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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Across the Scales of the Nucleus: Understanding Short Range Correlations from Medium Modification to Probe Independence

The atomic nucleus presents an intricate system due to the non-linear forces described by Quantum Chromodynamics (QCD) that govern its structure. The range of scales involved is remarkable; the most massive nuclei weigh approximately five orders of magnitude more than the quarks that compose them. The nucleus can be analyzed at various levels, from quarks to hadrons to the nucleus as a whole. Short-Range Correlations (SRCs) within the nucleus play a significant role that spans these diverse scales. At the most fundamental level, SRCs influence the interaction between nucleons. The nucleon-nucleon (NN) interaction, arising from QCD, is crucial in determining nuclear properties. SRCs serve as valuable probes for measuring this NN interaction, as the nucleons within SRCs become effectively decoupled from the rest of the nucleus. Multiple experimental techniques, including electron scattering, have been employed to investigate the NN interaction through SRCs. However, our first project demonstrates that inclusive measurements alone are inadequate to constrain this interaction fully. Moving to the scale of the nucleus, SRCs contribute to the high-momentum tail of the nuclear spectral function. While the low-momentum region is characterized by nucleons exhibiting bulk properties, nucleons begin to pair into SRCs at higher momenta. Our research aims to bridge the understanding between the mean-field portion of the nucleus and its high-momentum SRC components. Additionally, SRCs affect the quark structure of protons, as evidenced by the EMC effect, which indicates that quarks behave differently when protons are embedded within a nucleus—an effect referred to as medium modification. This thesis explores the correlation between SRCs and medium modification across various experimental setups. Finally, we seek to establish an interpretation of the nuclear ground state. Accomplishing this requires demonstrating that our SRC observables are independent of the probe’s scale and scheme. The concluding project of this thesis illustrates how we utilize triple coincidence quasi-elastic scattering across a range of (Q2) values to develop a model-dependent framework for understanding SRC distributions within the nucleus’s ground-state wavefunction.

Denniston, A. W. Denniston [University of Tel Aviv↗
DOE OSTI2025

High Spatial Resolution Mapping of Retained Fission Gas

Fission gas isotopic analysis provides quantitative high precision determination of irradiated nuclear fuel burnup, offers diagnostic value, and informs fuel performance models. A measurement capability has been developed at Idaho National Laboratory (INL) for the release of retained fission gas using a focused laser and static noble gas mass spectrometry (MS) analysis. This high resolution (10s microns spot size) capability was demonstrated using Xe implanted metal foils.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2024

Utah FORGE: 2024 Discrete Fracture Network Model Data

The Utah FORGE 2024 Discrete Fracture Network (DFN) Model dataset provides a set of files representing discrete fracture network modeling for the FORGE site near Milford, Utah. The dataset includes four distinct DFN model file sets, each corresponding to different time frames and modeling approaches in 2024. These models characterize both natural and induced fractures in the geothermal reservoir, which consists of crystalline granitic and metamorphic rock approximately 8,000 feet below the ground surface. The dataset includes a reference DFN model from February 2024 that incorporates planar fractures and well trajectories, as well as upscaled permeability, porosity, compressibility, and storage values on specified grids. Additionally, there are models based on new microseismic (MEQ) data from May and July 2024, including fracture planes fitted to the latest MEQ catalog datasets, tensile fractures from hydraulic stimulation, and an alternative connected DFN for modeling purposes. Coordinate data is provided in both global and local frames, with detailed instructions on the transformations used to align with principal stress orientations. The dataset also includes notes and calculation files for estimating fracture sizes and differences between various fracture sets. There are subfolders for Global Coordinates and Local Coordinates. To move from the global to the local coordinate frame, fractures and wells were a) rotated 20 degrees counterclockwise looking down about the global point (335376.400482041, 4263189.99998761, 250.093546450195) to better align with the principal stresses; and b) translated by (-335408.68, -4263010.9, 1150). Upscaled permeability values using the _XYZ suffix show directions with respect to the global XYZ coordinate frame, while those using the _IJK suffix are aligned with local coordinate frame.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Greenhouse Gas Emissions and Decarbonization Potential of Global Fired Clay Brick Production

Fired clay bricks (FCBs) are a dominant building material globally due to their low cost and simplicity of production, especially in low- and middle-income countries. With a projected rising housing demand, commensurate growth in brick demand is anticipated, the production of which could result in significant greenhouse gas (GHG) emissions. Robust models are needed to estimate brick demand and emissions to systematically address decarbonization pathways. Few sources report production values; hence, we present two novel proxy models: (i) a consumption prediction model, relying on country-specific clay extraction data, dynamic building stock modeling, and average material intensity use allowing for projections to 2050; and (ii) a GHG emissions model, using literature-based data and production technology-specific inputs. Based on these models, the current global FCB consumption is estimated as 2.18 Gt annually, resulting in approximately 500 million tCO2e (1% of current global GHG emissions). If unaddressed, this fraction could increase to 3.5-5% in 2050 considering a moderate SSP 2-4.5 climate change mitigation scenario. Consequently, we explored three potential decarbonization pathways: (i) improving energy efficiency; (ii) shifting production to best practices; and (iii) replacing half of FCB demand with hollow concrete blocks, resulting in 27%, 49%, and 51% reduction in GHG emissions, respectively.

Olsson, Josefine A↗
DOE OSTI2025

Quantifying UAS Observation Error Variance Used in Data Assimilation Systems and Its Impact on Predictive Skill

Observation error determines the weights of the observations and background state used in data assimilation to generate analyses. Quantifying observation error is critical for the optimal assimilation of observational data sets. Uncrewed Aircraft System (UAS) observations have shown potential benefits in filling observational gaps in the lower atmosphere; however, characterization of their error characteristics has been limited. To optimize the use of UAS observations in numerical weather prediction, UAS observation error is estimated based on the 3‐cornered hat diagnostic approach which uses three independent estimates of the atmospheric state. This approach is applied to data from the 2018 Lower Atmospheric Profiling Studies at Elevation‐a Remotely‐piloted Aircraft Team Experiment field campaign using collocated UAS and rawinsonde observations along with output from a set of convection‐permitting model simulations. The estimated observation error values for UAS temperature, wind, and relative humidity measurements were found to be only weakly dependent on height AGL with mean values equal to 0.5°C, 0.8 m s −1 , and 3%, respectively. Only the newly estimated observation error for temperature differed from that previously used to assimilate commercial aircraft observations into global models (1.0°C). However, using this reduced temperature observation error produced more accurate mesoscale analyses and forecasts of both terrain‐driven flows and convection initiation generated by colliding outflow boundaries within the San Luis Valley of Colorado.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Adsorption of terbium (III) on DGA and LN resins: Thermodynamics, isotherms, and kinetics

Two commercially available extraction chromatography (EXC) resins containing N,N,N’,N’-tetra-n-octyldiglycolamide (DGA Resin, Normal, 50 – 100 μm) and Bis(2-ethylhexyl) phosphate (LN Resin, 100 – 150 μm) were used as adsorbents to study fundamental adsorption properties such as thermodynamic values, equilibrium isotherms, and kinetic uptake models for terbium(III) adsorption. Weight distribution ratios (D w ) for terbium on DGA and LN resins were measured using a [ 160 Tb]Tb 3+ radiometric tracer in nitric acid as a function of acidity, temperature, initial analyte concentration, and equilibrium time. The D w values showed increasing binding affinity for DGA resin at high nitric acid concentrations and decreasing binding affinity for LN resins. Thermodynamic studies for DGA and LN resins revealed that the Gibbs free energy (ΔG) increased consistently with temperature. To model equilibrium data, increasingly higher parameter equilibrium isotherm models (Henry (1) < Langmuir, Freundlich (2) < Redlich-Peterson (3) < Fritz-Schluender (4)) were compared on their root mean squared errors (RMSE) and adjusted determination coefficients to determine the most applicable model. In all cases, the empirical four-parameter Fritz-Schluender isotherm demonstrated a superior fit. Similar comparisons for reaction-based kinetic models (Pseudo-first-order < Pseudo-second-order < Pseudo-n-order) revealed that the higher-order PNO model yielded a superior fit of kinetic data for both resins. Furthermore, in some cases, adsorption isotherms and kinetic models could also be modeled by a lower-order model with minimal change in error parameters. Weber-Morris plots revealed that two linear sections are observed for each resin, where the first linear segment is attributed to fast (film diffusion) adsorption of terbium, followed by slower intraparticle diffusion of terbium through the pores as the rate-limiting step. Based on the Weber-Morris plot, both film and intraparticle diffusion are involved in controlling the kinetic rate of adsorption for DGA and LN resins.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Challenges in Tracking Waste Reduction Performance Improvement in Manufacturing Plants

The recently released Circularity Gap Report 2023 by the Circle Economy Foundation states that the circularity score for the global economy is declining. The US Environmental Protection Agency (EPA) tracked municipal solid waste from 1960 to 2018 and found that 50% of the waste was destined for landfills. EPA estimates that US industry is responsible for 2.7 Gt of solid nonhazardous waste annually in the US mostly linear economy model. The circular economy framework aims to decouple economic value generation from the extraction of virgin materials from nature. The linear model of material extraction and disposal at the end of life is highly unsustainable. Manufacturing companies are adopting ambitious waste reduction targets to achieve sustainability. Through the Better Plants program, US DOE has established the Waste Reduction Network, which offers technical assistance to partners to achieve their ambitious waste reduction goals. Basic requirements of establishing a target include identifying a baseline, quantifying waste performance, and measuring progress over time. One problem faced by industry is unstandardized metrics for quantifying waste performance that may not be well suited to demonstrate progress. This paper studies traditional methods used to measure waste performance and highlights advantages, disadvantages, and limitations of each method. It also examines the suitability of applying the methods in different manufacturing circumstances. Finally, the paper presents a case study of a large manufacturer that faced inconsistencies in its tracked measurement metric. A solution was proposed and implemented to alter the methodology to enable more accurate waste performance tracking against a baseline.

circular economy↗
DOE OSTI2025

Thermo-Mechanical Phase-Field Modeling of Fracture in High-Burnup UO2 Fuels Under Transient Conditions

This study presents a novel multiphysics phase-field fracture model to analyze high-burnup uranium dioxide (UO2) fuel behavior under transient reactor conditions. Fracture is treated as a stochastic phase transition, which inherently accounts for the random microstructural effects that lead to variations in the value of fracture strength. Moreover, the model takes into consideration the effects of temperature and burnup on thermal conductivity. Therefore, the model is able to predict crack initiation, propagation, and complex morphologies in response to thermal gradients and stress distributions. Several simulations were conducted to investigate the effects of operational and transient conditions on fracture behavior and the resulting cracking patterns. High-burnup fuels exhibit reduced thermal conductivity, elevating temperature gradients and resulting in extensive radial and circumferential cracks. Transient heating rates and temperatures significantly affect fracture patterns, with higher heating rates generating steeper gradients and more irregular crack trajectories. This approach provides critical insights into fuel integrity during accident scenarios and supports the safety evaluation of extended burnup limits.

Chemistry↗
DOE OSTI2025

ELM model simulations of Plum Island Ecosystems LTER low marsh site 2018-2020

Model simulations using the Department of Energy's Energy Exascale Earth System Model (E3SM) land model (ELM) with improved capabilities to represent vegetation response to salinity and inundation. The simulations were conducted for a tidal salt marsh at Plum Island Ecosystems Long Term Ecological Research (LTER) site near Rowley, Massachusetts, USA; the site is a low marsh dominated by Spartina alterniflora. The model was forced with site-specific meteorology, salinity and tidal cycles from 2018-2020. Four sets of model simulations are included and described below:1. Parameterization of the salinity response function. These simulations tested different combinations of values for optimal salinity and salinity tolerance.2. Model evaluation. This comparison conducted simulations using the default model, the salinity function only, the submergence function only, and both the salinity and submergence functions. 3. Salinity scenarios. These simulations used the 2018 salinity input data varied by -5 to +10 ppt salinity.4. Water level scenarios. These simulations used the tide height varied by -10 to +50 cm. These simulations were used to demonstrate how the salinity and submergence functions better represent carbon uptake by tidal salt marshes.The data package includes netCDF files used as forcing files for tide height and salinity, one for each year 2018-2020 at observed salinity concentrations, and an additional three forcing files in which salinity concentrations were varied 5 ppt lower, 5 ppt higher, and 10 ppt higher than the measured 2018 time series. Also included are python scripts for creating forcing files, plain text parameter and command files for running simulations, model outputs in netCDF format, and python scripts for visualizing outputs. Code for the modified E3SM model is archived in Sulman et al 2023 at doi:10.15485/1991625. More detail about files is provided in the README.md file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Evaluation of simulated HPGe detector efficiencies in OpenMC compared to MCNP

In late 2023, the open-source radiation transport code OpenMC introduced a pulse-height tally (PHT) feature, enabling users to track the total energy deposited by individual photons in OpenMC cells. This function represents an important improvement of the OpenMC code because it allows users to simulate the response function of a gamma detector without relying on closed-source alternatives. Despite this, limited work has been published evaluating OpenMC as a radiation transport code for simulating gamma spectroscopy experiments. This study attempts to demonstrate the usefulness of OpenMC in this space by directly comparing its PHT output to MCNP (a trusted industry-standard Monte Carlo code). In the first half of this study, a radiation transport experiment is described in which a detector with a complex internal geometry is exposed to various gamma-emitting isotopes ( 133 Ba, 137 Cs, and 60 Co) over a range of distances. The setup of this experiment was modeled in MCNP with sufficient detail to capture the efficiency characteristics of a high purity germanium (HPGe) detector for the primary gammas of each isotope. After good agreement between the MCNP model and experiment was achieved, an identical model was produced in OpenMC to allow direct comparison between the full energy peak (FEP) values produced in OpenMC and MCNP. The results show strong agreement between OpenMC and MCNP across the full range of tested energies, with each model’s FEP values typically within 2% of each other and most FEP areas within 4% of experimental data. Worse agreement was seen between the Monte Carlo codes and experiment below 300 keV (an expected result). For the 662 keV line of 137 Cs, both codes were found in poor agreement with experiment and each other over the full range of distances tested (possibly indicating an error with the 137 Cs experimental data). Ignoring the anomalous results of the 662 keV line, all other data show good qualitative and quantitative agreement between MCNP and OpenMC. This result demonstrates the accuracy of OpenMC’s PHT feature for spectroscopic applications in which detector efficiency is a primary concern.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2026

Microreactor Core Transportation Cask Model Description for Criticality Safety Validation Basis Assessment (Rev. 2)

Criticality safety analyses are completed on transportation casks used for microreactor whole core shipment to provide examples of models and analyses to industry, regulators, and nuclear community at large to be used in verification and validation analyses of similar applications. The microreactors considered are based on a Gas-Cooled Microreactor (GCMR) and a Heat-Pipe Microreactor (HPMR), both utilize HALEU fuel in the form of TRISO particles and various other design options considered in industry microreactor designs. Variant design options of GCMR and HPMR were also investigated to provide a wider application range for each technology. Criticality safety analyses for the GCMR and HPMR packages were performed using the CSAS6 sequence of SCALE 6.3.2 with the ENDF/B-VII.1-based continuous energy neutron libraries. Different scenarios were investigated, including normal operation and water flooded conditions to represent nominal and hypothetical accident scenarios. Sensitivity and similarity analyses are also performed using the TSUNAMI sequence of SCALE 6.3.2, and the similarity analysis uses all the experiments from the ICSBEP Handbook with High Enriched Uranium (HEU), Intermediate and mixed Enriched Uranium (IEU) and Low Enriched Uranium (LEU) systems. Many ICSBEP experiments were found marginally similar, with similarity index (ck) values greater than 0.8, to the GCMR and HPMR cask models, especially in flooded conditions that may be more constraining due to reduced reactivity margins. Some experiments using TRISO fuel particles and graphite moderator, including the recent THETA and Deimos experiments from LANL, together with some IRPhEP experiments, were also used for the similarity analyses. These TRISO-fueled and graphite moderated experiments behaved similarly to the GCMR models, with maximum ck value greater than 0.9, but they are less similar to the HPMR models. This observation indicates that additional critical experiments might be needed to further validate the criticality safety models, especially for heat-pipe based microreactor transport packages and for non-flooded transportation configurations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Equivalency Factors and Mixed Isotope Subcritical Limits in H-Canyon [Slides]

Accurate references and documentation are of upmost importance, especially with the current workforce makeup. Tribal knowledge is likely to be lost with turnover. Using a questioning attitude is a great way to find gaps in existing analysis and “normal practices.” Most of the references reviewed are from the 1970’s, with the most recent authored in 1994. Many of these references have been revised and/or superseded in the years since. Though safe, many of the values are likely overconservative, as improvements with modeling and additional critical experiments have been performed in the years since. It would be prudent to reevaluate, clarify, and simplify the values used in H-Canyon.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Mechanistic Modeling of TEG Dehydrator Emissions in Oil and Gas Industry

This work presents a mechanistic modeling approach for simulating methane emissions from triethylene glycol (TEG) dehydrators used in oil & gas (O&G) operations. The model was developed as a modular component of the Mechanistic Air Emissions Simulator (MAES) tool, incorporating species-specific absorption and emission dynamics through two-level, second-order polynomial regression (PR) models trained on ProMax simulation data: (1) species-level regression models that track the transfer rates of individual gas species within the dehydrator unit streams, and (2) outlet flow stream regression models that predict the fraction of inlet gas distributed among the outlet streams of the dehydrator unit. These behaviors were characterized over a range of glycol circulation ratios, wet gas pressures, and temperatures. The model was validated using root mean square error (RMSE) analysis. The species-level PR achieved low root mean square error (RMSE) values (<0.03) for light hydrocarbon species across all dehydrator components, ranging from 0.0009 for methane to 0.029 for normal pentane. Similarly, the outlet-level PR yielded RMSE values below 0.002 for the dry gas fraction, 0.001 for the flash tank fraction, and 0.002 for the still vent fraction, demonstrating strong agreement between predicted and reference ProMax values. When deployed at field facilities, the model significantly improved MAES-simulated dehydrator emissions, revealing that gas-assisted glycol pump emissions are the dominant contributors to both dehydrator-level and site-level methane emissions under uncontrolled conditions. Further analysis of the 154 dehydrator units reported by operators under the AMI 2024 project showed that 54 units (31%) used gas-driven glycol pumps, of which 6 units (11%) operated with uncontrolled flash tanks, and 22 units (40.7%) were identified as potentially oversized. Of the six dehydrator units with uncontrolled gas-assisted pumps, pump emissions accounted for 90.25% of total dehydrator emissions and 63.10% of total site-level emissions. These findings highlight substantial opportunities for emissions mitigation through equipment upgrades.

MAES↗
DOE OSTI2026

A non-intrusive framework using acoustic signals and deep learning for boiling diagnostics in visual-limited environments

Accurate monitoring of boiling heat transfer is critical for safeguarding high-power systems operating in environments where conventional optical diagnostics are hindered by radiation fields or restricted visual accessibility. This study presents a non-intrusive framework that integrates hydroacoustic sensing with deep learning to infer near-wall boiling characteristics and enable predictive thermal assessment without visual access. In a prototypical subcooled flow-boiling facility representative of the Isotope Production Facility (IPF) at Los Alamos, hydrophones capture boiling-induced acoustic emissions that are transformed into background-removed Short-Time Fourier Transform (STFT) spectrograms. A convolutional neural network (CNN) then regresses heat flux, wall superheat, and key bubble parameters directly from these spectrograms. The CNN achieved predictive accuracy under nominal conditions and demonstrated robustness and generalization under acoustic noise for Signal-to-Noise Ratios (SNRs) down to approximately 0 dB. When integrated into an ANSYS CFX wall-boiling model, the acoustically inferred parameters reproduced boiling curve and critical heat flux (CHF) values consistent with image-based benchmarks. Furthermore, the model retained reliable performance under moderate variations in bulk temperature, flow rate, and hydrophone placement, confirming its generalizability across practical boundary conditions. These results demonstrate the feasibility of hydroacoustic-based deep learning as a viable path toward real-time, radiation-tolerant boiling diagnostics and predictive thermal safety assessment in inaccessible systems such as the IPF.

42 ENGINEERING↗
DOE OSTI2024

Wave-powered water pump for upwelling in aquaculture: Numerical model and ocean test

Wave-powered upwelling can increase the productivity and survivability of several aquaculture species. This enhancement is due to transporting cold, nutrient-rich ocean water, typically found lower in the water column, to the surface. Macroalgaes, like kelp, exhibit increased growth from these altered conditions. The University of New Hampshire’s (UNH) wave-powered water pump (wave pump) is a point absorber wave energy converter (WEC) that uses ocean waves to create relative motion between a spar buoy and a concentric float which drives an internal pump. A numerical model of the wave pump was developed using WEC-Sim to predict device performance in the ocean. Wave pump performance was evaluated during a five day ocean test near Appledore Island in Maine in March 2023, where volumetric flow rate, relative distance between spar and float, and wave conditions were measured. These data were then used for numerical model validation. The ocean deployment recorded the device’s performance in a variety of sea states, with average significant wave heights up to 0.7 m. The ocean test data were compared to the WEC-Sim numerical model of the device with favorable results. Average values of device stroke period, stroke height, and flow rate agreed between the ocean test and model data to within approximately 16 to 22%. Furthermore, the validated numerical model provides a valuable tool for improving the design and developing a commercial-scale, wave-powered water pump for use in aquaculture.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Observation of Λ Hyperon Local Polarization in 𝑝-Pb Collisions at $\sqrt{s_{NN}}$ = 8.16 TeV

The polarization of the Λ and $\bar{Λ}$ hyperons along the beam direction has been measured in proton-lead (𝑝-Pb) collisions at a center-of-mass energy per nucleon pair of 8.16 TeV. The data were obtained with the CMS detector at the LHC and correspond to an integrated luminosity of 186.0 ± 6.5 nb −1 . A significant azimuthal dependence of the hyperon polarization, characterized by the second-order Fourier sine coefficient 𝑃 𝑧,s⁢2 , is observed. The 𝑃 𝑧,s⁢2 values decrease as a function of charged particle multiplicity, but increase with transverse momentum. A hydrodynamic model that describes the observed 𝑃 𝑧,s⁢2 values in nucleus-nucleus collisions by introducing vorticity effects does not reproduce either the sign or the magnitude of the 𝑝-Pb results. These observations pose a challenge to the current theoretical implementation of spin polarization in heavy ion collisions and offer new insights into the origin of spin polarization in hadronic collisions at LHC energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗