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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2026

The ballad of LLM agents: philosophical reasoning for chemistry

Large language models (LLMs) show remarkable potential for scientific reasoning but often produce unreliable or scientifically unactionable outputs when faced with multi-step logic, domain grounding, and interpretability challenges, especially in complex fields like chemistry and materials science. Here, we introduce a framework of philosophical reasoning agents, inspired by canonical thinkers such as Socrates, Descartes, Kant, and Hume, to guide LLM behavior via structured prompt engineering. These agents embody distinct reasoning paradigms (dialectical inquiry, deductive logic, rule-based judgment, and empirical validation) and are evaluated across multiple chemistry subdomains, physical, analytical, general, inorganic, and organic chemistry, using the ChemBench benchmark. Our agentic prompting approach yields substantial accuracy gains on open-ended numerical chemistry questions, with gains of +11.5 percentage points for GPT-4o with Hume, +4.5 percentage points for GPT-5 with Kant, and +21.8 percentage points for GPT-5.1 with Socrates at the strict 1% error threshold, relative to the corresponding base models. Beyond accuracy, we observe benchmark-level model–agent performance patterns, suggesting that different prompting styles interact differently with each base model. These findings demonstrate that embedding philosophy-of-science principles into multi-agent frameworks can improve and produce interpretable, adaptive, and domain-aligned scientific LLMs.

Harb, Hassan [Argonne National Laboratory (ANL), A↗
DOE OSTI2021

The “Brookhaven Brassie” and the Response to the Three Mile Island Accident

In the mid-1970s, American civil defense authorities became increasingly concerned with the potential threat of fission reactor accidents. Research from the Defense Civil Preparedness Agency began to be aimed not just at the ever-present threat of nuclear warfare, but also peacetime emergencies as part of a "dual use" philosophy. The Brookhaven National Laboratory received funding to create a prototype radioiodine air sampling system, with multiple publications detailing the creation of the air sampler itself and a special CD V-700 survey meter that accompanied it. In late March 1979, the system found its first operational employment at the reactor accident at Three Mile Island, Pennsylvania. Despite successful use and further study, the BNL Air Sampler was not widely fielded by the federal government. However, lessons learned from its employment and development may be applicable to contemporary radiological emergency response.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Toughening materials: enhancing resistance to fracture

It has been said that ‘God invented plasticity, but the Devil invented fracture!’ Both mechanisms represent the two prime modes of structural failure, respectively, plastic collapse and the rupture/breaking of a component, but the concept of developing materials with enhanced resistance to fracture can be difficult. This is because fracture resistance invariably involves a compromise—between strength and ductility, between strength and toughness—fundamentally leading to a ‘conflict’ between nano-/micro-structural damage and the mechanisms of toughening. Here, we examine the two major classes of such toughening: (i) intrinsic toughening, which occurs ahead of a crack tip and is motivated by plasticity—this is the principal mode of fracture resistance in ductile materials, and (ii) extrinsic toughening, which occurs at, or in the wake of, a crack tip and is associated with crack-tip shielding—this is generally the sole mode of fracture resistance in brittle materials. We briefly examine how these distinct mechanistic processes have been used to toughen synthetic materials—intrinsically in gradient materials and in multiple principal-element metallic alloys with the example of metallic glasses and high-entropy alloys, and extrinsically in ceramics with the example of ceramic-matrix composites—in comparison to Nature which has been especially adept in creating biological/natural materials which are toughened by one or both mechanistic classes, despite often consisting of constituents with meagre mechanical properties. The success of Nature has been driven by its ability to cultivate the development of materials with multiple length-scale hierarchical structures that display ingenious gradients and structural adaptability, a philosophy which we need to emulate and more importantly learn to synthesize to make structural materials of the future with unprecedented combinations of mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Random insights into the complexity of two-dimensional tensor network calculations

Projected entangled pair states (PEPS) offer memory-efficient representations of some quantum many-body states that obey an entanglement area law and are the basis for classical simulations of ground states in two-dimensional (2d) condensed matter systems. However, rigorous results show that exactly computing observables from a 2d PEPS state is generically a computationally hard problem. Yet approximation schemes for computing properties of 2d PEPS are regularly used, and empirically seen to succeed, for a large subclass of (“not too entangled”) condensed matter ground states. Adopting the philosophy of random matrix theory, in this work, we analyze the complexity of approximately contracting a 2d random PEPS by exploiting an analytic mapping to an effective replicated statistical mechanics model that permits a controlled analysis at a large bond dimension. Through this statistical-mechanics lens, we argue that (i) although approximately sampling wave-function amplitudes of random PEPS faces a computational-complexity phase transition above a critical bond dimension, and (ii) one can generically efficiently estimate the norm and correlation functions for any finite bond dimension. Furthermore, these results are supported numerically for various bond-dimension regimes. It is an important open question whether the above results for random PEPS apply more generally also to PEPS representing physically relevant ground states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Infrared-safe energy weighting does not guarantee small nonperturbative effects

Infrared and collinear (IRC) safety has long been used a proxy for robustness when developing new jet substructure observables. This guiding philosophy has been carried into the deep learning era, where IRC-safe neural networks have been used for many jet studies. For graph-based neural networks, the most straightforward way to achieve IRC safety is to weight particle inputs by their energies. However, energy-weighting by itself does not guarantee that perturbative calculations of machine-learned observables will enjoy small nonperturbative corrections. Here, in this paper, we demonstrate the sensitivity of IRC-safe networks to nonperturbative effects, by training an energy flow network (EFN) to maximize its sensitivity to hadronization. We then show how to construct Lipschitz energy flow networks (L-EFNs), which are both IRC safe and relatively insensitive to nonperturbative corrections. We demonstrate the performance of L-EFNs on generated samples of quark and gluon jets, and showcase fascinating differences between the learned latent representations of EFNs and L-EFNs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Two-way coupled particle-turbulence interaction: Effect of numerics and resolution on fluid and particle statistics

Euler-Lagrange point-particle simulation has emerged as a premier methodology for studying dispersed particle-laden flows. This method's popularity stems from its ability to resolve fine-scale fluid structures while also tracking individual particles at reduced cost using an appropriate particle acceleration model. However, the point-particle model has known convergence issues in that refinement of the fluid grid can lead to changes in the predicted statistics. The reasons for non-convergence are twofold: the point-particle two-way coupling force in the Navier-Stokes equations requires a numerical regularization and, without careful implementation, yields a singular force on the fluid with grid refinement. The second factor that yields grid-dependent statistics is that the point-particle force model in general depends on the undisturbed fluid velocity. When the undisturbed fluid velocity is not robustly modeled in a grid-insensitive way, the calculated force for both particles and fluid will be grid-dependent, contaminating their respective statistics. While the first issue regarding regularizing the point-particle source term has received attention in the literature, the consequences of robustly modeling the undisturbed velocity in the context of grid refinement of turbulence has received little attention. Here, we consider decaying homogeneous isotropic turbulence laden with particles at different Stokes numbers. For a given Stokes number, we systematically refine the grid and demonstrate that explicitly modeling the undisturbed fluid velocity yields relative grid insensitivity for the energy of the particle and fluid phases, as well as acceleration of the particles. We also demonstrate that an appropriately defined dissipation rate is also grid-insensitive when an undisturbed fluid velocity correction is used. In contrast, when the undisturbed fluid velocity is modeled using the conventional approach of interpolating the local fluid velocity to the particle location, we show this procedure yields divergent statistics with grid refinement. In particular, we show that higher-order interpolation of the fluid velocity in two-way coupled problems is worse than lower-order interpolation, in the absence of a correction procedure to estimate the undisturbed fluid velocity. We also examine velocity derivative statistics of the fluid phase and demonstrate that these statistics are not in general convergent even when the undisturbed fluid velocity is explicitly modeled. Collectively, the observations in this paper are used to present a philosophy on the types of questions which are answerable with point-particle methods.

42 ENGINEERING↗
DOE OSTI2020

Tunable magnetic order in low-symmetry SeO 3 ligand linked TM 3 (SeO 3 ) 3 H 2 O ( TM =Mn , Co, and Ni) compounds

The ability to design crystal lattices with specific sublattice geometries has long been sought after especially in the context of harnessing magnetic frustration to elicit emergent physics. One approach which has seen some success recently is to design magnetic sublattices chemically through the use of nonmagnetic linker ligands as scaffolding for the magnetic ions. In this work we report the magnetic properties of one such family of materials, the transition metal (TM) selenite hydrates with chemical formula TM 3 (SeO 3 ) 3 H 2 O. These materials link highly distorted TMO 6 octahedra via nonmagnetic [SeO 3 ] 2+ linkers. Studying members with TM = Mn, Co, and Ni we use magnetic susceptibility and neutron powder diffraction to identify antiferromagnetic order in all three compounds with moderate frustration indexes. A comparison of the magnetic structures suggests that while the overall structure of the SeO 3 scaffolding remains unchanged the TM effects changes in the magnetic properties through tuning the internal bonding parameters and the single-ion physics. Changing from Mn to Co is found to be particularly consequential manifesting changes in both the ordered-moment direction and in the direction of the ordering vector. Field-dependent measurements of the susceptibility and heat capacity reveal metamagnetic transitions in both Mn 3 (SeO 3 ) 3 H 2 O and Co 3 (SeO 3 ) 3 H 2 O indicating nearby magnetic ground states accessible under relatively small applied fields. Density functional theory calculations broadly confirm these results, showing both a sensitivity of the magnetic structure to the TM and its local environment. Although no spin liquid behavior is achieved, these results suggest the fruitfulness of such synthesis philosophies and encourage future work to engender higher frustration in these materials via doping, field, pressure, or larger linker ligands.

36 MATERIALS SCIENCE↗
DOE OSTI2025

SCR-based Medium Voltage DC Solid-State Circuit Breaker

This paper describes a medium voltage solid-state circuit breaker (SSCB) based on SCR technology, featuring short fault-interruption time and a minimal turn-off auxiliary circuit. The SSCB design incorporates a specialized SCR and a commutation circuit designed with an objective to reduce the required SCR hold-off/turn-off time, tq, which primarily determines the fault interruption duration. To validate the design, simulation analysis is presented, and a 1.5 kV 300 A SSCB prototype has been built and tested. The results confirm the effectiveness of the proposed design philosophy demonstrating the SSCB's ability to interrupt a 200 A load current in less than 50 μs. The proposed SCR-based SSCB has been developed for DC applications but is equally applicable to AC applications.

Kandula, Prasad [ORNL] (ORCID:0000000174017284)↗
DOE OSTI2021

Interactive Supercomputing With Jupyter

Rich user interfaces like Jupyter have the potential to make interacting with a supercomputer easier and more productive, consequently attracting new kinds of users and helping to expand the application of supercomputing to new science domains. For the scientist-user, the ideal rich user interface delivers a familiar, responsive, introspective, modular, and customizable platform upon which to build, run, capture, document, re-run, and share analysis workflows. From the provider or system administrator perspective, such a platform would also be easy to configure, deploy securely, update, customize, and support. Jupyter checks most if not all of these boxes. But from the perspective of leadership computing organizations that provide supercomputing power to users, such a platform should also make the unique features of a supercomputer center more accessible to users and more composable with high performance computing (HPC) workflows. Project Jupyter’s core design philosophy of extensibility, abstraction, and agnostic deployment, has allowed HPC centers like NERSC to bring in advanced supercomputing capabilities that can extend the interactive notebook environment. This has enabled a rich scientific discovery platform, particularly for experimental facility data analysis and machine learning problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Advanced Metering Infrastructure for Distribution Planning and Operation: Closing the Loop on Grid-Edge Visibility

In the recent history of electric utilities, the potential to have visibility of the grid edge is gaining significance for the reliable planning and operation of a clean energy smart grid. Before the recent large-scale customer adoption of distributed energy resources (DERs), distribution networks were planned with a simpler fit-and-forget philosophy. The importance of customer-sited DERs to achieve climate change goals marks a major shift for utility operations. Changes to traditional fit-and-forget planning paradigms require better availability of grid-edge data. Smart metering is an enterprise-wide tool that is enabling visibility when and where it has been most needed. As of 2020, the rollout of smart metering, or advanced metering infrastructure (AMI), had reached more than 100 million meters in the United States, and nearly half of all electricity customers are now equipped with a smart meter (Figure 1). Smart meters are quickly becoming a ubiquitous data capture feature of smart grids. AMI enables utilities to record and measure electricity usage and power-flow metrics at a minimum of hourly intervals and at least once a day. At a minimum, AMI enables interval metering, automatic meter reading enabling accurate and time-interval billing, and the ability to provide feedback on customer energy consumption.

advanced metering infrastructure↗
DOE OSTI2021

Novel control solutions for DoS attack delay mitigation in grid-connected and standalone inverters

This paper introduces two novel control solutions, which allow localised delay compensation for grid-connected and standalone inverters. As the prediction horizon of the existing controllers are quite small as compared to large communication delays and information unavailability due to denial-of-service (DoS) attacks, the proposed strategy offers a robust delay mitigation range using localized dynamics. Its design philosophy is leveraged via a prediction policy using the inner control loop dynamics. Based on different control objectives in grid-connected and standalone mode, the proposed solutions have been augmented into the control system accordingly. Finally, its robustness under various communication delay and DoS attacks have been tested.

Roig Greidanus, Mateo D.↗
DOE OSTI2022

Creation of Simulated Test Cases for the Oscillation Source Location Contest

This paper describes in detail the design process and creation of 13 oscillatory test cases for the IEEE and NASPI co-hosted Oscillation Source Locating Contest conducted in 2021. The challenges behind the 13 cases are fully demystified. Based on the philosophy, implementation considerations and techniques used for the case design presented in this paper, interested readers can create additional interesting cases for testing the efficiency of their oscillation source location methods.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Modeling Grid Data Flows for Transmission and Distribution Operations: Review, Design, Next Steps

Operational scenarios of the power grids grow multifold to accommodate the diverse needs of both the utilities and end consumers, and the various other stakeholders in-between. To comprehensively model and apply analytics to support objectives and business functions of grid sectors, a reliable approach to characterize and design data flows is crucial. The flows bridge business functions with communications protocols, stakeholders such as the grid actors, and data interfaces comprising different data objects. Additionally, constraints applied to the flow such as cybersecurity, trust, privacy, and ownership among others intersect these entities, requiring the delineation of their interactions under different scenarios. This paper aims to not only highlight relevant research in the space of grid data flows, but also proposes, for the transmission-distribution sector, a novel modeling approach that marries the aforementioned entities: objectives, business functions, data interfaces, communication protocols, data stakeholders, and flow constraints. It elaborates on the design philosophy and the significance of each entity within the model and applies it to an example function of fault location, isolation and service restoration (FLISR). Finally, the next steps to extend the application of this data flow model for other practical operational scenarios are discussed.

Sundararajan, Aditya [ORNL] (ORCID:000000033577854↗
DOE OSTI2020

An Integrated Indexing and Search Service for Distributed File Systems

Data services such as search, discovery, and management in scalable distributed environments have traditionally been decoupled from the underlying file systems, and are often deployed using external databases and indexing services. However, modern data production rates, looming data movement costs, and the lack of metadata, entail revisiting the decoupled file system-data services design philosophy. In this article, we present TagIt, a scalable data management service framework aimed at scientific datasets, which can be integrated into prevalent distributed file system architectures. A key feature of TagIt is a scalable, distributed metadata indexing framework, which facilitates a flexible tagging capability to support data discovery. Furthermore, the tags can also be associated with an active operator, for pre-processing, filtering, or automatic metadata extraction, which we seamlessly offload to file servers in a load-aware fashion. We have integrated TagIt into two popular distributed file systems, i.e., GlusterFS and CephFS. Our evaluation demonstrates that TagIt can expedite data search operation by up to 10× over the extant decoupled approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Methods for Estimating Hydrogen Fuel Tank Characteristics

The pressure vessels needed to store hydrogen for next-generation hydrogen fuel cell vehicles are expected to be a substantial portion of the total system mass, volume, and cost. Gravimetric capacity, volumetric capacity, and cost per kilogram of usable hydrogen are key performance metrics that the U.S. Department of Energy (DOE) uses to determine the viability of hydrogen fuel cell systems. Research and development related to hydrogen storage systems covers a wide range of potential operating conditions, from cryogenic temperatures to high temperatures (above ambient) and low pressure to high pressure. Researchers at PNNL have developed methods for estimating these key pressure vessel characteristics to support on-board hydrogen storage system design and performance evaluation and to support decision-making about DOE hydrogen storage system research investments. This article describes the pressure tank estimation methodology that has been used as a stand-alone calculation and has been incorporated into larger system evaluation tools. The methodology estimates the geometry, mass, and material cost of type I, type III, and type IV pressure vessels based on operating pressure and material strength at the system's operating temperature, using classical thin-wall and thick-wall pressure vessel stress calculations. The geometry, mass, and material cost requirements of the pressure vessel have significant impacts on the total system performance. For example, hydrogen storage materials that can separately achieve a very high hydrogen density can be deemed impractical for use in fuel cell vehicle hydrogen storage systems because the pressure tank containing them is too large, heavy, or expensive. This article describes the design philosophy and analytical process of the tank characteristic estimation methodology, which has been implemented in spreadsheet calculation tools and system-level analysis tools used by DOE researchers. Each of the three tank types (type I, type III, and type IV) uses a different analysis methodology with some common elements. This article also provides examples of implementing the methodology to perform parametric studies of all three pressure vessel types. The goal of this article is to present the methodology in sufficient detail so it can be implemented in other hydrogen fuel cell vehicle design and analysis tools.

42 ENGINEERING↗
DOE OSTI2025

From breaking rules to making rules in materials science

This editorial is a perspective article discussing the broader philosophy of synthesis science, emphasizing how techniques such as MBE allow researchers to manipulate bonding, structure, and defects beyond equilibrium thermodynamics, enabling the design of new materials and emergent properties through controlled growth and epitaxial engineering.

Jalan, Bharat [Univ. of Minnesota, Minneapolis, MN↗
DOE OSTI2023

UFO 2.0: the ‘Universal Feynman Output’ format

Abstract We present an update of the Universal FeynRules Output model format, commonly known as the UFO format, that is used by several automated matrix-element generators and high-energy physics software. We detail different features that have been proposed as extensions of the initial format during the last ten years, and collect them in the current second version of the model format that we coin the Universal Feynman Output format. Following the initial philosophy of the UFO, they consist of flexible and modular additions to address particle decays, custom propagators, form factors, the renormalisation group running of parameters and masses, and higher-order quantum corrections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗