together, we identify a skin microbiome for the well-studied nematode model and propose its value in conferring host fitness advantages in naturalized contexts. IMPORTANCE The genetic model organism C. elegans has recently emerged as a tool for understanding host–microbiome interactions. Nearly all of these studies either focus on pathogenic or gut-resident microbes. Little is known about the existence of native, nonpathogenic skin microbes or their function. We demonstrate that members of a modified C. elegans model microbiome, mCeMbio, can adhere to the animal's cuticle and confer protection from noxious environments. We combine a novel micro-swab tool, the first 16S microbial sequencing data from relatively unperturbed C. elegans , and physiological assays to demonstrate microbially mediated protection of the skin. This work serves as a foundation to explore wild C. elegans skin microbiomes and use C. elegans as a model for skin research.

16S RNA↗
DOE OSTI2021

Chapter 6: Economic Development: Renewables, Sustainable Economies, & Carbon Offsets

This chapter reviews economic development issues and opportunities that Tribes face in the age of climate change. It includes summaries pertaining to Tribal histories and trauma, harmful federal policies and subsequent land tenure issues, and the surge of economic sovereignty through renewable energy development on Tribal lands, including carbon offset markets. Recommendations are offered to reinforce and expedite Tribal economic self-determination on Tribal lands in the context of climate change. The chapter opens with the narrative of the Ute Mountain Ute Tribe of southwest Colorado, describing how this Tribe developed a large-scale solar economic development project to reduce their Tribal energy bills and decrease their dependence on fossil fuel usage. A researched overview of Economic Development as it relates to Tribes and climate change follows these narratives, beginning with the Key Messages and Recommendation that the authors have identified.

climate change↗
DOE OSTI2025

Enhancing building resilience in cold climates: Integrating heat pump technologies with renewable energy

As electrification advances and Cold Climate Heat Pump technology progresses, ensuring grid stability becomes increasingly critical for effective heating in cold climates. However, natural disasters, especially during winter, pose significant threats to grid stability, impacting the reliability of air-source heat pumps. Despite these challenges, the integration of renewable energy sources and storage solutions in heating systems has not been extensively studied within the context of resilience. Here, this paper delves into the literature on renewable-powered heat pumps to assess their potential in enhancing building resilience in U.S. cold climate zones, which are particularly susceptible to extreme weather and grid disruptions. By leveraging renewable sources—solar, geothermal, and water—in conjunction with heat pump technology and supported by thermal or battery storage, this approach aims to provide a dependable solution for maintaining indoor heating during grid failures. Our analysis begins with a review of various renewable energy sources suitable for heat pumps, followed by an exploration of their application in cold climate regions across the U.S., and discussions on potential integration strategies with heat pump systems. This study highlights the advantages and suitability of solar irradiance and geothermal resources, emphasizing the importance of tailored, site-specific assessments to maximize energy efficiency and resilience. Additionally, it outlines the economic and environmental considerations necessary for implementing such systems and identifies potential challenges and areas for future research to facilitate the broader integration of renewable energy in heating solutions for enhanced resilience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Quasi-stationary Planetary Scale Waves in Modern Climate Models

We evaluate climate model simulations of geopotential height at the largest space-time scales, considering the first Fourier components (in longitude) of long-term climatological means. Quasi-stationary planetary scale waves emerge from this analysis. Variations of these waves are important components of climate change, for example associated with regional drought. Systematic examination of their long-term climatology provides context for understanding their evolution in time. We compare four reanalysis datasets with “historical runs” from the latest version of the Coupled Model Intercomparison Project (CMIP) and find general agreement, but we also identify model errors outside the range of both observational uncertainty and the uncertainty implied by interannual variability. Errors in wave phase have possible implications for climate model projections of regional climate and of shifting weather patterns. One model in the set we examine, originally created nearly 20 years before the others, exhibits noticeably greater errors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Nitrosamine decomposition

The disclosure provides methods and systems for decreasing nitrosamine content, e.g., in the context of non-aqueous solvent systems. It includes a method including receiving a non-aqueous solvent system and contacting the non-aqueous solvent system with a composition including one or more alkoxides to give a treated solvent system having a nitrosamine content that is lower than the starting nitrosamine content. Similarly, it includes a system including a first unit configured to remove undesirable components from a gas stream; a second unit holding a composition including one or more alkoxides, and a conduit to connect these units.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ecosystem service benefits to water users from perennial biomass production

We report although many agree that a transition to renewable energy sources is needed to avoid the climate consequences of continued reliance on fossil sources, price is a barrier. For renewable energy sources, including bioenergy, penetrating energy markets depends on lowering prices to compete with the price of fossil sources, but the tools used in decision making, such as supply curves, exclude non-market benefits from ecosystem services. Here, we extend the economic concept of an economic supply curve to account for ecosystem services co-produced with perennial biomass. We developed three new types of supply curves to visualize the increased supply of biomass (‘sustainable supply’) with sufficient water-quality benefits to offset biomass production costs. Using these tools, we show that the value of water-quality improvements could significantly reduce the break-even price of perennial feedstocks if it were available to farmers. In the most optimistic case, nearly half of potential biomass supply in a large tributary of the Mississippi river basin carried water purification value exceeding the cost of biomass production. Furthermore, adding the value to swimmers and waders offset production cost for over 90% of potential supply. Simulated benefits were context specific. For example, total value for water drinkers peaked at an intermediate level of fertilizer application. Geographically, benefits were highest in the eastern portion of the river basin. This research shows where the sustainable supply is needed and can generate value; the next step is to match this supply with credit buyers. Efforts to internalize the values of ecosystem services into biomass prices could help to meet Biden administration targets to meet 100% of sustainable aviation fuels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Aerosol Optical Properties as Part of the Long-Term Aerosol Measurements in Puerto Rico (AOP-LAMP) Field Campaign Report

The University of Puerto Rico-Rio Piedras Campus (UPR-RP) has been measuring aerosol optical, chemical, and microphysical properties at Cape San Juan (CSJ, also known as CPR) since 2004. This site has also hosted several intensive field campaigns, with context provided by the long-term measurements. Hurricane Maria largely destroyed the station on September 20, 2017, forcing a cessation of the measurements. The scientific focus of this intensive operational period was to use a U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) aerosol shelter to enable the resumption of long-term aerosol measurements. This AMF shelter is now the main aerosol shelter for CSJ operations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Defined synthetic microbial communities colonize and benefit field-grown sorghum

The rhizosphere constitutes a dynamic interface between plant hosts and their associated microbial communities. Despite the acknowledged potential for enhancing plant fitness by manipulating the rhizosphere, the engineering of the rhizosphere microbiome through inoculation has posed significant challenges. These challenges are thought to arise from the competitive microbial ecosystem where introduced microbes must survive, and the absence of adaptation to the specific metabolic and environmental demands of the rhizosphere. Here, in this study, we engineered a synthetic rhizosphere community (SRC1) with the anticipation that it would exhibit a selective advantage in colonizing the host Sorghum bicolor, thereby potentially fostering its growth. SRC1 was assembled from bacterial isolates identified either for their potential role in community cohesion through network analysis or for their ability to benefit from host-specific exudate compounds. The growth performance of SRC1 was assessed in vitro on solid media, in planta under gnotobiotic laboratory conditions, and in the field. Our findings reveal that SRC1 cohesion is most robust when cultivated in the presence of the plant host under laboratory conditions, with lineages being lost from the community when grown either in vitro or in a native field setting. We establish that SRC1 effectively promotes the growth of both above- and below-ground plant phenotypes in both laboratory and native field contexts. Furthermore, in laboratory conditions, these growth enhancements correlate with the transcriptional dampening of lignin biosynthesis in the host. Collectively, these results underscore the potential utility of synthetic microbial communities for modulating crop performance in controlled and native environments alike.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The Sustainability Index: a new tool to breed for reduced greenhouse-gas emissions intensity in Australian dairy cattle

Context The Australian dairy industry has a target to reduce greenhouse-gas (GHG) emissions intensity by 30% between 2015 and 2030. At the animal level, apart from nutritional modifications and other management practices, selecting animals that emit less GHG can be a cost-effective and long-term strategy. Given the world’s demand for protein is increasing, selecting for animals with lower GHG emissions per unit of production, i.e. emissions intensity, is a realistic approach that addresses the key issue of emissions reduction while maintaining farm productivity. Aim To develop a selection index for Australian dairy cattle to breed for reduced emissions intensity. Methods The Sustainability Index was built based on the existing Balanced Performance Index (BPI) but placed greater emphasis on production, survival, health and feed efficiency. Key results In August 2022, DataGene released the Sustainability Index that can be used by dairy farmers to select animals with lower environmental footprints. Compared with BPI, the weights for protein, fat, survival, mastitis resistance and feed efficiency increased by 2.6-, 1.4-, 2.8-, 1.3- and 3.8-fold respectively. It is expected that with the use of the Sustainability Index, emissions intensity will be reduced by 7.64%, 8.96% and 5.52% respectively in Holstein, Jersey and Red breeds by 2050, compared with the 2015 level. The corresponding values when selecting for BPI were 6.34%, 7.91% and 5.23% respectively. However, the trade-off in BPI when using the Sustainability Index will be AUD0.79, AUD0.83, AUD0.22 per cow per year for Holstein, Jersey and Red breeds respectively. Conclusions The current profit index BPI has contributed to reduction in emissions intensity. To enhance the rate of improvement in emissions intensity, the Sustainability Index can be used with minimal impacts on profit. Implications To breed for lower emissions intensity, farmers can select animals with high Sustainability Index values that are published on DataVat (datavat.com.au) and the Good Bulls App. To lower gross emissions, combinations of additional measures such as management of diet, adjustment to animal numbers, management of stored manure, and appropriate use of carbon neutral fertiliser, renewable fuels and energy, will need to be adopted on farms.

Agriculture↗
DOE OSTI2021

Carbon Calculator for Land Use and Land Management Change from Biofuels Production (CCLUB)

The Carbon Calculator for Land Use and Land Management Change from Biofuels Production (CCLUB) has been developed as an integral part of Argonne National Laboratory’s Greenhouse Gases, Regulated Emissions, and Energy use in Technologies (GREET) model to analyze greenhouse gas (GHG) emissions from land use change (LUC) and land management change (LMC) in the context of overall biofuel life-cycle analysis (LCA). CCLUB relies on i) biofuel production scenarios, ii) LUC and LMC scenarios, and iii) emission factors (EF) to generate GHG emissions of LUC and LMC for biofuel production in gram carbon dioxide equivalent (CO2e) per MJ of fuel produced. Figure 1 outlines the calculations and data sources within CCLUB that are described in this document and Table 1 identifies where these data are stored and used within CCLUB, which is built in Microsoft Excel.

09 BIOMASS FUELS↗
DOE OSTI2024

Animal displacement from marine energy development: Mechanisms and consequences

For marine wave and tidal energy to successfully contribute to global renewable energy goals and climate change mitigation, marine energy projects need to expand beyond small deployments to large-scale arrays. However, with large-scale projects come potential environmental effects not observed at the scales of single devices and small arrays. One of these effects is the risk of displacing marine animals from their preferred habitats or their migration routes, which may increase with the size of arrays and location. Many marine animals may be susceptible to some level of displacement once large marine energy arrays are increasingly integrated into the seascape, including large migratory animals, non-migratory pelagic animals with large home ranges, and benthic and demersal mobile organisms with more limited ranges, among many others. Yet, research around the mechanisms and effects of displacement have been hindered by the lack of clarity within the international marine energy community regarding the definition of displacement, how it occurs, its consequences, species of concern, and methods to investigate the outcomes. This review paper leveraged lessons learned from other industries, such as offshore development, to establish a definition of displacement in the marine energy context, explore which functional groups of marine animals may be affected and in what way, and identify pathways for investigating displacement through modeling and monitoring. In the marine energy context, we defined displacement as the outcome of one of three mechanisms (i.e., attraction, avoidance, and exclusion) triggered by an animal's response to one or more stressors acting as a disturbance, with various consequences at the individual through population levels. The knowledge gaps highlighted in this study will help the regulatory and scientific communities prepare for mitigating, observing, measuring, and characterizing displacement of various animals around marine energy arrays in order to prevent irreversible consequences.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Multicriteria Measures to Assess the Sustainability of Diets: A Systematic Review

Abstract Context Assessing the overall sustainability of a diet is a challenging undertaking requiring a holistic approach capable of addressing the multicriteria nature of this concept. Objective The aim was to identify and summarize the multicriteria measures used to assess the sustainability characteristics of diets reported at the individual level by healthy adults. Data Sources Articles were identified via PubMed, Scopus, and Web of Science. The search strategy consisted of key words and MeSH terms, and was concluded in September 2022, covering references in English, Spanish, and Portuguese. Data Extraction This systematic review followed the PRISMA guidelines. The search identified 5663 references, from which 1794 were duplicates. Two reviewers independently screened the titles and abstracts of each of the 3869 records and the full-text of the 144 references selected. Of these, 7 studies met the inclusion criteria. Data Analysis A total of 6 multicriteria measures were identified: 3 different Sustainable Diet Indices, the Quality Environmental Costs of Diet, the Quality Financial Costs of Diet, and the Environmental Impact of Diet. All of these incorporated a health/nutrition dimension, while the environmental and economic dimensions were the second and the third most integrated, respectively. A sociocultural sustainability dimension was included in only 1 of the measures. Conclusion Despite some methodological concerns in the development and validation process of the identified measures, their inclusion is considered indispensable in assessing the transition towards sustainable diets in future studies. Systematic Review Registration PROSPERO registration no. CRD42022358824.

Rei, Mariana (ORCID:0000000189453708)↗
DOE OSTI2022

Biorefinery upgrading of herbaceous biomass to renewable hydrocarbon fuels, Part 1: Process modeling and mass balance analysis

Process simulation has long been a well-established tool to track key operational, design, and mass and energy balance metrics for pre-commercial technologies such as advanced lignocellulosic biofuels. While tools such as this are well-documented in the public literature around 2nd-generation cellulosic ethanol technologies (which have been scaled up to commercial deployment to some degree over the past decade), such models and analysis information remain more sparse for more complex biorefinery pathways focused on producing drop-in hydrocarbon fuels and blend-stocks, particularly regarding information required to support air emissions or other environmental analysis. In this work, we summarize key details for an established "design case" modeling the conversion of herbaceous lignocellulosic biomass into a renewable diesel hydrocarbon blend-stock based on a representative lipid pathway from oleaginous yeast. The process is based on a biochemical deconstruction and upgrading approach utilizing deacetylation and dilute acid pretreatment, followed by enzymatic hydrolysis, fermentation, and catalytic upgrading of hydrolysate sugars to fuels. We provide key mass and energy balance outputs from the process models, with accompanying stream tables and component-level flowrates. A total of 12 model scenarios are presented spanning two feedstocks, three biorefinery scales, and two processing approaches for the lignin/residual solids waste streams. This "Part 1" manuscript presents the resulting impacts across the 12 cases on fuel yields and key output streams, focused here on direct biorefinery air emissions for selected components including CO 2 as well as sulfur (SOx) and nitrogen oxides (NOx). In the context of cleaner production, the latter focus on selected biorefinery air emission outputs establishes an initial baseline estimate and accompanying framework of the model cases, upon which an accompanying "Part 2" study will build to refine the values for these and other air pollutants across these scenarios, also considering mitigation options to comply with applicable regulatory standards. We also highlight further optimization opportunities based on potential tradeoffs identified here between air emissions versus life-cycle greenhouse gas profiles attributed to the disposition of lignin/residual solids.

09 BIOMASS FUELS↗
DOE OSTI2023

Deriving spatially explicit direct and indirect interaction networks from animal movement data

Abstract Quantifying spatiotemporally explicit interactions within animal populations facilitates the understanding of social structure and its relationship with ecological processes. Data from animal tracking technologies (Global Positioning Systems [“GPS”]) can circumvent longstanding challenges in the estimation of spatiotemporally explicit interactions, but the discrete nature and coarse temporal resolution of data mean that ephemeral interactions that occur between consecutive GPS locations go undetected. Here, we developed a method to quantify individual and spatial patterns of interaction using continuous‐time movement models (CTMMs) fit to GPS tracking data. We first applied CTMMs to infer the full movement trajectories at an arbitrarily fine temporal scale before estimating interactions, thus allowing inference of interactions occurring between observed GPS locations. Our framework then infers indirect interactions—individuals occurring at the same location, but at different times—while allowing the identification of indirect interactions to vary with ecological context based on CTMM outputs. We assessed the performance of our new method using simulations and illustrated its implementation by deriving disease‐relevant interaction networks for two behaviorally differentiated species, wild pigs ( Sus scrofa ) that can host African Swine Fever and mule deer ( Odocoileus hemionus ) that can host chronic wasting disease. Simulations showed that interactions derived from observed GPS data can be substantially underestimated when temporal resolution of movement data exceeds 30‐min intervals. Empirical application suggested that underestimation occurred in both interaction rates and their spatial distributions. CTMM‐Interaction method, which can introduce uncertainties, recovered majority of true interactions. Our method leverages advances in movement ecology to quantify fine‐scale spatiotemporal interactions between individuals from lower temporal resolution GPS data. It can be leveraged to infer dynamic social networks, transmission potential in disease systems, consumer–resource interactions, information sharing, and beyond. The method also sets the stage for future predictive models linking observed spatiotemporal interaction patterns to environmental drivers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Solvent-driven aqueous separations for hypersaline brine concentration and resource recovery

Solvent-driven separation processes can extract water and high-value minerals from high salinity or contaminated brines, simultaneously reducing the environmental impact of brine disposal and enabling resource recovery. The efficient dewatering of hypersaline brines is essential for the sustainable minimal and zero liquid discharge processing of industrial wastewaters. Fractional crystallization can selectively extract ions from contaminated waste streams, allowing critical materials to be recycled, including transition and lanthanide metals required for renewable energy generation and storage. Mass transfer in solvent-driven water extraction occurs across a liquid–liquid interface, eliminating the scaling and fouling of membrane and heat exchanger surfaces and limiting the need for extensive pretreatment. Solvent-driven fractional crystallization can leverage sequential treatment and control of process conditions to rapidly recover salts without requiring evaporation of water. Despite promising applications, the principles and potential of solvent-driven aqueous separations remain poorly understood. This critical review explores the opportunities presented by solvent-based aqueous separations from the molecular to process scale, evaluating the chemistry of solvation and system design in the broader context of desalination, resource recovery, water softening, and mineral production.

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

Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process‐Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process-based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data-constrained representation of the sterile triploid Miscanthus (IL clone) within the process-based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam-derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO 2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field-measured biomass. Building on the calibrated operating state, parameter-response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post-calibration GPP R 2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R 2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

ecosys↗