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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

EvoNet: A phylogenomic and systems biology approach to identify genes underlying plant survival in marginal, low‐N soils

The DOE‐BER “EvoNet” project investigates the genetic and molecular basis of plant resilience in extreme environments. We do this by identifying key genes that enable “extreme survivor” species to thrive in the nitrogen-poor soils of Chile’s hyper-arid Atacama Desert. Our collections focus on 32 Atacama extremophile species, including seven grass species with potential biofuel applications. To identify genes-of-importance to survival we compared genomic and transcriptomic profiles of extremophile species that thrive in the Atacama to those of closely related “sister” species from nitrogen-rich arid and mesic regions of California. Deep RNA sequencing and de novo transcriptome assembly across these triplet species sets supported a phylogenomic framework for identifying positively selected genes associated with adaptive divergence. Our integrative analysis combined ecological and environmental data, metagenomics, evolutionary and systems biology, and metabolomics. This enabled us to create an unprecedented framework for systematically understanding how non-model plants have adapted to survive in extreme conditions. Our resulting database of positively selected ortholog groups in the extremophile plants offers promising targets for engineering crop and biofuel species with enhanced resilience to drought and extreme weather. Additionally, our newest dataset explores and exploits a complementary metabolomic approach. This new aspect provides innovative strategies to manipulate plant cell metabolism, further supporting efforts to improve agricultural productivity in the face of extreme climates. Importantly, our combined evolutionary- and metabolomic-based strategies focused on convergent patterns of adaptation, providing a genetic and metabolomic toolkit for improving crop and biofuel resilience across diverse plant species. Finally, our novel exploration of ecological and evolutionary dynamics delivered to the community a phylogenomic computational pipeline called “PhyloGeneious.” Our continued adaptations of this pipeline are publicly available to expedite evolutionary genomic research for future scientific discoveries. In total, our DOE-BER has provided genomic, metabolomic, and computational strategies to understand how extremophile plants provide evolutionary and physiological targets for improving agricultural and biofuel production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Active operator learning with predictive uncertainty quantification for partial differential equations

With the increased prevalence of neural operators being used to provide rapid solutions to partial differential equations (PDEs), understanding the accuracy of model predictions and the associated error levels is necessary for deploying reliable surrogate models in scientific applications. Existing uncertainty quantification (UQ) frameworks employ ensembles or Bayesian methods, which can incur substantial computational costs during both training and inference. Here, we propose a lightweight predictive UQ method tailored for Deep operator networks (DeepONets) that also generalizes to other operator networks. Numerical experiments on linear and nonlinear PDEs demonstrate that the framework’s uncertainty estimates are unbiased and provide accurate out-of-distribution uncertainty predictions with a sufficiently large training dataset. Our framework provides fast inference and uncertainty estimates that can efficiently drive outer-loop analyses that would be prohibitively expensive with conventional solvers. We demonstrate how predictive uncertainties can be used in the context of Bayesian optimization and active learning problems to yield improvements in accuracy and data-efficiency for outer-loop optimization procedures. In the active learning setup, we extend the framework to Fourier Neural Operators (FNO) and describe a generalized method for other operator networks. To enable real-time deployment, we introduce an inference strategy based on precomputed trunk outputs and a sparse placement matrix, reducing evaluation time by more than a factor of five. Our method provides a practical route to uncertainty-aware operator learning in time-sensitive settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The DECADE cosmic shear project IV: cosmological constraints from 107 million galaxies across 5,400 deg$^2$ of the sky

We present cosmological constraints from the Dark Energy Camera All Data Everywhere (DECADE) cosmic shear analysis. This work uses shape measurements for 107 million galaxies measured through Dark Energy Camera (DECam) imaging of $5,\!412$ deg$^2$ of sky that is outside the Dark Energy Survey (DES) footprint. We derive constraints on the cosmological parameters $S_8 = 0.791^{+0.027}_{-0.032}$ and $Ω_{\rm m} =0.269^{+0.034}_{-0.050}$ for the $Λ$CDM model, which are consistent with those from other weak lensing surveys and from the cosmic microwave background. We combine our results with cosmic shear results from DES Y3 at the likelihood level, since the two datasets span independent areas on the sky. The combined measurements, which cover $\approx\! 10,\!000$ deg$^2$, prefer $S_8 = 0.791 \pm 0.023$ and $Ω_{\rm m} = 0.277^{+0.034}_{-0.046}$ under the $Λ$CDM model. These results are the culmination of a series of rigorous studies that characterize and validate the DECADE dataset and the associated analysis methodologies (Anbajagane et. al 2025a,b,c). Overall, the DECADE project demonstrates that the cosmic shear analysis methods employed in Stage-III weak lensing surveys can provide robust cosmological constraints for fairly inhomogeneous datasets. This opens the possibility of using data that have been previously categorized as ``unusable'' for cosmic shear analyses, thereby increasing the statistical power of upcoming weak lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Investigating shock-induced chemical reactions in Ni+Al multilayers: A continuum-based mesoscale approach with Arrhenius kinetics and artificial thermal conduction

A new continuum-based mesoscale modeling approach for shock-induced chemical reactions (SICRs) in Ni+Al multilayers is demonstrated in Sandia’s shock physics hydrocode, CTH. The approach utilizes Arrhenius-type kinetics and artificial thermal conduction. Our work builds upon previous efforts to parameterize equations of state for Ni x Al y [J. Appl. Phys. 137, 075102 (2025)], as well as simulations of inert shocks in realistic 2D microstructures [J. Appl. Phys. 137, 225301 (2025)]. To calibrate the reaction kinetics, pairs of the reaction coordinate, R′, vs time are extracted from the molecular dynamics (MD) literature. Here, the MD-informed kinetics are used to simulate the dynamic evolution of pressure and temperature in 2D mesoscale simulations. Overall, the MD-informed kinetics obtained for planar interfaces are too slow, as initial reaction is not observed on a nanosecond time scale. Even with quasi-periodic shock focusing leading to the formation of so-called “hot-spots,” the hot spots are unable to grow and coalesce using the fitted Arrhenius rate constants. However, by increasing the rate constants by two orders of magnitude, SICRs are observed at a shock pressure near 30 GPa, which is supported by experiments. Consequently, these mesoscale simulations suggest that unresolved shear-based mechanical mixing might possibly account for the discrepancies in kinetic rates, with shock-generated intense perturbations, interfacial vortical flows, and elevated temperatures serving as favorable reaction conditions. Future work will calibrate a shear-dependent reaction rate from the MD simulations with realistic interfaces that are wavy, diffuse, and disordered.

Kittell, David E. [Sandia National Laboratories (S↗
DOE OSTI2025

Structural Evolution of Mixed-Addenda Keggin Polyoxometalate Anions with Atom-by-Atom Substitution

Polyoxometalates (POMs) are molecular metal oxides with distinctive electronic properties that make them promising materials for applications in energy, sensors, and memory devices. One of the most promising methods of tuning the stability, photochromic, redox, and electron-spin properties of POMs is through the substitution of the metal “addenda” atoms that, along with oxygen, constitute their cage-like structures. Because traditional synthesis methods typically produce a distribution of POMs, the isolation and characterization of multimetallic POMs with predetermined stoichiometry remains challenging. The presence of multiple energetically accessible isomers further complicates the experimental characterization and theoretical modeling of multimetallic POMs. Herein, we leverage the distinguishing mass-selection capabilities of ion soft landing to prepare stoichiometrically selected Keggin PMo x W 12-x O 40 3- (x = 0 – 6, 8, 10, and 12) POMs on self-assembled monolayer surfaces free of the solvent molecules and counterions that often confound characterization of complex species at interfaces. The structures of the supported POMs are characterized with atom-by-atom precision using in situ infrared (IR) reflection absorption spectroscopy complemented by detailed density functional theory calculations. Our joint experimental and theoretical results reveal an almost linear shift in the positions of the IR bands towards lower wavenumbers with an increase in the number of lighter molybdenum atoms compared to heavier W atoms in PMoxW 12-x O 40 3- . The theoretical calculations also indicate that numerous isomeric structures may be populated at the experimental conditions and, consequently, contribute to the overall IR spectra. In conclusion, our findings indicate that in addition to the number of substituted addenda atoms and the presence of multiple isomeric structures, interactions with the surface play an important role in determining the IR spectra and structure of supported bimetallic POMs.

Prabhakaran, Venkateshkumar [Pacific Northwest Nat↗
DOE OSTI2025

Cerebellar dysfunction in a mouse model of childhood-onset manganese-induced dystonia parkinsonism

Humans with pathogenic variants of the manganese (Mn) transporter gene SLC39A14 exhibit highly elevated brain Mn concentrations and childhood-onset dystonia-parkinsonism. Here we show that Slc39a14-knockout (KO) mice, a preclinical model of the disease with elevated Mn concentrations in the CB, express deficits in physiological tremor implicating cerebellar (CB) dysfunction. Imaging of intracellular Mn in Purkinje cells (PCs) using synchrotron-based X-ray fluorescence microscopy confirmed highly elevated Mn concentrations in the PCs of Slc39a14-KO mice. To determine biological pathways altered in the CB of Slc39a14-KO mice relative to wildtype (WT), we performed RNA sequencing and discovered significant upregulation of pathways and genes regulating immune response and cell death. To substantiate these findings, we performed quantitative autoradiography of the neuroinflammation biomarker Translocator Protein 18 kDa (TSPO) which was significantly increased in the CB of Slc39a14-KO mice relative to WT. The latter findings were confirmed via immunostaining with the microglial marker Iba-1, revealing widespread microglia activation and clustering in the CB cortex. Immunostaining for cleaved caspase-3 (cCASP3), a marker of apoptosis, showed increased number of PCs with positive immunolabeling for cCASP3 in Slc39a14-KO mice relative to WT. Degeneration of PCs was confirmed by Hematoxylin and Eosin (H&E) staining. Lastly, functional electrophysiological assessment of CB neurocircuitry revealed a marked decrease in firing rates of cerebellar nuclei (CN) neurons and increased variability of PC simple spikes firing. Collectively, these findings show, for the first time, Mn-induced PC degeneration and dysfunctional CB circuitry in Slc39a14-KO mice providing additional evidence for the pathological underpinnings of the dystonia-like movements, balance, and gait abnormalities in SLC39A14 mutation carriers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A DECADE of dwarfs: first detection of weak lensing around spectroscopically confirmed low-mass galaxies

We present the first detection of weak gravitational lensing around spectroscopically confirmed dwarf galaxies, using the large overlap between DESI DR1 spectroscopic data and DECADE/DES weak lensing catalogs. A clean dwarf galaxy sample with well-defined redshift and stellar mass cuts enables excess surface mass density measurements in two stellar mass bins ($\log \rm{M}_*=[8.2, 9.2]~M_\odot$ and $\log \rm{M}_*=[9.2, 10.2]~M_\odot$), with signal-to-noise ratios of $5.6$ and $12.4$ respectively. This signal-to-noise drops to $4.5$ and $9.2$ respectively for measurements without applying individual inverse probability (IIP) weights, which mitigates fiber incompleteness from DESI's targeting. The measurements are robust against variations in stellar mass estimates, photometric shredding, and lensing calibration systematics. Using a simulation-based modeling framework with stellar mass function priors, we constrain the stellar mass-halo mass relation and find a satellite fraction of $\simeq 0.3$, which is higher than previous photometric studies but $1.5σ$ lower than $Λ$CDM predictions. We find that IIP weights have a significant impact on lensing measurements and can change the inferred $f_{\rm{sat}}$ by a factor of two, highlighting the need for accurate fiber incompleteness corrections for dwarf galaxy samples. Our results open a new observational window into the galaxy-halo connection at low masses, showing that future massively multiplexed spectroscopic observations and weak lensing data will enable stringent tests of galaxy formation models and $Λ$CDM predictions.

To, Chun-Hao [Chicago U., Astron. Astrophys. Ctr.;↗
DOE OSTI2025

Weather and climate extremes in a changing Arctic

Weather and climate extremes are increasingly occurring in the Arctic. Here, in this Review, we evaluate historical and projected changes in rare Arctic extremes across the atmosphere, cryosphere and ocean and elucidate their driving mechanisms. Clear shifts occur in mean and extreme distributions after ~2000. For instance, pre-2000 to post-2000 observational probabilities of 1.5 standard deviation events increase by 20% for atmospheric heat waves, 76.7% for Atlantic layer warm events, 83.5% for Arctic sea ice loss and 62.9% for Greenland Ice Sheet melt extent — in many cases, low probability, rare extreme events in the early period become the norm in the latter period. These observed changes can be explained using a ‘pushing and triggering’ concept, representing interplay between external forcing and internal variability: long-term warming destabilizes the climate system and ‘pushes’ it to a new state, allowing subsequent variability associated with large-scale atmosphere–ocean–ice interactions and synoptic systems to ‘trigger’ extreme events over different timescales. Ongoing anthropogenic warming is expected to further increase the frequency and magnitude of extremes, such that simulated probabilities of 1.5 standard deviation events increase by 72.6% for atmospheric heat waves, 68.7% for Atlantic layer warm events and 93.3% for Greenland Ice Sheet melt rate between historic (1984–2014) and future (2069–2099) periods under a very high emission scenario. Future research should prioritize the development of physically based metrics, enhance high-resolution observation and modelling capabilities and improve understanding of multiscale Arctic climate drivers.

atmospheric dynamics↗
DOE OSTI2025

The DECADE cosmic shear project III: validation of analysis pipeline using spatially inhomogeneous data

We present the pipeline for the cosmic shear analysis of the Dark Energy Camera All Data Everywhere (DECADE) weak lensing dataset: a catalog consisting of 107 million galaxies observed by the Dark Energy Camera (DECam) in the northern Galactic cap. The catalog derives from a large number of disparate observing programs and is therefore more inhomogeneous across the sky compared to existing lensing surveys. First, we use simulated data-vectors to show the sensitivity of our constraints to different analysis choices in our inference pipeline, including sensitivity to residual systematics. Next we use simulations to validate our covariance modeling for inhomogeneous datasets. Finally, we show that our choices in the end-to-end cosmic shear pipeline are robust against inhomogeneities in the survey, by extracting relative shifts in the cosmology constraints across different subsets of the footprint/catalog and showing they are all consistent within 1σ to 2σ. This is done for forty-six subsets of the data and is carried out in a fully consistent manner: for each subset of the data, we re-derive the photometric redshift estimates, shear calibrations, survey transfer functions, the data vector, measurement covariance, and finally, the cosmological constraints. Our results show that existing analysis methods for weak lensing cosmology can be fairly resilient towards inhomogeneous datasets. This also motivates exploring a wider range of image data for pursuing such cosmological constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

DVMDOSTEM v0.8.3: a terrestrial ecosystem model designed to represent arctic, boreal and permafrost ecosystem dynamics

The impacts of climate change on natural ecosystems are the result of complex physical and ecological processes operating and interacting at a variety of spatio-temporal scales, that can be represented in process-based ecosystem models. DVMDOSTEM is an advanced process-based terrestrial ecosystem model (TEM) designed to study ecosystem responses to climate changes and disturbances. It has a particular focus on permafrost regions (i.e. regions characterized by soils that stay partially frozen all year round for at least two consecutive years), encompassing boreal, arctic, and alpine landscapes. The model couples two previous versions of the Terrestrial Ecosystem Model (TEM) (McGuire et al., 1992): DVMTEM that includes a dynamic vegetation module (DVM) (E. S. Euskirchen et al., 2009), and DOSTEM that includes a dynamic organic soil module (DOS) (H. Genet et al., 2013; Yi et al., 2010). DVMDOSTEM simulates processes at yearly and monthly scales, with some physical processes operating at an even finer temporal resolution. Its versatility allows for site-specific to regional simulations, making it valuable for predicting shifts in permafrost, vegetation, and carbon (C) and nitrogen (N) dynamics. While DVMDOSTEM has been described in the methods sections of many manuscripts, this paper is the first stand alone description of DVMDOSTEM, independent of a particular scientific investigation.

Carman, Tobey B. [Univ. of Alaska, Fairbanks, AK (↗
DOE OSTI2025

In-device Battery Failure Analysis

Lithium-ion batteries are indispensable power sources for a wide range of modern electronic devices. However, battery lifespan remains a critical limitation, directly affecting the sustainability and user experience. Conventional battery failure analysis in controlled lab settings may not capture the complex interactions and environmental factors encountered in real-world, in-device operating conditions. Here, this study analyzes the failure of commercial wireless earbud batteries as a model system within their intended usage context. Through multiscale and multimodal characterizations, the degradations from the material level to the device level are correlated, elucidating a failure pattern that is closely tied to the specific device configuration and operating conditions. The findings indicate that the ultimate failure mode is determined by the interplay of battery materials, cell structural design, and the in-device microenvironment, such as temperature gradients and their fluctuations. This holistic, in-device perspective on environmental influences provides critical insights for battery integration design, enhancing the reliability of modern electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Elucidating the phase transformations and grain growth behavior of O3-type sodium-ion layered oxide cathode materials during high temperature synthesis

Understanding the formation mechanism of layered oxide cathodes via solid-state synthesis is imperative to achieving controllability over their materials properties and electrochemical behaviors. In this work, we investigate the phase and microstructure evolution during the synthesis of NaNi 1/3 Fe 1/3 Mn 1/3 O 2 , a model sodium-ion layered oxide cathode, using a combination of imaging, diffraction, and spectroscopic techniques. We unravel the synthetic mechanistic pathways involved in the high-temperature calcination reaction, as well as elaborate the synthesis-microstructure-performance relationship of this material. The formation of the final layered oxide phase involves a gradual transformation through a sodiated oxyhydroxide intermediate. During the reaction, the precursor dehydration reaction dominates at 250–550 °C, while the major sodiation reaction occurs at 550–850 °C. Alongside multiple stages of phase transformations, the final grain structure formation occurs through the continuous growth of the (003) and (104) facets. During the reaction, Mn acts as the charge-compensating element and exhibits depth-dependent characteristics. When the sodiation reaction dominates over dehydration, the reaction intermediates undergo gradual electronic structure changes with increasing temperature, as indicated by the spectral features of TM3d-O2p hybrid states. Calcination duration is also a critical parameter governing the microstructure, surface reactivity, phase fraction distribution and electrochemical performance of the material. The optimal calcination duration was determined to be 18 hours at 850 °C under the conditions evaluated here. Calcination beyond this duration was found to be detrimental to electrochemical performance due to Na and O loss and heterogeneous sodium distribution throughout the particles. Our work sheds light on the complex crystallographic-chemical-microstructural evolution of sodium ion layered oxide cathodes and provides insight into precisely tuning material properties which are intimately linked to battery performances.

25 ENERGY STORAGE↗
DOE OSTI2025

Measurement of directed flow in Au + Au collisions at $\sqrt{s{NN}}$ = 19.6 and 27 GeV with the STAR event plane detector

In heavy-ion collision experiments, the global collectivity of final-state particles can be quantified by anisotropic flow coefficients (𝑣 𝑛 ) . The first-order flow coefficient, also referred to as the directed flow (𝑣 1 ), describes the collective sideward motion of produced particles and nuclear fragments in heavy-ion collisions. It carries information on the very early stage of the collision, especially at large pseudorapidity (𝜂), where it is believed to be generated during the nuclear passage time. Directed flow therefore probes the onset of bulk collective dynamics during thermalization, providing valuable experimental guidance to models of the pre-equilibrium stage. In 2018, the Event Plane Detector (EPD) was installed in STAR and used for the Beam Energy Scan phase-II (BES-II) data taking. The combination of EPD (2.1 < |𝜂| < 5.1) and high-statistics BES-II data enables us to extend the 𝑣 1 measurement to the forward and backward 𝜂 regions. In this paper, we present the measurement of 𝑣 1 over a wide 𝜂 range in Au + Au collisions at $\sqrt{s_{NN}}$ = 19.6 and 27 GeV using the STAR EPD. The results of the analysis at $\sqrt{s_{NN}}$ = 19.6 GeV exhibit excellent consistency with the previous PHOBOS measurement, while elevating the precision of the overall measurement. The increased precision of the measurement also revealed finer structures in heavy-ion collisions, including a potential observation of the first-order event-plane decorrelation. Multiple physics models were compared to the experimental results. Only a transport model and a three-fluid hybrid model can reproduce a sizable 𝑣 1 at large 𝜂 as was observed experimentally. The model comparison also indicates 𝑣 1 at large 𝜂 might be sensitive to the QGP phase transition.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Measurements of ϒ states production in 𝑝 + 𝑝 collisions at $\sqrt{s}$ = 500 GeV with STAR: Cross sections, ratios, and multiplicity dependence

We report measurements of ϒ⁡(1⁢𝑆), ϒ⁡(2⁢𝑆) and ϒ⁡(3⁢𝑆) production in 𝑝 + 𝑝 collisions at $\sqrt{s}$ =500 GeV by the STAR experiment in year 2011, corresponding to an integrated luminosity ℒ int = 13 pb −1 . The results provide precise cross sections, transverse momentum (𝑝 T ) and rapidity (𝑦) spectra, as well as cross section ratios for 𝑝 T < 10 GeV/c and |𝑦| < 1. The dependence of the ϒ yield on charged particle multiplicity has also been measured, offering new insights into the mechanisms of quarkonium production. The data are compared to various theoretical models: the color evaporation model (CEM) accurately describes the ϒ⁡(1⁢𝑆) production, while the color glass condensate+nonrelativistic quantum chromodynamics (CGC+NRQCD) model overestimates the data, particularly at low 𝑝 T . Conversely, the color singlet model (CSM) underestimates the rapidity dependence. These discrepancies highlight the need for further development in understanding the production dynamics of heavy quarkonia in high-energy hadronic collisions. The trend in the multiplicity dependence is consistent with CGC/saturation and string percolation models or ϒ production happening in multiple parton interactions modeled by PYTHIA 8.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Precision Measurement of Net-Proton-Number Fluctuations in Au + Au Collisions at RHIC

We report precision measurements on cumulants (𝐶 𝑛 ) and factorial cumulants (𝜅 𝑛 ) of (net) proton number distributions up to fourth order in Au + Au collisions over center-of-mass energies $\sqrt{s_{NN}}$ = 7.7–27 GeV from phase II of the Beam Energy Scan program at RHIC. (Anti)protons are selected at midrapidity (|𝑦| < 0.5) within a transverse momentum range of 0.4 < 𝑝 𝑇 < 2.0 GeV/𝑐. Relative to various noncritical-point model calculations and peripheral collision 70%–80% data, the net proton 𝐶 4 /𝐶 2 measurement in 0%–5% collisions shows a minimum around 19.6 GeV for significance of deviation at ∼2–5⁢𝜎. A minimum in 𝐶 4 /𝐶 2 with respect to a noncritical baseline is expected to be a characteristic feature of the signature associated with a critical point in the QCD phase diagram. In addition, deviations from noncritical baselines around the same collision energy region are also seen in proton factorial cumulant ratios, especially in 𝜅 2 /𝜅 1 and 𝜅 3 /𝜅 1 . As a result, dynamical model calculations including a critical point are called for in order to understand these precision measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Measurement of In-Medium Jet Modification Using Direct Photon + Jet and 𝜋 0 + Jet Correlations in 𝑝 + 𝑝 and Central Au + Au Collisions at $\sqrt{s_{NN}}$ = 200 GeV

The STAR Collaboration presents measurements of the semi-inclusive distribution of charged-particle jets recoiling from energetic direct-photon (𝛾 dir ) and neutral-pion (𝜋 0 ) triggers in 𝑝 + 𝑝 and central Au + Au collisions at $\sqrt{s_{NN}}$ =2 00 GeV over a broad kinematic range, for jet resolution parameters 𝑅 = 0.2 and 0.5. Medium-induced jet yield suppression is observed to be larger for 𝑅 = 0.2 than for 0.5, reflecting the angular range of jet energy redistribution due to quenching. The predictions of model calculations incorporating jet quenching are not fully consistent with the observations. Furthermore, these results provide new insight into the physical origins of jet quenching.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Measurement of flow coefficients in high-multiplicity 𝑝 + Au, 𝑑 + Au, and 3 He + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV

Flow coefficients (𝑣 2 and 𝑣 3 ) are measured in high-multiplicity 𝑝 + Au, 𝑑 + Au, and 3 He + Au collisions at a center-of-mass energy of $\sqrt{s_{NN}}$ = 200 GeV using the STAR detector. The measurements utilize two-particle correlations with a pseudorapidity requirement of |𝜂| < 0.9 and a pair gap of |Δ⁢𝜂| > 1.0. The primary focus is on analysis methods, particularly the subtraction of nonflow contributions. Four established nonflow subtraction methods are applied to determine 𝑣 𝑛 , validated using the HIJING event generator. 𝑣 𝑛 values are compared across the three collision systems at similar multiplicities; this comparison cancels the final-state effects and isolates the impact of initial geometry. While 𝑣 2 values show differences among these collision systems, 𝑣 3 values are largely similar, consistent with expectations of subnucleon fluctuations in the initial geometry. The ordering of 𝑣 𝑛 differs quantitatively from previous measurements using two-particle correlations with a larger rapidity gap, which, according to model calculations, can be partially attributed to the effects of longitudinal flow decorrelations. As a result, the prospects for future measurements to improve our understanding of flow decorrelation and subnucleonic fluctuations are also discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗