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At least 1,171 records · Page 65

A Framework to Demonstrate a DNP3 Interface With a CIM-Based Data Integration Platform: Preprint

The contemporary electrical grid is characterized by its complexity and abundance of data. A control-rich environment supported by information and communication technologies within an Advanced Distribution Management System (ADMS) presents a viable and cost-effective option for utility companies aiming to implement advanced real-time analytical schemes for monitoring and remotely controlling distribution feeders. Modular platform-based approaches to distribution operations require a structured framework for acquiring field device measurements, performing analytics, converting the setpoint to the correct protocol, and sending it on the appropriate communications network to the field devices. We present the development and deployment of an application service to integrate an open-source standardsbased platform with an ADMS test bed with field devices using the Distributed Network Protocol (DNP3) for data exchange. The step-by-step procedure for establishing the DNP3-Master service on an open-source distribution platform is outlined, comprehensively explaining the Master setup process. Moreover, sample use case results highlight the capabilities of the DNP3- Master service setup. Results demonstrate the scalability and configurability of the DNP3-Master service, making it adaptable for integration with other relevant applications, thus providing potential opportunities for real-world field trials and real-time assessments.

ADMS↗

Investigating the interconnectedness of active transportation and public transit usage as a primer for Mobility-as-a-Service adoption and deployment

With the advent of Mobility-as-a-Service packages to reduce car usage and (by extension) greenhouse gas emissions, it is crucial that researchers and practitioners consider mutual determinants and outcomes that link the adoption of multiple alternative modes. This study therefore investigates the joint usage of active travel (walking, cycling, bike-sharing) and public transit (bus, rail) modes with respect to personal and situational contexts. Online survey data (n = 826) were collected across six Midwestern U.S. states using Amazon MTurk. Respondents indicated their average weekly usage of eight travel modes across three trip purposes so that multimodality could be assessed. Several psychological constructs were extracted via (a) the stages of change framework, used to indicate willingness to adopt new behavior, and (b) confirmatory factor analysis conducted on Likert scales rooted in theories of community, identity, norms, personality, and well-being. A multiple-indicators multiple-causes structural equation model is then employed to investigate the process of adopting a modality style that incorporates active and transit modes. The model confirms that compatible physical and social contexts, as well as navigational skills and openness to learning, are key primers of multimodalism. However, a path juncture stemming from neighborhood support for mobility innovation illustrates a potential polarity in outcomes between individuals and communities. In addition, the stage of active mobility adoption is linked to identity and norm activation, offering further guidance on what influences readiness for change. The seamless integration of mobility services is critical to matching the convenience and comfort of the private vehicle; understanding potential pathways to sustainable mobility, though, requires analyses and interventions that are driven by well-being outcomes and grounded in rigorous psychological frameworks. Here, the research findings offer practical guidance for identifying intervention opportunities to be linked with MaaS enrollment while demonstrating the need to illuminate how mobility might relate to social cohesion, identity expression, and various sources of satisfaction.

42 ENGINEERING↗

LOCOMOTIVES - Comprehensive Impact and Cost Assessment Framework of Carbon Lowering Approaches for the US Rail Freight System

The goal of this project is to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first quarter, the project focused on collecting data, establishing a simulation workflow, and engaging industry through the creation of the Industry Advisory Board (IAB). In the second quarter, the project focused on selecting fuel pathways and powertrain technologies, setting performance targets, conducting a techno-economic analyses, and developing the simulation framework that would serve as the backbone of the future toolhead. The third quarter involved developing an industry-oriented interactive dashboard powered by a five-step sequential framework, as well as holding industry advisory board meetings as per the initial technology-to-market plan. In the remaining project quarters, the NUFRIEND dashboard were fine-tuned with the help of IAB member feedback and in-depth scenario analyses were conducted to support the techno-economic analysis of energy sources. Additionally, dashboard documentation, project insights, and open-source code on GitHub were prepared and released. Throughout the project, the team completed testing and analysis of all model components, integrated all initial test scenarios, and conducted stakeholder engagement. Lower-carbon drop-in fuels can be deployed as admixtures and are considered uniform across the network at a desired penetration rate, while hydrogen and battery-electric technology deployment poses a more complex problem as they require significant investments to be made in the siting of refueling/charging facilities and the replacement of locomotive fleets. Thus, strategies for locating and sizing refueling/charging facilities on a railroad’s network to meet their energy demands were developed to inform deployment decisions. To address this challenge, the Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework presents a five-step sequential framework to select O-D paths, locate facilities, reroute flows, size facilities, and evaluate the deployment for alternative energy sources that require locomotive powertrains to be converted and new refueling infrastructure to be deployed. The NUFRIEND Framework is an industry-oriented tool for simulating the deployment of new energy technologies across the US freight rail network. The framework provides a comprehensive network-level optimization and scenario simulation tool for decarbonizing the freight rail sector, addressing the uncertainties surrounding technological developments by supporting sensitivity analyses for different operational and technological parameters through a transparent and flexible input module. It offers practical alternatives to diesel locomotives and can be applied for any railroad considering the specific network structure and freight demand, outputting evaluation metrics for the associated emissions and costs relative to diesel operations. A number of relevant simulation scenarios were run and analyzed for key insights on the value of different alternative technologies for freight rail decarbonization. The project developments and findings have been presented at numerous conferences and events.

08 HYDROGEN↗

The Psyche Planning Software Subsystem: Creating a Robust Toolset for a Discovery-class Mission

Psyche is a Discovery-class mission to the small metal-rich asteroid (16) Psyche, and is slated to launch in 2022. Psyche, like many missions, requires low-cost activity planning and sequence generation that serves as the backbone to overall uplink design. Such tools must be maintainable over long periods of operations, and powerful enough to solve complex issues that deep-space one-off missions encounter. In this paper we introduce cost-effective solutions that leverage inner- and open-source principles to meet a variety of common and novel use cases.The uplink process that was designed to meet these challenges is presented, as well as the data-flow through the high-level architecture of the planning software subsystem. The user-facing planning tools are described, particularly the Science Opportunity Analyzer, the Plan Editor, Psyche’s planning automation in the Blackbird framework, and Psyche Simulation Reports. All these applications are either new or have been substantially revamped to meet Psyche’s concept of operations. In particular, ensuring the entire toolchain can correctly process epoch-relative activities is discussed. Underlying the main applications are a common set of dependencies developed and maintained by a new cross-mission association of planning developers. In this way, Psyche can inherit well-tested functionality which saves effort and ensures its developers can focus on solving domain challenges. Quality control of the applications and libraries is ensured with a code-review and unit-test based novel ‘CM lite’ process. Collaboration with international industry and academia using the open-source modules is already occurring.The planning and scheduling software is designed to maximize operator awareness of the integrated plan at every step of the process and use common interfaces and file formats to easily transfer information. Design choices plus the team’s test-driven development process enables more expansive capabilities compared to the decentralized planning and sequence generation functions typical of Discovery-class orbiters without significant development cost increases. Benefits and drawbacks of Psyche’s approach are discussed, including comparison to other missions and tools where appropriate.

Ramanathan, Keshav↗

A Framework for Successful Research Experiences in the Classroom: Combining the Power of Technology and Mentors

Authentic research opportunities in the classroom are most impactful when they are student-driven and inquiry-based. These experiences are even more powerful when they involve technology and meaningful connections with scientists. In today's classrooms, activities are driven by state required skills, education standards, and state mandated testing. Therefore, programs that incorporate authentic research must address the needs of teachers. NASA's Expedition Earth and Beyond (EEAB) Program has developed a framework that addresses teacher needs and incorporates the use of technology and access to mentors to promote and enhance authentic research in the classroom. EEAB is a student involvement program that facilitates student investigations of Earth or planetary comparisons using NASA data. To promote student-led research, EEAB provides standards-aligned, inquiry-based curricular resources, an implementation structure to facilitate research, educator professional development, and ongoing support. This framework also provides teachers with the option to incorporate the use of technology and connect students with a mentor, both of which can enrich student research experiences. The framework is structured by a modeled 9-step process of science which helps students organize their research. With more schools gaining increased access to technology, EEAB has created an option to help schools take advantage of students' interest and comfort with technology by leveraging the use of available technologies to enhance student research. The use of technology not only allows students to collaborate and share their research, it also provides a mechanism for them to work with a mentor. This framework was tested during the 2010/2011 school year. Team workspaces hosted on Wikispaces for Educators allow students to initiate their research and refine their research question initially without external input. This allows teams to work independently and rely on the skills and interests of team members. Once teams finalize their research question, they are assigned a mentor. The mentor introduces himself/herself, acknowledges the initial work the team has conducted, and asks a focused question to help open the lines of communication. Students continue to communicate with their mentor throughout their research. As research is completed, teams can share their investigation during a virtual presentation. These live presentations allow students to share their research with their mentor, other scientists, other students, parents, and school administrators. After the initial year of testing this authentic research process, EEAB is working to address the many lessons learned. This will allow the program to refine and improve the overall process in an effort to maximize the benefits. Combined, these powerful strategies provide a successful framework to help teachers enhance the skills and motivation of their students, preparing them to become the next generation of scientists, explorers, and STEM-literate citizens of our nation.

Graff, Paige Valderrama↗

DTLMod: A simulation framework for in situ workflow optimization

In situ processing workflows have become essential for coping with the explosion in data volume and velocity in large-scale scientific computing, providing domain scientists with early insights at runtime. Multiple frameworks implement this paradigm through a data transport layer (DTL), offering different data access modes and deployment schemes, but researchers currently lack the appropriate tools to assess design and deployment options before committing to costly real experiments. We introduce DTLMod, an open-source simulated DTL that enables performance evaluation of in situ workflow configurations at scale. Built on SimGrid, it links into any SimGrid-based simulator and is available in C++ and Python. We evaluate DTLMod along four axes: scalability (tens of thousands of simulated processes across interconnected clusters in seconds, with linear memory scaling), versatility (three implementation variants trading fidelity for speed), accuracy (simulated times faithfully reflecting real behavior), and practical utility (two use cases demonstrating evidence-based workflow design decisions).

Suter, Fred [ORNL] (ORCID:0000000319021955)↗

Status of the data acquisition, trigger, and slow control systems of the Mu2e experiment at Fermilab

The Mu2e experiment at the Fermilab will search for a coherent neutrinoless conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement by a factor of 10,000 over existing limits. In this work, the Mu2e Trigger and Data Acquisition System (TDAQ) uses otsdaq framework as the online Data Acquisition System (DAQ) solution. Developed at Fermilab, otsdaq integrates several framework components — an artdaq-based DAQ, an art-based event processing, and an EPICS-based detector control system (DCS), and provides a uniform multi-user interface to its components through a web browser. Data streams from the Mu2e tracker and calorimeter are handled by the artdaq-based DAQ and processed by a one-level software trigger implemented within the art framework. Events accepted by the trigger have their data combined, post-trigger, with the separately read out data from the Mu2e Cosmic Ray Veto system. Foundation of the Mu2e DCS, EPICS – an Experimental Physics and Industrial Control System – is an open-source platform for monitoring, controlling, alarming, and archiving. A prototype of the TDAQ and the DCS systems has been built and tested over the last three years at Fermilab’s Feynman Computing Center, and now the production system installation is underway. This work presents their status and focus on the installation plans and procedures for racks, workstations, network switches, gateway computers, DAQ hardware, slow controls implementation, and testing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Combined effects of emitter–emitter and emitter–plasmonic surface separations dictate photoluminescence enhancement in a plasmonic field

The brightness of an emitter can be enhanced by metal-enhanced fluorescence, wherein the excitonic dipole couples with the electromagnetic field of the surface plasmon. In this report, we experimentally map the landscape of photoluminescence enhancement (EF exp ) of emitters in a plasmonic field as a function of the emitter–emitter separation, s, and the emitter–plasmon distance, t. We use Au nanoparticles overcoated with inert spacers as plasmonic systems and CdSe/ZnS quantum dots (QDs) as an emitter bearing opposite surface charges. The t and s are varied by changing the spacer thickness and number density of QDs on the plasmonic surface, respectively. The electrostatic binding of emitters on the plasmonic surface and their number density are established by following the variation of zeta-potential. EF exp is high, when t is short and s is large; nevertheless, it decreases when the emitter–emitter interaction dominates due to plasmon assisted nonradiative processes. In the absence of a plasmonic field, the enhancement observed is attributed to environmental effects and is independent of s, confirming the role of the electric field. Indeed, the distance dependence of EF exp closely follows the decay of the plasmonic field upon dilution of the emitter concentration on nanoparticles’ surface (s = 18 nm). The QD–plasmon system is visualized in the framework of the Thomson problem, and classical electrodynamics calculations give the trends in t and s dependence of the photoluminescence. Being the first report on the simultaneous dependence of t and s on plasmon-enhanced photoluminescence, the results presented herein will open newer opportunities in the design of hybrid systems with a high brightness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Convergent Manufacturing of Large-Scale Components for Nuclear Applications, via Additive Manufacturing and Powder Metallurgy Hot Isostatic Pressing

Powder metallurgy (PM)–hot isostatic pressing (PM-HIP) has long been recognized as a powerful route for producing fully dense, near net shape metallic components. By consolidating powders under high temperature and pressure, HIP provides isotropic properties, uniform microstructures, and scalability to complex geometries that are vital for sectors such as aerospace, energy, and nuclear power. Yet despite these advantages, the technology has remained constrained by costly trial and error canister fabrication, limitations of conventional forging, and incomplete knowledge about how the canister design influences final part properties. Additive manufacturing (AM), by contrast, thrives on design freedom and geometric flexibility but struggles with speed, scalability, and cost when applied to very large structures. The research presented in this report investigated how a convergent manufacturing approach, combining AM with PM-HIP, can merge the strengths of both technologies, leveraging AM’s flexibility for canister design and HIP’s consolidation capability to deliver reliable, large, and complex parts. The work progressed through three case studies that built on one another in scale and complexity. Small cylindrical canisters fabricated by conventional methods, laser powder bed fusion, and directed energy deposition were filled with stainless steel powders and subjected to HIP. The resulting parts demonstrated near-full density and mechanical properties on par with wrought stainless steel, showing for the first time that AM canisters can be a direct substitute for conventional ones without sacrificing quality. The next step involved a medium-scale, noncentrosymmetric T-valve, which is an enclosed, multibranch geometry that tested the limits of AM + PM-HIP integration. The T-valve achieved predictable shrinkage and uniform densification, confirming feasibility for enclosed designs. However, this study also revealed oxide inclusions and interfacial challenges at the AM + HIP boundary, underscoring the critical importance of controlling interface chemistry and employing robust, in situ strategies, such as melt pool monitoring and thermal monitoring, coupled with nondestructive evaluation techniques such as x-ray computed tomography. Finally, the effort culminated in fabricating a large-scale impeller weighing nearly 2000 lb and spanning 5 ft in diameter. Produced via multirobot wire arc AM and hot isostatic pressed to near-full density, the impeller validated industrial-scale feasibility. Predictive models closely matched experimental shrinkage, tensile properties were spatially uniform across the component, and the AM + PM-HIP interface proved mechanically sound despite the presence of oxide-decorated prior particle boundaries. This large-scale demonstration is a major milestone, showing that hybrid AM + PM‑HIP can reliably deliver components at reactor-relevant scales. Collectively, these studies charted a logical pathway: small-scale work built scientific confidence, medium-scale work highlighted opportunities and challenges, and large-scale work proved industrial impact. The overarching conclusion of this report is that AM + PM-HIP should not be seen as a replacement for forging but as a complementary pathway that provides the US with flexibility, resilience, and new options for manufacturing nuclear-grade components. Looking ahead, several directions emerge as critical to sustaining progress. Predictive modeling must become faster, more accessible, and more accurate, with digital twins and machine learning reducing reliance on trial and error. Powders and alloys must be optimized for HIP, with improved cleanliness, reduced oxides, and tailored chemistries that enhance creep, fatigue, and irradiation resistance. Interfaces between AM and HIP regions must be better engineered through coatings, machining strategies, and surface treatments to mitigate oxide formation and ensure reliable bonding to explore opportunities for HIP of targeted compositional parts, as well as multimaterial HIP cladding applications. Monitoring and nondestructive evaluation need to expand, incorporating multimodal sensors, x-ray computed tomography, and real-time data integration through platforms such as Pelican. At the same time, the pathway to industrial adoption requires techno-economic analysis, machinability studies, and qualification frameworks aligned with industry and regulatory standards. Finally, workforce and academic engagement must be strengthened. Programs that train technicians and engineers for US Navy and US Department of Energy manufacturing challenges should be paired with academic partnerships to support fundamental research, with open sharing of non-export-controlled data to accelerate innovation and build the next generation of experts. In conclusion, this report demonstrates that hybrid AM + PM-HIP is scientifically viable and strategically important. By combining the design agility of AM with the consolidation strength of HIP and embedding modeling, monitoring, and workforce development, this approach provided a transformative new capability for US manufacturing. The path forward is clear: hybrid AM + PM-HIP is not just a promising research direction but is also potentially an industrially relevant pathway that can reshape how nuclear-grade components are designed, qualified, and deployed.

36 MATERIALS SCIENCE↗

The AI Bus architecture for distributed knowledge-based systems

The AI Bus architecture is layered, distributed object oriented framework developed to support the requirements of advanced technology programs for an order of magnitude improvement in software costs. The consequent need for highly autonomous computer systems, adaptable to new technology advances over a long lifespan, led to the design of an open architecture and toolbox for building large scale, robust, production quality systems. The AI Bus accommodates a mix of knowledge based and conventional components, running on heterogeneous, distributed real world and testbed environment. The concepts and design is described of the AI Bus architecture and its current implementation status as a Unix C++ library or reusable objects. Each high level semiautonomous agent process consists of a number of knowledge sources together with interagent communication mechanisms based on shared blackboards and message passing acquaintances. Standard interfaces and protocols are followed for combining and validating subsystems. Dynamic probes or demons provide an event driven means for providing active objects with shared access to resources, and each other, while not violating their security.

Schultz, Roger D.↗

The Core Flight System (cFS): NASA Quality Flight Software to Power Science and Exploration Available to the World

The presentation is planned to be a continuation of two previous discussions completed at the FSW Workshop regarding the cFS Test Framework (CTF) and Engineering Data Sheets (EDS). The presentation will also cover the latest advancements in cFS, including: 1. Quick into to cFS 2. An overview of our software release process + Git repo 3. Release of EDS files for the cFE + open-source apps 4. Overview of how to independently verify EDS files using CTF + what they can be used for. 5. Future plans for cFS. This presentation complements the talk on configuration management of distributed cFS repos, to be presented by Tam Ngo from Johnson Space Center.

Dan Knutsen↗

Pyrazine-Fused Porous Graphitic Framework-Based Mixed Matrix Membranes for Enhanced Gas Separations

Membrane-based separations can mitigate the capital- and energy-intensive challenges associated with traditional thermally driven processes. To further push the boundary of gas separations, mixed matrix membranes (MMMs) have been extensively exploited; however, identifying an optimal nanofiller to boost the separation performance of MMMs beyond Robeson permeability-selectivity upper bounds remains an ongoing challenge. In this study, a new class of MMMs based on pyrazine-fused crystalline porous graphitic frameworks (PGFs) is reported. At a loading of 6 wt % PGFs, the MMMs surpass the current H 2 /CH 4 Robeson upper bound, ideally suited for applications such as H 2 regeneration. In addition, the fabricated MMMs exhibit appealing CO 2 separation performance, closely approaching the current Robeson upper bounds for CO 2 separation. Compared with the pristine polymeric membranes, the PGF-based MMMs display a record-high enhancement of gas permeability over 120% while maintaining intrinsic gas selectivities. Highlighting the crucial role of the crystallinity of nanofillers, this study demonstrates a facile and effective approach in formulating high-performance MMMs, complementing state-of-the-art membrane formation processes. The design principles open the door to energy-efficient separations of gas mixtures with enhanced productivity compatible with the current membrane manufacturing.

36 MATERIALS SCIENCE↗

A Framework for Assessing Economic and Environmental Trade-offs of Internalized Emission Costs in ERCOT Grid Planning

The power grid is on the cusp of a massive transition driven by three major areas: 1) the growth in demand for electricity, 2) efforts to decarbonize the United States economy, and 3) a desire to mitigate social disparities from the impact of electricity generation on local populations. However, most studies of the electricity sector do not include equity impacts in their models. This study seeks to do so by developing a comprehensive and generalizable model tailored to the Electric Reliability Council of Texas (ERCOT) grid, designed to incorporate the equity impacts of electricity generation in a decarbonized and resilient framework. To integrate equity into our research, we incorporate environmental externalities into our capacity expansion model of ERCOT. Specifically, we factor in intermediate-level local marginal damages of precursor pollutants (NH3, NOx, primary PM2.5, SO2, and VOC) and global pollutant CO2 into the cost of generating electricity. We do this by taking into account county population, county ambient pollution concentration, and generator emission rates. Leveraging open-source modeling tools, such as PowerGenome, pyGRETA, and GenX we construct a county-level model to account for these costs. We integrate these marginal damages into the variable operations and maintenance costs of generators, for both existing and potential future builds. This study’s findings suggest that the value of a dynamic social cost of carbon (SSC) will cover criteria pollutant marginal damages within the ERCOT grid and solar and wind is expected to increase out to 2035. Key metrics evaluated within this research include fuel mix distribution across technologies, transmission and grid infrastructure costs, CO2 emissions, local pollutants marginal damages, and the variation in generation capacity built by the model. These results and framework can be used to support grid decisions that explicitly include distributional and procedural equity within a decarbonized and sustainable grid framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A multisite decomposition of the tensor network path integrals

Tensor network decompositions of path integrals for simulating open quantum systems have recently been proven to be useful. However, these methods scale exponentially with the system size. This makes it challenging to simulate the non-equilibrium dynamics of extended quantum systems coupled with local dissipative environments. In this work, we extend the tensor network path integral (TNPI) framework to efficiently simulate such extended systems. The Feynman–Vernon influence functional is a popular approach used to account for the effect of environments on the dynamics of the system. In order to facilitate the incorporation of the influence functional into a multisite framework (MS-TNPI), we combine a matrix product state (MPS) decomposition of the reduced density tensor of the system along the sites with a corresponding tensor network representation of the time axis to construct an efficient 2D tensor network. The 2D MS-TNPI network, when contracted, yields the time-dependent reduced density tensor of the extended system as an MPS. The algorithm presented is independent of the system Hamiltonian. We outline an iteration scheme to take the simulation beyond the non-Markovian memory introduced by solvents. Applications to spin chains coupled to local harmonic baths are presented; we consider the Ising, XXZ, and Heisenberg models, demonstrating that the presence of local environments can often dissipate the entanglement between the sites. We discuss three factors causing the system to transition from a coherent oscillatory dynamics to a fully incoherent dynamics. The MS-TNPI method is useful for studying a variety of extended quantum systems coupled with solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Challenging conventional assumptions in PV: a high-throughput open-air approach to low-cost perovskite module production

Perovskite solar modules (PSMs) offer a promising pathway to low-cost photovoltaics, yet their commercialization is challenged by manufacturing scalability, device uniformity, additive costs, interlayer complexity, and module stability. This study introduces a comprehensive technoeconomic analysis of single junction PSM's and projections for tandem perovskite-Si modules that integrate all materials and manufacturing steps, module performances, projected lifetimes, and manufacturing costs across scales. Here, we highlight an open-air manufacturing approach to fabricate all active layers of serially interconnected PSMs, including electrodes and charge transport layers, enabling high-throughput production without inert or vacuum environments. The analysis reveals two orders of magnitude throughput enhancement and cost reductions of 24% in all-open-air production, escalating to over 60% at 1 GW factory capacity compared to conventional methods. Levelized cost of energy (LCOE) projections for utility-scale installations over 30 years, accounting for module replacement and recycling, demonstrate the potential to achieve the 2030 US target of $0.03 per kWh with realistic 7–11-year PSM lifetimes, outperforming incumbent silicon-based modules. Neither four terminal (4T) nor two terminal (2T) tandem-Si PSMs improve over single junction perovskite or silicon LCOE regardless of higher efficiencies at any modeled lifetime. Addressing PSM technical challenges with a cost-modeling framework guides commercialization efforts and provides a convincing pathway for challenging incumbent Si-based PV.

14 SOLAR ENERGY↗

A general framework for gravitational charges and holographic renormalization

We develop a general framework for constructing charges associated with diffeomorphisms in gravitational theories using covariant phase space techniques. This framework encompasses both localized charges associated with space–time subregions, as well as global conserved charges of the full space–time. Expressions for the charges include contributions from the boundary and corner terms in the subregion action, and are rendered unambiguous by appealing to the variational principle for the subregion, which selects a preferred form of the symplectic flux through the boundaries. The Poisson brackets of the charges on the subregion phase space are shown to reproduce the bracket of Barnich and Troessaert for open subsystems, thereby giving a novel derivation of this bracket from first principles. In the context of asymptotic boundaries, we show that the procedure of holographic renormalization can be always applied to obtain finite charges and fluxes once suitable counterterms have been found to ensure a finite action. This enables the study of larger asymptotic symmetry groups by loosening the boundary conditions imposed at infinity. We further present an algorithm for explicitly computing the counterterms that renormalize the action and symplectic potential, and, as an application of our framework, demonstrate that it reproduces known expressions for the charges of the generalized Bondi–Metzner–Sachs algebra.

Physics↗

Thermally Activated Adsorption in Metal–Organic Frameworks with a Temperature‐Tunable Diffusion Barrier Layer

Abstract Modification of the external surfaces of metal–organic frameworks offers a new level of control over their adsorption behavior. It was previously shown that capping of MOFs with ethylenediamine (EDA) can effectively retain small gaseous molecules at room temperature. Reported here is a temperature‐induced variation in the capping‐layer gate‐opening mechanism through a combination of in situ infared experiments and ab initio simulations of the capping layer. An atypical acceleration and increase in the loading of weakly adsorbed molecules upon raising the temperature above room temperature is observed. These findings show the discovery of novel temperature‐dependent kinetics that goes beyond standard kinetics and suggest a new avenue for tailoring selective adsorption by thermally tuning the surface barrier.

Tan, Kui↗

Conditional deep generative models for simultaneous simulation and reconstruction of entire events

We extend the particle-flow neural assisted simulations (arnassus) framework of fast simulation and reconstruction to entire collider events. In particular, we use two generative artificial intelligence tools, continuous normalizing flows and diffusion models, to create a set of reconstructed particle-flow objects conditioned on truth-level particles from CMS Open Simulations. While previous work focused on jets, our updated methods now can accommodate all particle-flow objects in an event along with particle-level attributes like particle type and production vertex coordinates. This approach is fully automated, entirely written in Python, and GPU-compatible. Using a variety of physics processes at the LHC, we show that the extended arnassus is able to generalize beyond the training dataset and outperforms the standard, public tool elphes.

Dreyer, Etienne [Weizmann Institute of Science, Re↗