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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

USE OF TWO-PISTON SPLAT QUENCHING TO INVESTIGATE & CHARACTERIZE THE IMPACT OF COMPOSITIONAL VARIATIONS ON RAPID SOLIDIFICATION MICROSTRUCTURES & SUB-MICROSCALE FEATURES IN STAINLESS STEEL ALLOY.

The objective of this dissertation was to use two-piston splat quenching (SQ) to investigate the impact of compositional modifications on the solidification and microstructure of rapidly solidified austenitic stainless steels (SS) and to demonstrate the ability of SQ to quickly and effectively simulate rapid solidification conditions similar to those found in powder bed fusion (PBF) additive techniques. PBF techniques like laser powder bed fusion (LPBF) are being implemented across a breadth of research and industrial applications to create parts with complex geometries and performance capabilities while pushing the current limits of processing conditions and understanding of material systems. In this work, SQ was used to experimentally produce rapid solidification in 20+ unique austenitic SS compositions with systematic variations of the chrome and nickel equivalency ratio (Cr/Nieq) through targeted compositional modifications. From the targeted change of Cr, Ni, and Mo concentrations in rapidly solidified SS alloys, the ferrite solidification mode was found to be the primary solidification mode at significantly lower Cr/Nieq than previously predicted for RS. Also, decreasing concentrations of Fe at a constant Cr/Nieq ratio (i.e., different Fe isopleths), or increased Mo concentrations at a constant Cr/Nieq ratio were found to suppress the ferrite to austenite massive transformation when compared to alloys with lower concentrations at the same Cr/Nieq. Using an established empirical relationship between cell size and cooling rate, the SQ technique was estimated to produce cooling rates between 106 and 108 K/s. Thermal gradients were extracted from 2-D heat transfer simulations of the SQ solidification event and used with these cooling rates to produce solidification rate estimates for SQ which were between 0.4-1.6m/s. The primary solidification mode was observed to be the determining factor in which elements segregated to the cell boundaries during RS, for which Cr and Mo were the main elements to segregate during primary austenite solidification and Ni during primary ferrite solidification. Finally, the solidification rates and conditions produced by SQ experiments resulted in similar microstructures, features, and microsegregation to what was found in LPBF samples of the same feedstock.

Hasenbusch, Zachary↗
DOE OSTI2024

Characterization of compositional variation and solidification condition on rapid solidification behavior of beta stabilized titanium

Rapid solidification (RS) is a field of study that has increased in importance due to the rise of additive manufacturing (AM) techniques. The breakdown of equilibrium at the solid-liquid interface results in an inability to use traditional solidification models that have been applied to great success in casting. As such, there is a current need for a high-throughput testing method to screen alloys at rapid solidification conditions without the significant cost for powder atomization. In this work, twin hammer splat quenching (SQ) is utilized and theoretically developed as a technique uniquely placed to test alloy systems for AM applications. Using analytical thermal spray models and numerical heat transfer simulations, the cooling rate and solidification conditions of splat quenching are compared across several parameters to evaluate the key parameters for generating cooling rates relevant to AM process. Once a framework for the cooling rates and relevancy of SQ are developed, SQ was used to process alloy compositions in the Ti5553 alloy space (AMS 7026) to study the formation of detrimental secondary phases occurring upon rapid quenching from the melt. A martensitic phase is found to occur at the lower end of the standard, but the composition listed in the standard were found to be safe. Finally, the rapid solidification behavior of Ti-5553 is evaluated by comparing splat quenching, laser welding, and plasma atomization that offer a wide window of solidification conditions. The segregation and solidification structure are analyzed and compared to models to provide a deeper understanding of the solidification behavior of beta stabilized titanium alloys.

Williamson, Christopher J.↗
DOE OSTI2024

METHOD FOR EXPOSING IRRADIATED FUEL CLADDING TO RAPID THERMAL TRANSIENTS

Reactor core materials exposed to rapid thermal transients during accidents can experience significant changes in mechanical properties as irradiation hardness is recovered. Understanding material performance during transients using computer modeling requires accurate descriptions of mechanical property evolution with time and temperature. A simple experimental capability was developed to expose irradiated Zircaloy to a simulated thermal transient using immersion in molten tin (at 675°C) to rapidly heat and hold before rapidly cooling with a water quench. Multiple heating-cooling cycles using a nonirradiated tensile specimen showed simplicity and viability. Based on preliminary test results, a robust system was established for routine evaluation of simulated thermal accident scenarios in the Low Activation Materials Design and Analysis (LAMDA) laboratory at Oak Ridge National Laboratory (ORNL). This paper summarizes system development and nonirradiated Zircaloy commissioning test results. Future experiments will conduct tensile tests on irradiated Zircaloy after various rapid temperature profiles.

Byun, TS↗
DOE OSTI2026

Splat Quenching as a High Throughput Rapid Solidification Testing Method for Developing Additive Manufacturing Alloys

Splat quenching as a high throughput rapid solidification screening tool is evaluated. Samples were made using known alloys (SS316, IN625, Ti-5553) to evaluate and establish the microstructures for a variety of alloy systems as well as the predicted cooling rates. The samples are inductively heated and levitated prior to being struck between two platens that produce a high contact pressure and a thin sample resulting in cooling rates on the order of 10 6 to 10 7 K/s. Process parameters were evaluated with analytical models in addition to numerical simulations to provide an effect of process variables such as substrate material, melt superheat, and platen velocity on the resulting solidification. The splat thickness was found to be controlled by platen velocity, melt superheat, as well as the feedstock volume. The sample thickness is the key controlling factor for varying the average cooling rate experienced by the splat quenched sample. The splat quenching techniques can reach regions of rapid solidification space that meet and exceed laser and electron beam techniques across the sample. In conclusion, the results of the study provide a useful foundation in understanding the splat quenching technique and its potential as a low effort tool to explore rapid solidification effects on alloys.

Alloy Design↗
DOE OSTI2024

The importance of cycle-by-cycle data in performing rapid battery technology development and validation

Lithium-ion battery (LiB) technology is playing a crucial role in transforming the predominantly fossil fuel-based transportation and stationary storage sectors to achieve a low-carbon economy. Rapid innovation in the LiB materials to electrode to cell design is happening to satisfy the performance, life, and safety metrics required by those myriads of applications. Lately, advanced analytics, such as machine-learning or artificial intelligence (ML/AI) techniques, are being used more frequently to aid in expedited LiB technology development, performance validation, and life prediction. The success of these techniques often relies on a large volume of well-defined and high-quality battery test data. On the other hand, most battery developers and research and development (R&D) communities are still following a classical approach to develop batteries, which is running calendar- and/or cycle-aging tests, performing reference performance tests (RPTs), and conducting post-mortem analyses periodically without paying attention to the wealth of data often not collected during the calendar or cycle life aging tests. This sparse data collection approach is time- and resource-intensive, requiring data capture and evaluation of months to years of RPT data to diagnose accurate battery state of performance, health, and safety. Even so, the underlying aging modes and mechanisms can be missed. If collected properly, battery test data during cycling or calendaring can be efficiently combined with ML/AI techniques to create powerful tools in the rapid diagnosis of battery state of performance, health, and safety along with insights into underlying aging modes and mechanisms. In this report, we discuss the importance of effective cycle-by-cycle (CBC) data collection with example case studies. Within a reasonable timeframe, RPT data are often inadequate in capturing many of the crucial battery aging dynamics, which often predominantly show up in CBC test data. Finally, we also show examples of ML/AI techniques that use CBC data in rapid diagnosis and projection of LiB state of health (SOH) to motivate the scientific community in collecting and using CBC data to facilitate expeditious technology development and validation.

25 ENERGY STORAGE↗
DOE OSTI2021

Development of a rapid viability RT-PCR (RV-RT-PCR) method to detect infectious SARS-CoV-2 from swabs

Since the rapid onset of the COVID-19 pandemic, its causative virus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), continues to spread and increase the number of fatalities. To expedite studies on understanding potential surface transmission of the virus and to aid environmental epidemiological investigations, here we developed a rapid viability reverse transcriptase PCR (RV-RT-PCR) method that detects viable (infectious) SARS-CoV-2 from swab samples in <1 day compared to several days required by current gold-standard cell-culture-based methods. The method integrates cell-culture-based viral enrichment in a 96-well plate format with gene-specific RT-PCR-based analysis before and after sample incubation to determine the cycle threshold (C T ) difference (ΔC T ). An algorithm based on ΔC T ≥ 6 representing ~ 2-log or more increase in SARS-CoV-2 RNA following enrichment determines the presence of infectious virus. The RV-RT-PCR method with 2-hr viral infection and 9-hr post-infection incubation periods includes ultrafiltration to concentrate virions, resulting in detection of <50 SARS-CoV-2 virions in swab samples in 17 h (for a batch of 12 swabs), compared to days typically required by the cell-culture-based method. The SARS-CoV-2 RV-RT-PCR method may also be useful in clinical sample analysis and antiviral drug testing, and could serve as a model for developing rapid methods for other viruses of concern.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Rapid, Sensitive, Label-Free Electrical Detection of SARS-CoV-2 in Nasal Swab Samples

Rapid diagnosis of coronavirus disease 2019 (COVID-19) is key for the long-term control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) amid renewed threats of mutated SARS-CoV-2 around the world. Here, we report on an electrical label-free detection of SARS-CoV-2 in nasopharyngeal swab samples directly collected from outpatients or in saliva-relevant conditions by using a remote floating-gate field-effect transistor (RFGFET) with a 2-dimensional reduced graphene oxide (rGO) sensing membrane. RFGFET sensors demonstrate rapid detection (<5 min), a 90.6% accuracy from 8 nasal swab samples measured by 4 different devices for each sample, and a coefficient of variation (CV) < 6%. Also, RFGFET sensors display a limit of detection (LOD) of pseudo-SARS-CoV-2 that is 10 000-fold lower than enzyme-linked immunosorbent assays, with a comparable LOD to that of reverse transcriptionpolymerase chain reaction (RT-PCR) for patient samples. To achieve this, comprehensive systematic studies were performed regarding interactions between SARS-CoV-2 and spike proteins, neutralizing antibodies, and angiotensin-converting enzyme 2, as either a biomarker (detection target) or a sensing probe (receptor) functionalized on the rGO sensing membrane. Finally, taken together, this work may have an immense effect on positioning FET bioelectronics for rapid SARS-CoV-2 diagnostics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Extensive Genome-Wide Phylogenetic Discordance Is Due to Incomplete Lineage Sorting and Not Ongoing Introgression in a Rapidly Radiated Bryophyte Genus

The relative importance of introgression for diversification has long been a highly disputed topic in speciation research and remains an open question despite the great attention it has received over the past decade. Gene flow leaves traces in the genome similar to those created by incomplete lineage sorting (ILS), and identification and quantification of gene flow in the presence of ILS is challenging and requires knowledge about the true phylogenetic relationship among the species. We use whole nuclear, plastid, and organellar genomes from 12 species in the rapidly radiated, ecologically diverse, actively hybridizing genus of peatmoss (Sphagnum) to reconstruct the species phylogeny and quantify introgression using a suite of phylogenomic methods. We found extensive phylogenetic discordance among nuclear and organellar phylogenies, as well as across the nuclear genome and the nodes in the species tree, best explained by extensive ILS following the rapid radiation of the genus rather than by postspeciation introgression. Our analyses support the idea of ancient introgression among the ancestral lineages followed by ILS, whereas recent gene flow among the species is highly restricted despite widespread interspecific hybridization known in the group. Our results contribute to phylogenomic understanding of how speciation proceeds in rapidly radiated, actively hybridizing species groups, and demonstrate that employing a combination of diverse phylogenomic methods can facilitate untangling complex phylogenetic patterns created by ILS and introgression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Ancient Rapid Radiation Explains Most Conflicts Among Gene Trees and Well-Supported Phylogenomic Trees of Nostocalean Cyanobacteria

Prokaryotic genomes are often considered to be mosaics of genes that do not necessarily share the same evolutionary history due to widespread horizontal gene transfers (HGTs). Consequently, representing evolutionary relationships of prokaryotes as bifurcating trees has long been controversial. However, studies reporting conflicts among gene trees derived from phylogenomic data sets have shown that these conflicts can be the result of artifacts or evolutionary processes other than HGT, such as incomplete lineage sorting, low phylogenetic signal, and systematic errors due to substitution model misspecification. Here, we present the results of an extensive exploration of phylogenetic conflicts in the cyanobacterial order Nostocales, for which previous studies have inferred strongly supported conflicting relationships when using different concatenated phylogenomic data sets. We found that most of these conflicts are concentrated in deep clusters of short internodes of the Nostocales phylogeny, where the great majority of individual genes have low resolving power. We then inferred phylogenetic networks to detect HGT events while also accounting for incomplete lineage sorting. Our results indicate that most conflicts among gene trees are likely due to incomplete lineage sorting linked to an ancient rapid radiation, rather than to HGTs. Moreover, the short internodes of this radiation fit the expectations of the anomaly zone, i.e., a region of the tree parameter space where a species tree is discordant with its most likely gene tree. In this work, we demonstrated that concatenation of different sets of loci can recover up to 17 distinct and well-supported relationships within the putative anomaly zone of Nostocales, corresponding to the observed conflicts among well-supported trees based on concatenated data sets from previous studies. Our findings highlight the important role of rapid radiations as a potential cause of strongly conflicting phylogenetic relationships when using phylogenomic data sets of bacteria. We propose that polytomies may be the most appropriate phylogenetic representation of these rapid radiations that are part of anomaly zones, especially when all possible genomic markers have been considered to infer these phylogenies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Three-dimensional nanoscale reduced-angle ptycho-tomographic imaging with deep learning (RAPID)

X-ray ptychographic tomography is a nondestructive method for three dimensional (3D) imaging with nanometer-sized resolvable features. The size of the volume that can be imaged is almost arbitrary, limited only by the penetration depth and the available scanning time. Here we present a method that rapidly accelerates the imaging operation over a given volume through acquiring a limited set of data via large angular reduction and compensating for the resulting ill-posedness through deeply learned priors. The proposed 3D reconstruction method “RAPID” relies initially on a subset of the object measured with the nominal number of required illumination angles and treats the reconstructions from the conventional two-step approach as ground truth. It is then trained to reproduce equal fidelity from much fewer angles. After training, it performs with similar fidelity on the hitherto unexamined portions of the object, previously not shown during training, with a limited set of acquisitions. In our experimental demonstration, the nominal number of angles was 349 and the reduced number of angles was 21, resulting in a x140 aggregate speedup over a volume of 4.48 x 93.18 x 3.92 μm 3 and with (14nm) 3 feature size, i.e. ~ 10 8 voxels. RAPID’s key distinguishing feature over earlier attempts is the incorporation of atrous spatial pyramid pooling modules into the deep neural network framework in an anisotropic way. We found that adjusting the atrous rate improves reconstruction fidelity because it expands the convolutional kernels’ range to match the physics of multi-slice ptychography without significantly increasing the number of parameters.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Image Analysis for Rapid Assessment and Quality-Based Sorting of Corn Stover

Imaging in the visible spectrum is a low-cost tool that can be readily deployed for in-field or over-belt monitoring of biomass quality for bio-refining operations. Rapid image analysis coupled with innovative preprocessing may reduce the impacts of feedstock variability through identification of contaminants or other material attributes to guide selective sorting and quality management. Image analysis was employed to evaluate the quality of corn stover in red-green-blue (RGB) chromatic space. This study used controlled, bench-scale imaging as a proof-of-concept for rapid quality assessment of corn stover based on variations in material attributes, including chemical and physical attributes, that relate to biological degradation and soil contamination. Additionally, logistic regression-based classification algorithms were used to develop a method for biomass screening as a function of biological degradation or soil contamination. This study demonstrated the use of image analysis to extract features from RGB color space to investigate variations in critical material attributes from chemical composition of corn stover. Fourier transform infrared (FT-IR) suggested a correlation between red band intensity and biological degradation, while detailed surface texture analysis was found to distinguish among variations in ash. These insights offer promise for development of a rapid screening tool that could be deployed by farmers for in-field assessment of biomass quality or biorefinery operators for in-line sorting and process optimization.

09 BIOMASS FUELS↗
DOE OSTI2020

The Susceptibility of Juvenile American Shad to Rapid Decompression and Fluid Shear Exposure Associated with Simulated Hydroturbine Passage

Throughout many areas of their native range, American shad (Alosa sapidissima) and other Alosine populations are in decline. Though several conditions have influenced these declines, hydropower facilities have had significant negative effects on American shad populations. Hydropower facilities expose ocean-migrating American shad to physical stressors during passage through hydropower facilities, including strike, rapid decompression, and fluid shear. In this laboratory-based study, juvenile American shad were exposed separately to rapid decompression and fluid shear to determine their susceptibility to these stressors and develop dose–response models. These dose–response relationships can help guide the development and/or operation of hydropower turbines and facilities to reduce the negative effects to American shad. Relative to other species, juvenile American shad have a high susceptibility to both rapid decompression and fluid shear. Reducing or preventing exposure to these stressors at hydropower facilities may be a potential method to assist in the effort to restore American shad populations.

13 HYDRO ENERGY↗
NASA NTRS2023

Interchangeable Use of GNSS and Seismic Data for Rapid Earthquake Characterization: 2021 Chignik Earthquake, Alaska

Earthquake magnitude estimation using peak ground velocities (PGV) derived from 13 Global Navigation Satellite Systems (GNSS) data has shown promise for rapid 14 characterization of damaging earthquakes. Here we examine the feasibility of using 15 GNSS-derived velocity waveforms as interchangeable data for ground motion estimation 16 and other products that typically rely on strong-motion seismic records. Our study 17 compares PGVs derived from high-rate GNSS to those computed from high-rate seismic 18 records (strong-motion and velocity), at co- and closely-located stations. The recent 2021 Manuscript Click here to access/download;Manuscript;Manuscript_Final.docx 2 19 Mw 8.2 Chignik earthquake in Alaska that was recorded on co-located GNSS and strong20 motion sensors provides the perfect opportunity to compare the two data streams and 21 their application in rapid response. The Chignik velocity records appear almost identical 22 at co-located GNSS and strong-motion stations when observed at frequencies < 0.25 Hz. 23 GNSS and strong-motion derived velocity data are further employed to generate rapid 24 estimates of PGV-derived moment magnitudes for the earthquake. The moment 25 magnitude estimates from GNSS and joint GNSS/seismic data are within ~ ±0.4 26 magnitude units (Fang et al., 2020) of the final magnitude (Mw 8.2). ShakeMaps 27 generated for the 2021 Chignik earthquake using GNSS and seismic PGVs show notable 28 agreement between them, and show negligible shifts in PGV contours when co-/closely 29 located GNSS and seismic stations are substituted for one another. Therefore, we posit 30 that GNSS is a powerful alternative or addition to seismic data and vice versa.

Earthquake rapid response↗
DOE OSTI2023

Influence of Molybdenum on Rapid Solidification Microstructure and Microsegregation in Primary Ferrite Solidified Stainless Steel

Due to the widespread use and familiarity of austenitic stainless steels in many industries these alloys are often the first materials used when adapting new processing techniques. The rapid cooling and solidification rates that occur during fusion based additive manufacturing processes like powder bed fusion cause a fundamental shift in the solidification behavior of the material. While the effects that Cr and Ni have on the microstructure have been fairly well documented across a range of solidification conditions, the impact of alloying elements like Mo are not as well understood at rapid solidification rates. For this study, four custom stainless steel alloy feedstocks were made with targeted modification of the Cr and Mo concentrations to maintain a constant Cr/Ni eq ratio of ~1.7. Two-piston splat quenching was used to produce rapidly solidified samples and the solidification mode, phase, and cell size were investigated. Solidification rates were estimated to be between 0.4 and 1.5m/s. A comparison of the microsegregation and partitioning behavior of Cr, Ni and Mo in ferrite solidified material was also performed for the different alloy compositions. Variations of the Mo concentration between each feedstock showed no measurable influence on the solidification/cooling rates, solidification morphology, or the partitioning of Mo. Furthermore, higher concentrations of Mo were found to significantly increase the amount of ferrite phase in the microstructure by suppressing the ferrite to austenite massive transformation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evaluation of the economic implications of varied pressure drawdown strategies generated using a real-time, rapid predictive, multi-fidelity model for unconventional oil and gas wells

Experience has suggested that pressure maintenance in hydraulically fractured reservoirs via lower, more sustained production drawdowns may offer improved cumulative recovery and overall resource extraction efficiency compared to more rapid drawdown approaches aimed at generating high initial production. However, given the inherent variability of oil and natural gas markets, operators pursue production strategies that maximize profitability over resource extraction efficiency. This study focuses on evaluating the implications of contrasting pressure drawdown strategies on the long-term production and resulting economics for a real, producing unconventional gas well in the Marcellus Shale of the Appalachian Basin using a techno-economic analysis approach. Our research combines elements of well-specific horizontal well design, production forecasting, equipment sizing and capital cost estimation, operating cost estimation, and revenue and tax calculations. Gas production forecast outlook scenarios were generated under varying pressure drawdowns using two approaches: 1) a novel physics-informed machine learning workflow and 2) traditional reservoir simulation. A discounted cash flow model was used to evaluate the resulting economic implications for each drawdown scenario—generating output for exploring the coupled effect of factors like the timing and volume of gas production, prevailing economic and market conditions for natural gas, and overall estimated ultimate recovery on profitability metrics such as internal rate of return and net present value. Results show that there is potential to maximize the cumulative gas produced in the specific case study well by employing a lower pressure drawdown. Conversely, the greatest profitability is achieved using rapid drawdown as signified by a small, specific subset of our outlook scenarios. On an averaging basis, we find that the combinations of highest cumulative producing and most profitable scenarios occur under lower drawdowns with long (>40 years) producing timeframes, but require higher relative gas price and lower discounting considerations. Further, the machine learning predictive outlooking capability proved effective for enabling rapid generation of a multitude of scenario forecasts. As a result, a variety of prominent example cases could be generated to strike the balance of greater productivity and economic return given their associated producing features and economic conditions when compared to similar producing scenarios—critical insight that offers improved decision support for unconventional oil and gas operations.

42 ENGINEERING↗
DOE OSTI2021

Bayesian learning for rapid prediction of lithium-ion battery-cycling protocols

Advancing lithium-ion battery technology requires the optimization of cycling protocols. A new data-driven methodology is demonstrated for rapid, accurate prediction of the cycle life obtained by new cycling protocols using a single test lasting only 3 cycles, enabling rapid exploration of cycling protocol design spaces with orders of magnitude reduction in testing time. We achieve this by combining lifetime early prediction with a hierarchical Bayesian model (HBM) to rapidly predict performance distributions without the need for extensive repetitive testing. The methodology is applied to a comprehensive dataset of lithium-iron-phosphate/graphite comprising 29 different fast-charging protocols. HBM alone provides high protocol-lifetime prediction performance, with 6.5% of overall test average percent error, after cycling only one battery to failure. Here, by combining HBM with a battery lifetime prediction model, we achieve a test error of 8.8% using a single 3-cycle test. In addition, the generalizability of the HBM approach is demonstrated for lithium-manganese-cobalt-oxide/graphite cells.

25 ENERGY STORAGE↗
DOE OSTI2024

Multiplicity dependence of ϒ production at forward rapidity in pp collisions at $\sqrt{s}$ = 13 TeV

The measurement of ϒ(1S), ϒ(2S), and ϒ(3S) yields as a function of the charged-particle multiplicity density, d N ch /d η , using the ALICE experiment at the LHC, is reported in pp collisions at √s = 13 TeV. The Υ meson yields are measured at forward rapidity (2.5 < y < 4) in the dimuon decay channel, whereas the charged-particle multiplicity is defined at central rapidity (| η | <1). Both quantities are divided by their average value in minimum bias events to compute the self-normalized quantities. The increase of the self-normalized ϒ(1S), ϒ(2S), and ϒ(3S) yields is found to be compatible with a linear scaling with the self-normalized d N ch /d η , within the uncertainties. The self-normalized yield ratios of excited-to-ground ϒ states are compatible with unity within uncertainties. Similarly, the measured double ratio of the self-normalized ϒ(1S) to the self-normalized J/ ψ yields, both measured at forward rapidity, is compatible with unity for self-normalized charged-particle multiplicities beyond one. The measurements are compared with theoretical predictions incorporating initial or final state effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Υ production and nuclear modification at forward rapidity in Pb–Pb collisions at $\sqrt{S_{NN}}$ = 5.02 TeV

The production of Υ mesons in Pb–Pb collisions at a centre-of-mass energy per nucleon pair $\sqrt{S_{NN}}$ = 5.02 TeV is measured with the muon spectrometer of the ALICE detector at the LHC. The yields as well as the nuclear modification factors are determined in the forward rapidity region 2.5 < y < 4.0, as a function of rapidity, transverse momentum and collision centrality. The results show that the production of the Υ(1S) meson is suppressed by a factor of about three with respect to the production in proton– proton collisions. For the first time, a significant signal for the Υ(2S) meson is observed at forward rapidity, indicating a suppression stronger by about a factor 2–3 with respect to the ground state. The measurements are compared with transport, hydrodynamic, comover and statistical hadronisation model calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗