Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “k mean”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Production of neutron-rich heavy nuclei in deep-inelastic 208 Pb + 208 Pb collisions within the stochastic mean-field theory

In deep-inelastic collisions of heavy nuclei, reaction products with a wide range of mass and charge are produced. Such collisions been considered as a possible way to produce superheavy nuclei, as an alternative to fusion reactions. To provide reliable theoretical predictions, it is desired to develop microscopic approaches that correctly and accurately describe nucleon transfer processes in dissipative collisions of heavy nuclei. The purpose of the present work is (1) to investigate the mechanism of nucleon transfers in dissipative collisions of two heavy nuclei, and (2) to explore possible pathways to produce neutron-rich heavy nuclei, through detailed theoretical analyses of fluctuations and correlations in nucleon transfers in 208 Pb + 208 Pb reactions. Three-dimensional time-dependent Hartree-Fock (TDHF) calculations are performed for the collisions of 208 Pb + 208 Pb at 𝐸 c.m. = 832, 936, and 1040 MeV, using the Skyrme SLy4d energy density functional. To calculate fluctuations and correlations in nucleon transfers, we employ the stochastic mean-field (SMF) theory, and the results are compared with another theoretical framework currently available, the time-dependent random phase approximation (TDRPA). Primary and secondary production cross sections are calculated with the SMF theory combined with a statistical model, GEMINI ++ . Using information of nucleon flow across a neck of colliding nuclei in TDHF calculations, we solve quantal diffusion equations for fluctuations and correlations in nucleon transfers based on the SMF theory. From the SMF calculations, we obtain the time evolution of diffusion coefficients as well as fluctuations and correlations in nucleon transfers for a range of initial orbital angular momenta. We compare the results of the SMF calculations with those of TDRPA, showing that TDRPA tends to predict substantially larger fluctuations and correlations in strongly damped collisions of heavy nuclei, which exhibit complex initial angular momentum dependence, while the SMF results provide almost constant (stable) values. Using the obtained fluctuations and correlations, we calculate primary and secondary production cross sections for the 208 Pb + 208 Pb collisions. From the results, we find that both lighter and heavier reaction products as compared to 208 Pb are produced for a wide region in the 𝑁−𝑍 plane as primary products, thanks to the quantal diffusion mechanism in the dissipative collisions. However, we show that cross sections for production of heavy nuclei with 𝑍 ≳ 90 or 𝑁 ≳ 135 are washed out due to secondary particle evaporation and/or fission processes. On the other hand, we find that there remain sizable cross sections for production of neutron-rich nuclei along 𝑁 = 126 with 𝑍< 82, even after secondary disintegration processes. We demonstrate that the secondary production cross sections depend weakly on incident energies, but lower (higher) energy is slightly preferred for production of nuclei with smaller (larger) atomic numbers as compared to 𝑍 = 82. Here, based on the microscopic SMF calculations, it has been shown that deep-inelastic collisions of heavy nuclei, such as 208 Pb + 208 Pb examined in this study, can be a promising means to produce neutron-rich heavy nuclei along 𝑁=126. Discrepancies between the SMF and TDRPA approaches are left unsolved for future investigations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Development of an Efficient Conjugate Heat Transfer Modeling Framework to Optimize Mixing-Limited Combustion of Ethanol in a Diesel Engine

Mixing controlled combustion of alcohol fuels has been identified as a promising technology based on their low propensity for particulate and NOx production, but the higher heats of vaporization and auto-ignition temperatures of these fuels make their direct use in diesel engine architectures a challenge. To realize the potential of alcohol-fueled combustion, a computational fluid dynamics (CFD) modeling framework is developed, validated, and exercised to identify designs that maximize engine thermal efficiency. To evaluate the use of thermal barrier coatings (TBCs), a simplified one-dimensional (1D) conjugate heat transfer (CHT) modeling framework is employed. The addition of the 1D CHT model only increases the computational expense by 15% relative to traditional approaches, yet offers more accurate heat transfer predictions over constant temperature boundary conditions. The validated model is then used to explore a range of injector orientations and piston bowl geometries. Using a design of experiments (DoE) approach, several designs were identified that improved fuel-air mixing, shortened the combustion duration, and increased thermal efficiency. The most promising design was fabricated and tested in a Caterpillar 1Y3700 single-cylinder oil test engine (SCOTE). Engine testing confirmed the findings from the CFD simulations and found that the co-optimized injector and piston bowl design yielded over 2-percentage point increase in thermal efficiency at the same equivalence ratio (0.96) and over 6-percentage point increase at the same engine load (10.1 bar indicated mean effective pressure (IMEP)), while satisfying design constraints for peak pressure and maximum pressure rise rate.

Magnotti, Gina M.↗
DOE OSTI2024

Exploring 2D X-ray diffraction phase fraction analysis with convolutional neural networks: Insights from kinematic-diffraction simulations

Abstract Deep-learning models are effective for analyzing the complex information in 2D X-ray diffraction (XRD) patterns. Accurately collecting parameters of the material sample is crucial during model training, significantly impacting model performance. In this study, we employ a kinematic-diffraction simulator to generate simulated 2D XRD patterns for Ti–6Al–4V alloy, allowing precise control of sample parameters. These simulated patterns are used to train convolutional neural networks, predicting $$\upbeta$$ β -phase volume fractions. The training data set consists exclusively of 2D XRD patterns with pure $$\upalpha$$ α - or pure $$\upbeta$$ β -phase, while the testing set incorporates patterns with intermediate phase volume fraction. In particular, we investigate how the architectures of the model influence prediction reliability and computational performance. Experimental results reveal that, with appropriate training, the convolutional neural network accurately detects intermediate phase volume fractions even trained with only pure-phase patterns, achieving a mean square error accuracy of $$9.4 \times 10^{-4}$$ 9.4 × 10 - 4 . Graphical abstract

Yue, Weiqi↗
DOE OSTI2024

Global 1 km land surface parameters for kilometer-scale Earth system modeling

Earth system models (ESMs) are progressively advancing towards the kilometer scale (“k-scale”). However, the surface parameters for land surface models (LSMs) within ESMs running at the k-scale are typically derived from coarse-resolution and outdated datasets. This study aims to develop a new set of global land surface parameters with a resolution of 1 km for multiple years from 2001 to 2020, utilizing the latest and most accurate available datasets. Specifically, the datasets consist of parameters related to land use and land cover, vegetation, soil, and topography. Differences between the newly developed 1 km land surface parameters and conventional parameters emphasize their potential for higher accuracy due to the incorporation of the most advanced and latest data sources. To demonstrate the capability of these new parameters, we conducted 1 km resolution simulations using the E3SM Land Model version 2 (ELM2) over the contiguous United States. Our results demonstrate that land surface parameters contribute to significant spatial heterogeneity in ELM2 simulations of soil moisture, latent heat, emitted longwave radiation, and absorbed shortwave radiation. On average, about 31 % to 54 % of spatial information is lost by upscaling the 1 km ELM2 simulations to a 12 km resolution. Using eXplainable Machine Learning (XML) methods, the influential factors driving the spatial variability and spatial information loss of ELM2 simulations were identified, highlighting the substantial impact of the spatial variability and information loss of various land surface parameters, as well as the mean climate conditions. The comparison against four benchmark datasets indicates that ELM generally performs well in simulating soil moisture and surface energy fluxes. The new land surface parameters are tailored to meet the emerging needs of k-scale LSM and ESM modeling with significant implications for advancing our understanding of water, carbon, and energy cycles under global change. The 1 km land surface parameters are publicly available at https://doi.org/10.5281/zenodo.10815170 (Li et al., 2024).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Theoretical description of atomtronic Josephson junctions in an optical lattice

Experimental realizations of “atomtronic” Josephson junctions have recently been created in annular traps in relative rotation with respect to potential barriers that generate the weak links. If these devices are additionally subjected to an optical lattice potential, then they can incorporate strong-coupling Mott physics within the design, which can modify the behavior and can allow for interesting new configurations of barriers and of superfluid flow patterns. We examine theoretically the behavior of a Bose superfluid in an optical lattice in the presence of an annular trap and a barrier across the annular region which acts as a Josephson junction. As the superfluid is rotated, circulating super-currents appear. Beyond a threshold superfluid velocity, phase slips develop, which generate vortices. We use a finite temperature strong-coupling expansion about the mean-field solution of the Bose Hubbard model to calculate various properties of such devices. Additionally, we discuss some of the rich behavior that can result when there are Mott regions within the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Estimating Fine-Resolution Shortwave Broadband Albedo of Croplands from Harmonized Landsat and Sentinel-2 Data

Altered surface albedo due to land-cover conversions and management is a significant driver of global climate change. Albedo can be directly measured at ground stations, and remote sensing data can be used to scale-up albedo values to regional and global levels. Some previous studies have retrieved fine-resolution (10–30 m) instantaneous albedo and coarse-resolution (500–1000 m) daily mean albedo from remote sensing data, but they all required the input of Moderate Resolution Imaging Spectroradiometer (MODIS) albedo information at 500-m resolution, and none have assembled both instantaneous and daily albedo based exclusively on fine-resolution satellite data. Here, to address this issue, we compiled 387 instantaneous and 346 daily albedo records using field net radiometer measurements from the bioenergy croplands at the W. K. Kellogg Biological Station in southwest Michigan. We then connected these albedo records with a suite of variables derived from harmonized Landsat and Sentinel-2 data through two machine learning algorithms (random forest regression and extreme gradient boosting) to retrieve clear-sky instantaneous and daily shortwave broadband albedo. The performance statistics indicate reasonable accuracy of model results [root-mean-square error (RMSE)] around or below 0.03 except for snow-covered surfaces), suggesting that the retrieval of both instantaneous and daily albedo based exclusively on fine-resolution satellite data is promising. To facilitate the use of fine-resolution albedo products at the global level, future efforts need to include more albedo records of diverse surface cover types, as well as to accurately model daily albedo for cloudy days to address the “clear-sky bias.”

Harmonized Landsat and Sentinel-2↗
DOE OSTI2021

Differentiating Hund from Mott physics in a three-band Hubbard-Hund model: Temperature dependence of spectral, transport, and thermodynamic properties

We study the interplay between Mott physics, driven by Coulomb repulsion U, and Hund physics, driven by Hund's coupling J, for a minimal model for Hund metals, the orbital-symmetric three-band Hubbard-Hund model (3HHM) for a lattice filling of 1/3. Hund-correlated metals are characterized by spin-orbital separation (SOS), a Hund's-rule-induced two-stage Kondo-type screening process, in which spin screening occurs at much lower energy scales than orbital screening. By contrast, in Mott-correlated metals, lying close to the phase boundary of a metal-insulator transition, the SOS window becomes negligibly small and the Hubbard bands are well separated. Using dynamical mean-field theory and the numerical renormalization group as real-frequency impurity solver, we identify numerous fingerprints distinguishing Hundness from Mottness in the temperature dependence of various physical quantities. Furthermore, These include ARPES-type spectra, the local self-energy, static local orbital and spin susceptibilities, resistivity, thermopower, and lattice and impurity entropies. Our detailed description of the behavior of these quantities within the context of a simple model Hamiltonian will be helpful for distinguishing Hundness from Mottness in experimental and theoretical studies of real materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Crystal structure, compressibility, and thermal expansion of uranium mononitride

The behavior of the uranium mononitride (UN) crystal structure at nonambient conditions is disputed, with studies proposing various mutually exclusive distortions and transformations of the conventional face-centered-cubic structure at extreme temperatures and pressures. Here, in this study, we investigated the UN lattice with diamond anvil cell x-ray diffraction experiments at pressures up to 92 GPa and with density functional theory calculations at temperatures up to 1000 K and pressures up to 90 GPa. We determined that while the UN structure is nearly cubic at ambient conditions, its lattice angle (𝛼) varies as a function of pressure and temperature, meaning its structure can be more precisely described as face-centered-rhombohedral with 𝛼 ≈ 90∘. Over the range of conditions we investigated, UN exhibits a single, isostructural phase transition at ≈ 35 GPa, where 𝛼 collapses to ≈ 86°. Measurements and calculations agree that the compressibility of UN increases significantly beyond this transition, with the bulk modulus falling from ≈ 200 GPa in the low-pressure phase to 121 ± 3 GPa (according to calculations) or 58 ± 4 GPa (according to measurements) in the high-pressure phase. Our measurements also allowed us to constrain the bulk modulus of 𝛼−U 2 ⁢N 3 to 240 ± 10 GPa.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Adiabatic expansion cooling of antihydrogen

Magnetically trapped antihydrogen atoms can be cooled by expanding the volume of the trap in which they are confined. We report a proof-of-principle experiment in which antiatoms are deliberately released from expanded and static traps. Antiatoms escape at an average trap depth of 0.08 ± 0.01 K (statistical errors only) from the expanded trap while they escape at average depths of 0.22 ± 0.01 and 0.17 ± 0.01 K from two different static traps. (We employ temperature-equivalent energy units.) Detailed simulations qualitatively agree with the escape times measured in the experiment and show a decrease of 38 % (statistical error < 0.2 % ) in the mean energy of the population after the trap expansion without significantly increasing antiatom loss compared to typical static confinement protocols. This change is bracketed by the predictions of one-dimensional and three-dimensional semianalytic adiabatic expansion models. These experimental, simulational, and model results are consistent with obtaining an adiabatically cooled population of antihydrogen atoms that partially exchanged energy between axial and transverse degrees of freedom during the trap expansion. This result is important for future antihydrogen gravitational experiments which rely on adiabatic cooling, and it will enable antihydrogen cooling beyond the fundamental limits of laser cooling. Published by the American Physical Society 2024

Ahmadi, M.↗
DOE OSTI2022

Pressure effect on magnetism and valence in ferromagnetic superconductor Eu(Fe 0.75 Ru 0.25 ) 2 As 2

Eu(Fe 0.75 Ru 0.25 ) 2 As 2 is an intriguing system with unusual coexistence of superconductivity and ferromagnetism, providing a unique platform to study the nature of such coexistence. To establish a magnetic phase diagram, time-domain synchrotron Mössbauer experiments in 151 Eu have been performed on a single crystalline Eu(Fe 0.75 Ru 0.25 ) 2 As 2 sample under hydrostatic pressures and at low temperatures. Upon compression the magnetic ordering temperature increases sharply from 20 K at ambient pressure, reaching ~49 K at 10.1GPa. With further compression, the magnetic order is suppressed and eventually collapses. Isomer shift values from Mössbauer measurements and x-ray absorption spectroscopy data at Eu L 3 edge show that pressure drives Eu ions to a homogeneous intermediate valence state with mean valence of ~2.4 at 27.4 GPa, possibly responsible for the suppression of magnetism. Synchrotron powder x-ray diffraction experiment reveals a tetragonal to collapsed-tetragonal structural transition around 5 GPa, a lower transition pressure than in the parent compound. Furthermore, these results provide guidance to further work investigating the interplay of superconductivity and magnetism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Isotope effects on energy transport in the core of ASDEX-Upgrade tokamak plasmas: Turbulence measurements and model validation

Design and operation of future tokamak fusion reactors using a deuterium–tritium 50:50 mix requires a solid understanding of how energy confinement properties change with ion mass. This study looks at how turbulence and energy transport change in L-mode plasmas in the ASDEX Upgrade tokamak when changing ion species between hydrogen and deuterium. For this purpose, both experimental turbulence measurements and modeling are employed. Local measurements of ion-scale (with wavevector of fluctuations perpendicular to the B-field k⊥< 2 cm−1, k⊥ρs< 0.2, where ρs is the ion sound Larmor radius using the deuterium ion mass) electron temperature fluctuations have been performed in the outer core (normalized toroidal flux ρTor=0.65−0.8) using a multi-channel correlation electron cyclotron emission diagnostic. Lower root mean square perpendicular fluctuation amplitudes and radial correlation lengths have been measured in hydrogen vs deuterium. Measurements of the cross-phase angle between a normal-incidence reflectometer and an ECE signal were made to infer the cross-phase angle between density and temperature fluctuations. The magnitude of the cross-phase angle was found larger (more out-of-phase) in hydrogen than in deuterium. TRANSP power balance simulations show a larger ion heat flux in hydrogen where the electron-ion heat exchange term is found to play an important role. These experimental observations were used as the basis of a validation study of both quasilinear gyrofluid trapped gyro-Landau fluid-SAT2 and nonlinear gyrokinetic GENE codes. Linear solvers indicate that, at long wavelengths (k⊥ρs<1), energy transport in the deuterium discharge is dominated by a mixed ion-temperature-gradient (ITG) and trapped-electron mode turbulence while in hydrogen transport is exclusively and more strongly driven by ITG turbulence. The Ricci validation metric has been used to quantify the agreement between experiments and simulations taking into account both experimental and simulation uncertainties as well as four different observables across different levels of the primacy hierarchy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

An efficient LC-MS method for isomer separation and detection of sugars, phosphorylated sugars, and organic acids

Abstract Assessing central carbon metabolism in plants can be challenging due to the dynamic range in pool sizes, with low levels of important phosphorylated sugars relative to more abundant sugars and organic acids. Here, we report a sensitive liquid chromatography–mass spectrometry method for analysing central metabolites on a hybrid column, where both anion-exchange and hydrophilic interaction chromatography (HILIC) ligands are embedded in the stationary phase. The liquid chromatography method was developed for enhanced selectivity of 27 central metabolites in a single run with sensitivity at femtomole levels observed for most phosphorylated sugars. The method resolved phosphorylated hexose, pentose, and triose isomers that are otherwise challenging. Compared with a standard HILIC approach, these metabolites had improved peak areas using our approach due to ion enhancement or low ion suppression in the biological sample matrix. The approach was applied to investigate metabolism in high lipid-producing tobacco leaves that exhibited increased levels of acetyl-CoA, a precursor for oil biosynthesis. The application of the method to isotopologue detection and quantification was considered through evaluating 13C-labeled seeds from Camelina sativa. The method provides a means to analyse intermediates more comprehensively in central metabolism of plant tissues.

Plant Sciences↗
DOE OSTI2023

Magnetoresistance anomaly during the electrical triggering of a metal-insulator transition

Phase separation naturally occurs in a variety of magnetic materials and it often has a major impact on both electric and magnetotransport properties. In resistive switching systems, phase separation can be created on demand by inducing local switching, which provides an opportunity to tune the electronic and magnetic state of the device by applying voltage. Here we explore the magnetotransport properties in the ferromagnetic oxide La 0.7 ⁢Sr 0.3 ⁢MnO 3 (LSMO) during the electrical triggering of an intrinsic metal-insulator transition (MIT), which produces volatile resistive switching. This switching occurs in a characteristic spatial pattern, i.e., the formation of a high-resistance barrier perpendicular to the current flow, enabling an electrically actuated ferromagnetic-paramagnetic-ferromagnetic phase separation. At the threshold voltage of the MIT triggering, both anisotropic and colossal magnetoresistances exhibit anomalies including a large increase in magnitude and a sign flip. Computational analysis revealed that these anomalies originate from the coupling between the switching-induced phase separation state and the intrinsic magnetoresistance of LSMO. Furthermore, this work demonstrates that driving the MIT material into an out-of-equilibrium resistive switching state provides the means for electrical control of the magnetotransport phenomena.

Complex oxides↗
DOE OSTI2023

Hanford Double Shell Waste Tank Corrosion Studies (Final Report)

For fiscal year (FY) 2022, the Savannah River National Laboratory (SRNL) focused on two experimental tasks related to Hanford Double Shell Tank (DST) chemistry and integrity. The first task focused on understanding risk of corrosion due to formation of either continuous layers or discrete patches of solids on the tanks' inner sidewalls and bottoms. The tank bottom solids contact corrosion testing focused on studying the effects of forming a dry adherent solids layer on a carbon steel substrate. Long-term exposure tests and electrochemical tests were performed to investigate the effect of drying (i.e., removing water) from the solids phase. The second task focused on corrosion of the exterior of the secondary liner. In previous years, vapor corrosion inhibitors (VCIs) were investigated as a means of mitigating corrosion of the exterior of the secondary liner. During FY22 the utilization of nitrogen was explored as a means of corrosion mitigation. The corrosion test results with nitrogen were compared with the corrosion mitigation performance of the VCIs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Thermoradiative energy conversion in infrared interband cascade InAs/GaSb/AlInSb/GaSb type-II superlattice diodes

Thermoradiative energy conversion presents a means for the direct conversion of thermal energy through radiative transfer to a cold scene. However, much of the study of thermoradiative principles has been based on theory and simulations, with only sparse reports on the experimental demonstration of the concept. This work studies thermoradiative energy conversion in InAs/GaSb/AlInSb/GaSb type-II superlattice cascade devices. The devices exhibit a cutoff wavelength of 3.2 μm at 300 K, corresponding to a bandgap of 0.39 eV. Testing under a temperature-controlled chamber and scene demonstrates a maximum power density of 2.9 mW/m2 at a cell temperature of 121 °C. It is consistent with expected values for device operation limited by Shockley–Read–Hall non-radiative recombination. This result is a significant step in providing an experimental demonstration of thermoradiative energy conversion and a means to characterize cell performance, providing a foundation for further development to achieve practical values for power generation.

Islam, Md Toriqul (ORCID:0000000249871320)↗
DOE OSTI2023

Multiplicity and rapidity dependence of $\textrm{K}^{*}(\mathrm {{\textbf {892}}})^{0}$ and $\mathrm {\phi ({\textbf {1020}})}$ production in p–Pb collisions at $\sqrt{s_{\textrm{NN}}} =$ 5.02 TeV

The transverse-momentum (p T ) spectra of K*(892) 0 and Φ(1020) measured with the ALICE detector up to p T = 16 GeV/c in the rapidity range -1.2 < y < 0.3, in p–Pb collisions at the center-of-mass energy per nucleon–nucleon collision $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV are presented as a function of charged particle multiplicity and rapidity. The measured p T distributions show a dependence on both multiplicity and rapidity at low p T whereas no significant dependence is observed at high p T . A rapidity dependence is observed in the p T -integrated yield (dN/dy), whereas the mean transverse momentum ($\langle$p T $\rangle$) shows a flat behavior as a function of rapidity. The rapidity asymmetry (Y asym ) at low p T (< 5 GeV/c) is more significant for higher multiplicity classes. At high p T , no significant rapidity asymmetry is observed in any of the multiplicity classes. Both K*(892) 0 and Φ(1020) show similar Y asym . The nuclear modification factor (Q CP ) as a function of p T shows a Cronin-like enhancement at intermediate p T , which is more prominent at higher rapidities (Pb-going direction) and in higher multiplicity classes. At high p T (> 5 GeV/c), the Q CP values are greater than unity and no significant rapidity dependence is observed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Characterization of Noise in CMOS Ring Oscillators at Cryogenic Temperatures

Allan deviation provides a means to characterize the time-dependence of noise in oscillators and potentially identify the source characteristics. Measurements on a 130 nm, 7-stage ring oscillator show that the Allan deviation declines from 300 K to 150 K as expected, but surprisingly increases from 150 K to 11 K. At low temperatures, the measured Allan deviation can be well fit using a few random telegraph noise (RTN) sources over the range of a few kilohertz to a few gigahertz. Further, the RTN characteristics evolve to reveal an enhanced role in low-frequency noise at lower temperatures.

47 OTHER INSTRUMENTATION↗