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At least 73 records · Page 4

BESS Digital Assurance, Supply Chain Risk Management, and Emerging Regulation Session One

The TADA BESS Supply Chain Workshops are designed to equip participants with the knowledge and tools necessary to address the evolving challenges at the intersection of battery energy storage systems (BESS), cybersecurity, and supply chain vulnerabilities. The workshops emphasize the application of Cyber-Informed Engineering (CIE) principles using INL’s procurement guide and the CIE-BAT tool. Attendees will develop risk-based security strategies and actionable compliance roadmaps tailored to their BESS projects. Additionally, the program fosters a collaborative network of practitioners and provides guidance on navigating emerging regulatory requirements, including FEOC rules under the OBBB framework, to assess and enhance organizational readiness. This is Session 1 of 3. (Full Version)

25 - ENERGY STORAGE

Carbon-Based Quantum Information Science with Symmetry Protected Topological States (Final Report, DOE-BES award DE-SC0023105)

This research program established the scientific foundation for the rational, bottom-up design, synthesis, isolation, and investigation of symmetry-protected topological (SPT) electron spin qubits embedded in graphene nanoribbons (GNRs). The work focused on integrating atomically precise low-dimensional carbon nanostructures with emerging quantum logic architectures, providing a pathway toward scalable quantum materials for next-generation computing and sensing technologies. A central component of the program was the elucidation of fundamental relationships between real-space molecular architecture, local spin density distributions, electronic band dispersion, and energy level alignment in atomically precise GNR systems. These correlations define key operational parameters of SPT qubits and were systematically investigated to establish quantitative benchmarks against established molecular and solid-state spin qubit platforms. Attention was given to properties critical for quantum device performance, e.g. decoherence times, spectral sharpness of energy transitions, and tunable exchange interactions between spin states. The research demonstrated that these parameters can be engineered with atomic precision through scalable bottom-up synthetic strategies. Theory-guided design played a central role in identifying candidate structures hosting topologically protected spin states. Experimental validation was performed using both ensemble measurements and single-molecule characterization. In addition to advances in quantum materials synthesis, the program developed and applied spin-sensitive scanning probe microscopy techniques capable of directly probing quantum states and dynamic processes with atomic-scale spatial resolution. These capabilities enabled direct observation and characterization of quantum structures at the single-atom level. While the research activities were primarily hypothesis-driven fundamental investigations, the program adopted a comprehensive materials-by-design framework aimed at translating scientific discoveries into technological concepts compatible with scalable and intelligent manufacturing approaches.

36 MATERIALS SCIENCE

Lessons learned from the development and implementation of a workforce training curriculum for advanced controls for high performance HVAC systems

Over the past decade, academic research on advanced controls has slowly transitioned into new software platforms, giving rise to various companies developing and deploying these innovative products, including solutions for light commercial HVAC systems. However, the current workforce remains widely unprepared to install, maintain and operate these systems, particularly complex software-based control platforms, as most workforce training programs still focus on traditional building automation for large commercial buildings. This paper presents the development and piloting of curriculum for three key types of professionals: ● Technicians (trade-level): installing and maintaining modern high-performance HVAC systems and controls ● Programmers (undergrad-level): developing and implementing advanced controls ● Engineers and energy professionals (undergrad/grad-level): managing and evaluating system performance We share details of the material developed including training videos, open-source software, instruction manuals. We also present the results of a pilot implementation of the training materials with real students.

Casillas, Armando

Recommendations for Establishing Local Rural Electrification Programs Using Photovoltaic Systems [Recomendaciones Para la Implantacidn de Programas Locales de Electrificacidn Rural con Sistemas Fotovoltaicos]

Photovoltaic (PV) technology is becoming one the best options for supplying electricity to rural communities far from electrical networks and which have a small and disperse demand for electricity. As the cost of the technology goes down and its development advances, opportunities for applying it continue to grow. As a result, in the near future we will probably see an increase in massive application programs of this technology in rural Mexico. This document presents some of the most relevant problems needing immediate solution to increase the possibility of success in establishing photovoltaic programs for rural electrification in Mexico. These problems are influenced by economic, technological, engineering, infrastructural, social and political issues. The paper presents the requirements for an industrial center based on PV technology, the accessibility of replacement parts and maintenance service, development of financial solutions, training of the users and introducing norms and technical regulations. The document summarizes the issue of rural electrification in Mexico, emphasizing the low population density in these areas. A brief description is given of photovoltaics showing different configurations that can be utilized for supplying electricity to the rural areas. The issues involved and recommendations for introducing PV systems to the rural area are described.

14 SOLAR ENERGY

Nanoscale engineering and dynamic stabilization of mesoscopic spin textures

Thermalization, while ubiquitous in physics, has traditionally been viewed as an obstacle to be mitigated. In contrast, we demonstrate here the use of thermalization in the generation, control, and readout of “shell-like” spin textures with interacting 13 C nuclear spins in diamond, wherein spins are polarized oppositely on either side of a critical radius. The textures span several nanometers and encompass many hundred spins; they are created and interrogated without manipulating the nuclear spins individually. Long-time stabilization is achieved via prethermalization to a Floquet-engineered Hamiltonian under the electronic gradient field: The texture is therefore metastable and robust against spin diffusion. This enables the state to endure over multiple minutes before it decays. Our work on spin-state engineering paves the way for applications in quantum simulation and nanoscale imaging.

42 ENGINEERING

Feature Based Qualification (FBQ) of Wire Arc Additively Manufactured (WAAM) 17-4PH Martensitic Stainless Steels

The Department of Defense (DOD) programs of records desire to reduce the time and cost of the development and delivery loop in metal additive manufacturing (AM), including establishing forwarded AM capabilities. The success of these efforts relies on a robust and qualified process. To achieve this, the United States Army Combat Capabilities Development Command Ground Vehicle Systems Center Materials Engineering (GVME) needs to be able to quickly evaluate, test, and develop feedstocks, processes, and parts. This report is directed towards demonstrating the need for a framework for metal AM processes, defining and exploring geometries for metal AM process qualification, testing resultant deposition, and delivering actionable data.

36 MATERIALS SCIENCE

AOI [1] Advanced Manufacturing of Ceramic Anchors with Embedded Sensors for Process and Health Monitoring of Coal Boilers

Researchers at West Virginia University (WVU) developed methods to fabricate and test ceramic anchors with an embedded sensor technology for monitoring the health and processing conditions within pulverized coal (PC) and fluidized-bed combustion (FBC) boiler systems. The technology included the development of advanced manufacturing processes for 2D/3D printing electroceramic (conductive ceramic) sensor designs within the ceramic anchor microstructure during the manufacturing process. This advanced manufacturing process would allow for the precise control of local microstructure and composition in order to engineer layer-by-layer any protective and electrically active materials within the refractory anchor. This 3D printing technology would permit the rapid and controlled design of the refractory microstructure and embedded sensor design throughout the volume of the ceramic anchor. The work also included a method to interconnect the sensors to boiler shell through the anchor clamp, where the sensor signals will be processed by low-power electronics and transmitted wirelessly to a central processing hub. The end-goal of the program was to produce a ceramic anchor sensor system which would be ready for implementation within a coal boiler, and/or other similar refractory liner systems (such as that in the glass and metal manufacturing areas). The project objectives were to: 1) Define the chemical and microstructural stability, in addition to the electrical properties, of oxide and non-oxide ceramic composites to be embedded within the ceramic anchor compositions that may operate up to 1400ºC; 2) Develop and implement the 2D/3D printing technology to pattern and control the microstructure of the ceramic anchor and embedded sensor circuits; 3) Develop an interconnect technology which will permit easy installation of the ceramic anchors and signal collection at the boiler shell; 4) Develop low power analog electronics and wireless communication hardware to efficiently collect the sensor signal at each processing unit and transmit data to a central hub for data analysis; 5) Demonstrate the smart ceramic anchor system for temperature and liner fracture within a high-temperature processing unit, such as a boiler furnace or glass melting furnace floor/wall liner.

20 FOSSIL-FUELED POWER PLANTS

Initial Engineering Framework for Species Tracking in MSRs Involving Fuel Salt and Structures

This report implements a high-fidelity multiphysics modeling framework using the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program tools to track leaching and plating of materials between the fuel salt and structures in Molten Salt Reactors (MSRs). Specifically, this framework is demonstrated in modeling various processes within MSRs including hot and cold leg corrosion, redox potential driven corrosion, colloid precipitation and deposition, and noble metal plating and decay heat modeling. The model integrates neutronics, thermal-hydraulics, depletion, and thermochemistry to simulate the evolving chemical behavior of the fuel salt in interactions with structural materials. Initial findings suggest that hot-cold leg corrosion in MSR systems may become significant if the redox potential of the fuel salt is not sufficiently controlled. Additionally, the impact of noble metal decay heat deposition in large power reactors is explored. The resulting engineering framework for species tracking will be applied in the future toward specific validation work with ongoing experimental efforts focusing on both chloride and fluoride salt loop experiments with in-situ corrosion and redox control instrumentation.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

In previous work, we introduced process family design. The main idea is to design a platform of common elements, and, allowing us to capture additional cost savings, simultaneously design a family of processes, and reducing both engineering and deployment timelines. We formulate this as an optimization problem, specifically a nonlinear generalized disjunctive program (GDP). We have proposed two approaches for reformulating and solving this problem: one based on full-discretization of the design space and one that uses Machine Learning (ML) surrogates to replace the nonlinear process models. Using ML surrogates to predict required system costs and performance indicators allows us to reformulate the nonlinearities in the GDP generate an efficient MILP formulation. In this work, we apply the ML surrogate approach to two case studies. One case study involves designing a family of carbon capture systems to cover a set of different flue gas flow rates and inlet CO 2 concentrations, where we consider the absorber and stripper as common unit module types. The second case study focuses on a water-desalination process, where we design a family of these processes for a variety of salt concentrations and flow rates. In both of these case studies, we demonstrate a scalable optimization approach that enables the design of multiple processes simultaneously, reducing the time-to-market and overall costs by maximizing the cost savings due to both economies of scale and economies of numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Integrase-on-Demand

SAND2025-07449O Integrase-on-Demand is a software tool that allows users to identify regions in genomic sequences where genetic material can be integrated with high probability. It uses a database of integrases and their DNA attachment sites to search against any genomic sequence, producing a list of open sites, the integrase sequence, and the source of the genomic island. The program requires MASH software to be available on the system. It consists of a main script and a precomputed input file, with a taxonomy mode that searches closely related genomes and a search mode that looks for identical attachment site matches in the integrase/attachment input file. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Williams, Kelly [Sandia National Lab. (SNL-CA), Li

Low-Mass and High-Efficiency Engine for Medium-Duty Truck Applications

This collaborative multi-year advanced engine technology project summarized in the report is to develop low mass and high efficiency medium-duty truck engine. The project was proposed as a large-scale engine design and demonstration enabled by an advanced materials and manufacturing development program, with a comprehensive plan spanning a period of four years (two phases).

33 ADVANCED PROPULSION SYSTEMS

FEED Study of CarbonCapture Inc DAC and CarbonCure Utilization Technologies Using United States Steel’s Gary Works Plant Waste Heat (Final Report)

The University of Illinois at Urbana-Champaign (UIUC) led this project to produce a front-end engineering design (FEED) study of an advanced Direct Air Capture and Utilization System (DACUS) system that can remove a minimum of 5,000 tonnes/yr net of carbon dioxide from air (based on cradle-to-gate LCA) and utilizing the CO 2 to produce low carbon intensity ready mix concrete. The designed system, if built, would be larger than any currently existing Direct Air Capture (DAC) collector in the U.S. Such carbon capture technologies are critical to meeting the goals of the DOE’s program to accelerate climate-critical technology. In addition to the power sector, industrial facilities for the manufacture of steel and cement/concrete are among the major sources of anthropogenic CO 2 . DAC is a promising new technology for reducing CO 2 , a potent greenhouse gas, in the atmosphere but is expensive, in part due to the energy required to adsorb and desorb captured CO 2 during cycles. By integrating CarbonCapture Inc. (CCI) DAC modules at United States Steel's Gary Works (USS) and utilizing the site's waste heat, energy, and location this project evaluates the feasibility of utilizing the captured CO 2 and the logistics of transportation. CarbonCapture Inc. has developed an innovative DAC system using novel adsorbents to cost-effectively capture CO 2 . The captured, liquified gas will be trucked to ready-mix concrete plants within the region, the closest of which is approximately 3.5 miles away, where CarbonCure will inject it into concrete during the mixing process at the facilities. The carbon dioxide reacts with concrete, mineralizing into calcium carbonate (CaCO 3 ), permanently locking the greenhouse gas into the matrix of the building material. This FEED study demonstrated a full CO 2 value chain for DACUS from industrial facilities. It also provided a means for Visage Energy Corp. (Visage) to assess the impact of this holistic approach on job creation, regional economic impact, and environmental justice. The project team also included Sargent & Lundy (S&L) to provide the constructability review and costing of the integration of the DAC with the steel plant. Ecotek Engineering USA, LLC designed the outside battery limit (OSBL) infrastructure to connect the DAC and the plant. Activities performed during the project included: (1) Project Management Plan; (2) Technology Maturation Plan (TMP); (3) Initial Workforce Readiness Plan; (4) Workforce Readiness Plan; (5) Front-End Engineering Design (FEED) Study; (6) Project Design Basis; (7) Hazards and Operability (HAZOP) Study; (8) Constructability Review; (9) Project Cost Assessment; (10) Logistics Analysis of CO 2 Transportation to the Utilization Site; (11) Business Case Analysis; (12) Life Cycle Analysis (LCA); (13) Environmental Health and Safety (EH&S) Analysis; (14) Environmental Justice Analysis; and (15) Economic Revitalization and Job Creation Outcomes Analysis. This report provides a summary of the outcomes and results of the project, which was performed between Oct. 1, 2022, through Sept. 30, 2024.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Truchas Overview

Truchas and Truchas-PBF are two sister codes for part-scale multi-physics modeling of manufacturing processes. Both programs are open source and made publicly available. They’re designed for efficient use of HPC resources and can be programmatically driven from Python packages. This enables automatic execution and analysis of ensembles of simulations, in some cases allowing 1000s of simulations to be evaluated in a day on HPC. Beyond just giving engineers a window into the concealed internal state of a system, the goal of Truchas is to provide a framework for developing novel manufacturing processes by understanding how the entire space of engineering inputs affects thermal state. It often is used to explore combinations of capabilities uncommon in commercial software, or to scale up analyses beyond the capabilities of commercial software.

97 MATHEMATICS AND COMPUTING

Improving Self-Driving Labs: Quantifying System-Level Experiment Repeatability and Broadening Instrument-Level Compatibility

Modular Autonomous Research System (MARS) is a self-driving laboratory (SDL) which performs wet-lab science with peptide-lanthanide combinations in an automated and, ultimately, an autonomous manner to aid in soil analysis for domestic lithium mining. Autonomous experimentation involves automated experimentation, experiment planning, and active learning. MARS consists of a 6-axis robotic arm (UR5e) on a linear rail, pipette robots (Opentrons 2), and microplate readers. These components transport, operate on, and collect data with chemical solutions in standard labware. For effective autonomy, MARS must perform system-level labware operations repeatably, plan experiments autonomously, and be portable between research-domains. Repeatability is evaluated by labware placement precision, such that future operations can properly locate labware, as well as the elapsed time, so that low variance mean estimates of experiment duration can inform high-level researcher decision making. Autonomous experiment planning is the next step to decouple experimentation from human management; however, there is a conflict between the ideal system-level experiment goals and the constraints imposed by instruments’ limitations. Sub-domain portability is a long-term goal to extend MARS’ research beyond the chemistry of peptide-lanthanide binding to other sub-domains without having to invest significant overhead to system retrofitting. To address these goals, we manually trained the robotic arm labware placement and modelled statistical failurerate and uncertainty Additionally, we benchmarked the duration and variance of each experiment sub-operation as a heuristic for research decision making. Next, we use a parameterized geometric program (PGP) approach to design experiments that optimize system-level objectives and satisfy instrument-level constraints. Lastly, we proposed a Python framework to maximize MARS’ extensibility to other scientific sub-domains through a JSON-based experiment specification.

36 MATERIALS SCIENCE

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION

Radio Frequency Field Programable Gate Array Implementation of Reflectometry Cable Monitoring

PNNL has developed an innovative cable testing system that leverages the Xilinx RF System-on-Chip (RFSoC) technology to create a more flexible and capable measurement tool than traditional approaches. The architecture is designed on the ZCU111 development board and takes advantage of the high-speed digital to analog converters (DAC) and analog to digital converters (ADC) to generate and capture digitally synthesized waveforms. The platform allows engineers to easily adjust power, frequency, duration and modulation on the fly rather than being locked into fixed hardware configurations

Tedeschi, Jonathan [Pacific Northwest National Lab

Analytical simulation of meander morphology from equilibrium to long-term evolution: Impacts of channel geometry and vegetation-induced coarsening

This study introduces an innovative approach to modeling meandering river morphology, integrating and investigating the effects of geometric characteristics and vegetation-induced channel coarsening. The developed comprehensive framework combines several advanced techniques: Genetic Programming for refining the scour factor of transverse bed slope, a Leaf Area Index (LAI)-enhanced analytical model for quantifying vegetative flow resistance, and an upstream-weighted moving average method for efficient approximation of the convolution integral in meander migration calculations. The model is validated against both an idealized Kinoshita meander and a natural bend of the Tumen River (China) in equilibrium, demonstrating its robustness across diverse scales and conditions. The model's ability to simulate the long-term evolution, including cutoff events, provides valuable insight for river management strategies. The current findings demonstrate that channel geometry, particularly width-to-depth ratio, plays a dominant role in meander evolution, with wider channels prone to more complex and rapid morphological changes. Vegetation effects are most pronounced in channels with moderate width-to-depth ratios, where they can significantly influence migration rates and bed topography. A combination of channel widening and deepening, coupled with strategic vegetation management, can effectively enhance navigability while maintaining channel stability in the studied Tumen River reach. Sensitivity analyses highlight the complex interplay between hydraulic conditions, sediment characteristics, and vegetation in shaping river morphology. This research advances understanding of the multifaceted nature of meandering river systems and offers practical tools for informed decision-making in river engineering and environmental management, particularly in the context of climate change and increasing anthropogenic pressures on fluvial ecosystems.

54 ENVIRONMENTAL SCIENCES