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At least 91 records · Page 5

Impacts of stochastic coalescence variability on warm rain initiation using Lagrangian microphysics in box and large-eddy simulations

Various coalescence methods for Lagrangian microphysics schemes are tested in box and large-eddy simulation (LES) models, including the stochastic all-or-nothing super-droplet method (SDM) and a version of SDM (dSDM) that applies a fractional approach similar to the average impact method. In LES, variabilities driven by microphysics and by flow realizations are separated using the “piggybacking” technique. Rain initiation averaged over many realizations of the box model is delayed and rain variability increases as the number of super-drops per collision volume ( N SD ) is decreased using SDM. In contrast, rain initiation time using SDM in LES is insensitive to N SD for 32 ≤ N SD ≤ 512. This is explained through the interaction between LES grid boxes, each acting as a separate collision volume. Variability across the ensemble of LES collision volumes using SDM results in rain quickly initiating in some of the LES grid cells at low N SD and leading to a similar overall timing of rain initiation from the cloud compared to simulations with high N SD . There is a ~20% decrease in the total rain mass and mean rain flux as N SD is increased from 32 to 256, with little additional change as N SD is increased from 256 to 512. The fractional coalescence approach in dSDM leads to reduced microphysical variability and a 15-18 min delay in rain initiation compared to SDM. Finally, an additional LES ensemble with microphysical variability feeding back to the dynamics shows that flow variability dominates the impact of microphysical variability on rain properties. Thus, flow variability must be constrained to isolate impacts of microphysical variability.

54 ENVIRONMENTAL SCIENCES↗

Safety-Related Instrumentation and Control Pilot Upgrade (Initial Scoping Phase Implementation Report)

This research report (1) describes the process followed and products developed during the SR I&C Pilot Project Initial Scoping Phase, and (2) captures lessons learned. Exelon Generation and LWRS collaborated to develop a Digital Transformation Strategy as part of a larger Advanced Concept of Operations. The proposed SR I&C Pilot Upgrade provides a foundation stone for this Digital Transformation that will improve plant safety, reliability, and operational performance while lowering plant Total Cost of Ownership (TCO). Initial Scoping Phase activities for this Pilot Project have been performed in accordance with industry processes that have been adapted to better support digital upgrades. These processes include IP-ENG-001, Standard Design Process (SDP), NISP-EN-04, Standard Digital Engineering Process (SDEP), and Electric Power Research Institute (EPRI) Report 3002011816, Digital Engineering Guide (DEG). Completing Initial Scoping Phase Engineering and Operations, Licensing, and Project Management Activities was necessary to sufficiently bound the scope, schedule, and estimated cost of the Project to enable utility management to authorize moving into the Conceptual Design Phase. A significant finding of the Business Case Analysis (BCA) methodology developed and applied as part of this effort was that the growth rate of material costs for sustaining the operation of obsolete SR I&C equipment is accelerating. This directly contributed to the Project Economic Analysis created to justify continuing the Project. Project Initial Scoping Phase lessons learned have also been captured to assist the larger industry in understanding the Digital Transformation Strategy and SR I&C Pilot Project Initial Scoping Phase efforts. This is in keeping with the public/private partnership that has been established between the Department of Energy (DOE) and Exelon for this effort with engagement from the NRC. By addressing first-of-a-kind (FOAK) risks and capturing lessons learned, the SR I&C Pilot Upgrade Project addresses technical, regulatory, and business risks to enable subsequent implementers of similar upgrade.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

ICE Calculator 2.0: Final Report for Phase 1 of the National Initiative to Update the Interruption Cost Estimate (ICE) Calculator

In 2021, Berkeley Lab and Resource Innovations, Inc. launched the “ICE 2.0 Initiative” – a national study to refresh the underlying data and enhance the functionality of the ICE Calculator. The Initiative involves Berkeley Lab contracting with sponsoring utilities to administer identical, updated and comprehensive interruption cost surveys to statistically representative samples of each utility’s customers. Berkeley Lab and Resource Innovations then pool the survey results across the utilities and use them to update the analytical engines that drive the ICE Calculator. The ICE 2.0 Initiative is being conducted in phases. Each phase involves the administration of interruption cost surveys to the customers of sponsoring utilities, followed by an update to the ICE Calculator based on analysis of the pooled survey results. This report describes the activities and findings from Phase 1 of the ICE 2.0 Initiative. Phase 1 was sponsored by eight utilities: American Electric Power, Commonwealth Edison, Dominion Energy, Duke Energy, DTE Electric, Exelon, National Grid, and Puget Sound Energy. Phase 1 involved 11 customer interruption cost survey activities representing a total of 24 electricity distribution service territories, 23 of them located in the Eastern and Midwestern regions of the U.S. and one located in the Pacific Northwest. ICE 2.0 vs. 1.0 Comparison This memorandum compares customer power interruption costs estimated using the recently updated Interruption Cost Estimate (ICE) Calculator (“ICE 2.0”) to the original ICE Calculator (“ICE 1.0”). ICE 1.0 was developed in 2009 based on 15 independent power interruption cost surveys conducted by 10 electric utilities between 1989 and 2012. ICE 2.0 was developed in 2025 through a national initiative based on a consistent set of power interruption cost surveys and 11 surveying efforts conducted across 24 electric utility service territories between 2022 and 2024.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Initial Uncertainty Analysis of Carbon Tetrachloride Contamination and Remediation in the Ringold A and Lower Mud Units at the Central Plateau

The long-term effectiveness of groundwater cleanup at the Hanford Site Central Plateau depends on predictive models that can capture key uncertainties in contaminant fate and transport. Carbon tetrachloride (CCl 4 ), a persistent and toxic compound, presents particular challenges due to variability in degradation rates, uncertainty in initial plume distribution, and subsurface heterogeneity. These uncertainties directly influence plume persistence, migration pathways, and remedy performance, and thus must be systematically evaluated to support long-term remediation planning. To address these gaps, a large-scale Monte Carlo analysis was conducted using the Plateau to River (P2R) model framework. The modeling approach parameterized three primary uncertainty factors: (1) degradation rate, (2) initial plume distribution, and (3) hydraulic conductivity. Degradation was represented as a first-order process, with half-lives ranging from 70 to 700 years. Initial plume distributions were created using a geostatistical simulation method (sgsim), which generates many equally plausible versions of how contaminants might be distributed underground. From this, 100 different scenarios were mapped onto the P2R grid. Variability in hydraulic conductivity was represented in a similar way, with 100 scenarios each for the Ringold Lower Mud and Ringold A units (layers 6 and 7), based on fitted exponential variograms and conditioned to well data. In total, more than 1000 realizations were simulated to assess plume behavior under uncertainty. Results demonstrate that degradation kinetics exert the strongest control over plume persistence: Shorter half-lives produced rapid mass reduction, while longer half-lives yielded persistent plumes with limited attenuation. A nonlinear response was observed, with steep mass reductions at half-lives greater than 200 years and near-linear declines beyond this threshold, reflecting interactions between degradation and pumping. The initial plume distribution strongly influenced early transport patterns, with broader sources generating larger plume footprints, although pump-and-treat operations constrained plume migration to managed areas. By comparison, hydraulic conductivity variability in the Ringold units had only a secondary influence, modifying spreading behavior without altering the dominant migration pathways governed by source configuration and hydraulic controls. Overall, the analysis highlights that uncertainty in degradation rate and initial plume configuration are the primary drivers of variability in plume predictions, while conductivity heterogeneity plays a limited role. These findings underscore the need for improved site-specific data on degradation processes and source characterization to enhance the reliability of long-term performance assessments and to better inform remedial decision-making at the Central Plateau.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

ICE Calculator 2: Final Report for Phase 1 and 2 of the National Initiative to Update the Interruption Cost Estimate (ICE) Calculator

ICE 2.0 Phase 2 Final Report In 2021, Berkeley Lab and Resource Innovations, Inc. launched the “ICE Calculator 2 Initiative” – a national study to refresh the underlying data and enhance the functionality of the ICE Calculator. The Initiative involves Berkeley Lab contracting with sponsoring utilities to administer identical, updated and comprehensive interruption cost surveys to statistically representative samples of each utility’s customers. Berkeley Lab and Resource Innovations then pool the survey results across the utilities and use them to update the analytical engines that drive the ICE Calculator. The ICE Calculator 2 Initiative is being conducted in phases. Each phase involves the administration of interruption cost surveys to the customers of sponsoring utilities, followed by an update to the ICE Calculator based on analysis of the pooled survey results. This report describes the activities and findings from Phase 1 and 2 of the ICE Calculator 2 Initiative. Phase 1 was sponsored by eight utilities: American Electric Power, Commonwealth Edison, Dominion Energy, Duke Energy, DTE Electric, Exelon, National Grid, and Puget Sound Energy. Phase 2 was sponsored by six utilities: Empire District Electric Company, Evergy Missouri, Pacific Gas & Electric, San Diego Gas & Electric, Southern California Edison, and Union Electric. Phase 1 and 2 involved 15 customer interruption cost survey activities representing a total of 30 electricity distribution service territories. ICE Calculator Version 2.0 and 2.2 Comparison This memorandum describes–at a high-level–the improvements in interruption cost estimates for the version 2.2 of the ICE Calculator (released February 2026) compared to version 2.0 (released in April 2025). Version 2.2 of the ICE Calculator corresponds to Phase 2 of the initiative, while version 2.0 corresponds to Phase 1. The improvements in version 2.2 result from both a significant increase in the number of customer responses that have been collected and the identification of seven additional factors that help estimate customer interruption costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Initial–Final Mass Relation for Hydrogen-deficient White Dwarfs

The initial–final mass relation represents the total mass lost by a star during the entirety of its evolution from the zero age main sequence to the white-dwarf cooling track. The semiempirical initial–final mass relation (IFMR) is largely based on observations of DA white dwarfs, the most common spectral type of white dwarf and the simplest atmosphere to model. We present a first derivation of the semiempirical IFMR for hydrogen-deficient (non-DA) white dwarfs in open star clusters. We identify a possible discrepancy between the DA and non-DA IFMRs, with non-DA white dwarfs ≈0.07 M {sub ⊙} less massive at a given initial mass. Such a discrepancy is unexpected based on theoretical models of non-DA formation and observations of field white dwarf mass distributions. If real, the discrepancy is likely due to enhanced mass loss during the final thermal pulse and renewed post-AGB evolution of the star. However, we are dubious that the mass discrepancy is physical and instead is due to the small sample size, to systematic issues in model atmospheres of non-DAs, and to the uncertain evolutionary history of Procyon B (spectral type DQZ). A significantly larger sample size is needed to test these assertions. In addition, we also present Monte Carlo models of the correlated errors for DA and non-DA white dwarfs in the initial–final mass plane. We find the uncertainties in initial–final mass determinations for individual white dwarfs can be significantly asymmetric, but the recovered functional form of the IFMR is grossly unaffected by the correlated errors.

79 ASTRONOMY AND ASTROPHYSICS↗

A Framework for Characterizing the Initial Thermal Conditions of Light-Duty Vehicles in Response to Representative Utilization Patterns, Ambient Conditions, and Vehicle Technologies

It is widely understood that the thermal state of a light-duty vehicle at the beginning of a trip influences the vehicle performance throughout the drive cycle. Cold starts, or initial states with component temperatures near ambient conditions, are strongly correlated with reduced vehicle performance and energy efficiency and with increased emissions. Despite this understanding, there is little literature available that characterizes initial thermal states beyond empirical studies and simplified analyses of dwell times. We introduce a framework that considers vehicle activity patterns, including the previous drive event, duration of the previous dwell event, and relevant ambient conditions occurring during these events. Moreover, the framework allows for technologies to influence the prominence of cold starts and warm starts. An example application of the methodology using a powertrain model approach revealed the significance of all constituent factors: controlling for ambient conditions, the shortest dwell lengths corresponded to an average initial oil temperature of 70°C versus 23°C for the long dwell length simulations, and aggressive conditioning cycles corresponded to an average initial oil temperature of 51°C versus only 35°C for a short conditioning cycle. The coldest ambient conditions evaluated (-30°C to -10°C) produced a weighted initial oil temperature of 19°C versus 57°C for the warmest ambient conditions evaluated (30°C to 50°C). Finally, we introduce weighting factors that account for the real-world frequency of conditioning cycle and dwell length combinations. The procedure outlined may be useful for discovering real-world performance improvements associated with vehicle technologies, a topic of interest to both vehicle manufacturers and regulators.

33 ADVANCED PROPULSION SYSTEMS↗

Safety-Related Instrumentation & Control Pilot Upgrade Initiation Phase Implementation Report

This research report (1) describes the process followed and products developed during the SR I&C Pilot Project Initial Scoping Phase, and (2) captures lessons learned. Exelon Generation and LWRS collaborated to develop a Digital Transformation Strategy as part of a larger Advanced Concept of Operations. The proposed SR I&C Pilot Upgrade provides a foundation stone for this Digital Transformation that will improve plant safety, reliability, and operational performance while lowering plant Total Cost of Ownership (TCO). Initial Scoping Phase activities for this Pilot Project have been performed in accordance with industry processes that have been adapted to better support digital upgrades. These processes include IP-ENG-001, Standard Design Process (SDP) [Reference 2], NISP-EN-04, Standard Digital Engineering Process (SDEP) [Reference 3], and Electric Power Research Institute (EPRI) Report 3002011816, Digital Engineering Guide (DEG). Completing Initial Scoping Phase Engineering and Operations, Licensing, and Project Management Activities was necessary to sufficiently bound the scope, schedule, and estimated cost of the Project to enable utility management to authorize moving into the Conceptual Design Phase. A significant finding of the Business Case Analysis (BCA) methodology developed and applied as part of this effort was that the growth rate of material costs for sustaining the operation of obsolete SR I&C equipment is accelerating. This directly contributed to the Project Economic Analysis created to justify continuing the Project. Project Initial Scoping Phase lessons learned have also been captured to assist the larger industry in understanding the Digital Transformation Strategy and SR I&C Pilot Project Initial Scoping Phase efforts. This is in keeping with the public/private partnership that has been established between the Department of Energy (DOE) and Exelon for this effort with engagement from the NRC. By addressing first-of-a-kind (FOAK) risks and capturing lessons learned, the SR I&C Pilot Upgrade Project addresses technical, regulatory, and business risks to enable subsequent implementers of similar upgrades.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Role of Material Condition in Precursor Corrosion Damage and Stress Corrosion Crack Initiation Behavior of Alloy 600 in PWR Primary Water

Stress corrosion crack (SCC) initiation testing has been performed on a 15% cold-worked UNS N06600 (Alloy 600) heat in the mill-annealed (MA), solution annealed (SA), and thermally treated (TT) conditions to assess the role of grain boundary (GB) carbides on stress-assisted intergranular attack (IGA) and short crack nucleation and growth. The SCC initiation tests were conducted at constant load equivalent to materials yield stress in 360oC simulated PWR primary water with dissolved hydrogen at the Ni/NiO stability line. Results revealed the highest SCC initiation susceptibility in the Alloy 600 MA material followed by the TT and SA materials, suggesting the GB carbide distribution did not have a controlling effect on SCC initiation resistance. Quantitative assessments were conducted on IGA and short cracks to help understand this phenomenon and the role of GB carbides on precursor damage development that lead to differences in macroscopic SCC initiation behavior are discussed.

Zhai, Ziqing↗

Remediation of Temporary Storage Sites in Support of the Port Hope Area Initiative - 20295

The Port Hope Area Initiative is a community-based solution for the long-term management of historic low level radioactive waste (LLRW) resulting from 60 years of uranium and radium processing operations in the Town of Port Hope which is located in Ontario, Canada. The Eldorado refinery, on the north shore of Lake Ontario, began refining radium-226 from pitchblende ore, later transitioning to the refining of uranium. Through the history of the operation, LLRW was deposited throughout the town of Port Hope as a result of fugitive emissions from the plant and/or through the re-use of process residues as building material and backfill. Historical clean-up activities conducted in the late 1970's involved the remediation of approximately 400 properties and the relocation of 100,000 cubic metres of contaminated soil to a disposal facility in Chalk River operated by Atomic Energy of Canada Limited (AECL). Owing to space limitations at that disposal facility, any LLRW identified through construction monitoring since that time has been stored in the community at three temporary storage sites located throughout the town. These include: the Centre Pier mound that contained approximately of 19,800 m{sup 3} of LLRW-impacted soil that originated from the construction of a new water treatment plant; two mounds located at a licensed storage facility containing LLRW obtained from residential clean-up activities (11,000 m{sup 3}); and a small pad adjacent to the municipal sewage treatment plant containing 2200 m{sup 3} of LLRW-containing sludge. With the construction of a new long-term waste management facility (LTWMF) that has been designed to house all of the LLRW identified within Port Hope, the three sites were early candidates for remediation. The clean-up of the three temporary storage sites was a significant milestone for the Port Hope Area Initiative. After a decade of planning and consultation, this work represents the first sites in the municipality to be remediated with the waste being safety removed and transferred to the newly constructed LTWMF. This paper discusses the challenges associated with the clean-up activities for these three sites and the strategies employed to address those challenges. These included weather-related challenges, owing to the seasons over which the work was conducted as well as those associated with working within a closely-knit community. Canadian Nuclear Laboratories (CNL), working on behalf of the federal government, has worked diligently to develop a positive and trusting relationship with the community. Consequently, the successful execution of this project needed to be sensitive to, and respectful of the needs of the community. In addition to the usual Health, Safety and Environment training, project staff received community awareness training that spoke to the history of this community-based initiative and the expected behavior when working within the community. Transportation routes were defined based on safety and the need to minimize disruption to local traffic while haul-times where scheduled around school bus hours to enhance public safety. The successful completion of this first of many remediation projects to be completed under the Port Hope Area Initiative reflected years of careful planning. Nevertheless, there were a number of 'lessons learned' that have been applied on other ongoing projects be completed under the Port Hope Area Initiative. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Effect of thermal conditioning on the initiation threshold of secondary high‐explosives

While most performance metrics of high–explosive (HE) based devices like detonation velocity, detonation pressure, and energy output are expected to degrade over time, the evolution of initiation threshold appears less clear, with claims of both increasing and decreasing trends in threshold having been made in the literature. This work analyzes D–optimally designed sequential binary test data for a few thermally conditioned porous–powder and polymer–bonded HE initiator systems using a Bayesian likelihood method employing the probit regression model. Here we find that in most cases the initiation threshold decreases (i.e., sensitivity increases) upon accelerated thermal conditioning. However, such results are nuanced and influenced by factors like the contact area of initiating stimulus, HE characteristics like density and specific surface area, as well as possible thermally induced changes to other materials and interfaces involved.

36 MATERIALS SCIENCE↗

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

The optimization of functional materials is important to enhance their properties, but their complex geometries pose great challenges to optimization. Data-driven algorithms efficiently navigate such complex design spaces by learning relationships between material structures and performance metrics to discover high-performance functional materials. Surrogate-based active learning, continually improving its surrogate model by iteratively including high-quality data points, has emerged as a cost-effective data-driven approach. Furthermore, it can be coupled with quantum computing to enhance optimization processes, especially when paired with a special form of surrogate model (i.e., quadratic unconstrained binary optimization), formulated by factorization machine (FM). However, current practices often overlook the variability in design space sizes when determining the initial data size for optimization. In this work, we investigate the optimal initial data sizes required for efficient convergence across various design space sizes. By employing averaged piecewise linear regression, we identify initiation points where convergence begins, highlighting the crucial role of employing adequate initial data in achieving efficient optimization. These results contribute to the efficient optimization of functional materials by ensuring faster convergence and reducing computational costs in FM-based active learning.

active learning↗

Revisiting the initial irreversible capacity loss of LiNi 0.6 Co 0.2 Mn 0.2 O 2 cathode material batteries

Layered LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) attracts widespread attention primarily due to its potential for high energy density and moderate thermal stability. However, the low initial coulombic efficiency (ICE) of the material limits the maximum utilization of their capacity. The capacity loss in the first cycle occurs under 4.0V and keep almost constant are considered as common characteristics for NCM-based materials. A clear cognition on the initial capacity loss may light the way to improve the practical reversible capacity of NCM622 at 4.0V. Conducting operando X-ray diffraction during galvanostatic charge/discharge cycling at different temperature (25 degrees C, 45 degrees C and 60 degrees C) and different current (0.1C, 0.01C, 1C=120 mA g -1 ) in the voltage range of 2.7-4.0V, we find that only 8% of the measured initial irreversible capacity loss is associated with parasitic reactions that form cathode/electrolyte interface, and that the dominant contributors include the slow Li + diffusion kinetics (similar to 46% contribution) and irreversible O3/H1-3 phase transition (similar to 46% contribution). Finally, this semi-quantitative study provides new insight on initial capacity loss, guiding further targeted modification and fully utilization of NCM622.

25 ENERGY STORAGE↗

Effect of initial γ -irradiation on infrared laser ablation of poly(vinyl alcohol) studied by infrared spectroscopy

We report the effect of initial γ-irradiation of poly(vinyl alcohol) (PVA) on the kinetics of polymer ablation under CO 2 laser irradiation was studied using infra-red spectroscopy. The rate of laser ablation rapidly decreases with increasing time of laser ablation up to 10 s. Initial γ-irradiation of a dose up to 100 kGy reduces the rate of the laser ablation, just like the effect of laser exposure. The number of OH and CH groups decrease in PVA both with laser irradiation and with γ-irradiation. The number of OH groups decreases more under laser irradiation. Unsaturated bonds are formed in γ–irradiated PVA on the surface of the crater formed by laser ablation of the polymer that has undergone radiolysis. Increasing the dose of initial γ-irradiation from 100 to 2300 kGy leads to an increase in the intensity of the IR bands of the unsaturated bonds. The number of IR bands in the spectra of the laser ablation crater of PVA does not change with the dose of initial γ-irradiation. A dose of radiolysis of 3500 kGy significantly changes the IR spectra of both the ablation crater and the coating formed from the ablation products. Many bands characteristic for PVA are no longer present and the intensities of bands corresponding to unsaturated bonds are increased. A computational model for loss of water and ketone formation was developed for PVA and PVA including a diol using G3(MP2). The highest activation energy barrier step in the decomposition reaction was formation of the enol species and water was shown to catalyze all decomposition steps.

36 MATERIALS SCIENCE↗

Trainability of ReLU networks and Data-dependent Initialization

Here, in this paper, we study the trainability of rectified linear unit (ReLU) networks at initialization. A ReLU neuron is said to be dead if it only outputs a constant for any input. Two death states of neurons are introduced–tentative and permanent death. A network is then said to be trainable if the number of permanently dead neurons is sufficiently small for a learning task. We refer to the probability of a randomly initialized network being trainable as trainability. We show that a network being trainable is a necessary condition for successful training, and the trainability serves as an upper bound of training success rates. In order to quantify the trainability, we study the probability distribution of the number of active neurons at initialization. In many applications, overspecified or overparameterized neural networks are successfully employed and shown to be trained effectively. With the notion of trainability, we show that overparameterization is both a necessary and a sufficient condition for achieving a zero training loss. Furthermore, we propose a data-dependent initialization method in an overparameterized setting. Numerical examples are provided to demonstrate the effectiveness of the method and our theoretical findings.

97 MATHEMATICS AND COMPUTING↗

Calista Energy Management Assistance Initiative

The Calista Energy Management Assistance Initiative (CEMAI) provided technical assistance and capacity building for 56 Tribal communities in the Calista Region of Alaska as an effort to reduce costs, improve operational efficiency, enhance human capacity, and job opportunities. CEMAI catalyzed and guided numerous efforts into a consolidated and effective initiative that brought rural energy best practices, economies of scale, operational efficiencies, human capacity, and economic development to the forefront. Calista Corporation (Calista) is one of thirteen Alaska Native Regional Corporations created under the Alaska Native Claims Settlement Act of 1971 (ANCSA) in the settlement of aboriginal land claims. Calista was incorporated in Alaska on June 12, 1972. The Calista Region covers Alaska’s Bethel and Kusilvak (formerly Wade Hampton) Census areas and includes 56 communities. Calista partnered with Nuvista Light and Electric Cooperative (Nuvista) on the Department of Energy, Office of Indian Energy (DOE-OIE), CEMAI project. Nuvista is a non-profit that seeks to reduce energy costs and provide renewable sources of energy to the people of western Alaska. It is founded and led by a non-profit, Tribe, Native Corporations (including Calista), energy organizations, and Alaska Native stakeholders in the Yukon-Kuskokwim Delta (YK-D) Region; covering the same service boundaries and communities served by Calista. This partnership allowed Calista to direct the project work with local energy experts to respond to community needs. In this arrangement, Calista added credibility and regional accountability while Nuvista added energy-specific expertise and skill set in project management. The delivery of the CEMAI Workplan included short-term or on-demand responses to specific technical assistance requests from communities in addition to longer-term strategically directed activities such as workshops, coordinated training, and capacity development efforts across the region. CEMAI’s Workplan aimed to enhance communities’ readiness for establishing renewable energy projects and implementing energy efficiency initiatives. The CEMAI objectives included: (1) Identifying common operational needs and improvement opportunities for entities with an energy interest or responsibility. (2) Providing access to multi-level expertise to address existing challenges. (3) Developing specialized training programs to build local capacity and community readiness. (4) Nurturing the creation of regional support networks. (5) Increasing access to regional, state, and federal energy initiatives, funding, and expertise. (6) Improving technical skills, provide livable wages, and job opportunities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Initiator‐Driven Tailoring of Reactivity and Inhibition in Frontally Polymerized Dicyclopentadiene‐Co‐Dihydrofuran Thermosets

Incorporating 2,3‐dihydrofuran (DHF) into dicyclopentadiene (DCPD) enables frontally polymerizable, deconstructible thermosets via acid hydrolysis. At 5–20 mol% DHF and low initiator concentration (~100 ppm), DHF inhibits front propagation, lowers the glass transition temperature ( T g ) by up to 20°C, and quenches the front, especially at 20% DHF. This paper demonstrates that increasing the initiator concentration to 250–1000 ppm overcomes inhibition, enhances front speeds by ~50%, and suppresses quenching at the expense of pot‐life. Above 5 mol% DHF, an emergence of a second exotherm is observed, attributed to increased rate dependence on the inhibition of the initiator by DHF. Void formation from volatile DHF is suppressed by applying 110 kPa nitrogen, though at the cost of reduced front speed. Dynamic mechanical analysis shows that higher initiator concentration produced more highly cross‐linked polymers, with a ~20% increase in storage modulus at 25°C and a 20°C increase in T g .

deconstructible thermosets↗

Visible-Light-Initiated Free-Radical Polymerization by Homomolecular Triplet-Triplet Annihilation

Polymerization reactions initiated by ultraviolet light are ubiquitous in scores of industrial applications but would markedly benefit from visible-light activation to overcome stability, energy consumption, light penetration, and sample geometry limitations. The current work leverages visible-light-driven homomolecular triplet-triplet annihilation (TTA) in zinc(II) meso-tetraphenylporphyrin (ZnTPP) to initiate facile free-radical polymerization in trimethylolpropane triacrylate (TMPTA) and methyl acrylate (MA) monomers through ultrafast electron transfer quenching. Selective Q-band (S 1 ) excitation of ZnTPP in the green or yellow sensitizes TTA occurring between two 3 ZnTPP* energized chromophores, ultimately generating the highly reducing S 2 excited state on one ZnTPP molecule (E red = –2.13 V versus saturated calomel electrode, SCE). Subsequently, this S 2 state engages in electron transfer with TMPTA or MA, thereby initiating the radical polymerization process. Bimolecular electron transfer was confirmed through optically gated fluorescence upconversion. In conclusion, FT-IR and EPR spin-trapping experiments verified visible-light-initiated polymerization leading to the formation of well-defined macro- and microscopic objects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗