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The ART advanced materials program focuses on the application of materials and design methods to support advanced reactors deployment in the near and mid-term Covering materials, design, construction, licensing and operations. These slides speak to present and future Materials focus.
Significant developments made in quantum hardware and error correction recently have been driving quantum computing toward practical utility. However, gaps remain between abstract quantum algorithmic development and practical applications in computational sciences. In this perspective article, we propose several properties that scalable quantum computational science methods should possess. We further discuss how block-encodings and polynomial transformations can potentially serve as a unified framework with the desired properties. Recent advancements on these topics are presented, including the construction and assembly of block-encodings, and various generalizations of quantum signal processing (QSP) algorithms to perform polynomial transformations. The scalability of QSP methods on parallel and distributed quantum architectures is also highlighted. Promising applications in simulation and observable estimation in chemistry, physics, and optimization problems are presented. We hope this perspective serves as a gentle introduction to state-of-the-art quantum algorithms for the computational science community and inspires future development of scalable quantum computational science methodologies that bridge theory and practice.
The ART advanced materials program focuses on the application of materials and design methods to support advanced reactors deployment in the near and mid-term. This covers materials, design, construction, licensing and operations.
The complex multiscale and anisotropic nature of silicon carbide (SiC) ceramic matrix composite (CMC) makes it difficult to accurately model its performance in nuclear applications. The existing models for nuclear grade composite SiC do not account for the microstructural features and how these features can affect the thermal and structural behavior of the cladding and its anisotropic properties. In addition to the microstructural features, the properties of individual constituents of the composites and fiber tow architecture determine the bulk properties. Models for determining the relationship between the individual constituents’ properties and the bulk properties of SiC composites for nuclear applications are absent, although empirical relationships exist in the literature. Here, a hierarchical multiscale modeling approach was presented to address this challenge. This modular approach addressed this difficulty by dividing the various aspects of the composite material into separate models at different length scales, with the evaluated property from the lower-length-scale model serving as an input to the higher-length-scale model. The multiscale model considered the properties of various individual constituents of the composite material (fiber, matrix, and interphase), the porosity in the matrix, the fiber volume fraction, the composite architecture, the tow thickness, etc. By considering inhomogeneous and anisotropic contributions intrinsically, our bottom-up multiscale modeling strategy is naturally physics-informed, bridging constitutive law from micromechanics to meso-mechanics and structural mechanics. The effects that these various physical attributes and thermo-physical properties have on the composite’s bulk thermal properties were easily evaluated and demonstrated through the various analyses presented herein. Since silicon carbide fiber-reinforced SiC CMCs are also promising thermal–structural materials with a broad range of high-end technology applications beyond nuclear applications, we envision that the multiscale modeling method we present here may prove helpful in future efforts to develop and construct reinforced CMCs and other advanced composite nuclear materials, such as MAX phase materials, that can service under harsh environments of ultrahigh temperatures, oxidation, corrosion, and/or irradiation.
Aqueous zinc-ion batteries (AZIBs) offer a combination of safety and low cost, but they suffer from dynamic pH fluctuations that drive parasitic reactions and capacity fading. In this review, we report the current mechanistic understanding of the dynamic pH evolution across the electrolyte-electrode interface and its role in triggering interphase instability. We summarize advanced strategies to regulate pH, including electrolyte engineering, electrode surface modification, and interphase construction. We further discuss current methods for probing pH dynamics and outline potential future approaches for gaining deeper mechanistic and design insights.
Various types of microreactor designs are under consideration, and among those, the heat-pipe cooled reactor designs are currently being actively investigated at Idaho National Laboratory (INL). In order to support non-nuclear testing and demonstration of technology under the Department of Energy (DOE) Microreactor Program (MRP), Single Primary Heat Extraction and Removal Emulator (SPHERE) was designed and constructed to perform high-temperature heat pipe (HP) experiments at INL. Based on the SPHERE experimental setup, this summary paper conducts the preliminary investigations among the available literature and summarizes some potential advanced measurement techniques for operando high-temperature heat pipe which can be implemented to support MRP. The primary objective for the extensive literature research is to investigate the possibilities and feasibilities for designing and construct an advanced experimental test facility with the aim of producing high-fidelity high-resolution heat pipe data during its operations.
The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) framework underpins most of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) physics applications and coupling methods. Users interact with MOOSE in multiple ways to enable the construction of complex multiphysics models, including but not limited to compilation, input creation and syntax validation, meshing, solving the physics problem via MOOSE-based solvers and coupling, and output inspection. In FY23, numerous enhancements have been made to MOOSE to enhance the user experience. Reactor-oriented meshing capabilities in MOOSE have been expanded, an online tutorial was created and hosted on the MOOSE site, and a hands-on workshop was held for more than 100 users. The Language Server Protocol (LSP) capability has been implemented in MOOSE to better communicate correct syntax to the NEAMS Workbench user interface which is commonly used to validate input and submit jobs by users. Finally, several other user-facing improvements were made including the implementation of improved screen output and logging control, enhancements to the initial condition system, and enhancements of the MultiApp system commonly used for coupling. Collectively, these enhancements were driven by user needs and directly improve user ability to construct complex multiphysics models for nuclear reactors.
NREL’s Industrialized Construction Innovation Team has developed an ambitious plan to accelerate the integration of energy efficiency (EE) strategies with Industrialized Construction (IC). The United States (U.S.) construction industry is beginning to use IC methods to build multifamily apartment buildings to address affordability and labor shortages. Apart from reducing cost of construction and delivery times, the IC method of permanent modular construction has the potential to facilitate the integration of a wide range of EE strategies and advanced controls into such buildings. While there may be unintended EE benefits to IC such as a tighter envelope due to higher construction quality, the process has not been leveraged specifically to enhance EE. NREL aims to claim this missed opportunity and integrate IC benefits with EE as well as advanced controls, distributed energy resources, and grid-friendly design strategies. The paper proposes an ‘IC Assessment Framework’ to achieve affordable zero-energy modular multifamily buildings. Through the selection criteria of Design for Manufacturing and Assembly, the framework aims to distill a broad range of proven EE strategies for site-built into a set of strategies that qualify as easy to integrate for off-site. The output is a Factory Information Model (FIM) that represents a process-based digital twin to enable advanced time-and-motion study, plugs into open source building energy modeling platform (EnergyPlus), and serves as a vital tool facilitating wider adoption of EE integration. Conclusively, the paper delineates next steps for upcoming pilots with NREL’s IC partners towards developing a transformational pathway for our Clean Energy Future.
Precise insertion of DNA sequences at targeted locations in plant genomes is pivotal for synthetic biology, genetics, and crop improvement. Construct design plays a critical role in achieving precise insertions, yet practical guidance remains limited. This review provides an in-depth overview of construct design principles and targeted DNA insertion (knock-in) strategies in plants. We assess the strengths, limitations, and construct requirements of current knock-in methods for specific applications, including short, large, and multifragment insertions. Additionally, we explore the potential of adopting advanced nonplant technologies to enhance knock-in efficiency and precision in plants. This review provides a valuable resource for facilitating the effective application of knock-in technologies to genetically improve crops with minimal off-target effects.
Abstract Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by enabling the determination of high-resolution 3-Dimensional (3D) structures of large biological macromolecules. Protein particle picking, the process of identifying individual protein particles in cryo-EM micrographs for building protein structures, has progressed from manual and template-based methods to sophisticated artificial intelligence (AI)-driven approaches in recent years. This review critically examines the evolution and current state of cryo-EM particle picking methods, with an emphasis on the impact of AI. We conducted a comparative evaluation of popular AI-based particle picking methods, using both general machine learning metrics and specific cryo-EM structure determination metrics. This analysis involved constructing the 3D density map from the picked protein particles and assessing the obtained resolution and particle orientation diversity, underscoring the significant impact of AI on cryo-EM particle picking. Despite the advancements, we also identified key obstacles, such as handling complex micrographs with small proteins. The analysis provides insights into the future development of more sophisticated and fully automated AI methods in cryo-EM particle recognition.
We report the design concept and fabrication of MRI phantoms, containing blocks of aligned microcapillaires that can be stacked into larger arrays to construct diameter distribution phantoms or fractured, to create a “powder-averaged” emulsion of randomly oriented blocks for vetting or calibrating advanced MRI methods, that is, diffusion tensor imaging, AxCaliber MRI, MAP-MRI, and multiple pulsed field gradient or double diffusion-encoded microstructure imaging methods. The goal was to create a susceptibility-matched microscopically anisotropic but macroscopically isotropic phantom with a ground truth diameter that could be used to vet advanced diffusion methods for diameter determination in fibrous tissues. Two-photon polymerization, a novel three-dimensional printing method is used to fabricate blocks of capillaries. Double diffusion encoding methods were employed and analyzed to estimate the expected MRI diameter. Susceptibility-matched microcapillary blocks or modules that can be assembled into large-scale MRI phantoms have been fabricated and measured using advanced diffusion methods, resulting in microscopic anisotropy and random orientation. This phantom can vet and calibrate various advanced MRI methods and multiple pulsed field gradient or diffusion-encoded microstructure imaging methods. We demonstrated that two double diffusion encoding methods underestimated the ground truth diameter.
The development of advanced, high gradient accelerating structures is one of the leading activity of the particle accelerator community. In the technological research of new construction methods for these devices, high-power testing is a critical step for the verification of their viability. Recent experiments showed that accelerating cavities made out of hard copper, fabricated without high-temperature processes, can achieve better performance as compared with soft copper ones. Recently, we have built cavities using Tungsten Inert Gas welding and the high-power experiments confirmed that this joining process is a robust and low-cost alternative to brazing or diffusion bonding. This is a good solution for high-gradient operation, with a gradient of about 150 MV/m in X-band, at a breakdown rate of 10 -3 /pulse/meter using a shaped RF pulse with a 150 ns flat part. We continue the design, construction and high power tests of three-cells standing-wave X-band accelerating cavities fabricated with a split-open geometry, made of hard copper and vacuum-sealed by welding. Our aim is the fabrication of accelerating structures made out of hard copper alloys by using innovative cost-effective technologies. Moreover, our method of multiple-sector structures opens the way to new technological approaches and design methods, for example providing the possibility of placing dampers of the parasitic higher-order modes. Such structures with dampers allow for acceleration of multi-bunch beams, both in standing and in travelling-wave accelerating modality. Here, this paper describes the design of two cavities made of multiple sectors that were fabricated at the Italian Institute for Nuclear Physics in Frascati, Italy (INFN-LNF), assembled by means of clamping and then joined with the Tungsten Inert Gas welding in order to preserve the hardness of the metal. These are three-cell standing-wave X-band accelerating cavities, to be operated in the π-mode. We report the low-power RF tests of the first one, made of two halves, and the RF design of the second one, made of four quadrants. Both structures were built for high-gradient tests at SLAC National Accelerator Laboratory.
Abstract Coherent imaging techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the construction of brighter sources and high-rate detectors, coherent imaging methods like ptychography are poised to revolutionize nanoscale materials characterization. However, these advancements are accompanied by significant increase in data and compute needs, which precludes real-time imaging, feedback and decision-making capabilities with conventional approaches. Here, we demonstrate a workflow that leverages artificial intelligence at the edge and high-performance computing to enable real-time inversion on X-ray ptychography data streamed directly from a detector at up to 2 kHz. The proposed AI-enabled workflow eliminates the oversampling constraints, allowing low-dose imaging using orders of magnitude less data than required by traditional methods.
Many fungal species have been used in industrial production for biofuels and bioproducts. Developing strains with better performance in biomanufacturing requires systematic understanding of cellular metabolism. Genome-scale metabolic models (GEMs) offer a comprehensive view of interconnected pathways and a mathematical framework for downstream analysis. Recently, GEMs have been developed or updated in several industrially important fungi. Some of them incorporate enzyme constraints, enabling improved predictions of cell states and proteome allocation. In this report we provide an overview of these newly developed GEMs and computational methods that facilitate construction of enzyme-constrained GEMs and utilize flux predictions from GEMs. Furthermore, we highlight the pivotal roles of these GEMs in iterative design-build-test- learn cycles, ultimately advancing the field of fungal biomanufacturing.
Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.
Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.
We compute classical gravitational observables for the scattering of two spinless black holes in general relativity and N =8 supergravity in the formalism of Kosower, Maybee, and O’Connell (KMOC). We focus on the gravitational impulse with radiation reaction and the radiated momentum in black hole scattering at $ \mathcal{O} $(G 3 ) to all orders in the velocity. These classical observables require the construction and evaluation of certain loop-level quantities which are greatly simplified by harnessing recent advances from scattering amplitudes and collider physics. In particular, we make use of generalized unitarity to construct the relevant loop integrands, employ reverse unitarity, the method of regions, integration-by-parts (IBP), and (canonical) differential equations to simplify and evaluate all loop and phase-space integrals to obtain the classical gravitational observables of interest to two-loop order. The KMOC formalism naturally incorporates radiation effects which enables us to explore these classical quantities beyond the conservative two-body dynamics. From the impulse and the radiated momentum, we extract the scattering angle and the radiated energy. Finally, we discuss universality of the impulse in the high-energy limit and the relation to the eikonal phase.
This is the final report for the project “Demonstration High Temperature Superconducting Non- Planar Stellarator Magnet with Advanced Manufactured Assemblies”, funded by DOE, and performed by Type One Energy from September, 2020, to March 2024 involving the Fusion Technology Institute at the University of Wisconsin–Madison, the Plasma Science and Fusion Center (PSFC) at the Massachusetts Institute of Technology (MIT) and Commonwealth Fusion Systems (CFS) to design and fabricate the first non-planar HTS (REBCO) coil for a high-field stellarator based on the SPARC tokamak’s VIPER cable concept. Stellarators at high fields make high-temperature superconducting magnets necessary for a compact fusion device. But the asymmetric and non-planar nature of its components, especially the magnets make it difficult for scalable producibility. To address these challenges, two promising technologies have emerged: advanced manufacturing (AM) for the supporting plates for forming the magnets, and high-temperature superconducting (HTS) cables inside the plates. AM has advanced enough to produce stellarator components with the necessary geometric complexity, size, and the precision, leading to potentially significant reductions in production time, cost, and waste. The cost of HTS tape has decreased dramatically, and progress in HTS planar magnet development has reached a point where it can be proposed for application to complex 3D non-planar magnets. The main objective of this project is to develop, demonstrate and pre-commercialize a novel, non-planar HTS coil shape that remains superconducting to achieve production scalable reductions in time and cost and performance. The proposed technology is based on the novel concept of a precision sub-scale HTS nonplanar coil assembly. This project focuses on the design, fabrication, material optimization of cable design, and validation and demonstration of the high current carrying capability of superconducting magnets and their support in a complex 3D shape needed for application to stellarator magnetic plasma confinement. The specific objectives of this research program include: (1) The successful application of metal AM to build a precision sub-scale HTS nonplanar coil, (2) An HTS cable and cross-section design that can conform to the required nonplanar coil shape (bend radii as tight as 10-cm) and remains superconducting at an engineering current density of 1.35 kA/cm 2 at 77 K and 1 tesla at the conductor (5 kA in the cable). To achieve the above challenging goals, we have formed a multidisciplinary research team consisting of members from Type One Energy and UW-Madison, MIT PSFC and CFS with complementary skills and strong facilities. The team worked collaboratively on fundamental and applied research on the following three major technical areas: (1) Design, fabrication, and optimization of non-planar HTS Cable The ultimate goal of the project is to determine if commercial REBCO tapes and additive manufacturing can be used to fabricate high field (≥ 10T) non-planar coils with tight bending radii (≃ 100mm) and with a degradation of the critical current (Ic) smaller than 20% with respect to the expected performance. We started with shorter length cable to evaluate the scalability of the production process and eventually reached multiple turns for higher magnetic fields. Our findings suggest that a stellarator coil system of a relevant size, characterized by its asymmetric and non-planar components, can be fabricated using a formed cable in plate method. This system can be simulated using a large-scale modeling approach. The use of hybrid modeling 3 techniques will be pivotal in reducing the complexity of the model and in assessing expected performance in designs. (2) Modeling and simulation of the non-planar HTS Cable Multiphysics simulations are performed using the commercial software and are carried out in self-field conditions, involving 2D and 3D models and twisted around one slot of twist-pitched VIPER cable. Multiphysics simulations are mainly focused on the coil for the critical current evaluation, the magnetic field map, self-Lorentz forces and mechanical, and magnetothermal behavior and the quench dynamics. The detailed model and prediction of the superconducting performance of a stellarator-relevant demonstration cable from numerical simulations supports the results from the actual testing backing the results. A detailed description and results are provided in the later sections. (3) Design, fabrication, and optimization of support for the non-planar HTS Cable The team developed an additive manufactured (AM) coil positioning plate that formed into the required non-planar geometry (with bend radii as tight as 10-cm) and to acceptable tolerances required for a stellarator magnet: (+0.25-mm from ideal on dimensions of coil positioning plates and up to +1-mm from ideal for position of wound coil). The plate materials is also included in this selection process from fabrication and 3D printing perspective and commensurate with eventual application to a fusion reactor. From the cost effectiveness point of view, the HTS coil and plate has the potential to cost less than that made in conventional methods with less waste (<75% waste) reducing time (<50%) and cost (<50%), especially as the AM field matures. The application of advanced manufacturing in the construction of the support plates will also lead to cost reduction, as the cables can be easily replaced, thereby making the assembly modular. With such high primary cost and time savings, high current densities and magnetic field, the funded R&D work has validated the designs, proven the feasibility, and characterized the performance of the HTS coil and plate assembly, paving the way for a relevant-size stellarator coil system.