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Investigation of ion irradiation effects on mineral analogues of concrete aggregates

Irradiation can cause prominent damage to reactor concrete aggregates leading to amorphization, strength and modulus decrease, radiation induced volume expansion (RIVE) and micro-cracking, which limits their long-term performance. Here, to develop an improved understanding of irradiation effects in concrete, three mineral analogues of concrete aggregates (limestone, marble and quartzite) were irradiated by 5.5 MeV He ions and 13 MeV Ni ions to surface doses of 0.011 displacements per atom (dpa) and 0.23 dpa, respectively, at room temperature. The two different ion species allow irradiation spectrum effects (ionizing and displacive) to be examined. Irradiation induced cracks were observed in He irradiated limestone and marble, and Ni irradiated quartzite. Full amorphization was observed in Ni irradiated quartzite with 14.3 % RIVE, and ∼25 % hardness and modulus decrease, while almost no change was observed in He irradiated quartzite except 4.35 % RIVE, revealing a possible ionization enhanced diffusion effect for high energy light ions. Furthermore, partial amorphization was observed in Ni irradiated marble and limestone matrix with a 12 % hardness decrease in marble while no amorphization was observed for He irradiation with a 20 % hardness increase in limestone matrix. The role of knock-on damage and irradiation spectrum on amorphization, volumetric expansion and mechanical property changes are discussed. Moreover, the onset and critical doses for amorphization and RIVE in quartz are obtained for ion irradiations at room temperature. The dose dependence of RIVE exhibits a delay compared to the amorphization behavior. The superior irradiation resistance of calcite phase compared to quartz phase implies there could be advantages to using calcareous aggregates and lowering the usage of siliceous aggregates for concrete in nuclear power plants for extended operation beyond 60 years. However, other effects such as corrosion, aging and reactions during severe accidents should also be considered, and further investigations are needed.

Amorphous

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

Aggregation and Grid Security Workshop Report

The Aggregation and Grid Security Workshop - held on June 17-18, 2025, National Laboratory of the Rockies (NLR) in Golden, Colorado - brought together approximately 40 external stakeholders from the energy sector, including VPP owner/operators, aggregators, OEMs, utilities, testing & certification labs, trade associations, and cybersecurity vendors. Led by key facilitators, the workshop focused on addressing cybersecurity challenges and enhancing grid resilience for aggregated Distributed Energy Resources (DERs) and Virtual Power Plants (VPPs). The workshop was catalyzed by recognition that traditional, rearward-looking regulatory frameworks are insufficient to keep pace with technological change. There is a "missing understanding" of risk, an "absent security basis" for managing it, and an "untenable responsibility" due to unclear ownership and requirements. The workshop aimed to shift the mindset from reacting to past crises to proactively preparing for emerging threats, fostering forward resilience through risk simulation and collaborative action. This report summarizes the outcomes of the workshop, marking it a significant step toward a secure, reliable and affordable energy future.

14 SOLAR ENERGY

Chain rigidity controlled aggregation ability and solid-state microstructures for efficient stretchable conjugated polymer films

Stretchable conjugated polymer films with good electrical performance under mechanical deformation are highly desirable for soft electronics. However, the mechanical and electrical properties of these films, particularly in conjugated polymer:elastomer blends, are not fully understood at molecular level. Here, this study explores the relationships among molecular structure, aggregation ability, film microstructure, and the electrical/mechanical properties of three diketopyrrolopyrrole-based conjugated polymers (P1, P2, P3) with decreasing backbone rigidity and their corresponding polymer:elastomer blends. The most flexible polymer P3 shows strong aggregation, which forms highly crystalline fibers to produce fragile neat film and produces large isolated crystallites restricting charge transport in blend film. As chain rigidity increases, the P1 and P2 polymers show weaker aggregation, and produce smaller crystallites in neat films with enhanced ductility. P1 and P2 based blend films display nanocrystallites polymer networks with dispersed elastomer domains. As a result, we achieved near-constant charge mobility before and after stretching under 50 % strain for P2-based blend films with well-controlled pathways for both charge transport and energy dissipation. This study demonstrates the critical role of backbone rigidity in regulating the properties of stretchable conjugated polymer films, paving the way for more reliable and deformable materials in soft electronics.

36 MATERIALS SCIENCE

Effect of molecular permanent dipole moment on guest aggregation and exciton quenching in phosphorescent organic light emitting diodes

This study explores the effect of molecular permanent dipole moment (PDM) on aggregation of guest molecules in phosphorescent host–guest organic light-emitting diodes (OLEDs). Through a combination of photoluminescence measurements, high-angle annular dark-field scanning transmission electron microscopy analysis, and an Ising model based physical vapor-deposition simulation, we show that higher PDM of tris[2-phenylpyridinato-C2,N]iridium(III) guest can actually lead to a reduced aggregation relative to tris[bis[2-(2-pyridinyl-N)phenyl-C] (acetylacetonato)iridium(III) when doped into a non-polar host 1,3,5-tris(carbazol-9-yl)benzene. This study further explores the effect of host polarity by using a polar host 3′,5′-di(carbazol-9-yl)-[1,1′-biphenyl]-3,5-dicarbonitrile, and it is shown that the polar host leads to reduced guest aggregation. In conclusion, this study provides a comprehensive understanding of the impact of molecular PDM on OLED material efficiency and stability, providing insights for optimizing phosphorescent OLED materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Minimizing particle aggregation in Sm 2 Fe 17 N 3 powders: A CaO-assisted reduction-diffusion approach

We report a novel synthesis of Sm 2 Fe 17 N 3 powders using a CaO-assisted reduction-diffusion (RD) approach. CaO plays a crucial role during mechanochemical processing – acting both as a dispersant and a surface coating agent, which helps to prevent agglomeration due to sintering of Sm 2 Fe 17 particles during the RD step. Together with the added dispersant, the CaO by-product formed during RD can be easily removed in the washing step resulting in fewer aggregated Sm 2 Fe 17 N 3 particles and lower oxygen contamination in the final product. The impact of varying CaO amounts was examined, and synthesis conditions were optimized to achieve phase-pure Sm 2 Fe 17 N 3 powders with less aggregation of magnetic particles. The powders synthesized with addition of 1 wt% CaO as dispersant exhibited the highest hard-magnetic properties: a coercivity (H c ) of 10.7 kOe and a maximum energy product ((BH) max ) of 17.3 MGOe. By densifying the Sm 2 Fe 17 N 3 powders using high-pressure spark plasma sintering, a bulk magnet with a (BH) max of 21.1 MGOe with 88 % of theoretical density was produced. In conclusion, reducing aggregation of the Sm 2 Fe 17 N 3 increases coercivity and remanence of these magnets.

36 MATERIALS SCIENCE

Radiation damages the silicates present in polyphasic mineral aggregates causing concrete’s degradation

While many U.S. nuclear power plants have submitted Subsequent License Renewal Application to operate beyond 60 years, others are already considering Operations Beyond Eighty years. In such cases, concrete biological shields are exposed to neutron and gamma radiation exceeding prescribed thresholds. Radiation-induced volumetric expansion (RIVE), extensively studied in single crystals, may also contribute to the degradation of polycrystalline aggregates. Since minerals differ in atomic structure and chemistry, radiation can affect them in distinct ways. This study examines quartzite, marble, and limestone to evaluate how irradiation affects their physical attributes and chemical reactivity. Results show crystalline silicates experience significant RIVE damage and enhanced reactivity in alkaline solutions compared to non-irradiated phases. Enhanced intra- and inter-granular dissolution could compromise aggregate integrity. An empirical correlation links silicate dissolution rate to atomic constraints (density, rigidity) and radiation dose, providing a predictive framework for estimating changes in silicate aggregate properties within radiation-exposed concrete.

Bouissonnié, Arnaud [Univ. of California, Los Ange

Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.

42 ENGINEERING

Distribution System Congestion Management - A Survey of Reliable Integration for Aggregated Resources and Microgrids

Rising penetration of consumer-owned Distribution Grid Resources (DGRs), increasingly managed by third party aggregators and enrolled in grid services and wholesale market programs, can create localized congestion in distribution networks. Managing these constraints is challenging due to a persistent coordination and information gap: utilities are accountable for reliability and have network topology and state visibility, while aggregators control the DGR capability needed to relieve congestion. This survey synthesizes congestion management solutions for distribution systems with high DGR penetration, covering both market-based mechanisms (distribution level markets, locational pricing, flexibility auctions) and non-market-based solutions (network reconfiguration, direct DGR control, demand response, curtailment, etc.). The literature is organized across three decision horizons: long term planning, operational planning, and real-time operation. Special attention is devoted to emerging distribution system operator architectures and coordination frameworks spanning transmission system operators, aggregators, and microgrids. Drawing on recent case studies and implementations, we distill best practices, identify key technical and economic barriers, and outline research directions. The evidence points to a shift toward integrated congestion management that combines market signals with technical controls, enabled by improved monitoring, forecasting, and closed loop control capabilities.

Active Distribution Networks (ADN)

Divide and conquer: using RhizoVision Explorer to aggregate data from multiple root scans using image concatenation and statistical methods

Roots are important in agricultural and natural systems for determining plant productivity and soil carbon inputs. Sometimes, the amount of roots in a sample is too much to fit into a single scanned image, so the sample is divided among several scans, and there is no standard method to aggregate the data. Here, we describe and validate two methods for standardizing measurements across multiple scans: image concatenation and statistical aggregation. We developed a Python script that identifies which images belong to the same sample and returns a single, larger concatenated image. These concatenated images and the original images were processed with RhizoVision Explorer, a free and open-source software. An R script was developed, which identifies rows of data belonging to the same sample and applies correct statistical methods to return a single data row for each sample. These two methods were compared using example images from switchgrass, poplar, and various tree and ericaceous shrub species from a northern peatland and the Arctic. Most root measurements were nearly identical between the two methods except median diameter, which cannot be accurately computed by statistical aggregation. We believe the availability of these methods will be useful to the root biology community.

59 BASIC BIOLOGICAL SCIENCES

Distributed Cross-Channel Hierarchical Aggregation for Foundation Models

Vision-based scientific foundation models hold significant promise for advancing scientific discovery and innovation. This potential stems from their ability to aggregate images from diverse sources—such as varying physical groundings or data acquisition systems—and to learn spatio-temporal correlations using transformer architectures. However, tokenizing and aggregating images can be compute-intensive, a challenge not fully addressed by current distributed methods. In this work, we introduce the Distributed Cross-Channel Hierarchical Aggregation (D-CHAG) approach designed for datasets with a large number of channels across image modalities. Our method is compatible with any model-parallel strategy and any type of vision transformer architecture, significantly improving computational efficiency. We evaluated D-CHAG on hyperspectral imaging and weather forecasting tasks. When integrated with tensor parallelism and model sharding, our approach achieved up to a 75% reduction in memory usage and more than doubled sustained throughput on up to 1,024 AMD GPUs on the Frontier Supercomputer.

Tsaris, Aristeidis (aris) [ORNL] (ORCID:0000000277

Direct Observation of Elusive (DTBM‐SEGPHOS)CuH Monomer Enables Mechanistic Insights Into Hydrocupration, Aggregation, and Dynamics of Alkene Functionalization Catalysis

The bulky diphosphine DTBM-SEGPHOS is widely employed in CuH-catalyzed transformations as it provides remarkably active catalyst systems. The transient (DTBM-SEGPHOS)CuH monomer (LCuH) is the often-invoked active species. However, its instability has prevented spectroscopic characterization and mechanistic elucidation, hindering mechanistic understanding. We report low-temperature NMR spectroscopic characterization of LCuH, enabling quantitative kinetic analysis of the stoichiometric hydrocupration and catalytic hydroboration of cyclopentene, as well as the structural identification of two CuH clusters. LCuH inserts cyclopentene at −43°C, reaffirming its high reactivity toward olefins. LCuH deactivates to form L 2 Cu 3 H 3 and L 2 Cu 4 H 4 clusters, in which LCuH dimerization initiates aggregation. Kinetic analysis of reactions of unactivated alkenes indicates that competing on-cycle alkene hydrocupration and LCuH dimerization impact performance, as catalyst deactivation and turnover occur on comparable timescales. Structure–activity analysis using atomistic simulations shows that the steric profile of DTBM-SEGPHOS increases the CuH dimerization barrier by ∼7.7 kcal mol−1 compared to that of SEGPHOS, rationalizing the unique ability of DTBM-SEGPHOS to stabilize a reactive monomer for hydrocupration of broader alkene substrates. These findings illustrate the fundamental design principle that steric control of aggregation governs CuH catalyst performance, explaining both the exceptional activity of (DTBM-SEGPHOS)CuH and the limitations imposed by competing deactivation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Carbonation reaction of recycled concrete aggregates (RCA): CO 2 mass consumption under various treatment conditions

Concrete is a key building material around the world due to its excellent strength and durability. Recycling demolished concrete for new construction materials may play a significant role in sustainable development. Producing recycled concrete aggregates (RCA) from waste concrete is one approach for such an initiative. However, using RCA may pose challenges, such as reduced density, lower elastic modulus and strength, and increased water absorption. Recently, the carbonation of RCA has emerged as a method to address those concerns. This study explores the carbon sequestration capacity of RCA through carbonation, examining various parametric conditions, including initial CO 2 pressure, relative humidity, temperature, and pre-treatment approach. Both lab-scale and large-scale carbonation tests were conducted. Additionally, a cost analysis and CO 2 footprint assessment were performed. The findings showed that applying higher initial CO 2 pressures (e.g., 40–60 psi) and optimal relative humidity (~55 %) could significantly enhance the carbonation efficiency of RCA. Elevating temperature also led to accelerated CO 2 consumption, being more effective on the lab scale. The economic analysis presented potential cost benefits when substituting natural aggregates with CO 2 -treated RCA. All in all, these results suggest that the carbonation of RCA may provide significant environmental benefits through carbon sequestration, promoting sustainable construction practices.

36 MATERIALS SCIENCE

A coarse-grained model of clay colloidal aggregation and consolidation with explicit representation of the electrical double layer

The aggregation of clay minerals in liquid water exemplifies colloidal self-assembly in nature. These negatively charged aluminosilicate platelets interact through multiple mechanisms with different sensitivities to particle shape, surface charge, aqueous chemistry, and interparticle distance and exhibit complex aggregation structures. Experiments have difficulty resolving the associated colloidal assemblages at the scale of individual particles. Conversely, all-atom molecular dynamics (MD) simulations provide detailed insight on clay colloidal interaction mechanisms, but they are limited to systems containing a few particles. We develop a new coarse-grained (CG) model capable of representing assemblages of hundreds of clay particles with accuracy approaching that of MD simulations, at a fraction of the computational cost. Our CG model is parameterized based on MD simulations of a pair of smectite clay particles in liquid water. A distinctive feature of our model is that it explicitly represents the electrical double layer (EDL), i.e., the cloud of charge-compensating cations that surrounds the clay particles. Our model captures the simultaneous importance of long-range colloidal interactions (i.e., interactions consistent with simplified analytical models, already included in extant clay CG models) and short-range interactions such as ion correlation and surface and ion hydration effects. The resulting simulations correctly predict, at low solid-water ratios, the existence of ordered arrangements of parallel particles separated by water films with a thickness up to ~10 nm and, at high solid-water ratios, the coexistence of crystalline and osmotic swelling states, in agreement with experimental observations.

54 ENVIRONMENTAL SCIENCES

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

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