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At least 811 records · Page 45

Mitigating Transition Metal Dissolution from Mn-rich Cathodes: Influence of Processing and Testing Methods

Manganese-rich oxides continue to gain interest with respect to the development of Earth-abundant options for lithium-ion cathodes. Of the unique challenges that hinder the respective performance of various classes of such materials, manganese dissolution still stands as a common theme. The work herein explores Li 3 PO 4 as a robust surface protection layer on a prototypical, Co-free, manganese-rich cathode in the way of a lithium- and manganese-rich oxide. The study highlights the critical importance of synthesis and processing in realizing optimal performance of a given surface treatment by comparing sol-gel and atomic layer deposition methods. Furthermore, cycling protocols are emphasized as a critical factor in adequately gauging the efficacy of surface protection strategies to mitigate manganese dissolution and the subsequent electrochemical consequence. Optimized Li 3 PO 4 coatings coatings on lithium- and manganese-rich cathode particles are shown to greatly mitigate capacity fade, impedance rise, pore/void formation and mechanical damage during long-term cycling.

Mallick, Subhadip [Argonne National Laboratory (AN↗

Divertor Plasma Detachment Control Neural Network

DivControlNN is a state-of-the-art software tool that leverages advanced machine learning techniques to predict and control divertor plasma behavior in fusion reactors. Plasma, a highly energetic and electrically charged gas, requires meticulous management to protect reactor components and maintain optimal energy production. Conventional simulation methods, although extremely detailed, typically demand extensive computational time-making them unsuitable for real-time control scenarios. DivControlNN addresses this challenge by learning from tens of thousands of high-fidelity simulations, thereby creating a rapid surrogate model that can deliver near-instantaneous predictions. At the core of its functionality is a sophisticated technique known as latent space mapping, which condenses complex, high-dimensional plasma data into a compact, lower-dimensional representation. This streamlined representation enables the system to quickly forecast essential plasma properties and determine the precise conditions required for effective detachment. Detachment is a crucial process in which the plasma is cooled before reaching the divertor plates, thereby reducing heat loads and mitigating material erosion. In recent experiments conducted on the KSTAR tokamak in South Korea, DivControlNN successfully guided the detachment process without any fine-tuning-even when applied to a new tungsten divertor configuration. By achieving a computational speed-up of over one hundred million times compared to traditional simulation methods while maintaining low prediction errors, DivControlNN stands to significantly enhance real-time control and diagnostic capabilities in future fusion reactors. This breakthrough paves the way for safer, more reliable reactor operation and represents a major advancement toward realizing fusion energy as a practical, sustainable, and clean power source.

Xu, Xueqiao [Lawrence Livermore National Laborator↗

Multilayer Architecture Barriers for High Temperature Nuclear Applications

Innovative thin film multilayer metal/ceramic barrier coatings have been developed by Argonne National Laboratory to protect fuel cladding against different phenomena that can be encountered under the harsh operating conditions of advanced nuclear reactors. One phenomenon is Fuel-Cladding Chemical Interaction (FCCI), which can represent a challenge to the performance of steel-clad metallic fuels in sodium-cooled fast reactors (SFRs), especially when operating to high burnups at elevated cladding temperatures, and long fuel residence time. Another phenomenon is the corrosion of zirconium-based cladding under prototypic boiling water reactor (BWR) conditions and associated cladding during off normal conditions, including loss of coolant accidents (LOCA). This work provides details of the development and testing of a thin film (few microns) multilayer metal/ceramic (CrY/Y 2 O 3 ) coatings on steel cladding and its performance against FCCI. The coating architecture evolved through systematic mechanical testing, radiation tolerance assessments, and high-temperature diffusion studies from a preliminary multilayer concept to an optimized high-performance design. The optimized structure leverages stoichiometric Y 2 O 3 for its exceptional radiation stability, chemical inertness, and ultra-low fission product diffusivity (e.g., Ce diffusivity ~10 -20 m 2 /s in irradiated Y 2 O 3 at 650 °C). This is paired with ductile chromium-rich interlayers (Cr 95 Y 5 ), which significantly enhance fracture toughness and mechanical resilience. Design refinements, including increased ceramic layer thickness and optimized Cr–Y interlayer composition, eliminated fracture propagation and preserved coating integrity under extreme mechanical stress (>10× typical reactor conditions) and prolonged radiation exposure (~300 dpa). Those conditions are well beyond expected conditions during normal operations in SFR, and cover some of the transient conditions as well. In addition, the coating deposition was demonstrated to be applied uniformly to the inner surface of steel tubes representing prototypic SFR cladding. Another phenomenon under consideration in this work is the corrosion of zirconium-based cladding under prototypic boiling water reactor (BWR) conditions and associated off normal conditions including loss of coolant accident (LOCA). Another multilayer thin film coating is considered for mitigation of this phenomenon, where a coating of yttrium aluminum and yttrium aluminum ceramic/metal thin film coating. Preliminary results on the coating performance during high temperature thermal cycling (up to 1000 C) have shown promising performance of the coating. On-going optimization of the coating will continue in FY26.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗

Algorithm for Determination of Orion Ascent Abort Mode Achievability

For human spaceflight missions, a launch vehicle failure poses the challenge of returning the crew safely to earth through environments that are often much more stressful than the nominal mission. Manned spaceflight vehicles require continuous abort capability throughout the ascent trajectory to protect the crew in the event of a failure of the launch vehicle. To provide continuous abort coverage during the ascent trajectory, different types of Orion abort modes have been developed. If a launch vehicle failure occurs, the crew must be able to quickly and accurately determine the appropriate abort mode to execute. Early in the ascent, while the Launch Abort System (LAS) is attached, abort mode selection is trivial, and any failures will result in a LAS abort. For failures after LAS jettison, the Service Module (SM) effectors are employed to perform abort maneuvers. Several different SM abort mode options are available depending on the current vehicle location and energy state. During this region of flight the selection of the abort mode that maximizes the survivability of the crew becomes non-trivial. To provide the most accurate and timely information to the crew and the onboard abort decision logic, on-board algorithms have been developed to propagate the abort trajectories based on the current launch vehicle performance and to predict the current abort capability of the Orion vehicle. This paper will provide an overview of the algorithm architecture for determining abort achievability as well as the scalar integration scheme that makes the onboard computation possible. Extension of the algorithm to assessing abort coverage impacts from Orion design modifications and launch vehicle trajectory modifications is also presented.

Tedesco, Mark B.↗

Digitalization, Management and Synthesis of Thermal Hydraulic Legacy Data Using Dynamical System Scaling

A unique attribute of the nuclear industry is the extent by which designers, developers, operators, and regulators pay attention to demonstrating the safety case. The safety case for nuclear systems is a written, traceable expression of safety, demonstrating the system’s protective measures against uncontrolled radiological releases. The nuclear installation resiliency or safety takes overriding priority over function and performance. The preparation of the safety case heavily relies on extensive experimental campaigns that challenge the target design under a spectrum of postulated accident scenarios. For safety reasons, these experiments are typically conducted in sub-scale test apparatuses intended to reproduce the postulated accident scenarios and event sequences realistically but subject to proven similarity criteria, often referred to as scaling analyses. Since the dawn of the nuclear industry, significant resources have been committed to the construction and operation of such test facilities and a massive amount of data has been generated. Such test data have been and are still used to validate the fundamental assumptions of nuclear power plant phenomena. As we move into the digital world, capturing this multi-decades worth of information in a transparent, easily accessible, and usable manner for the public and industry stakeholders is of paramount importance. Over the last few years FPoliSolutions has been actively developing an enterprise digital data ontology platform (FPoliDON) intended to do just that. The concept was introduced in a paper at the previous NURETH edition and has been significantly enhanced since. With the vision of helping designers use the data to assess their safety case evaluation models, the platform was designed not only to ontologically organize the experimental data, but also to guide the user in the complex analytics associated with the interpretation and use of such test results. A new feature which has been recently added is the ability for the user to access a library of sophisticated mathematical procedures for performing scaling analyses. For this purpose, the Dynamical System Scaling (DSS) procedure invented by Dr. Jose’ Reyes was formulated as one of the services in the digital platform. These methods have been demonstrated to provide an excelled mathematical apparatus to identify similarity criteria or quantify distortions between measured data and the target prototypical conditions. Moreover, DSS can provide a level of synthesis across SETs and IETs which has the promise to yield efficiency in the evaluation code assessment activities. This is often a daunting and expensive task to set up evaluation models that support the safety case of current and future nuclear power plants.

Reyes, Jose↗

Panel Session 4 and 15: Japan Fukushima Daiichi D and D Update and Technological Challenges at Japan Fukushima Daiichi D and D and Update on Nuclear Overview and Development in Japan - Nuclear Fuel Cycle

Sessions 4 and 15 represent a two-part panel series that discusses progress and challenges associated with cleanup at Fukushima. Severe limitations on availability of original panelists from Japan due to strict restrictions put in place to alleviate the spread of coronavirus necessitated changes to both panels. The result was a significantly modified panel for Session 04 (shown above) and the elimination of all panelists for Session 15. The 4 and 15 Panel Sessions provide an overview of activities related to both the progress and challenges of cleanup and decommissioning of the Fukushima Daiichi Nuclear Power Station (NPS) in Japan. Five panelists discussed perspectives of the cleanup following a Tokyo Electric Power Company (TEPCO) video showing the progress on site since the devastating Great East Earthquake and tsunami that caused the explosions at three of the six reactors on the site. Three of the five panelists discussed on-going work being performed for the effort, while the other two provided expert perspectives of on strategic efforts at the site. The panel was attended by over 80 technologists and policy makers spanning the globe and was opened by Dr. Monica Regalbuto of Idaho National Laboratory and a short video provided by TEPCO. The video described changes at the site that spanned the cleanup efforts from stabilizing water intrusion into the contaminated reactor buildings to construction of new administrative facilities. The video explained the processes underway to retrieve spent fuel rods and challenges in retrieval of the compromised fuel debris. The video highlighted working condition improvements that included establishment of rest housing and a small convenience store on the site, and the rollback of protective equipment around the site due to decreases contamination. Panelists with presentations: Revision of 'the Mid-and-Long-Term Road-map towards the Decommissioning of TEPCO's Fukushima Daiichi Nuclear Power Station' (Paul Dickman); Sharing UK experience at Fukushima Daiichi (Adrian Simper); SRNL Japan (Andrew Fellinger); ABLE's Initiative to Dismantle the Exhaust Stack (Daniel Walter); JAEA R and D in Fukushima (Tokio Fukahori); TEPCO - Overview and Update of the Fukushima Decommissioning Process (Monica Regalbuto); Toshiba's Involvement in the Decommissioning of the Fukushima Daiichi Nuclear Power Plant (Yasuhiro Yuguchi); Remote Dismantling of the Exhaust Stack At Fukushima Dai-ichi NPS (Takashi Okutsu)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

TRANSPORTATION CONSIDERATIONS FOR USED FUEL AND ADVANCED NUCLEAR ENERGY TECHNOLOGIES

This study focuses on requirements and challenges pertaining to advanced transportable nuclear energy systems, which are currently in development and feature varying degrees of mobility. These reactors mostly use high-assay low-enriched uranium (HALEU) fuel, and only limited refueling is required during their lifecycles. Due to the smaller source terms, higher burnup fuel, and potentially higher thermal efficiency involved, the waste inventory will be less than that generated by conventional light-water reactors. However, the relevant regulatory requirements must be met when transporting HALEU fuel (whether fresh or used) inside the reactor vessel—mainly the fuel material transportation, siting, and physical protection requirements outlined in US Nuclear Regulatory Commission (NRC) regulations 10 CFR 71 and 73. Spent nuclear fuel (SNF), as well as irradiated fuel (used during any interval of reactor operation), contains highly radioactive materials that generate heat and necessitate special precautions during transportation. This study addresses the challenges that this incurs, and outlines potential solutions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

TRANSPORTATION CONSIDERATIONS FOR USED FUEL AND ADVANCED NUCLEAR ENERGY TECHNOLOGIES

This study focuses on requirements and challenges pertaining to advanced transportable nuclear energy systems, which are currently in development and feature varying degrees of mobility. These reactors mostly use high-assay low-enriched uranium (HALEU) fuel, and only limited refueling is required during their lifecycles. Due to the smaller source terms, higher burnup fuel, and potentially higher thermal efficiency involved, the waste inventory will be less than that generated by conventional light-water reactors. However, the relevant regulatory requirements must be met when transporting HALEU fuel (whether fresh or used) inside the reactor vessel—mainly the fuel material transportation, siting, and physical protection requirements outlined in US Nuclear Regulatory Commission (NRC) regulations 10 CFR 71 and 73. Spent nuclear fuel (SNF), as well as irradiated fuel (used during any interval of reactor operation), contains highly radioactive materials that generate heat and necessitate special precautions during transportation. This study addresses the challenges that this incurs, and outlines potential solutions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Manufacturing Challenges and Benefits When Scaling the HIAD Stacked-Torus Aeroshell to a 15 Meter Class System

Over a decade of work has been conducted in the development of NASA's Hypersonic Inflatable Aerodynamic Decelerator (HIAD) deployable aeroshell technology. This effort has included multiple ground test campaigns and flight tests culminating in the HIAD project's second generation (Gen-2) aeroshell system. The HIAD project team has developed, fabricated, and tested stacked-torus inflatable structures (IS) with flexible thermal protection systems (F-TPS) ranging in diameters from 3-6 meters, with cone angles of 60 and 70 degrees. To meet NASA and commercial near-term objectives, the HIAD team must scale the current technology up to 12-15 meters in diameter. Therefore, the HIAD project's experience in scaling the technology has reached a critical juncture. Growing from a 6-meter to a 15-meter class system will introduce many new structural and logistical challenges to an already complicated manufacturing process. Although the general architecture and key aspects of the HIAD design scale well to larger vehicles, details of the technology will need to be reevaluated and possibly redesigned for use in a 15-meter-class HIAD system. These include: layout and size of the structural webbing that transfers load throughout the IS, inflatable gas barrier design, torus diameter and braid construction, internal pressure and inflation line routing, adhesives used for coating and bonding, and F-TPS gore design and seam fabrication. The logistics of fabricating and testing the IS and the F-TPS also become more challenging with increased scale. Compared to the 6-meter aeroshell (the largest HIAD built to date), a 12-meter aeroshell has four times the cross-sectional area, and a 15-meter one has over six times the area. This means that fabrication and test procedures will need to be reexamined to account for the sheer size and weight of the aeroshell components. This will affect a variety of steps in the manufacturing process, such as: stacking the tori during assembly, stitching the structural webbing, initial inflation of tori, and stitching of F-TPS gores. Additionally, new approaches and hardware will be required for handling and ground testing of both individual tori and the fully assembled HIADs. There are also noteworthy benefits of scaling up the HIAD aeroshell to a 15m-class system. Two complications in working with handmade textile structures are the non-linearity of the material components and the role of human accuracy during fabrication. Larger, more capable, HIAD structures should see much larger operational loads, potentially bringing the structural response of the material components out of the non-linear regime and into the preferred linear response range. Also, making the reasonable assumption that the magnitude of fabrication accuracy remains constant as the structures grow, the relative effect of fabrication errors should decrease as a percentage of the textile component size. Combined, these two effects improve the predictive capability and the uniformity of the structural response for a 12-15-meter HIAD. In this presentation, a handful of the challenges and associated mitigation plans will be discussed, as well as an update on current manufacturing and testing that addressing these challenges.

Infatables↗

Single-dose mucosal replicon-particle vaccine protects against lethal Nipah virus infection up to 3 days after vaccination

Nipah virus (NiV) causes a highly lethal disease in humans who present with acute respiratory or neurological signs. No vaccines against NiV have been approved to date. Here, we report on the clinical impact of a novel NiV-derived nonspreading replicon particle lacking the fusion (F) protein gene (NiVΔF) as a vaccine in three small animal models of disease. A broad antibody response was detected that included immunoglobulin G (IgG) and IgA subtypes with demonstrable Fc-mediated effector function targeting multiple viral antigens. Single-dose intranasal vaccination up to 3 days before challenge prevented clinical signs and reduced virus levels in hamsters and immunocompromised mice; decreases were seen in tissues and mucosal secretions, critically decreasing potential for virus transmission. This virus replicon particle system provides a vital tool to the field and demonstrates utility as a highly efficacious and safe vaccine candidate that can be administered parenterally or mucosally to protect against lethal Nipah disease.

60 APPLIED LIFE SCIENCES↗

Multiscale and Multifidelity Modeling of a 3D Woven Composite Thermal Protection System

Complex three-dimensional (3D) woven composites have been considered by multiple NASA projects in recent years as a means of offering improved mechanical and thermal performance over traditional laminated composite systems. Parallel efforts have focused on developing simulation capabilities for these systems, which have traditionally and heavily relied on experimental testing to evaluate composite performance. One system is the Heatshield for Extreme Entry Environment Technology (HEEET), which is being considered for the thermal protection system on reentry spacecraft. Optical microscopy was used to characterize the blended carbon and phenolic fiber tows. A section of HEEET insulation layer was imaged with high-resolution micro-computed tomography (microCT) and segmented to separate individual tows, porous matrix, and voids. These data were used to develop multiscale thermomechanical computational models within the NASA Multiscale Analysis Tool (NASMAT). Two NASMAT modeling approaches were considered to capture the details of the 3D woven architecture: a coarse model appropriate for inclusion in multiscale structural analyses and a high-fidelity model created by downsampling the microCT data. Both elastic and thermal properties were computed and compared. The feasibility and challenges associated with modeling complex, hybrid 3D woven composites were also addressed.

NASMAT↗

Protection against Different Genotypes of Newcastle Disease Viruses (NDV) Afforded by an Adenovirus-Vectored Fusion Protein and Live NDV Vaccines in Chickens

The efficacy of an adenovirus-vectored Newcastle disease virus (NDV) vaccine expressing the fusion (F) NDV protein (adeno-F) was evaluated against challenges with virulent heterologous and homologous NDV strains to the F protein. In a preliminary study, two different doses (low and high) of adeno-F were tested against a virulent NDV strain containing the homologous NDV F protein, CA02. In a second study, at three weeks post-vaccination, the efficacy of the high dose of adeno-F was compared to a live attenuated NDV vaccine strain (LaSota) against three antigenically distinct virulent NDV challenge strains, one homologous (CA02) and two heterologous (TZ12, EG14) to F in the vectored vaccine. In both experiments, clinical signs, mortality, virus shedding, and humoral response were evaluated. In the first experiment, the survival rates from birds vaccinated with adeno-F at a high and low dose were 100% and 25%, respectively. In the second experiment, birds vaccinated with the high dose of adeno-F had a survival rate of 80%, 75%, and 65% after challenge with the CA02, TZ12, and EG14 viruses, respectively. All of the LaSota-vaccinated birds survived post-challenge no matter the NDV challenge strain. High antibody titers were detected after vaccination with LaSota by HI and ELISA tests. The majority of adeno-F-vaccinated birds had detectable antibodies using the ELISA test, but not using the HI test, before the challenge. The data show that both the similarity of the F protein of the adeno-F vaccine to the challenge virus and the adeno-F vaccination dose affect the efficacy of an adenovirus-vectored NDV vaccine against a virulent NDV challenge.

Ferreira, Helena L. (ORCID:0000000232613712)↗

Generation and evaluation of synthetic patient data

Background: Machine learning (ML) has made a significant impact in medicine and cancer research; however, its impact in these areas has been undeniably slower and more limited than in other application domains. A major reason for this has been the lack of availability of patient data to the broader ML research community, in large part due to patient privacy protection concerns. High-quality, realistic, synthetic datasets can be leveraged to accelerate methodological developments in medicine. By and large, medical data is high dimensional and often categorical. These characteristics pose multiple modeling challenges. Methods: In this paper, we evaluate three classes of synthetic data generation approaches; probabilistic models, classification-based imputation models, and generative adversarial neural networks. Metrics for evaluating the quality of the generated synthetic datasets are presented and discussed. Results: While the results and discussions are broadly applicable to medical data, for demonstration purposes we generate synthetic datasets for cancer based on the publicly available cancer registry data from the Surveillance Epidemiology and End Results (SEER) program. Specifically, our cohort consists of breast, respiratory, and non-solid cancer cases diagnosed between 2010 and 2015, which includes over 360,000 individual cases. Conclusions: We discuss the trade-offs of the different methods and metrics, providing guidance on considerations for the generation and usage of medical synthetic data.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic Nanopeptide Assemblies for Trans-Tympanic Drug Delivery

Aim: Otitis media is a common otolaryngologic diagnosis worldwide. Invasive methods to curtail and treat frequent occurrences are undesirable, thus necessitating the identification and production of a non-invasive approach to treating the disease. Due to tympanic membrane thickness, ototopical drug delivery is challenging. In this preliminary study, formulations integrating nanopeptides and thermoresponsive polymeric hydrogels are utilized to improve the efficiency of trans-tympanic membrane drug delivery. Methods: Peptides were synthesized using standard Fmoc (fluorenylmethoxycarbonyl protecting group) based solid state peptide synthesis on an automated peptide synthesizer. Ciprofloxacin release was simulated using multiwell microplates with porous inserts. Rate of Ciprofloxacin release was measured over a 48-hour period using a 200 uL solution of peptide fibers and Ciprofloxacin at 1 wt% each, and the labeled peptide at 0.1 wt% in PBS at pH of 7.4. The cytotoxicity of the PA (peptide amphiphile, specifically c16-AHL 3 K 3 -CO 2 H) micelle and fiber with and without ciprofloxacin was investigated by examining epidermal keratinocyte viability in the presence of the material at various concentrations. Laser scanning confocal microscopy was performed with excitation of the calcein dye at 485 nm and the PA-TAMRA (rhodamine labeled peptide) at 515 nm. Results: We have demonstrated the potential viability of a self-assembled peptide amphiphile hydrogel capable of transitioning from a network of 1D nanoscale fibers to 0D micelles. This dissociative mechanism of action yields a peptide that is an effective cell penetrating peptide (CPP) while temporally controlling the release of the antibiotic ciprofloxacin. Conclusion: This work highlights the potential utility of the dynamic process of an engineered peptide hydrogel capable of dissociating into CPPs capable of facilitating drug delivery across the tympanic membrane.

cell culture↗

Lawrence Livermore National Laboratory – Innovation and Partnerships Office (IPO): FY24 Technology Transfer Report (2025 Report V3)

Lawrence Livermore National Laboratory’s (LLNL) Innovation and Partnerships Office (IPO) is the focal point for Laboratory engagement with industry. Organizations partner with LLNL to unlock the commercial viability of breakthrough technologies invented at the Laboratory and collaborate to mature them in order to solve complex industry challenges. LLNL technology transfer connects cutting-edge science with real-world applications, empowering businesses to thrive while advancing the nation’s technological edge. We do this by identifying new economic opportunities, protecting LLNL intellectual property (IP) and transferring it to the private sector through licensing and partnerships

42 ENGINEERING↗

Moving the needle: Employing deep reinforcement learning to push the boundaries of coarse-grained vaccine models

Highly mutable infectious disease pathogens (hm-IDPs) such as HIV and influenza evolve faster than the human immune system can contain them, allowing them to circumvent traditional vaccination approaches and causing over one million deaths annually. Agent-based models can be used to simulate the complex interactions that occur between immune cells and hm-IDP-like proteins (antigens) during affinity maturation—the process by which antibodies evolve. Compared to existing experimental approaches, agent-based models offer a safe, low-cost, and rapid route to study the immune response to vaccines spanning a wide range of design variables. However, the highly stochastic nature of affinity maturation and vast sequence space of hm-IDPs render brute force searches intractable for exploring all pertinent vaccine design variables and the subset of immunization protocols encompassed therein. To address this challenge, we employed deep reinforcement learning to drive a recently developed agent-based model of affinity maturation to focus sampling on immunization protocols with greater potential to improve the chosen metrics of protection, namely the broadly neutralizing antibody (bnAb) titers or fraction of bnAbs produced. Using this approach, we were able to coarse-grain a wide range of vaccine design variables and explore the relevant design space. Our work offers new testable insights into how vaccines should be formulated to maximize protective immune responses to hm-IDPs and how they can be minimally tailored to account for major sources of heterogeneity in human immune responses and various socioeconomic factors. Our results indicate that the first 3 to 5 immunizations, depending on the metric of protection, should be specially tailored to achieve a robust protective immune response, but that beyond this point further immunizations require only subtle changes in formulation to sustain a durable bnAb response.

60 APPLIED LIFE SCIENCES↗

Microscale Electrochemical Corrosion of Uranium Oxide Particles

Understanding the corrosion of spent nuclear fuel is important for the development of long-term storage solutions. However, the risk of radiation contamination presents challenges for experimental analysis. Adapted from the system for analysis at the liquid–vacuum interface (SALVI), we developed a miniaturized uranium oxide (UO 2 )-attached working electrode (WE) to reduce contamination risk. To protect UO 2 particles in a miniatured electrochemical cell, a thin layer of Nafion was formed on the surface. Atomic force microscopy (AFM) shows a dense layer of UO 2 particles and indicates their participation in electrochemical reactions. Particles remain intact on the electrode surface with slight redistribution. X-ray photoelectron spectroscopy (XPS) reveals a difference in the distribution of U(IV), U(V), and U(VI) between pristine and corroded UO 2 electrodes. The presence of U(V)/U(VI) on the corroded electrode surface demonstrates that electrochemically driven UO 2 oxidation can be studied using these cells. Our observations of U(V) in the micro-electrode due to the selective semi-permeability of Nafion suggest that interfacial water plays a key role, potentially simulating a water-lean scenario in fuel storage conditions. This novel approach offers analytical reproducibility, design flexibility, a small footprint, and a low irradiation dose, while separating the α-effect. This approach provides a valuable microscale electrochemical platform for spent fuel corrosion studies with minimal radiological materials and the potential for diverse configurations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗