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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 OSTI2026

Outcomes of PAX sapiens-Supported Global Wildlife Data Sharing Conferences for Enhanced One Health Security (GWDSC)

Across two consecutive Global Wildlife Data Sharing Conferences supported by PAX sapiens—Year 1 (May 2024) at Pacific Northwest National Laboratory and Year 2 (2025) in Ciudad Real, Spain—the initiative converted wildlife data sharing from aspiration into operational reality, producing measurable impacts in platform development, data mobilization, standards harmonization, and international partnership formation. The conferences addressed a critical gap in global health security: while 75% of emerging infectious diseases affect both humans and animals and over 60% originate in wildlife, wildlife health surveillance has historically lagged behind human and agricultural sectors due to fragmented databases, inconsistent terminology, uneven capacity, and limited cross-border coordination. By convening practitioners, government agencies, international organizations, academic institutions, and NGOs, the GWDSC catalyzed trust-based relationships and practical workflows that enable earlier detection, better risk assessment, and more effective prevention of threats at the wildlife–domestic animal–human–environment interface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Optimization of COMPASS-U Support Structure

The global support structure for Compass Upgrade (COMPASS-U) employs many bolted and pinned components to improve the manufacturability of the whole structures. This is a departure from other designs used for highly loaded tokamaks, like Alcator C-Mod which used large forgings. Modeling of the numerous connections and interfaces was a challenge. This article will describe how to optimize the C-frame support structure with the goal to eliminate differential displacements at those interfaces and, importantly, minimize toroidal mutual displacement at the sliding joint of the toroidal field (TF) coils. The global support structure consists of 16 C-frames, and it can be simplified as a 1/8th cyclic symmetry model due to the eight vertical rods mounting that connect bottom CS and PF1-3 assemblies to the C-frames. Structure variants with different connection webs between two neighboring C-frames have been analyzed. The preloading of bolts can be split into several preload substeps to simulate the real assembly process of the COMPASS-U support structure. Additionally, the TF crown and the wedge plate can be further improved to become a solid part to better hold the TF coils.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Applying Compression-Based Metrics to Seismic Data in Support of Global Nuclear Explosion Monitoring

The analysis of seismic data for evidence of possible nuclear explosion testing is a critical global security mission that relies heavily on human expertise to identify and mark seismic signals embedded in background noise. To assist analysts in making these determinations, we adapted two compression distance metrics for use with seismic data. First, we demonstrated that the Normalized Compression Distance (NCD) metric can be adapted for use with waveform data and can identify the arrival times of seismic signals. Then we tested an approximation for the NCD called Sliding Information Distance (SLID), which can be computed much faster than NCD. We assessed the accuracy of the SLID output by comparing it to both the Akaike Information Criterion (AIC) and the judgments of expert seismic analysts. Our results indicate that SLID effectively identifies arrival times and provides analysts with useful information that can aid their analysis process.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

N 2 Onet: a global collaborative network facilitating advances in measurement, modeling, and mitigation of agricultural soil nitrous oxide emissions

Nitrogen (N) fertilizer supports global food production, but its use and overuse drive emissions of nitrous oxide (N 2 O), a potent and long-lived greenhouse gas. Understanding the drivers of N 2 O fluxes remains elusive, making it difficult to predict emissions in time and space and to develop and evaluate ways to lower emissions through management. Major scientific uncertainties underlying the understanding of the drivers of N 2 O fluxes identified in a workshop of N 2 O emissions experts include poor process-based understanding of controls on soil N 2 O emissions in the field; insufficient data to reduce uncertainty in N 2 O budgets from the field to regional scales, including N 2 O emission measurements and importantly, field-scale N balances; and high uncertainty in model predictions of soil N 2 O emissions across environmental and management conditions. To reduce these uncertainties, we present the concept of N 2 Onet, a global collaborative initiative to accelerate advances in N 2 O measurement, analyses, and mitigation. N 2 Onet will serve as an observational network of supersites with multi-scale measurements; a database hub for N 2 O flux and ancillary data; and a catalyst for community building, information sharing, and training. By coalescing and coordinating the global community of researchers, N 2 Onet will provide a roadmap for reducing N 2 O emissions from agriculture worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Global and regional hydrological impacts of global forest expansion

Abstract. Large-scale reforestation, afforestation, and forest restoration schemes have gained global support as climate change mitigation strategies due to their significant carbon dioxide removal (CDR) potential. However, there has been limited research into the unintended consequences of forestation from a biophysical perspective. In the Community Earth System Model version 2 (CESM2), we apply a global forestation scenario, within a Paris Agreement-compatible warming scenario, to investigate the land surface and hydroclimate response. Compared to a control scenario where land use is fixed to present-day levels, the forestation scenario is up to 2 °C cooler at low latitudes by 2100, driven by a 10 % increase in evaporative cooling in forested areas. However, afforested areas where grassland or shrubland are replaced lead to a doubling of plant water demand in some tropical regions, causing significant decreases in soil moisture (∼ 5 % globally, 5 %–10 % regionally) and water availability (∼ 10 % globally, 10 %–15 % regionally) in regions with increased forest cover. While there are some increases in low cloud and seasonal precipitation over the expanded tropical forests, with enhanced negative cloud radiative forcing, the impacts on large-scale precipitation and atmospheric circulation are limited. This contrasts with the precipitation response to simulated large-scale deforestation found in previous studies. The forestation scenario demonstrates local cooling benefits without major disruption to global hydrodynamics beyond those already projected to result from climate change, in addition to the cooling associated with CDR. However, the water demands of extensive forestation, especially afforestation, have implications for its viability, given the uncertainty in future precipitation changes.

Environmental Sciences & Ecology↗
DOE OSTI2026

Sustainable Critical Minerals: Mining, Production, and Legacy

Critical minerals (CMs) are required in renewable energy systems, electric vehicles, electronics, and national defense. Global demand has increased rapidly due to energy and digital transitions, and the United States has become increasingly reliant on vulnerable supply chains. Geological scarcity, trade barriers, environmental hurdles, and processing challenges impede domestic CM production growth. Emerging strategies, including circular economy practices and advanced sustainable mining and processing techniques, can mitigate supply chain and economic risks. To advance these approaches, consistent research priorities, policy revisions, and technology investments are required to develop a resilient CM supply. Doing so with a focus on sustainability goals can simultaneously advance domestic economic and technological goals while limiting environmental impacts and supporting global environmental goals.

biomining↗
DOE OSTI2021

A Comparative Techno-Economic Analysis of Renewable Methanol Synthesis Pathways from Biomass and CO2: Preprint

Global demand for methanol as both a chemical precursor and a fuel additive is rising. At the same time, numerous sustainable methanol production pathways are under development which, if commercialized, could present significant environmental benefits over traditional methanol synthesis pathways. There is a need to harmonize the analyses of sustainable pathways using a consistent techno-economic approach to evaluate the potential for commercialization of various pathways. This analysis considers economic and environmental factors critical to market acceptance of three sustainable pathways versus a commercial baseline. We suggest that biomass gasification to methanol represents a near-term viable pathway with high technology readiness level and commercially competitive market price. However, long-term solutions should consider CO2 electrolysis pathways which offer further improvements in sustainability metrics to support global decarbonization efforts.

biomass↗
DOE OSTI2025

Efficient secretion of a plastic degrading enzyme from the green algae Chlamydomonas reinhardtii

Abstract Plastic pollution has become a global crisis, with microplastics contaminating every environment on the planet, including our food, water, and even our bodies. In response, there is a growing interest in developing plastics that biodegrade naturally, thus avoiding the creation of persistent microplastics. As a mechanism to increase the rate of polyester plastic degradation, we examined the potential of using the green microalgaChlamydomonas reinhardtiifor the expression and secretion of PHL7, an enzyme that breaks down post-consumer polyethylene terephthalate (PET) plastics. We engineeredC. reinhardtiito secrete active PHL7 enzyme and selected strains showing robust expression, by using agar plates containing a polyester polyurethane (PU) dispersion as an efficient screening tool. This method demonstrated the enzyme’s efficacy in degrading ester bond-containing plastics, such as PET and bio-based polyurethanes, and highlights the potential for microalgae to be implemented in environmental biotechnology. The effectiveness of algal-expressed PHL7 in degrading plastics was shown by incubating PET with the supernatant from engineered strains, resulting in substantial plastic degradation, confirmed by mass spectrometry analysis of terephthalic acid formation from PET. Our findings demonstrate the feasibility of polyester plastic recycling using microalgae to produce plastic-degrading enzymes. This eco-friendly approach can support global efforts toward eliminating plastic in our environment, and aligns with the pursuit of low-carbon materials, as these engineered algae can also produce plastic monomer precursors. Finally, this data demonstratesC. reinhardtiicapabilities for recombinant enzyme production and secretion, offering a “green” alternative to traditional industrial enzyme production methods.

Science & Technology - Other Topics↗
DOE OSTI2024

Efficient secretion of a plastic degrading enzyme from the green algae Chlamydomonas reinhardtii

AbstractPlastic pollution has become a global crisis, with microplastics contaminating every environment on the planet, including our food, water, and even our bodies. In response, there is a growing interest in developing plastics that biodegrade naturally, thus avoiding the creation of persistent microplastics. As a mechanism to increase the rate of polyester plastic degradation, we examined the potential of using the green microalgaChlamydomonas reinhardtiifor the expression and secretion of PHL7, an enzyme that breaks down post-consumer polyethylene terephthalate (PET) plastics. We engineeredC. reinhardtiito secrete active PHL7 enzyme and selected strains showing robust expression, by using agar plates containing a polyester polyurethane (PU) dispersion as an efficient screening tool. This method demonstrated the enzyme’s efficacy in degrading ester bond-containing plastics, such as PET and bio-based polyurethanes, and highlights the potential for microalgae to be implemented in environmental biotechnology. The effectiveness of algal-expressed PHL7 in degrading plastics was shown by incubating PET with the supernatant from engineered strains, resulting in substantial plastic degradation, confirmed by mass spectrometry analysis of terephthalic acid (TPA) formation from PET. Our findings demonstrate the feasibility of polyester plastic recycling using microalgae to produce plastic-degrading enzymes. This eco-friendly approach can support global efforts toward eliminating plastic in our environment, and aligns with the pursuit of low-carbon materials, as these engineered algae can also produce plastic monomer precursors. Finally, this data demonstratesC. reinhardtiicapabilities for recombinant enzyme production and secretion, offering a “green” alternative to traditional industrial enzyme production methods.Graphical Abstract

Molino, João Vitor Dutra (ORCID:0000000324759807)↗
DOE OSTI2021

A comparative techno-economic analysis of renewable methanol synthesis from biomass and CO 2 : Opportunities and barriers to commercialization

Global demand for methanol as both a chemical precursor and a fuel additive is rising. At the same time, numerous renewable methanol production pathways are under development, which, if commercialized, could provide significant environmental benefits over traditional methanol synthesis pathways. However, it is difficult to compare technologies at different maturity levels, with differing feedstocks, and with significant differences in overall process design. Thus, there is a need to harmonize the analyses of renewable pathways using a consistent techno-economic approach to evaluate the potential for commercialization of various pathways. This analysis uses a novel cross-comparison method to assess near-term and long-term viability of both low- and high-maturity level technologies. Furthermore, the techno-economic assessment considers cost factors critical to market acceptance combined with carbon- and energy-efficiency assessments of three renewable pathways compared with a commercial baseline. We find that biomass gasification to methanol represents a near-term viable pathway with a high technology readiness level and commercially competitive market price. If cost-reducing technological improvements can be realized and scaled up in the CO 2 electrolysis pathways, the potential for higher carbon efficiencies may help drive market adoption of these more modular, direct conversion pathways in future markets as they present an opportunity to better support global decarbonization efforts through efficient waste carbon utilization.

09 BIOMASS FUELS↗
DOE OSTI2020

Data-driven learning of nonlocal physics from high-fidelity synthetic data

A key challenge to nonlocal models is the analytical complexity of deriving them from first principles, and frequently their use is justified a posteriori. Here, we extract nonlocal models from data, circumventing these challenges and providing data-driven justification for the resulting model form. Extracting data-driven surrogates is a major challenge for machine learning (ML) approaches, due to nonlinearities and lack of convexity — it is particularly challenging to extract surrogates which are provably well-posed and numerically stable. Our scheme not only yields a convex optimization problem, but also allows extraction of nonlocal models whose kernels may be partially negative while maintaining well-posedness even in small-data regimes. To achieve this, based on established nonlocal theory, we embed in our algorithm sufficient conditions on the non-positive part of the kernel that guarantee well-posedness of the learnt operator. These conditions are imposed as inequality constraints to meet the requisite conditions of the nonlocal theory. We demonstrate this workflow for a range of applications, including reproduction of manufactured nonlocal kernels; numerical homogenization of Darcy flow associated with a heterogeneous periodic microstructure; nonlocal approximation to high-order local transport phenomena; and approximation of globally supported fractional diffusion operators by truncated kernels.

42 ENGINEERING↗
DOE OSTI2024

Engineering the Novel Extremophile Alga Chlamydomonas pacifica for High Lipid and High Starch Production as a Path to Developing Commercially Relevant Strains

Microalgae offer a compelling platform for the production of commodity products, due to their superior photosynthetic efficiency, adaptability to nonarable lands and nonpotable water, and their capacity to produce a versatile array of bioproducts, including biofuels and biomaterials. However, the scalability of microalgae as a bioresource has been hindered by challenges such as costly biomass production related to vulnerability to pond crashes during large-scale cultivation. This study presents a pipeline for the genetic engineering and pilot-scale production of biodiesel and thermoplastic polyurethane precursors in the extremophile species Chlamydomonas pacifica. This extremophile microalga exhibits exceptional resilience to high pH (>11.5), high salinity (up to 2% NaCl), and elevated temperatures (up to 42 °C). Initially, we evolved this strain to also have a high tolerance to high light intensity (>2000 μE/m 2 /s) through mutagenesis, breeding, and selection. We subsequently genetically engineered C. pacifica to significantly enhance lipid production by 28% and starch accumulation by 27%, all without affecting its growth rate. We demonstrated the scalability of these engineered strains by cultivating them in pilot-scale raceway ponds and converting the resulting biomass into biodiesel and thermoplastic polyurethanes. This study showcases the complete cycle of transforming a newly discovered species into a commercially relevant commodity production strain. This research underscores the potential of extremophile algae, including C. pacifica, as a key species for the burgeoning sustainable bioeconomy, offering a viable path forward in mitigating environmental challenges and supporting global bioproduct demands.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Getting Hydrogen to the Gigaton Scale

Due to its ability to perform clean, efficient processes, hydrogen has long been promoted as the energy carrier of the future, but recent activity and advances suggest a tipping point has been reached as hydrogen is now being recognized by much of the world for its unique capabilities to strongly support global efforts in achieving climate neutrality. The coming decades will require a massive increase in the amount of hydrogen used in the energy system as well as a transition from largely thermochemical to predominantly electrochemical processes involving hydrogen. For this to happen, hydrogen will need to globally approach the gigaton-scale on an annual basis. Thus, before hydrogen can fully achieve its potential, challenges that need to be addressed include achieving scale and further research and development (R&D) advances.

climate neutrality↗
DOE OSTI2024

Optimizing Carbon Capture, Transport, and Storage: Overcoming Challenges with Machine Learning and Cost-Benefit Analysis

Carbon Capture, Utilization, and Storage (CCUS) is a critical strategy for reducing CO₂ emissions and mitigating climate change. However, its widespread deployment faces numerous challenges across the capture, transport, and storage phases. These challenges include the technical complexity of predicting subsurface behaviors during CO₂ injection, ensuring long-term storage integrity, optimizing transportation networks, and balancing the economic and environmental trade-offs. Addressing these issues requires an integrated approach combining advanced subsurface modeling with system-level analyses to assess costs, risks, and benefits. This presentation provides an overview of studies conducted by the National Energy Technology Laboratory (NETL) to tackle these challenges. NETL’s efforts encompass cutting-edge research in subsurface fluid behavior machine learning predictions, alongside the development of innovative tools for system optimization and economic evaluation. By bridging technical expertise and strategic analysis, NETL aims to advance the deployment of CCUS technologies to support global decarbonization efforts. Presented at the Carnegie Mellon University CEE IESS Student Seminar October 4, 2024.

Shih, Chung Yan↗
DOE OSTI2024

Environmental life-cycle analysis of hydrogen technology pathways in the United States

Hydrogen is a zero-carbon energy carrier with potential to decarbonize industrial and transportation sectors, but its life-cycle greenhouse gas (GHG) emissions depend on its energy supply chain and carbon management measures (e.g., carbon capture and storage). Global support for clean hydrogen production and use has recently intensified. In the United States, Congress passed several laws that incentivize the production and use of renewable and low-carbon hydrogen, such as the Bipartisan Infrastructure Law (BIL) in 2021 and the Inflation Reduction Act (IRA) in 2022, which provides tax credits of up to $3/kg depending on the carbon intensity of the produced hydrogen. A comprehensive life-cycle accounting of GHG emissions associated with hydrogen production is needed to determine the carbon intensity of hydrogen throughout its value chain. In the United States, Argonne’s R&D GREET ® (Greenhouse Gases, Regulated emissions, and Energy use in Technologies) model has been widely used for hydrogen carbon intensity calculations. This paper describes the major hydrogen technology pathways considered in the United States and provides data sources and carbon intensity results for each of the hydrogen production and delivery pathways using consistent system boundaries and most recent technology performance and supply chain data.

Elgowainy, Amgad↗
DOE OSTI2020

The Performance of a Spectral Wave Model at Predicting Wave Farm Impacts

For renewable ocean wave energy to support global energy demands, wave energy converters (WECs) will likely be deployed in large numbers (farms), which will necessarily change the nearshore environment. Wave farm induced changes can be both helpful (e.g., beneficial habitat and coastal protection) and potentially harmful (e.g., degraded habitat, recreational, and commercial use) to existing users of the coastal environment. It is essential to estimate this impact through modeling prior to the development of a farm, and to that end, many researchers have used spectral wave models, such as Simulating WAves Nearshore (SWAN), to assess wave farm impacts. However, the validity of the approaches used within SWAN have not been thoroughly verified or validated. Herein, a version of SWAN, called Sandia National Laboratories (SNL)-SWAN, which has a specialized WEC implementation, is verified by comparing its wave field outputs to those of linear wave interaction theory (LWIT), where LWIT is theoretically more appropriate for modeling wave-body interactions and wave field effects. The focus is on medium-sized arrays of 27 WECs, wave periods, and directional spreading representative of likely conditions, as well as the impact on the nearshore. A quantitative metric, the Mean Squared Skill Score, is used. Results show that the performance of SNL-SWAN as compared to LWIT is “Good” to “Excellent”.

environmental impacts↗
DOE OSTI2020

Foreward: Advancing the U.S. Offshore Renewable Energy Industry through Marine Renewable and Offshore Wind Energy Development

Foreward to special issue of MTSJ Journal: Energy security … it’s what everyone is talking about, and for good reason. Against the backdrop of a changing climate in which nearly two-thirds of electricity generation is credited to fossil fuels (IEA, 2019a), countries around the world are diversifying their energy portfolios, suppliers, and energy routes to reduce vulnerabilities to energy security risks (U.S. Chamber of Commerce, 2020). Energy security concerns are related to fuel supply chains, electricity generation, transmission, distribution, energy market functionality, and energy system resiliency (DOE, 2017). These concerns demonstrate the need for well-functioning and competitive energy markets and diverse sources and routes of energy supply (DOE, 2017). In addition, environmental protection, efficiency and infrastructure improvements, energy innovation, emergency response, and resilience are also needed (DOE, 2017). Renewable energy generation is, and will continue to be, a major contributor in energy portfolio diversification, which will reduce reliance on foreign energy sources (IEA, 2019b; Aslantürk & Kiprizli, 2020) and support global decarbonization (Sims, 2004; Rockström et al., 2017; Arabzadeh et al., 2020).

marine renewable energy (MRE), offshore wind energ↗