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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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371 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

MARVEL Reactor Digital Engineering Developments

The MARVEL reactor project has served to introduce a new generation of engineers to the processes required to transform a reactor design from simply an idea on paper into what will be an approved, constructed, and operational nuclear power system. Much as there have been advances in materials, analysis, and evaluation methodologies over the 50 years since the last reactor was built at INL, so too has the technology for managing the engineering process itself advanced. Digital Engineering tools and methods provide improved coordination between previously siloed engineering disciplines, reduced burdens of non-value-added data transcription processes and bring forward insights and improvements that might otherwise fall later in the design stage, where changes are much more costly. While the tools and techniques to support the full digital engineering vision are not yet complete, the MARVEL design processes provide valuable demonstrations and validations of key aspects and illuminate further areas for implementation by subsequent projects.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2024

Eliminating chemo-mechanical degradation of lithium solid-state battery cathodes during >4.5 V cycling using amorphous Nb2O5 coatings

Abstract Lithium solid-state batteries offer improved safety and energy density. However, the limited stability of solid electrolytes (SEs), as well as irreversible structural and chemical changes in the cathode active material, can result in inferior electrochemical performance, particularly during high-voltage cycling (>4.3 V vs Li/Li + ). Therefore, new materials and strategies are needed to stabilize the cathode/SE interface and preserve the cathode material structure during high-voltage cycling. Here, we introduce a thin (~5 nm) conformal coating of amorphous Nb 2 O 5 on single-crystal LiNi 0.5 Mn 0.3 Co 0.2 O 2 cathode particles using rotary-bed atomic layer deposition (ALD). Full cells with Li 4 Ti 5 O 12 anodes and Nb 2 O 5 -coated cathodes demonstrate a higher initial Coulombic efficiency of 91.6% ± 0.5% compared to 82.2% ± 0.3% for the uncoated samples, along with improved rate capability (10x higher accessible capacity at 2C rate) and remarkable capacity retention during extended cycling (99.4% after 500 cycles at 4.7 V vs Li/Li + ). These improvements are associated with reduced cell polarization and interfacial impedance for the coated samples. Post-cycling electron microscopy analysis reveals that the Nb 2 O 5 coating remains intact and prevents the formation of spinel and rock-salt phases, which eliminates intra-particle cracking of the single-crystal cathode material. These findings demonstrate a potential pathway towards stable and high-performance solid-state batteries during high-voltage operation.

Science & Technology - Other Topics↗
DOE OSTI2026

AutoBEM: A scalable framework for nationwide building energy simulation and retrofit evaluation in the United States

This paper presents AutoBEM, an integrated, automated framework for nationwide building energy modeling and retrofit evaluation in the United States. Unlike prior UBEM platforms that either rely primarily on representative stock sampling or operate at city scale, AutoBEM automates the generation of building-resolved, physics-based EnergyPlus/OpenStudio simulation models at national scale using GIS-derived geometry, prototype-based assumptions, and standardized scalable workflows. Leveraging the Model America dataset and high-performance computing, AutoBEM generates and simulates energy models for 122.9 million buildings, representing 97.8% of the U.S. building stock. These models are being made publicly and freely available as the Model America v1.0 (MAv1) dataset. AutoBEM supports detailed, building-level assessments of energy consumption, CO2 emissions, and post-processed anthropogenic heat emissions (AHE), and evaluates 151 energy conservation measures (ECMs) using localized utility pricing and building characteristics. In addition, AutoBEM incorporates both typical and future climate conditions through integration with Typical Meteorological Year (TMY) and Future TMY (fTMY) weather data derived from IPCC scenarios. In a case study of Phoenix, Arizona, AutoBEM identified several high-efficiency HVAC upgrades and selected envelope measures with short modeled payback periods (1.5 years) for certain building types and standards. Simulations under future climate scenarios (SSP5–RCP8.5) project an 11.3% increase in electricity use and a 32% reduction in natural gas demand by 2100, underscoring the need for climate-adaptive retrofit planning. By enabling reproducible, bottom-up, and location-specific analysis at scale, AutoBEM provides a step toward a national digital twin of the built environment and supports data-driven screening and planning for decarbonization, resilience, and energy equity.

Li, Hang [ORNL] (ORCID:0000000306001920)↗
DOE OSTI2026

Microstructure prediction for Ti-22Al-25Nb in laser powder bed fusion

This work presents a physics-informed framework for predicting solidification morphology and defect susceptibility in additively manufactured Ti–22Al–25Nb across a broad processing space. The framework integrates solidification microstructure selection (SMS) analysis with a single-track defect-based printability map to establish a unified methodology linking processing parameters to both interfacial morphology and manufacturability. Thermal gradients G and solidification rates R are first computed using the Thermo-Calc Additive Manufacturing (TC-AM) module, a finite-interface-dissipation (FID) phase-field (PF) model coupled with CALPHAD method is then employed to systematically distinguish planar and dendritic regimes as functions of $G$ and $R$. By superimposing the printability map onto the morphology projections, a comprehensive process–structure framework is obtained. Across most processing conditions, the predicted microstructure is predominantly dendritic, while planar growth emerges only under selected laser power $P$ and scan speed $v$ combinations. In addition to morphology classification, the framework quantifies the dendritic area fraction and introduces a width-based morphology descriptor to characterize the spatial extent of planar/dendritic regions within the melt pool. It provides mechanistic insight into the interplay between solidification physics and defect formation, offering practical guidance for parameter selection and microstructural control in Ti–22Al–25Nb additive manufacturing (AM).

36 MATERIALS SCIENCE↗
DOE OSTI2026

Identifying microstructures susceptible to pulverization in commercially irradiated high burnup UO2 under LOCA conditions

High burnup fuel fragmentation (HBFF) has been a concern in the nuclear industry for many years. When UO2 reaches and exceeds pellet average burnups around 55 GWd/tU, microstructural changes in the fuel pellet begin to occur that render the pellet susceptible to fine fragmentation under loss-of-coolant accident (LOCA) conditions. During a LOCA event, the cladding balloons and bursts, potentially releasing part of these fine fuel fragments into the reactor pressure vessel. This process is known as fuel fragmentation, relocation, and dispersal (FFRD). Presently, the US nuclear industry is developing a safety basis for FFRD with the goal of increasing burnups and pressurized water reactor cycle lengths. Increased cycle lengths would push the burnup limits of the fuel rods past the known threshold for HBFF susceptibility. In this work, the microstructural impact on HBFF was investigated by comparing the microstructures of as-irradiated rod segments to their post-LOCA tested counterparts. This investigation found that varied operational histories result in different microstructural evolutions across the pellet radius, which impacts the fragmentation behavior and radial location of the fragmentation. It is noted that regions with a high bubble density and a high density of grain boundaries fragment under LOCA-relevant conditions. In addition to the fragmentation that has been previously reported at the periphery of the fuel, fragmentation was also noted in the dark zone toward the fuel center. Analysis of the power histories of the fuel samples suggests that the dark zone forms in the central regions of the pellet between temperatures of approximately 740 and 960 °C.

McKinney, Casey [ORNL] (ORCID:0000000335383614)↗
DOE OSTI2023

Hybrid Data‐Driven Discovery of High‐Performance Silver Selenide‐Based Thermoelectric Composites

Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m −1 K −2 , which is a 75% improvement from the baseline composite (nominal composition of Ag 2 Se 1 ). In conclusion, the success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Gas permeation properties of amorphous zeolitic imidazolate framework membranes made by atomic/molecular layer deposition

Amorphous metal-organic framework (MOF) membranes are desirable because they may retain some of the molecular sieving properties of their crystalline counterparts while being free of grain boundary defects, which often hinder the consistent achievement of high membrane performance. However, current methods, like melting and compression, for fabricating amorphous MOF membranes involve multi-step processes that require the formation of a crystalline membrane first, that is then amorphized, and therefore, could be challenging to scale. Here, we utilize atomic/molecular layer deposition (ALD/MLD) of diethylzinc (DEZ) and 2-methylimidazole (2mIm) to directly synthesize ultrathin amorphous zeolitic imidazolate framework (aZIF) deposits on γ-alumina-coated α-alumina supports. As the number of ALD/MLD cycles increased from 10 to 300, gas permeances decreased while ideal selectivities increased. Mixture separation factors for C3H6/C3H8, CO2/N2, and H2/C3H8 as high as 4, 37, and 194, respectively, were obtained. At 200 °C and 2.5 bar equimolar feed of H2 and C3H8, a H2/C3H8 mixture separation factor of 185 is obtained with an H2 permeance of ca. 4.15x10-8 mol/m2-s-Pa (124 GPU). Additionally, the membrane achieves a CO2/N2 mixture separation factor of 37 at 25 °C and 1 bar with a CO2 permeance of ca. 3.96x10-8 mol/m2-s-Pa (118 GPU). Considering the vast array of compositionally distinct aZIFs that can be potentially deposited by this approach, an enormously large parameter space for membrane design is emerging to be explored.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Collapse of magnetized white dwarfs as site of heavy-element formation and kilonova signal

We present the first end-to-end calculation connecting the accretion-induced collapse (AIC) of a magnetized, rapidly rotating white dwarf to observable kilonova signatures, combining two-dimensional (2D) general-relativistic neutrino-magnetohydrodynamic simulations, followed by radiation hydrodynamics with in-situ nuclear network and 2D Monte Carlo radiative transfer with spatially resolved heating rates. Unlike all previous unmagnetized AIC models – which predicted proton-rich, $^{56}$Ni-dominated ejecta – strong magnetic fields eject ${\approx }\, 0.2\, \mathrm{ M}_\odot$ of neutron-rich material ($\langle Y_e \rangle \sim 0.24$) on dynamical time-scales, before neutrino irradiation can raise the electron fraction, enabling strong r-process nucleosynthesis up to and beyond the third peak. The resulting kilonova is lanthanide-rich ($X_{\rm lan} \approx 8~{{\ \rm per\ cent}}$) and dominated by near-infrared emission. We compute synthetic light curves in the Large Synoptic Survey Telescope and J ames Webb Space Telescope bands and find striking agreement, without parameter tuning, between the observations of AT 2023vfi/GRB 230307A and our broadband light curves for polar viewing angles. These results establish magnetized AIC as a viable channel for heavy r-process element production and a compelling progenitor candidate for long-duration gamma-ray bursts with kilonova signatures.

MHD↗
DOE OSTI2023

Electron Microscopy Studies of Soft Nanomaterials

This review highlights recent efforts on applying electron microscopy (EM) to soft (including biological) nanomaterials. We will show how developments of both the hardware and software of EM have enabled new insights into the formation, assembly, and functioning (e.g., energy conversion and storage, phonon/photon modulation) of these materials by providing shape, size, phase, structural, and chemical information at the nanometer or higher spatial resolution. Specifically, we first discuss standard real-space two-dimensional imaging and analytical techniques which are offered conveniently by microscopes without special holders or advanced beam technology. The discussion is then extended to recent advancements, including visualizing three-dimensional morphology of soft nanomaterials using electron tomography and its variations, identifying local structure and strain by electron diffraction, and recording motions and transformation by in situ EM. On these advancements, we cover state-of-the-art technologies designed for overcoming the technical barriers for EM to characterize soft materials as well as representative application examples. Here, the even more recent integration of machine learning and its impacts on EM are also discussed in detail. With our perspectives of future opportunities offered at the end, we expect this review to inspire and stimulate more efforts in developing and utilizing EM-based characterization methods for soft nanomaterials at the atomic to nanometer length scales in academic research and industrial applications.

Imaging↗
DOE OSTI2026

Liquified SO 2 induced solid/cathode electrolyte interphase for lithium ion batteries

Formation of robust solid/cathode electrolyte interphases (S/CEI) is vital for long-term stability and high-performance operation of lithium-ion batteries (LIBs), particularly under high voltage regimes. However, engineering electrochemically stable S/CEIs that effectively suppress interfacial side reactions remains a key challenge. Herein, we introduce a liquefied sulfur dioxide (SO 2 )– ionic liquid complex as a fluorine-free multifunctional electrolyte additive for the first time that significantly improves the formation of sulfate/sulfite-rich S/CEI layers at both graphite and NMC811 interfaces. The unique SO 2 -N coordination with a 1,2,4-triazolide-based ionic liquid enables homogeneous SO 2 dissolution, resulting in controlled SO 2 decomposition during the initial electrochemical cycle. This decomposition yields sulfur-rich interphase species that stabilize the electrolyte-electrode interface, reduce impedance growth, and lessen electrolyte decomposition. Electrochemical tests show significantly improved cycle life, reduced polarization, and increased Coulombic efficiency for both anodes and cathodes. XPS confirms the presence of SO 2 -derived surface species that contribute to interfacial stability. In conclusion, this approach highlights a new direction for interphase engineering using liquefied gas additives and opens pathways for sulfur-based S/CEI chemistry in advanced battery systems.

Graphite↗
DOE OSTI2023

Effect of the Nature of Both Cation and Anion Substitution on the Structural Symmetry of Li‐Rich 3 d ‐Metal Chalcogenide Electrodes

Abstract Li‐rich layered chalcogenides have recently led to better understanding of the anionic redox process and its associated high capacity while providing ways to overcome its practical limitations of voltage fade and irreversibility. This study reports on the feasibility of triggering anionic activity in Li 2 TiS 3 , through anionic substitution (Se for S) or cationic substitution (Fe for Ti). Herein, the chalcogenide chemical space is further explored to prepare mono‐substituted Li 1.7 Ti 0.85 Mn 0.45 Ch 3 (Ch = S/Se) and doubly substituted cationic and anionic phases (Li 1.7 Ti 0.85 Fe 0.45 S 3‐z Se z ) which crystallize either in the O3‐ or O1‐type structures depending upon substituents. All series show a bell‐shape capacity variation as function of the transition metal (TM) substitution degree with values up to 240 mAh g −1 . For specific compositions, a structural O3 to O1 phase transition is observed upon Li removal, which is not reversible upon Li re‐insertion due to kinetic limitations and negatively affects long‐term cycling performance. Density functional theory (DFT) calculations confirm the O3/O1 relative stability along the different series and point subtle electronic differences in the TM‐doping, rationalizing the structural and electrochemical behaviors of these phases upon cycling. These findings provide further insights into the link between structural and electronic stability, which is of key importance for designing chalcogenide‐based anionic redox compounds.

Chemistry↗
DOE OSTI2023

Composite Lithium Metal Structure to Mitigate Pulverization and Enable Long‐Life Batteries

In lithium metal batteries, non‐uniform stripping of lithium results in pit formation, which promotes subsequent non‐uniform, dendritic deposition. This viscous cycle leads to pulverization of lithium which promotes cell shorting or capacity degradation, symptoms further exaggerated by high electrode areal loading and lean electrolytes. Here, to address this challenge, a composite lithium metal anode is engineered that contains uniformly distributed, nanometer‐sized carbon particles. This composite lithium is shown to strip more uniformly since the growth of non‐uniform pits is intercepted by the carbon particles. This mechanism is corroborated by a continuum electrochemical model. Subsequent lithium deposition on carbon particles is also found to be more uniform than on the surface with irregular pits. Notably, the pulverization rate of composite lithium is 26 times slower than that of commercial lithium. Moreover, in a Li‐S battery with sulfurized polyacrylonitrile cathode, the use of the composite anode extends the cycle life by three times when the areal capacity is 8 mAh cm −2 . The approach of using an engineered lithium composite structure to address challenges during both stripping and plating can inform future designs of lithium metal anodes for high areal capacity operations.

high areal capacity↗
DOE OSTI2026

ClassNMSW- a real-time classification approach for non-recycled municipal solid waste using hyperspectral imaging

Real-time classification of non-recycled municipal solid waste (NMSW) is essential for efficient valorization. This study introduces ClassNMSW, a comprehensive framework for classifying 22 NMSW subclasses under industrial constraints by using hyperspectral imaging (HSI). A primary innovation of this work is the development of a variance-controlled spectral extraction algorithm. Unlike traditional methods that rely on simple averaging, this approach systematically investigates the extent of pixel extraction to minimize the loss of critical chemical information while maximizing data reduction thus ensuring high spectral fidelity with low computational cost. The approach developed in this work integrates automated, computer-vision-based background removal, eliminating the need for the manual thresholding common in current literature. To resolve ambiguities among chemically similar subclasses, a tiered classification and multi-camera fusion strategy (NIR17 and NIR22) is implemented. Results demonstrate that ClassNMSW achieves an object-wise weighted accuracy of 98.70% for single-sensor configurations and 100% under sensor fusion. A novel rolling-window strategy satisfies desired end-to-end latency of <2 s, satisfying the strict deterministic requirements of high-speed industrial sorting environments. The ClassNMSW framework provides a scalable foundation for advancing circularity and resource recovery in large-scale waste valorization operations.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A holistic platform for accelerating sorbent-based carbon capture

Abstract Reducing carbon dioxide (CO 2 ) emissions urgently requires the large-scale deployment of carbon-capture technologies. These technologies must separate CO 2 from various sources and deliver it to different sinks 1,2 . The quest for optimal solutions for specific source–sink pairs is a complex, multi-objective challenge involving multiple stakeholders and depends on social, economic and regional contexts. Currently, research follows a sequential approach: chemists focus on materials design 3 and engineers on optimizing processes 4,5 , which are then operated at a scale that impacts the economy and the environment. Assessing these impacts, such as the greenhouse gas emissions over the plant’s lifetime, is typically one of the final steps 6 . Here we introduce the PrISMa (Process-Informed design of tailor-made Sorbent Materials) platform, which integrates materials, process design, techno-economics and life-cycle assessment. We compare more than 60 case studies capturing CO 2 from various sources in 5 global regions using different technologies. The platform simultaneously informs various stakeholders about the cost-effectiveness of technologies, process configurations and locations, reveals the molecular characteristics of the top-performing sorbents, and provides insights on environmental impacts, co-benefits and trade-offs. By uniting stakeholders at an early research stage, PrISMa accelerates carbon-capture technology development during this critical period as we aim for a net-zero world.

Science & Technology - Other Topics↗
DOE OSTI2026

SAM Finite Volume Method Development Status Update: GCR Application, Restart, and MultiApp

The System Analysis Module (SAM) is being developed as a modern system analysis code for advanced non-light-water-reactor safety analysis under the U.S. DOE NEAMS program. Previous feasibility studies have demonstrated that a staggered-grid finite volume method (SG-FVM), implemented under the MOOSE framework, can deliver more than an order of magnitude speedup over the existing continuous Galerkin finite element method (CG-FEM) solver for liquid-cooled, incompressible but thermally expandable flow systems. This work extends the previous effort to compressible, gas-cooled reactor applications, where pressure couples directly into the mass equation adding additional nonlinearity into the equation system. New code capabilities are implemented for pebble bed high-temperature gas-cooled reactor (PB-HTGR) analysis, including a pebble bed CoreChannel component, built-in pebble bed effective thermal conductivity model and channel-to-channel crossflow model. The capabilities are tested, benchmarked, and demonstrated for problems with increased level of model and physical complexities, including the HTTU effective thermal conductivity test, the SANA passive cooling test, and a demonstration case using the GPBR200 reactor design covering steady-state operation, DLOFC and PLOFC transients. Across all cases, the SG-FVM solver demonstrated strong robustness and efficiency, and the solutions agree well with reference results and data. The finding of this work proves that SG-FVM is a viable and efficient solver pathway for compressible, gas-cooled reactor system analysis in SAM. In addition, work has been done to successfully support SAM-FVM recover/restart code feature that is essential to reactor safety analysis applications, and MultiApp code feature that is essential to multi-scale and multi-physics simulations. In summary, this work continued from previous feasibility studies, and further demonstrated that the SG-FVM will serve as a strong foundation for SAM’s advanced solver algorithm for future deployment.

Zou, Ling↗
DOE OSTI2024

Why Perovskite Thermal Stress is Unaffected by Thin Contact Layers

Metal halide perovskite photovoltaics have emerged as a high efficiency, low-cost alternative that can potentially rival or enhance conventional silicon technology. Despite exceptional initial power conversion efficiencies, achieving compliance with international standards and widespread adoption requires further enhancements to their operational stability. Notably, addressing mechanical strain and stress in brittle perovskites has emerged as a pivotal approach to mitigate chemical degradation and improve reliability during thermal cycling. Here, in this study, a popularized strain engineering strategy is investigated in which a high coefficient of thermal expansion (CTE) hole transport layer (i.e., PDCBT) is cast onto inorganic perovskite (CsPbI 2 Br) at 100 °C. Contrary to previously published results, the X-ray diffraction (XRD):Sin 2 ψ and substrate curvature measurement techniques show that the hole transport layer has no discernible impact on perovskite strain. The accuracy of the XRD:Sin 2 ψ method for measuring strain is highlighted in contrast to an analysis based on shifts of single XRD peaks which can be influenced by multiple artifacts. The findings in this study are in accordance with mechanics theory: thin layers are unable to induce significant strain changes in perovskite thin films as the force they apply is negligible compared to that applied by a thick and stiff substrate.

14 SOLAR ENERGY↗
DOE OSTI2026

Tokamak Energy’s pre-concept design for a fusion power plant: an overview of ST-E1

Climate change and rapidly rising energy demand, driven in part by artificial intelligence and data-centre growth, create an urgent need for stable, low-carbon, and abundant power. Fusion is a promising long-term solution, yet its commercialisation faces a fundamental paradox in today’s investment environment: pilot plants are essential to de-risk physics, engineering, and operations, but their limited lifetime energy output and high upfront costs make them difficult to finance. This paper presents Tokamak Energy’s response: ST-E1, a pre-concept design for a low-aspect-ratio tokamak power plant engineered specifically to overcome this challenge. ST-E1 is designed from the outset for phased operation—pilot and commercial phases, with an upgrade phase in between—with emphasis on commercial viability, maintainability, nuclear engineering, modularity, and upgradability. A key design principle is the deliberate separation of long-lived assets, such as the magnet cage and vacuum vessel, from replaceable in-vessel systems. This provides an attractive and credible investment approach to generate operational data and de-risk key technologies while preserving most capital-intensive assets for later commercial phases. The architecture supports continuous optimisation toward high net electric power (targeting 800–1000 MW net electric), a normalised capital expenditure of $\$$ 12–14k/kW of net electric power, and high availability (targeting > 80%). A tokamak core with a 5 m major radius, aspect ratio of 2.3, and on-plasma axis toroidal field of 5.25 T was selected to meet these objectives. This paper summarises the ST-E1 design philosophy, principal features, and development methodology. It introduces a Focus Collection of 11 papers detailing the pre-concept design of the entire tokamak and corresponding plant.

ST-E1↗