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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 127 records · Page 7

Overview/Recap of the 2020 Accelerated Irradiation of Reactor Structural Materials Workshop

The workshop provided a snapshot look at current international, in-reactor testing and irradiation capabilities. Gaps were identified where possible, and discussions focused on potential mitigation strategies and recommended paths forward. As new material innovations are being developed for in-reactor applications for reactor life extension long-term operation, and advanced reactor technologies, there is an increased need for materials qualification and assessment programs. In-reactor testing capabilities are vital to the on-going success of these DOE-NE programs and initiatives. In recent years, multiple international research reactors have been placed in a permanent shut-down state and have begun full decommissioning. These activities have created new risks in the delivery of on-going and/or expected research programs. Beyond performing simple irradiations in test reactors, few facilities exist internationally which can perform instrumented, in-situ irradiations on structural materials, and with the recent shut down of facilities hosted at Halden and NRU (example: instrumented fatigue loop, and in-situ creep), there are further gaps in the industry left un-filled. A new focus is being placed on the use of accelerator- based technologies to fill in some of these gaps, but these must be viewed as supplemental, and not surrogates to in-reactor capabilities

36 - MATERIALS SCIENCE↗

Adaptive laboratory evolution and metabolic engineering of Cupriavidus necator for improved catabolism of volatile fatty acids

Bioconversion of high-volume waste streams into value-added products will be an integral component of the growing bioeconomy. Volatile fatty acids (VFAs) (e.g., butyrate, valerate, and hexanoate) are an emerging and promising waste-derived feedstock for microbial carbon upcycling. Cupriavidus necator H16 is a favorable host for conversion of VFAs into various bioproducts due to its diverse carbon metabolism, ease of metabolic engineering, and use at industrial scales. Here, in this study, we report that a common strategy to improve product titers in C. necator, deletion of the polyhydroxybutyrate (PHB) biosynthetic operon, results in a significant growth defect on VFA substrates. Using adaptive laboratory evolution, we identify mutations to the regulator gene phaR, the two-component response regulator-histidine kinase pair encoded by H16_A1372/H16_A1373, and the tripartite transporter assembly encoded by H16_A2296-A2298 as causative for improved growth on VFA substrates. Deletion of phaR and H16_A1373 led to significantly reduced NADH abundance accompanied by large changes to expression of genes involved in carbon metabolism, balance of electron carriers, and oxidative stress tolerance that may be responsible for improved growth of these engineered strains. These results provide insight into the role of PHB biosynthesis in carbon and energy metabolism and highlight a key role for the regulator PhaR in global regulatory networks. By combining mutations, we generated platform strains with significant growth improvements on VFAs, which can enable improved conversion of waste-derived VFA substrates to target bioproducts.

09 BIOMASS FUELS↗

Transmission of Human Influenza A Virus in Pigs Selects for Adaptive Mutations on the HA Gene

Influenza A viruses (FLUAV) cause respiratory diseases in many host species, including humans and pigs. The spillover of FLUAV between swine and humans has been a concern for both public health and the swine industry. With the emergence of the triple reassortant internal gene (TRIG) constellation, establishment of human-origin FLUAVs in pigs has become more common, leading to increased viral diversity. However, little is known about the adaptation processes that are needed for a human-origin FLUAV to transmit and become established in pigs. Here, we generated a reassortant FLUAV (VIC11pTRIG) containing surface gene segments from a human FLUAV strain and internal gene segments from the 2009 pandemic and TRIG FLUAV lineages and demonstrated that it can replicate and transmit in pigs. Sequencing and variant analysis identified three mutants that emerged during replication in pigs, which were mapped near the receptor binding site of the hemagglutinin (HA). The variants replicated more efficiently in differentiated swine tracheal cells compared to the virus containing the wildtype human-origin HA, and one of them was present in all contact pigs. These results show that variants are selected quickly after replication of human-origin HA in pigs, leading to improved fitness in the swine host, likely contributing to transmission.

60 APPLIED LIFE SCIENCES↗

One dislocation at a time

The direct observation of enhanced dislocation mobility in iron by in situ electron microscopy offers key insights and adds to the ongoing debate on the mechanisms of hydrogen embrittlement. The tiniest atom in nature, hydrogen, is pervasive and sneaky. When hydrogen atoms, either from gas or liquid sources, come into contact with a metal, they rush into the solid and squeeze through the narrow spaces between the host atoms. Being chemically active, atomic hydrogen can potentially bind to either host or impurity atoms, forming hydrides and thus changing a material’s properties. Metals, which are well known and widely used in industry for their strength and ductility, can become dangerously brittle when exposed to hydrogen. Furthermore, this phenomenon is known as hydrogen embrittlement and can lead to catastrophic failure of a load-bearing part. For example, the hydrogen produced when water molecules break apart in coolants in a nuclear reactor can cause sudden failure of the pressure vessel. In another example, although blending hydrogen in natural-gas pipelines provides a promising pathway to transition into the hydrogen economy, it could lower the fatigue resistance of the pipeline steel, making it more susceptible to crack growth due to cyclic loading induced by pressure fluctuations in the pipeline. Remarkably, perhaps as a result of a multitude of recognized failure mechanisms in which hydrogen can potentially participate, it still remains unknown exactly why hydrogen makes a metal brittle. Now, writing in Nature Materials, Longchao Huang and colleagues present unambiguous experimental observations of hydrogen-enhanced dislocation mobility in iron, offering key insights into the hydrogen embrittlement mechanisms.

36 MATERIALS SCIENCE↗

2019 Anion Exchange Membrane Workshop Summary Report

The National Renewable Energy Laboratory, in coordination with the U.S. Department of Energy Fuel Cell Technologies Office, Advanced Research Projects Agency–Energy, and Los Alamos National Laboratory, hosted the 2019 Anion Exchange Membrane Workshop at the Sheraton Dallas Hotel in Dallas, Texas, on May 30, 2019. More than 50 industrial, academic, national laboratory, and government experts representing the needs of anion exchange membranes, membrane electrode assemblies, and system and stack components attended the workshop.

30 DIRECT ENERGY CONVERSION↗

Integration of a DER Management System in Riverside. Final report

The tasks in this project covered various aspects, including algorithm development, algorithm integration into a commercial Active Network Management (ANM) platform, hardware-in-the-loop (HIL) testing in an industry-standard testing platform, pilot demonstration in Riverside, California, and also cost and benefit analysis. The DERMS platform in this project can host different algorithms developed on different platforms (e.g., MATLAB and Python) and it can interact with different hardware devices (e.g., different PV inverters, battery inverters, and different sensors). The DER control solution are based on an advanced model-free, layered, and clustered DER control paradigm. At the core of the DER control algorithms was the concept of Extremum Seeking (ES), which is a model-free probing-based control technique. The ES-based control algorithms were tested on major real-world inverters; both individually and in a cluster. It was shown that even legacy equipment (or when paired with a few additional advanced equipment) can support such advanced control. The monitoring algorithms utilize a heterogeneous set of legacy and advanced sensor measurements, such as behind-the-meter DER sensors, distribution-level Phase Measurement Units, distribution-substation Supervisory Control and Data Acquisition (SCADA), and line current sensors, with their limited availability; in order to infer practical network conditions. Sensor data are utilized to achieve resource forecasting, phase identification, and distribution system state estimation. The technology that was developed and demonstrated in this project could be transformational to utilities, including the smaller municipal utilities such as in Riverside, which may not have the resources to deploy advanced distribution system and DERMS solutions in order to support high penetration of solar power integration. This project created a real-world prototype to provide utilities with an assessment of smart grid monitoring and control technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Managing Cyber Supply Chain Risk for Renewable Energy Technologies

On July 1, 2021, the U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) hosted a virtual workshop facilitated by the National Renewable Energy Laboratory (NREL). Cybersecurity supply chain experts, researchers, and leaders in government and industry came together to share information on current and future challenges in securing emerging technologies and technical architecture. From a cybersecurity perspective, we need to move from a cybersecurity approach that focuses principally on legacy asset owners to one that incorporates more emphasis on end-point device manufacturers and third-party integrators. Cybersecurity for the global digital supply chain for manufacturers of consumer end-point devices—such as smart solar inverters and smart electric vehicle (EV) chargers—will be critical to the future cyber health of the grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

This paper explores the development and application of an investment tool designed to quantify the costs and potential savings associated with integrating large language models (LLMs) into work week management optimization (WMO) within the nuclear industry. LLMs, with their advanced natural language processing capabilities, can significantly enhance various aspects of work management, such as problem identification, prioritization, planning, scheduling, information retrieval, and information summary. Our investment tool focuses on evaluating the return on investment (ROI) for LLM applications in WMO by considering four pivotal decision factors: model selection, application, user training, and hosting options. This paper details the development and implementation of the ROI model and illustrates its application through multiple case studies, analyzing the impact of different variables, such as work time saved, number of requests, and model performance, on the computed ROI over two years. The computed ROI is also compared over different hosting solutions. Our findings indicate that ROI increases with enhanced work time savings and optimal request load but can decline with high request volumes or increased model costs. This model aids decision-makers in the nuclear industry by providing a structured approach to assessing the economic viability and potential savings from integrating LLMs into WMO processes.

97 - MATHEMATICS AND COMPUTING↗

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

This paper explores the development and application of an investment tool designed to quantify the costs and potential savings associated with integrating large language models (LLMs) into work week management optimization (WMO) within the nuclear industry. LLMs, with their advanced natural language processing capabilities, can significantly enhance various aspects of work management, such as problem identification, prioritization, planning, scheduling, information retrieval, and information summary. Our investment tool focuses on evaluating the return on investment (ROI) for LLM applications in WMO by considering four pivotal decision factors: model selection, application, user training, and hosting options. This paper details the development and implementation of the ROI model and illustrates its application through multiple case studies, analyzing the impact of different variables, such as work time saved, number of requests, and model performance, on the computed ROI over two years. The computed ROI is also compared over different hosting solutions. Our findings indicate that ROI increases with enhanced work time savings and optimal request load but can decline with high request volumes or increased model costs. This model aids decision-makers in the nuclear industry by providing a structured approach to assessing the economic viability and potential savings from integrating LLMs into WMO processes.

99 - GENERAL AND MISCELLANEOUS↗

First Plant Cell Atlas symposium report

The Plant Cell Atlas (PCA) community hosted a virtual symposium on December 9 and 10, 2021 on single cell and spatial omics technologies. The conference gathered almost 500 academic, industry, and government leaders to identify the needs and directions of the PCA community and to explore how establishing a data synthesis center would address these needs and accelerate progress. This report details the presentations and discussions focused on the possibility of a data synthesis center for a PCA and the expected impacts of such a center on advancing science and technology globally. Community discussions focused on topics such as data analysis tools and annotation standards; computational expertise and cyber-infrastructure; modes of community organization and engagement; methods for ensuring a broad reach in the PCA community; recruitment, training, and nurturing of new talent; and the overall impact of the PCA initiative. These targeted discussions facilitated dialogue among the participants to gauge whether PCA might be a vehicle for formulating a data synthesis center. The conversations also explored how online tools can be leveraged to help broaden the reach of the PCA (i.e., online contests, virtual networking, and social media stakeholder engagement) and decrease costs of conducting research (e.g., virtual REU opportunities). Major recommendations for the future of the PCA included establishing standards, creating dashboards for easy and intuitive access to data, and engaging with a broad community of stakeholders. The discussions also identified the following as being essential to the PCA's success: identifying homologous cell-type markers and their biocuration, publishing datasets and computational pipelines, utilizing online tools for communication (such as Slack), and user-friendly data visualization and data sharing. In conclusion, the development of a data synthesis center will help the PCA community achieve these goals by providing a centralized repository for existing and new data, a platform for sharing tools, and new analytical approaches through collaborative, multidisciplinary efforts. A data synthesis center will help the PCA reach milestones, such as community-supported data evaluation metrics, accelerating plant research necessary for human and environmental health.

59 BASIC BIOLOGICAL SCIENCES↗

Metal–organic framework (MOF) materials as polymerization catalysts: a review and recent advances

Synthetic polymers are ubiquitous across both the industrial and consumer segments of the world economy. Catalysts enable rapid, efficient, selective, and even stereoselective, formation of desired polymers from any of a host of candidate monomers. While numerous molecular catalysts have been shown to be effective for these reactions, separation of the catalysts from reaction products is typically difficult – a potentially problematic complication that suggests instead the use of heterogeneous catalysts. Many of the most effective heterogeneous catalysts, however, comprise supported collections of reaction centres that are decidedly nonuniform in their composition, siting, and activity. Nonuniformity complicates atomic-scale evaluation of the basis for catalytic activity and thus impedes scientific hypothesis-driven understanding and development of superior catalysts. In view of the fundamental desirability of structural and chemical uniformity at the meso, nano, and even atomic scale, crystallographically well-defined, high-porosity metal–organic frameworks (MOFs) have attracted attention as model catalysts and/or catalyst-supports for a wide variety of chemical transformations. In the realm of synthetic polymers, catalyst-functionalized MOFs have been studied for reactions ranging from coordination-mediated polymerization of ethylene to visible-light initiated radical polymerizations. Nevertheless, many polymerization reactions remain to be explored – and, no doubt, will be explored, given the remarkable structural and compositional diversity of attainable MOFs. Noteworthy emerging studies include work directed toward more sophisticated catalytic schemes such as polymer templating using MOF pore architectures and tandem copolymerizations using MOF-supported reaction centres. Finally, it is appropriate to recognize that MOFs themselves are synthetic polymers – albeit, uncoventional ones.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessment of Cloud-based Applications for Enabling a Scalable Riskinformed Predictive Maintenance Strategy

The current light-water reactor fleet uses time-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging artificial intelligence (AI) and cloud computing technologies to achieve a cost-effective, predictive-maintenance strategy. This paper presents discussion and results on the application of cloud computing in the nuclear industry. The technical viability of cloud computing was analyzed using data from a boiling-water reactor’s safety relief valve. The models were hosted on three different systems: a local personal computer, Idaho National Laboratory’s high-performance computer system, and Microsoft Azure. The data were loaded and processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was determined that cloud computing affords adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, the benefit is that the plants no longer need to manage their own servers, software, cybersecurity, and information technology support staff for in-house data analytics purpose. Many of these features can be offloaded to the cloud provider for a potential cost savings. Demonstrating how AI can improve the maintenance and operation of non-safety-related systems seems the likely path forward for implementing AI and cloud computing resources inside nuclear power plants.

azure↗

Metabolic engineering strategies for sesquiterpene production in microorganism

Sesquiterpenes are a large variety of terpene natural products, widely existing in plants, fungi, marine organisms, insects, and microbes. Value-added sesquiterpenes are extensively used in industries such as: food, drugs, fragrances, and fuels. With an increase in market demands and the price of sesquiterpenes, the biosynthesis of sesquiterpenes by microbial fermentation methods from renewable feedstocks is acquiring increasing attention. Synthetic biology provides robust tools of sesquiterpene production in microorganisms. This review presents a summary of metabolic engineering strategies on the hosts and pathway engineering for sesquiterpene production. Advances in synthetic biology provide new strategies on the creation of desired hosts for sesquiterpene production. Especially, metabolic engineering strategies for the production of sesquiterpenes such as: amorphadiene, farnesene, bisabolene, and caryophyllene are emphasized in: Escherichia coli , Saccharomyces cerevisiae , and other microorganisms. Herein, challenges and future perspectives of the bioprocess for translating sesquiterpene production into practical industrial work are also discussed.

59 BASIC BIOLOGICAL SCIENCES↗

Development of Clostridium tyrobutyricum as a Microbial Cell Factory for the Production of Fuel and Chemical Intermediates From Lignocellulosic Feedstocks

Microbial conversion of lignocellulosic substrates to fuel and platform chemical intermediates offers a sustainable route to establish a viable bioeconomy. However, such approaches face a series of key technical, economic, and sustainability hurdles, including: incomplete substrate utilization, lignocellulosic hydrolysate, and/or end-product toxicity, inefficient product recovery, incompatible cultivation requirements, and insufficient productivity metrics. Development of a production host with native traits suitable for high productivity conversion of lignocellulosic substrates under process-relevant conditions offers a means to bypass the above-described hurdles and accelerate the development of microbial biocatalyst deployment. Clostridium tyrobutyricum , a native producer of short chain fatty acids, displays a series of characteristics that make it an ideal candidate for conversion of lignocellulosic substrates and thus represents a promising host for microbial production of diverse carboxylate-derived product suites. Herein, recent progress and future directions in the development of this bacterium as an industrial microbial cell factory, with emphases on the utilization of lignocellulosic substrates and metabolic engineering approaches, is reviewed.

59 BASIC BIOLOGICAL SCIENCES↗

Estimation of Large-Scale Wind Field Characteristics Using Supervisory Control and Data: Preprint

As the wind energy industry continues to pushfor increased power production and lower cost of energy, thefocus of research has expanded from individual turbines toentire wind farms. Among a host of interesting problems to besolved when considering the wind farm as a whole, we considerthe challenge of scalar field estimation, based on informationalready collected at the individual turbine level. We aim toestimate the large-scale, low-frequency characteristics of thewind field, such as the mean wind direction and the overalldecrease in wind speed across the farm, and employ a Kalmanfilter that models the wind field using a polynomial function.We compare the proposed method’s performance to both asimple averaging technique and filtering of individual turbinemeasurements. The method presented is not limited to windturbines and is applicable in other situations where multipleremote agents are used to estimate a scalar field.

large scale↗

Compilation of a Solar Mirror Materials Database and an Analysis of Natural and Accelerated Mirror Exposure and Degradation

The National Renewable Energy Laboratory (NREL) has been conducting exposure experiments on solar reflectors for over four decades. Thousands of mirror samples from over one hundred suppliers have been exposed to and monitored in a range of relevant environments. These test conditions include outdoor test settings and several controlled laboratory environments. These samples have been rigorously individually characterized using a series of reflectance measurements, visual inspections, and in some cases, in-depth composition analysis to identify degradation modes, reflectance losses, and other mirror properties integral to understanding the solar reflector's life cycle. Here, this paper compiles the decades of measurement data into a concise statistical analysis. It includes exposure and degradation data for numerous reflector types, including secondary-surface reflector permutations of polymer and glass superstrates with silver and aluminum reflectors as well as front-surface reflectors. The results herein are intended to analyze environmental stressors and degradation trends among various historical and state-of-the-art solar reflectors. It may be used to support solar reflector design, effective testing methodology, and inform manufacturing decisions moving forward. Presented are the results of the compiled database and an initial analysis for degradation rate modeling using full-spectrum and wavelength-dependent approaches. The database is a growing resource hosted on a live, publicly accessible website. In conjunction with the analysis presented here, it provides a valuable resource to the solar reflector manufacturing and testing industry.

14 SOLAR ENERGY↗

multiBreath.py

This is a research code which is intended to be made available to researchers to the password-protected simtk.org website which hosts the lung deposition simulation project "In-silico LADDER: Lung Aerosol Dosimetry for Drug and Environmental Research" headed by NIH PI Prof. Chantal Darquenne (UCSD). Industrial applications are more accurate deposition predictions of medical aerosols, including potentially subject-specific exposures. Accessing the code requires registration.

Kuprat, Andrew [Pacific Northwest National Laborat↗

Leptospira borgpetersenii serovar Hardjo and Leptospira santarosai serogroup Pyrogenes isolated from bovine dairy herds in Puerto Rico

Leptospirosis is one of the most common zoonotic diseases in the world and endemic in the Caribbean Islands. Bovine leptospirosis is an important reproductive disease. Globally, cattle are recognized as a reservoir host for L. borgpetersenii serovar Hardjo, which is transmitted via urine, semen, and uterine discharges, and can result in abortion and poor reproductive performance. The dairy industry in Puerto Rico comprises up to 25% of agriculture-related income and is historically the most financially important agricultural commodity on the island. In this study, we report the isolation of two different pathogenic Leptospira species, from two different serogroups, from urine samples collected from dairy cows in Puerto Rico: L. borgpetersenii serogroup Sejroe serovar Hardjo and L. santarosai serogroup Pyrogenes. Recovered isolates were classified using whole-genome sequencing, serotyping with reference antisera and monoclonal antibodies, and immunoblotting. These results demonstrate that dairy herds in Puerto Rico can be concurrently infected with more than one species and serovar of Leptospira, and that bacterin vaccines and serologic diagnostics should account for this when applying intervention and diagnostic strategies.

59 BASIC BIOLOGICAL SCIENCES↗