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At least 613 records · Page 34

Unconventional Complex Coacervation between Neutral Polymer and Inorganic Polyoxometalate in Aqueous Solution via Direct Water Mediation

Water, specifically in a hydration shell, is critical for many biological supramolecular aggregations in nature, where water can directly mediate intermolecular association via hydrogen bonding and is regarded as “structured water”. Conversely, little has been reported on the biomimetic water-mediated supramolecular assembly with adequately high water content to date, because of the competing thermodynamic processes of water hydration and water as a building block to participate in self-assembly. In this work, we explore water-mediated complexation based on entropy-driven biphasic coacervate formation using highly hydrophilic neutral polymer and inorganic mineral-analogous nanoclusters. For the first time (to the best of our knowledge), nonelectrostatic liquid–liquid separating coacervate formation is demonstrated between polyethylene glycol (PEG) and polyoxometalate (POM) nanoclusters in aqueous solutions of varied PEG and POM concentrations, POM types, and aqueous medium conditions. Comprehensive characterization using fluorescence microscopy, small-angle X-ray scattering, calorimetry, and other techniques has confirmed that the compositions, microstructure, and thermodynamics of PEG–POM complex coacervation are highly similar to entropy-driven complex coacervation between oppositely charged polyelectrolytes in aqueous solution. However, the effect of heavy water on critical POM concentration for the onset of coacervate formation suggests that water, instead of the counter ions as commonly debated for polyelectrolyte complex coacervation, is responsible for PEG–POM coacervate formation. Specifically, structured water works as a hydrogen bond donor for both highly hydrated PEG and POM to directly mediate the PEG–water–POM association, resulting in the release of excess hydrated water for entropy-driven PEG–POM complex coacervation. Furthermore, water-mediated complex coacervation could be developed as a general and simple strategy to build biomimetic hybrid nanomaterials with high water content for various applications from energy-related functional nanomaterials to biomedical ramification.

36 MATERIALS SCIENCE↗

Deciphering exopolysaccharide functional specificity via visualization of chemical motifs that mediate microbial-microenvironment interactions in soil micromodels

Exopolysaccharides (EPS) are carbohydrate-based matrices of microbial biofilms that microbes use to adapt to their surroundings. Microbial EPS also promotes soil aggregate stability and contributes toward soil health by reducing erosion caused by continued land use. The chemical structure of EPS, even within single species biofilms, can vary greatly: from repeating units and branching patterns to the non-carbohydrate decorations. Despite the wealth of knowledge on EPS chemistry, many unresolved questions regarding the biological implications of EPS chemical variations remain. Here, we develop a mass spectrometry imaging toolbox that reveal how EPS chemistry enables microbial adaptation to different microenvironments such as specific moisture, soil-biofilm interfaces, and food source proximity. First, we developed emulated soil micromodels (ESMs), microfluidic channels that simulate the physical properties of soil, for biofilm formation in different microenvironments. Then, in order to map chemical features of EPS in these micromodels, we develop strategies for in-situ releasing of oligosaccharides using specific enzymes. Lastly, we optimized matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) to spatially analyze the released compounds in ESMs.

54 ENVIRONMENTAL SCIENCES↗

Reactor Power Level Estimation by Fusing Multi-Modal Sensor Measurements

Estimates of the power level of a nuclear reactor based on measurements from an independent monitoring sensor system can help in the compliance verification of its declared operations. We present a three-level fusion method to estimate the power level of a nuclear reactor using features derived from infrared, electromagnetic, and acoustic sensor measurements collected in proximity to the reactor. Based on a simplified analytical model of the secondary coolant system of the reactor, we identify partial regression functions of the power level in terms of the temperature difference between inlet and outlet of coolant pipes, and the activity levels of four fans and four pumps, which are estimated as features from the sensor measurements. The power level estimator employs a combination of aggregate and complementary fusion steps at three levels to incorporate the multi-modal features in a structure that reflects the secondary cooling system and its partial regression functions. Using the measurements from a test campaign at an operational reactor, we show that this estimator achieves 3.47% or lower root mean square error under 5-fold cross validation. More generally, these results illustrate a progressive reduction in estimation error as additional modalities are appropriately incorporated, and that the fuser outperforms single modality features and their sub-combinations.

Rao, Nageswara↗

The Chemistry of Pluto and its Satellites

Pluto's bulk composition and the composition of the surface layers hold clues to the origin and evolution of a number of other Solar System bodies of comparable size in the region beyond Neptune. The July 14, 2015 flyby of the Pluto system with the New Horizons spacecraft afforded the opportunity to corroborate and greatly improve discoveries about the planet and its satellites derived Earth-based studies. It also revealed extraordinary details of the surface and atmosphere of Pluto, as well as the geology and composition of Charon and two smaller satellites. With a mean density of 1.86 g/sq cm, the bulk composition of Pluto is about two-thirds anhydrous solar composition rocky material and one-third volatiles (primarily H2O in liquid and solid states) by mass, the surface is a veneer of ices dominated by N2, with smaller amounts of CH4 and CO, as well as limited exposures of H2O ice (considered to be "bedrock"). N2, CH4, and CO occur as solid solutions at temperature-dependent mutual concentrations, each component being soluble in the others. Frozen C2H6 as a minor component has also been identified. Sublimation and recondensation of N2, CH4, and CO over seasonal (248 y) and Milankovich-type megaseasons (approx. 3 My) result in the redistribution of these ices over time and with latitude control. Solid N2 is found in glaciers originating in higher elevations and flowing at the present time into a basin structure larger than the State of Texas, forming a convecting lens of N2 that overturns on a timescale of order 10 My. The varied colors of Pluto's landscape arise from the energetic processing of the surface ices in processes that break the simple molecules and reassemble complex organic structures consisting of groups of aromatic rings connected by aliphatic chains. When synthesized in the laboratory by UV or electron irradiation of a Pluto mix of ice, this material, called tholin, has colors closely similar to Pluto. The Pluto ice tholin analog contains carboxylic acids, urea, ketones, aldehydes, amines, and some nitriles. The largest satellite, Charon has density 1.70 g/sq cm and it is about 3/5 anhydrous solar composition rock, with the remainder in H2O ice. The surface H2O ice is infused in some way with NH3, probably as a hydrate, distributed nonuniformly, but to some degree related to geological structures. Pluto's atmosphere is N2, CH4, with CO, C2-hydrocarbons, HCN, and other molecules in trace but detectable amounts. The atmosphere supports a complex haze structure with about 20 discrete layers, and suspected clouds. The haze is presumed to be made of aggregates of complex hydrocarbons (tholins) produced by photolysis of the atmospheric gases, and with similar composition to the ice tholins made on the planet's surface. Urea and a suite of carboxylic acids are of interest for prebiotic and biological chemistries.

SOLAR SYSTEMS↗

ICESat-2 Photon Classification: Finding Signal Photons in the ATL03 Geolocated Photon Data Product

ICESat-2 carries NASA's next-generation laser altimeter, ATLAS, (Advanced Topographic Laser Altimeter System), designed to measure changes in ice sheet height, sea ice freeboard, and vegetation canopy height. ATLAS contains a photon-counting lidar which transmits green (532-nm) pulses at 10kHz. Each pulse is split into 3 pairs of beams (one strong and one weak). Approximately 1014 photons per pulse travel from ATLAS through the atmosphere to reflect off the Earth's surface. Some return back into the ATLAS telescope where they are recorded. Photons from sunlight and instrument noise at the same wavelength are also recorded. The flight software time tags all photons within a 500m to 6 km range window and generates histograms. Using the histograms, it selects a telemetry window which varies from 20m over flat surfaces to hundreds of meters over rougher terrain. ATL03 contains the time, height (relative to the WGS-84 ellipsoid), latitude and longitude of every photon within the telemetry window. The basic challenge is to determine which of these photons were reflected off the surface. We have developed an algorithm that identifies these signal photons and assigns a confidence level (low, medium, or high) to each signal photon based on the signal to noise ratio. We present an overview of the signal identification algorithm and show the results on actual ICESat-2 data over ice sheet, sea ice, vegetated, and water surfaces. Higher level ATLAS products work with aggregations of the photons in order to determine the ellipsoidal height of the Earth, canopy height and structure, and other quantities of geophysical interest.

Remote Sensing↗

A Taxonomy for Classification and Comparison of Dataflows for GNN Accelerators

Recently, Graph Neural Networks (GNNs) have received a lot of interest because of their success in learning representations from graph structured data. However, GNNs exhibit different compute and memory characteristics compared to traditional Deep Neural Networks (DNNs). Graph convolutions require feature aggregations from neighboring nodes (known as the aggregation phase), which leads to highly irregular data accesses. GNNs also have a very regular compute phase that can be broken down to matrix multiplications (known as the combination phase). All recently proposed GNN accelerators utilize different dataflows and microarchitecture optimizations for these two phases. Different communication strategies between the two phases have been also used. However, as more custom GNN accelerators are proposed, the harder it is to qualitatively classify them and quantitatively contrast them. In this work, we present a taxonomy to describe several diverse dataflows for running GNN inference on accelerators. This provides a structured way to describe and compare the design-space of GNN accelerators.

97 MATHEMATICS AND COMPUTING↗

Vibration-Based Techniques for Concrete Structural Health Monitoring. Light Water Reactor Sustainability Program report

The objectives of this ongoing research project focus on health monitoring and data analytics of concrete slabs containing reactive aggregates and thus subjected to degradation due to alkali-silica reaction (ASR). A controlled concrete slab with four pockets of reactive aggregates (pure silica, and reactive aggregates from three different quarries) was cast at Vanderbilt University and cured in representative conditions to accelerate degradation due to ASR. A set of four concrete samples were also cast and cured at the University of Alabama for ASR testing. Of these four samples, two slabs contained reactive aggregates while the other two had the non-reactive aggregate counterparts mixed throughout the samples. Four additional slabs were cast and cured at the University of Nebraska- Lincoln. Of these four samples; one contained non-reactive aggregates and no reinforcement, one contained reactive aggregates and no reinforcement, one contained reactive aggregates and rebar reinforcement in one direction, and the last contained reactive aggregates and reinforcement in two directions. Single frequency and dual frequency tests were used on these slabs to locate ASR damage within the specimens containing reactive aggregates. The vibration tests were conducted with different sensor and actuator configurations to facilitate damage detection and localization. The results from the data analysis of the dynamic testing on concrete slabs are discussed in detail in this report. Results for damage localization are dependent on multiple parameters used in the tests. This report investigates different methods of data fusion including voting, raw averaging, damage index averaging, and Bayesian fusion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Temperature Dependence of Short and Intermediate Range Order in Molten MgCl 2 and Its Mixture with KCl

This article addresses the non-Debye-Waller temperature behavior in the intermediate range order for molten MgCl 2 and its mixtures with KCl from a theory, Molecular Dynamics and experimental X-ray scattering perspective and puts these findings in the context of discussions and controversies extending at least four decades. We find that these liquids are defined by two structural motifs. The first motif is associated with chains of positive-negative charge alternation; the second motif, which results in a prepeak in the structure function S(q), is associated with the interaction of Mg 2+ and Cl - ions that do not belong to the same charge alternation chain or aggregate. Our complementary X-ray scattering and computational results provide a quantitative explanation for the increase in intensity of the prepeak with temperature as opposed to the behavior of other peaks following normal Debye-Waller behavior. We note temperature has opposite effects on the prevalence of each of the two structural motifs, and the enhancement of one pattern appears to be at the detriment of the other. Whereas the intensity in S(q) associated with the charge alternation motif is diminished at higher temperature the opposite is true for the prepeak associated with the intermediate range order due to the second structural motif.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sandy Soil Microaggregates: Rethinking Our Understanding of Hydraulic Function

Core Ideas Sandy soil microaggregates are comprised of a solid sand core encrusted with fines. Thick films control a significant proportion of water retention in coarse sandy soil. Three water pools drain sequentially: capillary water, thick films, and adsorptive films. Film seepage rates should be considered when irrigating sandy soil. This study investigated the peculiar structure of microaggregates in coarse sandy soils that exhibit only external porosity and investigated their control on soil hydrology. The microstructure underpins a hydrologic existence that differs from finer textured soils where aggregates have internal porosity. Understanding the impact of these microaggregates on soil hydrology will permit improved agricultural irrigation management and estimates associated with ecosystem capacity and resiliency. Microstructure was investigated using a digital microscope, and aspects of the structure were quantified by sedimentation and computed microtomography. Sandy soil microaggregates were observed to be comprised of a solid sand‐grain core that is coated with fines, presumably cemented by organic media. This microstructure leads to three distinct water pools during drainage: capillary water, followed by thick films (1–20 μm) enveloping the outer surfaces of the crusted microaggregates, followed by adsorbed thin films (<1 μm). The characteristics of the thick films were investigated using an analytical model. These films may provide as much as 10 to 40% saturation in the range of plant‐available water. Using lubrication theory, it was predicted that thick film drainage follows a power law function with an exponent of 2. Thick films may also have a role in the geochemical evolution of soils and in ecosystem function because they provide contiguous water and gas phases at relatively high moisture contents. And, because the rough outer crust of these microaggregates can provide good niches for microbial activity, biofilm physics will dominate thick film processes, and consequently hydrologic, biologic, and geochemical functions for coarse sandy soils.

Paradiś, Ashley↗

Dynamics of Single Chains of Suspended Ferrofluid Particles

We present an experimental study of the dynamics of isolated chains made of super-paramagnetic particles under the influence of a magnetic field. The motivation of this work is to understand if the chain fluctuations exist and, if it does, how does the fluctuation affect chain aggregation. We find that single chains strongly fluctuate and that the characteristic frequency of their fluctuations is inversely proportional to the magnetic field strength. The higher the field the lower the characteristic frequency of the chain fluctuations. In the high magnetic field limit, chains behave like rigid rods without any internal motions. In this work, we used ferrofluid particles suspended in water. These particles do not have any intrinsic magnetization. Once a magnetic field is applied, a dipole moment is induced in each particle, proportional to the magnetic field. A dipolar magnetic interaction then occurs between particles. If dipole-dipole magnetic energy is higher than the thermal energy, the result is a structure change inside the dipolar fluid. The ratio of these two energies is expressed by a coupling constant lambda as: lambda = (pi(a(exp 3))(chi(exp 2))(mu(sub 0))(H(sub 0))(exp 2))/18kT Where a is the particle radius, mu(sub 0) is the vacuum magnetic permeability, H(sub 0) the applied magnetic field, k the Boltzmann constant and T the absolute temperature. If lambda > 1, magnetic particles form chains along the field direction. The lateral coalescence of several chains may form bigger aggregates especially if the particle volume fraction is high. While many studies and applications deal with the rheological properties and the structural changes of these dipolar fluids, this work focuses on the understanding of the chain dynamics. In order to probe the chain dynamics, we used dynamic light scattering (DLS) in self-beating mode as our experimental technique. The experimental geometry is such that the scattering plane is perpendicular to the magnetic field. Therefore, only motions in this plane are probed. A very dilute sample of a ferrofluid emulsion with a particle volume fraction of 10(exp -5) is used in this experiment. We chose such a low volume fraction to avoid multiple light scattering as well as lateral chain-chain aggregation. DLS measures the dynamic structure factor S(q,t) of the sample (q is the scattering wave vector, t is the time). In the absence of the magnetic field, identical particles of ferrofluid droplets are randomly distributed and S(q,t) reduces to exp(-q(exp 2)2D(sub 0)t). D(sub 0)=(kT/(6(pi)(eta)(a)) is the diffusion coefficient of Brownian particles (where Xi = (6(pi)(eta)(a)) is the Stokes frictional coefficient of a spherical particle in a fluid of viscosity eta). If interactions or polydispersity can not be ignored, an effective diffusion coefficient is introduced. Formally, D(sub eff) is defined as: D(sub eff) = - q(exp -2) partial derivative of (ln(S(q,t)) with respect to time, as t goes to 0. D(sub eff) reduces to D(sub 0) if no interactions and only a few particles size are present. Therefore, we can use DLS to measure particle size. The particle radius was found to be a=0.23 mu m with 7% of polydispersity. In this case, if we vary the scattering angle theta (and so q) we do not have any change in the measured diffusion coefficient: it is q-independent. When a magnetic field is applied, particles aggregate into chains if lambda > 1. We first studied the kinetics of the chain formation when lambda = 406. At a fixed scattering angle, we measured diffusion coefficient D(sub eff) as a function of time. Experimentally, we find that D(sub eff) decreases monotonously with time. Physically, this means that chains are becoming longer and longer. Since we are only sensitive to motions in the scattering plane and since chains have their main axis perpendicular to this plane, the measured diffusion coefficient is the trans-verse diffusion coefficient. We can relate D(sub eff) to the mean number of particles per chain N(t) at a given time and to the diffusion coefficient of an isolated particle D(sub 0) as D(sub eff)=f(N(t))D(sub 0). Since f(N) is known from other recent work, N can be expressed as a function of the time. We found a square root dependency: N(t) proportional to the square root of t. As expected for very low volume fraction, this behavior is characteristic of a diffusion-limited aggregation as suggested by several authors and by our previous work. In this study, we focus on the dependence of the effective diffusion coefficient on the scattering angle and the magnetic field strength. After the magnetic field is applied (lambda = 406) for a long time, typically 6 hours, kinetics of chain formation becomes very slow. Chain size does not vary much over the next hour period. Thus, we can perform different interesting experiments. First, at a fixed magnetic field, we measure the effective diffusion coefficient as a function of the scattering angle (from 5 to 130 deg). Our results show that the measured diffusion coefficient increases linearly with the scattering angle: D(sub eff) proportional to q. If we do the same experiment for different lambda values, D(sub eff) depends on lambda as D(sub eff) proportional to lambda(exp -1/2). We also find for different lambda values that the same asymptotic D(sub eff) value is obtained when q approaches zero. The angle dependency of D(sub eff) suggests that an additional motion exists besides chain drifting. Chain size is constant during experiment, which was verified by measuring the same diffusion coefficient at the beginning and at the end of the angle switching. If chains are rigid, D(sub eff) is independent of q. Therefore, we found that D(sub eff) not only measures the motion of the entire chain but also its internal fluctuations. These internal motions are the fluctuations of the particles in the chain. To understand the q dependency of D(sub eff), let us look at the probing length used. In our study, the characteristic length scale probed is l=2pi/q which is in the range of 0.9<l/a<20. When l is much larger than the particle radius (l/a going to infinity) we are mainly sensitive to the center of mass diffusion of the chain. D(sub eff) is then the diffusion of the entire chain and depends only on N but not on q and lambda. The value D(sub eff) allows us to obtain the number of particles per chain N. In the opposite limit (i.e. l/a < 1), we are sensitive to motions on the size of individual particles. The main contributions to the measured diffusion coefficient come from internal motions of the chains (i.e. particles' fluctuations inside the chain). We investigated also the effect of the chain size on D(sub eff). For the same value of the magnetic interaction lambda and different chain sizes, we found that the slope of D(sub eff) versus q decreases when N increases as a power law D(sub eff) proportional to N(exp -0.7). This is an important behavior because this means that the longer the chain the slower its internal fluctuations besides the whole chain motion.

Cutillas, S.↗

Distinct vibrational motions promote disparate excited-state decay pathways in cofacial perylenediimide dimers

A complex interplay of structural, electronic, and vibrational degrees of freedom underpins the fate of molecular excited states. Organic assemblies exhibit a myriad of excited-state decay processes, such as symmetry-breaking charge separation (SB-CS), excimer (EX) formation, singlet fission, and energy transfer. Recent studies of cofacial and slip-stacked perylene-3,4:9,10-bis(dicarboximide) (PDI) multimers demonstrate that slight variations in core substituents and H- or J-type aggregation can determine whether the system follows an SB-CS pathway or an EX one. However, questions regarding the relative importance of structural properties and molecular vibrations in driving the excited-state dynamics remain. Here, we use a combination of two-dimensional electronic spectroscopy, femtosecond stimulated Raman spectroscopy, and quantum chemistry computations to compare the photophysics of two PDI dimers. The dimer with 1,7-bis(pyrrolidin-1′-yl) substituents (5PDI2) undergoes ultrafast SB-CS from a photoexcited mixed state, while the dimer with bis-1,7-(3′,5′-di-t-butylphenoxy) substituents (PPDI2) rapidly forms an EX state. Examination of their quantum beating features reveals that SB-CS in 5PDI2 is driven by the collective vibronic coupling of two or more excited-state vibrations. In contrast, we observe signatures of low-frequency vibrational coherence transfer during EX formation by PPDI2, which aligns with several previous studies. We conclude that key electronic and structural differences between 5PDI2 and PPDI2 determine their markedly different photophysics.

Chemistry↗

Probing the shear-induced microstructure of a smectite clay aqueous suspensions using rheo-USANS and rheo-SIPLI measurements

Hypothesis: The static microstructure of aqueous sodium-montmorillonite (Na-Mt) suspensions at low ionic strengths (where Particle Size/Debye Length ≈1) exhibits both the particle–particle ordering as well as aggregation with repulsive ordered domains having characteristic optical birefringence and attractive aggregated entities larger than 20 µm resulting in ever-increasing yield stresses also known as physical aging-rejuvenation behavior. We hypothesize that the attractive particle–particle aggregation is the underlying cause behind the physical aging-rejuvenation behavior observed in Na-Mt suspensions with no contribution from structural dynamics driven by repulsive particle–particle ordering or jamming. Experiments: We investigate the shear-induced microstructure of aqueous Na-Mt suspensions in the sol and gel state using rheo-ultra-small angle neutron scattering (rheo-USANS) experiments at shear rates of 1, 50, 500, and 2000 s −1 . We also perform rheo-shear-induced polarization light imaging (rheo-SIPLI) experiments to relate ordering with shearing and aging. Findings: Shearing the suspensions at low to moderate shear rates induces particle–particle aggregation and shearing at high shear rates induces the breakage of particle–particle aggregation in the sol and gel states, suggesting the microstructural aggregation in the sol and gel state is shear sensitive and a full rejuvenation or breakage of particle–particle aggregation is only achieved at a minimum critical shear rate. The rheo-SIPLI experiments reveal that the sol and gel state exhibited strong Maltese cross patterns at a shear rate of 1000 s −1 , indicating particle–particle ordering. Post shearing, the gel exhibited temporal evolution of storage modulus without any noticeable influence on the appearance of the Maltese cross pattern indicating physical aging and particle ordering are distinct length scale phenomena in Na-Mt suspensions and the physical aging-rejuvenation behaviour is a feature of particle–particle aggregation as opposed to ordering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chromium segregation-induced oxide evolution in Ni-10Cr alloys during high-temperature oxidation

The oxidation behavior of a Ni-10(wt%)Cr alloy under high-temperature O 2 conditions is investigated using transmission electron microscopy and first-principles calculations. Results reveal that chromium segregation plays a central role in driving the evolution of complex oxide phase structures during oxidation. At low Cr concentrations, Cr preferentially segregates to NiO grain boundaries or internal pores, substituting for Ni atoms and forming Ni(Cr)O solid solutions. As Cr content increases, enhanced diffusion promotes Cr penetration into the NiO lattice, leading to the formation of multiphase oxide structures. First-principles modeling corroborates these findings: at low Cr concentrations, Cr atoms favor surface and grain-boundary segregation, while higher concentrations lead to Cr aggregation within the NiO bulk. Furthermore, the integrated experimental-theoretical approach provides atomistic insights into Cr-mediated mass transport mechanisms during alloy oxidation and offers valuable guidance for controlling oxide growth kinetics and phase stability in Ni-Cr alloys, with implications for improving oxidation resistance in high-temperature structural applications.

36 MATERIALS SCIENCE↗

Dust Coagulation in Protoplanetary Accretion Disks

The time evolution of dust particles in circumstellar disk-like structures around protostars and young stellar objects is discussed. In particular, we consider the coagulation of grains due to collisional aggregation. The coagulation of the particles is calculated by solving numerically the non-linear Smoluchowski equation. The different physical processes leading to relative velocities between the grains are investigated. The relative velocities may be induced by Brownian motion, turbulence and drift motion. Starting from different regimes which can be identified during the grain growth we also discuss the evolution of dust opacities. These opacities are important for both the derivation of the circumstellar dust mass from submillimeter/millimeter continuum observations and the dynamical behavior of the disks. We present results of our numerical studies of the coagulation of dust grains in a turbulent protoplanetary accretion disk described by a time-dependent one-dimensional (radial) alpha-model. For several periods and disk radii, mass distributions of coagulated grains have been calculated. From these mass spectra, we determined the corresponding Rosseland mean dust opacities. The influence of grain opacity changes due to dust coagulation on the dynamical evolution of a protostellar disk is considered. Significant changes in the thermal structure of the protoplanetary nebula are observed. A 'gap' in the accretion disk forms at the very frontier of the coagulation, i.e., behind the sublimation boundary in the region between 1 and 5 AU.

Schmitt, W.↗

Use of a 360-Degree Underwater Camera to Characterize Artificial Reef and Fish Aggregating Effects around Marine Energy Devices

Marine energy devices must be attached to the seafloor by their foundations, pilings, or anchors, and will have other parts in the water column like the devices themselves, mooring lines, and power export cables running along the seafloor. The installation and presence of these artificial structures will create physical changes that can disrupt or create new habitats, and potentially alter the behavior of mobile organisms such as fish around a device by attracting them to these new artificial reefs and fish aggregating devices. In this study, we tested a new approach for monitoring fish activity around a marine energy device anchor: a 360-degree underwater camera to keep the target (a wave energy converter’s anchor) in the field of view of the camera. The camera was deployed in three configurations (hand-held, tripod, video lander) at sites with different hydrodynamics and underwater visibilities. The video lander was the best configuration: very stable, versatile, and easy to handle. The 360-degree field of view enabled observing and counting fishes, which were more abundant at dusk than dawn or noon, around the anchor. Despite remaining challenges, 360-degree cameras are useful tools for monitoring animal interactions with marine energy devices.

360-degree camera↗

Performance Optimization Methods for a Memory-Bound, Unstructured-Grid CFD Application on Massively Parallel GPU Platforms

Computational performance of the FUN3D unstructured-grid computational fluid dynamics (CFD) application on massively parallel GPU environments is memory-bound and highly dependent upon efficient reads from and atomic updates to the irregular cell-, edge-, and node-based data structures. In this talk, we present recent efforts into optimizing select performance-critical kernels on NVIDIA Tesla V100 and A100 GPUs and AMD CDNA MI100 GPUs. A novel use of L2 cache residency controls and asynchronous loads into on-chip shared memory are explored on the A100 GPU for the sparse iterative solver, which is dominated by mixed-precision, sparse matrix vector multiplication. Demonstrations show that these methods improve global memory bandwidth utilization by 13.5% on the A100 GPU. Several techniques are also presented that use registers and/or shared memory to facilitate array transposition and aggregation which combine to reduce the frequency and increase the cache efficiency of floating-point atomic updates to the irregular data structures. These methods are demonstrated to improve the kernel throughput by nearly 500% on select kernels on the AMD MI100 over atomic updates directly to global memory. Overall, both V100 and A100 GPUs outperformed the MI100 GPU on kernels dominated by double-precision atomic updates; however, the techniques demonstrated here reduced the performance gap and improved the MI100 performance.

GPU CPU unstructured CFD memory↗