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At least 721 records · Page 40

Global quark spin correlations in relativistic heavy ion collisions

The observation of the vector meson’s global spin alignment by the STAR Collaboration reveals that strong spin correlations may exist for quarks and antiquarks in relativistic heavy-ion collisions in the normal direction of the reaction plane. We propose a systematic method to describe such correlations in the quark matter. We classify them as local and long range quark spin correlations in the system. We show in particular that the effective quark spin correlations contain the genuine spin correlations originated directly from the dynamical process as well as those induced by averaging over other degrees of freedom. We also show that such correlations can be studied by measuring the vector meson’s spin density matrix and hyperon-hyperon and hyperon-anti-hyperon spin correlations. We present the relationships between these measurable quantities and spin correlations of quarks and antiquarks. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Direct observations of shape fluctuation in long-time atomistic simulations of metallic nanoclusters

Metallic nanoclusters are functional materials whose unique physical and chemical properties are sensitively controlled by their shapes and structures. An in-depth understanding of their morphological stability is therefore of crucial importance. It has been well documented by transmission electron microscopy (TEM) studies that metallic nanoclusters can interconvert between different isomers. However, the relevant mechanisms remain elusive because the timescales of such shape fluctuations are too short to be resolved experimentally and yet too long for conventional atomistic simulations. By employing massively parallel accelerated molecular dynamics (AMD) simulations reaching timescales of milliseconds, here we provide a clear description of the dynamical processes leading to shape fluctuation in metallic nanoclusters of platinum, silver, copper, and gold at different sizes and temperatures. In all these materials, direct transformations between face-centered-cubic and fivefold symmetric structures (decahedron or icosahedron) are observed away from the melting point. These transitions occur following either a slip-mediated twinning mechanism or a surface-reconstruction driven process. The identified pathways are shown to be reversible, allowing for genuine shape fluctuation processes that do not involve melting or other external factors.

36 MATERIALS SCIENCE↗

Distributed X-ray photon correlation spectroscopy data reduction using Hadoop MapReduce

Multi-speckle X-ray photon correlation spectroscopy (XPCS) is a powerful technique for characterizing the dynamic nature of complex materials over a range of time scales. XPCS has been successfully applied to study a wide range of systems. Recent developments in higher-frame-rate detectors, while aiding in the study of faster dynamical processes, creates large amounts of data that require parallel computational techniques to process in near real-time. Here, an implementation of the multi-tau and two-time autocorrelation algorithms using the Hadoop MapReduce framework for distributed computing is presented. In conclusion, the system scales well with regard to the increase in the data size, and has been serving the users of beamline 8-ID-I at the Advanced Photon Source for near real-time autocorrelations for the past five years.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

In situ synchrotron X-ray total scattering measurements and analysis of colloidal CsPbX 3 nanocrystals during flow synthesis

In situ X-ray scattering measurements of CsPbX 3 (X = Cl, Br, I) nanocrystal formation and halide exchange at NSLS-II beamlines were performed in an automated flow reactor. Total scattering measurements were performed at the 28-ID-2 (XPD) beamline and small-angle X-ray scattering at the 16-ID (LiX) beamline. Nanocrystal structural parameters of interest, including size, size distribution and atomic structure, were extracted from modeling the total scattering data. The results highlight the potential of these beamlines and the measurement protocols described in this study for studying dynamic processes of colloidal nanocrystal synthesis in solution with timescales on the order of seconds.

nucleation↗

Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multi-phase and multi-field coupling and large time delay occur during its operation. In BF operation, the molten iron temperature (MIT) as well as Si, P and S contents of molten iron are the most essential molten iron quality (MIQ) indices, whose measurement, modeling and control have always been important issues in metallurgic engineering and automation field. This paper develops a novel data-driven nonlinear state space modeling for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques. First, to improve modeling efficiency, a data-driven hybrid method combining canonical correlation analysis and correlation analysis is proposed to identify the most influential controllable variables as the modeling inputs from multitudinous factors would affect the MIQ indices. Then, a Hammerstein model for the prediction of MIQ indices is established using the LS-SVM based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method to fit the complex nonlinear kernel function. Compared to the original Hammerstein model, this simplified model can not only significantly reduce the computational complexity, but also has almost the same reliability and accuracy for a stable prediction of MIQ indices. Last, in order to verify the practicability of the developed model, it is applied in designing a genetic algorithm based nonlinear predictive controller for multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approach.

Blast furnace (BF)↗

Rapid assessment of beech leaf disease in Fagus sylvatica buds

Abstract The European beech (Fagus sylvatica) is threatened by the foliar nematodeLitylenchus crenataesubsp.mccannii(Lcm), the causal agent of beech leaf disease (BLD). Thus far, the majority of studies regarding BLD have focused on American beech (F. grandifolia). To better determine the impact of Lcm in buds of European beech, a total of 54 buds were collected from naturally symptomatic trees. Here, we characterized for the first time the bud scale morphology of two different cultivars ofF. sylvaticainfected with Lcm. Detailed observations of asymptomatic and symptomatic bud scales provided insight into the physical changes and arrangements of cells in the bud scale, shedding light on the dynamic processes occurring during Lcm infection. In addition, we evaluated the suitability of using the bud scale morphology for the early detection of BLD and Lcm in naturally infected buds. The distinct cellular arrangement of symptomatic bud scales cells (i.e., asymmetric pattern of enlarged cells) provides a rapid and visual, user‐friendly methodology to prematurely diagnose BLD symptoms within the buds, as well as the detection of associated nematodes.

Forestry↗

From pools to flow: The PROMISE framework for new insights on soil carbon cycling in a changing world

Soils represent the largest terrestrial reservoir of organic carbon, and the balance between soil organic carbon (SOC) formation and loss will drive powerful carbon-climate feedbacks over the coming century. To date, efforts to predict SOC dynamics have rested on pool-based models, which assume classes of SOC with internally homogenous physicochemical properties. However, emerging evidence suggests that soil carbon turnover is not dominantly controlled by the chemistry of carbon inputs, but rather by restrictions on microbial access to organic matter in the spatially heterogeneous soil environment. The dynamic processes that control the physicochemical protection of carbon translate poorly to pool-based SOC models; as a result, we are challenged to mechanistically predict how environmental change will impact movement of carbon between soils and the atmosphere. In this study, we propose a novel conceptual framework to explore controls on belowground carbon cycling: Probabilistic Representation of Organic Matter Interactions within the Soil Environment (PROMISE). In contrast to traditional model frameworks, PROMISE does not attempt to define carbon pools united by common thermodynamic or functional attributes. Rather, the PROMISE concept considers how SOC cycling rates are governed by the stochastic processes that influence the proximity between microbial decomposers and organic matter, with emphasis on their physical location in the soil matrix. We illustrate the applications of this framework with a new biogeochemical simulation model that traces the fate of individual carbon atoms as they interact with their environment, undergoing biochemical transformations and moving through the soil pore space. We also discuss how the PROMISE framework reshapes dialogue around issues related to SOC management in a changing world. We intend the PROMISE framework to spur the development of new hypotheses, analytical tools, and model structures across disciplines that will illuminate mechanistic controls on the flow of carbon between plant, soil, and atmospheric pools.

54 ENVIRONMENTAL SCIENCES↗

Learning the solution operator of parametric partial differential equations with physics-informed DeepONets

Partial differential equations (PDEs) play a central role in the mathematical analysis and modeling of complex dynamic processes across all corners of science and engineering. Their solution often requires laborious analytical or computational tools, associated with a cost that is markedly amplified when different scenarios need to be investigated, for example, corresponding to different initial or boundary conditions, different inputs, etc. In this work, we introduce physics-informed DeepONets, a deep learning framework for learning the solution operator of arbitrary PDEs, even in the absence of any paired input-output training data. We illustrate the effectiveness of the proposed framework in rapidly predicting the solution of various types of parametric PDEs up to three orders of magnitude faster compared to conventional PDE solvers, setting a previously unexplored paradigm for modeling and simulation of nonlinear and nonequilibrium processes in science and engineering.

97 MATHEMATICS AND COMPUTING↗

Volcanic forcing degrades multiyear-to-decadal prediction skill in the tropical Pacific

Volcanic aerosol forcing can affect global climate, but its role in climate prediction remains poorly understood. We isolate the impact of volcanic eruptions on multiyear-to-decadal climate prediction skill by comparing two suites of initialized decadal hindcasts conducted with and without historical volcanic forcing. Unexpectedly, the inclusion of volcanic forcing in the prediction system significantly degrades the forecast skill of detrended multiyear-to-decadal sea surface temperature (SST) variability in the central-eastern tropical Pacific. The ensemble mean hindcasts produce multiyear-to-decadal tropical Pacific SST cooling in response to large tropical volcanic eruptions through thermodynamic and El Niño–Southern Oscillation (ENSO)–like dynamic processes. However, in observations, these eruptions coincided with tropical Pacific warming, which is well predicted by the no-volcano hindcasts and, hence, is likely related to internal climate variability. Improved model representation of volcanic response and its interaction with internal climate variability is required to advance prediction of tropical Pacific decadal variability and associated global impacts.

54 ENVIRONMENTAL SCIENCES↗

Characterization, comparison, and optimization of lattice light sheets

Lattice light sheet microscopy excels at the noninvasive imaging of three-dimensional (3D) dynamic processes at high spatiotemporal resolution within cells and developing embryos. Recently, several papers have called into question the performance of lattice light sheets relative to the Gaussian sheets most common in light sheet microscopy. Here, we undertake a theoretical and experimental analysis of various forms of light sheet microscopy, which demonstrates and explains why lattice light sheets provide substantial improvements in resolution and photobleaching reduction. The analysis provides a procedure to select the correct light sheet for a desired experiment and specifies the processing that maximizes the use of all fluorescence generated within the light sheet excitation envelope for optimal resolution while minimizing image artifacts and photodamage. We also introduce a new type of “harmonic balanced” lattice light sheet that improves performance at all spatial frequencies within its 3D resolution limits and maintains this performance over lengthened propagation distances allowing for expanded fields of view.

59 BASIC BIOLOGICAL SCIENCES↗

Visualizing the strong field–induced molecular breakup of C 60 via x-ray diffraction

Laser-driven dynamics in polyatomic molecules poses a complex many-body problem. Understanding intense light-matter interaction is crucial for steering intramolecular quantum dynamical processes. Here, we record time-resolved x-ray diffraction images of C 60 molecules during and after their interaction with intense near-infrared fields, giving direct access to structural changes of the molecules and their fragmentation in real time. Tuning the intensity of the excitation pulses, we uncover a transition from a weak-field regime of excited but stable molecules to a high-field regime dominated by Coulomb explosion. In the transition region, the molecules expand by up to 50% of their initial size within just 140 fs, with major fragmentation only setting in afterward. This work demonstrates that x-ray diffractive imaging is capable of retrieving time-resolved structural information of large molecules reshaped by intense laser fields. Laser-driven fragmentation is a first step toward observing molecular processes modified by laser fields of increasing intensity.

Schnorr, Kirsten [Paul Scherrer Inst. (PSI), Villi↗

Synthesis and Molecular Structures of (3-Hydroxy, 3-Chloro, 3-Arylamino)-N-acetyl-3-arylaminotropones

The structures of 5,7-di(tert-butyl)-2-(5,8-dimethyl-4-piperidinoquinolin-2-yl)-3-hydroxytropone, 5,7-di(tert-butyl)-3-chloro-2-(5,8-dimethyl-4-piperidinoquinolin-2-yl)tropone, 5,7-di(tert-butyl)- 3-(3,5-dimethylphenylamino)-2-(5,8-dimethyl-4-piperidinoquinolin-2-yl)tropone, and 3-(N-acetyl-3,5- dimethylphenylamino)-5,7-di(tert-butyl)-2-(5,8-dimethyl-4-piperidinoquinolin-2-yl)tropone were determined by X-ray diffraction. These compounds were synthesized through a series of transformations, including the nucleophilic substitution of the chlorine atom by piperidine in the starting 5,7-di(tert-butyl)-2-(4- chloroquinolin-2-yl)-3-hydroxytropone followed by the three-step functionalization of the 3-position in 3-hydroxytropone. The nature of dynamic processes in a solution of N-acetyl-3-arylaminotropone associated with the rotation of the N-acetyl group was revealed by the PCM/PBE0/6-31G(d,p) method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The nonlocal elastomagnetoelectrostatics of disordered micropolar media

The interactions of electric, magnetic, and elastic subsystems in nonlinear disordered micropolar media that possess a bending–torsion tensor and an nonsymmetric strain tensor have been studied in the framework of phenomenological elastomagnetoelectrostatics. A system of nonlinear equations for determining the ground state of these media has been obtained by the variational method. It is shown that nonuniform external and internal rotations not only create elastic stresses, but also generate additional electric and magnetic fields, while nonuniform elastic stresses and external fields induce internal rotations. The nonlocal character of the micropolar media significantly influences elementary excitations and nonlinear dynamic processes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Electric-field sensor based on a double quantum dot in a microcavity

A scheme for an optical quantum external-electric-field sensor based on a double quantum dot placed in a high-Q semiconductor microcavity is proposed. A model of the dynamic processes occurring in this system is developed, its spectral characteristics are investigated, and the noise stability of the sensor is examined. It is demonstrated that, owing to design features, the device has a number of advantages, including high sensitivity, the presence of different excitation and measurement channels, and the possibility of accurate determination of the spatial field distribution.

36 MATERIALS SCIENCE↗

Excitation of Nonlinear Spin Oscillations in an Antiferromagnet under the Action of Pulsed Terahertz Pumping

We present a model of excitation of nonlinear spin oscillations in an antiferromagnet under the action of terahertz pulses of an electromagnetic field. It is shown that, with increasing pumping pulse amplitude, the spin system response increases linearly in the fundamental (resonant) quasi-ferromagnetic mode and quadratically in the second harmonic. We have compared the theoretically obtained dependences of the intensities of the sample response amplitudes for the fundamental mode and the second harmonic with the experimental ones. The comparison demonstrates the applicability of the developed method of analyzing dynamic processes in antiferromagnets occurring under the action of terahertz electromagnetic pulses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗