Search NASA⌕ Search

SEARCH · Search NASA

Results for “advanced mitigation process”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Recent Advances in Assessing Environmental Effects of Marine Renewable Energy Around the World

Marine renewable energy (MRE) is increasingly of interest to coastal nations as a source of renewable energy that can support climate change mitigation goals as well as provide secure locally-produced energy for coastal and island communities. MRE extracts power from tidal streams, waves, ocean currents, run of rivers, and gradients in the ocean, with specialized devices developed and tested for each energy resource. Alongside development of MRE technologies and systems, first in Europe and then in North America, Australia, Asia, and other regions, it has been universally recognized that there is also a need to examine potential effects on marine animals, habitats, ecosystem processes, local communities and other sea users, to ensure that the MRE industry can be developed in a responsible and sustainable manner. This paper looks at the status of assessment and monitoring for potential environmental effects associated with MRE projects around the world. Over 80 projects were identified worldwide as having been tested, demonstrated, or commercially deployed with associated environmental monitoring. Five of the projects that represent tidal stream, wave, and run of river projects are examined in more detail to determine the types of data and information collected for those projects, the outputs of the monitoring campaigns, and the actions taken as a result of the data collection and analysis. Recommendations are provided for standardization of the monitoring approaches, instruments, and analysis methods at MRE project sites worldwide.

marine renewable energy, environmental effects, ri↗
DOE OSTI2024

Acid Etching‐Driven Self‐Assembly of Mn‐Shell Inducing Rock‐Salt Phase for Enhanced Single‐Crystal Ni‐Rich Cathodes

With the wide adoption of Li‐ion batteries, Ni‐rich cathode is considered as one of the most promising candidates of cathodes due to its high energy density and low cost. However, stability decreased with increasing Ni content in the Ni‐rich cathode. To solve this bottleneck, many strategies, such as coating, doping, surface modification, and special morphologies, have been developed. Herein, we introduce a groundbreaking approach for enhancing Ni‐rich cathode through an innovative acid etching process that promotes Mn shell self‐assembly, inducing a rock‐salt phase on the surface. This method not only simplifies the Ni‐rich cathode modification process, but also significantly improves the structural stability and electrochemical performance of Ni‐rich cathode. Our findings demonstrate that developed single‐crystal Ni‐rich cathode shows 3–34 % better stability compared to both commercial modified Ni‐rich cathode and unmodified counterparts. The unique Mn shell effectively mitigates reversible phase shifts during cycling, contributing to a remarkable enhancement in cycling stability. Additionally, this novel fabrication technique paves the way for cost‐effective production of high‐performance cathode materials, offering substantial benefits for lithium‐ion battery technology. And this study proves the potential of this method in advancing the design and development of durable, high‐capacity cathode materials for next‐generation batteries.

Ni-rich cathode↗
DOE OSTI2023

An Integrated Framework for Risk Assessment of Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology Refinement and Exploration

This report documents activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2023 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective, and secure DI&C technologies for digital upgrades/designs. A risk assessment-informed framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk informed capability to quantitatively estimate the safety margin obtained from plant modernization, especially for safety-related DI&C systems, (2) support and supplement existing risk informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of safety-related DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the LWRS-developed framework provides a means to address relevant technical issues by: (1) defining a risk informed analysis process for DI&C upgrade that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies in nuclear power plants (NPPs). Adding diversity within a system or components is the primary means to eliminate and mitigate CCFs, but diversity also increases system complexity and may not address all sources of systematic failures. Optimization of diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in safety-related DI&C systems of NPPs and supporting relevant design optimization, the proposed framework provides: (a) A best-estimate, risk informed capability to address new technical digital issues quantitatively, focusing on software CCFs in safety-related DI&C systems of NPPs; (b) A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to predict and prevent risk in the early design stage of DI&C systems; (c) Technical bases and risk informed insights to assist users address the risk informed alternatives for evaluation of CCFs in safety-related DI&C systems of NPPs; and (d) A risk informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The research and development efforts of this project in FY 2023 are focused on refining current methods on software CCF modeling and estimation and exploring additional innovative approaches to risk assessment of DI&C systems to enable a more comprehensive and complete assessment of various safety-related DI&C design architectures. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists. It should be noted that all the analyses are performed for the demonstration of the methodology, not for the evaluation of an actual digital control system. Results are obtained based on limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Evaluating the Nation's Pipeline Infrastructure with NETL's Advanced Infrastructure Integrity Model (AIIM)

This poster is a part of BIL-EDX4CCS Task 36: Advanced Infrastructure Integrity Modeling to Evaluate Existing Energy Infrastructure Reusability and Risk, the goal of which is to produce a smart tool that will assess existing energy infrastructure reusability and risk using the Advanced Infrastructure Integrity Model (AIIM). This model forecasts lifespan and potential risk using a multitude of factors such as incidents reports, structural characteristics, and the surrounding environment. The project aims to provide scientific insights for a better understanding of carbon storage (CS), potential to support CS stakeholder needs, national decarbonization, and mitigating climate change. AIIM will utilize an energy infrastructure database as its input, developed by acquiring publicly available data as well as NETL derived products. These resources include incidents, geohazards, and infrastructure variables. Soil data in the form of rasters and pipeline incident reports were processed and a script was developed to count the number of times features such as roads, railroads, and rivers intersected with pipeline segments which were then converted to points. Distance to oil and natural gas wells, petroleum ports, intermodal freight facilities, and geologic structures were also calculated. After data preparation and quality control was completed, the data was integrated into the pipeline points. Once models are complete, a smart tool will be created in the form of an online dashboard.

Malay, Caleb↗
DOE OSTI2025

Carbon mineralization pathways in interfacial adsorbed water nanofilms

Carbon mineralization in humidified carbon dioxide offers a promising route to mitigate anthropogenic emissions in a world stressed by water security. Despite its technological importance, our understanding of carbonation in water-poor environments lags, as traditional dissolution-precipitation pathways struggle to explain the adsorbed water nanofilm-mediated reactivity. Here, we utilize in operando X-ray diffraction (XRD) and advanced molecular simulations to investigate nanoconfined reactions driving forsterite carbonation, the magnesium-rich olivine. By examining magnesium ion dissolution and transport in atomistic simulations of the forsterite-water-carbon dioxide interface and comparing these with the in operando XRD activation energies, we identify both processes as rate-limiting at saturation. Our simulations reveal a mechanistic view of interfacial carbonation, where dissolution and precipitation are mediated by anomalous quasi two-dimensional diffusion. The transport process involves intermittent diffusive hopping in the desorbed state, separated by crawling events that are spatially short but temporally long. This understanding transcends carbon mineralization, with implications for understanding the transport of contaminants in geosystems, the design of multifunctional materials, water desalination, and molecular recognition systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Fermilab Booster loss modelling and rebalancing using Bayesian methods

Fermilab Booster is being upgraded for the PIP-II project to support 20Hz ramp rate at higher intensities. Loss trip limits determine the achievable peak power. To meet PIP-II requirements, losses need to be halved as compared to current levels. Losses primarily occur at injection and transition crossing, with both gradually increasing and threshold-like intensity-dependent behaviors. The existing simulation models are not yet good enough for quantitative loss predictions. In practice, it will be necessary to tune up the Booster using iterative methods and operator intuition. In this paper we present an effort to systematically model Booster losses using active learning (Bayesian exploration) techniques, and subsequently to rebalance them for higher trip limit margins. We first created several sets of spatially and temporally isolated orbit and optics knobs, and trained Gaussian process models for each beam loss monitor as well as beam current. This is a complex task due to safety and timing requirements – we discuss mitigations such as uncertainty constraints and approximate fitting. Once models are stable, we perform large-scale single and multi-objective tuning using scalarized objectives made up of critical beam loss locations. Our results demonstrate significant rebalancing of losses, increasing trip margins, as well as an overall improvement in beam transmission efficiency. We are exploring how to combine existing simulations with experimental data and automate the collection procedure so that more advanced surrogate models can be created over time.

Kuklev, Nikita [Fermilab]↗
DOE OSTI2022

Snowmass Instrumentation Frontier IF08 Topical Group Report: Noble Element Detectors

Particle detectors making use of noble elements in gaseous, liquid, or solid phases are prevalent in neutrino and dark matter experiments and are also used to a lesser extent in collider-based particle physics experiments. These experiments take advantage of both the very large, ultra-pure target volumes achievable and the multiple observable signal pathways possible in noble-element based particle detectors. As these experiments seek to increase their sensitivity, novel and improved technologies will be needed to enhance the precision of their measurements and to broaden the reach of their physics programs. The areas of R&D in noble element instrumentation that have been identified by the HEP community in the Snowmass process are highlighted by five key messages: IF08-1) Enhance and combine existing modalities (scintillation and electron drift) to increase signal-to-noise and reconstruction fidelity; IF08-2) Develop new modalities for signal detection in noble elements, including methods based on ion drift, metastable fluids, solid-phase detectors and dissolved targets. Collaborative and blue-sky R&D should also be supported to enable advances in this area; IF08-3) Improve the understanding of detector microphysics and calibrate detector response in new signal regimes; IF08-4) Address challenges in scaling technologies, including material purification, background mitigation, large-area readout, and magnetization; and IF08-5) Train the next generation of researchers, using fast-turnaround instrumentation projects to provide the design-through-result training no longer possible in very-large-scale experiments. This topical group report identifies and documents recent developments and future needs for noble element detector technologies. In addition, we highlight the opportunity that this area of research provides for continued training of the next generation of scientists.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Risk Analysis of Various Design Architectures for High Safety-significant Safety-related Digital Instrumentation and Control Systems of Nuclear Power Plants during Accident Scenarios

This report documents the plus-up activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2022 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades/designs. An integrated risk assessment technology for the DI&C systems was proposed for this strategy, which aims to (1) provide a best-estimate, risk-informed capability to quantitatively and accurately estimate the safety margin obtained from plant modernization, especially for the high safety-significant safety-related (HSSSR) DI&C systems, (2) support and supplement existing advanced risk-informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems to support system design decisions and diversity and redundancy applications, (4) assure the long-term safety and reliability of HSSSR DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals and deal with the expensive licensing justifications from regulatory insights, the LWRS-developed framework instructs nuclear vendors and utilities on how to effectively lower the costs associated with digital compliance and speed industry advances by: (1) defining an integrated risk-informed analysis process for DI&C upgrade, including hazard analysis, reliability analysis, and consequence analysis, (2) applying systematic and risk-informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development, licensing, and deployment of advanced DI&C technologies on nuclear power plant (NPPs). Adding diversity within system or components is the main means to eliminate and mitigate CCFs, but diversity also increases plant complexity and errors and may not address all sources of systematic failures. How to optimize the diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in HSSSR DI&C systems of NPPs and supporting relevant design optimization, the framework provides: ? An integrated best-estimate, risk-informed capability to address new technical digital issues quantitatively, accurately, and efficiently in plan modernization progress, such as software CCFs in HSSSR DI&C systems of NPPs ? A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to efficiently predict and prevent risk in the early design stage of DI&C systems ? Technical bases and risk-informed insights to assist U.S. Nuclear Regulatory Commission (NRC) and industry to address and fulfill the risk-informed alternatives for evaluation of CCFs in HSSSR DI&C systems of NPPs ? An integrated risk-informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The plus-up research and development efforts of this project in FY 2022 are focused on methodology improvement of software CCF modeling and estimation, prevention analysis, importance analysis and risk analysis of various design architectures of HSSSR DI&C systems. This work greatly enhances the capability of the LWRS-developed framework for the risk assessment and design optimization of safety-critical DI&C systems. It should be noted that all the analyses are performed for the demonstration of the LWRS-developed framework, not for the evaluation of relevant systems. Results are obtained based on very limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

HPDR: High-Performance Portable Scientific Data Reduction Framework

The rapid growth in scientific data generation is outpacing advancements in computing systems necessary for efficient storage, transfer, and analysis, particularly in the context of exascale computing. With the deployment of first-generation exascale computing systems and next-generation experimental facilities, this gap is widening and necessitates effective data reduction techniques to manage enormous data volumes. Over the past decade, various data reduction methods, including lossless compression, error-controlled lossy compression, and data refactoring, have been developed to accelerate I/O in scientific workflows. Despite significant reductions in data volume, these methods introduce considerable computational overhead, which can become the new bottleneck in data processing. To mitigate this, GPU-accelerated data reduction algorithms have been introduced. However, challenges remain in their integration into exascale workflows, including limited portability across different GPU architectures, substantial memory transfer overhead, and reduced scalability on dense multi-GPU systems. To address these challenges, we propose HPDR, a high-performance and portable data reduction framework. HPDR is designed to enable the execution of state-of-the-art reduction algorithms across diverse processor architectures while reducing memory transfer overhead to 2.3 % of the original, resulting in up to 3.5× faster throughput compared to existing solutions. It also achieves up to 96% of the theoretical speedup in multi-GPU settings. In addition, evaluations on accelerating I/O operations at scale up to 1,024 nodes of the Frontier supercomputer demonstrate that HPDR can achieve up to 103 TB/s reduction throughput, providing up to 4× acceleration in parallel I/O performance compared to existing data reduction routines. This work highlights the potential of HPDR to significantly enhance data reduction efficiency in exascale computing environments.

Chen, Jieyang [University of Oregon]↗
DOE OSTI2020

Co-op at Sandia National Laboratories (July - December 2019, Final Report)

This co-op was performed at Sandia National Laboratories (SNL) within the Weapon Surety Engineering 11 Department (9435), which is a customer-focused organization that provides engineering and system analysis expertise to ensure a safe deterrent throughout the entire weapon lifecycle. Engineers in 9435 develop a deep knowledge in both component and system function to support rigorous evaluation and mitigation of potential failure modes. They operate across multiple engineering disciplines (mechanical, electrical, computer, materials and systems engineering) with opportunities to develop crossdisciplinary capability. The team supports a variety of stockpile systems and is part of the product teams during development, design and production, as well as advanced concept and exploratory efforts. 9435 engineers use their extensive component and system knowledge, as well as experimental data and modeling, to ensure products function as intended with assured safety. Members of the department learn the function of multiple components, how those components integrate within the system and apply surety principles and processes to ensure a safe, secure, reliable, and effective U.S. nuclear deterrent.

42 ENGINEERING↗
DOE OSTI2022

Trade-off Analysis of Operational Technologies to Advance Cyber Resilience through Automated and Autonomous Response to Threats

The advancement of cyber resilience requires a preliminary stage of characterizing the trade-off space of mitigation options and how these might affect the stability and determinism of an operational technology (OT). This first step will set the stage for the proper cyber-secure and cyber-resilient design and confirm the affects that can be considered and approved by the OT and the security groups. To provide a baseline for this discussion, this paper provides a consideration of the cyberphysical interactions, possible mitigation steps against certain attacks and their corresponding affects that lend to the security design planning and evaluation process. As an integral part of the proposed scheme this work introduces the concept of systemwide fuzzer, i.e., a tool that manipulates the system state in an effort to determine mitigation response sequences that minimize detriments and maximize benefit in accordance with specified operational requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

NREL Hydrogen Sensor Testing Laboratory

Relevance: Detection is recognized as a critical element for hydrogen facility safety design and supports risk mitigation. Detection methodologies will support validation of H2 behavior research. Hydrogen point sensors play a critical role for safety and process monitoring, but other methodologies can be developed. Approach: NREL Sensor Laboratory tests and verifies sensor performance for manufacturers, developers, end-users, regulatory agencies and SDOs/CDOs NREL deployment activity supports regulatory requirement verification, hydrogen behavior models, and method development for use by stakeholders. Accomplishments and Progress: NREL's R&D accomplishments have supported developers, industry, and SDOs by providing sensor performance and deployment expertise not otherwise available. Development of alternative detection strategies for hydrogen applications have been initiated. HyWAM and advanced detection methodologies deployments at H2@Scale Facilities are being implemented. Collaborations: Collaboration with government laboratories, universities, private organizations and regulatory agencies has leveraged the NREL Sensor Laboratory's success in advancing hydrogen safety sensors and process control. Proposed Future Work: NREL will support hydrogen deployment by the proper implementation of hydrogen sensors and advanced detection strategies. NREL will continue to support science-based codes and standards. This effort will be guided by the needs of the hydrogen community.

codes and standards↗
DOE OSTI2024

AI-Driven Crack Detection for Remanufacturing Cylinder Heads Using Deep Learning and Engineering-Informed Data Augmentation

Detecting cracks in cylinder heads traditionally relies on manual inspection, which is time-consuming and susceptible to human error. As an alternative, automated object detection utilizing computer vision and machine learning models has been explored. However, these methods often face challenges due to a lack of sufficiently annotated training data, limited image diversity, and the inherently small size of cracks. Addressing these constraints, this paper introduces a novel automated crack-detection method that enhances data availability through a synthetic data generation technique. Unlike general data augmentation practices, our method involves copying cracks from one location to another, guided by both random and informed engineering decisions about likely crack formations due to cyclic thermomechanical loads. The innovative aspect of our approach lies in the integration of domain-specific engineering knowledge into the synthetic generation process, which substantially improves detection accuracy. We evaluate our method’s effectiveness using two metrics: the F2 score, which emphasizes recall to prioritize detecting all potential cracks, and mean average precision (MAP), a standard measure in object detection. Experimental results demonstrate that, without engineering insights, our method increases the F2 score from 0.40 to 0.65, while maintaining a stable MAP. Incorporating detailed engineering knowledge further enhances the F2 score to 0.70 and improves MAP to 0.57, representing increases of 63% and 43%, respectively. These results confirm that our approach not only mitigates the limitations of traditional data augmentation but also significantly advances the reliability and precision of crack detection in industrial settings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Properties of Nb x Ti (1–x) N thin films deposited on 300 mm silicon wafers for upscaling superconducting digital circuits

Scaling superconducting digital circuits requires fundamental changes in the current material set and fabrication process. The transition to 300 mm wafers and the implementation of advanced lithography are instrumental in facilitating mature CMOS processes, ensuring uniformity, and optimizing the yield. Here, this study explores the properties of Nb x Ti (1–x) N films fabricated by magnetron DC sputtering on 300 mm Si wafers. As a promising alternative to traditional Nb in device manufacturing, Nb x Ti (1–x) N offers numerous advantages, including enhanced stability and scalability to smaller dimensions, in both processing and design. As a ternary material, Nb x Ti (1–x) N allows engineering material parameters by changing deposition conditions. The engineered properties can be used to modulate device parameters through the stack and mitigate failure modes. We report characterization of Nb x Ti (1–x) N films at less than 2% thickness variability, 2.4% T c variability and 3% composition variability. Film resistivity (140–375 Ωcm) shows a strong correlation with the film oxygen content, while the critical temperature T c (4.6 K–14.1 K) is strongly affected by film stoichiometry and its microstructure has only a moderate effect on modifying T c . Our results offer insights about the interplay between film stoichiometry, film microstructure and critical temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Breakthrough innovations in carbon dioxide mineralization for a sustainable future

Greenhouse gas emissions and climate change concerns have prompted worldwide initiatives to lower carbon dioxide (CO 2 ) levels and prevent them from rising in the atmosphere, thereby controlling global warming. Effective CO 2 management through carbon capture and storage is essential for safe and permanent storage, as well as synchronically meeting carbon reduction targets. Lowering CO 2 emissions through carbon utilization can develop a wide range of new businesses for energy security, material production, and sustainability. CO 2 mineralization is one of the most promising strategies for producing thermodynamically stable solid calcium or magnesium carbonates for long-term sequestration using simple chemical reactions. Current advancements in CO 2 mineralization technologies, focusing on pathways and mechanisms using different industrial solid wastes, including natural minerals as feedstocks, are briefly discussed. However, the operating costs, energy consumption, reaction rates, and material management are major barriers to the application of these technologies in CO 2 mineralization. Further, the optimization of operating parameters, tailor-made equipment, and smooth supply of waste feedstocks require more attention to make the carbon mineralization process economically and commercially viable. Here, carbonation mechanisms, technological options to expedite mineral carbonation, environmental impacts, and prospects of CO 2 mineralization technologies are critically evaluated to suggest a pathway for mitigating climate change in the future. The integration of industrial wastes and brine with the CO 2 mineralization process can unlock its potential for the development of novel chemical pathways for the synthesis of calcium or magnesium carbonates, valuable metal recovery, and contribution to sustainability goals while reducing the impact of global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Economic solution for low carbon process heat: A horizontal, compact high temperature gas reactor

In 2018, nuclear energy generated 55% of United States’ and one third of the world’s carbon free electricity, making nuclear energy a key tool in efforts to mitigate climate change before 2050. However, the current nuclear technology, light water reactors (LWRs), is limited to 300°C, so it cannot be used to decarbonize industrial process heat which accounts for 12% of US greenhouse gas emissions. High temperature gas reactors (HTGRs) can meet the high temperature demand with carbon free nuclear heat. The estimated cost of HTGRs, such as the Next Generation Nuclear Plant (NGNP), are even higher than state-of-the-art LWRs. In this paper, we expanded our nuclear cost estimating tool to include HTGRs and find that the NGNP overnight capital costs were 32% higher than an advanced LWR per unit capacity. The higher cost will naturally result in larger risk to cost overrun as recently experienced by larger LWRs in western nations. With a design-to-build mindset to minimize cost and construction risk, we introduce the horizontal, compact HTGR (HC-HTGR). The reactor core and steam generator are mounted horizontally on rails and in-line with one another, decreasing the size of the reactor building relative to the power capacity four times when compared to traditional HTGRs. The HC-HTGR reduced overnight civil structure costs by 42%, indirect costs by 38%, and total capital costs by 20% from NGNP. We discussed the required engineering of new systems for the HC-HTGR including vessel supports, the reactor cavity cooling system, and steam generator design. Finally, we estimated the fuel and operations costs of the HC-HTGR, and a survey of low-carbon industrial process heat technology showed the HC-HTGR can deliver a highly competitive levelized cost of heat in the range of $6.13–12.48/GJ.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

A layered Prussian blue analogue as fast-charging negative electrode material for lithium-ion batteries

The simultaneous achievement of fast-charging and high specific capacity remains a critical challenge for lithium-ion battery negative electrodes. Here we report a layered manganese-based Prussian blue analogue, synthesized through vacancy control and subsequent thermal transformation. As a conversion-type negative electrode, this material exhibits high-rate performance, delivering a specific capacity of 510 mAh g −1 at a specific current of 8 A g −1 , and operates at a moderate average voltage of approximately 1.2 V vs. Li/Li + , which mitigates lithium plating risks. This high-rate capability stems from the analogue’s specific linkage configurations, which facilitate a high content of active transition metal and strong Li+ adsorption at nitrogen sites. The high transition metal content enables a high reversible capacity, while strong Li + adsorption promotes an efficient initial crystalline-to-amorphous transformation. This process induces dynamically reversible component migration during subsequent cycling, thereby enhancing conversion reaction kinetics. Our findings provide insights into the application of Prussian blue analogues as fast-charging negative electrode materials. The development of fast-charging and high-capacity negative electrodes is critical for advanced lithium-ion batteries. Here, authors use a vacancy engineering strategy to develop a layered Prussian blue analogue with competitive rate capability, delivering a specific capacity of 510 mAh g −1 at a specific current of 8 A g −1 .

25 ENERGY STORAGE↗
DOE OSTI2021

Enabling Pulse-level Programming, Compilation, and Execution in XACC

Noisy gate-model quantum processing units (QPUs) are currently available from vendors over the cloud, and digital quantum programming approaches exist to run low-depth circuits on physical hardware. These digital representations are ultimately lowered to pulse-level instructions by vendor quantum control systems to affect unitary evolution representative of the submitted digital circuit. Vendors are beginning to open this pulse-level control system to the public via specified interfaces. Robust programming methodologies, software frameworks, and backend simulation technologies for this analog model of quantum computation will prove critical to advancing pulse-level control research and development. Prototypical use cases for this include error mitigation, optimal pulse control, and physics-inspired pulse construction. Here we present an extension to the XACC quantum-classical software framework that enables pulse-level programming for superconducting, gate-model quantum computers, and a novel, general, and extensible pulse-level simulation backend for XACC that scales on classical compute clusters via MPI. Our work enables custom backend Hamiltonian definitions and gate-level compilation to available pulses with a focus on performance and scalability. We end with a demonstration of this capability, and show how to use XACC for pertinent pulse-level programming tasks.

97 MATHEMATICS AND COMPUTING↗