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Solid Surface Wetting and the Deployment of Drops in Microgravity

The complete or partial deployment of liquid samples in low gravity is primarily influenced by the interfacial properties of the specific liquid and solid materials used because the overwhelming bias of the Earth gravitational acceleration is removed. This study addresses the engineering aspects of injecting and deploying drops of prescribed volume into an acoustic positioning chamber in microgravity. The specific problems of interest are the design, testing, and implementation of injector tips to be used in a simuttaneously retracting dual-injector system used in the Drop Physics Module microgravity experiment facility. Prior to release, the liquid to be deployed must be retained within a restricted area at the very end of the injectors even under dynamic stimuli due to continuous injection flow as well as to the stepped motion of the injectors, and the final released drop must have a well determined volume as well as negligible residual linear or angular momentum from the deployment process. The outcome of Earthbased short-duration low gravity experiments had been the selection of two types of injector tips which were flown as back-up parts and were successfully utilized during the USML-1 Spacelab mission. The combination of a larger contact surface, liquid pinning with a sharp edge, and selective coating of strategic tip surfaces with a non-wetting compound has allowed a significant increase in the success rate of deployment of simple and compound drops of aqueous solutions of glycerol and silicone oil. The diameter of the samples studied in the Drop Physics Module ranged between 0.3 and 2.7 cm. The tests conducted onsrbit with a manually operated small device have allowed the calibration of the volume deployed for a few drop sizes. The design for improved tips to be used during the next USML flight is based on these results.

Trinh, E. H.

Foundation models for atomistic simulation of chemistry and materials

Conventional computational methods for modeling chemical and materials systems are limited by system size and timescale, forcing a trade-off between quantum-mechanical accuracy and the sampling needed for realistic observables. Large language and vision foundation models — pre-trained on massive datasets using transformer architectures — have revolutionized many fields. It is thus interesting to ask whether a foundation model — subject to suitable data, parameter scaling and training — could enable learned simulations of chemistry and materials. Here, in this study, we review the field of machine-learned interatomic potentials (MLIPs) and posit that scaling up large and diverse chemical and materials datasets and highly expressive architectures using advanced training strategies should result in models that are: more efficient, transferable, robust to out-of-distribution scenarios, and easier to fine-tune to a variety of downstream physical observables than models trained from scratch on small datasets corresponding to specific, targeted atomistic simulation tasks. We provide specific criteria for creating such large-scale MLIP foundation models, coordinated strategies for their development, evaluation and deployment, and highlight potential emergent capabilities that could transform predictive simulations in chemistry and materials science and accelerate discovery across multiple technological domains.

Yuan, Eric C.-Y. [University of California, Berkel

EVALS: Enhanced VALidation of Advanced Battery Supply Chains

This is an overview of EVALS (Enhanced VALidation of advanced battery Supply chains), funded by the U.S. Department of Energy Vehicle Technologies Office (VTO) and some initial data from a transformational laboratory directed research and development (LDRD) program project funded at NREL. EVALS aims to accelerate the process to bring domestic and allied primary sources of battery materials online, from production to deployment.

ADVANCED PROPULSION SYSTEMS

Science of Scale-Up: Accelerating chemical manufacturing technology development workshop report

The Science of Scale-Up: Accelerating chemical manufacturing technology development workshop report outlines key insights and actionable recommendations for accelerating the scale-up of disruptive chemical manufacturing technologies. Convened in October 2024, the workshop brought together approximately fifty experts from academia, industry, national laboratories, and government agencies to address the barriers and solutions for maturing technologies from proof-of-concept to commercialization. The report identifies seven critical themes for enabling faster scale-up. These themes were explored through general discussions and breakout sessions focused on three specific chemical manufacturing technologies—electrochemical, thermochemical, and biological conversion processes. The findings emphasize the importance of interdisciplinary collaboration, robust funding mechanisms, and shared resources to overcome technical barriers and accelerate technology deployment. The report also highlights technology-specific challenges and opportunities, including the need for advanced materials, scalable manufacturing processes, and integrated testing environments. For electrochemical manufacturing processes, durability and material optimization are key priorities, while thermochemical processes require novel reactor designs and better supply chain integration. Biological conversion processes face hurdles in strain engineering, reactor design, and process integration. Across all technologies, the workshop emphasized the importance of leveraging computational tools, standardized protocols, and collaborative networks to address knowledge gaps and technical barriers. By acting on these insights, stakeholders can reduce the timeline for scaling up critical chemical manufacturing technologies, ensuring their timely impact on manufacturing competitiveness, and environmental sustainability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

PVDeg: Enhancing Usability and AI-Driven Multi-Mechanism Degradation Modeling

PVDeg version 0.7.0, released in December 2025, introduced major enhancements to improve usability and performance. This update reorganized tutorials and tool notebooks to create a more intuitive experience, enabling users to easily follow and adapt workflows for their specific analyses. In addition to structural improvements, both the notebooks and core logic underwent significant optimization for efficiency, robustness, and style. These refinements were supported by new testing frameworks built on nbval and pytest, adherence to PEP8 standards, and extensive code refactoring, which collectively simplify onboarding for new developers. Looking ahead, version 0.8.0 will deliver advanced AI-driven capabilities. The primary focus is to further develop and automate the degradation workflow, designed to analyze PV module degradation across diverse locations and system configurations. By integrating large language models (LLMs) to scan literature and compile a comprehensive database of materials and degradation rates, this feature will enable modeling of multiple materials and mechanisms within a single, streamlined workflow. Users will be able to evaluate degradation impacts on different system architectures under varying environmental conditions, facilitating informed decisions on bill-of-materials optimization for specific deployment scenarios. These advancements position PVDeg as a powerful, user-friendly tool for accelerating PV reliability research and system design.

14 SOLAR ENERGY

Halide Perovskite Solar Photovoltaics

Technological progress in photovoltaic (PV) technologies provides hope that a comprehensive and desperately needed decarbonization of the energy sector is possible. Commercially successful PV technologies based predominantly on silicon wafer technology are reliable and cost-effective, but remain capital- and carbon-intensive. In this context, emerging PV technologies, such as metal-halide perovskites (MHPs), could further catalyze the energy transition by providing technological opportunities for even lower-cost, mass-producible, high-efficiency solar cells with a significantly reduced "carbon footprint." This themed issue of MRS Bulletin on "Halide perovskite solar photovoltaics summarizes the current state of the art, challenges, and opportunities of perovskite photovoltaics with contributions and perspectives from six expert teams worldwide. The topics covered provide a status update on perovskite PV, remaining hurdles to their deployment, and challenges to realizing the potential of this technology to impact climate goals. Articles in this collection address scalability of perovskite PV and prospects for industrial manufacturing; perovskite PV as an add-on technology on top of commercial silicon PV; environmental and sustainability considerations; and durability and reliability considerations. Further considerations include prospects of automation, coupled to artificial intelligence and machine learning, for accelerating material-based solutions to these outstanding challenges including the possibilities of discovering new absorber and device component materials to enable success and ultimately deployment of these next-generation PVs.

metal-halide perovskites

Irradiation And Post-Irradiation Examination Plan For A709

The Advanced Materials and Manufacturing Technologies program is proposing a neutron irradiation campaign for alloy 709 (A709) plate product developed by the Advanced Reactor Technologies program. This irradiation campaign will support the deployment of A709 (included welded components) by providing data of engineering importance, such as data that can be used for establishing end-of-life design parameters and knockdown factors for irradiated materials properties versus properties for non-irradiated material. It will also advance the scientific understanding of A709 irradiation behaviors and material property evolution, which is vital for deploying A709 components into reactors with different neutron spectra, neutron fluxes, and irradiation temperatures as well as accelerating the deployment of new product forms and weld procedures. This document presents the plan for the neutron irradiation and post-irradiation examination for A709 and the scientific and technical basis for the plan.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Report on the Integration of Experimental and Modeling Data for Initial Equivalence Study of Microstructural Evolution in Irradiated LPBF 316SS

Advanced materials and manufacturing technologies are poised to improve the safety and design characteristics of nuclear technologies and meet US energy, environmental, and economic needs. In particular, metal additive manufacturing (AM) provides an opportunity to produce novel materials and component geometries, but their use is not without hurdles arising from the inherent microstructure variability that can result from the layer-by-layer build approach. Given the greater possible microstructure variability in AM materials—and the dearth of materials test reactors—it is impractical to rely solely on neutron irradiation studies to produce data for materials qualification for every possibility. This work within the Advanced Materials and Manufacturing Technologies (AMMT) Environmental Effects technical area contributes to the rapid qualification framework by developing a science-driven framework for the accelerated qualification of materials for nuclear environments. A key product of the Environmental Effects technical area of the AMMT program is the Licensing Approach with Ions and Neutrons (LAIN). This approach recognizes that whether using existing materials in new environments, newly developed materials tailored for these environments, or new manufacturing methods, the traditional decades-long approach for materials qualification does not facilitate rapid deployment. In FY 2023, the AMMT program presented a conceptual framework of specific steps to fulfill several technical challenges associated with qualifying materials for performance in radiation environments on an accelerated time frame informed by the state of the art in materials science and a review of the current regulatory landscape. The objective of this section of the Environmental Effects technical area is to critically evaluate and refine the proposed qualification framework presented under AMMT by integrating the research results of the neutron irradiations, the ion irradiations, and modeling efforts. These ongoing efforts span across Argonne National Laboratory (ANL), Idaho National Laboratory (INL), and Oak Ridge National Laboratory (ORNL) and are closely coordinated.

36 MATERIALS SCIENCE

An approach to combine neutron and ion irradiation data to accelerate material qualification for nuclear reactors

Next-generation nuclear power plants are generally characterized by higher operating temperatures, increased neutron fluences and energies, and distinct corrosive coolant environments versus the existing light water reactor fleet. Whether using existing materials in new environments, newly developed materials tailored for these environments, or new manufacturing methods, the traditional decades-long approach for materials qualification does not facilitate rapid deployment. Ion irradiation has demonstrated success in reproducing material microstructure and select property evolution resulting from neutron irradiation with three to four orders of magnitude reduction in time and cost, making it an ideal candidate for accelerated irradiation testing. Because microstructure has a large impact on bulk material properties, limited neutron irradiation data at lower damage levels can in principle be combined with accelerated ion testing results and modeling and simulation to form an accurate prediction of microstructure evolution and select properties under different neutron irradiation conditions and at higher damage levels. The objective of this work is to present a conceptual framework of specific steps to fulfill several technical challenges associated with qualifying materials for performance in radiation environments on an accelerated time frame. A brief review of the regulatory landscape for materials in nuclear environments is presented, followed by additional overviews to understand the current state of the art for correlation of materials properties across radiation environments using experimental and computational methodologies. Finally, the roles of academia, national laboratories, and industry in the advancement of this accelerated materials qualification framework are discussed as a path forward, with possible case studies presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

Presentation material for a paper presented at the GHGT-17 conference, Calgary, Canada, October 20-24, 2024. The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

CO2 geologic storage

Developing Multiphysics, Integrated, High-Fidelity, Massively Parallel Computational Capabilities for Fusion Applications Using MOOSE

As the need for fusion as a clean, sustainable, and abundant energy source grows internationally, so does the need for multiphysics, computational tools to model, study, and predict the complex interactions between plasma, materials, and engineering processes. These tools have a crucial role to play in solving scientific and engineering challenges and accelerating fusion energy deployment. To address these needs, modeling capabilities should enable massively parallel, multiphysics, fully integrated high-fidelity simulations of fusion systems. Additional attributes, such as being open source and modular while maintaining high software quality assurance standards will maximize impact by ensuring accessibility for all and wide acceptance, rapid expansion and development, as well as reliability, efficiency, and robustness. In this paper, we describe how the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has a track record of success in the fission space thanks to the attributes listed above, can be leveraged in the fusion energy field. We highlight key successes of the MOOSE application in the fission space and describe how MOOSE has been and is being applied to fusion applications in the United States---e.g., Tritium Migration Analysis Program, version 8 (TMAP8), MOOSE Fusion Module, Fusion ENergy Integrated multiphys-X (FENIX)---and the United Kingdom---e.g., AURORA, Achlys, Apollo. These efforts aim to establish a suite of tools that can be further extended to accelerate fusion energy deployment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

NLR CSP Optical Facilities: Illuminating the Path Forward Through Innovation and Impact: Agreement 38490

This initiative is a multi-faceted project at the National Laboratory of the Rockies (NLR) aimed at strengthening its Concentrating Solar Power (CSP) Optical Facilities to advance the development of low-cost, high-performance materials for solar and other applications. The project's strategy is built on three pillars: strategic stakeholder engagement, diligent facility maintenance and utilization, and the development of new research capabilities. The overarching goal is to ensure the facilities remain state-of-the-art resources for industry and academia, thereby accelerating the conversion of concentrated sunlight into energy. A key driver of the project is an international Advisory Board, which provides critical guidance on research priorities and industry needs, leading to new collaborations and secured funding. This external engagement, combined with proactive outreach to industry partners, ensures the lab's work remains aligned with real-world challenges, including materials durability and performance certification. Significant efforts in facility maintenance have addressed challenges with aging infrastructure. Notable achievements include the complete refurbishment of the hail-damaged Ultra-Accelerated Weathering System (UAWS) and the successful replacement of a failing 15-year-old Lambda 1050 spectrophotometer with a new-generation model, substantially upgrading material characterization capabilities. These maintenance activities were complemented by achieving a prestigious ISO 9001:2015 certification for the Advanced Optical Materials Labs, formally recognizing the quality and reliability of NLR's measurement capabilities. Despite these successes, challenges remain, including high demand for the High Flux Solar Furnace (HFSF) and intermittent failures of other key instruments. The project has delivered major advancements in research techniques and capabilities. At the Flatirons campus, a new indoor laboratory, was established to house advanced deflectometry and photogrammetry systems for heliostat characterization. For on-sun testing, a novel, actively cooled turning mirror was developed for the HFSF, enabling more realistic testing of particle receivers and components. A collaboration with Virginia Tech successfully demonstrated the high-temperature durability of a new solar absorber coating through extensive cyclic testing. Concurrently, new modeling took place to better predict material degradation on rough, fractal surfaces. In summary, this project has systematically enhanced NLR's CSP Optical Facilities through strategic upgrades, rigorous maintenance, and stakeholder-guided research. By overcoming equipment failures, budgetary constraints, and logistical hurdles, the project has reinforced NLR's role as a central hub for CSP innovation and materials testing. Future work will focus on securing diverse funding, expanding collaborations, and continuing to provide the critical infrastructure needed to accelerate the development and deployment of next-generation technologies.

14 SOLAR ENERGY

Accelerated Irradiation Testing and Post-Irradiation Characterization: U.S.-Based Capabilities for Advanced Nuclear Systems and Radioisotope Production

Irradiation experiments and post-irradiation examinations, together referred to as irradiation testing (IRT), are prerequisites for nuclear fuel and material qualification for the deployment of new and advanced reactors, as well as radioisotope production, thereby ensuring regulatory compliance. Qualified research and test reactors (RTRs) and testing facilities are essential to enable IRT to verify performance and safety under prototypical reactor conditions. In the past, qualification of new fuels or structural materials required about 20 years. Synergist strategies, advanced tools, and qualified methods are needed to greatly reduce this timeframe of IRT and radioisotope production. This study, termed accelerated-IRT, focuses on identifying gaps and leveraging U.S.-based RTRs and material testing capabilities, leveraging the preliminary evaluation and qualification of selected RTRs to provide a generic as well as specific-case solution paths forward, ensuring adherence to stringent regulatory standards. Furthermore, IRT and radioisotope production utilizing qualified RTRs necessarily includes modeling and simulation to support the design (i.e. neutronics, thermal, and structural aspects) and manufacturing of irradiation test specimens, vehicles, capsules, apparatuses, and flow loops. In addition, IRT can be improved by applying advanced manufacturing techniques and in-pile sensors and instrumentation, as discussed in this study.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Dark Sector and Gravitational Waves Searches with SRF Cavities at SQMS

The Superconducting Quantum Materials and Systems Center, led by Fermi National Accelerator Laboratory, is one of five research centers funded by the U.S. Department of Energy as part of a national initiative to develop and deploy the world’s most powerful quantum computers and sensors. The SQMS Center uses world-record quality-factor superconducting radio-frequency, or SRF, cavities as ultra-sensitive quantum probes. Within the quantum sensing thrust, researchers are developing experiments based on cavities and novel quantum devices to search for particles beyond the Standard Model, dark matter candidates, gravitational waves and fundamental material properties. The seminar will focus on Dark SRF and MAGO activities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Graduating Sustainable Industrial Decarbonization Solutions from the Laboratory to Real-World Deployments

Accelerating innovation and integration of industrial decarbonization technology solutions is crucial for achieving industry-wide net-zero greenhouse gas emissions targets. This can be accomplished in various ways through increased utilization of low-embodied carbon materials and the adoption of advanced manufacturing techniques in construction practices. At the National Renewable Energy Laboratory (NREL), we facilitate dialogue and action across all sectors to uncover industry needs to inform innovation, and explore ways we can help with implementation of emerging solutions in the real world. As an applied laboratory, NREL sits between academia and industry to fully bridge the gap from foundational science research to examining the feasibility of market applications. Integration of innovative technologies and solutions that are efficient, resilient, and grid-interactive will play a pivotal role in supporting a clean energy future. However, it is imperative that these solutions prioritize equitable outcomes, addressing the challenges faced by all communities. By embracing decarbonization, the construction industry can revolutionize itself, promoting sustainability, reducing carbon emissions, conserving resources, while enhancing performance and durability - all major steps toward a greener and more sustainable future.

cement

Investigation into Scalable and Detection-Enhanced Satellite Conjunction Assessment

Imaging opportunities (viewable conjunctions) of Resident Space Objects (RSOs) by satellites are not continuously discovered. We propose to continuously produce and report viewable conjunctions among objects in orbit. Viewable conjunctions are events in space and time when a satellite may favorably view a Resident Space Object (RSO). Favorability is defined by a set of constraints, e.g., solar illumination, distance between observer and target, orbital location for viewable event. Computing viewable conjunctions requires calculation of orbital propagation while considering constraints based on the state vectors of position, velocity, with covariance for both satellite and RSO. We propose two parallel lanes of effort: acceleration and research. The objective of acceleration is to avoid missed opportunities and reduce latency for satellite maneuver requests through continuous prediction and reporting of viewable conjunctions. The effort will begin by deploying currently available software on dedicated systems and continue with optimizing the code for high performance computing hardware. The research lane aims to expand RSO inspection and modeling capabilities. Among our current research ideas are spectral characterization of RSO materials and planning multiple observations to recover RSO 3D form. Computing resources at Oak Ridge National Laboratory (ORNL) are available for the acceleration work. Laika, Maxar conjunction prediction dashboard software, and Bluesim, Maxar orbital propagation software, are expected to be the first software in the acceleration lane. Laike and Bluesim are to be provided by the sponsor, and output will be made accessible through its dashboard. Deliverables will follow a gated schedule to the sponsor. ORNL will provide progressively more robust viewable conjunction assessments from both modelled and actual ephemerides.

97 MATHEMATICS AND COMPUTING

Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation

We present a multi-agentic workflow for critical materials recovery that deploys a series of AI agents and automated instruments to recover critical materials from produced water and magnet leachates. This approach achieves selective precipitation from real-world feedstocks using simple chemicals, accelerating the development of efficient, adaptable, and scalable separations to a timeline of days, rather than months and years.

Ritchhart, Andrew J.