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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Testing meson portal dark sector solutions to the MiniBooNE anomaly at the Coherent CAPTAIN Mills experiment

A solution to the MiniBooNE excess invoking rare three-body decays of the charged pions and kaons to new states in the MeV mass scale was recently proposed as a dark-sector explanation. This class of solution illuminates the fact that, while the charged pions were focused in the target-mode run, their decay products were isotropically suppressed in the beam-dump-mode run in which no excess was observed. This suggests a new physics solution correlated to the mesonic sector. We investigate an extended set of phenomenological models that can explain the MiniBooNE excess as a dark sector solution, utilizing long-lived particles that might be produced in the three-body decays of the charged mesons and the two-body anomalous decays of the neutral mesons. Over a broad set of interactions with the long-lived particles, we show that these scenarios can be compatible with constraints from LSND, KARMEN, and MicroBooNE, and evaluate the sensitivity of the ongoing and future data taken by the Coherent CAPTAIN Mills experiment to a potential discovery in this parameter space. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Improved chemistry restraints for crystallographic refinement by integrating the Amber force field into Phenix

The refinement of biomolecular crystallographic models relies on geometric restraints to help to address the paucity of experimental data typical in these experiments. Limitations in these restraints can degrade the quality of the resulting atomic models. Here, an integration of the full all-atom Amber molecular-dynamics force field into Phenix crystallographic refinement is presented, which enables more complete modeling of biomolecular chemistry. The advantages of the force field include a carefully derived set of torsion-angle potentials, an extensive and flexible set of atom types, Lennard–Jones treatment of nonbonded interactions and a full treatment of crystalline electrostatics. The new combined method was tested against conventional geometry restraints for over 22 000 protein structures. Structures refined with the new method show substantially improved model quality. On average, Ramachandran and rotamer scores are somewhat better, clashscores and MolProbity scores are significantly improved, and the modeling of electrostatics leads to structures that exhibit more, and more correct, hydrogen bonds than those refined using traditional geometry restraints. In general it is found that model improvements are greatest at lower resolutions, prompting plans to add the Amber target function to real-space refinement for use in electron cryo-microscopy. This work opens the door to the future development of more advanced applications such as Amber -based ensemble refinement, quantum-mechanical representation of active sites and improved geometric restraints for simulated annealing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Machine learning approaches for intentional materials engineering

In this article, the development of nanoporous metals and metallic composites through dealloying processes presents significant opportunities in materials engineering. However, designing multicomponent precursor alloys and establishing corresponding processing methods that yield predictable compositions and nanostructures remain a complex challenge. This article explores how machine learning (ML)-augmented computational and experimental methodologies can tackle these challenges by predicting precursor alloy compositions, final nanoporous structures, and mechanical properties, while integrating ML-enabled autonomous experimentation for material design and quantification. We highlight recent advancements in applying ML to nanostructured materials design via dealloying and discuss how techniques from other nanomaterial designs can be adapted for improved control over morphological and compositional outcomes in nanoporous and nanocomposite materials. Furthermore, we explore the role of ML in autonomous synchrotron x-ray experimentation, enabling real-time feedback between modeling and experimental setups. ML-driven approaches to microstructure characterization and mechanical property prediction are also examined, with a focus on modeling and advanced imaging techniques such as three-dimensional nanotomography. Finally, this article outlines future directions for ML-enhanced materials science, emphasizing the exploration of high-dimensional parameter spaces and the incorporation of materials kinetics into processing and property evaluation, ultimately advancing the design of nanoporous structures and materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2021

IOTA Run 2 Beam Dynamics Studies in Nonlinear Integrable Systems

Nonlinear integrable optics is a promising design approach for suppressing fast collective instabilities. To study it experimentally, a new storage ring, the Integrable Optics Test Accelerator (IOTA), was built at Fermilab. IOTA has recently completed its second scientific run, incorporating many hardware and instrumentation improvements. This report presents the results of the two integrable optics experiments - the quasi-integrable Henon-Heiles octupole system and the fully integrable Danilov-Nagaitsev system. We demonstrate tune spread and dynamic aperture in agreement with tracking simulations, and a stable crossing of the integer resonance. Based on recovered single-particle phase space dynamics, we show improved invariant jitter consistent with intended effective Hamiltonian. We conclude by outlining future plans and efforts towards proton studies and larger designs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Proton Dynamics Scenarios in the Integrable Optics Test Accelerator (IOTA) at Fermilab

The Integrable Optics Test Accelerator (IOTA) at Fermilab provides a versatile platform for studying the interplay of space-charge, impedance, and non-linear optics in high-intensity hadron beams within synchrotrons and storage rings. This report examines the parameters and dynamics of 2.5~MeV proton beam operations in two configurations of the bare IOTA lattice: one for demonstrating Non-linear Integrable Optics with the Danilov-Nagaitsev magnet, and the other for use with electron cooling. We offer order-of-magnitude estimates of the transverse emittance growth rate as a function of beam intensity, highlighting contributions from residual gas scattering, intra-beam scattering, and space-charge effects. Under nominal conditions, the beam lifetime is projected to be less than 7~minutes at low intensity with the current vacuum quality, and fewer than 100,000~turns at high intensity due to strong space-charge effects. The calculations presented here will guide strategies to mitigate emittance growth and inform future IOTA experiments.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Complementarity between neutrinoless double beta decay and collider searches for heavy neutrinos in composite-fermion models

Composite-fermion models predict excited quarks and leptons with mass scales which can potentially be observed at high-energy colliders like the LHC; the most recent exclusion limits from the CMS and ATLAS Collaborations corner excited-fermion masses and the compositeness scale to the multi-TeV range. At the same time, hypothetical composite Majorana neutrinos would lead to observable effects in neutrinoless double beta decay ($0\nu \beta \beta$) experiments. In this work, we show that the current composite-neutrino exclusion limit $M_N>4.6$ TeV, as extracted from direct searches at the LHC, can indeed be further improved to $M_N>8.8$ TeV by including the bound on the nuclear transition $^{136}$Xe $\to ^{136}$Ba + $2e^-$. Looking ahead, the forthcoming HL-LHC will allow probing a larger portion of the parameter-space, nevertheless, it will still benefit from the complementary limit provided by $0 \nu \beta \beta$ future detectors to explore composite-neutrino masses up to $12.6$ TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Why Are There so Few Reports of High-Energy Electron Drift Resonances? Role of Radial Phase Space Density Gradients

Models of monochromatic Pc5 (2–7 mHz) ultralow frequency (ULF) wave interactions with high energy (greater than ~1 MeV) electrons predict drift resonant interactions that can cause rapid radial transport and acceleration. There are few reports of electron drift resonance at energies greater than ~1 MeV, in contrast to lower energies; moreover, all previous reports occur in the aftermath of interplanetary shocks. These two facts are difficult to reconcile with theory and numerical simulations predicting that greater than ~1 MeV drift resonances should occur more often and in a wider variety of driving conditions. In this study, we show that a combination of observational sampling biases and nominal radial phase space density gradients is one explanation for this discrepancy between theory and observations. In particular, we examine electron dynamics in two case studies with very similar satellite coverage, solar wind conditions, and Pc5 wave properties, yet with different radial phase space density profiles. Using global wave and particle observations, we show that the events have vastly different particle responses despite having similar wave properties. Placing these results in context with past studies, we further show here that nominal radial PSD gradients near geostationary orbit can mask the expected drift resonance particle response and explain (1) the small number of past greater than ~1 MeV drift resonance reports and (2) the restriction of these reports to interplanetary shock events. We argue that future observational studies characterizing radial transport via drift resonance should examine global particle dynamics, including observations of the radial phase space density profile.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Quantum simulation of hyperbolic space with circuit quantum electrodynamics: From graphs to geometry

We show how quantum many-body systems on hyperbolic lattices with nearest-neighbor hopping and local interactions can be mapped onto quantum field theories in continuous negatively curved space. Here, the underlying lattices have recently been realized experimentally with superconducting resonators and therefore allow for a table-top quantum simulation of quantum physics in curved background. Our mapping provides a computational tool to determine observables of the discrete system even for large lattices, where exact diagonalization fails. As an application and proof of principle we quantitatively reproduce the ground state energy, spectral gap, and correlation functions of the noninteracting lattice system by means of analytic formulas on the Poincaré disk, and show how conformal symmetry emerges for large lattices. This sets the stage for studying interactions and disorder on hyperbolic graphs in the future. Importantly, our analysis reveals that even relatively small discrete hyperbolic lattices emulate the continuous geometry of negatively curved space, and thus can be used to experimentally resolve fundamental open problems at the interface of interacting many-body systems, quantum field theory in curved space, and quantum gravity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Coupling 1D xRAGE simulations with machine learning for graded inner shell design optimization in double shell capsules

Advances in machine learning provide the ability to leverage data from expensive simulations of high-energy-density experiments to significantly cut down on computational time and costs associated with the search for optimal target designs. This study presents an application of cutting-edge Bayesian optimization methods to the one-dimensional (1D) design optimization of double shell graded layer targets for inertial confinement fusion experiments. This investigation attempts to reduce hydrodynamic instabilities while retaining high yields for future NIF experiments. Machine learning methods can use predictive physics simulations to identify graded layer designs from within the vast design space that demonstrate high predicted performance, including novel designs with high uncertainty in performance that may hold unexpected promise. By applying machine learning tools to the simulation design, we map the trade-off between 1D yield and instability, specifically isolating parameter ranges, which maintain high performance while showing significantly improved Rayleigh–Taylor stability over the point design. Furthermore, the groundwork laid in this study will be a useful design tool for future NIF experiments with graded layer targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Special Considerations for the Removal and Disposal of Micro-Reactor Experiments

Idaho National Laboratory (INL) is preparing to host several microreactor experiments through 2030 and beyond. Two new test beds currently under development will operate as microreactor or nuclear system experiment user facilities. Test bed experiments will be performed in series, with each nuclear experiment installed, operated, and removed before installation of the subsequent experiment. The necessarily brief transition period between experiments introduces unique equipment removal and radioactive waste disposal challenges. This paper evaluates equipment removal and radioactive waste management topics associated with tight sequencing of nuclear experiments and presents some of the solutions and approaches currently planned to meet these special considerations for one such experiment, the Molten Chloride Reactor Experiment (MCRE), slated for operation at INL’s Laboratory for Operation and Testing in the United States (LOTUS). The MCRE project is a collaboration between Southern Company Services, TerraPower, and INL, among others, to provide integral nuclear data that will advance molten salt fast reactor technology. MCRE will be the first critical fast-spectrum circulating fuel system ever operated and the first experiment operated in the LOTUS test bed. The experiment will nominally operate at zero power with planned low power excursions as part of operational planning for MCRE has been to minimize at-power operations to limit fission product formation while still achieving experimental objectives. After the experiment is complete, MCRE will be allowed to radioactively decay for a short period (nominally 90 days) prior to system defueling, flushing, removal, and disposal of all MCRE equipment, readying the test bed for the next nuclear experiment. Equipment removal and radioactive waste disposal have been integral to MCRE project planning since the Cooperative Research and Development Agreement was formalized in 2021. Due to requirements for future use of the test bed, the MCRE system, of necessity, must be removed in a much shorter time frame than typical for historic reactor decommissioning projects at INL. This results in minimal time for radioactive decay, resulting in not only elevated radiation dose rates but also the presence of short-to-medium-lived isotopes not typically encountered in the reactor decommissioning and radioactive waste management space. Additional unique constraints placed on the project include lack of intrinsic remote-operations capabilities in the test bed, space constraints in the test bed once MCRE has been installed, and contamination minimization requirements to return the test bed to as-found conditions to enable future use. This paper discusses planned solutions to these challenges. Approaches for implementing remote or semi-remote technologies in a non-hot cell environment with limited space availability are discussed. The paper also summarizes the systems engineering approach for concept development and design of equipment removal systems, which are being implemented concurrent with the MCRE design phase, providing feedback to system designers to incorporate features enabling efficient and safe equipment removal approaches. The timing of this paper at a relatively early phase of the project is meant to highlight the importance of early planning for nuclear system decommissioning while reactor design is ongoing to allow design feedback on componentry driven from decommissioning system needs. As new, innovative nuclear reactor technologies enter the nuclear market sector, reactor experiments are crucial for providing new integral nuclear data that establish safe operational margins for technology advancement. Microreactor experiments at INL will require safe, effective, and timely decommissioning approaches, which in turn require nuclear systems designed to expedite decommissioning. In addition to the advancement of nuclear reactor technologies, these nuclear experiments provide an opportunity to demonstrate, deploy, and test new removal and disposal capabilities to support the next generation of nuclear reactor technology.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

NoRA: A Tensor Network Ansatz for Volume-Law Entangled Equilibrium States of Highly Connected Hamiltonians

Motivated by the ground state structure of quantum models with all-to-all interactions such as mean-field quantum spin glass models and the Sachdev-Ye-Kitaev (SYK) model, we propose a tensor network architecture which can accomodate volume law entanglement and a large ground state degeneracy. We call this architecture the non-local renormalization ansatz (NoRA) because it can be viewed as a generalization of MERA, DMERA, and branching MERA networks with the constraints of spatial locality removed. We argue that the architecture is potentially expressive enough to capture the entanglement and complexity of the ground space of the SYK model, thus making it a suitable variational ansatz, but we leave a detailed study of SYK to future work. We further explore the architecture in the special case in which the tensors are random Clifford gates. Here the architecture can be viewed as the encoding map of a random stabilizer code. We introduce a family of codes inspired by the SYK model which can be chosen to have constant rate and linear distance at the cost of some high weight stabilizers. We also comment on potential similarities between this code family and the approximate code formed from the SYK ground space.

Physics↗
DOE OSTI2020

LHS 1815b: The First Thick-disk Planet Detected by TESS

We report the first discovery of a thick-disk planet, LHS 1815b (TOI-704b, TIC 260004324), detected in the Transiting Exoplanet Survey Satellite (TESS) survey. LHS 1815b transits a bright (V = 12.19 mag, K = 7.99 mag) and quiet M dwarf located 29.87 ± 0.02 pc away with a mass of 0.502 ± 0.015 M {sub ⊙} and a radius of 0.501 ± 0.030 R {sub ⊙}. We validate the planet by combining space- and ground-based photometry, spectroscopy, and imaging. The planet has a radius of 1.088 ± 0.064 R {sub ⊕} with a 3σ mass upper limit of 8.7 M {sub ⊕}. We analyze the galactic kinematics and orbit of the host star LHS 1815 and find that it has a large probability (P {sub thick}/P {sub thin} = 6482) to be in the thick disk with a much higher expected maximal height (Z {sub max} = 1.8 kpc) above the Galactic plane compared with other TESS planet host stars. Future studies of the interior structure and atmospheric properties of planets in such systems using, for example, the upcoming James Webb Space Telescope, can investigate the differences in formation efficiency and evolution for planetary systems between different Galactic components (thick disks, thin disks, and halo).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A historical overview of the activation and porosity of metal–organic frameworks

Since the first reports of metal–organic frameworks (MOFs), this unique class of crystalline, porous materials has garnered increasing attention in a wide variety of applications such as gas storage and separation, catalysis, enzyme immobilization, drug delivery, water capture, and sensing. A fundamental feature of MOFs is their porosity which provides space on the micro- and meso-scale for confining and exposing their functionalities. Therefore, designing MOFs with high porosity and developing suitable activation methods for preserving and accessing their pore space have been a common theme in MOF research. Reticular chemistry allows for the facile design of MOFs from highly tunable metal nodes and organic linkers in order to realize different pore structures, topologies, and functionalities. With the hope of shedding light on future research endeavors in MOF porosity, it is worthwhile to examine the development of MOFs, with an emphasis on their porosity and how to properly access their pore space. In this review, we will provide an overview of the historic evolution of porosity and activation of MOFs, followed by a synopsis of the strategies to design and preserve permanent porosity in MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Biofuels for a sustainable future

Rapid increases of energy consumption and human dependency on fossil fuels have led to the accumulation of greenhouse gases and consequently, climate change. As such, major efforts have been taken to develop, test, and adopt clean renewable fuel alternatives. Production of bioethanol and biodiesel from crops is well developed, while other feedstock resources and processes have also shown high potential to provide efficient and cost-effective alternatives, such as landfill and plastic waste conversion, algal photosynthesis, as well as electrochemical carbon fixation. In addition, the downstream microbial fermentation can be further engineered to not only increase the product yield but also expand the chemical space of biofuels through the rational design and fine-tuning of biosynthetic pathways toward the realization of "designer fuels" and diverse future applications.

09 BIOMASS FUELS↗
DOE OSTI2025

Direct deflection of Millicharged radiation

Millicharged particles are generic in theories of dark sectors. A cosmic or local abundance of them may be produced by the early universe, stellar environments, or the decay or annihilation of dark matter/dark energy. Furthermore, if such particles are light, these production channels result in a background of millicharged radiation. We show that light-shining-through-wall experiments employing superconducting RF cavities can also be used as “direct deflection” experiments to search for this relativistic background. The millicharged plasma is first subjected to an oscillating electromagnetic field of a driven cavity, which causes charge separation in the form of charge and current perturbations. In turn, these perturbations can propagate outwards and resonantly excite electromagnetic fields in a well-shielded cavity placed nearby, enabling detection. We estimate that future versions of the existing Dark SRF experiment can probe orders of magnitude of currently unexplored parameter space, including millicharges produced from the Sun, the cosmic neutrino background, or other mechanisms that generate a thermal abundance with energy density as small as ~ 10$^{−4}$ that of the cosmic microwave background.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Earth-scattering induced modulation in low-threshold dark matter experiments

Dark matter particles with sufficiently large interactions with ordinary matter can scatter in the Earth before reaching and scattering in a detector. This induces a modulation in the signal rate with a period of one sidereal day. We calculate this modulation for sub-GeV dark matter particles that interact either with a heavy or an ultralight dark-photon mediator and investigate the resulting signal in low-threshold detectors consisting of silicon, xenon, or argon targets. The scattering in the Earth is dominated by dark matter scatters off nuclei, while the signal in the detector is easiest to observe from dark matter scattering off electrons. We investigate the properties of the modulation signal and provide projections of the sensitivity of future experiments. We find that a search for a modulation signal can probe new regions of parameter space near the energy thresholds of current experiments, where the data are typically dominated by backgrounds.

Models for Dark Matter↗
DOE OSTI2026

Optimal CO 2 storage management considering safety constraints in multi-stakeholder multi-site GCS projects: A Markov game perspective

Geological carbon storage (GCS) projects could involve a diverse array of stakeholders or players from public, private, and regulatory sectors, each with different objectives and responsibilities. Given the complexity, scale, and long-term nature of GCS operations, determining whether individual stakeholders can independently optimize their interests — or whether collaborative coalition agreements are needed — remains a central question for effective GCS project planning and management. To access large, high-quality storage resources, future GCS deployment may increasingly occur in geologically connected sites, where shared geological features such as pressure space and reservoir pore capacity can lead to competitive behavior among stakeholders. In this work, we propose a paradigm based on Markov games to quantitatively investigate how different coalition structures affect the goals of stakeholders. We frame this multi-stakeholder multi-site problem as a multi-agent reinforcement learning problem with safety constraints. Our approach enables agents to learn optimal strategies while complying with safety regulations. We present an example where multiple operators are injecting CO 2 into their respective project areas in a geologically connected basin. To address the high computational cost of repeated simulations of high fidelity models, a previously developed surrogate model based on the Embed-to-Control (E2C) framework is employed. Our results demonstrate the effectiveness of the proposed framework in addressing optimal management of CO 2 storage when multiple stakeholders with different objectives and goals are involved.

58 GEOSCIENCES↗
DOE OSTI2021

A Machine Learning Approach for the Prediction of Formability and Thermodynamic Stability of Single and Double Perovskite Oxides

Perovskite oxides continue to attract huge interest due to their fascinating and wide-ranging properties for diverse applications. The tunability of these properties may be further enhanced by increasing their compositional complexity via double perovskite-ordered configurations containing multiple cations. In this work, we focus on an exhaustive chemical space of single and double oxide perovskites and optimally explore this space to identify novel compositions that are likely to form stable compounds. Critically, we examine the relationship between formability, the practical ability to synthesize a compound, and stability, the thermodynamic preference to form the structure. Our formability and stability training data sets were enumerated from the available experimental literature and in-house density functional theory computations and contained 1505 and 3469 examples, respectively, representing state-of-the-art in the current open literature in perovskite and double perovskite compounds. Subsequently, cross-validated and highly accurate machine learning classification models are built using these training data sets and employed to screen for novel stable oxide perovskites. The study identifies (1) atomic features relevant to prediction of formability and stability in perovskite and double perovskite compounds, (2) the importance of including energy contributions due to local structural relaxations going beyond the high symmetry perovskite phase, and (3) 437,828 double perovskite compounds that are likely to be stable and 891,188 compounds that are likely to be formable. From the intersection of this large chemical space of formable and stable oxide perovskites, 414 compositions are identified as the most promising candidates for future experimental synthesis of novel oxide perovskites. The developed models may be generalized and have implications beyond perovskite discovery if applied to other families of compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗