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DOE OSTI2026

Organic Rankine Cycle Integration and Optimization for High Efficiency CHP Genset Systems (Final Technical Report)

This project successfully advanced the integration of Organic Rankine Cycle (ORC) technology with reciprocating engine–based combined heat and power (CHP) systems to improve electrical efficiency, total CHP efficiency, and grid-responsive operation. Over three budget periods, the work progressed from high-temperature ORC component development and thermodynamic model validation to next-generation system design, working fluid transition, and techno-economic analysis. Key technical accomplishments include development and validation of a thermodynamic model capable of accurately predicting ORC performance across an expanded temperature and pressure envelope; successful identification and validation of low-global-warming-potential (GWP) working fluids—most notably R1233zd(E)—as viable replacements for R245fa; and demonstration of scalable ORC architectures suitable for integration with 1–20 MW class reciprocating engines. These advances enable flexible CHP configurations that can increase electrical output while maintaining high overall utilization of available thermal energy. The project also produced a clean-sheet design for a next-generation ORC system targeting substantially higher power output per unit, supported by detailed component selection, heat exchanger evaluation, and system-level modeling. Techno-economic analyses indicate that ORC-enabled flexible CHP systems can meet or exceed Department of Energy (DOE) efficiency targets while providing value to both facility operators and the electric grid.. Late-stage testing of the largest next-generation ORC prototype identified limitations related to pump net positive suction head (NPSH) requirements and condenser flooding under certain operating conditions. Although these issues constrained full validation of that configuration within the project timeframe, they provided clear and actionable design guidance for future system refinements. Importantly, validated modeling, smaller-scale testing, and working fluid evaluations confirmed the technical viability of the overall approach. In aggregate, this project met its core objectives by establishing validated design tools, de-risking key ORC technologies for CHP applications, and defining a credible pathway toward commercialization of flexible, high-efficiency CHP systems. The results form a strong foundation for continued development and deployment beyond the conclusion of the DOE-funded effort.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

Potential biological control agents of Geosmithia morbida restrict fungal pathogen growth via mycoparasitism and antibiosis

Abstract Thousand cankers disease of Juglans (walnut) and Pterocarya (wingnut) spp. (Fagales: Juglandaceae) is caused by the fungal pathogen Geosmithia morbida Kolarík, Freeland, Utley, and Tisserat (Hypocreales: Bionectriaceae) and bark beetle pest/vector, Pityophthorus juglandis Blackman (Coleoptera: Curculionidae). To further the development of biological management strategies for thousand cankers disease, we assessed the ability of 14 endophytic Trichoderma (Hypocreales: Hypocreaceae) isolates and the commercially available isolate T. afroharzianum strain KRL-AG2 to inhibit the in vitro growth of three different G. morbida isolates via mycoparasitism and antibiosis. To identify factors that may affect field success of candidate biological control agents, we quantified the growth responses of Trichoderma spp. and the commercially available entomopathogenic fungus, Beauveria bassiana (Bals.-Criv.) Vuill. (Hypocreales: Cordycipitaceae) strain GHA, to the plant secondary metabolite and antimicrobial compound, juglone in vitro. A total of 12 Trichoderma isolates (from six different Trichoderma species) demonstrated antagonistic activity towards G. morbida in dual-plate assays. Juglone consistently reduced the growth of B. bassiana strain GHA and 14 of the 15 screened Trichoderma isolates in vitro. Additionally, one metabolite-producing Trichoderma isolate, TN4-47, completely inhibited the growth of all three G. morbida isolates across all tested metabolite concentrations and had comparatively greater tolerance to juglone compared to other Trichoderma isolates. Future lines of research should focus on characterizing the active antagonistic compound present in the metabolite filtrates, determine the mode of action of the active component(s), and elucidate how abiotic and biotic factors may influence the growth, persistence, and antagonistic activity of candidate biological control agents in planta .

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Using Generative AI to implement the discrepancy checker for a Nearly Autonomous Management and Control System for Advanced Reactors

Developments related to generative artificial intelligence (AI) have brought a major breakthrough in AI. These developments are rapidly accelerating developments in different science and engineering applications. Nearly Autonomous Management and Control (NAMAC) system provides recommendations to the operator for maintaining the safety and performance of the reactor. The discrepancy checker (DC) is an important component of the NAMAC) system, whose goal is to determine if the plant is moving towards the expected system state after the control actions are injected. In this work, we explore generative AI methods, particularly, a generative pretrained transformer (GPT) for implementing the DC function in NAMAC. The GPT-based DC aims to alert the operator in situations outside NAMAC’s scope and act as a chatbot the operator can use to retrieve relevant information. This study involves two versions of GPT developed by OpenAI: GPT-3.5 and GPT-4. These GPTs are trained on huge amounts of undisclosed general domain datasets. We explored two methods to adapt GPTs for DC implementation in NAMAC: fine-tuning and retrieval augmented generation. A small knowledge base (information file) that encompasses rules for DC implementation and some general information related to NAMAC has been created to support DC implementation using GPT. In this work, the GPT-based DC implementations have been tested for their reasoning abilities, comprehension, information retrieval, and extraction abilities. It should be noted that this paper only presents a preliminary study to test the feasibility of DC implementation using generative AI technology. Given the potential risks and severe consequences associated with nuclear reactor applications, combined with the black-box nature of AI, extensive offline and online testing and reliability analyses of GPT-based DCs are needed for further developing such capabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Progress of Gas Injection EOR Surveillance in the Bakken Unconventional Play—Technical Review and Machine Learning Study

Although considerable laboratory and modeling activities were performed to investigate the enhanced oil recovery (EOR) mechanisms and potential in unconventional reservoirs, only limited research has been reported to investigate actual EOR implementations and their surveillance in fields. Eleven EOR pilot tests that used CO2, rich gas, surfactant, water, etc., have been conducted in the Bakken unconventional play since 2008. Gas injection was involved in eight of these pilots with huff ‘n’ puff, flooding, and injectivity operations. Surveillance data, including daily production/injection rates, bottomhole injection pressure, gas composition, well logs, and tracer testing, were collected from these tests to generate time-series plots or analytics that can inform operators of downhole conditions. A technical review showed that pressure buildup, conformance issues, and timely gas breakthrough detection were some of the main challenges because of the interconnected fractures between injection and offset wells. The latest operation of co-injecting gas, water, and surfactant through the same injection well showed that these challenges could be mitigated by careful EOR design and continuous reservoir monitoring. Reservoir simulation and machine learning were then conducted for operators to rapidly predict EOR performance and take control actions to improve EOR outcomes in unconventional reservoirs.

Energy & Fuels↗

DOE OSTI2025

Financing Options for Onsite Generation, Energy Storage, and Energy Efficiency Projects

Across sectors, commercial and industrial facilities are benefiting from the implementation of renewable energy generation, storage, and energy efficiency projects. Despite the potential for these projects to reduce onsite energy consumption, build resiliency, and lower operational costs in the long term, the initial expenses are often high. However, there are a growing number of financing mechanisms that can be leveraged. When deployed strategically, these mechanisms can give organizations the financial tools to install projects that accomplish their energy goals. In 6 steps, this resource introduces organizations to a general process to contextualize the many different financing options, ultimately facilitating an informed selection of financing mechanisms. Step 1 discusses the importance of establishing clear organizational preferences. Step 2 briefly introduces common financing options and Steps 3 and 4 provide guidance for selecting mechanisms based on locational availability and organizational preferences. Finally, Steps 5 and 6 show how mechanisms can be combined with incentives and provide preliminary guidance for selecting and engaging with external partners. While this document provides a general approach to selecting a financing mechanism for renewable energy generation, storage, and/or energy efficiency, it does not contain tax and/or legal advice. A tax advisor should be consulted before taking any action.

25 ENERGY STORAGE↗

DOE OSTI2025

A critical review and meta-analysis of energy demand, carbon footprint, and other environmental impacts from carbon fiber manufacturing

The demand for carbon fibers and carbon fiber-reinforced polymers (CFRPs) is rapidly growing due to their outstanding mechanical properties and potential to enhance sustainability, particularly for lightweighting applications. However, carbon fibers are typically produced from fossil-based feedstocks, involve energy-intensive processes, and have limited options for sustainable end-of-life management or circularity. Despite these challenges, the energy demand and lifecycle environmental implications of their production remain poorly understood. Here, we conduct a critical literature review and meta-analysis of carbon fiber manufacturing, revealing significant variations in reported energy demand, carbon footprint, and lifecycle inventory data. Our analysis makes two novel contributions. First, we identify key underlying factors driving these variations. Second, we highlight that carbon fiber, far from being a homogeneous product, has grades varying substantially in mechanical properties, end-use markets, energy intensity of manufacturing processes, and therefore environmental impacts—an aspect often underrepresented in life cycle assessments. We assert that current data are insufficient for reliably evaluating environmental impacts, posing a risk of misleading decision-making. Addressing this gap requires new lifecycle inventory datasets clearly incorporating carbon fiber heterogeneity and key influencing factors identified in this study. Additionally, we propose actionable recommendations, including a checklist, to advance sustainability in the carbon fiber sector.

CED↗

DOE OSTI2025

X-ray crystallographic and hydrogen deuterium exchange studies confirm alternate kinetic models for homolog insulin monomers

Despite the crucial role of various insulin analogs in achieving satisfactory glycemic control, a comprehensive understanding of their in-solution dynamic mechanisms still holds the potential to further optimize rapid insulin analogs, thus significantly improving the well-being of individuals with Type 1 Diabetes. Here, we employed hydrogen-deuterium exchange mass spectrometry to decipher the molecular dynamics of newly modified and functional insulin analog. A comparative analysis of H/D dynamics demonstrated that the modified insulin exchanges deuterium atoms faster and more extensively than the intact insulin aspart. Additionally, we present new insights derived from our 2.5 Å resolution X-ray crystal structure of modified hexamer insulin analog at ambient temperature. Furthermore, we obtained a distinctive side-chain conformation of the Asn3 residue on the B chain (AsnB3) by operating a comparative analysis with a previously available cryogenic rapid-acting insulin structure (PDB_ID: 4GBN). The experimental conclusions have demonstrated compatibility with modified insulin’s distinct cellular activity, comparably to aspart. Additionally, the hybrid structural approach combined with computational analysis employed in this study provides novel insight into the structural dynamics of newly modified and functional insulin vs insulin aspart monomeric entities. It allows further molecular understanding of intermolecular interrelations driving dissociation kinetics and, therefore, a fast action mechanism.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Uncertainty-Aware and Explainable Human Error Detection in the Operation of Nuclear Power Plants

The timely and accurate identification of incidents, such as human factor error, is important to restore nuclear power plants (NPPs) to a stable state. However, the identification of abnormal operating conditions is difficult because of the existence of multiple scenarios. In addition, to implement mitigation actions rapidly after an incident occurs, operators must accurately identify an incident by monitoring the trends of many variables. The mental burden posed by this can increase human error and cause failure in identifying incidents. Failure to identify incidents directly results in erroneous mitigation measures, which are detrimental to NPPs. In this study, we leverage uncertainty-aware models to identify such errors and thereby increase the chances of mitigating them. We use the data collected from a physical test bed. The goal is to identify both certain and accurate models. For this, the two main aspects of focus in this study are explainable artificial intelligence (XAI) and uncertainty quantification (UQ). While XAI elucidates the decision pathway, UQ evaluates decision reliability. Their integration paints a comprehensive picture, signifying that understanding decisions and their confidence should be interlinked. Thus, in this study we leverage UQ measures (e.g. entropy and mutual information) along with Shapley additive explanations to gain insights into the features contributing to both accuracy and uncertainty in error identification. Furthermore, our results show that uncertainty-aware models combined with XAI tools can explain the artificial intelligence–prescribed decisions, with the potential of better explaining errors for the operators.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2026

Microsecond-latency feedback at a particle accelerator by online reinforcement learning on hardware

The commissioning and operation of future large-scale scientific experiments will challenge current tuning and control methods. Reinforcement learning (RL) algorithms are a promising solution due to their ability to dynamically adapt to changing environments and consider delayed consequences. In many real-world applications, RL policies must produce actions in real time, often within microseconds to milliseconds, imposing significant constraints on system latency and computational overhead that conventional machine learning libraries are not designed to handle. To control phenomena in real time at these timescales, RL needs to be deployed on-the-edge, namely on dedicated hardware located near the system it controls, without relying on a host CPU or cloud-based inference. In this work we present the design and deployment of an experience accumulator system in a particle accelerator. In this system, deep-RL algorithms run using hardware acceleration and act within a few microseconds, enabling the use of RL for control of phenomena like beam instabilities. The training uses the collected data offline to reduce the number of operations carried out on the acceleration hardware. The proposed architecture was tested in real experimental conditions at the Karlsruhe research accelerator, a synchrotron light source, where the system was used to control artificially induced horizontal betatron oscillations in real-time, with a control loop period of just 2.7 μs. The results showed a performance comparable to the commercial feedback system available at the accelerator, demonstrating the viability and potential of this approach. Due to the self-learning and reconfiguration capability of this implementation, a seamless application to other control problems is possible. Applications range from particle accelerators to large-scale research and industrial facilities.

FPGA↗

DOE OSTI2026

Qualitative Risk Assessment of Legacy Wells within the Estimated Prairie State Generating Company Area of Review

This report details the digitization of a legacy wellbore database, including data processing assumptions, parameter estimation, and risk assessment methodology. The database, comprising 6,454 documents, was provided by ISGS. It includes valuable data from the Prairie State Generating Company (PSGC) and One Earth Energy (OEE) sites of the CarbonSAFE Phase III – Illinois Storage Corridor project. The report focuses on wells within a 15-mile radius from the Lively Grove #1 (LG#1) well at PSGC site, evaluating subsurface conditions and potential risks. A total of 4,386 wellbores within 15 miles of the LG#1 well were filtered based on depth and formation codes. LG#1 is the stratigraphic well at the PSGC site drilled in 2021. Ninety-four (94) wells penetrating the Maquoketa Shale Group (the primary confining unit) within the estimated area-of-review (AoR) for the PSGC site were evaluated using a qualitative risk assessment (QRA) methodology. The QRA developed by Arbad et al. 2022 focuses on legacy wells within the AoR and categorizes them based on well construction details. The QRA identifies wells that need immediate attention by categorizing them based on penetration depth and protection. Wells within the AoR were categorized into nine groups based on penetrations and protections. These categories range from Type 1 wells, with no documentation, to Type 9 wells, which do not penetrate the primary confining unit or storage reservoir (unit). Well accessibility within the AoR varies based on well status, including Dry & Abandoned (DA), Plugged & Abandoned (PA), Injection (INJ), Oil/Gas Producing (PROD), and Observation (Obs) wells. Accessibility levels were determined by well construction, with DA wells being the least accessible and Observation wells the most accessible, impacting gas leakage detection possibilities. Remedial action priority of wells decreases from Type 1 to Type 9 wells. Type 1 to Type 6 wells with status DA and PA require immediate attention, while Type 7 and Type 8 wells are low priority. A risk matrix used to prioritize corrective actions for legacy wells is proposed to categorize wells within an AoR based on penetrations, protections, and accessibility. The methodology involves data acquisition, well categorization into nine types, and determining CO 2 leakage pathways using well schematics and geospatial mapping. This approach is particularly useful for managing the integrity of legacy wells throughout the lifecycle of a Carbon Capture and Storage (CCS) project. A qualitative risk assessment of 94 wells within the AoR of the PSGC site identified 54 wells with high priority for corrective action due to penetration of the primary containment seal. The assessment utilizes color-coded maps to categorize well types and prioritize corrective actions, providing a comprehensive analysis. Schematics of wells penetrating the primary confining unit were drawn, and leakage pathways were identified. Details of all wells penetrating the confining zone are provided in the appendix, including information on well types, plugging, and casing status.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Optimizing bioenergy biofuel harvest: a comparative analysis of stepwise and integrated methods for economic and environmental sustainability

Switchgrass is a promising bioenergy feedstock due to its high biomass yield potential, adaptability to marginal lands, and low carbon intensity for feedstock production. However, accurate cost estimation and assessment of greenhouse gas (GHG) emissions for the energy-intensive harvesting process are essential for evaluating the sustainability of bioenergy. This study provides a comparative analysis of two harvesting methods: the Stepwise Method, which separates operations into multiple stages, and the Integrated Method, which combines mowing and raking into a single pass. The analysis was conducted under four scenarios based on field sizes and biomass yields. Using three years of field-scale switchgrass harvest data from 125 sites, GHG emissions, energy consumption, and harvesting costs were quantified using the GREET model and techno-economic analysis. Additionally, regression analysis identified key climate and operational factors affecting fuel consumption. The Stepwise method was the most cost-effective for large fields with high biomass yield, achieving the lowest harvesting costs ($37.70 per ton). In contrast, the Integrated Method performed better in small fields and low-yield conditions, reducing GHG emissions by 9 % and energy use by 5 %. Regression analysis confirmed that a larger field size reduced fuel consumption, while higher biomass yield and longer operational time increased fuel use. Maximum temperature also contributed to a slight increase in fuel consumption. Furthermore, these results provide actionable insights for optimizing harvesting strategies based on field-specific conditions and operational goals, contributing to the economic and environmental sustainability of bioenergy production.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Digital Assurance Checklist for Homeowners and Installers

This document provides a comprehensive Digital Assurance Checklist for securing behind-the-meter energy assets, focusing on both installers and homeowners. As distributed energy resources (DERs) such as solar PV and battery storage become integral to residential energy systems, cybersecurity emerges as a critical component of reliability and safety. The guide outlines actionable steps for installers during pre-installation, commissioning, and post-installation phases, emphasizing practices like network segmentation, credential management, firmware validation, and homeowner education. For homeowners, the document introduces a tiered approach to cyber hygiene—from essential measures like strong Wi-Fi credentials and automatic updates to advanced strategies such as network segmentation, DNS filtering, and intrusion detection. By adopting these practices, stakeholders can mitigate cyber risks, safeguard energy infrastructure, and ensure resilient, secure operation of DER systems. Additional resources and references to industry standards are included to support implementation.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Digital Assurance Checklist for Homeowners and Installers

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Chemical Process Safety at TRISO-Based, Metal-Based, and Salt-Based Fuel Fabrication Facilities: Technical Assessment and Guidance Assessment

As part of efforts to prepare for potential and ongoing safety reviews for licensing of advanced non-light-water reactor fuel cycles, the U.S. Nuclear Regulatory Commission (NRC) tasked Pacific Northwest National Laboratory to prepare an assessment on the state of knowledge of potential chemical processes at fuel cycle facilities supporting the front end of these fuel cycles, and to assess the associated regulatory guidance. This report provides a technical assessment of chemical process safety considerations to support NRC licensing reviews of fabrication processes for tri-structural isotropic (TRISO) based, metallic-based, and salt-based fuels. The assessments involved collecting publicly available information on the fuel fabrication processes to (i) identify the operational process steps, characteristics and chemicals involved, (ii) identify the physical safety considerations and health safety considerations during licensing reviews of the various process steps, and (iii) collect information to support assessments of severity of accidents and potential mitigative measures to be implemented. The assessment provides a foundational basis on chemical process safety considerations for advanced fuel fabrication activities, although it is recognized that licensing reviews may necessitate design-specific considerations. The specific conditions under which chemical hazards emerge will require process-specific considerations, highlighting the importance of process-informed interpretation. The assessment also determined that exposure guidelines and limits to assess the consequences of acute exposures are limited for some chemicals, although alternative limits and supplementary information from databases or safety data sheets provide sufficient information to evaluate consequences of acute exposures. In addition, it was identified that metallic and salt fuel fabrication processes may involve beryllium, which is an exposure hazard. The regulatory framework for the licensing of advanced fuel cycle facilities, per 10 CFR Part 70 Domestic Licensing of Special Nuclear Material, is deemed robust and flexible to address the chemical safety considerations in this report. A review was conducted on various regulatory guidance and technical basis documents. This included reviewing NUREG-1520, Revision 2, Standard Review Plan for Fuel Cycle Facilities License Applications – Final Report and the process descriptions in Appendix A of NUREG/CR-6410, Nuclear Fuel Cycle Facility Accident Analysis Handbook, to address advanced fuel types. As new fuels will involve process-specific chemical uses, process-specific considerations are provided in this report. Additionally, it is noted that the U.S. Department of Energy protective action criteria database includes Temporary Emergency Exposure Limits (TEELs) for process-specific chemicals. This report provides technical information to support chemical safety assessments of new advanced fuel cycle facilities and identifies technical and safety information to support licensing reviews. No regulatory barriers were identified for the licensing of advanced fuel cycle facilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Zero-Emission Transit Bus Needs Assessment

The transition to zero-emissions vehicles (ZEVs) in public transit has gained traction due to significant federal investments from the Bipartisan Infrastructure Law (BIL) and the Inflation Reduction Act (IRA). This needs assessment, commissioned by the Joint Office of Energy and Transportation and conducted by researchers at the Idaho National Laboratory, explores the current state of electrification in transit agencies, identifying barriers to implementation, potential funding sources, and operational considerations necessary for a successful transition. The assessment involved qualitative interviews with representatives from 19 transit service providers across diverse geographic regions. Key findings highlight the challenges related to bus facilities and operations, which require careful planning for charging infrastructure and maintenance capabilities to accommodate battery electric buses (BEBs) and hydrogen fuel cell buses (HFCBs). Agencies reported operational hurdles due to the shorter range of BEBs compared to diesel buses, necessitating revised scheduling and routing strategies. Despite these challenges, many agencies expressed optimism about their capacity to adapt. Funding availability emerged as a critical factor influencing the transition to ZEVs. While agencies welcomed increased financial support, particularly from the Low or No Emission Grant Program (Lo-No), concerns about the sustainability of this funding and the ongoing operational costs were prevalent. The need for a comprehensive funding inventory was underscored to ensure transit agencies are aware of all available resources. Technological constraints were significant barriers to ZEV adoption. The limited range of BEBs was frequently cited as a concern, leading to operational challenges and reliability issues. Agencies reported difficulties in sourcing replacement parts, which exacerbated downtime and maintenance challenges. Workforce development and training were identified as pivotal for a successful transition. Many agencies rely heavily on manufacturers for technician training, highlighting the need for scalable training programs that equip staff with the necessary skills to maintain electric powertrains effectively. This assessment offers actionable recommendations for the Joint Office, including enhancing outreach to transit agencies, developing resources for effective utility partnerships, and facilitating comprehensive training programs. Establishing a zero-emission bus evaluation program to track performance metrics such as cost, range, and reliability could provide valuable insights for transit agencies. The needs assessment provides a detailed examination of the challenges and opportunities facing transit agencies in their transition to zero-emissions bus fleets. By addressing these issues through targeted support, stakeholders can collaboratively work towards a cleaner, more sustainable public transportation system that benefits all communities.

33 - ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

From Data to Knowledge: A Graph-Based Reliability Approach to Assess System Health

With the goal of maximizing plant reliability and availability, complex systems such as nuclear power plants continuously monitor and record the performance and the health status of many components, assets, and systems. Such data may take the form of online monitoring data, condition reports, and maintenance reports and it carries the potential to provide system engineers with insights into anomalous behaviors or degradation trends as well as the possible causes behind them and to predict their direct consequences. The analysis of such data poses however few challenges. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly tackles these challenges, and it focuses on the integration of all these data elements in order to assist plant system engineers in analyzing component, assets, and systems performances and optimize maintenance activities. This is performed by 1) extracting knowledge from textual data via technical language processing methods, and 2) quantifying system, asset, and component health from numeric condition-based data. We rely on model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Numeric and textual data elements are then associated with an MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Nanoparticle-mediated antagonism of sustained endosomal signaling of the calcitonin receptor-like receptor provides enhanced and persistent relief of oral cancer pain

By improving the delivery and tumor retention of chemotherapeutics, nanomedicines hold potential for cancer treatment. The usefulness of nanoparticle (NP)-encapsulated analgesics for the cancer pain treatment is comparatively unexplored. We investigated whether NPs encapsulating olcegepant (OCP), an antagonist of the calcitonin receptor-like receptor (CLR) for the calcitonin gene-related peptide (CGRP), effectively relieved oral cancer pain in mice. Because persistent endosomal CLR signaling in Schwann cells mediates craniofacial pain, we reasoned that the predisposition of NPs to accumulate in endosomes could be leveraged to effectively relieve oral cancer pain. By expressing biosensors for activated CLR, Gα proteins and β-arrestins in HEK293T and Schwann cells, we found that CGRP activates CLR signaling first at the plasma membrane and then in early, late and recycling endosomes and the cis- and trans-Golgi apparatus. We synthesized biocompatible NPs encapsulating OCP and fluorophores by integrating hydrophobic ion pairing nanoformulation with Flash NanoPrecipitation. NPs slowly released OCP and accumulated in early endosomes, leading to sustained inhibition of endosomal CLR signaling in HEK293T and Schwann cells. Oral cancers were established in mice, which led to heightened pain-like responses. After intra-tumoral injection, NPs were retained in tumors for at least one week. OCP-loaded NPs almost completely reversed allodynia and hyperalgesia for a prolonged period, whereas unencapsulated OCP had small and transient effects. The NP accumulation in endosomal sites of pain signaling, the sustained release of antagonist, and the retention of NPs in tumors explain their beneficial actions. Thus, NP-encapsulation holds promise for the relief of painful cancers that are inadequately treated by opioids.

Calcitonin gene-related peptide↗

DOE OSTI2026

Polyoxometalate-Assisted Crystallization: A General Strategy Enabling Structural Characterization of Molecular Radium Complexes

A fundamental understanding of radium (Ra) coordination chemistry has been hindered by the scarcity and radiological hazards of 226 Ra, leaving the structural characterization of molecular Ra complexes almost entirely unexplored. Here, we introduce a polyoxometalate (POM)-assisted crystallization strategy that enables single-crystal X-ray diffraction analysis of Ra–chelator complexes from microgram-scale samples. Employing the plenary Keggin anion [SiW 12 O 40 ] 4– , we isolated and structurally characterized Ra 2+ complexes of 18-crown-6 and the bis-picolinate macrocycle macropa, together with their Sr 2+ and Ba 2+ analogues. The resulting structures reveal systematic, size-dependent trends in coordination number and metal-donor distances across the alkaline earth series and provide the first direct experimental measurements of Ra–N and Ra–OCOO bond distances. Together, these results establish POM-assisted crystallization as a robust approach for obtaining solid-state structural information on Ra 2+ complexes of organic chelators, opening new opportunities to advance the coordination chemistry needed to fully realize radium’s potential in isotope production and targeted radiotherapy. More broadly, this approach expands the experimental toolkit available for studying scarce, highly radioactive elements accessible only in microgram quantities.

Anions↗