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At least 523 records · Page 29

Uranium particle age dating, aggregation, and model age best estimators

We present important aspects of uranium particle age dating by Large-Geometry Secondary Ion Mass Spectrometry (LG-SIMS) that can introduce bias and increase model age uncertainties, especially for small, young, and/or low-enriched particles. This metrology is important for applications related to International Nuclear Safeguards. We explore influential factors related to model age estimation, including the effects of evolving surface chemistry on inter-element measurements of particles (e.g., Th and U), detector background, and aggregation methods using simulated and actual particle samples. We introduce a new model age estimator, called “mid68”, that supplements 95% confidence intervals, providing a “best estimate” and uncertainty about the most likely age. The mid68 estimator can be calculated using the Feldman and Cousins method or Bayesian methods and provides a value with a symmetric uncertainty that can be used for calculations and approximate aggregation of processed model age values when the raw data and correction factors are not available. For particles yielding low 230 Th counts amidst nonzero detector background, their underlying model age probability distributions are asymmetric, so the mid68 estimator provides additional robust information regarding the underlying model age likelihood. This study provides a comprehensive and timely examination of critical aspects of uranium particle age dating as more laboratories establish particle chronometry capabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pricing Strategy of Electric Vehicle Aggregators Based on Locational Marginal Price to Minimize Photovoltaic (PV) Curtailment

The global climate crisis demands urgent action to mitigate global warming. Using renewable energy sources, such as solar and wind power, for electricity generation is crucial. This shift from centralized to distributed power systems, however, brings challenges, including voltage fluctuations and renewable energy curtailment. The rapid growth of the electric vehicle (EV) industry adds complexity, increasing overall electricity demand and straining the power supply during peak charging times. This paper proposes a scheduling strategy for EV aggregators to reduce renewable energy curtailment and stabilize grid operation by strategically scheduling EV charging. Using Multi -Agent Transport Simulation (MATSim), a traffic simulation tool, EV driving data in Denver, Colorado, USA, were modeled. The EV aggregator adjusts charging fees based on locational marginal prices, encouraging EVs to charge at different stations according to pricing. Simulations on an IEEE 33-bus system with distributed energy resources and EV charging stations validate the proposed algorithm, demonstrating its effectiveness in reducing curtailment by 12.55% and stabilizing grid operation.

33 ADVANCED PROPULSION SYSTEMS↗

A comparison of thermal zone aggregation methods

The impact of increasing energy prices on building operation budgets has fueled demand for more energy-efficient structures. Existing building energy simulation tools generate an immense amount of data yet comparatively little knowledge. This paper introduces a framework that allows aggregation-based model reduction to operate on geometric building information models. The resulting aggregation sequence provides designers with faster simulations and affords insight into complex multi-scale thermal interactions. A comparison of the trade-off between simulation speed and accuracy for three hierarchical cluster partitioning methods concludes the discussion.

97 MATHEMATICS AND COMPUTING↗

A Reduced-Order Aggregated Model for Parallel Inverter Systems with Virtual Oscillator Control

This paper introduces a reduced-order aggregated model for parallel-connected inverters controlled with virtual oscillator control (VOC). The premise of VOC is to modulate inverter dynamics to emulate those of nonlinear oscillators with the goal of realizing a stable ac microgrid in the absence of communication, synchronous generation, or a stiff grid. To obtain a reduced-order model for a system of parallel-connected inverters with VOC, we first formulate a set of scaling laws that describe how the controller and filter parameters of a given inverter depend on its voltage and power rating. Subsequently, we show that N parallel inverters which adhere to this scaling law can be modeled with the same structure and hence the same computational burden of the model of a single inverter. The proposed aggregate model is experimentally validated on a system of three parallel inverters with heterogeneous power ratings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Real-Time Procurement Strategies of a Proactive Distribution Company With Aggregator-Based Demand Response

In this paper, we present a real-time trading framework for distribution networks where a rational aggregator is identified as a broker by contracting with individual demands and dealing with the distribution company. Demand response capability is characterized by the coexistence of elastic and inelastic demand components. A one-leader multi-follower bi-level model is proposed to derive the procurement strategies, i.e., the upperlevel problem intends to maximize the profit of the proactive distribution company, while the lower-level expresses the profit maximization per rational aggregator. The proposed model is then transformed into a solvable mathematical program with equilibrium constraints through a primal-dual approach. A modified 33-bus distribution network is utilized to demonstrate the effectiveness of the proposed model.

demand response (DR)↗

Homomorphic Encryption for Electrical Metering Aggregation: Protecting the Privacy of Building Tenants

Electrical meters are devices that measure consumer electricity usage. The data collected by these meters is necessary for utility billing and electrical grid management but can also be used to assess the environmental impact of buildings. Prior research has found that unprotected metering data could potentially be used to infer some information about the behaviors of building tenants by detecting changes in electricity usage. For example, a period of low electricity usage could suggest that the tenants are not in the building. As smart metering becomes more common, there is a growing need for data privacy protections for metering data that do not negatively impact the quality and availability of data used for energy management and billing applications. To identify potential solutions, we developed a Python-based data aggregation platform to analyze the potential efficacy of privacy-enhancing technologies for energy metering applications. This platform aggregates groups of metering sites into virtual buildings, which could potentially detach changes in electrical activity from individual tenants, making it more difficult to track the activity of a specific tenant. To further protect data during analysis, this project utilizes homomorphic encryption as part of its initial approach. Homomorphic encryption offers a means of protecting energy consumption data while permitting mathematical operations to be performed without the need to know the data contents. This allows for data to be processed into usable statistics without revealing energy consumption information. A series of homomorphic encryption libraries were evaluated to determine their applicability and limitations in the context of metering data. The use of these techniques may help to reassure consumers and encourage further adoption of smart grid infrastructure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fast-Tracking Technology Solutions to Boost Cybersecurity in Virtual Power Plant and Aggregator Operations

This presentation was presented at the Aggregation and Grid Security Workshop - held on June 17-18, 2025, at NREL in Golden, Colorado. The goal of the two-day workshop was to address the critical cybersecurity challenges for the future electric grid. This presentation overviews NREL's work in evaluating cybersecurity technology solutions for virtual power plant and aggregator operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Data-Driven and Multiscale Modeling of DNA-Templated Dye Aggregates

Dye aggregates are of interest for excitonic applications, including biomedical imaging, organic photovoltaics, and quantum information systems. Dyes with large transition dipole moments (μ) are necessary to optimize coupling within dye aggregates. Extinction coefficients (ε) can be used to determine the μ of dyes, and so dyes with a large ε (>150,000 M –1 cm –1 ) should be engineered or identified. However, dye properties leading to a large ε are not fully understood, and low-throughput methods of dye screening, such as experimental measurements or density functional theory (DFT) calculations, can be time-consuming. In order to screen large datasets of molecules for desirable properties (i.e., large ε and μ), a computational workflow was established using machine learning (ML), DFT, time-dependent (TD-) DFT, and molecular dynamics (MD). ML models were developed through training and validation on a dataset of 8802 dyes using structural features. A Classifier was developed with an accuracy of 97% and a Regressor was constructed with an R2 of above 0.9, comparing between experiment and ML prediction. Using the Regressor, the ε values of over 18,000 dyes were predicted. The top 100 dyes were further screened using DFT and TD-DFT to identify 15 dyes with a μ relative to a reference dye, pentamethine indocyanine dye Cy5. Two benchmark MD simulations were performed on Cy5 and Cy5.5 dimers, and it was found that MD could accurately capture experimental results. The results of this study exhibit that our computational workflow for identifying dyes with a large μ for excitonic applications is effective and can be used as a tool to develop new dyes for excitonic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

light Scattering by Aggregate Particles

We have investigated scattering properties of aggregates, emphasizing the size of constituent monomers comparable with the wavelength of visible light, in order to model the scattering properties of cometary dust. This has differentiated our study from previous investigations of aggregates in which the size of the monomers was much smaller than the wavelength.

Polarization scattering comets cometary dust aggre↗

FATE: The drifting Fish Aggregating Device (dFAD) TrajEctory Modeling Tool for Marine Protected Area Management

Drifting fish aggregating devices (dFADs) routinely enter marine protected areas (MPAs) and may undermine MPA protections by drifting out of the MPA with the aggregated fish biomass, or grounding and damaging sensitive coral reef habitats. MPA managers must decide whether to deploy resources in response to dFAD intrusions. To address this issue, we propose to quantify dFAD activity in relation to ocean currents, fish biomass, and animal telemetry at Palmyra Atoll, part of the Pacific Remote Islands Marine National Monument in the central Pacific Ocean. Specifically, we propose to develop the dFAD TrajEctory Tool (FATE). FATE is an innovative decision support tool that will use NASA observations and numerical models to predict future dFAD trajectories and inform TNC and USFWS whether they should deploy tactical resources (boats, personnel) to monitor, intercept, or retrieve dFADs that have entered the Refuge. The objectives are to use NASA observational constraints on ocean winds and currents to assist with the ecological management of the Palmyra Atoll NWR and MPA. Specifically, we will deliver an operational software tool that quantifies the grounding risk associated with each tracked dFAD and decision support for grounding risk mitigation via intercept at sea. This project addresses Element 3.3: Protected area management of the 2022 Ecological Conservation Solicitation by developing a tool needed by MPA managers to make tactical and strategic decisions focused on improving the effectiveness of MPAs. By quantifying the riskof dFADs, this project will help monitor and better inform the deployment of tactical (ships/personnel) and strategic (legislative) resources to better manage MPAs. This project is a collaboration between The Nature Conservancy, who operate long-term projects within the Palmyra MPA, and the U.S. Fish and Wildlife Service, who have the authority to make decisions related to its management. We expect that the results of our proposal will benefit marine resources within the Palmyra MPA and could be transferred to other remote MPAs within the US and other island nations within the Pacific Ocean.

TrajEctory↗

A Reduced-Order Aggregated Model for Parallel Inverter Systems with Virtual Oscillator Control: Preprint

This paper introduces a reduced-order aggregated model for parallel-connected inverters controlled with virtual oscillator control (VOC). The premise of VOC is to modulate inverter dynamics to emulate those of nonlinear oscillators with the goal of realizing a stable ac microgrid in the absence of communication, synchronous generation, or a stiff grid. To obtain a reduced-order model for a system of parallel-connected inverters with VOC, we first formulate a set of scaling laws that describe how the controller and filter parameters of a given inverter depend on its voltage and power rating. Subsequently, we show that N parallel inverters which adhere to this scaling law can be modeled with the same structure and hence the same computational burden of the model of a single inverter. The proposed aggregate model is experimentally validated on a system of three parallel inverters with heterogeneous power ratings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High‐Speed Slot‐Die Coating with Donor‐Priority Rapid Aggregation Kinetics for Improved Morphology and Efficiency in Ecofriendly Organic Solar Cells

Abstract Solution‐processable organic solar cells (OSCs) represent a promising renewable photovoltaic technology with significant potential for eco‐compatible production. While high power conversion efficiencies (PCEs) have been achieved in OSCs, scaling this technology for high‐throughput manufacturing remains challenging. Key reason lies in the lack of efficient control strategies for the complex and long‐duration morphology evolution during high‐speed coating process with ecofriendly solvents. Here, a donor‐priority rapid aggregation process (DP‐RAP) scheme is proposed to solve this issue by adjusting the aggregation kinetics of donor and acceptor components. DP‐RAP enables blends with a nanoscale fiber network structure and favorable crystallinity, which contributes to balanced carrier transport and reduced recombination losses. As a result, the PCE is improved from 14.3% (reference) to 17.4% (DP‐RAP) for ultra‐high speed coated PM6:BTP‐eC9 devices in atmosphere, which is one of the highest values for non‐halogenated solvent‐processed solar cells at coating speeds of 500 mm s −1 . Moreover, the DP‐RAP based devices remain a stable PCE of approximately 17.4% across a broad range of coating speeds (20–500 mm s −1 ), illustrating its tolerance to the varied manufacturing conditions. This work highlights a promising avenue for the high‐speed, ecofriendly production of efficient OSCs, pushing the boundaries of practical manufacturing in renewable energy technologies.

Chemistry↗

High-Voltage Photogeneration Exclusively via Aggregation-Induced Triplet States in a Heavy-Atom-Free Nonplanar Organic Semiconductor

The electron–hole recombination kinetics of organic photovoltaics (OPVs) are known to be sensitive to the relative energies of triplet and charge-transfer (CT) states. Yet, the role of exciton spin in systems having CT states above 1.7 eV—like those in near-ultraviolet-harvesting OPVs—has largely not been investigated. Here, aggregation-induced room-temperature intersystem crossing (ISC) to facilitate exciton harvesting in OPVs having CT states as high as 2.3 eV and open-circuit voltages exceeding 1.6 V is reported. Triplet excimers from energy-band splitting result in ultrafast CT and charge separation with nonradiative energy losses of <250 meV, suggesting that a 0.1 eV driving force is sufficient for charge separation, with entropic gain via CT state delocalization being the main driver for exciton dissociation and generation of free charges. This finding can inform engineering of next-generation active materials and films for near-ultraviolet OPVs with open-circuit voltages exceeding 2 V. Contrary to general belief, this work reveals that exclusive and efficient ISC need not require heavy-atom-containing active materials. Molecular aggregation through thin-film processing provides an alternative route to accessing 100% triplet states on photoexcitation.

25 ENERGY STORAGE↗

Engineering of Self‐Aggregation‐Resistant MnO 2 Heterostructure with A Built‐in Field for Enhanced High‐Mass‐Loading Energy Storage

Abstract Although MnO 2 has been intensively investigated for energy storage, further applications are limited by van der Waals force‐triggered self‐aggregation that always leads to poorly exposed active sites and compromised reaction dynamics, especially under high‐mass‐loading conditions. Herein, by synergistically coupling interfacial modulation with the Kirkendall effect, this work achieves in situ topological structure reorganization of MnOOH toward the high‐aspect‐ratio MnO 2 heterostructure (Heter‐MnO 2 ) with fully exposed active sites, which is ready to assemble into self‐supporting high‐mass‐loading film (30 mg cm −2 ) with restrained self‐aggregation. Theoretical calculation and dynamics analysis results demonstrate the generation of the built‐in field within the heterostructure, thus enhancing the electronic‐transfer and ionic‐adsorption/transport rates. As such, the 30 mg cm −2 Heter‐MnO 2 electrode achieves a superior areal capacitance of 4762 mF cm −2 at 1 mA cm −2 and a sound rate performance (79% at 100 mA cm −2 ) comparable to those of low‐mass‐loading/thin‐film electrodes. As a proof of concept, the fabricated planar interdigital quasi‐solid‐state symmetric micro‐supercapacitor (MSC) based on the Heter‐MnO 2 electrode can deliver a remarkable areal capacitance of 181 mF cm −2 and a considerable volumetric energy density of 10.3 mWh cm −3 . This methodology highlights the promise of surface/interface chemistry modulation for the configuration of easy‐to‐integrate hierarchical nanostructures to better meet practical energy applications.

Chemistry↗

Surfactant-Induced Interfacial Aggregation of Porphyrins for Structuring Color-Tunable Liquids

Locking nonequilibrium shapes of liquids into targeted architectures by interfacial jamming of nanoparticles is an emerging area in material science. 5,10,15,20-tetrakis(4-sulfonatophenyl) porphyrin (H 6 TPPS) shows three different aggregation states that present an absorption imaging platform to monitor the assembly and jamming of supramolecular polymer surfactants (SPSs) at the liquid/liquid interface. The interfacial interconversion of H 6 TPPS, specifically H 4 TPPS 2- dissolved in water, from J- to an H-aggregation was induced by strong electrostatic interactions with amine-terminated polystyrene dissolved in toluene at the water/toluene interface. We find that this resulted in color-tunable liquids due to interfacial jamming of the SPSs formed between H 4 TPPS 2- and amine-terminated polystyrene. However, the formed SPSs cannot lock in nonequilibrium shapes of liquids. In addition, a self-wrinkling behavior was observed when amphiphilic triblock copolymers of PS-block-poly(2-vinylpyridine)-block-poly(ethylene oxide) were used to interact with H 4 TPPS 2- . Subsequently, the SPSs formed can lock in nonequilibrium shapes of liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian model aggregation for ensemble-based estimates of protein pKa values

This paper investigates an ensemble-based technique called Bayesian Model Averaging (BMA) to improve the performance of protein amino acid p$K_a$ predictions. Structure-based p$K_a$ calculations play an important role in the mechanistic interpretation of protein structure and are also used to determine a wide range of protein properties. A diverse set of methods currently exist for p$K_a$ prediction, ranging from empirical statistical models to {\it ab initio} quantum mechanical approaches. However, each of these methods are based on a set of assumptions that have inherent bias and sensitivities that can effect a model's accuracy and generalizability for p$K_a$ prediction in complicated biomolecular systems. We use BMA to combine eleven diverse prediction methods that each estimate pKa values of amino acids in staphylococcal nuclease. These methods are based on work conducted for the pKa Cooperative and the pKa measurements are based on experimental work conducted by the Garc{\'i}a-Moreno lab. Our study demonstrates that the aggregated estimate obtained from BMA outperforms all individual prediction methods in our cross-validation study with improvements from 40-70\% over other method classes. This work illustrates a new possible mechanism for improving the accuracy of p$K_a$ prediction and lays the foundation for future work on aggregate models that balance computational cost with prediction accuracy.

electrostatics↗

Aggregation of Heteropolyanions Implicates the Presence of Zundel Ions Near Air-Water Interfaces

Protons play crucial roles in the interactions between hetero-polyanions (HPAs) in aqueous solutions and solid acid salts. We report the aggregation behaviours of Keggin HPAs near the surfaces of heteropolyacid solutions. The structure of the aggregated HPA layer near the solution-vapour phase boundary closely resembles the solid-state crystal structure of the hetero-polyacids in which the HPAs are connected by Zundel ions. The resemblance not only implicates the presence of protons in the form of planar Zundel ions near the air-water interface but, also, suggests that these align parallel to the interface. This study demonstrates an indirect means of assessing the impact of protons on HPA interactions near air-water interfaces and, in general, provides new insights about interfacial proton chemistry of heteropolyacids.

Air-water interface↗

Residual fracture energy of natural and recycled aggregate concrete after exposure to high temperatures

Abstract Fracture energy ( G F ) represents the average total energy consumed in the whole process of crack propagation. Using one parameter of G F , it is not sufficient to describe the fracture behavior during crack stable and unstable propagation periods. In this study, the G F , stable fracture energy ( G FS ) and unstable fracture energy ( G FU ) of natural and recycled aggregate concrete (RAC) were investigated by using three‐point bending tests. Totally, 128 cubic specimens (100 mm × 100 mm × 100 mm) and 64 notched beams with size of 510 mm × 100 mm × 100 mm were manufactured to test the compressive strength ( f cu ), splitting tensile strength ( f t ), load–deflection (P‐δ), and load‐cracking mouth opening displacement (P‐CMOD) curves, considering different replacement levels (0%, 30%, 70%, and 100%) of recycled coarse aggregate (RA) and high temperatures exposure (20, 100, 200, and 300°C). The effects of RA substitutions and temperatures on basic mechanical properties, G F , G FS , and G FU were analyzed. The results demonstrated that the f cu , f t , and elastic modulus ( E ) decreased with the incremental temperature. The G FS of concrete with different RA substitutions first decreased and then increased, and the minimum value appeared at 200°C. The G F and G FU of concrete with different RA substitutions increased with the elevated temperature, and the increase rate decreased with RA substitutions. When the temperature is less than 100°C, the G F and G FU of concrete remained mostly unchanged with the increase of RA substitutions, while the temperature reached 200 and 300°C, the G F and G FU of concrete increased and decreased with the increase of RA substitutions, respectively.

Chen, Wei↗