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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

Development of the high energy engineering X-ray (HEX) superconducting wiggler, magnetic measurement, installation, and commissioning

The High energy Engineering X-ray (HEX) diffraction beamline at the National Synchrotron Light Source II (NSLS-II) at Brookhaven National Lab (BNL) is the first high-energy beamline capable of reaching 200 keV for a monochromatic beam. With the 3 GeV electron beam energy for the NSLS-II ring, only the superconducting wiggler (SCW) producing greater than 4 T peak field can cover these ranges with a sufficient number of photons. The 1.2 m-long HEX-SCW has a period length of 70 mm and a field strength on-axis of 4.3 T. It utilizes no liquid helium, and the vertical aperture size of the electron beam vacuum chamber is 8 mm. Unlike regular undulators/wigglers, there is no standard configuration for the magnetic measurement system for superconducting insertion devices. The NSLS-II Insertion Devices group has developed, in collaboration with the vacuum group, a novel in-vacuum Hall mapper with a 1.75 m in-vacuum linear motor and an in-vacuum flip coil system utilizing many commercial-off-the-shelf products. The measurements were conducted at the BNL, and the device was installed in the ring and commissioned. Here, this paper provides a description of the SCW and its magnetic measurement systems, as well as a brief account of the installation and commissioning efforts.

36 MATERIALS SCIENCE↗

Towards stacking fault energy engineering in FCC high entropy alloys

Stacking Fault Energy (SFE) is an intrinsic alloy property that governs much of the plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for many years as a key intrinsic mechanical property, its inference via experimental observations or prediction using, for example, computationally intensive first-principles methods is challenging. This difficulty precludes the explicit use of SFE as an alloy design parameter. In this work, we combine DFT calculations (with necessary configurational averaging), machine-learning (ML) and physics-based models to predict the SFE in the fcc CoCrFeMnNiV-Al high-entropy alloy space. The best-performing ML model is capable of accurately predicting the SFE of arbitrary compositions within this 7-element system. Finally, this efficient model along with a recently developed model to estimate intrinsic strength of fcc HEAs is used to explore the strength–SFE Pareto front, predicting new-candidate alloys with particularly interesting mechanical behavior.

36 MATERIALS SCIENCE↗

Hybrid Organic Inorganic Perovskites: Physical Properties and Applications (in 4 Volumes)

This four-volume handbook gives a state-of-the-art overview of hybrid organic inorganic perovskites, both two dimensional (2D) and three dimensional (3D), from synthesis and characterization and simulation to optoelectronic devices (such as solar cells and light emitting diodes), spintronics devices and catalysis application. The editors, coming from academia and national laboratory, are known for their didactic skills as well as their technical expertise. Coordinating the efforts of 30 expert authors in 21 chapters, they construct the story of hybrid perovskite structural and optical properties, electronic and spintronic response, laser action, and catalysis from varied viewpoints: materials science, chemical engineering, and energy engineering. The four volumes are arranged according to the focus material properties. Volume 1 is focused on the material physical properties including structure, deposition characteristic and the structure of the electronic bands and excitons of these compounds. Volume 2 covers the hybrid perovskite optical properties including the ultrafast optical response, photoluminescence and laser action. Volume 3 contains the spin response of these compounds including application such as spin valves, photogalvanic effect, and magnetic response of light emitting diodes and solar cell devices. Finally, and highly relevant to tomorrow's energy challenges, volume 4 is focused on the physics and device properties of the most relevant applications of the hybrid perovskites, namely photovoltaic solar cells. The text contains many high-quality colorful illustrations and examples, as well as thousands of up-to-date references to peer-reviewed articles, reports and websites for further reading. This comprehensive and well-written handbook is a must-have reference for universities, research groups and companies working with the hybrid organic inorganic perovskites.

applications↗

Engineering the cellulolytic extreme thermophile Caldicellulosiruptor bescii to reduce carboxylic acids to alcohols using plant biomass as the energy source

Abstract Caldicellulosiruptor bescii is the most thermophilic cellulolytic organism yet identified (Topt 78 °C). It grows on untreated plant biomass and has an established genetic system thereby making it a promising microbial platform for lignocellulose conversion to bio-products. Here, we investigated the ability of engineered C. bescii to generate alcohols from carboxylic acids. Expression of aldehyde ferredoxin oxidoreductase (aor from Pyrococcus furiosus) and alcohol dehydrogenase (adhA from Thermoanaerobacter sp. X514) enabled C. bescii to generate ethanol from crystalline cellulose and from biomass by reducing the acetate produced by fermentation. Deletion of lactate dehydrogenase in a strain expressing the AOR–Adh pathway increased ethanol production. Engineered strains also converted exogenously supplied organic acids (isobutyrate and n-caproate) to the corresponding alcohol (isobutanol and hexanol) using both crystalline cellulose and switchgrass as sources of reductant for alcohol production. This is the first instance of an acid to alcohol conversion pathway in a cellulolytic microbe.

Biotechnology & Applied Microbiology↗

Engineering defect energy landscape of CoCrFeNi high-entropy alloys by the introduction of additional dopants

The concept of high-entropy alloys (HEAs) focusing on tuning the overall chemical complexity represents a novel alloy design strategy. In contrast, alloying of a metallic matrix with minor doping elements with limited and localized tunability has been a common practice to improve material performance. Combining the idea of globally engineering defect energy landscape in HEAs and the localized doping strategy in dilute alloys, in this work, we explore doping effects of minor elements in a HEA matrix to further enhance the overall and localized chemical tunability, aiming to improve its irradiation resistance. Specifically, we study the influence of minor Al, Cu, Ti, and Pd substitutional doping elements on defect energetics in a CoCrFeNi model HEA based on density-functional theory (DFT) calculations. The DFT results indicate that the formation and migration energies of vacancies can be strongly influenced when a dopant is introduced at the first nearest neighbor shells around a vacancy. On the other hand, interstitial energetics are only slightly affected. Among the four elements, Ti and Pd generally decrease vacancy formation energies and increase vacancy migration energies more significantly than Al and Cu. The doping effects become more pronounced when the concentration of the substitutional dopants increases. Based on the energy distributions obtained from DFT, we build a kinetic Monte Carlo (kMC) model to assess the impact of dopants on vacancy-mediated diffusivity in the doped HEAs. Our results suggest that Ti and Pd can lower the tracer diffusivity in the considered HEAs and act as trapping sites, whereas Cu may enhance the atomic transport. This work indicates that substitutional doping in HEAs is an effective strategy in metallurgy to further tune the defect and transport properties of complex alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Enabling a Flexible Grid with Increased Penetration of DER: Techno-economic Analysis of Metal Hydride Thermochemical Energy Storage Integrated with Stirling Engine for Grid Energy Storage Applications

This report summarizes the results of a techno-economic assessment of the capital and operational expenses for 3 scenarios utilizing a TES/Stirling engine system which is charged by an electric heater to provide grid power and energy storage. While there are several integration possibilities and material choices that could be utilized in such systems, three difference scenarios were chosen for this assessment to reflect an anticipated deployment of the technology where each might require different TES system configurations. Additionally, an enhanced version of the HTMH is considered to demonstrate the expected impact on costs with further technology development. The predicted capital and operational LCOS for the system configurations range from $0.0198/kWhr e - $0.0734/kWhr e which compare positively to the LCOS for lithium ion battery storage ranging from $0.087/kWhr e – $0.329/kWhr e . The key drivers for cost improvements to the system are material property enhancements in the HTMH primarily related to reducing the costs associated with the HTMH vessel and heat exchangers. This analysis demonstrates the potential benefits and flexibility of integrating a Stirling engine with a metal hydride-based TES system and suggests that the MH TES technology, at its current level of development, provides a highly competitive alternative to lithium ion batteries for large scale grid energy storage applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Artificial Intelligence and Digital Engineering as Enablers for System Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world’s energy demands and build energy security.

42 - ENGINEERING↗

Artificial Intelligence and Digital Engineering as Enablers for Systems Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world?s energy demands and build energy security.

42 - ENGINEERING↗

West Virginia University Industrial Assessment Center (Final Progress Report)

The Industrial Assessment Center at West Virginia University has been successful in workforce development, and in generation of energy savings for manufacturing facilities during the period 2016 to 2021. Graduate and undergraduate students have benefited from energy assessment experience and most of them have found good positions as energy engineers and analysts in the industrial sector. Several peer reviewed research papers in archival journals as well as conference papers on the topic of energy engineering and assessment have been published. The implemented energy savings for manufacturing facilities have been significant in the areas of lighting, compressed air, process heating, steam, HVAC, chillers and cooling towers, and motors. In addition, water use reduction, smart manufacturing applications to save energy, cyber security evaluation, energy management, productivity improvements and waste reduction opportunities that lead to energy intensity reductions have been explored. The students have obtained an opportunity to interact with energy efficiency and productivity improvement professionals at various conferences and workshops and their research has generated important results. In summary, the West Virginia University Industrial Assessment Center (WVU-IAC) has fulfilled its mission in regard to workforce development, energy efficiency for manufacturing facilities, and laid a strong platform enhancing sustainability through reductions in carbon emissions achieved through energy efficiency and energy management initiatives and reductions in water usage and waste reduction. During the project period (2016-2021) the WVU-IAC has made numerous energy efficiency, water use reduction, waste reduction, and productivity improvement recommendations, a significant number of them having been implemented by the manufacturing facilities. The research adds significant understanding to the area of energy efficiency, water and waste reduction, and productivity improvement. The technical effectiveness and economic feasibility of the methods and techniques investigated and demonstrated through this project have been exemplary, resulting in significant recommended and implemented resource savings and reductions in carbon emissions. The project has been of significant benefit to the public owing to replication of results within the industrial sector, thus reducing operating costs for businesses that result in increase of growth and employment, as well as community benefits in terms of reductions in carbon emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Achieving Multimodal and Multicolor Luminescence in LaAlO 3 :Pr 3+ , Gd 3+ via Trap Engineering and Energy Transfer

Achieving multimodal luminescence within a single phosphor is vital for multifunctional applications but remains challenging due to complex color tuning and trap engineering. In this study, we report Pr 3+ and Gd 3+ co‐doped LaAlO 3 (LAO:PG) phosphors, designed through careful modulation of multilevel traps and Pr 3+ → Gd 3+ energy transfer dynamics. These materials exhibit diverse luminescence modes, including down‐conversion luminescence (DCL), up‐conversion luminescence (UCL), persistent luminescence (PersL), optically stimulated luminescence (OSL), and thermally stimulated luminescence (TSL) across a wide spectral range. Unlike previously studied Pr 3+ ‐doped LAO, the co‐doped LAO:PG shows DCL in both UV‐visible and NIR regions and displays ultraviolet‐C UCL under visible excitation. Notably, we observe, for the first time, PersL lasting several minutes in these phosphors—an improvement over the non‐PersL behavior of Pr 3+ ‐only doped LAO. Additionally, the LAO:PG phosphors exhibit strong OSL response. TSL analysis reveals five distinct trap levels linked to these properties. Density functional theory calculations further correlate intrinsic defects to these traps, supporting a proposed mechanism for the observed multimodal luminescence. These findings highlight LAO:PG as a promising platform for developing advanced phosphors with integrated luminescence modes, paving the way for future applications in data storage, phototherapy, and anti‐counterfeiting technologies.

Chemistry↗

Gromov ground state in phase space engineering for fusion energy

Phase space engineering by rf waves plays important roles in both thermal D-T fusion and nonthermal advanced fuel fusion, but not all phase space manipulation is allowed; certain fundamental limits exist. In addition to Liouville's theorem, which requires the manipulation to be volume preserving, Gromov's nonsqueezing theorem imposes another constraint. Here, the Gardner ground state is defined as the ground state accessible by smooth volume-preserving maps. However, the extra Gromov constraint should produce a higher-energy ground state. An example of a Gardner ground state forbidden by Gromov's nonsqueezing theorem is given. The challenge question is “What is the Gromov ground state, i.e., the lowest energy state accessible by smooth symplectic maps?” This is a difficult problem. As a simplification, we conjecture that the linear Gromov ground state problem is solvable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Lehigh University Industrial Assessment Center (Final Technical Report for the Period 2016 to 2021)

This is the final technical report summarizing the activities Industrial Assessment Center at Lehigh University sponsored by the Department of Energy for the period September 1, 2016 till September 30, 2021. During this period, the Industrial Assessment Center at Lehigh University was successful in training numerous energy engineers of the future, and helped many manufacturing plants in New Jersey and Eastern Pennsylvania. The center and its activities helped save a great deal of energy, related fuel costs and along the way mitigated tons of CO2 emissions. The report covers many of the numerical details related to the center activities. The Industrial Center at Lehigh University is one of the most successful ones and this is made evident by the statistics included as part of this report and best center award bestowed upon the center.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Plant Engineers Solar Energy Handbook: Southern California Region

Discussed in order after the introduction are solar components and systems (collectors, storage, service hot water systems, space heating with liquid and air systems, space cooling, heat pumps and controls); computer programs for system optimization; local solar and weather data; a description of buildings and plants in Southern California applying solar technology; current Federal and California solar legislation; standards, codes and performance testing information; a listing of manufacturers, distributors, and professional services available in Southern California region; and information access. Finally, solar design check lists for those engineers who wish to design their own systems. The program for the Solar Workshop for the Plant Engineer, March 30, 1978, Los Angeles, California is included.

14 SOLAR ENERGY↗

Multimodal single-Cell/ Particle imaging and engineering for energy conversion in bacteria (Final Technical Report)

Hybrid inorganic-microbial systems have emerged as a potentially transformative approach to combine the light-harvesting capability of inorganic semiconductors and the ability of microbes to orchestrate complex chemical transformations. The objective of this collaborative research is to combine quantum materials synthesis, bacterial synthetic biology, and multimodal single-entity imaging to quantitatively study how hybrid QD-bacteria systems convert light to value chemicals at the single-to-sub cell level, with the ultimate goal of gaining insights to guide the engineering of QDs and bacterial genetics for more efficient bioenergy conversion. The final technical report summarizes our achievements toward this objective.

09 BIOMASS FUELS↗

Methods for making chemoautotrophic cells by engineering an energy conversion pathway and a carbon fixation pathway

The present disclosure identifies pathways, mechanisms, systems and methods to confer chemoautotrophic production of carbon-based products of interest, such as sugars, alcohols, chemicals, amino acids, polymers, fatty acids and their derivatives, hydrocarbons, isoprenoids, and intermediates thereof, in organisms such that these organisms efficiently convert inorganic carbon to organic carbon-based products of interest using inorganic energy, such as formate, and in particular the use of organisms for the commercial production of various carbon-based products of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of Energy Saving Analysis for Different Industries

This study analyzes the energy consumption and saving performance in the industries in the U.S.A. All energy assessments implemented were for facilities whose annual energy consumptions were less than 9,000,000 kWh (small- and medium-sized industries) that belong to the manufacturing industries with Standard Industrial Classification (SIC) codes ranging from 2000 to 3999 in addition to SIC codes starting with 49. In this study, assessments are classified based on the SIC codes with recommendations analysis for each classification to get a better idea of what recommendations were suggested in each major industrial sector, knowing that 68 assessments were made, and their SIC ranged from 14 to 49. In addition, this study could be considered as a guide for energy engineers and other personnel involved in the energy assessment process. The information investigated can give a better prediction for composing better energy-demanding industries and minimizing energy consumption. More than 61 energy assessments were conducted for manufacturing facilities and analyzing the data gathered and processed. Through the research, the Fabricated Metal industry achieved the highest average kWh savings and cost savings within the industries studied in this study. According to the average gigajoule (GJ) savings, the fabricated metal industry ranked second within the studied industries. Conversely, Food and Kindred Products achieved the highest GJ energy savings within the studied industries. Overall, lighting, motors, compressors, and heating, ventilation, and air conditioning (HVAC) were the most contributing industries in a total of 547 recommendations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Application of machine learning to evaluating and remediating models for energy and environmental engineering

Machine learning (ML) algorithms have been increasingly successful in their applications to solve energy and environmental engineering problems. ML algorithms have the advantage of being able to solve highly nonlinear issues effectively. Furthermore, considering the limited sample size of data collected in energy and environmental engineering, obtaining a ML model with reasonable accuracy is simple. Unfortunately, the vast majority of the current applications of ML algorithms lack effective screening of dominant factors and comprehensive model validation, which weakens the predictive ability of the models. The present study takes the minimum miscible pressure (MMP) of CO 2 - oil systems as an example. It establishes a systematic and robust predictive model to address this issue. Based on 147 sets of slim tube tests, the predictive models of the MMPs are investigated by application of eight ML algorithms. The paper concludes that most of the published ML models in the field of energy and environmental engineering prediction are not reliable. Furthermore, it addresses the main reasons for the poor performance of some predictive models built by ML and provides guidelines on how to make such models robust. Further, to the best of our knowledge, this is the first study to point out the defects of current ML modeling methods and propose countermeasures for their application in energy and environmental engineering problems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗