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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 OSTI2023

Dynamic Aperture of the PIP-II Accumulator Ring (PAR)

The Proton Improvement Plan-II (PIP-II) will include a superconducting linear accelerator which will accelerate H- ions to 800MeV, at an intensity never seen before. A proposed PIP-II Accumulator Ring (PAR) can reduce the injection losses to the booster, enhance the ramp up of the Long Baseline Neutrino Facility (LBNF) and support experiments in Dark Sector Physics. When the beam is circulating in PAR at its full intensity, it will then be transferred to the Booster via single turn injection. Strong PAR focusing results in larger phase advances, shorter focal lengths and higher machine tunes, which creates robust beam envelope control. Particles will be able to survive modest excursions from the elliptical phase-space trajectories of linear optics, and any loss of particles would be due to reduced dynamic aperture. The values for tunes and chromaticities are flexible and will continue to evolve as the lattice matures. Since there will be non-linear terms impacting the particles’ trajectories, tracking will include realistic magnetic field errors and installation alignment errors to determine the dynamic aperture as a function of the machine tunes. This will allow us to determine the optimum operating point in phase-space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters

High-precision calorimeter simulation at current and future colliders imposes rapidly growing computational demands, motivating the development of machine-learning surrogates for traditional Monte Carlo tools such as Geant4. Flow matching and diffusion-based generative models have become leading approaches for high-dimensional fast simulation because of their sample quality, but typically require ${\cal O}(100)$ function evaluations at inference and often rely on auxiliary networks to constrain global observables, compromising streamlined end-to-end generation. We introduce a unified framework that improves the balance between speed, shower quality, and physics fidelity. The method combines: (i) an average velocity field integrator that enables sampling in one or a few evaluations; (ii) a learned generative prior in shower space, constructed from data rather than random noise; and (iii) physics-guided loss terms that impose inductive biases on key observables during training. These elements are training time regularizers, preserving end-to-end inference with no additional cost. With only one or a few evaluation steps, the model achieves shower quality competitive with state-of-the-art flow and diffusion approaches, tested on several public high granularity calorimeter datasets. The results demonstrate inter-layer shower structure consistent with the underlying physics, providing a strong candidate for future fast simulation workflows.

Jiang, Cheng [Edinburgh U.]↗
DOE OSTI2022

Computational evolution of high-performing unfused non-fullerene acceptors for organic solar cells

Materials optimization for organic solar cells (OSCs) is a highly active field, with many approaches using empirical experimental synthesis, computational brute force to screen a subset of chemical space, or generative machine learning methods that often require significant training sets. While these methods may find high-performing materials, they can be inefficient and time-consuming. Genetic algorithms (GAs) are an alternative approach, allowing for the “virtual synthesis” of molecules and a prediction of their “fitness” for some property, with new candidates suggested based on good characteristics of previously generated molecules. In this work, a GA is used to discover high-performing unfused non-fullerene acceptors (NFAs) based on an empirical prediction of power conversion efficiency (PCE) and provides design rules for future work. The electron-withdrawing/donating strength, as well as the sequence and symmetry, of those units are examined. The utilization of a GA over a brute-force approach resulted in speedups up to 1.8 × 10 12 . New types of units, not frequently seen in OSCs, are suggested, and in total 5426 NFAs are discovered with the GA. Of these, 1087 NFAs are predicted to have a PCE greater than 18%, which is roughly the current record efficiency. While the symmetry of the sequence showed no correlation with PCE, analysis of the sequence arrangement revealed that higher performance can be achieved with a donor core and acceptor end groups. Future NFA designs should consider this strategy as an alternative to the current A-D-A'-D-A architecture.

14 SOLAR ENERGY↗
DOE OSTI2021

Computational Fluid Dynamics Simulations to Support Efficiency Improvements in Aluminum Smelting Process

Smelting is broadly described as the extraction of a metal from its ore. In the United States, aluminum is commonly produced by smelting alumina in bauxite using the Hall-Héroult process. Optimization of equipment and processes in conventional smelting is crucial to enhancing process efficiency and productivity, is necessary for improving the techno-economic feasibility, which directly manifests as the growth of the American economy. To achieve optima, insightful data on the multiphysics phenomena that are inherent to the process must be obtained through physical investigation or high-fidelity numerical simulations. The resolution of relevant scales in time and space for smelting operations requires intensive, high-performance computing (HPC) simulations. Hostile operating conditions limit physical data acquisition to specific techniques; therefore, these data do not describe the multiscale interaction of simultaneous effects. Fortunately, in recent decades, significant advancements in computing hardware and computational methods have made the numerical resolution of such a complex process possible. In this study, a high-fidelity simulation of aluminum smelting was performed using an open-source tool, OpenFOAM, which analyzed many parameters characteristic to underlying phenomena. A multiphysics model based on the Eulerian-Eulerian multifluid approach was adopted. This model can resolve critical issues in the electrolytic smelting of aluminum, such as bubbling of carbon dioxide from the anode(s), magnetohydrodynamics from electromagnetic effects, ionic dissolution of the alumina in the electrolyte, and the evolution of thermal profiles. This study provides valuable connectivity for characteristic data that can direct the future designs of efficient smelters. A basic framework to model and simulate the smelting process using OpenFOAM is presented for user modification in keeping with process development. Of relevance to the flow field, a detailed investigation of vortices produced by bubble motion and electromagnetics is discussed, along with their impact on the evolution of thermal profiles. The predictions show small-scale vortices in the clearance between the anode and cathode caused by magnetic forces. Predictions also indicate relatively large-scale vortices in the inter-anode space resulting from carbon dioxide rising through the electrolytic flow field. The formation of vortices at the edges of anodes was shown to direct alumina charged by the feeder to the bottom of the anodes, thus preventing the entrapment of gas bubbles in the periphery of the bottom of the anode. Symmetry was observed in the location of cold spots in the electrolytic mixture in the vicinity of the feeder. Cold spots were also observed in the clearance between the anode and cathode due to the flow’s transmission of unconverted alumina to this region.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Calibration of cloud and aerosol related parameters for solar irradiance forecasts in WRF-solar

Model parameters are a major source of uncertainty in numerical weather prediction. Recently, the Weather Research and Forecasting model with Solar extensions (WRF-Solar) has been upgraded by enhancing the treatment of sub-grid scale cloud and aerosols with augmentations of a sub-grid scale cloud scheme (CLD3) and an upgraded aerosol-aware Thompson-Eidhammer scheme (TE14). However, the value of model parameters associated with these parameterizations are assigned based on limited measurements or theoretical calculations. Calibrating the most sensitive parameters has the potential to improve solar irradiance predictions. Here, we adopted a multiobjective surrogate-based optimization (SBO) framework to calibrate nine parameters used in CLD3 and TE14 that lead to the largest sensitivity in simulated irradiance. The normalized mean-absolute-error (NMAE) of global horizontal irradiance (GHI) and direct normal irradiance (DNI) are minimized by calibrating WRF-Solar over two regions including the Southern Great Plains (SGP) and Central California, in order to focus on parameter calibration under cloudy conditions with different aerosol loading. The results show that generalized linear model (GLM)-based surrogate models approximate physical models well, particularly when the third order and three-way interaction terms are considered. The SBO framework efficiently searches the parameter space for optimal solutions with less computational costs than directly calibrating the physical model. We first calibrate CLD3 parameters over the less-polluted SGP region. Optimized CLD3 parameters alone result in NMAE reduction by 14% for the site-mean and up to 33% for individual cases over the SGP region. With further calibration of TE14 parameters over the Central California during active fire periods, the optimized parameters lead to over 20% reductions of NMAE. Our investigation reveals, however, that optimizing TE14 has a limited impact on irradiance simulations under less-polluted conditions in the SGP.

14 SOLAR ENERGY↗
DOE OSTI2022

Hypothesis Learning in Automated Experiment: Application to Combinatorial Materials Libraries

Machine learning is rapidly becoming an integral part of experimental physical discovery via automated and high-throughput synthesis, and active experiments in scattering and electron/probe microscopy. This, in turn, necessitates the development of active learning methods capable of exploring relevant parameter spaces with the smallest number of steps. In this work, an active learning approach based on conavigation of the hypothesis and experimental spaces is introduced. This is realized by combining the structured Gaussian processes containing probabilistic models of the possible system's behaviors (hypotheses) with reinforcement learning policy refinement (discovery). This approach closely resembles classical human-driven physical discovery, when several alternative hypotheses realized via models with adjustable parameters are tested during an experiment. This approach is demonstrated for exploring concentration-induced phase transitions in combinatorial libraries of Sm-doped BiFeO 3 using piezoresponse force microscopy, but it is straightforward to extend it to higher-dimensional parameter spaces and more complex physical problems once the experimental workflow and hypothesis generation are available.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Unified many-worlds browsing of arbitrary physics-based animations

Manually tuning physics-based animation parameters to explore a simulation outcome space or achieve desired motion outcomes can be notoriously tedious. This problem has motivated many sophisticated and specialized optimization-based methods for fine-grained (keyframe) control, each of which are typically limited to specific animation phenomena, usually complicated, and, unfortunately, not widely used. In this paper, we propose Unified Many-Worlds Browsing (UMWB), a practical method for sample-level control and exploration of physics-based animations. Our approach supports browsing of large simulation ensembles of arbitrary animation phenomena by using a unified volumetric WORLDPACK representation based on spatiotemporally compressed voxel data associated with geometric occupancy and other low-fidelity animation state. Beyond memory reduction, the WORLDPACK representation also enables unified query support for interactive browsing: it provides fast evaluation of approximate spatiotemporal queries, such as occupancy tests that find ensemble samples ("worlds") where material is either IN or NOT IN a user-specified spacetime region. WORLDPACKS also support real-time hardware-accelerated voxel rendering by exploiting the spatially hierarchical and temporal RLE raster data structure. Our UMWB implementation supports interactive browsing (and offline refinement) of ensembles containing thousands of simulation samples, and fast spatiotemporal queries and ranking. We show UMWB results using a wide variety of physics-based animation phenomena---not just JELL-O ® .

Computer Science↗
DOE OSTI2021

A derivation of Born’s rule from symmetry

Highlights: • A very simple proof for the rule by which we calculate probabilities in quantum mechanics. We here put forward a simple argument for Born’s rule based on the requirement that transition probabilities in quantum mechanics should not be a function of the number of degrees of freedom in the system, or the dimension of the Hilbert-space, respectively. The argument presented here can be interpreted as deriving Born’s rule from a symmetry requirement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

S -matrix positivity without Lorentz invariance: a case study

We investigate the analytic structure of scattering amplitudes in theories in which Lorentz invariance is spontaneously broken. We do so by computing and studying the S-matrix for a simple example: a superfluid described by a complex scalar with quartic interactions. The computation is confined to tree-level, for there are no absolutely stable single-particle states, though the lifetime can be made long by lowering the chemical potential. For the 2 → 2 amplitude in center-of-mass configurations, not only is crossing symmetry violated, there appears a tree level branch cut for unphysical kinematics. Its appearance is a consequence of non-analyticity in the dispersion relation. The branch point defines a new scale in the problem, which scales inversely with the chemical potential. In this example, even derivatives of the forward amplitude are positive while odd derivatives are negative. This pattern can be understood in a general way in the limit of a small chemical potential, or weak Lorentz breaking.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Celestial gluon amplitudes from the outside in

We show that, given a two-dimensional realization of the celestial OPE in self-dual Yang-Mills, we can find a scalar source around which scattering amplitudes replicate correlation functions computed from the 2D ‘gluon’ operators in a limit where a dynamic massless scalar decouples. We derive conditions on the two-dimensional three-point correlation function so that such a source exists and give two particular examples of this construction, one in which gluons are constructed from vertex operators in the semiclassical limit of Liouville theory and another in which the soft gluons arise from generalized free fields. Finally, we identify a bulk dual to the level of the boundary Kac-Moody algebra and discuss moving beyond the decoupling limit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Zwanziger’s pairwise little group on the celestial sphere

We generalize Zwanziger’s pairwise little group to include a boost subgroup. We do so by working in the celestial sphere representation of scattering amplitudes. We propose that due to late time soft photon and graviton exchanges, matter particles in the asymptotic states in massless QED and gravity transform under the Poincaré group with an additional pair of pairwise celestial representations for each pair of matter particles. We demonstrate that the massless abelian and gravitational exponentiation theorems are consistent with the proposed pairwise Poincaré transformation properties. For massless QED we demonstrate that our results are consistent with the effects of the Faddeev-Kulish dressing and the abelian exponentiation theorem for celestial amplitudes found in arXiv:2012.04208. We discuss electric and magnetic charges simultaneously as it is especially natural to do so in this formalism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Sunbeam: Near-sun statites as beam platforms for beam-driven rockets

Here, we outline a method of beamed power for propulsion that utilizes relativistic electron beams. The physics of charged particle beam propagation in the space plasma environment is discussed and the long-range (> 100 AU) advantage of relativistic electron beams is emphasized. A preliminary statite-based beam emitter for powering probes to 0.1c is proposed and the challenges in beamed-power uses are explored.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Higher-rank tensor field theory of non-abelian fracton and embeddon

We formulate a new class of tensor gauge field theories in any dimension that is a hybrid class between symmetric higher-rank tensor gauge theory (i.e., higher-spin gauge theory) and anti-symmetric tensor topological field theory. Our theory describes a mixed unitary phase interplaying between gapless and gapped topological order phases (which can live with or without Euclidean, Poincaré, or anisotropic symmetry, at least in ultraviolet high or intermediate energy field theory, but not yet to a lattice cutoff scale). The “gauge structure” can be compact, continuous, abelian or non-abelian. Our theory sits outside the paradigm of Maxwell electromagnetic theory in 1865 and Yang–Mills isospin/color theory in 1954. We discuss its local gauge transformation in terms of the ungauged vector-like or tensor-like higher-moment global symmetry. The non-abelian gauge structure is caused by gauging the non-commutative symmetries: a higher-moment symmetry and a charge conjugation (particle–hole) symmetry. Vector global symmetries along time direction may exhibit time crystals. We explore the relation of these long-range entangled matters to a non-abelian generalization of Fracton order in condensed matter, a field theory formulation of foliation, the spacetime embedding and Embeddon that we newly introduce, and possible fundamental physics applications to dark matter or dark energy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Three-dimensional Skyrme Hartree-Fock-Bogoliubov solver in coordinate-space representation

The coordinate-space representation of the Hartree-Fock-Bogoliubov theory is the method of choice to study weakly bound nuclei whose properties are affected by the quasiparticle continuum space. To describe such systems, we developed a three-dimensional Skyrme-Hartree-Fock-Bogoliubov solver HFBFFT based on the existing, highly optimized and parallelized Skyrme-Hartree-Fock code Sky3D. The code does not impose any self-consistent spatial symmetries such as mirror inversions or parity. The underlying equations are solved in HFBFFT directly in the canonical basis using the fast Fourier transform. To remedy the problems with pairing collapse, we implemented the soft energy cutoff and pairing annealing. The convergence of HFB solutions was improved by a sub-iteration method. The Hermiticity violation of differential operators brought by Fourier-transform-based differentiation has also been solved. Furthermore, the accuracy and performance of HFBFFT were tested by benchmarking it against other HFB codes, both spherical and deformed, for a set of nuclei, both well-bound and weakly-bound.

3D coordinate-space representation↗
DOE OSTI2026

Discovery of a new phase transition and high-valent redox mechanism in Fe-substituted Na 2 Mn 3 O 7

Sodium-ion batteries are a promising lower-cost alternative to lithium-ion batteries, but further improvements in electrochemical performance are required. One strategy to increase capacity is to enable reversible high-valent cationic and anionic redox in layered cathode materials; however, this is typically accompanied by structural degradation. Here, in this study, we elucidate the mechanism by which Fe-doped Na 2 Mn 3 O 7 , featuring ordered transition metal-vacancies, achieves reversible high-valent redox. Using Mössbauer spectroscopy, soft X-ray absorption spectroscopy (XAS), and in-situ hard XAS, we demonstrate reversible high-valent cationic redox involving both Fe and Mn while in-situ Raman confirms the absence of local structural degradation associated with oxygen redox. Combining in-situ X-ray diffraction with theoretical calculations, we further identify a previously unreported global phase transition from the $\bar{P1}$ to the $P2_1/c$ space group during electrochemical cycling and develop a physical model describing this structural evolution. These results provide insights for structurally stable layered sodium transition metal oxide cathodes with reversible high-valent redox.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Understanding the Hydrogeochemical Response of a Mountainous Watershed Using Integrated Surface‐Subsurface Flow and Reactive Transport Modeling

Abstract Climate change and other disturbances significantly impact hydrogeochemical exports from mountainous headwater catchments such as the Upper Colorado River Basin. Developing a mechanistic understanding of how the physical and chemical processes interact in time and space in an integrated manner is key to quantifying the future impacts of such disturbances. The hydrogeochemical response of a mountainous catchment in the 2010–2019 period is evaluated quantitatively using a high‐resolution model that simulates integrated hydrology, and transport and reactions for selected solutes and minerals. The model assumes that pyrite is present only at depth while calcite is distributed uniformly, and captures the observed C‐Q reasonably well. Distinct C‐Q dynamics are observed in an average (WY16), a wet (WY17), and a dry (WY18) water year. The model also quantifies the water fraction from surface, shallow and deep groundwater compartments using tracers, and suggests greater groundwater contributions to peak stream discharge in the dry WY18. Results demonstrate that calcium concentrations do not change significantly from year to year, while sulfate shows significant temporal variability. Pyrite dissolution is affected by the changing hydrological drivers where it is enhanced in the dry WY18; calcite dissolution supplements calcium dilution under high flow conditions. The model simulates the reaction hotspots controlled by hydrological conditions, and the spatially‐resolved results show that higher soil saturation and less snowpack occur earlier on the south‐facing side than on the north‐facing side. This is a first‐of‐its‐kind demonstration of a model that integrates hydrologic processes, including evapotranspiration, and reactive transport to enable a predictive understanding of hydrogeochemical exports.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Application of the AI2 Climate Emulator to E3SMv2's Global Atmosphere Model, With a Focus on Precipitation Fidelity

Abstract Can the current successes of global machine learning‐based weather simulators be generalized beyond 2‐week forecasts to stable and accurate multiyear runs? The recently developed AI2 Climate Emulator (ACE) suggests this is feasible, based upon 10‐year simulations with a network trained on output from a physics‐based global atmosphere model using a grid spacing of approximately 110 km and forced by a repeating annual cycle of sea‐surface temperature. Here we show that ACE, without modification, can be trained to emulate another major atmospheric model, EAMv2, run at a comparable grid spacing for at least 10 years with similarly small climate biases—a prerequisite to wider applicability. With an analysis that combines multiple temporal, spatial, and frequency domain perspectives, we show that ACE faithfully represents the spatiotemporal structure of EAMv2 precipitation and related variables. Finally, we show that a pretrained ACE network is able to adapt to a new global climate model simulation data set with 10 fewer training steps than when starting from random initialization, all while still maintaining low levels of climate bias. Further analysis of these fine‐tuning experiments reveal ACE's intriguing ability to interpolate between distinct global climate models.

Duncan, James P. C.↗
DOE OSTI2021

Infrared spectroscopy of RG–Co + (H 2 O) complexes (RG = Ar, Ne, He): The role of rare gas “tag” atoms

RG n –Co + (H 2 O) cation complexes (RG = Ar, Ne, He) are generated in a supersonic expansion by pulsed laser vaporization. Here, complexes are mass-selected using a time-of-flight spectrometer and studied with infrared laser photodissociation spectroscopy, measuring the respective mass channels corresponding to the elimination of the rare gas “tag” atom. Spectral patterns and theory indicate that the structures of the ions with a single rare gas atom have this bound to the cobalt cation opposite the water moiety in a near-C 2v arrangement. The O–H stretch vibrations of the complex are shifted compared to those of water because of the metal cation charge-transfer interaction; these frequencies also vary systematically with the rare gas atom attached. The efficiencies of photodissociation also vary with the rare gas atoms because of their widely different binding energies to the cobalt cation. The spectrum of the argon complex could only be measured when at least three argon atoms were attached. In the case of the helium complex, the low binding energy allows the spectra to be measured for the low-frequency H–O–H scissors bending mode and for the O–D stretches of the deuterated analog. The partially resolved rotational structure for the antisymmetric O–H and O–D stretches reveals the temperature of these complexes (6 K) and establishes the electronic ground state. The helium complex has the same 3 B 1 ground state as the tag-free complex studied previously by Metz and co-workers (2013), but the A rotational constant is contaminated by vibrational averaging from the bending motion of the helium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗