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At least 325 records · Page 18

SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs

Genome-wide association studies (GWAS) at biobank scale are computationally intensive, especially for admixed populations requiring robust statistical models. SAIGE is a widely used method for generalized linear mixed-model GWAS but is limited by its CPU-based implementation, making phenome-wide association studies impractical for many research groups. We developed SAIGE-GPU, a GPU-accelerated version of SAIGE that replaces CPU-intensive matrix operations with GPU-optimized kernels. The core innovation is distributing genetic relationship matrix calculations across GPUs and communication layers. Applied to 2068 phenotypes from 635 969 participants in the Million Veteran Program, including diverse and admixed populations, SAIGE-GPU achieved a 5-fold speedup in mixed model fitting on supercomputing infrastructure and cloud platforms. We further optimized the variant association testing step through multi-core and multi-trait parallelization. Deployed on Google Cloud Platform and Azure, the method provided substantial cost and time savings. Source code and binaries are available for download at https://github.com/saigegit/SAIGE/tree/SAIGE-GPU-1.3.3. A code snapshot is archived at Zenodo for reproducibility (DOI: [10.5281/zenodo.17642591]). SAIGE-GPU is available in a containerized format for use across HPC and cloud environments and is implemented in R/C++ and runs on Linux systems.

Rodriguez, Alex [Argonne National Laboratory (ANL)↗

DiffLense: a conditional diffusion model for super-resolution of gravitational lensing data

Abstract Gravitational lensing data is frequently collected at low resolution due to instrumental limitations and observing conditions. Machine learning-based super-resolution techniques offer a method to enhance the resolution of these images, enabling more precise measurements of lensing effects and a better understanding of the matter distribution in the lensing system. This enhancement can significantly improve our knowledge of the distribution of mass within the lensing galaxy and its environment, as well as the properties of the background source being lensed. Traditional super-resolution techniques typically learn a mapping function from lower-resolution to higher-resolution samples. However, these methods are often constrained by their dependence on optimizing a fixed distance function, which can result in the loss of intricate details crucial for astrophysical analysis. In this work, we introduce DiffLense , a novel super-resolution pipeline based on a conditional diffusion model specifically designed to enhance the resolution of gravitational lensing images obtained from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). Our approach adopts a generative model, leveraging the detailed structural information present in Hubble space telescope (HST) counterparts. The diffusion model, trained to generate HST data, is conditioned on HSC data pre-processed with denoising techniques and thresholding to significantly reduce noise and background interference. This process leads to a more distinct and less overlapping conditional distribution during the model’s training phase. We demonstrate that DiffLense outperforms existing state-of-the-art single-image super-resolution techniques, particularly in retaining the fine details necessary for astrophysical analyses.

Computer Science↗

Nuclear Safety [Vol. 29, No. 1, January-March 1988]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. THE CHERNOBYL ACCIDENT: 1 Core History and Nuclide Inventory of the Chernobyl Core at the Time of Accident by Gerald Kirchner and Cornelius C. Noack; GENERAL SAFETY CONSIDERATIONS: 6 Nonprescriptive Nuclear Safety Regulation: The Example of Loss of Offsite Power by M. W. Golay, V. P. Manno, and C. Vlahoplus, Jr., 20 Nuclear Power Safety Goals in Light of the Chernobyl Accident by C. Whipple and C. Starr; ACCIDENT ANALYSIS: 29 Containment Loads from Severe Accidents—U.S. Program by W. Kerr and M. K. Dey; PLANT SAFETY FEATURES: 36 Safety Characteristics of Modern High-Temperature Reactors: Focus on German Designs by W. Kröger, H. Nickel, and R. Schulten; ENVIRONMENTAL EFFECTS: 49 Radiation Hormesis and Nuclear Safety by C. C. Congdon; OPERATING EXPERIENCES: 58 Evaluation of Nonradiological Water Chemistry at Power Reactors by Harvey Zibulsky, James J. Kottan, Walter J. Pasciak, Mary Ann Castrogivanni, and Sujit Banerjee, 64 Reactor Shutdown Experience Compiled by J. W. Cletcher, 67 Operating U.S. Power Reactors Compiled by E. G. Silver; RECENT DEVELOPMENTS: 85 General Administrative Activities Compiled by E. G. Silver, 94 Reports, Standards, and Safety Guides by D. S. Queener, 100 Status of Power-Reactor Projects Undergoing Licensing Review Compiled by E. G. Silver, 103 Proposed Rule Changes as of Sept. 30, 1987; ANNOUNCEMENTS: 5 Northwestern University Short Course on Radiation Safety, 28 International Approach to Nuclear Safety (After Three-Mile Island and Chernobyl), 57 RPI Short Course on Modern Developments in Boiling Heat Transfer and Two-Phase Flow, 107 20th DOE/NRC Nuclear Air Cleaning Conference, 110 Third International Topical Meeting on Nuclear Power Plant Thermal Hydraulics and Operations, 108 The Authors, 111 Indexes to Nuclear Safety, Volume 28.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Accumulation of trace elements in soil and fauna within a site historically contaminated with coal combustion residues

Legacy contaminants tied to energy production are a worldwide concern. Coal combustion residues (CCRs) contain high concentrations of potentially toxic trace elements such as arsenic (As), mercury (Hg), and selenium (Se), which can persist for decades after initial contamination. Coal combustion residue disposal methods, including aquatic settling basins and landfills, can facilitate environmental exposure through intentional and accidental releases. Wildlife exposed to CCRs can experience numerous deleterious effects, such as on development, reproduction, and survival. In the current study, we quantified and compared concentrations of As, Hg, Se, and strontium (Sr) within soils and target fauna (three vertebrate and three invertebrate taxa) from a CCR-contaminated site and a reference site within the U.S. Department of Energy’s Savannah River Site, South Carolina, United States. Our objectives were to (1) compare current concentrations of tested elements in soil and resident fauna to levels from our reference site, (2) assess natural attenuation of elements in soils by comparing current concentrations to historic levels, and (3) evaluate the biomagnification potential of the elements measured via body burden and trophic position correlations among fauna. Here, element concentrations were higher in contaminated soils than reference soils; however, concentrations in 2022 were unchanged from concentrations measured in 2003, suggesting no natural attenuation of tested elements. Additionally, target fauna had elevated As, Se, and Sr levels in comparison to reference samples. A positive correlation was observed in southern toads between Sr concentrations and trophic position, as assessed by nitrogen stable isotope ratios, suggesting potential for biomagnification of Sr within our study system. Collectively, our results demonstrate that legacy contaminants are still present and bioaccumulate in a diversity of taxa in a CCR-contaminated site that has not received effluents in more than 50 years, suggesting monitoring programs in CCR-contaminated sites should be maintained long term in the absence of remediation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Cybersecurity for the Operational Technology Environment (CyOTE)

The Department of Energy’s Cybersecurity, Energy Security, and Emergency Response Office (CESER) has partnered with Idaho National Laboratory (INL) and energy companies to develop CyOTE. This research initiative addresses cybersecurity threats against operational technology (OT) networks by sharing intelligence about adversarial tactics and techniques with the energy sector. CyOTE improves the sector’s ability to detect anomalous behavior that indicates potential malicious cyber activity in OT networks.

99 GENERAL AND MISCELLANEOUS↗

Bridging paradigms: Designing for HPC-Quantum convergence

Here, this paper presents a comprehensive software stack architecture for integrating quantum computing (QC) capabilities with High-Performance Computing (HPC) environments. While quantum computers show promise as specialized accelerators for scientific computing, their effective integration with classical HPC systems presents significant technical challenges. We propose a hardware-agnostic software framework that supports both current noisy intermediate-scale quantum devices and future fault-tolerant quantum computers, while maintaining compatibility with existing HPC workflows. The architecture includes a quantum gateway interface, standardized APIs for resource management, and robust scheduling mechanisms to handle both simultaneous and interleaved quantum–classical workloads. Key innovations include: (1) a unified resource management system that efficiently coordinates quantum and classical resources, (2) a flexible quantum programming interface that abstracts hardware-specific details, (3) A Quantum Platform Manager API that simplifies the integration of various quantum hardware systems, and (4) a comprehensive tool chain for quantum circuit optimization and execution. We demonstrate our architecture through implementation of quantum–classical algorithms, including the variational quantum linear solver, showcasing the framework’s ability to handle complex hybrid workflows while maximizing resource utilization. This work provides a foundational blueprint for integrating QC capabilities into existing HPC infrastructures, addressing critical challenges in resource management, job scheduling, and efficient data movement between classical and quantum resources.

97 MATHEMATICS AND COMPUTING↗

Enterprise Artificial Intelligence Strategy for Los Alamos National Laboratory

In the 1984 martial arts drama film, The Karate Kid, a young Daniel LaRusso is unexpectedly placed in an adversarial environment unable to eYectively adapt to a series of new threats and limitations. Fortunately for the main character, once placed under the tutelage of a Mr. Miyagi, he finds resiliency not through the adoption of new tools, but a re-focused set of fundamentals. Much in the same way that Daniel learns waxing on and buYing oY car wax by hand has rewards for Karate, LANL is choosing the harder path of self-hosting Large Language Models (LLMs) for enterprise use instead of only relying on buying access to a hosted AI service like Azure’s OpenAI Application Programming Interface (API). We also are not willing to wait for software-as-a-service (SAAS) AI services to meet us where we need to be from a FedRAMP accreditation standpoint. Our operations regularly depend on access at CUI, UCNI, ITAR and other FIPS-199 moderate-impact data levels and hosting our own services gives us the right security and compliance posture to be useful across the broad range of our work at LANL. With the rise in threats to critical infrastructure, cloud service providers (CSPs), and supply chain attacks from both state and non-state actors, we are not placing the bet that SAAS hosted AI services will be available when we need them. Should a major event occur, we do not want our staY and operations left without a pathway for us to fix the problem and resume the use of AI tools.

42 ENGINEERING↗

Godiva IV central cavity neutron environment characterization with threshold neutron detectors

Godiva IV is a cylindrical fast burst reactor comprised of approximately 65 kg of highly enriched uranium that is operated by Los Alamos National Laboratory and sited at the National Criticality Experiments Research Center at the Nevada National Security Site in Nevada in the United States. Godiva IV is typically operated at delayed critical and in the regime spanning from sub-prompt to super-prompt bursts. Godiva IV is used for sample irradiations, criticality safety demonstrations, dosimetry studies, and for studying super-prompt behavior. In preparation for both an upcoming experiment to reduce uncertainties in the prompt fission spectrum for 235U using threshold neutron detectors, and for future research using Godiva IV, it was desired to exercise the process of the selection of threshold neutron detectors/activation foils, radiation metrology, and the subsequent adjustment of the neutron spectrum. For this exercise, nine high purity threshold neutron detectors/activation foils were irradiated in a Godiva IV burst. The foils were then analyzed using a high-purity germanium detector in the NCERC counting laboratory to determine end of irradiation specific activities for available IRDFF-II reactions. This work summarizes the Godiva IV foil irradiation, radiation metrology results, and adjusted neutron spectrum. The results of this exercise ultimately characterized the neutron environment inside the sample irradiation cavity inside Godiva IV to a higher degree than previously performed, informed decisions for the upcoming larger scale experiment, and will inform future neutron spectrum characterizations at NCERC.

Whitman, Nicholas H.↗

High Energy Density Physics of Inertial Confinement Fusion Ablator Materials

The historic December 5, 2022 experiment at Lawrence Livermore National Lab’s (LLNL) National Ignition Facility (NIF) reached fusion energy ignition for the first time. This is the most important scientific breakthrough of the 21st century paves the way to future clean inertial fusion energy (IFE). The diamond (high density carbon (HDC)) ablator material used in this experiment displays detrimental effects due to the development of hydrodynamic instabilities at the diamond/fuel interface under shock compression. New alternatives to diamond ablators are required to step up the energy yield in ICF experiments. The unique combination of mechanical strength (approaching that of diamond), the ability to accommodate high-Z dopants (in contrast to diamond), and the tunability of the properties (through synthesis material with varying sp 3 content) make amorphous carbon (a-C) a promising material for next-generation IFE ablative capsules. However, despite its critical importance to the IFE program, the behavior of a-C carbon at extreme temperatures and pressures remains largely unexplored. The primary goals of this project were to perform groundbreaking dynamic compression experiments and predictive simulations to uncover the fundamental high-energy-density physics of amorphous carbon. Our goals were (1) to uncover the metastability range of amorphous carbon and probe phase transitions to diamond or metastable supercooled liquid carbon; (2) to acquire high-quality equation of state (EOS) data and develop an experimentally validated EOS from machine-learning MD simulations of the complex states of carbon; and (3) to uncover the complex behavior of carbon liquid in both thermodynamically stable and metastable supercooled states by accessing large areas of carbon phase diagram with amorphous samples with variable sp 3 content. Our proposed experimental program included measurements of equation of state and diffraction measurements using the Omega EP laser at the Laboratory of Laser Energetics at the University of Rochester. The theoretical/simulation program involved the development of machine-learning models of the complex response of amorphous carbon under dynamic compression by performing molecular dynamics simulations at experimental time and length scales using leadership class DOE supercomputers. Simulations guided experiments to observe predicted phenomena and acquire critical experimental data in specific pressure-temperature domains to validate theoretical models. This research delivered fundamental properties of novel amorphous carbon IFE ablator material, including phase diagram and EOS. These results will aid in IFE target design and implosion experiments. A unique combination of predictive simulations and dynamic and static experiments provided a highly inspirational intellectual environment for graduate students and postdocs involved in this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Material Control and Accounting for Liquid-Fueled Molten Salt Reactors: Material Control and Holdup Considerations

The US Nuclear Regulatory Commission (NRC) will likely require license applicants for liquid-fueled molten salt reactors (MSRs) with circulating fuel to submit a nuclear material control and accounting (MC&A) plan or detailed MC&A program description for the facility. In liquid-fueled MSRs with special nuclear material (SNM) in bulk (i.e., not in discrete items) form and rapidly changing quantities due to fuel transmutation and depletion, using traditional nuclear material accounting methods with material balance evaluations is challenging. In reactors with changing inventories, these expected quantities of SNM must be calculated based on operational parameters. Reducing uncertainties on these expected quantities is challenging in the case of MSRs without decades of operational experience to verify and validate predictive computational codes. Moreover, many areas in MSRs are inaccessible because of high-temperature and high-radiation environments, making measurements challenging.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Practical Insights on Applying Simulation-Based Control Methods in Experimental Studies

Advanced nuclear reactors are crucial to the future of energy both in the United States and around the globe. In contrast to the current operating fleet, they are characterized as being deployable in remote locations and able to operate in semi-autonomous or autonomous fashion. This leap forward necessitates a new reactor control paradigm. Because advanced nuclear reactors are still under development in the United States, the creation of new control methods to achieve autonomous operations has been based on systems modeling and simulation. However, an important factor in successfully deploying these new control methods is the ability to seamlessly transition from simulation environments to real-world settings. Control methods tested in both simulation and experimental settings need to be investigated in the context of advanced reactor applications. This work developed a series of simple controllers for Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor operating in load-following scenarios. These controllers were tested in both simulation and experimental settings, and a comparative performance analysis was performed. The simulation tests leveraged the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software developed in a previous stage of the current effort, along with the MARVEL Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The experimental tests leveraged the COMMAND software, MARVEL models, and the U.S. Department of Energy Microreactor Program’s Microreactor Automated Control System (MACS). MACS was developed to serve as a control method testbed. It was customized to mirror the MARVEL microreactor, and COMMAND enabled MACS to emulate the physics of MARVEL. The load-following controller was developed using the simulation platform, with efforts to emulate real systems by introducing actuator saturation and noise. These factors were incrementally accounted for in the controller design. After finalizing the controller design, it was implemented with the experimental setup. The experimental conditions tested included an initial test under conditions similar to the final simulation test, and two additional scenarios. The first scenario introduced additional actuator saturation to account for equipment aging over time, which was unknown to the controller. The second scenario introduced sensor delay, a phenomenon anticipated with the use of remote operations or wireless communication in advanced reactors. These tests revealed several notable differences. While the controller performed well in simulation, it exhibited several limitations when transitioning to hardware. The main challenges involved maintaining the steady-state target power, as evidenced by larger error values between the true reactor power and setpoint power, as well as persistent oscillations in controlled reactor power. These issues could lead to unacceptable transient conditions in real reactor testing. Introducing actuator aging and stochastic delays in the experimental setup significantly impacted controller performance, resulting in increased overshoot and undershoot, and exacerbated error and oscillations previously mentioned. These findings underscore the importance of experimental testbeds for testing and validating control methods, as controllers developed using only theory and/or simulation may perform unexpectedly when applied to actual hardware. This research emphasizes the need for an experimental testbed for achieving such validation.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

An end-to-end workflow for executing a classically bootstrapped variational quantum algorithm on an academic quantum computer

Academic quantum computing platforms often face unique challenges in executing quantum workloads due to fragmented software environments and limited engineering support. Unlike commercial ecosystems, academic devices typically evolve without full-stack integration in mind, making it difficult to run complex applications—such as variational quantum algorithms (VQA)—reliably and efficiently. Issues such as incompatible software layers and lack of automated job management significantly increase the overhead of theory-experiment collaboration. To address these challenges, we develop a modular, end-to-end workflow that decouples application-layer code from low-level hardware control, automates circuit submission and result collection, and supports fine-grained circuit-level job scheduling and recovery. The architecture employs a dual-end application programming interface (API) design, enabling robust operation across unstable or resource-constrained hardware backends. For practical use, the framework is lightweight and user-friendly, allowing rapid prototyping of full-stack workflows using basic Python tools. We validate this workflow on a high-fidelity trapped-ion quantum computer by demonstrating a variational quantum eigensolver (VQE) experiment with a classically bootstrapped ansatz initialization technique. The system successfully executed over 60,000 circuits across multiple molecular test cases with minimal human intervention, highlighting the framework’s effectiveness in enabling reproducible, resilient quantum experimentation in academic settings.

Clifford↗

AstraAI v1

AstraAI is an open-source, structure-aware AI coding agent designed for large scientific and DOE-HPC codebases such as AMReX-based applications. Unlike general-purpose coding assistants, AstraAI combines retrieval-augmented generation (RAG) with compiler-level Abstract Syntax Tree (AST) analysis to perform precise, scope-constrained code modifications. It identifies exact function spans, enforces locality of edits, and maintains cross-file invariants, enabling deterministic and build-safe transformations in complex C++/GPU environments. AstraAI is intended for developers working on large, evolving HPC frameworks where correctness, reproducibility, and structural integrity are critical. Typical use cases include modifying physics kernels, updating GPU device lambdas, and performing multi-file refactors without breaking compilation or runtime semantics. Compared to conventional LLM-based coding agents - even those with repository access - AstraAI provides structural guarantees rather than free-form text patches. It minimizes unintended diffs, prevents scope drift, preserves formatting and build stability, and reduces structural hallucinations. By integrating compiler tooling directly into the generation loop, AstraAI transforms AI-assisted coding from probabilistic text editing into deterministic, structure-preserving program transformation suitable for mission-critical scientific software.

Natarajan, Mahesh [Lawrence Berkeley National Labo↗

Design, Fabrication and On-Sun Performance Evaluation of SiC Receiver Feature Specimens for CST Applications Using Additively Manufactured SiC Materials

Increasing operating temperatures of solar receivers is paramount to the efficiency of concentrated solar thermal (CST) and solar power (CSP) systems. Successful development of CST systems to generate heat for industrial applications requires significant increase in temperature capability and techno-economically viability of the receiver systems. Supported by an award from the Solar Technology Office (SETO), US Department of Energy (DOE), GE Aerospace Research in collaboration with Heliogen Holdings Inc and Sandia National Lab, is engaged in the development of ultra-High Operating Temperature SiC-matrix Solar Thermal Air Receiver (HOTSSTAR) enabled by additive manufacturing. The program objective is to demonstrate SiC receiver with air exit temperatures up to 1100 oC and high thermal efficiencies. We report design, fabrication and on-sun test results of SiC components of a prototype 50kW (thermal) HOTSSTAR module. The receiver module architecture is based on a radial airflow design and consists of a series of radial SiC receiver sectors organized around a SiC center absorber. The SiC components are fabricated using binder-jet printed SiC followed by melt-infiltration reaction bonding process. To enhance the reliability and to minimize the risk of cracking damage of SiC test articles in thermal gradient and thermal shock environment of the application, the components were laminated with GE’s MI SiC-SiC CMC. Following extensive design and lab test analyses, selected SiC component designs are tested at Heliogen Lancaster Solar field under highly concentrated solar fluxes around 2000 suns to assess the thermal performance characteristics under realistic field conditions. We report on the test results and compare the thermal performances of different HOTSSTAR SiC absorbers. Finally, we discuss fabrication and initial assembly of a 50kW prototype test module in preparation of on-sun field tests to assess the performance of our final design.

CST, CSP, high temperature, air receiver, SiC, add↗

Securing Future Energy Supplies: From Renewables to Microreactors

This session will provide insight into how future energy deployments, critical to national-level programs focused on reducing carbon emissions, can be secured-by-design using lessons learned from current energy infrastructure. It will begin with an overview of current threats and risks associated with renewable energy assets and systems, primarily wind and solar, focusing on their control architecture and key system functions for both efficient and safe operations. This talk will then translate the key takeaways from current renewable infrastructure into applications for securing future energy systems, including microreactors and small modular reactors (SMRs), based on planned concepts of operations and control. Microreactors and SMRs are intended to be factory-assembled with commercially available components and deployed in more remote or distributed environments, necessitating centralized control centers, remote monitoring, and offsite maintenance and technical support. All of these factors lead these assets to a security posture and controls more similar to today's renewable energy assets than today's nuclear reactors, which represents a significant shift in mindset for the nuclear industry. This talk will provide justification for this shift as well as a path forward to motivate securing these groundbreaking technologies from the outset of their design and deployment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Deactivation of Mo/H-ZSM-5 in Microwave-Assisted and Thermal-Driven Methane Dehydroaromatization

A better understanding of catalyst deactivation is needed to improve catalyst design and performance in microwave-enhanced methane dehydroaromatization (MDA). Here, this study investigates the deactivation of a molybdenum supported H-ZSM-5 zeolite (Mo/H-ZSM-5) catalyst in MDA under microwave-heated conditions, comparing its performance to that of the same catalyst under conventional heating. While the microwave-assisted (MW) process achieved higher benzene yields, the catalyst experienced faster deactivation due to the selective and rapid deposition of coke within the pores of the zeolite, as confirmed through Brunauer–Emmett–Teller (BET), X-ray diffraction (XRD), ammonia-temperature programmed desorption (NH 3 -TPD), thermal gravimetric analysis (TGA), temperature programmed oxidation (TPO), and X-ray photoelectron spectroscopy (XPS) analyses. The quantification of total coke content via TGA/TPO and surface carbon (XPS) revealed that nearly twice as much coke was deposited on the catalyst under MW conditions compared to that on the conventionally heated material, and the coke exhibited a more conductive and graphitic nature. The accelerated deactivation rates were attributed to the formation of hot spots in the MW system, leading to enhanced coupling with coke formed in situ during the reaction and resulting in increased Mo reduction. Observations indicated that the CO activation used to carburize the catalyst prior to the reaction is not advantageous in the MW heating environment. The presence of large amounts of Mo oxides at elevated temperatures (through hot spots) exposed to methane leads to instability under the reaction conditions. Optimizing the activation environment and improvement of the Mo dispersion within the pores are potential strategies to improve catalyst stability.

Mo/H-ZSM-5 zeolite↗

Preparing MPICH for exascale

The advent of exascale supercomputers heralds a new era of scientific discovery, yet it introduces significant architectural challenges that must be overcome for MPI applications to fully exploit its potential. Among these challenges is the adoption of heterogeneous architectures, particularly the integration of GPUs to accelerate computation. Additionally, the complexity of multithreaded programming models has also become a critical factor in achieving performance at scale. The efficient utilization of hardware acceleration for communication, provided by modern NICs, is also essential for achieving low latency and high throughput communication in such complex systems. In response to these challenges, the MPICH library, a high-performance and widely used Message Passing Interface (MPI) implementation, has undergone significant enhancements. Here, this paper presents four major contributions that prepare MPICH for the exascale transition. First, we describe a lightweight communication stack that leverages the advanced features of modern NICs to maximize hardware acceleration. Second, our work showcases a highly scalable multithreaded communication model that addresses the complexities of concurrent environments. Third, we introduce GPU-aware communication capabilities that optimize data movement in GPU-integrated systems. Finally, we present a new datatype engine aimed at accelerating the use of MPI derived datatypes on GPUs. These improvements in the MPICH library not only address the immediate needs of exascale computing architectures but also set a foundation for exploiting future innovations in high-performance computing. By embracing these new designs and approaches, MPICH-derived libraries from HPE Cray and Intel were able to achieve real exascale performance on OLCF Frontier and ALCF Aurora respectively.

Guo, Yanfei [Argonne National Laboratory (ANL), Ar↗