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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 343 records · Page 19

Future of End-User Support

IT Service Management (ITSM) is an inimitable, ever-changing practice that is critical to all far-reaching organizations, including Sandia National Laboratories. With recent developments in technology and society – spurred by major events like the advent of ChatGPT and the pandemic – it is as important as ever to consider the implications and opportunities for ITSM. This report strategically synthesizes existing information about ITSM structures and examines the current state of Sandia’s service management entity: CCHD. Then, it looks at the emerging state of the world, culminating in CCHD-tailored recommendations for continual service improvement (CSI). Ultimately, the biggest matters to address are staff tenure, ticket documentation, and self-service facilitation. The next step might be to introduce AI to service channels in a non-system-invasive manner, namely a chatbot on the main CCHD page. All would serve to enhance end-user experiences, and by proxy Sandia’s output.

97 MATHEMATICS AND COMPUTING↗

High Performance Solvent for NGCC Flue Gas CO 2 Capture (Final Technical Report)

Amine-based solvent absorption is the most mature and reliable technology for large scale CO 2 capture, dating back to the 1930s when monoethanolamine (MEA) was used to treat acid gases from oil refineries. However, while strategic advancements have optimized the CO2 capture process, the cost of capture remains high, where current estimates suggest that CO 2 capture costs are around $\$$72/tonne of CO 2 . To address this, solvent development and optimization have become a focus of current research. This project sought to develop a high-performance solvent to reduce the overall cost of CO 2 capture from NGCC flue gas. Here, solvent optimization focused on: (1) reducing the energy required for CO 2 desorption in a reboiler, (2) improving CO 2 absorption and desorption reaction kinetics, (3) improving solvent stability, and (4) reducing environmental impacts. Susteon has developed and evaluated a promoted solvent, Sustenol™, for NGCC flue gas CO 2 capture. The optimized Sustenol™ also shows a higher dynamic CO 2 absorption capacity of ~0.5 mol CO2 /mol amine compared to 0.25 mol CO2 /mol amine for 30 wt% MEA. Additionally, the solvent is oxidatively, thermally and hydrothermally stable, which leads to lower solvent loss and emissions. These advancements have resulted in a solvent regeneration energy of 2.16 GJ/tonne of CO 2 which is >30% lower than current state-of-the-art commercial and emerging solvents. Combined with empirical data from the bench and pilot scale testing, this preliminary TEA study indicated the cost of CO 2 capture by Sustenol™ for 97% CO 2 removal at $\$$54/tonne and for 90% removal at $\$$49/tonne, with a pathway to achieve $\$$45/tonne of CO 2 with continued process and solvent advancements. Susteon has developed a technology roadmap to reduce the cost of CO 2 capture to <$\$$45/tonne for NGCC flue gas. Susteon plans to derisk this technology for commercial deployment through comprehensive solvent degradation testing, long-term testing in a pilot plant at 5 tonne CO2 /day and demonstration scale testing at 100 tonne CO2 /day with NGCC flue gas and engineering design studies to qualify Sustenol™ as a drop-in replacement solvent.

03 NATURAL GAS↗

Cyber Halo Innovation Research Program (CHIRP) Handbook: CHIRP Program Document 2026

The Cyber Halo Innovation Research Program (CHIRP) handbook outlines a comprehensive framework designed to advance space cybersecurity education, workforce development, recruitment efforts for United States Space Force (USSF) Space Systems Command (SSC) and the Department of the Airforce, and foster students’ professional growth. It provides an overview of CHIRP's objectives and strategic focus, establishing the foundation for participant engagement through a network of collaborations with academic institutions, contracted industry partners, training and certification organizations, federal agencies, and community organizations. It states a clear participation strategy for SSC and Pacific Northwest National Laboratory (PNNL) for program execution and successful support for student transition to a career in space cybersecurity.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Vibration mitigation in interlocking metasurfaces

Interlocking metasurfaces (ILMs) are a new class of mechanical metamaterials with patterned surface features that enable joining of two adjacent bodies, serving as an alternative to welds, fasteners, or adhesives. While the strength of ILMs has been explored previously, it is also possible to envision ILMs that possess the ability to dampen vibration or tailor energy transmission across the interface. In this study, we explore the vibration transmission under frequency sweep and random excitation of three ILM designs. This is the first study to characterize the response of ILMs under vibration. We find that ILMs which are tightly coupled (e.g., small interference fit) behave as a linear system and depart only marginally from the behavior of a solid body. However, through strategic manipulation of the ILM topology, and in particular the fit clearances, we show that vibrations can be damped by over an order of magnitude. Design strategies to employ ILMs for vibration mitigation are developed using a first-order model.

Bolmin, O. [Carnegie Mellon Univ., Pittsburgh, PA ↗

Modeling the Fundamental Radiation Chemistry of the Organic Diluent, and the Effect of Metal Ion Complexation on the Radiochemical Behavior of Active Compounds

All used nuclear fuel (UNF) reprocessing technologies must operate efficiently in the presence of an intense, multi-component (predominantly alpha, beta, and gamma) radiation field. Consequently, radiation-induced degradation of reprocessing systems is of concern, as it negatively impacts process performance over time due to the destruction of both active compounds (ligands, phase modifiers, holdback agents, etc.) and the formation of degradation products. Reprocessing solvent system radiolysis has been linked to changes in separation efficiency and physical properties of solvent mixtures, solvent-recycle longevity, crud formation, and other unexpected outcomes that impact the efficient recovery of valuable materials (e.g., the actinides) and the volume of hazardous radioactive waste for final disposal, i.e., in a geological repository. Consequently, a fundamental understanding of radiolytic processes and their effects on reprocessing solvent system performance is critical for: (i) the cost-effective development and innovation of separation technologies; (ii) the design and implementation of predictive radiation chemical models for process monitoring and lifetimes; and (iii) potentially the ability to exploit radiolytic phenomenon to our benefit, e.g., strategic radiolysis of active molecules to liberate specific degradation products that aid subsequent process stages. Despite extensive investigation into the radiolytic behavior of active solvent system compounds, little attention has been given to understanding (i) the radiation chemical behavior and modification of the organic diluent and (ii) the effect of metal ion complexation on the radiochemical behavior of active compounds.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Policy Reforms to Unleash Domestic Critical Minerals Mining and Processing

The United States faces growing strategic and economic risks due to its limited ability to mine, process, and refine the minerals required for national defense, energy systems, advanced manufacturing, and emerging technologies. Although the country possesses significant geological resources, development has been slowed by long and unpredictable permitting timelines, fragmented regulatory responsibilities, limited midstream processing capacity, and a shrinking technical workforce. These structural barriers have created supply chain vulnerabilities that constrain industrial growth and reduce national resilience. This report presents a comprehensive set of reforms intended to modernize the nation’s approach to critical minerals. The recommendations address federal permitting, environmental review processes, the legal framework governing mining activities, interagency coordination, domestic processing and refining capacity, and the education and workforce systems needed to support long term industry development. The analysis emphasizes practical steps to shorten project timelines, improve regulatory clarity, expand processing infrastructure, enable recovery from both conventional and nontraditional sources, and update outdated requirements that hinder the development of essential materials. Taken together, the recommended reforms would strengthen domestic supply chains, improve investment certainty, and reduce dependence on external minerals and processing infrastructure. By aligning policy, regulatory frameworks, and workforce capabilities with national needs, the United States can build a more resilient and secure critical minerals ecosystem that supports long term economic competitiveness and technological leadership.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Energy Options Analysis Project (Final Report)

This Bear River Band of Rohnerville Rancheria (BRB) Energy Options Analysis Project provides a rigorous and comprehensive near-term renewable energy implementation plan that aligns with the BRB’s long term strategic vision of “zero net annual utility energy consumption.” Final recommendations were arrived at by following four key project phases:A gas and electricity load assessment was conducted for all existing buildings using historic consumption data, and projected loads of new or anticipated buildings using building designs. A renewable energy resource assessment was conducted that estimated the gross generation potential of solar and wind, constrained to areas that could potentially be developed. Other renewable generation technologies were not considered feasible to meet the loads of the BRB. Demand-side efficiency and fuel switching opportunities were identified that can reduce electrical and gas consumption. These opportunities were not integrated into the load assessment in order to provide a conservative implementation plan, but are recommended to be pursued in order to cost-optimize projects during a feasibility assessment. A strategic vision advisory committee was organized and consulted when iterating on the viability of possible projects. These project phases resulted in finalizing the following three solar PV projects for the near term, which also lay the foundation for a future community-scale or multiple-facility microgrid for added resiliency. Additional solar PV on the hillside south of the Tish-Non Community Center. Solar plus battery storage microgrid at the Pump & Play fuel station. Solar PV at the Casino.

14 SOLAR ENERGY↗

RADIATION DOSE SIMULATIONS FOR JEFFERSON LAB’S PERMANENT MAGNET RESILIENCY LDRD STUDY

In late 2023, Thomas Jefferson National Accelerator Facil- ity (Jefferson Lab) funded a Laboratory Directed Research and Development (LDRD) grant dedicated to investigating the impact of radiation on permanent magnet materials. This research initiative is specifically geared towards assessing materials slated for use in the CEBAF energy upgrade. The experimental approach involves strategically placing perma- nent magnet samples throughout the accelerator, exposing them to varying radiation doses. The simulation code BD- SIM is used to first validate the data and then to simulate the effects on future higher energy passes to study the degra- dation effects on the permanent magnets. In this paper we present the progress of that work.

Deitrick, K.↗

Basin-specific geochemistry to promote unconventional efficiency

This project focused on two strategic geochemistry-based research thrusts and provided new knowledge in the following areas: (i) mitigation of scale precipitation in shale reservoirs; and (ii) improvement of hydrocarbon extractions from tight matrix pore space. Additionally, we developed a new acoustic monitoring approach to nondestructively monitor shale alteration in-situ in the laboratory and subsurface.

20 FOSSIL-FUELED POWER PLANTS↗

Star–Galaxy Image Separation with Computationally Efficient Gaussian Process Classification

Abstract We introduce a novel method for discerning optical telescope images of stars from those of galaxies using Gaussian processes (GPs). Although applications of GPs often struggle in high-dimensional data modalities such as optical image classification, we show that a low-dimensional embedding of images into a metric space defined by the principal components of the data suffices to produce high-quality predictions from real large-scale survey data. We develop a novel method of GP classification hyperparameter training that scales approximately linearly in the number of image observations, which allows for application of GP models to large-size Hyper Suprime-Cam Subaru Strategic Program data. In our experiments, we evaluate the performance of a principal component analysis embedded GP predictive model against other machine-learning algorithms, including a convolutional neural network and an image photometric morphology discriminator. Our analysis shows that our methods compare favorably with current methods in optical image classification while producing posterior distributions from the GP regression that can be used to quantify object classification uncertainty. We further describe how classification uncertainty can be used to efficiently parse large-scale survey imaging data to produce high-confidence object catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗

Optimal Strategies for Hybrid Battery‐Storage Systems Design

As stationary hybrid energy‐storage systems (HESS) for power systems applications have recently drawn interest due to their enhanced performance and decreasing cost, developing systematic approaches for HESS design while considering controls is gaining traction. Herein, a method is presented to optimally design hybrid battery storage by proposing a mathematical modeling framework, formulated as a mixed integer linear programming model. The optimization is capable of handling multiple subsystems of batteries, considering their economic and technological performance. Decisions involve sizing of the batteries, optimal temporal and strategic dispatch to end uses, and energy sources for charging each battery. The applicability of the model is tested on four case studies for three battery chemistries representing distinct objectives: high‐power, high‐energy, and second life. Compared to traditionally designed battery storage with a homogeneous battery, optimally designed hybrid systems can save 12%–26% of system costs, depending on the nature of the dispatch profile. Findings point to design preference toward the second life battery supplemented with some high‐power or high‐energy battery capacity, or both. With the utilized electricity price structure, customers can experience approximately 10%–35% reduction in their bills.

Koleva, Mariya↗

Towards physics-informed explainable machine learning and causal models for materials research

From emergent material descriptions to estimation of properties stemming from structures to optimization of process parameters for achieving best performance – all key facets of materials science and related fields have experienced tremendous growth with the introduction of data-driven models. This gradual progression goes at par with developments of machine learning workflows, from purely data-driven shallow models to those that are well-capable in encoding more complex graphs, symbolic representations, invariances, and positional embeddings. Furthermore, this perspective aims at summarizing strategic aspects of such transitions while providing insights into the requirements of bringing in explainable, interpretable predictive models, and causal learning to aid in materials design and discovery. Although the focus remains on a variety of functional materials by providing a handful of case studies, the applications of such integrated methodologies are universal to facilitate fundamental understandings of materials physics while enabling autonomous experiments.

36 MATERIALS SCIENCE↗

Science challenges and research opportunities for plasma applications in microelectronics

Low-temperature plasmas (LTPs) are essential to manufacturing devices in the semiconductor industry, from creating extreme ultraviolet photons used in the most advanced lithography to thin film etching, deposition, and surface modifications. It is estimated that 40%–45% of all process steps needed to manufacture semiconductor devices use LTPs in one form or another. LTPs have been an enabling technology in the multidecade progression of the shrinking of device dimensions, often referred to as Moore’s law. New challenges in circuit and device design, novel materials, and increasing demands to achieve environmentally benign processing technologies require advances in plasma technology beyond the current state-of-the-art. The Department of Energy Office of Science Fusion Energy Sciences held a workshop titled Plasma Science for Microelectronics Nanofabrication in August 2022 to discuss the plasma science challenges and technical barriers that need to be overcome to continue to develop the innovative plasma technologies required to support and advance the semiconductor industry. One of the key outcomes of the workshop was identifying a set of priority research opportunities (PROs) to focus attention on the most strategic plasma science challenges to address to benefit the semiconductor industry. For each PRO, scientific challenges and recommended strategies to address those challenges were identified. Furthermore, this article summarizes the PROs identified by the workshop participants.

36 MATERIALS SCIENCE↗

Los Alamos National Laboratory Laboratory Directed Research and Development Program (FY22 Annual Progress Report)

Laboratory Directed Research and Development (LDRD) helps Los Alamos National Laboratory solve national security challenges through excellence in mission-focused science, technology, and engineering. The DOE Laboratory and Site-Directed Research and Development programs are among the most impactful sources of research and development for our Nation. The heart of the LDRD program is high-risk, high-reward research that creates innovative technical solutions for some of the Nation’s most difficult challenges. The LDRD programs follow strategic guidance derived from the missions of the U.S. Department of Energy, the National Nuclear Security Administration (NNSA), and the Laboratory.

99 GENERAL AND MISCELLANEOUS↗

Los Alamos National Laboratory Laboratory Directed Research and Development Program: FY25 Annual Progress Report

Laboratory Directed Research and Development (LDRD) helps Los Alamos National Laboratory solve national security challenges through excellence in mission-focused science, technology, and engineering (ST&E). The Department of Energy (DOE) Laboratory and Site-Directed Research and Development programs are among the most impactful sources of research and development for our Nation. The heart of the LDRD program is high-risk, high-reward research that creates innovative technical solutions for some of the Nation’s most difficult challenges. The LDRD programs follow strategic guidance derived from the missions of the U.S. Department of Energy, the National Nuclear Security Administration (NNSA), and the Laboratory.

99 GENERAL AND MISCELLANEOUS↗

Human Dimensions of Energy Systems Workshop - September 6-7, 2022: Findings and Next Steps

Advanced energy technologies and informed policies are necessary but not sufficient to accelerate the energy transition at the speed required to meet our shared climate and energy resilience goals. To fully understand and implement integrated energy systems, we need to be able to model and analyze the complete system-of-systems, including the behavior of people interacting with and being impacted by energy systems. The purpose of this workshop is: Understand how human behavior and decisions affect the performance of energy systems with a focus on resilience and human well-being; Identify opportunities to improve energy system design to explicitly consider human behavior and well-being; Enhance our capability to model and predict human actions. Develop the ability to stress test these integrated systems; Identify or develop requirements and tools for more robust system designs that can be used for human-in-the-loop exercises and training; Identify opportunities for joint research, joint appointments, and collaboration; and Guide internal investments and strategic hires.

analyze↗

CIE Curriculum Guide (V.2.0)

The Cyber-Informed Engineering (CIE) Curriculum Guide offers a comprehensive framework, guidance, and resources for integrating CIE into university-level engineering programs and related educational activities. The primary goal is to help educators adopt CIE principles into their teaching to produce future engineers and technicians who understand digital risks in modern engineered systems, thereby addressing the nation’s infrastructure resilience needs. This guide outlines practical integration examples, links to resources to accelerate CIE adoption, and shares insights from partner academic institutions on various implementation strategies. CIE is a framework for embedding engineered controls that mitigate the impact of cyber-attacks in any cyber-physical system used in critical energy infrastructure and other sectors. Developed by the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER), the National Cyber-Informed Engineering Strategy emphasizes embedding CIE into formal education, training, and credentialing. This guide supports this strategic objective by providing examples of integrating CIE concepts into engineering curricula, from class activities to new courses and certificate programs. The importance of educating cyber-informed engineers is underscored by the evolving cybersecurity threats facing engineered systems. As industrial control systems (ICS) increasingly incorporate digital technologies, the responsibility for security extends to both cyber professionals and engineers. CIE addresses critical gaps in designing and protecting physical systems with digital components against cyber risks, ensuring engineers consider digital risk throughout the engineering design lifecycle. Currently, engineering education does not routinely include cyber-informed principles, highlighting a gap in addressing modern engineering system risks. This guide advocates for updating engineering curricula to include digital risk management as a fundamental element. By doing so, future engineers will be equipped to design resilient systems that mitigate digital risks from the outset. Through this guide, engineering faculty can integrate CIE into their curricula, bridging the gap between digital risk and engineering. This approach prepares a cyber-informed workforce capable of safeguarding the cyber-physical systems crucial to national security and public welfare. By embedding CIE into education and training, institutions can produce engineers and technicians who can effectively mitigate cyber impacts throughout the engineering design lifecycle, resulting in more secure critical infrastructures.

42 - ENGINEERING↗