Prospects of core–edge integrated no-ELM and small-ELM scenarios for future fusion devices
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70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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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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Task 3.1: Research and Development Guiding Technoeconomic Analysis and Life-Cycle Assessment
Technologies under development aim to increase yields of desired end products, reduce overall raw material costs, and/or develop more energy-efficient strategies for product recovery. Techno-economic analysis (TEA) and life-cycle assessments (LCA) help assure that economic and sustainability predictions of the technologies are unbiased and compelling and provide guidance to experimentalists on areas that need focus. Building on previous work, the performance-advantaged bioproducts and bioprocessing separations project (SepCon) continues to use the integrated TEA and LCA to evaluate and guide technologies under development and target challenges relevant to the industry and the Bioenergy Technologies Office (BETO) priority pathways. The analysis team aims to provide credible, unbiased assessments for each technology under development, with ongoing assessments to guide experimental teams. Additionally, the team also supports journal publications highlighting key findings.
biofuels↗
Additive Manufacturing in the Nuclear Reactor Industry
This article discusses the application of additive manufacturing in the nuclear reactor industry.Additive manufacturing for nuclear applications increased significantly in the late 2010s due to rapid progress in technology, particularly with methods using metals and ceramics.Because these manufacturing technologies are uniquely data-rich, they allow for an advanced understanding of materials, and they offer the potential to predict part performance based on build data. The inherent characteristics of additive manufacturing technologies allow for rapid prototyping and geometric freedom, making it possible to implement an accelerated agile design process for advanced nuclear reactor applications. Predictive high-fidelity multiphysics simulations are crucial to fully leverage this geometric flexibility. Qualification and regulator acceptance ultimately determine the breadth and scope of applications for these technologies. The US Department of Energy Office of Nuclear Energy Transformational Challenge Reactor program integrates many of these elements to accelerate the deployment of additive manufacturing technologies to industry.
Betzler, Benjamin↗
How to Decarbonize Our Energy Systems: Process‐Informed Design of New Materials for Carbon Capture
Decarbonisation from a variety of industrial and power emission sectors highlights a marked need for capture technologies that can be optimized for different CO 2 sources and integrated into an equally diverse range of applications of captured CO 2 as a feedstock. Some capture technologies are already operated at an industrial scale but may not be optimal for all required applications. Advanced tailored sorbent-based technologies allow flexible operation and reduced costs as they offer higher capture capacities and significantly lower energy penalties than the state-of-the-art systems. To accelerate the discovery, development, and deployment of novel advanced materials, it is critically important that efforts between experimentalists, theoreticians, and process engineers are coordinated. The PrISMa project addresses this challenge by integrating materials design with process design and environmental considerations to allow for tailor-making carbon capture solutions optimally tuned for local sources and sinks. In this article, we highlight some of the recent results obtained with the PrISMa platform.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
2020 Exascale Computing Project Annual Meeting (Executive Summary Report)
The Exascale Computing Project (ECP) delivers specific applications, software products, and outcomes on DOE computing facilities. Integration across these elements for specific hardware technologies for exascale system instantiations is fundamental to ECP success. The outcome of the ECP is the delivery of a capable exascale computing ecosystem to provide breakthrough solutions addressing our most critical challenges in scientific discovery, energy assurance, economic competitiveness, and national security. This outcome is not a matter of ensuring more powerful computing systems. The ECP is designed to create more valuable and rapid insights from a wide variety of applications (“capable”), which requires a much higher level of inherent efficacy in all methods, software tools, and ECP-enabled computing technologies to be acquired by DOE laboratories (“ecosystem”). The ECP annual meeting provides a unique opportunity for the core technical expertise in the United States focused on achieving this next plateau of computational science and computing performance to engage in direct discussions on project execution. Face-to-face gatherings in technical communities like this are common and needed for the exchange of scientific ideas and technical performance. The ECP annual meeting stands apart from other technical conferences and meetings in the computing community as it is uniquely and solely focused on the execution of the ECP and the integration of technical activities leading to the creation of the exascale computing ecosystem for the future. The direct interaction of key critical technical staff, who are leaders in their respective fields, and the resulting give-and-take between software, applications, and hardware and the technical co-design therein, is unique and essential to the effective execution of the ECP. The first annual meeting was held in Knoxville, Tennessee, January 31 – February 2, 2017 and brought together, for the first time, a diverse collection of researchers from 16 DOE national laboratories as well as university computer and computational science researchers to discuss shared problems and joint solutions for the development of a capable exascale computing ecosystem. These interactions resulted in focused technical plans and an energized community centered on advances for ECP. The second annual meeting was held in Knoxville, Tennessee, February 5–9, 2018. It included 643 individual thought leaders and performers in application development, software research and deployment, and hardware research and integrators, all of whom are part of the multifaceted, billion dollar HPC community. This meeting provided a platform to discuss and disseminate numerous examples where researchers with common goals and synergistic solutions came together for the first time to deliver tangible results. Additionally, at the 2018 meeting, ECP researchers had the opportunity to digest all US HPC vendor R&D product roadmaps pointing to exascale – not only to learn how their research can play a role, but, more importantly, to influence those roadmaps to ensure successful delivery on DOE applications that will contribute to (if not solve) problems of national interest in national security, science, energy, and health, as well as growing security threats. The third annual meeting was held in Houston, Texas, January 14–17, 2019. With a 19% increase in the number of registrations (768 people), and the change in location, the third annual meeting was considered the most impactful of the three at the time. The new website provided a better platform for the dissemination of the content, the new venue as a meeting hotel instead of a conference center facilitated interactions and discussions after event hours, and the addition of an award-winning mobile event conference app (Whova) transformed dramatically the attendee experience at the event. This fourth annual meeting was held in Houston, Texas, February 3-7, 2020. This meeting had an increase in the number of attendees for a total of 824 people registered (782 attendees) and included numerous enhancements based on feedback and lessons learned from previous meetings, some of which are listed here: Improved quality of the sessions, their material and the whole program.; Had more industry participation and addition of external collaborators from overseas.; Published the full agenda earlier to better accommodate attendance and travel plans based on schedule.; Centralized all sessions in one venue.; Provided additional hotels and room blocks for the attendees.; Improved communication with the audience (links, material, directions, notifications, etc.) to go paperless.; Enhanced side meeting scheduling, management and user experience.; Made available additional space and tables for impromptu meetings and side discussions.; Improved IT and A/V solutions for speakers. In addition, our final survey captured the following points as opportunities for improvement in future meetings: consider a different meeting location that is more pedestrian friendly, reduce talks during working meals to allow more collaboration and informal time, adapt the agenda to acknowledge attendees from different timezones, consider recording some of the tutorials and/or sessions to share broadly with the HPC community, have a larger poster room, provide additional power strips, and improve the WiFi.
97 MATHEMATICS AND COMPUTING↗
Assessing Low-Temperature Geothermal Play Types: Relevant Data and Play Fairway Analysis Methods
This data catalog contains information on low temperature geothermal play types. The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) supports the Geothermal Heating and Cooling Geospatial Datasets and Analysis project, conducted by the National Renewable Energy Laboratory (NREL). This project is part of a broader effort to demonstrate the multifaceted value of integrating geothermal power and geothermal heating and cooling technologies into national decarbonization strategies and community energy plans. There is a need to establish baseline low-temperature geothermal resource data sets and evaluate methods for deploying these technologies. This project aims to reduce exploration risk of low temperature geothermal systems by collecting baseline datasets that can be used for Play Fairway Analysis methodologies. This data catalog contains links to publicly available datasets from different sources that can be relevant for the low temperature geothermal systems. This submission contains data catalogs for Alaska, Hawaii, and the Conterminous United States, as well as a technical report on the methods used to classify and asses the geothermal play types.
15 GEOTHERMAL ENERGY↗
Modular Staged Pressurized Oxy-Combustion (SPOC) Power Plant for Coal and Biomass – Integration of Combustor Boiler and DCC
Critical to the future of power generation is the development of a power plant that will be capable of flexible operation to meet the needs of the modern grid, providing resilient, low-emissions power to a grid that is increasingly seeing a large penetration of intermittent wind and solar. The modular Staged, Pressurized Oxy-Combustion (SPOC) process envisioned by and under development at Washington University in St. Louis (WUSTL) has the potential to achieve these goals. The process offers: 1) a modular plant design for improved operational flexibility; 2) fuel-staging combined with pressurized oxy-combustion, which leads to smaller plant size, higher plant efficiency, and lower cost for pollutant and greenhouse gas removal compared with traditional carbon-capture equipped coal power plants; and 3) small modular boilers and pollutant removal units that can be fabricated in shop and assembled on site, further reducing plant capital costs. Under DOE's support (DE-FE0031925), WUSTL is advancing the development of the critical components for the SPOC power plant, including the integrated combustion system and the direct contact cooler (DCC) from Technology Readiness Level (TRL) 4 to TRL-5, which would allow these technologies to be subsequently incorporated into a pilot plant. This talk will present an overview of the SPOC technology, CFD modeling and validation for burner and boiler development, and recent results to evaluate critical components for system integration needed to advance its TRL.
Magalhaes, Duarte↗
Recent Advances in Machine Learning for Fiber Optic Sensor Applications
Over the last three decades, fiber optic sensors (FOS) have gained a lot of attention for their wide range of monitoring applications across many industries, including aerospace, defense, security, civil engineering, and energy. FOS technologies hold great promise to form the backbone for next‐generation intelligent sensing platforms that offer long‐distance, high‐accuracy, distributed measurement capabilities and multiparametric monitoring with resilience to harsh environmental conditions. The major limitations posed by FOS are 1) cross‐sensitivity, 2) enormous volume and large data generation, 3) low data processing speed, 4) degradation of signal‐to‐noise ratio over the fiber length, and 5) overall cost of sensor and interrogator systems. These challenges can be overcome by building advanced data analytics engines enabled by recent breakthroughs in machine learning (ML) and artificial intelligence (AI). This article presents a comprehensive review of recent studies that integrate ML and AI algorithms with FOS technologies. This review also highlights several FOS technology development directions that promise a significant impact on widespread use for several industrial applications, with an emphasis on energy systems monitoring. A perspective on future directions for further research development is also provided.
97 MATHEMATICS AND COMPUTING↗
Energy Systems Integration Facility (ESIF): World-Class Systems Integration Capabilities and Research
The Energy Systems Integration Facility (ESIF), located at the National Renewable Energy Laboratory (NREL) South Table Mountain campus, is a world-renowned user facility for research and development of modern, advanced, and clean energy technologies. ESIF is distinguished by its continuously evolving, highly integrated systems that span throughout the building, connecting research capabilities across multiple laboratories and test areas. The primary ESIF research systems include: [1] data, cyber, and control networks, [2] research electrical distribution buses (REDB), [3] thermal integration infrastructure, and [4] hydrogen systems. The data, cyber, and control networks provide monitoring, control, communication, automation, visualization, and time series data storage and tagging capabilities for research projects and ESIF systems, including facility safety functions. The REDB system consists of four dedicated AC and DC electrical power networks that can connect devices located across the facility through versatile, automatic circuit configuration to support complex power electronics experiments up to the megawatt-scale. The thermal integration infrastructure consists of three temperature-conditioned water loops that provide heating and cooling interfaces and capabilities for thermal energy research. The hydrogen systems provide megawatt-scale hydrogen production, drying, compression, high-pressure storage, and delivery to laboratory end uses, including hydrogen fuel cell vehicle fueling. The ESIF research systems interconnect and extend throughout the various lab areas of the facility to create elaborate networks composed of diverse technologies for cutting-edge research. The ESIF capabilities are operated and stewarded by the ESIF Research Operations group, who also actively upgrade and advance the systems to ensure they remain ahead of anticipated research - enabling the success of many pioneering energy integration projects. The poster, created by members of the ESIF Research Operations team, highlights and summarizes the four core integrated systems at ESIF. The poster was first presented at the internal NREL Energize Forum on May 13th, 2024, and received the "Best Poster" award.
capabilities↗
Integrated Energy Systems: 2020 Roadmap
This roadmap defines potential industrial scale integrated energy systems (IES) and identifies key technology gaps to achieving commercial deployment of such systems. IES under consideration could include multiple energy generation resources and energy use paths, with a focus on low-emission technologies, such as nuclear and renewable generators. Together these technologies provide affordable, reliable, and resilient energy while simultaneously reducing environmental emission of CO 2 and greenhouse gases (GHGs). System design and optimization would consider both technical performance and economic viability within various deployment markets.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration
Wearable silicone wristbands are a rapidly growing exposure assessment technology that offer researchers the ability to study previously inaccessible cohorts and have the potential to provide a more comprehensive picture of chemical exposure within diverse communities. However, there are no established best practices for analyzing the data within a study or across multiple studies, thereby limiting impact and access of these data for larger meta-analyses. We utilize data from three studies, from over 600 wristbands worn by participants in New York City and Eugene, Oregon, to present a first-of-its-kind manuscript detailing wristband data properties. We further discuss and provide concrete examples of key areas and considerations in common statistical modeling methods where best practices must be established to enable meta-analyses and integration of data from multiple studies. Finally, we detail important and challenging aspects of machine learning, meta-analysis, and data integration that researchers will face in order to extend beyond the limited scope of individual studies focused on specific populations.
Bramer, Lisa M.↗
Data to Accompany: Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration
Wearable silicone wristbands are a rapidly growing exposure assessment technology that offer researchers the ability to study previously inaccessible cohorts and have the potential to provide a more comprehensive picture of chemical exposure within diverse communities. However, there are no established best practices for analyzing the data within a study or across multiple studies, thereby limiting impact and access of these data for larger meta-analyses. We utilize data from three studies, from over 600 wristbands worn by participants in New York City and Eugene, Oregon, to present a first-of-its-kind manuscript detailing wristband data properties. We further discuss and provide concrete examples of key areas and considerations in common statistical modeling methods where best practices must be established to enable meta-analyses and integration of data from multiple studies. Finally, we detail important and challenging aspects of machine learning, meta-analysis, and data integration that researchers will face in order to extend beyond the limited scope of individual studies focused on specific populations.
Bramer, Lisa M↗
Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL
The clean energy transformation includes the integration of distributed energy resources with the power grid, which has led to a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Power grids infrastructure represents an operational technology environment that has become a system of systems, integrating heterogeneous devices which are both software-and hardware-intensive; as a result, there are increasing demands to exploit advances in the commodity of software-hardware infrastructures to improve energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, which leads to vulnerabilities and undesirable outcomes. The use of formal methods to characterize and prove system requirements removes ambiguity, increases automation, and provides high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system-level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.
formal methods↗
Understanding Reliability Trade-Offs in 1T-nC and 2T-nC FeRAM Designs
Ferroelectric random access memory (FeRAM) is a promising candidate for energy-efficient nonvolatile memory, particularly for logic-in-memory and compute-in-memory (CIM) applications. Among the available cell architectures, One-Transistor–n-Capacitor (1T-nC) and two-transistor–n-capacitor (2T-nC) FeRAMs each offer distinct trade-offs in density, scalability, and reliability. In this work, we present a comparative study of these two architectures under both dimensional scaling ( XY/Z shrinkage) and vertical integration (increasing stacked capacitors per cell). Using technology computer-aided design (TCAD) and circuit-level simulations, we analyze how scaling impacts ferroelectric capacitance, parasitic coupling, and floating-node (FN) dynamics, which together dictate sense margin (SM) and read stability. A key mitigation strategy—floating unselected capacitors—is applied to both architectures, effectively decoupling the SM from the number of stacked capacitors and enabling tractable analysis across scaling regimes. Results show that 1T-nC suffers more from charge sharing with the bitline (BL), while 2T-nC benefits from transistor isolation and stronger low-voltage sensing at the cost of increased area. By systematically evaluating these behaviors across scaling directions, this work establishes the reliability trade-offs of 1T-nC and 2T-nC cells and provides design guidelines for high-density, vertically integrated FeRAM systems.
1T-nC↗
A Sub-Threshold Low-Power Integrated Bandpass Filter for Highly-Integrated Spectrum Analyzers
Low-power analog filter banks provide frequency analysis with minimal power and space requirements, making them viable solutions for integrated remote audio- and vibration-sensing applications. Compared with their digital counterparts, analog filter banks are better suited to achieve the lower power consumption necessary for IoT applications. In this work, the design and implementation of a sub-threshold complementary metal-oxide semiconductor (CMOS) integrated low-power tunable bandpass filter channel for signal spectrum analysis and signal discrimination is presented, including performance improvements to stability and precise matching between filter stages. The 8 th -order filter channel achieves an effective Q-factor of 4.5 and dynamic range of 60 dB, has an operational frequency range from 2 kHz to 100 kHz, and consumes 256 µW nominally at the highest center frequency. An integrated analog Gm-C filter topology is selected for this application. Functionally, the high-Q bandpass filter transfer function is implemented via four cascaded 2 nd -order filter cells and is fabricated in 130-nm 1.2-V CMOS technology, making it suitable for use in monolithic integrated spectral analysis (MISA) applications.
Long, Gavin↗
CeTaN 3 and CeNbN 3 : Prospective Nitride Perovskites with Optimal Photovoltaic Band Gaps
Perovskites constitute an exceptionally tunable materials family with diverse applications in electronics, optoelectronics, energy, and quantum technologies. Out of the thousands of known perovskites, the majority of compounds are oxides, halides, and chalcogenides. In contrast, only two nitride perovskites are currently known. In this work we perform a thorough ab initio computational screening of possible nitride perovskites, and we identify two new compounds, CeNbN 3 and CeTaN 3 , with band gaps in the near-infrared to visible range, depending on temperature. In their room-temperature orthorhombic phase, we predict that both compounds exhibit direct or quasidirect band gaps in the range 1.1–2.0 eV, with the Pnma phases matching the Shockley–Queisser limit for photovoltaic energy conversion efficiency. Further, these compounds are also predicted to be strong light absorbers, with absorption coefficients surpassing those of high-performance semiconductors such as GaAs and CH 3 NH 3 PbI 3 . The present findings reveal a potentially new class of nitride semiconductors with promise for electronics, optoelectronics, and light harvesting and for integration with existing nitride-based lighting technology.
36 MATERIALS SCIENCE↗
A Review of Quantum Computing Technologies in Power System Optimization
As modern power grids increasingly integrate variable renewable generation, distributed energy resources, and energy storage systems, classical optimization techniques are facing unprecedented challenges. This review examines the emerging application of quantum computing to overcome these challenges in power system optimization, including optimal power flow (OPF), unit commitment (UC), economic dispatch (ED), and intelligent switching and topology optimization (IS-TO). Recent research has introduced various quantum methodologies—such as gate-based, annealing-based, variational algorithms, and quantum-inspired algorithms—to address the combinatorial complexity inherent in grid reconfiguration and energy management. The review summaries the quantum algorithms, quantum devices and the power system test cases, highlighting hybrid quantum–classical strategies that leverage the complementary strengths of both paradigms. Some quantum advantages have been observed, including theoretical speedup, accurate simulation results, scalable qubit usage, efficient QUBO mapping. In particular, the review emphasizes the importance of integrating quantum optimization techniques with classical control frameworks, these hybrid approaches demonstrate the potential to improve real-time grid management and operational reliability. A significant portion of the analysis is devoted to the practical limitations of current quantum devices. Present-day quantum hardware, operating in the noisy intermediate-scale quantum (NISQ) era, remains highly sensitive to noise and limited in qubit connectivity, which constrains the scale and accuracy of implemented algorithms. The review delves into specific challenges such as the need for qubit-efficient encoding techniques and error mitigation strategies that are critical for handling real-world grid optimization problems. In addition, the work draws attention to the performance discrepancies between theoretical quantum speedups and experimental validations, underscoring the importance of rigorous benchmark studies using representative power grid test cases. In summary, this review highlights both the promise and limitations of quantum computing for power system optimization. It provides a comprehensive overview of the state-of-the-art technologies, categorizes recent advancements in algorithm design, and discusses practical considerations for implementation, and serves as an informative resource on current research. Future research directions include developing robust hybrid frameworks, advancing qubit-efficient formulations, and scaling up experimental demonstrations to confirm the theoretical advantages of quantum methods in large-scale power system operations.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Developing and Demonstrating Nuclear-based Integrated Energy Systems
Overview of the DOE Office of Nuclear Energy program for integrated energy systems in support of the MARVEL technology review (October 19-20, 2022).
08 HYDROGEN↗