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At least 361 records · Page 20

Nature of the narrow optical band in H*-aggregates: Dozy-chaos–exciton coupling

Dozy chaos emerges as a combined effect of the collective chaotic motion of electrons and nuclei, and their chaotic electromagnetic interactions in the transient state of molecules experiencing quantum transitions. Following earlier discussions of the well-known Brönsted relations for proton-transfer reactions; the temperature-dependent electron transfer in Langmuir–Blodgett films; the shape of the optical bands of polymethine dye monomers, their dimers, and J-aggregates, this paper reports one more application of the dozy-chaos theory of molecular quantum transitions. The qualitative and quantitative explanations for shape of a narrow and blue-shifted optical absorption band in H{sup *}-aggregates is given on the basis of the dozy-chaos theory by taking into account the dozy-chaos–exciton coupling effect. It is emphasized that in the H{sup *}-aggregate chromophore (dimer of cyclic bis-thiacarbocyanines) there is a competition between two Frenkel exciton transitions through the chaotic reorganization motion of nuclear environment. As a result, the highly organized quantum transition to the upper exciton state becomes an exciton-induced source of dozy chaos for the low organized transition to the lower exciton state. This manifests itself in appearing the narrow peak and broad wing in the optical spectrum pattern of H{sup *}-aggregates. A similar enhancement in the H{sup *}-effect caused by the strengthening of the exciton coupling in H{sup *}-dimers, which could be achieved by synthesizing tertiary and quarternary thiacarbocyanine monomers, is predicted.

36 MATERIALS SCIENCE↗

CAMELOT: A machine learning approach for coarse-grained simulations of aggregation of block-copolymeric protein sequences

We report the development and deployment of a coarse-graining method that is well suited for computer simulations of aggregation and phase separation of protein sequences with block-copolymeric architectures. Our algorithm, named CAMELOT for Coarse-grained simulations Aided by MachinE Learning Optimization and Training, leverages information from converged all atom simulations that is used to determine a suitable resolution and parameterize the coarse-grained model. To parameterize a system-specific coarse-grained model, we use a combination of Boltzmann inversion, non-linear regression, and a Gaussian process Bayesian optimization approach. The accuracy of the coarse-grained model is demonstrated through direct comparisons to results from all atom simulations. We demonstrate the utility of our coarse-graining approach using the block-copolymeric sequence from the exon 1 encoded sequence of the huntingtin protein. This sequence comprises of 17 residues from the N-terminal end of huntingtin (N17) followed by a polyglutamine (polyQ) tract. Simulations based on the CAMELOT approach are used to show that the adsorption and unfolding of the wild type N17 and its sequence variants on the surface of polyQ tracts engender a patchy colloid like architecture that promotes the formation of linear aggregates. These results provide a plausible explanation for experimental observations, which show that N17 accelerates the formation of linear aggregates in block-copolymeric N17-polyQ sequences. The CAMELOT approach is versatile and is generalizable for simulating the aggregation and phase behavior of a range of block-copolymeric protein sequences.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A mobile system for a comprehensive online-characterization of nanoparticle aggregates based on wide-angle light scattering and laser-induced incandescence

A mobile demonstrator for the comprehensive online-characterization of gas-borne nanoparticle aggregates is presented. Two optical measurement techniques are combined, both utilizing a pulsed Nd:YAG laser as light source. Aggregate size and fractal dimension are measured by Wide-Angle Light Scattering (WALS). An ellipsoidal mirror images elastically scattered light from scattering angles between 10° and 165° onto a CCD-camera chip resulting in an almost complete scattering diagram with high angular resolution. Primary particle size and volume fraction are measured by time-resolved Laser-Induced Incandescence (TiRe-LII). Here, particles are heated up to about 3000 K by the short laser pulse, the enhanced thermal radiation signal is detected with gated photomultiplier tubes. Analysis of the signal decay time and maximum LII-signal allows for the determination of primary particle diameter and volume fraction. The performance of the system is demonstrated by combined measurements on soot nanoparticle aggregates from a soot aerosol generator. Particle and aggregate sizes are varied by using different equivalence ratios of the combustion in the generator. Soot volume fraction can be adjusted by different levels of dilution with air. Online-measurements were carried out demonstrating the favorable performance of the system and the potential for industrial applications such as process control and product development. The particle properties obtained are confirmed through transmission electron microscopy analysis on representative samples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Molecular model of J-aggregated pseudoisocyanine fibers

Aggregated cyanines form ordered supramolecular structures with the potential to transport energy efficiently over long distances, a hallmark of photosynthetic light-harvesting complexes. In concentrated aqueous solution, pseudoisocyanine (PIC) spontaneously forms fibers with a chiral J-band red-shifted 1600 cm -1 from the monomeric 0–0 transition. A cryogenic transmission electron microscopy analysis of these fibers show an average fiber width of 2.89 nm, although the molecular-level structure of the aggregate is currently unknown. To determine a molecular model for these PIC fibers, the calculated spectra and dynamics using a Frenkel exciton model are compared to experiment. A chiral aggregate model in which the PIC monomers are neither parallel nor orthogonal to the long axis of the fiber is shown to replicate the experimental spectra most closely. This model can be physically realized by the sequential binding of PIC dimers and monomers to the ends of the fiber. Furthermore, these insights into the molecular aggregation model for aqueous PIC can also be applied to other similar cyanine-based supramolecular complexes with the potential for long-range energy transport, a key building block for the rational design of novel excitonic systems

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Estimating PV power from aggregate power measurements within the distribution grid

The increased integration of photovoltaic (PV) systems in distribution grids reduces visibility and situational awareness for utilities because the PV systems' power production is usually not monitored by them. To address this problem, a method called Contextually Supervised Source Separation (CSSS) has been recently adapted for real-time estimation of aggregate PV active power generation from aggregate net active and reactive power measurements at a point in a radially configured distribution grid (e.g., substation). In its original version, PV disaggregation is formulated as an optimization problem that fits linear regression models for the aggregate PV active power generation and true substation active power load. This paper extends the previous work by adding regularization terms in the objective function to capture additional contextual information such as smoothness, by adding new constraints, by introducing new regressors such as ambient temperature, and by investigating the use of time-varying regressors. Furthermore, we perform extensive parametric analysis to study tuning of the objective function weighting factors in a way that maximizes performance and robustness. The proposed PV disaggregation method can be applied to networks with either a single PV system (e.g., megawatt scale) or many distributed ones (e.g., residential scale) connected downstream of the substation. Simulation studies with real field recorded data show that the enhancements of the proposed method reduce disaggregation error by 58% in winter and 35% in summer compared to previous CSSS-based work. When compared against a commonly used transposition model based approach, the reduction in disaggregation error is more pronounced (78% reduction in winter and 45% in summer). Additional simulations indicate that the proposed algorithm is also applicable for PV systems with time-varying power factors. In conclusion, overall, our results show that—with appropriate modeling and tuning—it is possible to accurately estimate the aggregated PV active power generation of a distribution feeder with minimal or no additional sensor deployment.

14 SOLAR ENERGY↗

Semi-grand canonical Monte Carlo simulation of the acrolein induced surface segregation and aggregation of AgPd with machine learning surrogate models

The single atom alloy of AgPd has been found to be a promising catalyst for the selective hydrogenation of acrolein. It is also known that the formation of Pd islands on the surface will greatly reduce the selectivity of the reaction. As a result, the surface segregation and aggregation of Pd on the AgPd surface under reaction conditions of selective hydrogenation of acrolein are of great interest. In this work, we lay out a workflow that can predict the surface segregation and aggregation of Pd on a FCC(111) AgPd surface with and without the presence of acrolein. We use machine learning surrogate models to predict the AgPd bulk energy, AgPd slab energy, and acrolein adsorption energy on AgPd slabs. Then, we use the semi-grand canonical Monte Carlo simulation to predict the surface segregation and aggregation under different bulk Pd concentrations. Under vacuum conditions, our method predicts that only trace amount of Pd will exist on the surface at Pd bulk concentrations less than 20%. However, with the presence of acrolein, Pd will start to aggregate as dimers on the surface at Pd bulk concentrations as low as 6.5%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiple generations of grain aggregation in different environments preceded solar system body formation

The solar system formed from interstellar dust and gas in a molecular cloud. Astronomical observations show that typical interstellar dust consists of amorphous (a-) silicate and organic carbon. Bona fide physical samples for laboratory studies would yield unprecedented insight about solar system formation, but they were largely destroyed. The most likely repositories of surviving presolar dust are the least altered extraterrestrial materials, interplanetary dust particles (IDPs) with probable cometary origins. Cometary IDPs contain abundant submicron a-silicate grains called GEMS (glass with embedded metal and sulfides), believed to be carbon-free. Some have detectable isotopically anomalous a-silicate components from other stars, proving they are preserved dust inherited from the interstellar medium. However, it is debated whether the majority of GEMS predate the solar system or formed in the solar nebula by condensation of high-temperature (>1,300 K) gas. Here, we map IDP compositions with single nanometer-scale resolution and find that GEMS contain organic carbon. Mapping reveals two generations of grain aggregation, the key process in growth from dust grains to planetesimals, mediated by carbon. GEMS grains, some with a-silicate subgrains mantled by organic carbon, comprise the earliest generation of aggregates. These aggregates (and other grains) are encapsulated in lower-density organic carbon matrix, indicating a second generation of aggregation. Since this organic carbon thermally decomposes above ~450 K, GEMS cannot have accreted in the hot solar nebula, and formed, instead, in the cold presolar molecular cloud and/or outer protoplanetary disk. We suggest that GEMS are consistent with surviving interstellar dust, condensed in situ, and cycled through multiple molecular clouds.

79 ASTRONOMY AND ASTROPHYSICS↗

RAPID COAGULATION OF POROUS DUST AGGREGATES OUTSIDE THE SNOW LINE: A PATHWAY TO SUCCESSFUL ICY PLANETESIMAL FORMATION

Rapid orbital drift of macroscopic dust particles is one of the major obstacles to planetesimal formation in protoplanetary disks. We re-examine this problem by considering the porosity evolution of dust aggregates. We apply a porosity model based on recent N-body simulations of aggregate collisions, which allows us to study the porosity change upon collision for a wide range of impact energies. As a first step, we neglect collisional fragmentation and instead focus on dust evolution outside the snow line, where the fragmentation has been suggested to be less significant than inside the snow line because of the high sticking efficiency of icy particles. We show that dust particles can evolve into highly porous aggregates (with internal densities of much less than 0.1 g cm{sup -3}) even if collisional compression is taken into account. We also show that the high porosity triggers significant acceleration in collisional growth. This acceleration is a natural consequence of the particles' aerodynamical properties at low Knudsen numbers, i.e., at particle radii larger than the mean free path of the gas molecules. Thanks to this rapid growth, the highly porous aggregates are found to overcome the radial drift barrier at orbital radii less than 10 AU (assuming the minimum-mass solar nebula model). This suggests that, if collisional fragmentation is truly insignificant, formation of icy planetesimals is possible via direct collisional growth of submicron-sized icy particles.

79 ASTRONOMY AND ASTROPHYSICS↗

Design and Implementation of Papyrus: Parallel Aggregate Persistent Storage

A surprising development in recently announced HPC platforms is the addition of, sometimes massive amounts of, persistent (nonvolatile) memory (NVM) in order to increase memory capacity and compensate for plateauing I/O capabilities. However, there are no portable and scalable programming interfaces using aggregate NVM effectively. This paper introduces Papyrus: a new software system built to exploit emerging capability of NVM in HPC architectures. Papyrus (or Parallel Aggregate Persistent -YRU- Storage) is a novel programming system that provides features for scalable, aggregate, persistent memory in an extreme-scale system for typical HPC usage scenarios. Papyrus mainly consists of Papyrus Virtual File System (VFS) and Papyrus Template Container Library (TCL). Papyrus VFS provides a uniform aggregate NVM storage image across diverse NVM architectures. It enables Papyrus TCL to provide a portable and scalable high-level container programming interface whose data elements are distributed across multiple NVM nodes without requiring the user to handle complex communication, synchronization, replication, and consistency model. We evaluate Papyrus on two HPC systems, including UTK Beacon and NERSC Cori, using real NVM storage devices.

Kim, Jungwon↗

Opportunities for Price Manipulation by Aggregators in Electricity Markets

Aggregators of distributed generation are playing an increasingly crucial role in the integration of renewable energy in power systems. However, the intermittent nature of renewable generation makes market interactions of aggregators difficult to monitor and regulate, raising concerns about potential market manipulation by aggregators. In this paper, we study this issue by quantifying the profit an aggregator can obtain through strategic curtailment of generation in an electricity market. We show that, while the problem of maximizing the benefit from curtailment is hard in general, efficient algorithms exist when the topology of the network is radial (acyclic). Further, we highlight that significant increases in profit are possible via strategic curtailment in practical settings.

Azizan Ruhi, Navid (ORCID:0000000242992963)↗

Microstructure and bonding between calcium aluminate cement‐containing gahnite–alumina matrix and refractory aggregates

Calcium aluminate cement enhances the thermomechanical properties of refractory castables through the formation of acicular calcium hexaluminate (CaO·6Al 2 O 3 ), Ca 2 Mg 2 Al 28 O 46 (CAM-I), and CaMg 2 Al 16 O 27 (CAM-II) phases in MgO- or MgAl 2 O 4 -containing castables. The compatibility of CA 6 with gahnite (ZnAl 2 O 4 ), and acicular Ca 2 Zn 2 Al 28 O 46 (CAZ-I) and CaZn 2 Al 16 O 27 (CAZ-II) phases formation have been previously reported. Here, in this work, the interaction between a CAC binder containing ZnAl 2 O 4 -Al 2 O 3 matrix with commonly used refractory aggregates such as tabular alumina (TA), alumina-rich (AR90, AR78) and stoichiometric (SM72) MgAl 2 O 4 spinels, and fused and dead-burned magnesia (FM, DBM, respectively) were investigated at 1650°C for 5 h. Microstructural analysis, using digital microscopy, scanning electron microscopy, and energy dispersive spectroscopy, revealed the formation of acicular CaZn 0.18 Al 11.82 O 18.91 , CAZ-I and CAZ-II grains, and strong interfacial bonding between the matrix and TA and spinel aggregates. FM and DBM were found to debond from the matrix. Thick interface layers were observed between the matrix and all the aggregates but TA. Null hypothesis significance testing (NHST) shows that the difference in the number of acicular grains between the interface zone and the bulk matrix (Z) is statistically significant for AR90/Z, SM72/Z, FM/Z, and DBM/Z interfaces, but not significant for TA/Z and AR78/Z. The role of the aggregates’ chemistry on the interfacial bonding and microstructure evolution is discussed.

Ramteke, Rajat Durgesh [Univ. of Alabama, Birmingh↗

SU-G-TeP4-09: Development of a Plan Data Aggregator for Time Efficient Physics Second-Checks of Machine Parameters for External Beam Treatment Plans

Purpose: Physics second-checks for external beam radiation therapy are performed, in-part, to verify that the machine parameters in the Record-and-Verify (R&V) system that will ultimately be sent to the LINAC exactly match the values initially calculated by the Treatment Planning System (TPS). While performing the second-check, a large portion of the physicists’ time is spent navigating and arranging display windows to locate and compare the relevant numerical values (MLC position, collimator rotation, field size, MU, etc.). Here, we describe the development of a software tool that guides the physicist by aggregating and succinctly displaying machine parameter data relevant to the physics second-check process. Methods: A data retrieval software tool was developed using Python to aggregate data and generate a list of machine parameters that are commonly verified during the physics second-check process. This software tool imported values from (i) the TPS RT Plan DICOM file and (ii) the MOSAIQ (R&V) Structured Query Language (SQL) database. The machine parameters aggregated for this study included: MLC positions, X&Y jaw positions, collimator rotation, gantry rotation, MU, dose rate, wedges and accessories, cumulative dose, energy, machine name, couch angle, and more. Results: A GUI interface was developed to generate a side-by-side display of the aggregated machine parameter values for each field, and presented to the physicist for direct visual comparison. This software tool was tested for 3D conformal, static IMRT, sliding window IMRT, and VMAT treatment plans. Conclusion: This software tool facilitated the data collection process needed in order for the physicist to conduct a second-check, thus yielding an optimized second-check workflow that was both more user friendly and time-efficient. Utilizing this software tool, the physicist was able to spend less time searching through the TPS PDF plan document and the R&V system and focus the second-check efforts on assessing the patient-specific plan-quality.

60 APPLIED LIFE SCIENCES↗

Empirical Study of Focus-Plus-Context and Aggregation Techniques for the Visualization of Streaming Data

Analysis of streaming data often involves both real-time monitoring of incoming data as well as contextual awareness of data history. A focus-plus-context approach can support both goals, with variable levels of visual aggregation making it possible to provide a high level of detail for incoming and recent data while providing contextual information about recent history. Visual aggregation reduces data resolution in order to show the context of data over large periods of time within a limited display space. With a controlled experiment, we evaluated the effectiveness of different types of aggregation for four types of stream-analysis tasks. Overall, the results show that a focus-plus-context design has little negative impact on the ability to successfully monitor and analyze streaming data, making it possible to show longer periods of time than other approaches. However, visual aggregation can be problematic for trend recognition tasks. This research demonstrates how the effectiveness of the visualization depends on the specifics of the analysis task.

Ragan, Eric↗

Boundary Layer Height and Buoyancy Determine the Horizontal Scale of Convective Self-Aggregation

Organized rainstorms and their associated overturning circulations can self-emerge over an ocean surface with uniform temperature in cloud-resolving simulations. This phenomenon is referred to as convective self-aggregation. Convective self-aggregation is argued to be an important building block for tropical weather systems and may help regulate tropical atmospheric humidity and thereby tropical climate stability. Here the author presents a boundary layer theory for the horizontal scale λ of 2D (x, z) convective self-aggregation by considering both the momentum and energy constraints for steady circulations. This theory suggests that λ scales with the product of the boundary layer height h and the square root of the amplitude of density variation between aggregated moist and dry regions in the boundary layer, and that this density variation mainly arises from the moisture variation due to the virtual effect of water vapor. Furthermore, this theory predicts the following: 1) the order of magnitude of λ is ~2000 km, 2) the aspect ratio of the boundary layer λ/h increases with surface warming, and 3) λ decreases when the virtual effect of water vapor is disabled. These predictions are confirmed using a sui te of cloud-resolving simulations spanning a wide range of climates.

54 ENVIRONMENTAL SCIENCES↗

Shapes and Fall Orientations of Ice Particle Aggregates

Testing the often-made assumption that ice particle aggregates (snowflakes) are well represented by oblate spheroids, ellipsoid fits are applied to aggregate images. An algorithm to retrieve both the ellipsoidal parameters and the orientations of the fitted ellipsoids is applied to Multi-Angle Snowflake Camera measurements of ice particle aggregates observed in Alaska. The resulting ellipsoids have shapes closer to prolate spheroids than the oft-assumed oblate spheroids. A robust linear relationship exists between the two characteristic aspect ratios of the ellipsoids. The most probable orientation of the maximum dimension of the retrieved ellipsoids is not in the horizontal plane, and the rotational angles of the maximum dimensions in the horizontal plane are not uniform, but instead display some correlation with the wind direction at the times of the measurements. The retrieval results can be used to improve the representation of aggregates in microphysics and/or electromagnetic radiation scattering models applicable to radar and satellite measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Inter-Species Cross-Seeding: Stability and Assembly of Rat–Human Amylin Aggregates

Diseases such as type 2 diabetes, Alzheimer’s and Parkinson’s share as common feature the accumulation of mis-folded disease-specific protein aggregates into fibrillar structures, or plaques. These fibrils may either be toxic by themselves, or act as reservoirs for smaller cytotoxic oligomers. This suggests to investigate molecules as potential therapeutics that either reduce fibril formation or increase fibril stability. One example is rat amylin, which can inhibit aggregation of human amylin, a hallmark of type 2 diabetes. In the present paper, we use molecular dynamics to compare the stability of various preformed aggregates, built out of either human amylin, rat amylin, or mixtures of both. We considered two types of fibril-like oligomers: a single-layer in-register conformation, and a double-layer conformation in which the first U-shaped layer consists of rat amylin and the second layer of human amylin. Our results explain the weak amyloid-inhibiting properties of rat amylin and suggest that membrane leakage due to pore formation is responsible for the toxicity of rat amylin observed in a recent experiment. Together, our results put in question the use of rat amylin or the similar FDA approved drug pramlintide as an inhibitor of human amylin aggregation. They also point to mixed human-rat amylin fibril-like oligomers as possible model-systems for studies of amyloid formation that involve cross-species transmission.

59 BASIC BIOLOGICAL SCIENCES↗

Commercial and Multifamily Building Tenant Energy Usage Aggregation and Privacy

In a number of cities and states, building owners are required to disclose and/or benchmark their building energy use. This requires the building owner to possess monthly whole-building energy usage information, which can be challenging for buildings in which individual tenants have their own utility meters and accounts with the utility. Some utilities and utility regulators have turned to aggregation of customer data as a way to give building owners the whole-building energy usage data while protecting customer privacy. However, no utilities or regulators appear to have conducted a concerted statistical, cybersecurity, and privacy analysis to justify the level of aggregation selected. Therefore, the Tennant Data Aggregation Task was established to help utilities address these issues and provide recommendations as well as a theoretical justification of the aggregation threshold. This study is focused on the use case of submitting data for ENERGY STAR Portfolio Manager (ESPM), but it also looks at other potential use cases for monthly energy consumption data.

data aggergation↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 13: Functional Specification Report(Deliverable D9))

This report provides functional specification for the AGGREGATE project and associated modules/ tools being developed for outage management and restoration with the Distributed Energy Resources (DERs). This report also provide initial validation of the developed modules and performance metrics. The AGGREGATE team at this stage has been collaborating with General Electric (GE) and Seattle City Light (SCL) to move forward from offline validation to online validation using commercial advanced distribution management system (ADMS). Hence, the functional specifications documents, which outline the requirement of various modules, is provided to address the integration of the modules, including 1) real-time model update and aggregation tools module, 2) observability and controllability metric module, 3) fault location solution service restoration module, 4) transmission-distribution co-simulation module, and 5) advanced distribution management system module. integration of different AGGREGATE modules and functional specification provides the foundation for online multi-scenario testing using SCL system model.

42 ENGINEERING↗