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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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LuSEE-night power distribution system design

The Lunar Surface Electromagnetic Experiment at Night (LuSEE-Night) is a low-frequency, 0.5 to 50 MHz, radio experiment on the radio-quiet far side of the Moon. The instrument will be launched by NASA Commercial Lunar Payload Services in 2026. The LuSEE-Night instrument core is composed of a radio frequency spectrometer (SPT) processing signals from four antennas, the Data Controller Board (DCB), low electromagnetic interference (EMI) Picket Fence Power Supply (PFPS), and Power Distribution Unit (PDU). The battery powers the instrument during the lunar night and stores energy harvested by the solar panel array during the lunar day. The battery charging is controlled by the Power Conditioning and Distribution Unit (PCDU). The unregulated power is supplied either by the SpaceCraft (S/C) or the battery and gets distributed to the PFPS, communication radio, heaters, and deployables through the PDU. The PFPS generates all regulated low-voltage rails using switching regulation synchronized to the LuSEE-Night clock, which ensures self-generated EMI will be confined to well-defined frequency bins. Here, we discussed the unregulated power distribution system architecture and functionality. The PDU engineering and flight modules are developed and characterized to confirm compliance with LuSEE-Night requirements. At the time of writing, all power subsystem components have been integrated into the payload.

47 OTHER INSTRUMENTATION↗

Field Validation of a Grid-Interactive Efficient Building Software Solution

The U.S. General Services Administration's (GSA's) Green Proving Ground (GPG) program, in partnership with the National Laboratory of the Rockies (NLR), completed a field study of a Grid-Interactive Efficient Buildings (GEB) software solution. The study focused on a single testbed facility to test the GEB functionality of the software solution, along with other features. The testbed facility - a courthouse - is a common building type in GSA's vast building portfolio, offering potentially impactful findings on a scalable level. The study evaluated Prescriptive Data's technology, Nantum OS, a connected building operating system ("GEB Solution") which aggregates multiple sources of previously siloed building data and combines that data with external sources, such as weather information or utility signals, into a single integrated platform. A GEB Solution is a type of Energy Management Information System (EMIS). EMIS is defined as a system of devices, data services, and software applications that communicates with any building system or third-party data source to aggregate and transform data into new capabilities to aid in the optimization of energy use at the building, campus, or agency level. This specific GEB Solution is an EMIS with ASO, automated system optimization, offering supervisory control of certain aspects of the Building Automation System (BAS). Multiple features were evaluated including, but not limited to, Continuous Demand Management to avoid setting new monthly kilowatt (kW) peaks, energy efficiency for reduction of kilowatt hours (kWh) and natural gas consumption, and automated demand response (ADR) for purposes of lowering demand during a utility called Demand Response (DR) event. The testbed facility was the Foley Federal Building and US Courthouse ("Foley Federal Building") located in Las Vegas, NV. This is a 209,496 sq. ft. building constructed in the 1960s with major renovations in 2004. The facility was a good candidate due to the large prevalence of office and courthouse spaces in the GSA portfolio of buildings. It also has many features which allow integration into and control of the building and a strong facilities team to assist with the study. Quantitative and qualitative performance objectives were developed using GSA's GPG GEB project template along with input from the vendor and building facility staff; these are outlined in Table 1. The quantitative performance objectives focused on continuous demand management, energy efficiency, and automated demand response. The qualitative performance objectives focused on the ease of installation and commissioning as well as the operability of the GEB solution. Other performance metrics that are reported on include carbon reduction, cost effectiveness, and occupant acceptance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An open control sequence specification to scale building demand flexibility via analytics software

For over two decades, researchers and practitioners have showcased the ability of large commercial buildings to provide grid services by shedding or shifting load. Various utility demand response (DR) and virtual power plant (VPP) programs throughout the United States are presently utilizing these demand-side resources. However, growth of these programs have been limited, in part due to the high cost necessary to integrate the DR control strategies into the building automation system (BAS). Implementing these strategies involves adjusting control sequences, necessitating dozens of hours of customized programming per building, limiting their adoption to large organizations and progressive owners. Recent efforts by researchers and industry have demonstrated the capability of energy management and information systems (EMIS), originally designed for fault detection and diagnostics, to interface with existing BAS and perform supervisory control to optimize building operations. While these approaches are quickly being adopted by industry, demand flexibility (DF) control strategies remain limited in product offerings. One of the challenges is the lack of documented best-practice DF sequences, despite the rich literature on field implementations. This paper develops a new open-specification for a zone-based temperature adjustment shed strategy for commercial building HVAC systems, describing the specification’s implementation in two EMIS tools in both experimental and field settings. Both implementations successfully reduced electric load by at least 40% on average during the called event, while maintaining temperature limits. This study’s detailed process from specification to deployment shows the potential for scalability as well as highlights challenges related to integration with heterogeneous BAS products.

Granderson, Jessica↗

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

Packages of Distributed Energy Technologies Demonstrating Demand Flexibility at Community Scale

The combination of increased electric load growth across all sectors, deferred electrical infrastructure investment, and other factors resulting in variable electric power supply, has created technical challenges to maintaining a resilient and reliable grid. Many federal, regional, and local efforts are in play to modernize the electric grid, including advancing building technologies and distributed energy resources (DERs) that are utilizing smarter controls to become responsive to both occupant and grid needs. This report reviews ten pilot projects demonstrating how groups of buildings combined with behind-the-meter (BTM) DERs such as electric vehicle (EV) charging, battery storage, flexible HVAC and domestic hot water systems, and photovoltaic systems can reliably and cost effectively provide grid services. Each of the ten pilot projects aim to deliver both energy efficiency and demand flexibility (DF) while supporting load growth. The ten demonstration teams are piloting flexible DER packages across diverse communities of residential and commercial buildings to address a variety of regional grid needs. The outcomes of these pilot projects will be used to inform future scaling through utility program development. This paper characterizes the ten teams, showcasing the decision-making process used by each group to develop their packages (Section 2), the grid services they plan to deliver (Section 3), the types of DER packages selected for deployment within building sectors (Section 4) and trends between building sector, DER types, and grid services In order to achieve community scale benefits, the pilot projects must utilize aggregated control mechanisms for coordinating buildings and DERs together. Several types of coordinated control architectures have evolved amongst the teams, influenced by use type, existing market conditions, and integration type. Three coordinated controls architectures have been characterized, highlighting their use cases, benefits, challenges, and tradeoffs in their design. These insights can aid utilities, control vendors, and developers in scaling community-level energy systems (Paul, 2024). Ultimately, the technology packages selected by the ten teams will be coordinated to provide power system services, also known as grid services. Insights from these demonstrations will be useful for grid operators, regulators, aggregators and other stakeholders as they look to deploy demand flexible resources as grid services in the future. The grid services that each team is targeting for demonstration are described in Section 3 and Section 4. Methods for evaluating the grid services have been described in the paper Metrics for Evaluating Grid Service Provision from Communities of Grid-interactive and Efficient Buildings and other DER (MacDonald, 2023). To identify technology packages for demonstration, Section 2 shows that project teams used a range of analysis approaches, including building energy modeling, AMI data analysis, cost-benefit frameworks, and utility pilot data. Some teams emphasized technical modeling to quantify grid impacts and demand reduction potential, while others prioritized economic evaluations, stakeholder input, or exploratory pilots to inform deployment decisions. This diversity reflects the need to tailor selection methods to project goals, available data, and organizational context. Section 5 discusses trends between the DER technologies deployed and the grid service provisions from each team. Residential buildings (multifamily and single family) lean towards technologies that enhance energy efficiency (e.g. weatherization upgrades, smart thermostats) and onsite power generation integration (e.g. solar PV). Commercial building demonstrations prioritize technologies that ensure operational reliability (e.g. battery storage) and centralized energy management systems and optimization solutions. Teams that are deploying controllable storage-based technologies are more likely to provide grid services that require a near real-time response. Teams incorporating load shifting technologies like smart thermostats with HEMs are likely to include energy markets participation and customer bill management offerings. Campus demonstrations are adopting diverse sets of DERs to emphasize renewable generation, paired with centralized control. This section also describes technologies that were considered during project planning but ultimately excluded from final deployment. These demonstrations reveal that effective DER package design should be tailored to building type, customer segment, and construction vintage. Multifamily buildings benefit from centralized HVAC upgrades and supervisory controls, while single-family homes are well-suited for individualized technologies like solar, storage, and smart home energy monitors. Commercial and campus settings prioritize EMIS integration and load optimization. New construction enables cost-effective integration of DER-ready infrastructure, whereas retrofits require deployments aligned with owner and tenant value streams. For utility program planners, early coordination with developers and building owners, paired with segmented and modular program offerings, can improve adoption, scalability, and grid impact.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles

The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.

47 OTHER INSTRUMENTATION↗

A ModEx Framework for Watershed Subsurface Investigation With Limited Geophysical Data Using Machine Learning and Hydrologic Modeling

Abstract Subsurface heterogeneity influences watershed hydrology strongly but remains difficult to characterize at catchment scales with sparse and costly field data. Geophysical surveys such as electromagnetic induction (EMI) provide local spatial subsurface images yet scaling them to watershed scales and converting EMI‐derived resistivity into hydraulic properties remains a challenge. We present a Model–Experiment (ModEx) framework that integrates limited EMI data with machine learning (ML) and hydrologic modeling to improve process representation and guide field investigations. Sparse EMI surveys were scaled to the catchment scale using a Random Forest model, and the resulting resistivity fields were combined with nearby borehole constraints to parameterize a hydrologic model. The EMI‐informed hydrological simulations improved predictions of streamflow sustained by subsurface flow and shallow saturation patterns. By combining EMI data and ML with hydrologic modeling, the ModEx framework guides future subsurface surveys, providing a transferable and efficient strategy for data–model integration across diverse watersheds. Plain Language Summary Mapping the underground network of soil and rock that controls water is essential for predicting floods and droughts, but seeing underground is difficult and expensive. We cannot drill everywhere, so scientists use geophysical tools to scan broad areas. There are two key challenges: these geophysical scans are often sparse across the whole watershed, and the geophysical data is hard to translate into water‐related properties. We used artificial intelligence to solve these problems. We taught a computer to find patterns linking the limited geophysical data to the land surface properties. This allowed it to fill in the gaps and create a complete, useful subsurface map for the entire watershed. This new map improves hydrologic simulations, leading to more accurate predictions of water movement in the watershed. It also helps scientists build better models with less data and generates a priority map showing where to measure next, making future investigations more efficient. Key Points Limited EMI scaled with ML improves catchment‐scale subsurface parameterization for hydrologic models The framework integrates hydrologic modeling with limited geophysical data to support subsurface investigation design ModEx framework offers a transferable data–model integration strategy that quantifies and reduces uncertainty guiding watershed studies

Chen, Hang↗

5G-TSN Architecture Capable of Providing Real-time Situational Awareness to Fossil-Energy (FE) Generation Systems (Final Technical Report)

This final report highlights the comprehensive achievements of the project focused on developing and validating a 5G-Time Sensitive Networking (TSN) architecture tailored for real-time operational awareness in fossil energy systems. The initiative successfully advanced through a series of technical milestones, including the integration of EMI-aware network models, deployment of advanced simulation frameworks, and real-world performance characterization at key sites such as UTEP and Fabens. Through the strategic use of NetSim® software, the team created and validated network configurations for wired and wireless environments, tested under varying congestion conditions, and verified network slicing implementations for URLLC-specific applications. Major accomplishments include the migration of simulation tools to the latest NetSim® version to support accurate modeling of TSN and network slicing, extensive EMI measurement campaigns, and the development of a robust simulation model for end-to-end SCADA system integration. Simulations compared both TDD and FDD duplexing modes, revealing insights into their performance under congested conditions. The wireless network was benchmarked for throughput, jitter, and delay metrics, aligning with 3GPP Release 15/16 and IEEE 802.1-TSN standards. A peer-reviewed conference paper was accepted and published, contributing to the broader academic and industrial discourse on 5G-TSN integration in energy systems, in addition to a journal article. Despite minor delays due to software limitations, the project achieved its objectives and delivered validated architecture ready for deployment in advanced energy network environments.

01 COAL, LIGNITE, AND PEAT↗

Ligand‐Directed Actinide Oxo‐Bond Manipulation in Actinyl Thiacalix[4]arene Complexes

Understanding the chemistry of the inert actinide oxo bond in actinyl ions AnO2 2+ is important for controlling actinide behavior in the environment, during separations, and in nuclear waste (An=U, Np, Pu). The thioether calixarene TC4A (4-tert-butyltetrathiacalix[4]arene) binds equatorially to the actinyl cation forming a conical pocket that differentiates the two trans-oxo groups. The 'ate' complexes, [A]2[UO2(TC4A)] (A=[Li(DME)2], HNEt3) and [HNEt3]2[AnO2(TC4A)] (An=U, Np, Pu), enable selective oxo chemistry. Silylation of the UVI oxo groups by bis(trimethylsilyl)pyrazine occurs first at only the unencapsulated exo oxo and only one silylation is needed to enable migration of the endo oxo out of the cone, whereupon a second silylation affords the stable UIV cis-bis(siloxide) [A]2[U(OSiMe3)2(TC4A)]. Calculations confirm that only one silylation event is needed to initiate oxo rearrangement, and that the putative cis dioxo isomer of [UO2(TC4A)]2- would be stable if it could be accessed synthetically, at only 23 kcal.mol-1 in energy above the classical trans dioxo. Calculations for the transuranic cis[AnO2(TC4A)]2- (An=Np, Pu) are at higher energies, 30-35 kcal.mol-1, retaining the U complexes as the more obvious target for a cis-dioxo actinyl ion. The aryloxide (OAr) groups of the macrocycle are essential in stabilizing this as-yet unseen uranyl geometry as further bonding in the TC4A U-OAr groups stabilizes the U=O 'yl' bonds, explaining the stability of the putative cis[UO2(TC4A)]2- in this ligand framework.

Pyrch, Mikaela M↗

Ligand‐Directed Actinide Oxo‐Bond Manipulation in Actinyl Thiacalix[4]arene Complexes

Abstract Understanding the chemistry of the inert actinide oxo bond in actinyl ions AnO 2 2+ is important for controlling actinide behavior in the environment, during separations, and in nuclear waste (An=U, Np, Pu). The thioether calixarene TC4A (4‐ tert ‐butyltetrathiacalix[4]arene) binds equatorially to the actinyl cation forming a conical pocket that differentiates the two trans‐ oxo groups. The ‘ate’ complexes, [A] 2 [UO 2 (TC4A)] (A=[Li(DME) 2 ], HNEt 3 ) and [HNEt 3 ] 2 [AnO 2 (TC4A)] (An=U, Np, Pu), enable selective oxo chemistry. Silylation of the U VI oxo groups by bis(trimethylsilyl)pyrazine occurs first at only the unencapsulated exo oxo and only one silylation is needed to enable migration of the endo oxo out of the cone, whereupon a second silylation affords the stable U IV cis‐ bis(siloxide) [A] 2 [U(OSiMe 3 ) 2 (TC4A)]. Calculations confirm that only one silylation event is needed to initiate oxo rearrangement, and that the putative cis dioxo isomer of [UO 2 (TC4A)] 2− would be stable if it could be accessed synthetically, at only 23 kcal.mol −1 in energy above the classical trans dioxo. Calculations for the transuranic cis [AnO 2 (TC4A)] 2− (An=Np, Pu) are at higher energies, 30–35 kcal.mol −1 , retaining the U complexes as the more obvious target for a cis ‐dioxo actinyl ion. The aryloxide (OAr) groups of the macrocycle are essential in stabilizing this as‐yet unseen uranyl geometry as further bonding in the TC4A U‐O Ar groups stabilizes the U=O ‘yl’ bonds, explaining the stability of the putative cis [UO 2 (TC4A)] 2− in this ligand framework.

Pyrch, Mikaela M. [College of Chemistry University↗