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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

Observation of seasonal variations of the flux of high-energy atmospheric neutrinos with IceCube

Atmospheric muon neutrinos are produced by meson decays in cosmic-ray-induced air showers. The flux depends on meteorological quantities such as the air temperature, which affects the density of air. Competition between decay and re-interaction of those mesons in the first particle production generations gives rise to a higher neutrino flux when the air density in the stratosphere is lower, corresponding to a higher temperature. A measurement of a temperature dependence of the atmospheric νμ flux provides a novel method for constraining hadronic interaction models of air showers. It is particularly sensitive to the production of kaons. Studying this temperature dependence for the first time requires a large sample of high-energy neutrinos as well as a detailed understanding of atmospheric properties. We report the significant (> 10 σ) observation of a correlation between the rate of more than 260,000 neutrinos, detected by IceCube between 2012 and 2018, and atmospheric tem peratures of the stratosphere, measured by the Atmospheric Infrared Sounder (AIRS) instrument aboard NASA’s AQUA satellite. For the observed 10% seasonal change of effective atmospheric temperature we measure a 3.5(3)% change in the muon neutrino flux. This observed correlation deviates by about 2-3 standard deviations from the expected correla tion of 4.3% as obtained from theoretical predictions under the assumption of various hadronic interaction models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Measurement and interpretation of same-sign W boson pair production in association with two jets in $pp$ collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

This paper presents the measurement of fiducial and differential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W ± W ± jj) using 139 fb –1 of proton-proton collision data recorded at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity difference. The measured fiducial cross sections for electroweak and inclusive W ± W ± jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.) fb and 3.38 ± 0.22 (stat.) ± 0.19 (syst.) fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confidence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H ±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H ±± mass near 450 GeV, with a global significance of 2.5 standard deviations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Fast-ion transport in quasisymmetric equilibria in the presence of a resonant Alfvénic perturbation

Significant progress has been made in designing magnetic fields that provide excellent confinement of the guiding-centre trajectories of alpha particles using quasisymmetry (QS). Given the reduction in this transport channel, we assess the impact of resonant Alfvén eigenmodes (AEs) on the guiding-centre motion. The AE amplitudes are chosen to be consistent with experimental measurements and large-scale simulations. We evaluate the drift resonance condition, phase-space island width and island overlap criterion for quasisymmetric configurations. Kinetic Poincaré plots elucidate features of the transport, including stiff transport above a critical perturbation amplitude. Our analysis highlights key departures from the AE-driven transport in tokamaks, such as the avoidance of phase-space island overlap in quasihelical configurations and the enhanced transport due to wide phase-space islands in low magnetic shear configurations. In configurations that are closer to QS, with QS deviations $\delta B/B_0 \lesssim 10^{-3}$ , the transport is primarily driven by the AE, while configurations that are further from QS, $\delta B/B_0 \sim 10^{-2}$ , experience significant transport due to the QS-breaking fields in addition to the AE.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Measurement of simplified template cross sections of the Higgs boson produced in association with W or Z bosons in the H → b b ¯ decay channel in proton-proton collisions at s = 13 TeV

Differential cross sections are measured for the standard model Higgs boson produced in association with vector bosons (W, Z) and decaying to a pair of b quarks. Measurements are performed within the framework of the simplified template cross sections. The analysis relies on the leptonic decays of the W and Z bosons, resulting in final states with 0, 1, or 2 electrons or muons. The Higgs boson candidates are either reconstructed from pairs of resolved b-tagged jets, or from single large-radius jets containing the particles arising from two b quarks. Proton-proton collision data at $\sqrt{s}$ =13 TeV, collected by the CMS experiment in 2016–2018 and corresponding to a total integrated luminosity of 138 fb -1 , are analyzed. The inclusive signal strength, defined as the product of the observed production cross section and branching fraction relative to the standard model expectation, combining all analysis categories, is found to be μ = $1.15^{+0.22}_{-0.20}$. This corresponds to an observed (expected) significance of 6.3 (5.6) standard deviations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Search for doubly and singly charged Higgs bosons decaying into vector bosons in multi-lepton final states with the ATLAS detector using proton-proton collisions at $\sqrt{s}$ = 13 TeV

A search for charged Higgs bosons decaying into W ± W ± or W ± Z bosons is performed, involving experimental signatures with two leptons of the same charge, or three or four leptons with a variety of charge combinations, missing transverse momentum and jets. A data sample of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018 is used. The data correspond to a total integrated luminosity of 139 fb -1 . The search is guided by a type-II seesaw model that extends the scalar sector of the Standard Model with a scalar triplet, leading to a phenomenology that includes doubly and singly charged Higgs bosons. Two scenarios are explored, corresponding to the pair production of doubly charged H ±± bosons, or the associated production of a doubly charged H ±± boson and a singly charged H ± boson. No significant deviations from the Standard Model predictions are observed. H ±± bosons are excluded at 95% confidence level up to 350 GeV and 230 GeV for the pair and associated production modes, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A versatile machine learning workflow for high-throughput analysis of supported metal catalyst particles

Accurate and efficient characterization of nanoparticles (NPs), particularly regarding particle size distribution, is essential for advancing our understanding of their structure-property relationship and facilitating their design for various applications. In this study, we introduce a novel two-stage artificial intelligence (AI)-driven workflow for NP analysis that leverages prompt engineering techniques from state-of-the-art single-stage object detection and large-scale vision transformer (ViT) architectures. This methodology is applied to transmission electron microscopy (TEM) and scanning TEM (STEM) images of heterogeneous catalysts, enabling high-resolution, high-throughput analysis of particle size distributions for supported metal catalyst NPs. The model's performance in detecting and segmenting NPs is validated across diverse heterogeneous catalyst systems, including various metals (Ru, Cu, PtCo, and Pt), supports (silica (SiO 2 ), γ-alumina (γ-Al 2 O 3 ), and carbon black), and particle diameter size distributions with mean and standard deviations ranging from 1.6 ± 0.2 nm to 9.7 ± 4.6 nm. The proposed machine learning (ML) methodology achieved an average F1 overlap score of 0.91 ± 0.01 and demonstrated the ability to disentangle overlapping NPs anchored on catalytic support materials. The segmentation accuracy is further validated using the Hausdorff distance and robust Hausdorff distance metrics, with the 90th percent of the robust Hausdorff distance showing errors within 0.4 ± 0.1 nm to 1.4 ± 0.6 nm. In conclusion, our AI-assisted NP analysis workflow demonstrates robust generalization across diverse datasets and can be readily applied to similar NP segmentation tasks without requiring costly model retraining.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Fine-Scale Variability of Observed and Simulated Surface Albedo Over the Southern Great Plains

Surface albedo can be highly variable in both space and time. The Department of Energy’s Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field study provides a unique opportunity to characterize the variability over the Southern Great Plains of the United States using integrated tower, aircraft, and satellite observations of the surface albedo and Normalized Difference Vegetation Index (NDVI). The primary advantage of the aircraft and satellite observations is the ability to examine the spatial distribution of surface albedo and NDVI over a large area, while the tower measurements have the ability to examine both diurnal and day-to-day variability at a single location. In general, consistency was found between both the broadband (BB) albedo and NDVI measured from the surface, air and space. There was a small increase from 0.186 to 0.194 in the aircraft BB surface albedo between May and September (about 4% change), while the MODIS black-sky BB surface albedo increased from 0.151 to 0.166 over the same period (about 10% change) while the standard deviations in the aircraft and MODIS BB albedo were similar. The largest seasonal differences in both the aircraft BB albedo and NDVI were found for areas with winter wheat or forest, while areas with pasture or grasses showed a smaller seasonal diversity. The Weather Research and Forecasting (WRF) model was used to simulate the BB surface albedo. In comparison with the aircraft and satellite observations, the WRF-simulated BB surface albedo had no seasonal change and a much narrower distribution.

Berg, Larry K.↗
DOE OSTI2024

Establishing ZIF‐8 as a reference material for hydrogen cryoadsorption: An interlaboratory study

Abstract Hydrogen storage by cryoadsorption on porous materials has the advantages of low material cost, safety, fast kinetics, and high cyclic stability. The further development of this technology requires reliable data on the H 2 uptake of the adsorbents, however, even for activated carbons the values between different laboratories show sometimes large discrepancies. So far no reference material for hydrogen cryoadsorption is available. The metal‐organic framework ZIF‐8 is an ideal material possessing high thermal, chemical, and mechanical stability that reduces degradation during handling and activation. Here, we distributed ZIF‐8 pellets synthesized by extrusion to 9 laboratories equipped with 15 different experimental setups including gravimetric and volumetric analyzers. The gravimetric H 2 uptake of the pellets was measured at 77 K and up to 100 bar showing a high reproducibility between the different laboratories, with a small relative standard deviation of 3–4 % between pressures of 10–100 bar. The effect of operating variables like the amount of sample or analysis temperature was evaluated, remarking the calibration of devices and other correction procedures as the most significant deviation sources. Overall, the reproducible hydrogen cryoadsorption measurements indicate the robustness of the ZIF‐8 pellets, which we want to propose as a reference material.

08 HYDROGEN↗
DOE OSTI2022

Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18–72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18–73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I 2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen’s d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Verification of an improved equation-free projective integration method for neoclassical plasma-profile evolution in tokamak geometry

A brute-force, long-time gyrokinetic simulation of plasma profile evolution in magnetic fusion devices is not desirable due to large computational resource requirements and a possible accumulation of numerical error. The equation-free projective integration method of Keverekidis et al. [Commun. Math. Sci. 1(4), 715–762 (2003)] is one of the outstanding candidates in projecting micro-scale simulations to a longer timescale. However, its application to tokamak plasma has not been fruitful due to the appearance of spurious transient oscillations in the lifting process, which are present when the kinetic simulations are initialized with a simplified model distribution function and which make the kinetic simulations to deviate from the desired paths. In this work, a kinetically informed lifting algorithm is added to the equation-free projective integration method, which is then verified in the electrostatic gyrokinetic particle-in-cell code XGCa [R. Hager and C. S. Chang, Phys. Plasmas 23, 042503 (2016)] for a neoclassical ion heat transport problem with adiabatic electrons. This new lifting operator is demonstrated to control spurious transients, enabling an over four-times reduction in the overall computing time in the time-evolution of the ion temperature profile in an axisymmetric toroidal plasma. Further reduction in the computing time is found to be limited due to the stability properties of the linear least squares projective integrator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗
DOE OSTI2026

Scalable Layer-by-Layer Electrospray-Assisted Interfacial Polymerization: Enabling Large-Area Polyamide Membrane Fabrication

Layer-by-layer electrospray-assisted interfacial polymerization (LBL-EAIP) has recently been proposed as an alternative approach for fabricating polyamide membranes with precisely controlled thickness and polymerization degree, showing great potential for reverse osmosis (RO) membrane synthesis. In this article, we report a scale-up strategy for LBL-EAIP to enable its practical application in RO membrane manufacturing. A multi-jet electrospray apparatus was developed, and the device configuration and process parameters were carefully adjusted to produce polyamide-on-polyethersulfone thin film composite (TFC) membranes with consistently high salt rejection and water permeance across the membrane area. Specifically, an average 97.1% NaCl rejection from a 2000 ppm NaCl feed was achieved with an area-to-area deviation of 1%, along with a deionized water permeance of 0.90 ± 0.11 LMH/bar at 15 bar feed pressure. In addition, a Fourier-transform infrared spectroscopy (FTIR)-based analytical method was developed for semi-quantitative assessment of membrane thickness and compositional uniformity, enabling rapid mapping of film microstructure and chemical variations. This work provides a pathway to scale up LBL-EAIP technology, bridging the gap between laboratory-scale innovation and industrial-scale manufacturing.

Feng, Yue (ORCID:0000000221343980)↗
DOE OSTI2024

Interaction-enhanced nesting in spin-fermion and Fermi-Hubbard models

The spin-fermion (SF) model postulates that the dominant coupling between low-energy fermions in near critical metals is mediated by collective spin fluctuations (paramagnons) peaked at the Néel wave vector, Q N , connecting hot spots on opposite sides of the Fermi surface. It has been argued that strong correlations at hot spots lead to a Fermi surface deformation (FSD) featuring flat regions and increased nesting. This conjecture was confirmed in the perturbative self-consistent calculations when the paramagnon propagator dependence on momentum deviation from Q N is given by χ − 1 ∝ | Δ q | . Using diagrammatic Monte Carlo (diagMC) technique we show that such a dependence holds only at temperatures orders of magnitude smaller than any other energy scale in the problem, indicating that a different mechanism may be at play. Instead, we find that a χ − 1 ∝ | Δ q | 2 dependence yields a robust finite- T scenario for achieving FSD. To link phenomenological and microscopic descriptions, we applied the connected determinant diagMC method to the ( t − t ′ ) Hubbard model and found that at large U / t > 5.5 before the formation of electron and hole pockets (i) the FSD defined as a maximum of the spectral function is not very pronounced; instead, it is the lines of zeros of the renormalized dispersion relation that deforms toward nesting, and (ii) the static spin susceptibility is well described by χ − 1 ∝ | Δ q | 2 . Flat FS regions yield a nontrivial scenario for realizing a non-Fermi liquid state. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Search for pair-produced vector-like top and bottom partners in events with large missing transverse momentum in $pp$ collisions with the ATLAS detector

A search for pair-produced vector-like quarks using events with exactly one lepton ($e$ or $μ$), at least four jets including at least one $b$-tagged jet, and large missing transverse momentum is presented. Data from proton–proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV, recorded by the ATLAS detector at the LHC from 2015 to 2018 and corresponding to an integrated luminosity of 139 fb –1 , are analysed. Vector-like partners $T$ and $B$ of the top and bottom quarks are considered, as is a vector-like $X$ with charge +5/3, assuming their decay into a $W$, $Z$, or Higgs boson and a third-generation quark. No significant deviations from the Standard Model expectation are observed. Upper limits on the production cross-section of $T$ and $B$ quark pairs as a function of their mass are derived for various decay branching ratio scenarios. The strongest lower limits on the masses are 1.59 assuming mass-degenerate vector-like quarks and branching ratios corresponding to the weak-isospin doublet model, and 1.47 TeV (1.46 TeV) for exclusive $T$→$Zt$ ($B/X$→$Wt$) decays. In addition, lower limits on the $T$ and $B$ quark masses are derived for all possible branching ratios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurement of single top-quark production in the s-channel in proton–proton collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A measurement of single top-quark production in the s-channel is performed in proton–proton collisions at a centre-of-mass energy of 13 TeV with the ATLAS detector at the CERN Large Hadron Collider. The dataset corresponds to an integrated luminosity of 139 fb –1 . The analysis is performed on events with an electron or muon, missing transverse momentum and exactly two $b$-tagged jets in the final state. A discriminant based on matrix element calculations is used to separate single-top-quark s-channel events from the main background contributions, which are top-quark pair production and $W$-boson production in association with jets. The observed (expected) signal significance over the background-only hypothesis is 3.3 (3.9) standard deviations, and the measured cross-section is $σ$ = ${8.2}_{-2.9}^{+3.5}$ pb, consistent with the Standard Model prediction of $σ^{SM}$ = ${10.32}_{–0.36}^{+0.40}$ pb.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

QSO photometric redshifts using machine learning and neural networks

ABSTRACT The scientific value of the next generation of large continuum surveys would be greatly increased if the redshifts of the newly detected sources could be rapidly and reliably estimated. Given the observational expense of obtaining spectroscopic redshifts for the large number of new detections expected, there has been substantial recent work on using machine learning techniques to obtain photometric redshifts. Here, we compare the accuracy of the predicted photometric redshifts obtained from deep learning (DL) with the k-nearest neighbour (kNN) and the decision tree regression (DTR) algorithms. We find using a combination of near-infrared, visible, and ultraviolet magnitudes, trained upon a sample of Sloan Digital Sky Survey quasi-stellar objects, that the kNN and DL algorithms produce the best self-validation result with a standard deviation of σΔz = 0.24 (σΔz(norm) = 0.11). Testing on various subsamples, we find that the DL algorithm generally has lower values of σΔz, in addition to exhibiting a better performance in other measures. Our DL method, which uses an easy to implement off-the-shelf algorithm with neither filtering nor removal of outliers, performs similarly to other, more complex, algorithms, resulting in an accuracy of Δz < 0.1 up to z ∼ 2.5. Applying the DL algorithm trained on our 70 000 strong sample to other independent (radio-selected) data sets, we find σΔz ≤ 0.36 (σΔz(norm) ≤ 0.17) over a wide range of radio flux densities. This indicates much potential in using this method to determine photometric redshifts of quasars detected with the Square Kilometre Array.

Curran, S. J.↗
DOE OSTI2023

The Forward Physics Facility at the High-Luminosity LHC

High energy collisions at the High-Luminosity Large Hadron Collider (LHC) produce a large number of particles along the beam collision axis, outside of the acceptance of existing LHC experiments. The proposed Forward Physics Facility (FPF), to be located several hundred meters from the ATLAS interaction point and shielded by concrete and rock, will host a suite of experiments to probe standard model (SM) processes and search for physics beyond the standard model (BSM). In this report, we review the status of the civil engineering plans and the experiments to explore the diverse physics signals that can be uniquely probed in the forward region. FPF experiments will be sensitive to a broad range of BSM physics through searches for new particle scattering or decay signatures and deviations from SM expectations in high statistics analyses with TeV neutrinos in this low-background environment. High statistics neutrino detection will also provide valuable data for fundamental topics in perturbative and non-perturbative QCD and in weak interactions. Experiments at the FPF will enable synergies between forward particle production at the LHC and astroparticle physics to be exploited. We report here on these physics topics, on infrastructure, detector, and simulation studies, and on future directions to realize the FPF’s physics potential.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Nonideal mixing effects in warm dense matter studied with first-principles computer simulations

Here, we study nonideal mixing effects in the regime of warm dense matter (WDM) by computing the shock Hugoniot curves of BN, MgO, and MgSiO 3 . First, we derive these curves from the equations of state (EOS) of the fully interacting systems, which were obtained using a combination of path integral Monte Carlo calculations at high temperature and density functional molecular dynamics simulations at lower temperatures. We then use the ideal mixing approximation at constant pressure and temperature to rederive these Hugoniot curves from the EOS tables of the individual elements. We find that the linear mixing approximation works remarkably well at temperatures above ~2 × 10 5 K, where the shock compression ratio exceeds ~3.2. The shape of the Hugoniot curve of each compound is well reproduced. Regions of increased shock compression, which emerge because of the ionization of L and K shell electrons, are well represented, and the maximum compression ratio of the Hugoniot curves is reproduced with high precision. Some deviations are seen near the onset of the L shell ionization regime, where ionization equilibrium in the fully interacting system cannot be well reproduced by the ideal mixing approximation. This approximation also breaks down at lower temperatures, where chemical bonds play an increasingly important role. However, the results imply that the equilibrium properties of binary and ternary mixtures in the regime of WDM can be derived from the EOS tables of the individual elements. This significantly simplifies the characterization of binary and ternary mixtures in the WDM and plasma phases, which otherwise requires large numbers of more computationally expensive first-principles computer simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗