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DOE OSTI2024

Software defined networking moving target defense honeypot

Disclosed herein are systems, methods, and storage media for thwarting cyber-attacks and data theft. A computing system receives packets and compares with a configuration resource. The computing system determines that the packet does not match the configuration resource and transmits a packet to a decoy environment via an SDN switch. The decoy environment is configured to generate time-out, service unavailable, or restricted access messages. In some embodiments, the computing system determines the packet does match the configuration and transmits the packet to a production network via an SDN switch. The SDN switch is communicatively connected to the decoy environment through a first channel and communicatively connected to a production environment through a separate second channel. The computing system is further configured to create and transmit to the SDN switch, rules to manage transmitting the packet to either the decoy environment or the production environment.

Lyle, Joshua A.↗

DOE OSTI2024

Group-III nitride devices and systems on IBAD-textured substrates

A multilayer structure including a hexagonal epitaxial layer, such as GaN or other group III-nitride (III-N) semiconductors, a <111>oriented textured layer, and a non-single crystal substrate, and methods for making the same. The textured layer has a crystalline alignment preferably formed by the ion-beam assisted deposition (IBAD) texturing process and can be biaxially aligned. The in-plane crystalline texture of the textured layer is sufficiently low to allow growth of high quality hexagonal material, but can still be significantly greater than the required in-plane crystalline texture of the hexagonal material. The IBAD process enables low-cost, large-area, flexible metal foil substrates to be used as potential alternatives to single-crystal sapphire and silicon for manufacture of electronic devices, enabling scaled-up roll-to-roll, sheet-to-sheet, or similar fabrication processes to be used. The user is able to choose a substrate for its mechanical and thermal properties, such as how well its coefficient of thermal expansion matches that of the hexagonal epitaxial layer, while choosing a textured layer that more closely lattice matches that layer. Electronic devices such as LEDs can be manufactured from such structures. Because the substrate can act as both a reflector and a heat sink, transfer to other substrates, and use of external reflectors and heat sinks, is not required, greatly reducing costs. Large area devices such as light emitting strips or sheets may be fabricated using this technology.

Matias, Vladimir↗

DOE OSTI2025

AGC-2 Graphite Preirradiation Data Analysis Report

This report describes the specimen loading order and documents all preirradiation examination material property measurement data for graphite specimens contained within the Second Advanced Graphite Capsule (AGC 2) irradiation capsule. The AGC 2 capsule is the second in six planned irradiation capsules comprising the Advanced Graphite Creep (AGC) test series. The AGC test series is used to irradiate graphite specimens in order to garner quantitative data necessary for predicting the irradiation behavior and operating performance of new nuclear grade graphites. This testing will ascertain the in service behavior of the graphite for pebble bed and prismatic very high temperature reactor designs. Similar to the First Advanced Graphite Capsule (AGC 1) preirradiation examination report, material property tests were conducted on specimens from 18 nuclear grade graphite types. However, AGC 2 tested an increased number of specimens (i.e., 512) prior to loading them into the AGC 2 irradiation assembly. All AGC 2 specimen testing was conducted at Idaho National Laboratory from July 2009 to August 2010. This report also details the specimen loading methodology for graphite specimens inside the AGC 2 irradiation capsule. The AGC 2 capsule design requires “matched pair” creep specimens that have similar dose levels above and below the neutron flux profile mid plane. This provides similar specimens with and without an applied load. Analysis in this document utilizes the neutron flux profile calculated for the AGC 2 capsule design, the capsule dimensions, and the size (i.e., length) of the selected graphite specimens to create a stacking order that produces “matched pairs” of graphite specimens above and below the AGC 2 capsule elevation mid point, thus providing specimens with similar neutron dose levels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Filter-Banks for Ultra-Wideband Communications, Sensing, and Localization

Recently, filterbank multi-carrier spread spectrum (FBMC-SS) has been proposed as a candidate waveform for ultrawideband (UWB) communications. It has been noted that FBMCSS is a perfect match to this application, leading to a trivial method of matching to the required spectral mask at different regions of the world. FBMC-SS also allows easy rejection of high-power interfering signals that may appear over different parts of the UWB spectral band. In this paper, we concentrate on the use of staggered multitone spread spectrum (SMT-SS) for UWB communications. SMT makes use of offset QAM modulation to transmit data symbols over narrowband, overlapping subcarrier bands. This form of FBMC-SS is well-suited to UWB communications because it has good spectral efficiency and a flat power spectral density (PSD), resulting in good utilization of the UWB spectral mask. Additionally, we explore new methods for multi-coding that result in higher bit rates than previous FBMCSS systems. Moreover, we study methods for equalizing the UWB multipath channel and cancelling narrowband interference. Excellent performance of the proposed methods are substantiated by presenting simulation results.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Automated Waterbox Inspection for Nuclear Power Plants Using Computer Vision - Based Change Detection

Nuclear power plant waterboxes require regular inspection for leaks, missing components, and structural damage during maintenance outages. Traditional manual inspection is time-consuming and poses safety risks from confined space entry. We developed an automated computer vision system for drone-based waterbox inspection in partnership with Florida Light and Power. Our approach uses feature detection and matching to identify critical changes between baseline and current inspection images, automatically flagging additions (leaks/debris), removals (missing plugs), and translations (displaced components) while compensating for drone movement and environmental variations. We systematically evaluated six feature matching methods, from classical approaches (SIFT+BF) to state-of-the-art neural networks (SuperPoint+SuperGlue), using both standard benchmarks (HPatches) and waterbox-specific validation with real-world augmentations. SuperPoint+SuperGlue achieved superior performance with 7.82 pixels RMSE and 100% success rate—2.8x better accuracy than our baseline. While the pre-trained model has commercial licensing restrictions for nuclear deployment, our findings validate this architecture for custom training. We implemented a real-time GUI demonstrating the SIFT+BF approach for immediate deployment, processing drone feeds at 30 FPS with color-coded change visualization. Future work includes training a custom SuperPoint+SuperGlue model on waterbox data and integrating Vision-Language Models for automated reporting and maintenance guidance.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2026

Heat Transfer Experiments of a 1st Stage Blade Cascade for Supercritical CO2 Oxy-Combustion Turbine Application

The results of internally cooled 1st stage blade (S1B) cascade testing in a supercritical CO2 environment is presented. The turbine blade design has been previously established for the end application of an oxy-combustion turbine operating in the Allam-Fetvedt cycle with turbine inlet conditions of 305 bar and 1150°C. The internally cooled blade features leading edge (LE) region impingement cooling, mid-section ribbed serpentine passages, and a pin-finned trailing edge (TE) region before cooling ejection holes. The geometry for the tested blade cascade has a cooled central blade with un-cooled blades on either side to match flowpath areas of the actual turbine. The flowpath reuses internal components previously employed for mid-section region ribbed serpentine passage experiments that established Nusselt number enhancement ratios over a range of Reynolds numbers from 100,000-400,000. New components include flow conditioning plates upstream and downstream of the blade cascade to adequately represent the flow field and blade external heat transfer coefficient profiles for the actual turbine. The cooled central blade utilizes uniform crystal temperature sensors (UCTS) with six sensors each on the blade pressure and suction surfaces distributed radially and from LE to TE. The post-processed UCTS quantified the maximum wall temperature seen at each installed sensor location. The test procedure consisted of establishing supercritical CO2 cooling flow temperature and flow rate and maintaining it throughout the test. The flow rate aims to match that for the actual in-service turbine blade design and is maintained through an orifice restriction to keep the pressure differential between internal cooling flow and external hot flow nearly constant. For the sCO2 flow path external to the blade, temperatures were ramped throughout the test via control of the test loop’s natural gas burner heater. The maximum temperature seen was 468°C and held constant for a duration of 10 minutes at which the blade metal temperature was predicted to be at its maximum before ramping down. For the turbine blade design for service inlet conditions, external flow path computational fluid dynamics (CFD) results and an internal cooling 1-D thermal and hydraulic flow network model using experimentally validated correlations served as thermal finite element (FE) boundary conditions to predict blade metal temperatures. These predicted temperatures were subsequently utilized in a structural FE model to predict blade life ratings dictated by Haynes 282 creep strength data, having a strong dependence on temperature. The boundary conditions experienced during testing are used in the same workflow and compared to the experimental results, with the goal of validating the analysis methodology and providing insight on the uncertainty in local metal temperature predictions.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2026

Joint Modeling of GD-1 and C-19 as Old Streams

DESI observational data for the GD-1 and C-19 streams are compared to stream simulations in a common evolving multi-halo potential of a Milky Way-like galaxy based on a cosmological simulation. The goal is to find the best match of the stream velocity spread and the density power spectrum stream density to simulations having either CDM or WDM subhalos. The cocoon velocity width integrated over the length of the stream is independent of orbital blurring along the stream and the power spectrum integrates over the width of the stream, sidestepping the geometric details of the streams. Streams develop from star clusters inserted at $\simeq$1 Gyr after the Big Bang and evolved for 13 Gyr to their current orbital positions. Streams in a CDM subhalo population provide the best match to the velocity width, with streams younger than 10 Gyr ruled out as insufficiently hot. The progenitor star cluster masses, which determine the fraction of stars released at late times which comprise the stream core, are found to be $\simeq 8\times 10^4 M_\odot$ for GD-1 and $\simeq 4\times 10^4 M_\odot$ for C-19, although the mass depends on the star cluster half mass radius. Stream heating leads to stream lumpiness which is measurable for the relatively large and clean GD-1 dataset. The stream density power spectrum measured along the length of the DESI GD-1 sample is in good agreement with CDM simulations, with 1.7 to 1.9 times more power than WDM 7 keV and 5.5 keV simulations.

Carlberg, Raymond G. [Toronto U.] (ORCID:000000027↗

DOE OSTI2026

Galaxy Clusters Selected via the Sunyaev-Zel'dovich Effect in 5 year data from the SPT-3G Main Survey

We report a new galaxy cluster catalog, selected using the thermal Sunyaev-Zel'dovich (SZ) effect, from 5 years of observations of the SPT-3G Main field. Drawn from arcminute-resolution data with white noise levels of 3.2, 2.5, and 8.9 $μ$K-arcmin at 95, 150, and 220 GHz, respectively, the sample consists of 8,892 cluster candidates detected above significance $ξ=4$, with an expected purity of $>82\%$ (4,480 at $ξ\ge5$ with purity $>99\%$). Using optical and infrared data we have confirmed 7,190 candidates as clusters. The sample spans a mass range $7.9 \times 10^{13}M_\odot/h_{70}< M_\textrm{500c} < 1.6 \times 10^{15}M_\odot/h_{70}$ with a median mass of $1.65 \times 10^{14}M_\odot/h_{70}$, and a redshift range of $0.0371$ and 271 at $z>1.5$. Compared to previous SZ cluster samples from South Pole Telescope and Atacama Cosmology Telescope data, the SPT-3G sample is highly consistent in mass and redshift but is significantly deeper, with per-cluster detection signal-to-noise 2-4 times higher and a cluster density of 4.5 confirmed clusters/deg$^2$. We cross match with eRASS1 cluster and point source catalogs, finding 1,279 and 1,319 matches, respectively. The SPT and eROSITA cluster mass estimates are in relatively good agreement. We perform a series of validation checks using both internal data splits and comparisons to external samples. These tests show increasing correlated (dusty) emission with redshift, with a $\sim17\times$ larger 220 GHz temperature increment for clusters at $z\sim1.5$ than $z\sim0.25$, but only weak evidence for correlated synchrotron emission. Finally, a number of clusters are flagged as candidate strong gravitational lenses.

Bleem, L. E. [Argonne (main); Chicago U., KICP; Ch↗

DOE OSTI2026

Real-Time Detection of Charge Jumps in Superconducting Qubits with a Convolutional Neural Network

Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge jumps), causing correlated errors that challenge fault-tolerant quantum computing while simultaneously providing a detection signature for quantum sensing applications. Current detection methods operate offline, introducing latency incompatible with in-the-loop qubit control. In this paper, an online detector of charge jumps for superconducting qubits, based on a dilated causal convolutional neural network (DCCNN) designed for in-the-loop deployment on the Quantum Instrumentation Control Kit (QICK) platform, is presented. The network is trained on synthetic Ramsey tomography scans generated from qubit templates measured at the Northwestern Experimental Underground Site (NEXUS) at Fermilab, and translated to FPGA firmware via hls4ml with ap_fixed$\langle 16,6 \rangle$ quantization, reaching a per-inference latency of $6.19 μ$s on the Zynq UltraScale+ RFSoC ZCU216. At this operating point the DCCNN matches the detection efficiency of the established offline $χ^2$ algorithm ($0.843 \pm 0.022$ vs. $0.866 \pm 0.020$ on $|Δq| \in [0.1, 0.5] e$ at matched false-positive rate), while requiring no per-qubit hyperparameter tuning. This shifts charge-jump detection from a post-hoc diagnostic to a control-loop primitive, enabling adaptive protocols that respond to radiation-induced events in situ, with applications to quantum-computing error mitigation and to the use of superconducting qubits as particle detectors.

Gaytan-Villarreal, Daniel [Carnegie Mellon U.]↗

DOE OSTI2022

16.52% Efficiency All-Polymer Solar Cells with High Tolerance of the Photoactive Layer Thickness

All-polymer solar cells (all-PSCs) have drawn growing attention and achieved tremendous progress recently, but their power conversion efficiency (PCE) still lags behind small-molecule-acceptor (SMA)-based PSCs due to the relative difficulty on morphology control of polymer photoactive blends. Here, in this work, low-cost PTQ10 is introduced as a second polymer donor (a third component) into the PM6:PY-IT blend to finely tune the energy-level matching and microscopic morphology of the polymer blend photoactive layer. The addition of PTQ10 decreases the π–π stacking distance, and increases the π–π stacking coherence length and the ordered face-on molecular packing orientation, which improves the charge separation and transport in the photoactive layer. Moreover, the deeper highest occupied molecular orbital energy level of the PTQ10 polymer donor than PM6 leads to higher open-circuit voltage of the ternary all-PSCs. As a result, a PCE of 16.52% is achieved for ternary all-PSCs, which is one of the highest PCEs for all-PSCs. In addition, the ternary devices exhibit a high tolerance of the photoactive layer thickness with high PCEs of 15.27% and 13.91% at photoactive layer thickness of ≈205 and ≈306 nm, respectively, which are the highest PCEs so far for all-PSCs with a thick photoactive layer.

14 SOLAR ENERGY↗

DOE OSTI2022

Using discrete Bayesian networks for diagnosing and isolating cross-level faults in HVAC systems

Fault detection and diagnosis (FDD) technologies are critical to ensure satisfactory building performance, such as reducing energy wastes and negative impacts on occupant comfort and productivity. Existing FDD technologies mainly focus on component-level FDD solutions, which could lead to mis-diagnosis of cross-level faults in heating, ventilating, and air-conditioning (HVAC) systems. Cross-level faults are those faults that occur in one component or subsystem, but cause operational abnormalities in other components or subsystems, and result in a building level performance degradation. How to effectively diagnose the root cause of a cross-level fault is the focus of this study. Here, this paper presents a novel discrete Bayesian Network (DisBN)-based method for diagnosing cross-level faults in an HVAC system commonly used in commercial buildings. A two-level DisBN structure model is developed in this study. The parameters used in the DisBN model are obtained either from expert knowledge or through machine-learning strategies from normal system operation data. Meanwhile, the probability parameters are discretized to incorporate the uncertainties associated with typical expert knowledge. Thus, the developed DisBN method addresses the challenges many other BN based FDD methods face, i.e., the lack of fault data for BN parameter training. The developed DisBN represents causal relationships between a fault and its cross-level system impacts (i.e., fault symptoms or fault indicators) by considering how fault impacts propagate across different levels in an HVAC system. A weather and schedule information-based Pattern Matching (WPM) method is employed to automatically create WPM baseline data sets for each incoming real time snapshot data from the building systems. Consequently, BN inference and real-time diagnostics are achieved by comparing incoming snapshot data and the WPM baseline data set. The proposed method is evaluated using experimental fault data collected in a campus building. Fault diagnosis results demonstrate that the WPM-DisBN method is effective at locating the root causes of cross-level faults in an HVAC system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Proxy-based Bayesian inversion of strain tensor data measured during well tests

Recent instrument developments have made it possible to measure the strain tensor caused by injecting or pumping fluid from aquifers or reservoirs, but the full value of these data is limited because the long runtimes of poroelastic forward models makes it impractical to use many inversion schemes. This limits the interpretation of strain data for managing the recovery of resources or storage of wastes in the subsurface. This paper describes a method of inverting deformation data using a poroelastic numerical simulator so the results can be used to manage reservoirs or aquifers. We developed a workflow designed to reduce the number of simulations sufficiently to make it feasible to use DREAMzs, an advanced Bayesian inversion method that translates the uncertainties from different sources into unbiased posterior parameter distributions and uncertainty envelopes around the field data. Using a KNN proxy model for the poroelastic simulator is key to reducing the overall computations, and the workflow includes a strategy for ensuring the proxy model results converge on the results from the simulator. The workflow is tested using an idealized example that verifies the ability to correctly identify parameters and characterize noise used to perturb the data. Field data from an injection test at an oil reservoir near Tulsa, Oklahoma, are also used to evaluate the efficacy of the workflow with a real dataset. The workflow identified 265 history matching solutions out of 1240 total simulation runs (21% acceptance ratio), where the results were used to characterize posterior parameter distribution and evaluate the prediction uncertainty. Furthermore, this workflow is significant because it enables strain tensor, or other geomechanical measurements to be interpreted to guide decision-making during energy and environmental processes in the subsurface.

42 ENGINEERING↗

DOE OSTI2021

Co-simulation of transactive energy markets: A framework for market testing and evaluation

The proliferation of distributed energy resources (DER)—and the ability to intelligently control these assets—is re-defining the electrical distribution system. As the number of controllable devices rapidly expands, grid operators must determine how to incorporate these assets while delivering reliable, equitable, and affordable electricity. One possible approach is to establish distribution-level electricity markets and allow devices/aggregations of devices to participate in price establishment. While this approach purports some of the same benefits as the highly successful wholesale electricity markets (i.e., open competition, efficient price discovery, reduced communication overhead), this needs to be researched and quantified via an analysis platform that models distribution-level markets at the appropriate fidelity. Specifically, the simultaneous evaluation of market performance, DER performance, DER bidding approaches, and distribution feeder power quality requires modeling that spans multiple technical areas. Co-simulation has emerged as a powerful tool in addressing this type of problem, where outputs depend on a range of underlying areas of expertise and associated models. In this paper we describe a solution, as implemented in the HELICS co-simulation platform, where we include (1) high fidelity house models, (2) intelligent bidding agents, (3) a modular market integration/design, and (4) a distribution feeder model. We then present a case study where we test two different market designs: (1) a pseudo-wholesale double-blind auction, and (2) an asynchronous matching market. In this work, the markets are run under two DER penetration levels and economic results are compared to full retail net energy metering and avoided cost net metering scenarios that bookend current approaches to remuneration of DER participation. We show the potential for transactive markets to provide increased value for most customers relative to net metering (and all customers relative to avoided cost scenarios) while decreasing costs for the utility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Foundations for high-order, conservative cut-cell methods: Stable discretizations on degenerate meshes

Cut-cell methods for unsteady flow problems can greatly simplify the grid generation process and allow for high-fidelity simulations on complex geometries. However, cut-cell methods have been limited to low orders of accuracy. This is driven, largely, by the variety of procedures typically introduced to evaluate derivatives in a stable manner near the highly irregular embedded geometry. Here, a completely new approach, termed TEMO (truncation error matching and optimization), is taken to solve this problem. The approach is based on two simple and intuitive design principles. These principles directly allow for the construction of stable 8th To the best of the authors' knowledge, these are the highest orders ever achieved for a cut-cell discretization by a significant margin. This is done for both explicit and compact finite differences and is accomplished without any geometric transformations or artificial stabilization procedures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Strain-relaxed tetragonal MAPbI 3 results in efficient mesoporous solar cells

In mesoporous organo-halide perovskite solar cells, the coexistence of tetragonal phase and cubic phase in the perovskite layer is found to result in strained crystal structure at the mesoporous TiO 2 (mp-TiO 2 )/perovskite heterointerface. This results in structural defects pinholes, grain boundaries, and interfacial porosity which is detrimental towards photovoltaic performance and device stability. The strain at the interface originates from the lattice mismatch between the mp-TiO 2 nanoparticles (NPs) and perovskite. Here, a transformative approach is demonstrated to realize relaxed and high purity tetragonal phase MAPbI 3 (RP) near the mp-TiO 2 interface region. This approach involves inserting a ~2 nm lattice matched buffer layer of cubic CsPbBr 3 between mp-TiO 2 NPs and MAPbI 3 , which serves as a template for epitaxial growth for top MAPbI 3 . As a result, the solar cell with relaxed MAPbI3 shows a power conversion efficiency (PCE) of 22.12% with significantly enhanced environmental, light, and thermal stability.

14 SOLAR ENERGY↗

DOE OSTI2022

Design of the High Rigidity Spectrometer at FRIB

A High Rigidity Spectrometer (HRS) has been designed for experiments at the Facility for Rare-Isotope Beams (FRIB) at Michigan State University (MSU). The HRS will allow experiments to be performed with the most exotic neutron-rich isotopes at high beam energies (≳100 MeV/u). The HRS consists of an analysis beamline called the High-Transmission Beamline (HTBL) and the spectrometer proper called the Spectrometer Section. Here, the maximum magnetic rigidity of the HRS is 8 Tm, which corresponds to the rigidities at which rare-isotope beams are optimally produced at FRIB. The resolving power, angular acceptance, and momentum acceptance are set to match the anticipated scientific program. An ion-optical design developed for the HRS is described in detail, along with the specifications of the associated magnet and detector systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Experimenting in the cloud: The digital divide's impact on innovation

This paper builds on a recent National Science Foundation working paper that identified a strong association between cloud use and various types of innovation but did not consider whether 1) cloud adoption is a reliable indicator of the innovation orientation of a firm, or 2) cloud adoption enables various types of innovation. We estimate propensity score matching and endogenous treatment effect models to control for innovation orientation, producing evidence to test the second explanation. Here, findings support an enabling effect of the cloud on innovation providing concrete evidence of the adverse impact of the digital divide.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2022

Superconducting Fourfold Fe(Te,Se) Film on Sixfold Magnetic MnTe via Hybrid Symmetry Epitaxy

Epitaxial Fe(Te,Se) thin films have been grown on various substrates but never been grown on magnetic layers. In this work, we report the epitaxial growth of fourfold Fe(Te,Se) film on a sixfold antiferromagnetic insulator, MnTe. The Fe(Te,Se)/MnTe heterostructure shows a clear superconducting transition at around 11 K, and the critical magnetic field measurement suggests the origin of the superconductivity to be bulk-like. Structural characterizations suggest that the uniaxial lattice match between Fe(Te,Se) and MnTe allows a hybrid symmetry epitaxy mode, which was recently discovered between Fe(Te,Se) and Bi 2 Te 3 . Furthermore, the Te/Fe flux ratio during deposition of the Fe(Te,Se) layer is found to be critical for its superconductivity. Now that superconducting Fe(Te,Se) can be grown on two related hexagonal platforms, Bi 2 Te 3 and MnTe, this result opens a new possibility of combining topological superconductivity of Fe(Te,Se) with the rich physics in the intrinsic magnetic topological materials (MnTe) n (Bi 2 Te 3 ) m family.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗