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At least 1,657 records · Page 92

Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oak Ridge Leadership Facility’s (OLCF) Summit supercomputer (using the full machine at 4600 nodes; at 98% of GPU utilization on all ~28000 NVIDIA Volta GPUs). PIConGPU has been selected as one of the the eight applications for OLCF’s coveted Center for Accelerated Application Readiness (CAAR) program aimed at the facility’s Frontier supercomputer (OLCF’s first exascale system to launch in 2021), to partner with our vendors (primary vendors: AMD and Cray/HPE) ensuring that Frontier will be able to perform large-scale science when it opens to users in 2022. To this effect, performance engineers on the PIConGPU team wanted to dive deep into the application to understand at the finest granularity, which portions of the code could be further optimized to exploit the hardware on Summit at it’s maximum potential and also to elucidate which key kernels should be tracked and optimized for the CAAR effort to port this code to Frontier. Any bottlenecks that are observed via performance profiling on Summit are likely to also impact scalability on the Frontier-dev system and the Frontier Early Access (EA) system. Additionally, the engineers wanted to take a closer look at the newest NVIDIA profiling tools which allows us to identify the most useful features on these tools and will provide an opportunity to compare it to new AMD and Cray’s performance analysis tool releases and provide feedback to our vendor partners on what features are most important and mission critical for CAAR efforts. The primary goal of this report is to focus on the evaluation of PIConGPU’s most time-intensive kernels using NVProf and NSight Suite. Three kernels, Current Deposition (also known as Compute Current), Particle Push (Move and Mark), and Shift Particles are known to be some of the most time-consuming kernels in PIConGPU. The Current xi Deposition kernel and Particle Push kernel both set up the particle attributes for running any physics simulation with PIConGPU, so it is crucial to improve the performance of these two kernels. In this report, we measure single GPU metrics for the three kernels, offer high level takeaways from the conducted analysis, and compare the profiling data from NSight Compute to that of NVProf. This analysis was performed using a grid size of 240 x 272 x 224, and 10 time steps with the Mid-November Figure of Merit (FOM) run setup. The Traveling Wave Electron Acceleration (TWEAC) science case used in this run is a representative science case for PIConGPU. This execution can also be used for baseline analysis on AMD MI50/ MI60 systems. As of the time of writing, the PIConGPU application has limited use for features of NSight Systems, so this report will mainly focus on insights garnered from NSight Compute. For this analysis, we run the “full” metric set available in NSight Compute version 2020.1.2 and use NSight Systems version 2020.3.1 to generate the application timeline.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Measurement of the dineutrino system kinematic variables in dileptonic top quark pair production in proton-proton collisions at $\sqrt{s}=13$ TeV

Differential top quark pair production cross sections are measured in the dilepton final states e + e − , μ + μ − , and e ± μ ∓ , as a function of kinematic variables of the two-neutrino system: the transverse momentum $p^{vv}_{\textrm{T}}$ of the dineutrino system, the minimum distance in azimuthal angle between $\vec{p}^{vv}_{\textrm{T}}$ and leptons, and in two dimensions in bins of both observables. The measurements are performed using CERN LHC proton-proton collisions at $\sqrt{s}=13$ TeV, recorded by the CMS detector between 2016 and 2018, corresponding to an integrated luminosity of 138 fb −1 . The measured cross sections are unfolded to the particle level using an unregularized least squares method. Results are compared with predictions by the standard model of particle physics, and found to be in agreement with theoretical calculations as well as Monte Carlo simulations.

Hadron-Hadron Scattering↗

Effects of time-dependent deformation of shale on the integrity of a geological nuclear waste repository

Safety assessment of geological nuclear waste repositories is essential for the permanent disposal of spent nuclear fuels and high-level radioactive waste. The long-term integrity of the host rock as well as the engineered barrier system (e.g., bentonite buffer) surrounding nuclear waste canisters is of particular importance as decay heat from nuclear waste canisters, which will last over thousands of years, significantly disturbs the thermo-hydromechanical (THM) state of the repository. In this study, THM coupled simulations were carried out to investigate the effect of time-dependent deformation (i.e., creep) of shale on the long-term integrity of a generic subsurface nuclear waste repository. The Norton-Bailey creep model, which is also known as the Lemaitre-Menzel-Schreiner model, was employed to simulate the power-law type creep that is observed in shales. The TOUGH-FLAC simulator was employed for the THM coupled modeling of the repository. The objective of this study is to assess the effect of creep in different shales (i.e., high creep shale vs. low creep shale) on long-term stress and permeability changes in the repository. Results show potential advantages of constructing repositories in the high creep shale, as deviatoric stress levels in the formation decreased to zero in 100 years since the emplacement of nuclear waste canisters and the permeability also decreased to the undamaged, intrinsic levels in 10,000 years. Also, mean effective stress levels in the bentonite buffer increased by 100% in the high creep shale case relative to the low creep shale case at 10,000 years due to creep-induced contraction of the nuclear waste disposal tunnel. However, in earlier periods (e.g., 1000 years), the stress levels in the bentonite buffer were twice smaller in the high creep shale case than in the low creep shale case, which shows a tradeoff between the intermediate- (~1000 years) and long-term (>10,000 years) compaction levels in the bentonite buffer depending on the creep characteristics of the host shale.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Microstructure evolution during near- T g annealing and its effect on shear banding in model alloys

By performing extensive molecular dynamics simulations, we investigate herein the deformation behavior in A l 90 S m 10 and C u 64.5 Z r 35.5 alloys after elongated isothermal annealing in the vicinity of the glass-transition temperature ( T g ). Different microstructural response to the annealing process was observed: A l 90 S m 10 maintains the glassy structure with improved energetic stability, enhanced short-range order (SRO), and a more pronounced spatial network that extends beyond the first atomic shell, while C u 64.5 Z r 35.5 forms nanocrystalline Laves C u 2 Zr phases. Shear banding occurs in both annealed systems under shear loading. For A l 90 S m 10 , the spatial network formed by the local clusters characterizing the SRO of the system is significantly weakened but remains appreciable in the shear band. In contrast, the crystalline ordering in the C u 64.5 Z r 35.5 is completely destroyed during shear banding. Consequently, while displaying higher yield strength, the annealed C u 64.5 Z r 35.5 sample appears to be less ductile. By carefully examining the effect of microstructures on the structural ordering in the shear band and the consequent mechanical response, our work contributes to a better understanding of the deformation mechanism of amorphous alloys as compared with that in crystalline materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum simulation: From spin models to gauge-gravity correspondence

Quantum many-body systems with coherent and controllable interactions enable the realization of novel quantum materials, the quantum simulation of problems that cannot be simulated on classical computers, computational systems that are exponentially faster than existing classical algorithms, and the direct investigation of the conjectured duality between gravitational theories and quantum field theories. This project focusses on quantum phase transitions in strongly interacting many-body spin systems, and in particular on the dynamical evolution near the critical point and across the phase transition. The dynamics of a large quantum system containing more than 50 qubits is investigated in various critical regimes. In particular, the Kibble-Zurek transition has been characterized and critical exponents have been measured. Furthermore, quantum many-body scars have been observed and characterized for the first time. We are investigating the Kibble-Zurek mechanism in the quantum phase transition in one dimension from a disordered system to a system with ordering induced by Rydberg interactions between neighboring atoms. The Kibble-Zurek mechanism describes the formation of topological defects as a system evolves across a phase transitions, and is expected to apply to a large number of problems, including cosmology, where it should describe the structure of domain formation in the early universe.

74 ATOMIC AND MOLECULAR PHYSICS↗

A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5

Abstract. Land models are essential tools for understanding and predicting terrestrial processes and climate–carbon feedbacks in the Earth system, but uncertainties in their future projections are poorly understood. Improvements in physical process realism and the representation of human influence arguably make models more comparable to reality but also increase the degrees of freedom in model configuration, leading to increased parametric uncertainty in projections. In this work we design and implement a machine learning approach to globally calibrate a subset of the parameters of the Community Land Model, version 5 (CLM5) to observations of carbon and water fluxes. We focus on parameters controlling biophysical features such as surface energy balance, hydrology, and carbon uptake. We first use parameter sensitivity simulations and a combination of objective metrics including ranked global mean sensitivity to multiple output variables and non-overlapping spatial pattern responses between parameters to narrow the parameter space and determine a subset of important CLM5 biophysical parameters for further analysis. Using a perturbed parameter ensemble, we then train a series of artificial feed-forward neural networks to emulate CLM5 output given parameter values as input. We use annual mean globally aggregated spatial variability in carbon and water fluxes as our emulation and calibration targets. Validation and out-of-sample tests are used to assess the predictive skill of the networks, and we utilize permutation feature importance and partial dependence methods to better interpret the results. The trained networks are then used to estimate global optimal parameter values with greater computational efficiency than achieved by hand tuning efforts and increased spatial scale relative to previous studies optimizing at a single site. By developing this methodology, our framework can help quantify the contribution of parameter uncertainty to overall uncertainty in land model projections.

54 ENVIRONMENTAL SCIENCES↗

Numerical investigation of equivalence ratio effects on Flex-Fuel mixing controlled combustion enabled by prechamber ignition

There is interest in adapting renewable and low-carbon intensity fuels to heavy-duty engines to help displace criteria and greenhouse gas emissions associated with diesel combustion. Low-carbon fuels have inherently low cetane numbers and thus pose a significant challenge when considering direct substitution in diesel combustion systems. Use of an actively fueled prechamber as an ignition source to initiate mixing-controlled combustion (PC-MCC) of low-cetane fuels is becoming an attractive combustion mode to alleviate the identified reactivity deficit. This work focuses on the utilization of an active prechamber to facilitate diesel-like combustion of bioethanol-gasoline fuel blends in a heavy-duty engine. Recent results in this emerging technology suggest that ignition quality is uniquely coupled to prechamber equivalence ratio. In this numerical study, the fundamental implications of prechamber equivalence ratio on the ignition performance of direct injected fuels ranging from E10 to E100 are investigated using CONVERGE. Parametric studies of the prechamber operating strategy were assessed at diesel-like conditions to characterize the performance trends relative to a diesel baseline at the same boundary conditions. Simulation results indicate that PC-MCC is flex-fuel capable and achieves diesel-like ignition qualities and combustion processes for all fuels considered under stoichiometric and rich prechamber conditions. To characterize the equivalence ratio trends observed, a novel inflow boundary modeling technique was utilized to prescribe turbulent jets in place of the prechamber where selective speciation of the jet composition was conducted to isolate the ignition contributions of radical and reacting species in lean, stoichiometric, and rich jets. The inflow boundary modeling suggests that excess fuel and combustion intermediates present in jets produced from stratified and fuel-rich prechamber operation promotes higher jet temperatures and as such are superior ignition sources. Relative to a lean prechamber jet, the peak temperature of a reacting jet from a rich prechamber was up to 600 K hotter at fixed distances from the orifice exit. Furthermore, radicals also demonstrated an influence on the ignition process, but the combustion mode was identified to be thermally dominant.

33 ADVANCED PROPULSION SYSTEMS↗

Continental United States may lose 1.8 petagrams of soil organic carbon under climate change by 2100

Abstract Aims High‐resolution information on soils’ vulnerability to climate‐induced soil organic carbon (SOC) loss can enable environmental scientists, land managers, and policy makers to develop targeted mitigation strategies. This study aims to estimate baseline and decadal changes in continental US surface SOC stocks under future emission scenarios. Location Continental United States. Time period 2014–2100. Methods We used recent SOC field observations ( n = 6,213 sites), environmental factors ( n = 32), and an ensemble machine learning (ML) approach to estimate baseline SOC stocks in surface soils across the continental United States at 100‐m spatial resolution, and decadal changes under the projected climate scenarios of Coupled Model Intercomparison Project Phase Six (CMIP6) earth system models (ESMs). Results Baseline SOC projections from ML approaches captured more than 50% of variability in SOC observations, whereas ESMs represented only 6–16% of observed SOC variability. ML estimates showed a mean total loss of 1.8 Pg C from US surface soils under the high‐emission scenario by 2100, whereas ESMs showed no significant change in SOC stocks with wide variation among ESMs. Both ML and ESM predictions agree on the direction of SOC change (net emissions or sequestration) across 46–51% of continental US land area. These differences are attributable to the high‐resolution site‐specific data used in the ML models compared to the relatively coarse grid represented in CMIP6 ESMs. Main conclusions Our high‐resolution estimates of baseline SOC stocks, identification of key environmental controllers, and projection of SOC changes from US land cover types under future climate scenarios suggest the need for high‐resolution simulations of SOC in ESMs to represent the heterogeneity of SOC. We found that the SOC change is sensitive to key soil related factors (e.g. soil drainage and soil order) that have not been historically considered as input parameters in ESMs, because currently more than 95% variability in the SOC of CMIP6 ESMs is controlled by net primary productivity, temperature, and precipitation. Using additional environmental factors to estimate the baseline SOC stocks and predict the future trajectory of SOC change can provide more accurate results.

54 ENVIRONMENTAL SCIENCES↗

Influence of design and operating parameters for additively manufactured intensified packing devices on CO 2 -Absorption column cooling and capture efficiency

Solvent-based CO 2 absorption is technologically a matured CO 2 capture pathway but suffers from: high regeneration energy demand, and solvent temperature rise and decreased capture efficiency caused by the heat of reaction. While research has focused on developing non-aqueous and low-aqueous solvents for decreasing the regeneration energy, the temperature bulge due to exothermic absorption is typically dealt with by cooling the solvent with an external inter-stage heat-exchanger. This approach may increase the overall process footprint, as well as capital and operating costs. Here, the current study explores a process intensification approach by incorporating inside the column an additively manufactured intensified packing device that consists of corrugated plates and internal coolant channels. The corrugated plates provide surface area for mass transfer between gas and liquid, while cooling fluid inside the internal channels removes heat from the exothermic reactive system. Two different intensified devices with specific surface areas of 266 m 2 /m 3 and 359 m 2 /m 3 were designed, manufactured, and tested inside a 2.06-m long and 0.203-m diameter column packed with commercial Mellapak 250Y packing. The device with a lower surface area showed up to 27 % reduction in cooling performance. A steady-state heat transfer model provides good agreement with the experimental column temperature and intra-stage heat removal data. Although a decrease in heat transfer performance was observed for the device with lower surface area, CO 2 capture experiments performed with simulated flue gas and low-aqueous solvent demonstrated that both intensified devices lead to a similar improvement of 12 % in capture efficiency. This study provides an understanding on simplifying the intensified packing device geometry and decreasing the device fabrication cost by 25 % without compromising with the CO 2 absorption performance of the packed column.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Recovering high-purity uranyl nitrate from simulated used nuclear fuel dissolver solutions by crystallization: rejecting technetium

The separation of U from Tc and other problematic fission product elements like Mo and Ru, along with Sr, Zr, Cs, and Nd, has been achieved via the crystallization of uranyl nitrate hexahydrate (UNH). Rejection of technetium as pertechnetate anion ( 99 TcO 4 – ) is an especially important feature of this system, as it otherwise tends to follow U (VI) in extractive separations. It also raises the salient question regarding why this oxoanion cannot replace nitrate within the crystalline lattice of UNH. Results showed high-yield (>90 %), high-purity (>99 %) recovery of U as UNH from solutions containing 99 TcO 4 – by simple reduction of temperature from 60°C to 20°C. There was no observable interaction of 99 TcO 4 – with UO 2 2+ . The addition of other cations like, Sr 2+ , Zr 4+ , Cs + , and Nd 3+ , also did not form secondary, contaminant solid phases, leaving the > 99 % of the fission product elements in the mother liquor, while the U was recovered at > 90 %. Similarly, Mo and Ru, when added to the mixture, were shown to behave as the other fission-product elements, remaining in the mother liquor during crystallization. As a result, DFT calculations showed that, despite the higher binding strength of TcO 4 – , HMoO 4 – , and BiO 3 – with the UO 2 2+ cation compared to NO 3 – , the hydrogen-bonding network of the two coordinated ions and four waters of hydration in the UNH crystal structure is the driving force for the high specificity of this separation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

First-Principles Statistical Mechanics Study of Magnetic Fluctuations and Order–Disorder in the Spinel LiNi 0.5 Mn 1.5 O 4 Cathode

While significant magnetic interactions exist in lithium transition metal oxides, commonly used as Li-ion cathodes, the interplay between magnetic couplings, disorder, and redox processes remains poorly understood. In this work, we focus on the high-voltage spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) cathode as a model system on which to apply a computational framework that uses first principles-based statistical mechanics methods to predict the finite temperature magnetic properties of materials and provide insights into the complex interplay between magnetic and chemical degrees of freedom. Density functional theory calculations on multiple distinct Ni–Mn orderings within the LNMO system, including the ordered ground-state structure (space group P4332), reveal a preference for a ferrimagnetic arrangement of the Ni and Mn sublattices due to strong antiferromagnetic superexchange interactions between neighboring Mn 4+ and Ni 2+ ions and ferromagnetic Mn–Mn and Ni–Ni couplings, as revealed by magnetic cluster expansions. These results are consistent with qualitative predictions using the Goodenough-Kanamori-Anderson rules. Simulations of the finite temperature magnetic properties of LNMO are conducted using Metropolis Monte Carlo. We find that a “semiclassical” Monte Carlo sampling method based on the Heisenberg Hamiltonian accurately predicts experimental magnetic transition temperatures observed in magnetometry measurements. This study highlights the importance of a robust computational toolkit that accurately captures the complex chemomagnetic interactions and predicts finite temperature magnetic behavior to help analyze experimental magnetic and magnetic resonance spectroscopy data acquired ex situ and operando.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The DOE E3SM v1.2 Cryosphere Configuration: Description and Simulated Antarctic Ice‐Shelf Basal Melting

Abstract The processes responsible for freshwater flux from the Antarctic Ice Sheet (AIS), ice‐shelf basal melting and iceberg calving, are generally poorly represented in current Earth System Models (ESMs). Here we document the cryosphere configuration of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) v1.2. This includes simulating Antarctic ice‐shelf basal melting, which has been implemented through simulating the ocean circulation within static Antarctic ice‐shelf cavities, allowing for the ability to calculate ice‐shelf basal melt rates from the associated heat and freshwater fluxes. In addition, we added the capability to prescribe forcing from iceberg melt, allowing for realistic representation of the other dominant mass loss process from the AIS. In standard resolution simulations (using a noneddying ocean) under preindustrial climate forcing, we find high sensitivity of modeled ocean/ice shelf interactions to the ocean state, which can result in a transition to a high basal melt regime under the Filchner‐Ronne Ice Shelf (FRIS), presenting a significant challenge to representing the ocean/ice shelf system in a coupled ESM. We show that inclusion of a spatially dependent parameterization of eddy‐induced transport reduces biases in water mass properties on the Antarctic continental shelf. With these improvements, E3SM produces realistic ice‐shelf basal melt rates across the continent that are generally within the range inferred from observations. The accurate representation of ice‐shelf basal melting within a coupled ESM is an important step toward reducing uncertainties in projections of the Antarctic response to climate change and Antarctica's contribution to global sea‐level rise.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses

Abstract Lateral subsurface flow plays an essential role in sustaining the terrestrial ecosystem, but it is not explicitly represented in most Earth System Models. In this study, we implemented an explicit lateral saturated flow model into the E3SM land model (ELM). The model explicitly describes lateral flow in the saturated zone by representing, for each model grid, an idealized hillslope consisting of five hydrologically connected soil columns. We conducted three model experiments driven by 0.125° atmospheric forcing data during 1980–2015 over California using models of the default ELM, a modified version of ELM to enhance infiltration, and the model with the lateral saturated flow model. The simulated runoff, evapotranspiration, and terrestrial water storage anomaly (TWSA) from the three simulations were evaluated against available observations, and the model explicitly representing lateral flow performs best. The new model produces greater gridcell‐averaged evapotranspiration especially over the mountainous regions with moderate relief and seasonally dry climates. Most importantly, it improves the modeled seasonal variations, interannual variabilities, and the recent decadal decline of TWSA. Many of these improvements can be attributed to the enhanced ecosystem resilience to droughts as demonstrated by transpiration increases caused by lateral flow. Model sensitivity experiments suggest that subsurface runoff is most sensitive to the ratio between horizontal and vertical saturated hydraulic conductivity, followed by hillslope planforms (convergent, divergent, and uniform), number of columns, and lower boundary conditions. Future work should effectively characterize hillslopes in global models and explore the long‐term influences of lateral water movement on modeled biogeochemical cycle.

54 ENVIRONMENTAL SCIENCES↗

Large bandgap observed on the surfaces of EuZn 2 As 2 single crystals

EuM 2 As 2 (M = Zn, Cd, In, Sn etc.) is an excellent material system for studying magnetism-tuned topological properties. However, discrepancies exist between experimental data and theoretical calculations regarding the bulk and surface bandgaps. In this work, cleaved EuZn 2 As 2 crystals are studied using scanning tunneling microscopy/spectroscopy and density functional theory calculations. Triangular-shaped defect-induced modifications in the local density of states help distinguish between Eu-terminated and AsZn-terminated surfaces. While large bandgaps (~1.5 eV at 77 K) are observed on both pristine surfaces, the bandgap size is found to be highly sensitive to local heterogeneity, tending to decrease. By combining experimental observations with theoretical simulations, we conclude that the reduced bandgap in heterogeneous regions arises from Zn vacancies and/or substitution by As atoms, both impacting greater in the Eu surface electronic properties than those in the AsZn surface. This demonstrates the intimate relationship between the electronic structure and magnetism in EuZn 2 As 2 .

interfaces↗

Exploring the formation of gold/silver nanoalloys with gas-phase synthesis and machine-learning assisted simulations

While nanoalloys are of paramount scientific and practical interest, the main processes leading to their formation are still poorly understood. Key structural features in the alloy systems, including the crystal phase, chemical ordering, and morphology, are challenging to control at the nanoscale, making it difficult to extend their use to industrial applications. Here, in this contribution, we focus on the gold/silver system that has two of the most prevalent noble metals and combine experiments with simulations to uncover the formation mechanisms at the atomic level. Nanoparticles were produced using a state-of-the-art inert-gas aggregation source and analyzed using transmission electron microscopy and energy-dispersive X-ray spectroscopy. Machine-learning-assisted molecular dynamics simulations were employed to model the crystallization process from liquid droplets to nanocrystals. Our study finds a preponderance of nanoparticles with five-fold symmetric morphology, including icosahedra and decahedra which is consistent with previous results on mono-metallic nanoparticles. However, we observed that gold atoms, rather than silver atoms, segregate at the surface of the obtained nanoparticles for all the considered alloy compositions. These segregation tendencies are in contrast to previous studies and have consequences on the crystallization dynamics and the subsequent crystal ordering. We finally showed that the underpinning of this surprising segregation dynamics is due to charge transfer and electrostatic interactions rather than surface energy considerations.

36 MATERIALS SCIENCE↗

ReaxFF molecular dynamics simulations of electrolyte–water systems at supercritical temperature

We have performed ReaxFF molecular dynamics simulations of alkali metal–chlorine pairs in different water densities at supercritical temperature (700 K) to elucidate the structural and dynamical properties of the system. The radial distribution function and the angular distribution function explain the inter-ionic structural and orientational arrangements of atoms during the simulation. The coordination number of water molecules in the solvation shell of ions increases with an increase in the radius of ions. We find that the self-diffusion coefficient of metal ions increases with a decrease in density under supercritical conditions due to the formation of voids within the system. The hydrogen bond dynamics has been interpreted by the residence time distribution of various ions, which shows Li+ having the highest water retaining capability. The void distribution within the system has been analyzed by using the Voronoi polyhedra algorithm providing an estimation of void formation within the system at high temperatures. We observe the formation of salt clusters of Na+ and K+ at low densities due to the loss of dielectric constants of ions. The diffusion of ions gets altered dramatically due to the formation of voids and nucleation of ions in the system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vortex splitting in two-dimensional fluids and non-neutral electron plasmas with smooth vorticity profiles

Initially, elliptical, quasi-two-dimensional (2D) fluid vortices can split into multiple pieces if the aspect ratio is sufficiently large due to the growth and saturation of perturbations known as Love modes on the vortex edge. Presented here are experiments and numerical simulations, showing that the aspect ratio threshold for vortex splitting is significantly higher for vortices with realistic, smooth edges than that predicted by a simple “vortex patch” model, where the vorticity is treated as piecewise constant inside a deformable boundary. The experiments are conducted by exploiting the E × B drift dynamics of collisionless, pure electron plasmas in a Penning–Malmberg trap, which closely model 2D vortex dynamics due to an isomorphism between the Drift–Poisson equations describing the plasmas and the Euler equations describing ideal fluids. The simulations use a particle-in-cell method to model the evolution of a set of point vortices. The aspect ratio splitting threshold ranges up to about twice as large as the vortex patch prediction and depends on the edge vorticity gradient. This is thought to be due to spatial Landau damping, which decreases the vortex aspect ratio over time and, thus, stabilizes the Love modes. Near the threshold, asymmetric splitting events are observed in which one of the split products contains much less circulation than the other. These results are relevant to a wide range of quasi-2D fluid systems, including geophysical fluids, astrophysical disks, and drift-wave eddies in tokamak plasmas.

Physics↗

Ring currents modulate optoelectronic properties of aromatic chromophores at 25 T

The properties of organic molecules can be influenced by magnetic fields, and these magnetic field effects are diverse. They range from inducing nuclear Zeeman splitting for structural determination in NMR spectroscopy to polaron Zeeman splitting organic spintronics and organic magnetoresistance. A pervasive magnetic field effect on an aromatic molecule is the aromatic ring current, which can be thought of as an induction of a circular current of π-electrons upon the application of a magnetic field perpendicular to the π-system of the molecule. While in NMR spectroscopy the effects of ring currents on the chemical shifts of nearby protons are relatively well understood, and even predictable, the consequences of these modified electronic states on the spectroscopy of molecules has remained unknown. In this work, we find that photophysical properties of model phthalocyanine compounds and their aggregates display clear magnetic field dependences up to 25 T, with the aggregates showing more drastic magnetic field sensitivities depending on the intermolecular interactions with the amplification of ring currents in stacked aggregates. These observations are consistent with ring currents measured in NMR spectroscopy and simulated in time-dependent density functional theory calculations of magnetic field-dependent phthalocyanine monomer and dimer absorption spectra. Here, we propose that ring currents in organic semiconductors, which commonly comprise aromatic moieties, may present new opportunities for the understanding and exploitation of combined optical, electronic, and magnetic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗