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At least 19 records

Status and prospects for inertial fusion energy via lasers

Fusion energy is the ultimate clean and limitless energy source, but its development requires overcoming many scientific and technological challenges. For the first time in the 60-year long history of fusion research, ignition and target gain above unity (G>1) were demonstrated in the laboratory at the National Ignition Facility at the Lawrence Livermore National Laboratory in 2022. Turning laser fusion into an energy source requires that the results from single shot experiments be replicated at much higher repetition rates of many shots per second to produce high average power at relatively low cost. Furthermore, this requires the development of new laser technologies, mass production of suitable targets, accurate injection and tracking systems and new materials for the reactor chamber components and final optics. Ultra broadband and deep UV light are laser advances that can dramatically improve the laser energy coupling to the target thereby reducing the laser energy and power requirements.

Fusion energy

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

Next Generation Sensor Development (CRADA Final Report)

B. Project Scope This was a collaborative effort between Lawrence Livermore National Security, LLC (LLNS), as manager and operator of Lawrence Livermore National Laboratory (LLNL) and The Federal Reserve Bank of San Francisco ("FRBSF" or "Participant"), to research and develop advanced processing techniques to measure the fitness and authenticity of U.S. currency. The FRBSF previously partnered with LLNL to evaluate end-of-life predictions, review sensor requirements, develop communications protocols, and perform thermal analysis. These Strategic Partnership Projects (SPP) included SPP No. L20960 - Federal Reserve Currency Technology Office Studies, SPP No. L15900 - Development of a Common Detector Interface (CDI 2.0) Specification and Hardware Simulators, and SPP No. L15610 - Limited Design Review of a Second-Generation E-Material Authentication Sensor (EMAS2).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF

Enhancing 300 Degree Celsius Electronic Packaging with Ceramic PCBs and Advanced Interconnection Techniques

Geothermal energy development requires downhole tools that operate reliably at temperatures up to 320 °C. While MWD tools work without thermal protection and logging tools use vacuum flasks for limited high-temperature use, Sandia National Laboratories is developing durable electronics on ceramic PCBs with protective coatings to enable long-term operation of geothermal instruments at sustained temperatures up to 300 °C.

Wright, Andrew Alexander [Sandia National Laborato

Automated Calibration for Rapid Optical Spectroscopy Sensor Development for Online Monitoring

An automated platform has been developed to assist researchers in the rapid development of optical spectroscopy sensors to quantify species from spectral data. This platform performs calibration and validation measurements simultaneously. Real-time, in situ monitoring of complex systems through optical spectroscopy has been shown to be a useful tool; however, building calibration models requires development time, which can be a limiting factor in the case of radiological or otherwise hazardous systems. While calibration time can be reduced through optimized design of experiments, this study approached the challenge differently through automation. The ATLAS (Automated Transient Learning for Applied Sensors) platform used pneumatic control of stock solutions to cycle flow profiles through desired calibration concentrations for multivariate model construction. Additionally, the transients between desired concentrations based on flow calculations were used as validation measurements to understand model predictive capabilities. This automated approach yielded an incredible 76% reduction in model development time and a 60% reduction in sample volume versus estimated manual sample preparation and static measurements. The ATLAS system was demonstrated on two systems: a three-lanthanide system with Pr/Nd/Ho representing a use case with significant overlap or interference between analyte signatures and an alternate system containing Pr/Nd/Ni to demonstrate a use case in which broad-band corrosion species signatures interfered with more distinct lanthanide absorbance profiles. Both systems resulted in strong model prediction performance (RMSEP < 9%). Lastly, ATLAS was demonstrated as a tool to simulate process monitoring scenarios (e.g., column separation) in which models can be further optimized to account for day-to-day changes as necessary (e.g., baseline correction). Ultimately, ATLAS offers a vital tool to rapidly screen monitoring methods, investigate sensor fusion, and explore more complex systems (i.e., larger numbers of species).

47 OTHER INSTRUMENTATION

Solar Energy CommUnity Resiliency (Final Technical Report)

Final Technical Report for DE-EE0009336 Solar Energy CommUnity Resiliency (SECURE) The Solar Energy CommUnity Resiliency (SECURE) project aimed to support development of resilient community microgrids to improve grid reliability and maintain power during times of crisis. The SECURE project approached this objective by addressing key technical and business challenges impeding implementation of resilient community microgrids. To achieve the goals of this project, we pursued several specific objectives through comprehensive design and requirements development.

24 POWER TRANSMISSION AND DISTRIBUTION

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Fourth Edition

As the world increasingly seeks low-carbon energy solutions, solar power emerges as the most abundant resource on our planet. However, the challenge of effectively harnessing this energy is crucial in the coming years. Solar energy applications such as photovoltaics, solar heating and cooling, and concentrating solar power use different technologies to capitalize on sunlight. Each system has unique capabilities and requirements, underscoring the need for reliable information about solar resources across diverse installations, from residential rooftops to large-scale power plants. This is especially important for substantial projects, often exceeding $1 billion in construction costs. Before embarking on such ventures, it is imperative to obtain accurate data concerning solar resource quality and reliability at specific sites. Developers require detailed historical information, including seasonal, daily, hourly, and, ideally, subhourly variability to effectively predict a power plant's annual performance. Without these vital data, financial analyses fall short. Moreover, with the growing adoption of distributed photovoltaics, integrating these generation sources becomes critical to maintaining grid reliability and stability. By accurately forecasting generation patterns, utilities and system operators can facilitate greater integration of solar energy, thus ensuring the operational stability of the grid. The complexity and importance of these issues have prompted the foremost experts in the field to collaborate under the auspices of the International Energy Agency's (IEA's) Photovoltaic Power Systems Programme (PVPS) Task 16 to publish this handbook, which summarizes state-of-the-art information about all these topics. The efforts focus on providing reliable data and insights that can help shape our investments in solar energy and drive a sustainable future.

14 SOLAR ENERGY

Design and Development of the Handling Frame Assembly Table for the NIF Sustainment Project (Draft)

The Handling Frame Assembly Table is a custom designed piece of equipment developed to support the NIF Sustainment Project. The NIF Sustainment project's goal is to refurbish the National Ignition Facility (NIF), the world’s largest and most energetic laser, so it can continue advancing research in fusion energy, national security, and high energy density physics. A key aspect of this effort involves replacing all 1,728 blast shields on the NIF, which requires specialized equipment such as the Handling Frame Assembly Table to support the production of new blast shields. This project follows a systems engineering approach that guides the design sequence. This report documents the design process from initial concept through final design, including stakeholder analysis, requirements development, conceptual design, design analysis and validation, and final design. Future work will focus on building and commissioning the system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Design and Development of the Handling Frame Assembly Table for the National Ignition Facility Blast Shields

The Handling Frame Assembly Table is a custom designed piece of equipment developed to support the NIF Sustainment Project. The goal of the NIF Sustainment Project is to refurbish the National Ignition Facility (NIF), the world’s largest and most energetic laser, so it can continue advancing research in fusion energy, national security, and high energy density physics. A key aspect of this effort involves replacing all 1,728 blast shields on the NIF, which requires specialized equipment such as the Handling Frame Assembly Table to support the production of new blast shields. This project follows a systems engineering approach that guides the design sequence. This report documents the design process from initial concept through final design, including stakeholder analysis, requirements development, conceptual design, final design, and design validation. Future work will focus on building and commissioning the system.

42 ENGINEERING

Design and Development of the Handling Frame Assembly Table for the National Ignition Facility Blast Shields

The Handling Frame Assembly Table is a custom designed piece of equipment developed to support the NIF Sustainment Project. The goal of the NIF Sustainment Project is to refurbish the National Ignition Facility (NIF), the world’s largest and most energetic laser, so it can continue advancing research in fusion energy, national security, and high energy density physics. A key aspect of this effort involves replacing all 1,728 blast shields on the NIF, which requires specialized equipment such as the Handling Frame Assembly Table to support the production of new blast shields. This project follows a systems engineering approach that guides the design sequence. This report documents the design process from initial concept through final design, including stakeholder analysis, requirements development, conceptual design, final design, and design validation. Future work will focus on building and commissioning the system.

42 ENGINEERING

Design and Validation of a Cryogenic Dilatometer

This project focuses on the design and development of a cryogenic dilatometer capable of measuring the thermal expansion of materials at extremely low temperatures. Understanding how materials change dimension with temperature is critical for applications involving cryogenic environments, particularly laminated systems housing superconducting magnets, where small dimensional changes can significantly affect performance and reliability. To address this, a dilatometer system was designed to operate within a liquid nitrogen environment while accurately measuring displacements caused by thermal contraction. The purpose of this device is to determine the coefficient of thermal expansion (CTE) of a material. The design process involved defining functional requirements, developing mechanical and thermal concepts for the measurement apparatus, selecting appropriate materials compatible with cryogenic temperatures, and integrating sensors capable of detecting small dimensional changes. The resulting system aims to provide a practical and repeatable method for evaluating material thermal expansion at cryogenic temperatures, supporting research into composite use in superconducting applications that require accurate characterization of material behavior in low-temperature environments.

Schmitt, Nicholas [Northern Illinois U.]

Tracking and Positioning System for Floating Solar (CRADA Abstract)

The project goal is to develop a floating solar photovoltaics (FPV) tracking & position system that: (1) increases annual energy production of FPV projects by >10%, (2) lowers levelized cost of energy (LCOE) for FPV by >10%, and (3) leverages U.S. contract supply chain & manufacturing. The outcome of the project will be a certified tracking product that has undergone extensive field testing and is ready for commercial sales. The primary objectives for each budget period are: • BP1: Define product requirements, develop initial controls architecture and design other sub-components, complete small-scale pilot testing, install a larger-scale pilot, secure sites for commercial pilots, and develop the beta-version of a user portal. • BP2: complete control system and sub-component design, successful demonstration and testing at a commercial pilot, certification & bankability, finalize user portal, and complete various commercialization activities related to supply chain, customer acquisition, and sales. PNNL will provide support during both project phases for prototype development and testing of the controls architecture, software, and hardware components of the tracking and positioning system. PNNL will provide support during both project phases for prototype development and testing of the controls architecture, software, and hardware components of the tracking and positioning system. This effort represents PNNL’s first opportunity to support the floating solar photovoltaics (FPV) industry with capabilities, facilities, and personnel developed to contribute to the marine energy (e.g., wave and tidal energy) sector. This portfolio expansion leverages internal and DOE EERE investments and the growing visibility of PNNL-Sequim’s Marine and Coastal Research Laboratory (MCRL) and our marine research capabilities, in general. The development of effective and low-cost FPV platforms is a potential way to increase the nation’s set of tools for providing emission-free electricity without utilizing valuable terrestrial resources. Successful commercialization of such a project may lead to economic benefits through job creation, supply chain creation, and access to a cheaper source of electricity.

14 SOLAR ENERGY

Strategies for simulating the time evolution of Hamiltonian lattice field theories

Simulating the time evolution of quantum field theories given some Hamiltonian H requires developing algorithms for implementing the unitary operator e -iHt . A variety of techniques exist that accomplish this task, with the most common technique used so far being Trotterization, which is a special case of the application of a product formula. However, other techniques exist that promise better asymptotic scaling in certain parameters of the theory being simulated, the most efficient of which are based on the concept of block encoding. In this work we study the performance of such algorithms in simulating lattice field theories. We derive and compare the asymptotic gate complexities of several commonly used simulation techniques in application to Hamiltonian lattice field theories. Using the scalar $\hat{φ}$ 4 theory as a test, we also perform numerical studies and compare the gate costs required by product formulas and signal-processing-based techniques to simulate time evolution. For the latter, we use the linear combination of unitaries (LCU) construction augmented with the quantum Fourier transform circuit to switch between the field and momentum eigenbases, which leads to immediate order-of-magnitude improvement in the cost of preparing the block encoding. Further, this paper also includes a pedagogical review of the techniques used, in particular product formulas, LCU, qubitization, quantum signal processing, as well as the technique for simulating geometrically-local Hamiltonians developed by Haah, Hastings, Kothari, and Low.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC

Evaluation of antifouling surfaces using a method that employs mussel larvae settlement quantified by machine learning

Antifouling coating development requires extensive performance testing. Coatings that prevent aquatic larval settlement are of interest because many forms of macrofouling begin at the larval stage. However, field testing can be time consuming and poorly controlled. Herein is reported a screening tool, Settlement of Larvae Assay using Mussels (SLAM), for down-selecting materials prior to field testing. The method entails using a dense concentration of mussel larvae that are allowed to settle on submerged test surfaces. Settled larvae are then quantified to provide a measure of antifouling performance. The SLAM test differentiated coatings with only slight differences in formulation. To enable efficient quantification of dense larvae settlement, an automated counting method was developed that combines two analyses: a color thresholding identifies larvae clumps, and a machine learning algorithm identifies non-clumped larvae. Finally, this automated ‘hybrid’ approach rapidly quantifies settled larvae as effectively as manual counting but in a fraction of the time.

Mytilus

Distributed Acoustic Sensing for Whale Vocalization Monitoring: A Vertical Deployment Field Test

Abstract There is growing interest in floating offshore wind turbine (FOWT) technology, where turbines are installed on floating structures anchored to the seabed, allowing wind energy development in areas unsuitable for traditional fixed-platform turbines. Responsible development requires monitoring the impact of FOWTs on marine wildlife, such as whales, throughout the operational lifecycle of the turbines. Distributed acoustic sensing (DAS)—a technology that transforms fiber-optic cables into vibration sensor arrays—has been demonstrated for acoustic monitoring of whales using seafloor telecommunications cables. However, no studies have yet evaluated DAS performance in dynamic, engineered environments, such as floating platforms or moving vessels with complex, dynamic strain loads, despite their relevance to FOWT settings. This study addresses that gap by deploying DAS aboard a boat in Monterey Bay, California, where a fiber-optic cable was lowered using a weighted and suspended mooring line, enabling vertical deployment. Humpback whale vocalizations were captured and identified in the DAS data, noise sources were identified, and DAS data were compared to audio captured by a standalone hydrophone attached to the mooring line and a nearby hydrophone on a cabled observatory. This study is unique in: (1) deploying DAS in a vertical deployment mode, where noise from turbulence, cable vibrations, and other sources posed additional challenges compared to seafloor DAS applications; (2) demonstrating DAS in a dynamic, nonstationary setup, which is uncommon for DAS interrogators typically used in more stable environments; and (3) leveraging looped sections of the cable to reduce the noise floor and mitigate the effects of excessive cable vibrations and strain. This research demonstrates DAS’s ability to capture whale vocalizations in challenging environments, highlighting its potential to enhance underwater acoustic monitoring, particularly in the context of renewable energy development in offshore environments.

Saw, Jaewon

Mixed-anion electrolytes: from bulk speciation to interfacial dynamics in divalent metal electrodeposition

Mixing anions is emerging as a promising strategy for multivalent electrolyte design, allowing for adjustment of the solvation structure of bulk cations and enhancing the efficiency of electrochemical processes (e.g. metal deposition for batteries and catalysis). Further progress in electrolyte development requires a fundamental understanding of how tailored electrolyte speciation in mixed anion systems can modify the dynamic electrochemical interface during metal cycling. In this study, we present an anode-focused mechanistic study of exemplar Mg electrolytes containing three different secondary anions, correlating electrochemical behavior with bulk speciation and operando interfacial dynamics. Electrospray Ionization-Mass Spectrometry (ESI-MS) results reveal a general trend of forming mixed anion contact ion pairs (CIPs) across various anions, with the extent of ion pairing influenced by the association strength of the secondary anion. Operando multiharmonic electrochemical quartz crystal microbalance with dissipation (EQCM-D) reveals how these bulk species influence interfacial mass uptake, viscoelasticity, and solvent-coupled hydrodynamic behavior during deposition and stripping. The results indicate that Mg-containing ion pairs and solvated complexes shape adsorption, nucleation, and deposit growth, leading to distinct anion-dependent interphases ranging from more permeable, solvent-coupled layers to relatively compact and rigid deposits. This work establishes a quantitative link between bulk speciation and interfacial dynamics in divalent metal electrodeposition and provides mechanistic guidance for electrolyte design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Forming a database to study reversed magnetic shear from the National Spherical Torus eXperiment using machine learning

Achieving a long-lived reversed magnetic shear (RMS) target plasma in the National Spherical Torus eXperiment Upgrade will require developing various sustainment scenarios. To help with the ongoing plasma control efforts, the development of a new analysis for the motional Stark effect (MSE) diagnostic using a machine learning algorithm, namely, MSE-ML, is described. MSE-ML will be used to identify patterns during RMS discharges, some of which suffer magnetohydrodynamic (MHD) events resulting in current redistribution and monotonic q-profiles. A database consisting of q and magnetic shear profiles is being constructed primarily based on the existing National Spherical Torus eXperiment data with equilibrium reconstructions constrained by the magnetic field pitch angle profile measured using the multi-channel MSE diagnostic. An unsupervised k-means clustering of the data is developed to study the RMS formation as a function of time. The initial clustering from the q-profiles shows significant differences in both amplitude and the duration of the RMS period. As a goal, the clustering results that detect and distinguish shots with substantial and sustained RMS are to be used as a preprocessing step in a supervised algorithm to identify the underlying conditions that lead to long-lasting improved confinement with RMS. Another aim of the MSE-ML study is to identify precursors of RMS-destroying MHD events in either derived data such as the q-profile or directly measured data such as the magnetic field pitch angle profile.

Uzun-Kaymak, I. U. (ORCID:0000000276251493)