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At least 253 records · Page 14

Scalable Implementation of Mean-Field and Correlation Methods Based on Lie-Algebraic Similarity Transformation of Spin Hamiltonians in the Jordan–Wigner Representation

Recent work has highlighted that the strong correlation inherent in spin Hamiltonians can be effectively reduced by mapping spins to Fermions via the Jordan−Wigner transformation (JW). The Hartree−Fock method is straightforward in the Fermionic domain and may provide a reasonable approximation to the ground state. Correlation with respect to the Fermionic mean field can be recovered based on Lie-algebraic similarity transformation (LAST) with two-body correlators. Specifically, a unitary LAST variant eliminates the dependence on site ordering, while a nonunitary LAST yields size-extensive correlation energies. Whereas the first recent demonstration of such methods was restricted to small spin systems, we present efficient implementations using analytical gradients for the optimization with respect to the mean-field reference and the LAST parameters, thereby enabling the treatment of larger clusters, including systems with local spins s > $\frac{1}{2}$.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Grid-connected heat pump water heater benefits for low-income households in the Southeastern United States

Energy efficient heat pump water heaters (HPWHs) reduce customer energy costs; grid-connected controls further increase HPWH value by enabling energy storage and shifting demand to cheaper, off-peak periods. However, a HPWH’s first cost premium can put it out of reach for low-income customers. This paper will present results of an ongoing study exploring the benefits of load shifting HPWHs for 24 low-income households, aiming to support increased product deployment in this demographic. The study uses EcoPort modules to shift HPWH load for a study sample consisting primarily of low-income adults and seniors in North Carolina. Building upon prior studies, the study’s HPWH operating schedules are designed to maximize shifted energy and minimize participant electricity costs based on local time-of-use rates. The study documents load profiles of grid-connected HPWHs in a less-studied demographic group and explores how certain groups may have particularly flexible loads due to their unique usage profiles. The results are relevant for HPWH product performance in the Southeast. The study will quantify HPWH load shifting performance during North Carolina’s hot summer, temperate shoulder, and occasionally sub-freezing winter seasons, and the study includes installations in conditioned, semi-conditioned, and unconditioned spaces. Finally, study results will also explore how controlled HPWHs can provide value to the regional grid by reducing seasonal peaks via demand response. Lessons learned include HPWH acceptance for low-income and senior users, best practices for maintaining HPWH connectivity among users without prior product experience, and strategies to leverage remote monitoring to ensure optimal operation and enhance HPWH reliability.

Urigwe, Daniela↗

Understanding and Modeling Pooled Rideshare Acceptance: Influential Factors, Preferred User Experiences, and Implications

Ridesharing allows people to share a vehicle with others traveling in the same direction, which can reduce costs and traffic congestion. Pooled rideshare (PR) services, such as UberX Share and Lyft Shared, offer an economical and environmentally friendly alternative by matching passengers traveling similar routes. However, despite these benefits, PR adoption remains low due to concerns about safety, privacy, and convenience. This research explores the factors influencing PR adoption and provides recommendations to improve user acceptance. A nationwide survey of 5,385 participants across the U.S. was conducted to understand why people choose or avoid PR. The study identified five key factors influencing PR consideration: safety, service experience, privacy, traffic/environment, and time/cost. Additional research examined ways to optimize PR experiences by identifying four critical factors: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. To measure the impact of these factors, a statistical model called the Pooled Rideshare Acceptance Model (PRAM) was developed, providing insights into how each element influences PR adoption. Further analysis using the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMA) revealed how demographic characteristics such as age, gender, income, and past rideshare experience shape PR perceptions. Some key findings from the multigroup analyses showed that younger users valued technological features and environmental benefits, while older users prioritized reliability and service transparency. Additionally, privacy concerns were more significant for female users, while convenience was critical for higher-income groups. These results emphasize that a 'onesize-fits-all' approach to PR service design is not effective, highlighting the need for tailored strategies to address different user segments. Further, workshops were conducted with researchers and students to translate the findings into real-world solutions. These workshops and 3 all the statistical analyses led to the development of 95 actionable recommendations. The recommendations focus on key areas such as safety, service reliability, user education, and accessibility, offering tangible improvements to PR services. The insights from this study provide valuable guidance for policymakers, transportation network companies (TNCs), and researchers aiming to make PR services safer, more accessible, and widely accepted. By addressing user concerns, PR can become a more viable transportation option, supporting sustainable urban mobility and reducing reliance on private vehicles. Additionally, these findings emphasize the importance of user-centric service design in encouraging broader PR adoption. Future research should explore evolving trends in PR preferences, technological advancements, and policy changes to ensure continued improvements. By implementing these recommendations, PR services can better align with user expectations, enhance trust in shared mobility, and contribute to a more efficient transportation ecosystem.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantum Algorithms for Representation-Theoretic Multiplicities

Kostka, Littlewood-Richardson, Plethysm, and Kronecker coefficients are the multiplicities of irreducible representations in the decomposition of representations of the symmetric group that play an important role in representation theory, geometric complexity, and algebraic combinatorics. We give quantum algorithms for computing these coefficients whenever the ratio of dimensions of the representations is polynomial. We show that there is an efficient classical algorithm for computing the Kostka numbers under this restriction and conjecture the existence of an analogous algorithm for the Littlewood-Richardson coefficients. We argue why such classical algorithm does not straightforwardly work for the Plethysm and Kronecker coefficients and conjecture that our quantum algorithms lead to superpolynomial speedups. The conjecture about Kronecker coefficients was disproved by Panova [Polynomial time classical versus quantum algorithms for representation theoretic multiplicities, arXiv:2502.20253] with a classical algorithm which, if optimal, points to a 𝒪⁡(𝑛 4+2⁢𝑘 ) vs $\tilde{Ω}$⁡(𝑛 4⁢𝑘 2 +1 ) polynomial gap in quantum vs classical computational complexity for an integer parameter 𝑘.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Precision Computations in Strongly Coupled Conformal Field Theories (Final Technical Report)

Conformal Field Theories (CFTs) are quantum field theories that are invariant under the conformal symmetry group (which includes translations and rotations, but also local rescalings of spacetime). They are building blocks of general quantum field theories, and appear in many areas of physics, including statistical physics, condensed matter physics, particle physics, and quantum gravity. Because of their extra symmetries, the mathematical structure of CFTs is tightly constrained, and this leads to the idea of the ``conformal bootstrap," which is to use these mathematical structures to constrain, and in some cases determine, CFT observables. A new numerical implementation of the conformal bootstrap idea appeared in 2008 with the work of Rattazzi, Rychkov, Tonni, and Vichi. Their observation was that certain bootstrap constraints (conformal symmetry and unitarity) could be combined to yield a convex optimization problem that constraints CFT data. By solving this convex optimization problem on a computer, one could obtain bounds on observables like critical exponents and operator product expansion (OPE) coefficients. Over the course of this award, the PI has improved numerical bootstrap techniques by optimizing known algorithms and finding new ones for performing the required convex optimization computations. The PI has applied these techniques to compute high-precision observables in several important strongly-coupled systems. The PI has also explored both analytical and numerical bootstrap methods for constraining the space of low energy effective field theories of quantum gravity, and developed new analytical techniques for CFT and QFT more broadly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Best Practices for Equitable Solar Workforce Development

The Midwest Renewable Energy Association (MREA) was selected to serve as a lead organization for the U.S. Department of Energy Solar Energy Technology Office’s Equitable Solar Communities of Practice initiative. This project, facilitated through a partnership with ENERGYWERX, aimed to develop strategies to support the expansion of equitable benefits in solar adoption across the U.S. Specifically, the MREA was chosen to lead the solar workforce development community of practice, focusing on scaling the U.S. solar workforce, to meet growing industry demands and ensure that these opportunities are accessible and beneficial to all communities. For the purpose of this initiative, we define the solar workforce in line with the National Solar Jobs Census, which defines a solar worker as someone who spends a majority of their time on solar-related work. This also includes workers who spend a plurality of their time on solar tasks. It’s important to note that manufacturing jobs were not included in this research, as the focus is primarily on solar installation, development, and related roles. To achieve the goals of the Equitable Solar Communities of Practice initiative, the MREA leveraged existing resources and engaged a diverse core team and group of stakeholders including industry professionals, educators, policymakers, and community leaders. The MREA began with a literature review and gap analysis to identify existing best practices and gaps in the solar workforce. This was followed by a community convening to gather insights from a wide range of stakeholders. The findings informed the best practices and pathways to scale the benefits of solar workforce development, focusing on training programs, workforce services, apprenticeship, and justice, inclusion, and sustainability. This report outlines the background, methodology, findings, and conclusions drawn from the landscape and gap analysis, providing valuable insights into workforce needs and training program capacities across the U.S. The outcomes of this research are presented in this report and contain recommendations for optimizing workforce development and training funding to support the equitable growth of the solar industry, ensuring that the transition to solar energy is inclusive and beneficial for all communities.

14 SOLAR ENERGY↗

Enhancing HT-WGS catalyst performance with stable monovalent copper species via electron supply from defect-induced MgO

Magnesium oxide (MgO) exhibits excellent synergy with cerium oxide (CeO2), serving as either textural or electronic promoters during catalytic reactions. However, achieving well-dispersed CeO2-MgO is technically challenging because they are known not to form solid solutions, and the crystal growth of CeO2 suppresses the structure formation of MgO, leading to MgO being in an inhomogeneous amorphous state within CeO2-MgO. For this reason, most of research groups have been struggling with synthesizing well-dispersed CeO2-MgO. This leads them to focusing on the interaction between the active metal and cerium, overlooking the true role of magnesium. In this study, we successfully synthesized well-dispersed CeO2-MgO via a spray pyrolysis-assisted evaporation-induced self-assembly method, followed by the impregnation of Cu. The location and dispersion of Cu nanoparticles were highly dependent on the MgO distribution. Additionally, we revealed that this significantly influenced the catalytic activity and stability towards the HTS reaction and furthermore supplies electrons to monovalent Cu species, helping maintain the stable electron structure and oxidation state of Cu species considered as active sites. These findings suggest that optimizing the MgO distribution in CeO2-MgO is a promising strategy for developing efficient catalysts for the HTS reaction, emphasizing the role of MgO in designing high-performance catalysts.

Kim, Min-Jae↗

Status of the International Criticality Safety Benchmark Evaluation Project

The International Criticality Safety Benchmark Evaluation Project (ICSBEP) has continued its work generating evaluations of new and historical benchmark experiments since the last update to the nuclear criticality safety (NCS) community at the 12th International Conference on Nuclear Criticality Conference held in 2023. One additional version of the ICSBEP Handbook has been published since that update, and the Technical Review Group (TRG) held two in-person meetings to review and approve additional benchmarks. The 2022 and 2023 editions of the handbook were combined into one release (published in November 2024) and contained 13 new evaluations with 46 different configurations and two major revisions to existing evaluations. The 2024 version of the handbook, currently under publication review, will contain two new evaluations with 15 new configurations and one major revision to HEU-MET-FAST-028, the evaluation of Flattop with a uranium core. The ICSBEP TRG met again in person in April 2025 to review benchmarks for the 2025 ICSBEP Handbook and final comment resolution is currently ongoing. Many of the new benchmarks represent contemporaneous experiments that have been specifically optimized to provide validation cases relevant to the NCS community. One major area of focus for new critical experiments is to target the sparsely populated intermediate energy (or resonance) region. Another focus of many of the new benchmarks is to provide experiments sensitive to different materials, such as chlorine, hafnium, tantalum, titanium, molybdenum, chromium, and polymethyl methacrylate (PMMA, or Lucite). The ICSBEP continues to deliver high-quality, peer reviewed evaluations of integral experiments relevant to the nuclear data community.

HEU-MET-FAST-028↗

First-principles DFT modeling of nitrobenzene adsorption on the Ag(111) surface at varying monolayer coverages

Here, the adsorption behavior of nitrobenzene on the Ag(111) surface as a function of coverage is investigated using density functional theory. Adsorption energies and optimized geometries are analyzed together with isolated intermolecular interaction calculations and electronic structure analysis, including Bader charge partitioning and projected density of states, to disentangle the roles of adsorbate–surface bonding and through-space adsorbate–adsorbate interactions. At low and intermediate coverages (θ = 1/9 and θ = 2/9), bidentate adsorption at top sites is favored due to strong adsorbate–surface interactions, with additional stabilization at θ = 2/9 arising from favorable intermolecular separations. At higher coverage (θ = 1/3), bidentate adsorption is destabilized by strong intermolecular repulsion, and monodentate adsorption becomes energetically preferred as rotational freedom allows more favorable intermolecular spacing. Charge density differences, Bader charge, and density of states analyses show that charge transfer from the Ag surface is localized primarily on the nitro group and increases with coverage and adsorption denticity, although this increase does not directly correlate with adsorption strength at high coverage due to competing intermolecular interactions. These results demonstrate that surface coverage can induce a transition in preferred adsorption denticity driven by intermolecular interactions, highlighting the importance of adsorbate packing in organic molecule adsorption at metal interfaces.

36 MATERIALS SCIENCE↗

Use of Frit‐Disc Crucible Sets to Make Solution Growth More Quantitative and Versatile

The recent availability of step‐edge, frit‐disc crucible sets (generally sold as Canfield Crucible Sets or CCS) has led to multiple innovations associated with the group's use of solution growth. The use of CCS allows for the clean separation of liquid from solid phases during the growth process. This clean separation enables the reuse of the decanted liquid, either allowing for simple, economic, savings associated with recycling expensive precursor elements or allowing for the fractionation of a growth into multiple, small steps, revealing the progression of multiple solidifications. Clean separation of liquid from solid phases also allows for the determination of the liquidus line (or surface) and the creation, or correction, of composition–temperature phase diagrams. The reuse of clean decanted liquid has also allowed to prepare liquids ideally suited for the growth of large single crystals of specific phases by tuning the composition of the melt to the optimal composition for growth of the desired phase, often with reduced nucleation sites. Finally, it is discussed how solution growth and CCS use can be harnessed to provide a plethora of composition–temperature data points defining liquidus lines or surfaces with differing degrees of precision to either test or anchor artificial intelligence and/or machine‐learning‐based attempts to augment and extend the limited experimentally determined database.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

American cities in a time of global environmental change: the case of the Baltimore Social-Environmental Collaborative

The Baltimore Social-Environmental Collaborative (BSEC) Urban Integrated Field Laboratory seeks a new paradigm for urban climate research. Motivated by deep uncertainties in urban climate and the future of urban systems, BSEC works collaboratively across institutions and stakeholder groups to co-generate the science needed to advance energy security and resilience to extreme events across the city of Baltimore, Maryland, USA, and to do so in a manner that can inform similar efforts in other cities. BSEC begins with stakeholder priorities (health, affordable energy, etc) and designs observation networks and models to deliver climate science to address them. This takes the form of an iterative collaborative cycle, in which an initial research strategy is repeatedly updated in conversation with community partners, and researchers and stakeholders learn from each other. To date, this cycle has included multiple rounds of collaborative deliberation on urban heat mitigation, in which a multicriteria decision tool has been updated with more community-relevant spatial structure and modified optimization metrics. The guiding objective of this cycle is to inform potential ‘secure and resilient pathways’ for energy and infrastructure. In doing so, BSEC addresses fundamental urban science questions in natural and social sciences. It also tests our ability to integrate this science in a manner that advances participatory decision-making for urban resilience.

climate↗

Multilayer Electrodes with Metalized Polymer Current Collector for High-Energy Lithium-Ion Batteries with Extreme-Fast-Charging Capability

The pursuit of batteries capable of extreme fast charging (XFC), that also satisfy high energy and safety criteria, poses a significant challenge to current lithium-ion battery technologies. Additionally, the increasing demand for aluminum (Al) and copper (Cu) in electrification, and vehicle light weighting is driving these metals towards near-critical status in the medium term. This study introduced metalized polymer films by depositing an Al or Cu thin layer onto two sides of a polyethylene terephthalate (PET) film – named mPET/Al and mPET/Cu, as lightweight, cost-effective alternatives to traditional metal current collectors in LIBs. We have utilized current collectors that significantly reduce weight (by 73%), thickness (by 33%), and cost (by 85%) compared to traditional metal foil counterparts. We conducted an extensive evaluation of their mechanical and electrical properties, including in-plane and through-plane resistivities, affirming their suitability for the roll-to-roll battery manufacturing process. Additionally, a novel XFC testing protocol was employed to thoroughly assess the cells' (both half and full-cell) performance across various C-rates and under long-term tests. These advancements have the potential to enhance energy density to 280 Wh/kg at the electrode level under 10-minute charging at 6C. Through testing, including a novel XFC protocol across various C-rates and long-term cycling (up to 1000 cycles) in different cell configurations, we have demonstrated the superior performance of these metalized polymer films. Notably, mPET/Cu and mPET/Al foils exhibited comparable capacities to conventional cells under XFC, with the mPET cells showing a 27% improvement in energy density at 6C and maintaining significant energy density after 1000 cycles. This study underscored the potential of mPET foils to revolutionize the roll-to-roll battery manufacturing process and significantly advance the performance metrics of LIBs in EV applications. Moreover, our results suggest that there is potential to enhance the performance of mPET foils, especially mPET/Al, by optimizing the manufacturing process to achieve higher conductivity.

99 GENERAL AND MISCELLANEOUS↗

Data-driven Community-centered Resilient Assessment and Planning Toolkit for Nexus of Energy and Water (DCRAPT-NEW)

Urban areas, including Detroit and Pittsburgh, have suffered significant dual outages of the electrical and water infrastructure in the past decade due, in part, to the increasing number of extreme weather events. With increasing temperatures and rainfall intensity, these regions need to prepare for increasing extreme events through community-based energy and water resilience analysis, planning, and enhancement. This project developed a suite of open-source, open-access, community-centered, data-driven assessment and distributed energy resource (DER) and planning tools for energy and water resilience enhancement in urban areas. Through establishing a multi-level community awareness and engagement mechanism and a comprehensive collection of power outage and flooding data, an innovative group of community energy and water resilience assessment and planning tools have been developed for a wide range of users with differing and variable sets of data available to them. The developed tools include (1) DOE EAGLE-I data-driven, deep-learning assisted resilience assessment and DER planning tools at the county level with socioeconomic factors incorporated; (2) Utility annual power outage data-driven tools for long term resilience assessment and DER planning and 15-min power outage data-driven tools for short term resilience assessment and planning; (3) Detailed engineering tools for energy and water systems resilience assessment and planning when the system topology and component fragility curves are available; (4) Alternative Resiliency Metric Calculation that extracts and separates outage and restoration processes; and (5) Co-optimization tools that evaluate the resilience of the power and sewage system and allow users to conduct joint planning with energy and wastewater systems. The developed tools provide planners, decision-makers, and stakeholders with powerful capabilities to systematically evaluate system/community resilience and optimal and actionable guidance for enhancing resilience while prioritizing DER investments. The tools have been used and validated in Detroit and Pittsburgh and can be used in other areas of the nation. In addition, this project will (1) advance the knowledge and applications of machine-learning methods in analyzing and fusing different layers of information and generating meaningful data points such as generating rare weather events; (2) significantly improve the energy and water resilience of the identified communities in Detroit and Pittsburgh and prepare for more frequent and severe weather conditions; (3) help communities assess extreme weather event impacts and address short-term and long-term resilience-related issues The developed tools have been made public via GitHub and demonstrated to community stakeholders and utility companies via the two annual workshops and numerous community engagement meetings. The project outcomes are also disseminated through publications in various journals and conference proceedings, and presentations at top conferences.

13 HYDRO ENERGY↗

Community Public Mobility Using On-Demand, Low-Speed Electric Vehicles: A Case Study in Downtown St. Louis, Missouri

Legacy fixed route transit systems designed to serve commuters struggle to provide efficient and effective service for short neighborhood trips and for population groups unable to access and egress transit stops using active modes (e.g., elderly, disabled). Neighborhood on-demand transit (ODT) services using low-speed electric vehicles (LSEV) are an innovative technological solution that can help fill this gap in service (e.g., short, high-frequency trips) for diverse populations and trip types. This study evaluated user characteristics and travel behavior for a neighborhood ODT service (using LSEVs) in downtown St. Louis, Missouri using responses from a community survey (n=244), ridership data, and vehicle trajectory information. A comparative analysis between neighborhood ODT, fixed route transit, and transportation network companies (TNC) was also conducted from the perspectives of total travel time, cost, and greenhouse gas emissions. Ultimately, the goal of the analysis was to motivate and inform holistic public mobility systems where different services are optimized to meet specific community needs. Findings indicate that the neighborhood ODT was effective at reaching diverse populations (elderly (20%), lower income (27%), and households with limited access to private vehicles (34%)). ODT reduced total travel time by 32% compared to fixed route transit, produced 2.4 - 4.3 times less greenhouse gas emissions per passenger mile (compared to transit and TNCs), and was more affordable (free to users) than alternative options ($1 for transit, $10-12 for TNCs). Overall satisfaction rates were high, with 80% of respondents rating the service a 4 or 5 out of 5.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A code-to-code benchmark for magneto-convection in a horizontal duct

Liquid metals and magnetic fields are used in many technical applications such as metallurgy, crystal growth and nuclear fusion reactors. When an electrically conducting fluid moves in a magnetic environment, electric currents and electromagnetic forces are generated that affect velocity and pressure losses in the flow. These magnetohydrodynamic (MHD) interactions have to be investigated to optimize the engineering processes. The characteristics of MHD flows depend on the geometrical configuration, the strength of the applied magnetic field, the electrical properties of fluid and structural materials and the thermal conditions. In the so-called blankets for fusion reactors, where liquid metals are used to breed the plasma fuel component tritium and to extract the generated heat, magneto-convective flows play a crucial role in determining heat and mass transfer. Therefore, the availability of numerical codes to simulate this type of flow is mandatory and their validation is a necessary step to guarantee the reliability of the results. For that reason, a benchmark problem has been defined to simulate liquid metal flows in a horizontal rectangular duct heated from below and exposed to a non-uniform magnetic field. Results obtained by five research groups using different codes are compared.

benchmark↗

Self‐Assembled Monolayer Templating for Engineered Nanopinholes in Passivated Contact Solar Cells

We present a novel self-assembled monolayer (SAM)-based technique to make nanopinhole-enabled passivated contacts on silicon solar cells by tuning the SAM coverage area and etch selectivity. We deposit trimethyl-silyl Si(CH 3 ) 3 groups using hexamethyldisilazane (HMDS) as the precursor over passivating dielectric layers and their stacks (SiO 2 , SiN x , SiO 2 /SiN x ) and interrupt the HMDS attachment chemistry shortly before a full monolayer is formed on its surface. Subsequent etching in dilute HF produces pinholes through the dielectric layers due to the higher etch resistance of the SAM to HF etching. The pinhole areal density (10 4 –10 8 /cm 2 ) and size (10–1000 nm) can be tuned both by duration of HMDS attachment and HF etch time. Pinholes were characterized by atomic force microscopy, tetramethylammonium hydroxide (TMAH) selective etch, and Ag decoration by electroless plating. Polysilicon (poly-Si) passivated contacts enabled by pinholes were formed by subsequent deposition of doped amorphous silicon (a-Si:H) followed by thermal crystallization and dopant drive-in. At optimal areal pinhole density ≈10 7 /cm 2 , contacts exhibit both passivation and carrier transport via pinholes as evidenced by electron beam induced current, transmission line measurements, and carrier lifetime measurements. Solar cells based with these pinhole contacts show V oc = 723 mV and FF = 80.3%. The remaining SAM layer does not affect device performance.

14 SOLAR ENERGY↗

Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu\beta\beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76 Ge to achieve a half-life sensitivity of 10 27 (10 28 ) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of $0.024 ^{+0.004}_{-0.003} \%$ after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.

artificial intelligence↗

Collaborative Design of Robust Adaptation Pathways for Urban Flooding Resilience in Baltimore

Urban pluvial flooding poses a growing threat to the city of Baltimore, driven by changes in climate and rainfall, increased impervious area, aging infrastructure, and severe social inequity. Adaptations to urban flooding should strengthen community-scale resilience while navigating the uncertainties associated with future actions. However, the highly uncertain future climate and conflicting stakeholder objectives complicate the selection of effective and socially acceptable strategies. This study addresses these challenges through a community-informed Multi Objective Robust Decision Making (MORDM) process, coupled with Dynamic Adaptation Policy Pathways (DAPP). Community stakeholders are engaged on a large scale through community partnerships, including priority identification sessions, focus groups, and metric identification workshops. The combination of community partnership, MORDM, and DAPP will create an original set of adaptation pathways which are aligned with community goals and values, and furthermore are adjustable under changing future constraints and conditions. This framework will enhance the city's capacity to respond to evolving pluvial flood conditions while accounting for diverse stakeholder interests and will provide guidance for addressing both the immediate and long-term challenges of urban flooding in Baltimore.

BSEC↗