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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Carbon-negative production of acetone and isopropanol by gas fermentation at industrial pilot scale

Many industrial chemicals that are produced from fossil resources could be manufactured more sustainably through fermentation. In this work, we describe the development of a carbon-negative fermentation route to producing the industrially important chemicals acetone and isopropanol from abundant, low-cost waste gas feedstocks, such as industrial emissions and syngas. Using a combinatorial pathway library approach, we first mined a historical industrial strain collection for superior enzymes that we used to engineer the autotrophic acetogen Clostridium autoethanogenum. Next, we used omics analysis, kinetic modeling and cell-free prototyping to optimize flux. Finally, we scaled-up our optimized strains for continuous production at rates of up to ~3 g/L/h and ~90% selectivity. Life cycle analysis confirmed a negative carbon footprint for the products. Unlike traditional production processes, which result in release of greenhouse gases, our process fixes carbon. These results show that engineered acetogens enable sustainable, high-efficiency, high-selectivity chemicals production. We expect that our approach can be readily adapted to a wide range of commodity chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Interfacial solvation-structure regulation for stable Li metal anode by a desolvation coating technique

Rechargeable lithium (Li) metal batteries face challenges in achieving stable cycling due to the instability of the solid electrolyte interphase (SEI). The Li-ion solvation structure and its desolvation process are crucial for the formation of a stable SEI on Li metal anodes and improving Li plating/stripping kinetics. This research introduces an interfacial desolvation coating technique to actively modulate the Li-ion solvation structure at the Li metal interface and regulate the participation of the electrolyte solvent in SEI formation. Through experimental investigations conducted using a carbonate electrolyte with limited compatibility to Li metal, the optimized desolvation coating layer, composed of 12-crown-4 ether-modified silica materials, selectively displaces strongly coordinating solvents while simultaneously enriching weakly coordinating fluorinated solvents at the Li metal/electrolyte interface. This selective desolvation and enrichment effect reduce solvent participation to SEI and thus facilitate the formation of a LiF-dominant SEI with greatly reduced organic species on the Li metal surface, as conclusively verified through various characterization techniques including XPS, quantitative NMR, operando NMR, cryo-TEM, EELS, and EDS. The interfacial desolvation coating technique enables excellent rate cycling stability (i.e., 1C) of the Li metal anode and prolonged cycling life of the Li||LiCoO 2 pouch cell in the conventional carbonate electrolyte (E/C 2.6 g/Ah), with 80% capacity retention after 333 cycles.

42 ENGINEERING↗
DOE OSTI2016

A Comparison Study of Offshore Wind Support Structures with Monopiles and Jackets for U.S. Waters: Preprint

U.S. experience in offshore wind is limited, and high costs are expected unless innovations are introduced in one or multiple aspects of the project, from the installed technology to the balance of system (BOS). The substructure is the main single component responsible for the BOS capital expenditure (CapEx) and thus one that, if improved, could yield significant levelized cost of energy (LCOE) savings. For projects in U.S. waters, multimember, lattice structures (also known as jackets) can render required stiffness for transitional water depths at potentially lower costs than monopiles (MPs). In this study, we used a systems engineering approach to evaluate the LCOE of prototypical wind power plants at six locations along the eastern seaboard and the Gulf of Mexico for both types of support structures. Using a reference wind turbine and actual metocean conditions for the selected sites, we calculated loads for a parked and an operational situation, and we optimized the MP- and jacket-based support structures to minimize their overall mass. Using a suite of cost models, we then computed their associated LCOE. For all water depths, the MP-based configurations were heavier than their jacket counterparts, but the overall costs for the MPs were less than they were for jackets up to depths of slightly less than 30 m. When the associated manufacturing and installation costs were included, jackets resulted in lower LCOE for depths greater than 40 m. These results can be used by U.S. stakeholders to understand the potential for different technologies at different sites, but the methodology illustrated in this study can be further employed to analyze the effects of innovations and design choices throughout wind power plant systems.

17 WIND ENERGY↗
DOE OSTI2017

Accurate force field for molybdenum by machine learning large materials data

In this work, we present a highly accurate spectral neighbor analysis potential (SNAP) model for molybdenum (Mo) developed through the rigorous application of machine learning techniques on large materials data sets. Despite Mo's importance as a structural metal, existing force fields for Mo based on the embedded atom and modified embedded atom methods still do not provide satisfactory accuracy on many properties. We will show that by fitting to the energies, forces and stress tensors of a large density functional theory (DFT)-computed dataset on a diverse set of Mo structures, a Mo SNAP model can be developed that achieves close to DFT accuracy in the prediction of a broad range of properties, including energies, forces, stresses, elastic constants, melting point, phonon spectra, surface energies, grain boundary energies, etc. We will outline a systematic model development process, which includes a rigorous approach to structural selection based on principal component analysis, as well as a differential evolution algorithm for optimizing the hyperparameters in the model fitting so that both the model error and the property prediction error can be simultaneously lowered. We expect that this newly developed Mo SNAP model will find broad applications in large-scale, long-time scale simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Assessing the Feasibility of Bordered Block Diagonal Reordering in Power System Matrices using Fully Convolutional Network

In electromagnetic transient (EMT) simulations for power systems and inverter-based resources (IBRs), the arrangement of states within the system's linear equations, represented by matrix A in Ax=b, is critical. The state ordering in matrix A can highlight distinct characteristics of the system's graph, and identifying an optimal state ordering is crucial for efficient computation. The choice of state ordering, however, is dependent on the solver used, as each solver may perform optimally with different matrix patterns. With a wide array of matrix reordering algorithms available, selecting the most suitable one becomes challenging without insights into the matrix's ideal configuration. To address this, the paper proposes a fully convolutional network (FCN) to evaluate the reordering potential of the A matrix into a bordered block diagonal (BBD) pattern, which is commonly observed in power system and IBR modeling. The FCN's assessment aims to streamline the solver's operation, which in turn could substantially reduce the computational time required to find a solution.

Xia, Qianxue↗
DOE OSTI2025

Data for "RT-EZ: A Golden Gate Assembly Toolkit for Streamlined Genetic Engineering of Rhodotorula toruloides"

For economic and sustainable biomanufacturing, the oleaginous yeast Rhodotorula toruloides has emerged as a promising platform for producing biofuels, pharmaceuticals, and other valuable chemicals. However, genetic manipulation of R. toruloides has been limited by its high GC content and the lack of a replicating plasmid, necessitating gene integration into the genome of the yeast. To address these challenges, we developed the RT-EZ ( R. toruloides Efficient Zipper) toolkit, a versatile tool based on Golden Gate assembly, designed to streamline R. toruloides engineering with improved efficiency and flexibility. The RT-EZ toolkit simplifies vector construction by incorporating new features such as bidirectional promoters and 2A peptides, color-based screening using RFP, and sequences optimized for both Agrobacterium tumefaciens-mediated transformation (ATMT) and easy linearization, enabling straightforward selection and transformation. Notably, the RT-EZ kit can be used to construct an expression cassette with four different genes in one assembly reaction, significantly improving vector construction speed and efficiency. The utility of the RT-EZ toolkit was demonstrated through the successful synthesis of arachidonic acid in R. toruloides by coexpressing fatty acid elongases and desaturases. This result underscores the potential of the RT-EZ toolkit to advance synthetic biology in R. toruloides , providing a streamlined method for addressing genetic engineering challenges in the yeast.

gene editing↗
DOE OSTI2019

Short-term Interventions for Long-term Change: Spreading Stable Green Norms in Networks

Strong empirical evidence suggests that people infer prevailing pro-environmental norms based on the behavior of people they encounter and engage with. These norms seem to be adopted in response to both internal motivation and social pressure. To formalize such behavior, the economic literature has introduced theoretical models that include moral and social drivers. We complement this theoretical literature by analyzing the adoption of green behavior in presence of social networks. Leveraging insights from the network-science literature, we extend an existing model of socially contingent moral motivation to include characteristics of human social behavior that have been shown, empirically, to matter for green behavior, but which have been neglected by most theoretical models. Our network moral-motivation model leads naturally to spatial-heterogeneity in environmental norms. Consistent with non-network models, we show that temporary subsidy can lead to stable equilibria with positive adoption, even when the subsidy is discontinued. In our model, however, regulators can achieve significant savings by targeting subsidies. With our computational exercises, using small semi-realistic networks, we quantify the gains of targeting subsidies, or social interventions, towards optimal seed groups. These gains may be large compared to widespread subsidies, or random selection of seed groups, and depend on the society’s structural characteristics. Furthermore, considering social networks may change radically the performance of initiatives aimed at promoting the adoption of green behavior.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

An Overview of Natural Gas Conversion Technologies for Co-Production of Hydrogen and Value-Added Solid Carbon Products

This report was prepared in response to the U.S. Department of Energy Fuel Cell Technologies Office Congressional Appropriation language to support research on carbon-free production of hydrogen using new chemical processes that utilize natural gas to produce solid carbon and hydrogen. The U.S. produces 9-10 million tons of hydrogen annually with more than 95% of the hydrogen produced by steam-methane reforming (SMR) of natural gas. SMR is attractive because of its high hydrogen yield; but it also converts the carbon to carbon dioxide. Non-oxidative thermal decomposition of methane to carbon and hydrogen is an alternative to SMR and produces CO 2 -free hydrogen. The produced carbon can be sold as a co-product, thus providing economic credit that reduces the delivered net cost of hydrogen. The combination of producing hydrogen with potentially valuable carbon byproducts has market value in that this allows greater flexibility to match the market prices of hydrogen and carbon. That is, the higher value product can subsidize the other in pricing decisions. In this report we highlight the relevant technologies reported in the literature—primarily thermochemical and plasma conversion processes—and recent research progress and commercial activities. Longstanding technical challenges include the high energetic requirements (e.g., high temperatures and/or electricity requirements) necessary for methane activation and, for some catalytic processes, the separation of solid carbon product from the spent catalyst. We assess current and new carbon product markets that could be served given technological advances, and we discuss technical barriers and potential areas of research to address these needs. We provide preliminary economic analysis for these processes and compare to other emerging (e.g., electrolysis) and conventional (e.g., SMR) processes for hydrogen production. The overarching conclusion of this study is that the cost of hydrogen can be potentially reduced to target levels of $2/kg with the co-production and sale of a sufficiently high-value carbon product. Technological advances are required to understand the reaction conditions and design reactor systems that can achieve high yields of the select carbon products and segregate or separate the high-value carbon products, and optimize the production process for both hydrogen and carbon.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Ontario International Airport Fleet Electrification Blueprint: Zero-Emission Vehicle Technology Assessment for Energy Optimization [Slides]

Ontario International Airport Authority (OIAA)'s Electric Vehicle (EV) Blueprint project presentation focuses on the possibilities for fleet electrification, including medium heavy duty charging and hydrogen refueling and their associated planning, infrastructure, operation, and maintenance options. This report includes detailed list of available electric ground support equipment (GSE), description of NREL tools for EV infrastructure design and optimization, and analyses of the current fleet and the potential grid impacts of electrification. Key recommendations are made in regard to simulation-based and in-depth system analyses to identify optimal charging infrastructure and long-term grid stability, and to ensure that the selected station architecture will provide enough space and capacity for future expansion and resiliency.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Thermopile Energy Harvesting for Subsurface Wellbore Sensors (Final Report)

Robust in situ power harvesting underlies all efforts to enable downhole autonomous sensors for real-time and long-term monitoring of CO 2 plume movement and permeance, wellbore health, and induced seismicity. This project evaluated the potential use of downhole thermopile arrays, known as thermoelectric generators (TEGs), as power sources to charge sensors for in situ real-time, long-term data capture and transmission. Real-time downhole monitoring will enable “Big Data” techniques and machine learning, using massive amounts of continuous data from embedded sensors, to quantify short- and long-term stability and safety of enhanced oil recovery and/or commercial-scale geologic CO 2 storage. This project evaluated possible placement of the TEGs at two different wellbore locations: on the outside of the casing; or on the production tubing. TEGs convert heat flux to electrical power, and in the borehole environment, would convert heat flux into or out of the borehole into power for downhole sensors. Such heat flux would be driven by pumping of cold or hot fluids into the borehole—for instance, injecting supercritical CO 2 —creating a thermal pulse that could power the downhole sensors. Hence, wireless power generation could be accomplished with in situ TEG energy harvesting. This final report summarizes the project’s efforts that accomplished the creation of a fully operational thermopile field unit, including selection of materials, laboratory benchtop experiments and thermal-hydrologic modeling for design and optimization of the field-scale power generation test unit. Finally, the report describes the field unit that has been built and presents results of performance and survivability testing. The performance and survivability testing evaluated the following: 1) downhole power generation in response to a thermal gradient produced by pumping a heated fluid down a borehole and through the field unit; and 2) component survivability and operation at elevated temperature and pressure conditions representative of field conditions. The performance and survivability testing show that TEG arrays are viable for generating ample energy to power downhole sensors, although it is important to note that developing or connecting to sensors was beyond the scope of this project. This project’s accomplishments thus traversed from a low Technical Readiness Level (TRL) on fundamental concepts of the application and modeling to TRL-5 via testing of the fully integrated field unit for power generation in relevant environments. A fully issued United States Patent covers the wellbore power harvesting technology and applications developed by this project.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

A Multidisciplinary Approach to Integrated Energy Systems: Advanced Nuclear Plants with Thermal Storage for Dynamic and Flexible Operation in Diverse Markets

Energy supply, distribution, and demand are continuously evolving in accordance with the integration of new power generation sources. In the United States, there is a progressive shift toward incorporating fluctuating energy sources such as wind and solar into the energy mix, alongside the distributed generation. Simultaneously, we are seeing a revolution in consumer technologies such as electric vehicles, energy devices for both residential and commercial use, and industrial processes—all contributing to a fundamental change in energy consumption dynamics. These scenarios have led to huge demand for enhanced flexibility from nuclear power plants (NPPs), requiring them to operate with unprecedented adaptability. Furthermore, advanced NPPs (A-NPPs) could potentially apply to scenarios in which power generation flexibility is prioritized over its current and conventional baseload generation capacity for traditional demand patterns. The present work covers several configurations for coupling nuclear energy production with thermal energy storage (TES). Previous work evaluated systems entailing a simple nuclear-TES configuration that used steam as a heat source for the TES of three different advanced reactors (ARs), but its heat diversion ratio (HDR) for charging was limited. The present work proposes a new configuration that features full decoupling of the nuclear reactor and the power cycle, using reactor coolant (i.e., gas) as a heat source for the TES and offering a theoretically unlimited HDR. This configuration is, however, more complex, as both high- and low-temperature TES (HT-TES and LT-TES) systems are required in order to cover the extended temperature range. Although this configuration imposes certain limitations on the discharge system configuration, it also presents the opportunity to design a more efficient system. For this case in particular, a steam reheat cycle is advantageous. Conventional TES systems take advantage of nominal efficiency when discharging, whereas the reheat cycle in the fully decoupled TES system affords a significant efficiency increase over conventional cases. Material selection, component/equipment sizing, and costing analyses were performed, followed by economic dispatch and size optimization. Dynamic models were developed for the decoupled system in order to generate insights into aspects of off design operation (e.g., drops in cycle efficiency), and these models enable exploration of potential mitigation strategies for addressing such drops. The models also highlight the need to design fail-safes that ensure continuous operational stability and minimize the impact of power ramping on the reactor parameters.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

High Throughput Genome Releaser

In this study, we present the development of a High Throughput Genome Releaser, an innovative device addressing common challenges in screening PCR. This genome DNA releaser is designed for rapid, cost-effective, and efficient DNA extraction, optimized for subsequent PCR reactions. Our experimentation with various synthetic materials led us to select a particular type of plastic that mirrors the properties of glass cover slides, providing a smooth surface and effective compression capabilities. We engineered a 96-well device equipped with a 96-well plate and a top rod, operable both manually and automatically, which is compatible with widely used liquid-handling robot decks. This compatibility enhances ease of use in high-throughput PCR setups. Additionally, we developed software to support its automatic functions. The genome releaser facilitates the extraction of PCR-amplifiable genomic DNA from 96 samples within minutes, eliminates the need for extraction buffers, and is adaptable to a wide range of microorganisms and cells. This versatility could significantly advance biomanufacturing processes.

42 ENGINEERING↗
DOE OSTI2024

Electrochemical Oxidation of Seawater for Renewable Energy Generation and Storage in Coastal Areas

In this work, we demonstrated how the Clean Sustainable Electrochemical Treatment process can be used to process seawater while simultaneously generating molecular hydrogen. The specific goal of this project is to (1) demonstrate selective removal of chemical oxygen demand over the oxygen and chlorine evolution reactions, (2) optimize electrode composition to improve electrochemical performance, and (3) demonstrate long-term (>100 h) stability experiments.

08 HYDROGEN↗
DOE OSTI2026

Virtual Growth of SRF Materials

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Fermilab]↗
DOE OSTI2020

PopSyCLE: A New Population Synthesis Code for Compact Object Microlensing Events

We present a new Milky Way microlensing simulation code, dubbed PopSyCLE (Population Synthesis for Compact object Lensing Events). PopSyCLE is the first resolved microlensing simulation to include a compact object distribution derived from numerical supernovae explosion models and both astrometric and photometric microlensing effects. We demonstrate the capabilities of PopSyCLE by investigating the optimal way to find black holes (BHs) with microlensing. Candidate BHs have typically been selected from wide-field photometric microlensing surveys, such as OGLE, by selecting events with long Einstein crossing times (tE > 120 days). These events can be selected at closest approach and monitored astrometrically in order to constrain the mass of each lens; PopSyCLE predicts a BH detection rate of ~40% for such a program. We find that the detection rate can be enhanced to ~ 85% by selecting events with both tE > 120 days and a microlensing parallax of πE < 0.08. Unfortunately, such a selection criterion cannot be applied during the event as πE requires both pre- and post-peak photometry. However, historical microlensing events from photometric surveys can be revisited using this new selection criteria in order to statistically constrain the abundance of BHs in the Milky Way. The future WFIRST microlensing survey provides both precise photometry and astrometry and will yield individual masses of O(100 - 1000) black holes, which is at least an order of magnitude more than is possible with individual candidate follow-up with current facilities. The resulting sample of BH masses from WFIRST will begin to constrain the shape of the black hole present-day mass function, BH multiplicity, and BH kick velocity distributions

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Diversification of multipotential postmitotic mouse retinal ganglion cell precursors into discrete types

The genesis of broad neuronal classes from multipotential neural progenitor cells has been extensively studied, but less is known about the diversification of a single neuronal class into multiple types. We used single-cell RNA-seq to study how newly born (postmitotic) mouse retinal ganglion cell (RGC) precursors diversify into ~45 discrete types. Computational analysis provides evidence that RGC transcriptomic type identity is not specified at mitotic exit, but acquired by gradual, asynchronous restriction of postmitotic multipotential precursors. Some types are not identifiable until a week after they are generated. Immature RGCs may be specified to project ipsilaterally or contralaterally to the rest of the brain before their type identity emerges. Optimal transport inference identifies groups of RGC precursors with largely nonoverlapping fates, distinguished by selectively expressed transcription factors that could act as fate determinants. Our study provides a framework for investigating the molecular diversification of discrete types within a neuronal class.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Detecting and quantifying materials in containers utilizing an inverse algorithm with adaptive regularization

A method, system and computer program product for automatically detecting and quantifying materials in containers (e.g., luggage, storage containers, equipment or componentry for processing or handling). An X-ray radiograph of a container is generated. A set of materials of interest (e.g., plutonium, steel) is selected to determine if the object comprises or contains materials of interest. An estimate of the areal densities or thicknesses of each of the selected materials of interest is obtained by minimizing an objective function with respect to the areal densities or thicknesses for each of the selected materials of interest. Adaptive regularization is implemented in the objective function to improve optimization results by adding a constraint to the objective function, where the constraint penalizes the objective function for solutions that do not line up with a prior belief about the solution form (e.g., the solution should not be negative or especially noisy).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Does the Perfect Waste Package Exist? Development of a Decisional Tool Addressing this Challenge - 17053

The definition of a safe, technically, economically and societally acceptable waste management strategy is highly dependent on the Waste Acceptance Criteria in each country and on the already available disposal routes. It is the reason why there is not a single solution but a combination of optimized solutions depending on the type of waste and on each country's considerations. In fact, when operating a nuclear plant or performing its decommissioning or legacy waste management, one has to consider a large waste diversity in term of natures, types, volumes and radioactivity spectra. All nuclear operators have to take-up the challenge of implementing solutions for conditioning its waste in packages suitable for transport short to long term interim storage and final disposal of it (or prepare for final disposal if the repository is not yet available). Operators have then to answer the following dilemma: either define a complete strategy packaging the waste for final disposal, or 'containerising' it temporarily, pending final disposal. The strategy is highly country dependent; in the first case, one has to take into account the available information and future orientations relative to acceptability of the packages in order to define a robust solution. The approach implemented in France requires a close dialogue between the Operators, the Safety Authority, the Administration and the stakeholders. Moreover it pushes forward whenever possible standardization, contributing to cost minimization. If the second approach has the advantage of leaving the options open, and reducing the initial investments, it inevitably requires future retrieval and re-packaging with potential evolutions/degradation of the initial waste form. It also induces the potential risk to produce additional secondary waste. As an additional drawback, it introduces uncertainties and unknowns related to the future waste management criteria and to the costs. The general idea is that, depending on context, a given route (i.e., treatment, conditioning, and transport), could be considered as efficient or not. Assessing a waste package is certainly highly context dependent. However it should be possible to recognize and to lead an evaluation based on a number of fixed criteria, whatever the context, to be addressed when assessing the development of a final waste package in connection to the overall management route. A waste package is always a combination of a waste container and a waste form and will have to be transported one day from the production site to the final repository or to off-site interim storage facilities. AREVA's approach consists in defining an evaluation grid based on a set of criteria which aim (i) to evaluate whether the different waste treatments, conditionings, transport and packages deserve to be considered within different national contexts, and (ii) to evaluate R and D actions to be performed for improving existing solutions or developing new ones. One of the key lessons to be drawn from AREVA's experience in developing waste packages is that the perfect waste doesn't exist even though the vitrified canister is probably the most efficient one. The performance of a package resulting from a compromise depends on context and is a strength combination between the waste container and the waste form. The approach is to evaluate a waste package development against different set of criteria and to draw optimization diagrams. In such diagram, a given waste package is assessed with respect to selected criteria such as waste form and waste container, stability, level of waste incorporation, integrity lifetime, secondary waste generation, transport, long term behavior, and economical effectiveness, etc. Addressing a waste form is a very key point. This evaluation grid and comparative approach will be presented through examples and comparison providing from AREVA feedback on waste package development related to complex waste management such as problematic waste or legacy waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

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