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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Upgrading Fermilab s Accelerator Control System with ACORN

The Fermilab Accelerator Complex is the largest national user facility in the Office of High Energy Physics (DOE/HEP) program and the only national user facility operating at Fermilab. Fermilab serves as the host to the Long Baseline Neutrino Facility/Deep Underground Neutrino Experiment (LBNF/DUNE), the laboratory’s flagship project for neutrino science that is under construction. LBNF/DUNE will be powered by megawatt beams from an upgraded accelerator, the Proton Improvement Plan II (PIP-II) that will replace the laboratory’s aging linear accelerator with a new one based on superconducting radio-frequency cavities. The Accelerator Controls Operations Research Network (ACORN) Project will support LBNF/DUNE and PIP-II by modernizing the accelerator control system. The project is at the conceptual design phase and looking to achieve Critical Decision 1 (CD-1) later this year. The scope and structure of the project will be presented, along with an overview of how that has changed in the past year. Current design and technology choices will be shared. Specific challenges facing the project will be addressed, along with current thinking on solutions.

Roehrig, Christian [Fermilab]↗
DOE OSTI2025

A comprehensive review of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) techniques in protonic ceramic cells (PCCs): Current status and future perspective

Protonic ceramic cells (PCCs) have emerged as a promising technology for power generation, energy storage, and value-added chemical synthesis, offering benefits such as fuel flexibility, low emissions, and efficient operation at intermediate temperatures (300–600 ​°C). Recently, significant breakthroughs in materials and manufacturing methods have markedly enhanced the performance of PCCs. However, establishing a fundamental understanding of their electrocatalytic reactions has gained less attention. As a fast and cost-effective method for physicochemical fingerprinting, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) has proven to be a surface-sensitive analytical tool for structural and functional studies. This review critically examines the most up-to-date applications of DRIFTS for characterizing key components of PCCs, including oxygen electrodes, protonic electrolytes, and hydrogen electrodes for different applications, with a focus on revealing hydration properties and catalytic reactions, and guiding rational material design. The challenges for advancing DRIFTS, including quantitative capabilities and operando applications for PCC investigations, are highlighted and strategies to tackle these challenges are discussed. Ultimately, this review underscores the critical role of DRIFTS in accelerating the development of high-performance and durable PCCs for next-generation energy solutions, offering methodologies and insights broadly applicable to a wide range of electrochemical energy conversion and storage technologies.

Diffuse Reflectance Infrared Fourier Transform Spe↗
DOE OSTI2023

Final Technical Report: Innovative Magnetron Power Sources for Superconducting RF (SRF) Accelerators

In this project, MUONS is designing and building custom magnetrons at Richardson Electronics (RELL) to test the predictions of the models and make improvements to the designs to match the needs of NP SRF accelerators and their life-cycle costs. To increase lifetime, the filament temperature is controlled by a feedback circuit that includes a model of back streaming of electrons. The gain of the magnetron is optimized by the design of an input port. A permanent magnet design with trim coil for amplitude adjustment reduces energy consumption. Moving the construction of the magnetron from prototype to manufacturing includes the utilization of RELL processes and designs. To the extent that outgassing of materials influences the lifetime of the magnetron, methods for minimizing outgassing was explored. Further experimentation of the potential of sub-critical voltage operation continues to be explored. The commercialization goal of the project will be naturally achieved as RELL already has world-wide marketing, sales, and support to exploit the assembly-line capabilities generated by this project to enable magnetron technologies for NP accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

A parallel variable population multi-objective optimizer for accelerator beam dynamics optimization

The simultaneous optimization of multiple objective functions is needed in many particle accelerator applications. In this paper, we present a parallel evolution based multi-objective optimizer that uses a variable population from generation to generation and an external storage to save good solutions. Two heuristic optimization methods, one uses the unified differential evolution and the other uses the real-coded genetic algorithm, are included in the optimizer to generate next generation candidate solutions, and are compared in the test examples. Finally, as an application, we applied this optimizer to the beam dynamics design optimization of a photoinjector and attained the optimal front solutions after 200 generations with the unified differential evolution offspring production scheme.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Tandem Photovoltaics Core Program Final Technical Report

The Tandem Photovoltaics Core Program was a multi-year initiative aimed at advancing hybrid tandem solar cell technologies to enhance solar module efficiency beyond the limits of single junction devices. This project focused on the development, testing, and scaling of prototype photovoltaic devices, with the goal of achieving commercial relevance and driving industry adoption. The work was divided into three tasks: 1) Comparative Analysis of Tandem Technologies: This task focused on quantifying energy yield under real-world conditions and assessing economic viability of tandems relative to silicon-based modules. The project's modeling framework incorporated performance data, cost of materials, and manufacturing process impacts to optimize tandem designs 2) Tandem Integration and Prototyping: In this task, we developed innovative tandem designs by combining metal halide perovskite (MHP) top cells and silicon (Si) bottom cells. The project focuses on both mechanical integration and direct deposition techniques to enable compatibility with commercially relevant Si technologies, such as passivated contact or PERC cells. 3) Scale-up and Reliability: This task addressed the challenges of large-area fabrication by developing scalable deposition methods and robust interconnection schemes for tandems. The project looked at different accelerated testing such as thermal cycling, damp heat exposure, and potential induced degradation, to ensure long-term stability of devices in field conditions. Tandem solar cells can greatly increase module efficiency beyond conventional single junction (SJ) devices, which are approaching their theoretical limit. There are many ways to fabricate a tandem cell or module in terms of materials used, configuration, and terminal connection. This SETO core project focused critical factors in enabling tandems to enter the market, including hardware integration, technoeconomic analysis (TEA), and energy yield analysis. We focused on MHP/Si hybrid tandem solar cells and modules as a model system for their versatility in module design comparisons, providing valuable insights for other tandem options. While champion cells with areas <1cm2 are regularly demonstrated by groups around the world, it is significantly more challenging to translate these advances into modules, and fewer institutions and companies are working at the module level. This project addressed questions about module fabrication, testing, and reliability that are hard to answer without actually fabricating prototypes. We also performed analysis and road-mapping activities to understand the potential for a wider variety of tandems, including all-perovskite tandems fabricated in collaboration with the Perovskite PV core program. Detailed technical results from this project are described for each task in Section 7.

14 SOLAR ENERGY↗
DOE OSTI2024

Chlorine Nuclear Data Evaluation Aided Through New LANSCE Measurements

The collaboration between the Los Alamos National Laboratory Neutron Science Center (LANSCE) and TerraPower LLC enables the enhanced understanding of fast spectrum critical systems consisting of chlorine. Specifically, TerraPower is interested in updating the nuclear data for the stable isotopes of chlorine, 35 Cl and 37 Cl, because these nuclides are the primary constituents of the chloride fuel salt in the Molten Chloride Reactor Experiment (MCRE), for which TerraPower is leading the design. The Cooperative Research and Development Agreement (CRADA) between the parties is funded by DOE’s Office of Nuclear Energy’s Gateway for Accelerated Innovation in Nuclear (GAIN) initiative to provide the nuclear community with access to the technical, regulatory, and financial support necessary to motivate innovative nuclear reactor technologies toward commercialization. New measurements of 35 Cl(n,p total ) and 35 Cl(n,α total ) were completed at LANSCE to constrain the reaction theory models that are used to generate the updated evaluations. The updated evaluations were then tested across the sensitivities of the MCRE by TerraPower to provide direct feedback to the evaluation for application specific sensitivities.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

CalCharge CRADA000008852 Master Agreement Amendment 1, Battery Consortium – Proprietary Activities

Lawrence Berkeley National Laboratory (LBNL) is partnering with the California Clean Energy Fund to launch CalCharge, an energy storage innovation accelerator, comprised of emerging and established California companies and related organizations developing battery technologies for the electric/hybrid vehicle transportation, the electric grid and consumer electronics markets. The vision of CalCharge is to accelerate the pace of technology innovation, business growth, and cluster development. Calcharge programs will deliver technology acceleration and technical expertise to the energy storage industry, as well as policy and market development support to strengthen the regional economy. LBNL shall collaborate with CalCharge members on the analysis and testing of battery and energy storage technologies. LBNL’s work will include analysis and testing of external design, examination of materials and components either separately or as a whole, and providing data and observations resulting from each collaboration. LBNL shall maintain and provide access to LBNL specialized facilities for research activities performed by or for CalCharge members. In addition, LBNL will provide expertise for short-term consultation, interpretation of testing data, or to clarify technical obstacles if requested by a Member. Over this time frame, Calcharge partnered with several start-ups to provide analytical resources. Those companies include Halotechnics, ZAF Energy Systems, Volkswagen Group of America, Toyota Motor Corporation, and Ensor Inc.

25 ENERGY STORAGE↗
DOE OSTI2023

A Novel Design for Improving the Control on the Stainless-Steel Vessel Welding Process for Superconducting Magnets

Stainless steel vessels see widespread use in superconducting magnets for particle accelerator applications. Their function varies in different magnet designs: they always provide the necessary liquid helium containment, but in some cases are also used to provide azimuthal prestress and can also be welded to the magnet end plate to provide additional longitudinal stiffness. A magnet designed with the bladder and key technology does not rely on the structural role of the vessel. They are structurally supported using azimuthally prestressed aluminum shells, and the longitudinal constraint by rods. In this case, the magnet designer would generally like to minimize the interaction between the magnet and the stainless-steel vessel and to minimize the coil stress variation due to the vessel. The stress state in the vessel and in the coil is a function of the circumferential interference, defined as the vessel azimuthal length minus the magnet circumference. The vessel and the magnet azimuthal length machining tolerances are relatively large resulting in significant stress variations in the superconducting coils. Here in this paper we introduce an interference-control shim, which can significantly limit the stress variation of the coils for a given variation of the interference. The effectiveness of the interference-control shim is evaluated numerically on the MQXF, the low-β quadrupole for the High Luminosity LHC.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Future Circular Collider Feasibility Study Report

Volume 1 of the FCC Feasibility Report presents an overview of the physics case, experimental programme, and detector concepts for the Future Circular Collider (FCC). This volume outlines how FCC would address some of the most profound open questions in particle physics, from precision studies of the Higgs and EW bosons and of the top quark, to the exploration of physics beyond the Standard Model. The report reviews the experimental opportunities offered by the staged implementation of FCC, beginning with an electron-positron collider (FCC-ee), operating at several centre-of-mass energies, followed by a hadron collider (FCC-hh). Benchmark examples are given of the expected physics performance, in terms of precision and sensitivity to new phenomena, of each collider stage. Detector requirements and conceptual designs for FCC-ee experiments are discussed, as are the specific demands that the physics programme imposes on the accelerator in the domains of the calibration of the collision energy, and the interface region between the accelerator and the detector. The report also highlights advances in detector, software and computing technologies, as well as the theoretical tools/reconstruction techniques that will enable the precision measurements and discovery potential of the FCC experimental programme. The content and structure of this report are guided by the scope and priorities defined in the mandate of the FCC Feasibility Study. It is therefore not intended to serve as an exhaustive review of the full physics potential of FCC. Several topics, already covered in earlier reports such as the FCC CDR, are not reiterated here or are addressed only briefly, in alignment with the study’s focus. This volume reflects the outcome of a global collaborative effort involving hundreds of scientists and institutions, aided by a dedicated community-building coordination, and provides a targeted assessment of the scientific opportunities and experimental foundations of the FCC programme.

Benedikt, M. [European Organization for Nuclear Re↗
DOE OSTI2025

Tool-Based Case Studies on Strategic Deployment of Untapped Micro-Pumped Hydro Storage in Michigan

With most classical hydropower sites already utilized and the global push for rapid integration of renewable energy sources accelerating, there is a critical need to identify alternative energy storage solutions. Pumped hydro energy storage, which accounts for the vast majority of global grid-scale storage, remains one of the most cost-effective and long-duration storage technologies available. Hence, this study presents a novel tool designed to assess the untapped potential of inland lakes and reservoirs for micro-PSH, using Michigan’s relatively flat landscape as a case study due to its extensive but underutilized water infrastructure. To ensure accuracy and reliability, the tool incorporates extensive data gathered from authorized sources, covering more than 420 water facilities and potential reservoirs in the state. The tool evaluates key parameters such as horizontal and vertical distances, volume, and the total storage capacity of each reservoir. Its robust assessment framework integrates these metrics to evaluate each site’s potential. The tool’s intuitive interface and geospatial visualizations support actionable insights for planners and scalable deployment of distributed storage infrastructure.

13 HYDRO ENERGY↗
DOE OSTI2025

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials

Thermoelectric materials offer a promising pathway to directly convert waste heat to electricity. However, achieving high performance remains challenging due to intrinsic trade-offs between electrical conductivity, the Seebeck coefficient, and thermal conductivity, which are further complicated by the presence of defects. This review explores how artificial intelligence (AI) and machine learning (ML) are transforming thermoelectric materials design. Advanced ML approaches including deep neural networks, graph-based models, and transformer architectures, integrated with high-throughput simulations and growing databases, effectively capture structure-property relationships in a complex multiscale defect space and overcome the “curse of dimensionality”. This review discusses AI-enhanced defect engineering strategies such as composition optimization, entropy and dislocation engineering, and grain boundary design, along with emerging inverse design techniques for generating materials with targeted properties. Finally, it outlines future opportunities in novel physics mechanisms and sustainability, highlighting the critical role of AI in accelerating the discovery of thermoelectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Demonstration of photoreactor platform for on-sun unassisted photoelectrochemical hydrogen generation with tandem III–V photoelectrodes

Photoelectrochemical (PEC) water splitting is a direct solar-driven technology that converts solar energy to storable chemical energy in the form of hydrogen. In addition to semiconductor and catalyst development for improved photoelectrodes, designing reactors for testing and operation of PEC systems under inherently dynamic outdoor solar illumination is necessary to further the commercial viability of PEC technology. Herein, we present a versatile photoreactor system mounted on a solar tracker for outdoor PEC testing and demonstrate unassisted PEC water splitting under real world on-sun conditions. GaInP 2 /GaAs tandem absorber photoelectrodes with a MoS 2 catalyst were fabricated and exhibit >8% solar-to-hydrogen efficiency. On-sun efficiency and stability of the photoelectrodes were characterized on both sunny and partly cloudy days with continuous monitoring of insolation and weather conditions. Furthermore, the versatile photoreactor and outdoor PEC testing capabilities and methods presented here can accelerate the development of other solar fuel generating systems and technologies.

solar fuels↗
DOE OSTI2026

Machine Learning for Mapping Multipactor Susceptibility in RF Systems: Capabilities and Generalization Constraints

Multipactor is a surface-driven electron avalanche phenomenon that degrades the performance and reliability of radio-frequency (RF) systems in particle accelerator and vacuum electronics applications. Multipactor behavior in a given device structure is conventionally assessed through susceptibility charts, which provide a parameter-space characterization of the instability. In this work, we assess the capabilities of machine-learning (ML) models to learn and predict such susceptibility charts and analyze the constraints governing their generalization across materials. Using a simulation-derived dataset spanning six distinct secondary-electron-yield material profiles in a canonical two-surface planar geometry, we train supervised regression models and artificial neural networks to predict the time-averaged electron growth rate, δavg, across the relevant parameter space. Model performance is evaluated using metrics that explicitly probe the structure of susceptibility charts, including Intersection over Union, Structural Similarity Index, and correlation analysis. Tree-based ensemble models outperform neural-network models in reconstructing susceptibility regions and in generalizing across material domains. Principal-component analysis reveals disjoint material feature distributions, indicating that the piecewise mode structure of multipactor susceptibility is difficult to represent with a single global model and that generalization is constrained by data coverage rather than by model complexity. An exhaustive reduced-coverage study further shows that sparse material-space coverage can yield mean performance in the same general range but producing large variability in the susceptibility-region overlap. These results clarify the capabilities of ML-based surrogate models for parameter-space characterization of multipactor discharge. They also provide guidance for their appropriate use in RF system design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Measurement of the fractional radiation length of a pixel module for the CMS Phase-2 upgrade via the multiple scattering of positrons

High-luminosity particle collider experiments such as theones planned at the High-Luminosity Large Hadron Collider requireever-greater vertexing precision of the tracking detectors,necessitating reductions in the material budget of the detectors.Traditionally, the fractional radiation length (x/X$_{0}$) ofdetectors is either estimated using known properties of theconstituent materials, or measured in dedicated runs of the finaldetector. In this paper, we present a method of direct measurementof the material budget of a CMS prototype module designed for thePhase-2 upgrade of the CMS detector using a 40–65 MeV positronbeam. A total of 630 million events were collected at the PaulScherrer Institut PiE1 experimental area using a three-planetelescope consisting of the prototype module as the central plane,surrounded by two MALTA monolithic pixel detectors. Fractionalradiation lengths were extracted from scattering angle distributionsusing the Highland approximation for multiple scattering. Astatistical technique recovered runs suffering from triggerdesynchronisation, and several corrections were introduced tocompensate for local inefficiencies related to geometric and beamshape constraints. Two regions of the module were surveyed andyielded average x/X$_{0}$ values of (0.72 ± 0.05)% and(0.95 ± 0.09)%, which are compatible with empirical estimatesfor these regions computed from known material properties of 0.753%and 0.892%, respectively. Two types of higher-granularity maps ofthe fractional radiation length were produced, subdivided eitherinto rectangular regions of uniform size, or polygonal-shapedregions of uniform material composition. The results bode well forthe CMS Phase-2 upgrade modules, which will play a key role in theminimisation of the material of the upgraded detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Infrastructure first principles for the Anthropocene

Abstract There appears to be a growing decoupling between the conditions that infrastructures were designed for and today’s rapidly changing environments. Infrastructures today are largely predicated on the technologies, goals, and governance structures from a century ago. While infrastructures continue to deliver untold value, there is growing evidence that these critical, basic, and lifeline systems appear ill-equipped to confront the volatility, uncertainty, accelerating conditions, and complexity that define them and their changing environments. Innovative and disruptive first principles are needed to guide infrastructures in the Anthropocene. Drawing from emerging infrastructure research and disciplines that appear better able to confront disruption and change, a novel set of first principles are identified: (1) Plan for complex conditions and surprise; (2) Recouple with agility and flexibility; (3) Govern for exploration and instability; (4) Build consensus as control decentralizes; (5) Restructure to engage with porous boundaries; and, (6) Cyberthreat planning is now mission critical. These principles should guide infrastructure planning recognizing the changing nature and increasingly obsolete boundaries that have defined engineered systems in the modern era.

Chester, Mikhail (ORCID:0000000293542102)↗
DOE OSTI2026

BSMV-mediated genome editing exhibits host-specific heritability: germline transmission in barley and somatic edits in Nicotiana benthamiana

Plant RNA virus–mediated guide RNA (gRNA) delivery represents a transformative advance in genome editing technologies. Unlike conventional transformation methods that rely on labor-intensive tissue culture and regeneration for each individual gRNA delivery, viral vectors can rapidly and systemically transmit gRNAs into pre-established Cas-expressing plants, providing an accelerated route for functional genomics and trait discovery directly in planta . However, key design parameters, including subgenomic promoter choice, transcript architecture, and their effects on viral fitness and editing outcomes, remain to be elucidated for most viral platforms. We developed five Barley stripe mosaic virus (BSMV) vectors, each with distinct subgenomic promoter elements to drive single gRNA expression. These were initially evaluated in Cas9-expressing transgenic Nicotiana benthamiana plants targeting the Phytoene desaturase ( PDS ) gene to compare their editing efficiencies. Single gRNAs expressed under the duplicated γb subgenomic promoter or when fused directly to the γb genome achieved the highest mutation frequencies (up to 90% at 60 days post-inoculation), whereas β1- and β2-driven sgRNAs produced delayed and reduced editing. Thus, promoter selection critically determines gRNA accumulation and the efficacy of BSMV-mediated genome editing. The top-performing design was then applied to Cas9-expressing barley ( Hordeum vulgare ) targeting HvCMF7 (conferring green-white variegation) and HvGW2.1 (impacts grain width and weight). BSMV spread systemically throughout barley, inducing somatic and heritable mutations at frequencies up to 100%, with virus-free edited progeny. In contrast, despite robust somatic editing in N. benthamiana, no heritable mutations were detected indicating species-dependent limitations in germline transmission. Our systematic comparison of subgenomic promoter architectures establishes clear design principles for optimizing viral vector–mediated delivery. Promoter choice and transcript structure critically shape editing efficiency and viral stability. The host-specific boundary for germline editing, defined by efficient heritable editing in barley but not N. benthamiana , highlights where BSMV offers advantages and where alternative vectors or hybrid strategies are required, guiding rational platform selection for diverse crop species and applications. Collectively, these findings establish BSMV as a promising next-generation vector for rapid, tissue culture–free, and transformation-independent genome editing in cereals and other recalcitrant monocots.

barley↗
DOE OSTI2020

TRANSENSOR: Transformer Real-time Assessment INtelligent System with Embedded Network of Sensors and Optical Readout. Final Report

Utilities across the world are wrestling with evolving market dynamics, population growth and climate change. Distributed Energy Resources (DERs) such as solar photovoltaics, distributed generators and energy storage systems are becoming important parts of the U.S. energy mix. These factors are driving an increasing need for low-cost grid asset monitoring. Aside from being costly, traditional utility monitoring systems are not sufficiently robust and do not provide real-time visibility into the condition of grid assets such as transformers. Lack of accurate real-time measurements on performance has resulted in the use of lagging indicators, such as oil sample analysis. To address this need, an innovative embedded optical sensing technology, Transformer Real-time Assessment Intelligent System (TRANSENSOR) was developed, validated and demonstrated in this project. To date, TRANSENSOR has focused on transformers but is extendable to other grid assets. In addition to the technology being embedded into new transformers during manufacturing, a retrofit configuration that can be installed on existing transformers in the field was also developed. It is anticipated that the ability to retrofit existing transformers will help accelerate adoption of the underlying TRANSENSOR technology. Phase 1 of the project focused on laboratory development and qualification of the technology. Following iterations and exploration of relevant optical sensing modalities and multiplexed configurations of interest for the transformer environment, an effective candidate configuration was agreed upon, down-selected and custom-designed for embedding into General Electric (GE) network transformers. Two new GE 500 kilovolt ampere (kVA), 27 kilovolt (kV) distribution network transformers were built with embedded fiber-optic (FO) sensors and successfully qualified per industry standards at GE’s Shreveport, Louisiana facility during Phase 1 of the project. Following the successful completion of Phase 1, the team proceeded to Phase 2, which focused on a field demonstration of the technology. Over Phase 2, the first new GE transformer built with embedded fiber-optic sensors was installed in an above-ground cage and connected to the grid at Con Edison’s Astoria facility. A second transformer equipped with TRANSENSOR was installed in an underground vault. Additionally, an older (1982 year model) GE transformer in an above-ground cage was retrofitted with fiber- optic sensors and reconnected to the grid at ConEd’s facility. Analysis of data acquired from the sensors showed interesting correlations with transformer loading. Additionally, key events such as transformer low-voltage network connection, primary-side energizing, and a pressure loss event from an oil sampling were detected by the TRANSENSOR system. Online data processing/feature extraction algorithms for the second transformer in the underground vault detected key features and event alerts that were transmitted through a wireless 4G connection. The remote deployment concept showed promising results with data collection running for a total of 8 months across the three (3) GE transformers instrumented for the Phase 2 field demonstration. This sets the stage well for further development and commercialization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗