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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Reduced Energetic Disorders in Dion–Jacobson Perovskites for Efficient and Spectral Stable Blue LEDs

Metal halide perovskites have witnessed great success in green, red, and near-infrared light-emitting diodes (LEDs), yet blue LEDs still lag behind. Reducing undesired energetic disorders – broad n -phases and halide segregation – is considered as the most critical strategy to further improve the performances. Here, the study reports a newly designed and synthesized di-ammonium ligand with rigid π -conjugated rings and additional methyl groups to construct Dion–Jacobson (DJ) structure. Augmented coordination from the extra ammonium site and increased effective bulkiness from methyl groups lead to better distribution control over conventional mono-ammonium ligands. This enhances the radiative recombination of blue emissions in the film with homogeneous energy landscape and improved surface morphology, as evidenced by a series of imaging and mapping techniques. As a result, it demonstrates DJ perovskite LEDs (PeLEDs) with peak external quantum efficiencies of ≈4% at 484 nm and ≈11% at 494 nm, which are among the top reported for pure DJ phase-based PeLEDs in the corresponding wavelength regions. The results deepen the understanding of regulating energetic disorders in perovskite materials via molecular engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2024

Properties of a fading AGN from SDSS-IV MaNGA

ABSTRACT We identify a fading AGN SDSS J220141.64+115124.3 from the internal Product Launch-11 (MPL-11) in Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. The central region with a projected radius of $\sim$2.4 kpc is characterized as LINER-like line ratios while the outskirts extended to $\sim$15 kpc show Seyfert-like line ratios. The ${\rm{[O {\small III}]}}$$\lambda$5007 luminosity of the Seyfert regions is a factor of 37 (2) higher than the LINER regions without (with) dust attenuation correction, suggesting that the AGN activity decreases at least $\sim$8 $\times$ 10$^3$ yr ($\sim$2.4 kpc/light-speed) ago. We model the emission line spectra in the central region with double Gaussian components (a narrow core and a broad wing) and analyse the properties of each component. The narrow core component mostly co-rotates with the stellar disc, whereas the broad wing component with a median of the velocity dispersion $\sim$300 km s$^{-1}$ is related to a wind outflow. The kinematic position angle (PA) of the ionized gas shows an $\sim 20^{\circ }$ twist from the galaxy centre to 1.5 effective radius. The median of the PA difference between the gas and stellar components is as large as $\sim 50^{\circ }$ within 0.4 effective radius. The tidal feature in DESI image and star–gas misalignment suggest this galaxy is a merger remnant. Combining all these observational results as well as public available X-ray and MIR luminosities, we confirm this is a fading AGN, the merger process kick-started the central engine to quasar phase which ionized gas composed of tidal debris, and now the activity of the central black hole decreases. The discontinuity in ${\rm{[O {\small III}]}}$$\lambda$5007 flux and EQW maps is due to multiple AGN outbursts triggered by merger remnant gas inflows.

Mo, Hao (ORCID:0000000234430768)↗
DOE OSTI2022

High-throughput investigation of structural evolution upon solid-state in Cu–Cr–Co combinatorial multilayer thin-film

Cu-Cr-Co combinatorial multilayer thin-films were prepared by a high-throughput ion beam sputtering system. Based on the thickness ratio among the individual nanoscale monolayers (Cu, Cr, Co), the resulting stoichiometry covered the entire phase diagram. The chemical composition and structure of Cu-Cr-Co combinatorial chip upon solid-state reaction were studied by lab-based micro-X-ray fluorescence (mu-XRF) and high-throughput synchrotron X-ray diffraction (XRD), respectively. A composition-structure map for Cu-Cr-Co combinatorial chip was developed through automated data analysis employing hierarchical clustering techniques. The structural evolution of Cu-Cr-Co combinatorial chip as a function of heat-treatment temperature, time, and modulation period were studied systematically. Furthermore, the effect of the elemental distribution in-depth direction was investigated to gain more insights regarding phase transformation. This work provides an efficient method and new perspectives for the design and optimization of the composition and structure of high-performance thin-films.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The anomaly of the CMB power with the latest Planck data

Abstract The lack of power anomaly is an unexpected feature observed at large angular scales in the maps of Cosmic Microwave Background (CMB) produced by the COBE, WMAP andPlancksatellites. This signature, which consists in a missing of power with respect to that predicted by the ΛCDM model, might hint at a new cosmological phase before the standard inflationary era.The main point of this paper is taking into account the latestPlanckpolarisation data to investigate how the CMB polarisation improves the understanding of this feature. With this aim, we apply to the latestPlanckdata, both PR3 (2018) and PR4 (2020) releases, a new class of estimators capable of evaluating this anomaly by considering temperature and polarisation data both separately and in a jointly way. This is the first time that the PR4 dataset has been used to study this anomaly. To critically evaluate this feature, taking into account the residuals of known systematic effects present in thePlanckdatasets, we analyse the cleaned CMB maps using different combinations of sky masks, harmonic range and binning on the CMB multipoles.Our analysis shows that the estimator based only on temperature data confirms the presence of a lack of power with a lower-tail-probability (LTP), depending on the component separation method, ≤ 0.33% and ≤ 1.76% for PR3 and PR4, respectively. To our knowledge, the LTP≤ 0.33% for the PR3 dataset is the lowest one present in the literature obtained fromPlanck2018 data, considering thePlanckconfidence mask. We find significant differences between these two datasets when polarisation is taken into account most likely due to a different level of systematics. Especially, the analysis with PR3 data, unlike that with PR4, seems to point towards a lack of power at large scales also for polarisation.Moreover, we also show that for the PR3 dataset the inclusion of the subdominant polarisation information provides estimates that are less likely accepted in a ΛCDM cosmological model than the only-temperature analysis over the entire harmonic-range considered. In particular, at ℓ max = 26, we found that no simulation has a value as low as the data for all the pipelines.

Astronomy & Astrophysics↗
DOE OSTI2025

Orbit-averaging and deposition accuracy for runaway electron beams in hybrid kinetic-MHD simulations of the runaway plateau

We develop a new procedure that combines the kinetic orbit runaway electron code (KORC) and the NIMROD extended-magnetohydrodynamic code to simulate runaway electrons (REs) in the post-disruption plateau. KORC integrates guiding-center orbits, with a barycentric-based binary search strategy providing initial guesses for the Newton–Raphson logical-to-physical coordinate inversion, ensuring reliable particle-to-mesh mapping in NIMROD, whose fields remain static for the present study. Samples are drawn in accord with experimental parallel current profiles of RE beams during the plateau phase. Deposition in NIMROD is verified through comparison with a Python-based finite-element code that ensures periodicity in the poloidal direction and continuity at the magnetic axis. Accurate representation of near-axis fields requires finer mesh resolution to prevent under- and overshoots in current density from orbit inaccuracies. Yet, at a fixed particle count, increasing mesh resolution amplifies statistical noise in the deposited fields. An orbit-averaging method accumulates partial current deposits over multiple kinetic steps and reduces the statistical noise with little added computational cost. By coupling kinetic routines from KORC directly into the NIMROD codebase, these developments lay essential groundwork for future self-consistent KORC–NIMROD coupling.

Algorithms and data structure↗
DOE OSTI2026

Coherence-mediated quantum thermometry in a hybrid circuit quantum electrodynamics architecture

Quantum thermometry plays a critical role in the development of low-temperature sensors and quantum information platforms. Here, in this work, we propose and analyze a hybrid circuit quantum electrodynamics architecture in which a superconducting qubit is dispersively coupled to two distinct bosonic modes: one initialized in a weak coherent state as a phase reference and information buffer and the other coupled to a thermal environment. We show that the qubit serves as a sensitive readout of the probe mode, mapping the interplay between thermal and coherent photon-number fluctuations onto measurable dephasing. This coherence-mediated mechanism enables improved sensitivity to thermal energy fluctuations in the sub-millikelvin regime through Ramsey interferometry. We derive analytic expressions for the probe coherence envelope, compute the quantum Fisher information for temperature estimation, and demonstrate numerically that the presence of a coherent reference enhances the qubit's sensitivity to small changes in thermal photon occupancy. Our results establish a coherence-enabled approach to thermometry and provide a scalable platform for future calorimetric sensing in high-energy physics and quantum metrology.

Zhu, Shaojiang [Fermi National Accelerator Laborat↗
DOE OSTI2026

Site-decorated model for unconventional frustrated magnets: Ultranarrow phase crossover and two-dimensional spin reversal transition

Here, the site-decorated Ising model is introduced to advance the understanding and experimental realization of the recently discovered one-dimensional (1D) finite-temperature ultranarrow phase crossover in an external magnetic field, while mitigating the geometric complexities of traditional bond-decorated models. The unconventional frustration and physics are clarified by exactly mapping the 1D site-decorated Ising model in a magnetic field onto a zero-field bond-decorated 𝐽 1 −𝐽 2 Ising model with conventional geometrical frustration. Furthermore, although higher-dimensional Ising models in an external field remain unsolved exactly, an exact solution for a spin-reversal transition—driven by an exotic, hidden half-ice, half-fire state induced by site decoration—is derived. This transition, triggered by a slight variation in temperature or magnetic field—without changing its direction—even in the weak-field limit, offers a promising route toward energy-efficient applications such as data storage and processing. The results suggest that site decoration offers an avenue for materials and device design, particularly in systems such as mixed 𝑑−𝑓 compounds, optical lattices, and neural networks, calling for further studies with site-decorated Heisenberg models. In addition, the site-decorated model offers a rigorous test ground for artificial intelligence (AI) in science, as the analytic derivation of the present results was not only validated but also improved by a general-purpose large language model, inspiring the use of AI as scientific discoverer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Exotic field theories for (hybrid) fracton phases from imposing constraints in foliated field theory

Fracton phases of matter are gapped phases of matter that, by dint of their sensitivity to UV data, demand non-standard quantum field theories to describe them in the IR. Two such approaches are foliated quantum theory and exotic field theory. In this paper, we explicitly construct a map from one to the other and work out several examples. In particular, we recover the equivalence between the foliated and exotic fractonic BF theories recently demonstrated at the level of operator correspondence. We also demonstrate the equivalence of toric code layers and the anisotropic model with lineons and planons to the foliated BF theory with one and two foliations, respectively. Finally, we derive new exotic field theories that provide simple descriptions of hybrid fracton phases from foliated field theries known to do so. Our results both provide new examples of exotic field theories and pave the way toward their systematic construction from foliated field theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

White Laue and powder diffraction studies to reveal mechanisms of HCP-to-BCC phase transformation in single crystals of Mg under high pressure

Mechanisms of hexagonal close-packed (HCP) to body-centered cubic (BCC) phase transformation in Mg single crystals are observed using a combination of polychromatic beam Laue diffraction and monochromatic beam powder diffraction techniques under quasi-hydrostatic pressures of up to 58 ± 2 GPa at ambient temperature. Although experiments were performed with both He and Ne pressure media, crystals inevitably undergo plastic deformation upon loading to 40–44 GPa. The plasticity is accommodated by dislocation glide causing local misorientations of up to 1°–2°. The selected crystals are tracked by mapping Laue diffraction spots up to the onset of the HCP to BCC transformation, which is determined to be at a pressure of 56.6 ± 2 GPa. Intensity of the Laue reflections from HCP crystals rapidly decrease but no reflections from crystalline BCC phase are observed with a further increase of pressure. Nevertheless, the powder diffraction shows the formation of 110 BCC peak at 56.6 GPa. The peak intensity increases at 59.7 GPa. Upon the full transformation, a powder-like BCC aggregate is formed revealing the destructive nature of the HCP to BCC transformation in single crystals of Mg.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Intrinsic Li Distribution in Layered Transition-Metal Oxides Using Low-Dose Scanning Transmission Electron Microscopy and Spectroscopy

Understanding Li distribution in layered lithium transition-metal oxide (LiTMO) cathodes in Li-ion batteries has been a major challenge at the atomic scale and nanoscale. Li is extremely difficult to study by transmission electron microscopy (TEM) because the high-energy electrons impart significant energy and cause massive migration. Here, we directly map the intrinsic spatial distribution and bonding of Li in LiNiO 2 -layered cathode materials using low-dose and low-loss electron energy loss spectroscopy (EELS). EELS spectra of the Li–K edge are measured simultaneously with O–K and Ni–L, M 3,2 edges from layered, cation-mixed, and rock-salt phases and directly matched with atomic-resolution scanning TEM images to correlate the changes in peak intensities and positions to the stoichiometry changes with continual loss of Li and O. Changes in the Li content in the LiNiO 2 particles as a function of electron beam dose are studied by sequential Li spectroscopic mapping. We show that the “intrinsic” Li distribution can be observed using a total dose of less than ~1.5 × 10 8 e – nm –2 at an accelerating voltage of 80 kV. The method of nanoscale mapping of Li distribution introduced in this study is applicable to high-Ni LiTMO cathode materials (>89% of Ni) as well as LiNiO 2 . Further study on the extra peaks of the Li–K edge reveals that the peak at ~59 eV is from the Li ions intercalated in between NiO 2 layers barely interacting with each other with less Li K shell electrons pulled to the L shell electrons in NiO 2 . Furthermore, the results shown here provide improved low-loss TEM characterization approaches that can be used to understand the intrinsic fundamental behaviors in Li-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Surrogate Model Integration with MOOSE XFEM for Creep Crack Growth

Ferritic-martensitic steels are key structural materials for advanced reactors but experience time-dependent deformation and damage under prolonged high temperature and irradiation, leading to creep-driven crack initiation and growth. High-fidelity models—crystal plasticity with irradiation mechanisms, phase-field for microstructural evolution, and continuum-damage viscoplasticity—capture the underlying physics but are too computationally intensive for broad design-space exploration and uncertainty quantification. This milestone advances a scalable alternative by integrating a microstructure-sensitive surrogate creep model into the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework and extending it to fracture via the extended finite element method (XFEM). The surrogate model, developed with collaborators at Sandia and Los Alamos National Laboratories, maps relevant microstructural descriptors to the viscoplastic response of HT9. We embed this surrogate within a coupled deformation-damage workflow in MOOSE/XFEM to simulate creep-driven crack initiation and propagation. Implementation enhancements include updates to the material interface, a plastic correction phase involving microstructure evolution, and fracture criteria to ensure numerical robustness and compatibility with the surrogate structure. Demonstrations on canonical creep benchmarks spanning uniaxial and multiaxial states show that the surrogate reproduces key trends of high-fidelity models while substantially reducing computational cost. The resulting capability bridges physics fidelity and performance, providing a practical path to a predictive, microstructure-aware assessment of creep and fracture in reactor materials.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Genuine k -partite correlations and entanglement in the ground state of the Dicke model for interacting qubits

Here, in this work, we calculate and study correlations of the Dicke model in the presence of qubit–qubit interaction. Whereas the analysis of correlations among its subsystems is essential for the understanding of corresponding critical phenomena and for performing quantum information tasks, the majority of correlation measures are restricted to bipartitions due to the inherent challenges associated with handling multiple partitions. To circunvent this we employ the calculation of Genuine Multipartite Correlations (GMC) based on the invariance of our model under particle permutation. We then quantify the correlations within each subpart of the system, as well as the percentage contribution of each GMC of order $k$, highlighting the many-body behaviors for different regimes of parameters. Additionally, we show that GMC signal both first- and second-order quantum phase transitions present in the model. Furthermore, as GMC encompasses both classical and quantum correlations, we employ Quantum Fisher Information (QFI) to detect genuine multipartite entanglement. Ultimately, we map the Dicke model with interacting qubits to spin in solids interacting with a quantum field of magnons, thus demonstrating a potential experimental realization of this model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Phonon excitations in Eu 2 Ir 2 O 7 probed by inelastic x-ray scattering

The study of phonon dynamics and its interplay with magnetic ordering is crucial for understanding the unique quantum phases in the pyrochlore iridates. Here, through inelastic x-ray scattering on a single crystal sample of the pyrochlore iridate Eu 2 Ir 2 O 7 , we map out the phonon excitation spectra in Eu 2 Ir 2 O 7 and compare them with the theoretical phonon spectra calculated using the density functional theory. Further, possible phonon renormalization across the magnetic long-range order transition is observed in our experiments, which is consistent with the results of the previous Raman scattering experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Crustal and uppermost mantle structure of Cape Verde from ambient noise tomography

SUMMARY We present a seismic ambient noise tomography of the Cape Verde archipelago, located in the Atlantic Ocean, approximately 600 km west of Senegal. We used 38 seismic broad-band stations that continuously recorded for 10 months, in order to construct the first 3-D model of Sv-wave velocities for the crust and uppermost mantle beneath the Cape Verde region. We started by computing phase cross-correlations for vertical component recordings using all possible inter-island station pairs. Next, a time–frequency phase-weighted stack was applied to obtain robust Rayleigh-wave group-velocity dispersion curves in the period band between 10 and 24 s. Group-velocity maps at different periods are obtained by inverting the dispersion curves. We then inverted the group-velocity maps to obtain the 3-D shear wave velocity structure of the crust and uppermost mantle beneath Cape Verde. The final 3-D model extends from 8 km down to 23 km and has a lateral resolution of about 50 km. The crust in the southwestern sector, encompassing Fogo, presents lower S-wave velocities that may be caused by the presence of melt pockets and/or hydrothermal fluids circulation. The uppermost mantle beneath the northwestern sector is characterized by higher S-wave velocities in agreement with previous results obtained from Ps and Sp receiver functions. Those high-velocity anomalies can reflect non-altered crust or remnants of magma chambers or solidified basaltic intrusions, which fed the volcanism in these islands. Our maps revealed the presence of crustal underplating across the entire archipelago, yet stronger beneath the groups Santo Antão—São Vicente—São Nicolau and Fogo—Santiago—Maio.

Carvalho, J. (ORCID:0000000310778994)↗
DOE OSTI2024

Electronic Structure, Spectroscopy and Correlation Effects in Novel Materials

This project was targeted on electronic structure, spectroscopic studies, and correlation effects in a variety of novel materials of great current interest. Spectroscopies resolved highly in momentum, energy or spatial dimensions are playing a key role in unraveling the nature of the ground state and excitation properties in wide classes of novel materials. The seminal insights thus obtained are of critical importance not only for answering some of the fundamental questions facing condensed matter physics and materials science today, but also for understanding and thus helping to design and develop new materials with desirable properties, which will continue to be the key to the survival of mankind and its energy needs as a technological society long into the future. However, spectroscopies do not provide a direct map of electronic states, but act as a very complex ‘filter’ or ‘mapping’ of the underlying spectrum. This connection between the electronic states and measured spectra—called the ‘matrix element effect’—is in general an extremely complex function of the phase space of the experiment (e.g. energy/polarization of photons in photoemission), presenting both a challenge and an opportunity. So motivated, this project pursued techniques for realistic treatment of electronic spectra of a wide variety of materials, which served as a prelude to formulating and implementing methodologies for making direct connection with various spectroscopies such as ARPES, STS/STM, and inelastic light scattering. Specific systems are topological materials, including 2D ultrathin films beyond graphene, novel superconductors, and nanocrystals, among others. Our goal was to exploit the strengths of various spectroscopies to piece together the most complete picture of electronic states in systems of current interest, enabling direct and sharpened confrontations with theoretical models, and also to help advance the reach of various spectroscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Distributed Mafic Rock Resources for Carbon Mineralization in Arizona

Ex-situ carbon mineralization is a process by which CO2 is reacted with alkaline silicate minerals and rocks to produce stable carbonate materials, which can be used for other industrial processes. Arizona, U.S.A., hosts abundant surficial mafic rocks in three young volcanic fields, Geronimo-San Bernardino, San Francisco, and Springerville, and other distributed locations throughout the state. We created a Mafic Rock Resource Inventory (MRRI) that categorizes geochemical, physical, and textural characteristics of a diverse suite of surficial mafic rock samples and provide a benchmark reaction dataset parameterizing the temperature, pressure, and pH conditions best suited ex-situ mineralization in different rock types. MRRI data is publicly available online via a map-viewer. We establish two reaction condition sets, varied in temperature, pressure, and pH, where crystal-rich and glassy rocks reach maximum reaction extent and different carbonate phases are formed. Systematic ex-situ mineralization experiments on 21 diverse rock types show trends in geochemical, mineralogical, and reactivity behavior and establish maximum effective capture capacity. From this, scoria cones in three Arizona volcanic fields have a ~62 Gt effective CO₂ storage capacity with one of the fields having a ~42 Gt storage capacity in lava flows. Reactivity results have applications to alkaline mafic rock resources exposed globally, including producing additional effective storage capacity estimates and scaled commercialization of mafic rock ex-situ mineralization, should reaction extents be improved through advances in mineralization techniques. MRRI data were used to create a Direct Air Capture to Mineralization (DACM) systems model, technoeconomic analysis, and life-cycle assessment. These documents are presented as three appendices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Reconstruction of Six-Dimensional Phase Space

A phase space is a mathematical representation of all possible physical states of a system. Particle beams at Fermilab exist within a six-dimensional (6D) phase space defined by three positional components, (x, y, z) and three momentum components, (px, py, pz). To reconstruct this space implies taking measurement data from detectors and mapping out particle behavior using computational methods. The beam detectors, however, are only able to detect spatial distribution among the events of the beam, therefore being limited to positional data. Also, due to the vast number of events in a particle beam, it is extremely difficult to analyze and differentiate every single one’s behavior. However, with Machine Learning (ML), which can distinguish between patterns and map out particle behavior more efficiently. We first used the particle beam software, G4beamline, to simulate a 10,000-event muon beam, adjusting parameters such as initial momentum magnitude (p¬0) and virtual detector position. Using ten virtual detectors, we analyzed p0 values such that minimum 9,990 events were analyzed by every detector. We then input the data from these beam simulations to a C++ program, that randomly selects 100 events, and creates a 2D histogram based on spatial distribution, detector position, and event intensity. This process is repeated 100 times to create 100 histograms per p0 value. These images were then input to a modified ResNet18 Convolutional Neural Network (CNN) for training, and to predict p0 from some unseen set of histograms. The model was accurate when trained on momentum increments of 5 MeV/c and provided with denser training samples around highly variable test values. These results displayed machine learning being able to accurately predict p0 from being trained on different particle behaviors.

Shirlee, Jermain [Fermilab]↗