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At least 811 records · Page 45

Development of a Comprehensive and Centralized Waste Management System - 19412

Information Systems Laboratories (ISL) has designed a new single, integrated, waste management and control system to administer all aspects of nuclear waste management. The overriding goal of the initiative is to provide federal, state, and local agencies with operational awareness, management, and programmatic support for all functions related to nuclear waste management. Over decades of waste management federal agencies have sponsored or directly paid for the development, operation, and control of multiple systems to track and control its waste - with varied success. Multiple contractors have generated disparate control systems/databases and literally mountains of data. Past approaches have not provided a single, integrated, real time data management system. ISL's analysis of past failed efforts has reveal four common symptoms: - Control/management systems that are not compatible; - Programmatic costs that increase with systems use and re-work; - Systems focused on specific sets of data; - Inaccurate or outdated data sets. An integrated waste management and control system that collects and displays real-time, accurate inventory, waste container certification, transportation certification, emplacement, and shipment related data improve operational awareness and overcomes these limitations. Using its vast knowledge and experience in developing numerous waste tracking and management systems, ISL has leveraged its own in-house knowledge and gathered requests from stakeholders all across the industry to design a system that meets the needs of users at all levels of the nuclear waste management process. Using the highly successful and widely used Waste Data System (WDS) designed for the Waste Isolation Pilot Plant as a core component, ISL has designed a system that greatly expands on the functionality of the WDS to exceed its current focus of management of Transuranic Waste shipments. The new system is designed to provide the ability to track a wide range of waste types from Transuranic, High Level, Low Level, Mixed, and any nuclear related material. The main focus of the system is to provide federal regulators a comprehensive and real-time oversight into the handling of all nuclear waste materials. Oversight activities include, but are not limited to, strategy development, projections, metrics, incentive development, tracking, budget review, government cost estimating, and integrated schedules. The major components of the system are summarized below: - The Centralized Waste Management System (CWMS), which will include assimilating and validating known sources of data into the CWMS. - The programmatic reporting support component, which will handle queries from regulators, track compliance with regulatory requirements, and maintain the dashboard for federal management. - Both the CWMS and the programmatic reporting support component will use a standard set of business rules that govern system operations and allow site and program specific needs and limits for all waste programs and types to be captured and maintained. This presentation will provide details of each component of the system detailing its use, interfaces with other components, and value to stakeholders. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Estimating PV power from aggregate power measurements within the distribution grid

The increased integration of photovoltaic (PV) systems in distribution grids reduces visibility and situational awareness for utilities because the PV systems' power production is usually not monitored by them. To address this problem, a method called Contextually Supervised Source Separation (CSSS) has been recently adapted for real-time estimation of aggregate PV active power generation from aggregate net active and reactive power measurements at a point in a radially configured distribution grid (e.g., substation). In its original version, PV disaggregation is formulated as an optimization problem that fits linear regression models for the aggregate PV active power generation and true substation active power load. This paper extends the previous work by adding regularization terms in the objective function to capture additional contextual information such as smoothness, by adding new constraints, by introducing new regressors such as ambient temperature, and by investigating the use of time-varying regressors. Furthermore, we perform extensive parametric analysis to study tuning of the objective function weighting factors in a way that maximizes performance and robustness. The proposed PV disaggregation method can be applied to networks with either a single PV system (e.g., megawatt scale) or many distributed ones (e.g., residential scale) connected downstream of the substation. Simulation studies with real field recorded data show that the enhancements of the proposed method reduce disaggregation error by 58% in winter and 35% in summer compared to previous CSSS-based work. When compared against a commonly used transposition model based approach, the reduction in disaggregation error is more pronounced (78% reduction in winter and 45% in summer). Additional simulations indicate that the proposed algorithm is also applicable for PV systems with time-varying power factors. In conclusion, overall, our results show that—with appropriate modeling and tuning—it is possible to accurately estimate the aggregated PV active power generation of a distribution feeder with minimal or no additional sensor deployment.

14 SOLAR ENERGY↗

Measuring stomatal and guard cell metrics for plant physiology and growth using StoManager1

Abstract Automated guard cell detection and measurement are vital for understanding plant physiological performance and ecological functioning in global water and carbon cycles. Most current methods for measuring guard cells and stomata are laborious, time-consuming, prone to bias, and limited in scale. We developed StoManager1, a high-throughput tool utilizing geometrical, mathematical algorithms, and convolutional neural networks to automatically detect, count, and measure over 30 guard cell and stomatal metrics, including guard cell and stomatal area, length, width, stomatal aperture area/guard cell area, orientation, stomatal evenness, divergence, and aggregation index. Combined with leaf functional traits, some of these StoManager1-measured guard cell and stomatal metrics explained 90% and 82% of tree biomass and intrinsic water use efficiency (iWUE) variances in hardwoods, making them substantial factors in leaf physiology and tree growth. StoManager1 demonstrated exceptional precision and recall (mAP@0.5 over 0.96), effectively capturing diverse stomatal properties across over 100 species. StoManager1 facilitates the automation of measuring leaf stomatal and guard cells, enabling broader exploration of stomatal control in plant growth and adaptation to environmental stress and climate change. This has implications for global gross primary productivity (GPP) modeling and estimation, as integrating stomatal metrics can enhance predictions of plant growth and resource usage worldwide. Easily accessible open-source code and standalone Windows executable applications are available on a GitHub repository (https://github.com/JiaxinWang123/StoManager1) and Zenodo (https://doi.org/10.5281/zenodo.7686022).

Wang, Jiaxin (ORCID:0000000348085085)↗

SECARB Project Overview Book

In 2003, the United States Department of Energy (DOE) issued awards initiating seven Regional Carbon Sequestration Partnerships (RCSP) spanning the United States and portions of Canada. Managed by DOE’s National Energy Technology Laboratory (NETL), the RCSPs currently represent more than 400 state agencies, universities, and private companies, spanning 43 states, three Native American Organizations, and four Canadian provinces. The Southern States Energy Board (SSEB) received an award on October 1, 2003, which established the Board’s overall management and administration of the Southeast Regional Carbon Sequestration Partnership, or SECARB. The geographical region currently includes 13 states and a network of more than 100 stakeholders. The Nation’s leading scientists, university researchers, national laboratories, industrial representatives, environmental organizations, and many others have taken a proactive approach at identifying and characterizing the most promising options for technology deployment and carbon dioxide (CO2) utilization and storage (CCUS) for the Southeast. The results obtained during these injections will be important to the future commercialization of CCUS technologies and the continued use of fossil fuels as a significant energy source in a manner that is environmentally responsible. Each of the six SECARB project locations has been locally coordinated by its own field team. The field teams assume responsibility for the technical scope of work, local education and outreach, permitting, monitoring, verification, and accounting (MVA), and maintaining the validation test’s schedule and budget. Each team contributes new information to the continued characterization of the region. In addition, a task is dedicated to integrating field data and filling gaps in regional characterization data sets. Data and tools developed in the Continued Characterization task are incorporated into a relational database and geographic information system (GIS). All field tests, the continued characterization project, and the cross-cutting functions are designed to support the DOE roadmap by validating technologies and identifying locations throughout the region that could support full-scale CCUS deployment opportunities. Detailed fact sheets for the SECARB projects are available on the SECARB website at www.secarbon.org (see “Projects” tab).

RCSP↗

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗

Perspectives on Designer Photocathodes for X-ray Free-Electron Lasers: Influencing Emission Properties with Heterostructures and Nanoengineered Electronic States

Here, the development of photoemission electron sources to specifically address the competing andnincreasingly stringent requirements of advanced light sources such as X-ray Free Electron Lasers (XFELs) motivates a comprehensive material-centric approach that integrates predictive compu- tational physics models, advanced nano-synthesis methods, and sophisticated surface science char- acterization with in situ correlated study of photoemission performance and properties. Related efforts in material science are adopting various forms of nanostructure (such as compositionally graded stoichiometry in heterostructured architectures, and quantum features) allowing for tailored electronic structure to control and enhance opto-electronic properties. These methods influence the mechanisms of photoemission (absorption, transport, and emission) but have not, as yet, been systematically considered for use in photocathode applications. Recent results and near-term op- portunities are described to exploit controlled functionality of nanomaterials for photoemission. An overview of the requirements and status is provided.

47 OTHER INSTRUMENTATION↗

A report on SHARP (Spacecraft Health Automated Reasoning Prototype) and the Voyager Neptune encounter

The development and application of the Spacecraft Health Automated Reasoning Prototype (SHARP) for the operations of the telecommunications systems and link analysis functions in Voyager mission operations are presented. An overview is provided of the design and functional description of the SHARP system as it was applied to Voyager. Some of the current problems and motivations for automation in real-time mission operations are discussed, as are the specific solutions that SHARP provides. The application of SHARP to Voyager telecommunications had the goal of being a proof-of-capability demonstration of artificial intelligence as applied to the problem of real-time monitoring functions in planetary mission operations. AS part of achieving this central goal, the SHARP application effort was also required to address the issue of the design of an appropriate software system architecture for a ground-based, highly automated spacecraft monitoring system for mission operations, including methods for: (1) embedding a knowledge-based expert system for fault detection, isolation, and recovery within this architecture; (2) acquiring, managing, and fusing the multiple sources of information used by operations personnel; and (3) providing information-rich displays to human operators who need to exercise the capabilities of the automated system. In this regard, SHARP has provided an excellent example of how advanced artificial intelligence techniques can be smoothly integrated with a variety of conventionally programmed software modules, as well as guidance and solutions for many questions about automation in mission operations.

Martin, R. G.↗

Mars Science Laboratory Rover Integrated Pump Assembly Bellows Jamming Failure

The Mars Science Laboratory rover and spacecraft utilize two mechanically pumped fluid loops for heat transfer to and from the internal electronics assemblies and the Radioisotope Thermo-Electric Generator (RTG). The heat transfer fluid is Freon R-11 (CFC-11) which has a large coefficient of thermal expansion. The Freon within the heat transfer system must have a volume for safe expansion of the fluid as the system temperature rises. The device used for this function is a gas-over-liquid accumulator. The accumulator uses a metal bellows to separate the fluid and gas sections. During expansion and contraction of the fluid in the system, the bellows extends and retracts to provide the needed volume change. During final testing of a spare unit, the bellows would not extend the full distance required to provide the needed expansion volume. Increasing the fluid pressure did not loosen the jammed bellows either. No amount of stroking the bellows back and forth would get it to pass the jamming point. This type of failure, if it occurred during flight, would result in significant overpressure of the heat transfer system leading to a burst failure at some point in the system piping. A loss of the Freon fluid would soon result in a loss of the mission. The determination of the source of the jamming of the bellows was quite elusive, leading to an extensive series of tests and analyses. The testing and analyses did indicate the root cause of the failure, qualitatively. The results did not provide a set of dimensional limits for the existing hardware design that would guarantee proper operation of the accumulator. In the end, a new design was developed that relied on good engineering judgment combined with the test results to select a reliable enough solution that still met other physical constraints of the hardware, the schedule, and the rover system.

bellows↗

Integrated quantum optical phase sensor in thin film lithium niobate

Abstract The quantum noise of light, attributed to the random arrival time of photons from a coherent light source, fundamentally limits optical phase sensors. An engineered source of squeezed states suppresses this noise and allows phase detection sensitivity beyond the quantum noise limit (QNL). We need ways to use quantum light within deployable quantum sensors. Here we present a photonic integrated circuit in thin-film lithium niobate that meets these requirements. We use the second-order nonlinearity to produce a squeezed state at the same frequency as the pump light and realize circuit control and sensing with electro-optics. Using 26.2 milliwatts of optical power, we measure (2.7 ± 0.2)% squeezing and apply it to increase the signal-to-noise ratio of phase measurement. We anticipate that photonic systems like this, which operate with low power and integrate all of the needed functionality on a single die, will open new opportunities for quantum optical sensing.

47 OTHER INSTRUMENTATION↗

A Transparent Translation from Legacy System Model into Common Information Model

Advances in the smart grid are forcing utilities toward better monitoring, control, and analysis of distribution systems, and require extensive cyber-based, intelligent systems and applications to realize various functionalities. The ability of systems, or components within systems, to interact and exchange services or information with each other is the key to the success of smart grid technologies, and it requires efficient information exchanging and data sharing infrastructure. The Common Information Model (CIM) is a standard that allows different applications to exchange information about an electrical system, and it has become a widely accepted solution for information exchange among different platforms and applications. However, most existing legacy systems were developed using their own languages rather than CIM. Integrating such legacy systems is a challenge for utilities, and the appropriate use of the integrated legacy systems is even more intricate. Thus, this paper describes an approach and open-source tool developed to translate legacy system models into CIM format. The developed tool was tested for a commercial distribution management system and simulation results have proved its effectiveness.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗

From Modular ADMS to Plug-and-Play Ops: Distribution Grid Operations with Platform-Level Orchestration to Enable Ambitious App Hosting

The core function of the distribution grid is to provide electricity to consumers affordably, reliably, and securely. In pursuing these core objectives, distribution utilities are accountable to customers, regulators, and in some cases, shareholders. Other third parties such as aggregators and microgrids can also have a stake in the smooth operation of the grid. Each of these stakeholders has economic, business, and/or governance objectives that inform their expectations of the distribution grid. This multi-objective, multi-stakeholder environment creates tension that must be reconciled to successfully design and operate the distribution grid. Innovative companies are competing to bring high-tech solutions to electric utilities and their customers that address each of these objectives. Many developers of advanced distribution management systems (ADMS) and distributed energy resource management systems (DERMS) have adopted a modular architecture that allows grid operators to select functions and features according to their individual system needs. A modular platform also allows the solution provider to develop and integrate specific new product modules; however, the need to pursue multiple objectives with a fixed set of controllable devices makes integration expensive whether it is done at the product development stage or the deployment stage. This cost creates a significant barrier to adoption and can lengthen the product to market time of new solutions. To fundamentally address the complexity of system integration for distribution grid operations, the U.S. Department of Energy Office of Electricity has funded the GridAPPS-D project at PNNL, which streamlines integration by contributing to standards development, defining system architecture, applying advanced mathematics, and developing open-source software to demonstrate the concept of an open data-integration platform for distribution operations. The open data-integration platform concept enables system operators and solution providers to deploy ambitious, best-of-breed applications (or apps) without continually reengineering for integration. Ambitious apps developed by different solution providers will inevitably attempt to achieve different control objectives with the same set of controllable devices. If the open platform itself can resolve these conflicts in a way that achieves the best available outcomes for all apps, doesn’t restrict the ambitious design of apps, and ensures safe and secure operations, apps will be able to plug-and-play with the platform at the same time as other ambitious apps. In this paper, we describe a framework called App Deconfliction that empowers a platform to assign setpoints to controllable devices based on the values preferred by different apps (and even external stakeholder entities like customers or aggregators). The App Deconfliction framework is compatible with several methods for determining setpoint values. We present two methods based on game theory that provide a subtle built-in incentive structure for developers to adapt their apps to the fact that they will be operating in a moderated multi-app environment and to favor device setpoints that have the most effect on their objectives over those that have the least effect. Our simulation-based demonstrations have shown that game-theory-based deconfliction can lead to a 7% improvement in control space utilization compared to design-based methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

pyam: Python Implementation of YaM

pyam is a software development framework with tools for facilitating the rapid development of software in a concurrent software development environment. pyam provides solutions for development challenges associated with software reuse, managing multiple software configurations, developing software product lines, and multiple platform development and build management. pyam uses release-early, release-often development cycles to allow developers to integrate their changes incrementally into the system on a continual basis. It facilitates the creation and merging of branches to support the isolated development of immature software to avoid impacting the stability of the development effort. It uses modules and packages to organize and share software across multiple software products, and uses the concepts of link and work modules to reduce sandbox setup times even when the code-base is large. One sidebenefit is the enforcement of a strong module-level encapsulation of a module s functionality and interface. This increases design transparency, system stability, and software reuse. pyam is written in Python and is organized as a set of utilities on top of the open source SVN software version control package. All development software is organized into a collection of modules. pyam packages are defined as sub-collections of the available modules. Developers can set up private sandboxes for module/package development. All module/package development takes place on private SVN branches. High-level pyam commands support the setup, update, and release of modules and packages. Released and pre-built versions of modules are available to developers. Developers can tailor the source/link module mix for their sandboxes so that new sandboxes (even large ones) can be built up easily and quickly by pointing to pre-existing module releases. All inter-module interfaces are publicly exported via links. A minimal, but uniform, convention is used for building modules.

Myint, Steven↗

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

Abstract Background To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers are needed. Purpose The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of their systems. Methods We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open‐source GPU‐accelerated Monte Carlo x‐ray imaging simulation code (MC‐GPU). We build on the previous version of the MC‐GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)‐approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x‐ray photon till its first interaction within the x‐ray detector. On the other hand, the signal spread in the x‐ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron–hole pairs or optical photons) using analytical equations in the detector. The analytical optical spread model for the indirect detector includes the depth‐dependent spread and collection of optical photons and relies on a pre‐computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x‐ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measured data. Results We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with direct detectors. Conclusions We have presented computational models of three commercially available FDA‐approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC‐GPU codes that can be used to replicate three systems are available in open source format through GitHub.

Sengupta, Aunnasha↗

Toward High-Voltage Cathodes for Zinc-Ion Batteries: Discovery Pipeline and Material Design Rules

Efficient energy storage systems are crucial to address the intermittency of renewable energy sources. As multivalent batteries, Zn-ion batteries (ZIBs), while inherently low voltage, offer a promising low-cost alternative to Li-ion batteries due to the viable use of zinc as the anode. However, to maximize the potential impact of ZIBs, rechargeable cathodes with improved Zn diffusion are needed. To better understand the chemical and structural factors influencing Zn-ion mobility within battery electrode materials, we employ a high-throughput computational screening approach to systematically evaluate candidate intercalation hosts for ZIB cathodes, expanding the chemical search space on empty intercalation hosts that do not contain Zn. We leverage a high-throughput screening funnel to identify promising cathodes in ZIBs, integrating screening criteria with density functional theory (DFT)-based calculations of Zn2+ intercalation and diffusion inside the host materials. Using these data, we identify the design principles that favor Zn-ion mobility in candidate cathode materials. Building on previous work on divalent-ion cathodes, this study broadens the chemical space for next-generation multivalent energy storage systems.

electrodes↗

Direct Deposition of Crystalline Ta 3 N 5 Thin Films on FTO for PEC Water Splitting

Tantalum Nitride is a promising photoanode material for solar water splitting, but the further study and practical use is constrained by the harsh conditions of the synthesis from Ta metal. Here we report the direct deposition of crystalline Ta 3 N 5 on FTO substrate via a custom-built ALD system. A combination of TaCl 5 (Ta-precursor) and ammonia (N-source) were sequentially pulsed into the ALD reactor with the substrate heated to 550 °C to deposit compact and thin films of Ta 3 N 5 with controllable thicknesses on FTO substrates. Importantly, it is shown that the FTO is chemically and structurally stable under the reducing conditions of ammonia at 550 °C. These electrodes produced an exceptional photocurrent onset potential of ~ 0.3 V vs. RHE with a maximum photocurrent of ~ 2.4 mA cm -2 at 1.23 V vs RHE. Results of photoelectrochemical investigations as a function of film thickness and illumination direction reveal that the performance of Ta 3 N 5 is controlled by a hole diffusion length of ~50 nm. These results are crucial for the successful integration of Ta 3 N 5 in efficient unassisted water splitting applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurement of the ionization response of amorphous selenium with 122 keV γ rays

In this work, we performed a measurement of the ionization response of 200 μm-thick amorphous selenium (aSe) layers under drift electric fields of up to 50 V/μm. The aSe target was exposed to ionizing radiation from a 57 Co radioactive source and the ionization pulses were recorded with high resolution. Using the spectral line from the photoabsorption of 122 keV γ rays, we measured the charge yield in aSe and the line width as a function of drift electric field. From a detailed microphysics simulation of charge generation and recombination in aSe, we conclude that the strong dependence of recombination on the ionization track density provides the dominant contribution to the energy resolution in aSe. These results provide valuable input to estimate the sensitivity of a proposed next-generation search for the neutrinoless ββ decay of 82 Se that aims to employ imaging sensors with an active layer of aSe. We estimate the RMS line width of the integrated ionization signal from neutrinoless ββ decay events (of deposited energy 3 MeV) to be 2.0% for a drift field of 50 V/μm. The energy resolution can be improved to 1% by correcting for the charge yield as a function of ionization density along the imaged electron tracks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Toward quantum networking with frequency-bin qudits

Quantum networking holds tremendous promise in transforming computation and communication. Entangled-photon sources are critical for quantum repeaters and networking, while photonic integrated circuits are vital for miniaturization and scalability. In this talk, we focus on generating and manipulating frequency-bin entangled states within integrated platforms. We encode quantum information as a coherent superposition of multiple optical frequencies; this approach is favorable due to its amenability to high-dimensional entanglement and compatibility with fiber transmission. We successfully generate and measure the density matrix of biphoton frequency combs from integrated silicon nitride microrings, fully reconstructing the state in an 8 × 8 two-qudit Hilbert space, the highest so far for frequency bins. Moreover, we employ Vernier electro-optic phase modulation methods to perform time-resolved measurements of biphoton correlation functions. Currently, we are exploring bidirectional pumping of microrings to generate indistinguishable entangled pairs in both directions, aiming to demonstrate key networking operations such as entanglement swapping and Greenberger–Horne–Zeilinger state generation in the frequency domain.

Myilswamy, Karthik V.↗