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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

AOI [1] Advanced Manufacturing of Ceramic Anchors with Embedded Sensors for Process and Health Monitoring of Coal Boilers

Researchers at West Virginia University (WVU) developed methods to fabricate and test ceramic anchors with an embedded sensor technology for monitoring the health and processing conditions within pulverized coal (PC) and fluidized-bed combustion (FBC) boiler systems. The technology included the development of advanced manufacturing processes for 2D/3D printing electroceramic (conductive ceramic) sensor designs within the ceramic anchor microstructure during the manufacturing process. This advanced manufacturing process would allow for the precise control of local microstructure and composition in order to engineer layer-by-layer any protective and electrically active materials within the refractory anchor. This 3D printing technology would permit the rapid and controlled design of the refractory microstructure and embedded sensor design throughout the volume of the ceramic anchor. The work also included a method to interconnect the sensors to boiler shell through the anchor clamp, where the sensor signals will be processed by low-power electronics and transmitted wirelessly to a central processing hub. The end-goal of the program was to produce a ceramic anchor sensor system which would be ready for implementation within a coal boiler, and/or other similar refractory liner systems (such as that in the glass and metal manufacturing areas). The project objectives were to: 1) Define the chemical and microstructural stability, in addition to the electrical properties, of oxide and non-oxide ceramic composites to be embedded within the ceramic anchor compositions that may operate up to 1400ºC; 2) Develop and implement the 2D/3D printing technology to pattern and control the microstructure of the ceramic anchor and embedded sensor circuits; 3) Develop an interconnect technology which will permit easy installation of the ceramic anchors and signal collection at the boiler shell; 4) Develop low power analog electronics and wireless communication hardware to efficiently collect the sensor signal at each processing unit and transmit data to a central hub for data analysis; 5) Demonstrate the smart ceramic anchor system for temperature and liner fracture within a high-temperature processing unit, such as a boiler furnace or glass melting furnace floor/wall liner.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Force-triggered, Bio-based, Sealants for Prefabricated Building Components: Towards Improved Efficiency, Performance and Sustainability

The prefabricated building construction industry has made extensive progress in expediting the manufacture of prefabricated components at offsite plants. However, this progress has not translated to the assembly of the prefabricated components at the construction site. Case in point, sealing the joints between components to prevent air leaks requires the manual application of tape, caulk, or spray foam at the jobsite, and performance is highly dependent on the skills of the installer. To reduce assembly time and improve assembly quality of prefabricated components, we developed a sealant that can be installed at the plant and triggered at the jobsite. Additionally, we used this opportunity to lower the use of fossil fuel derived feedstocks and introduced bio-based alternatives to decrease the embodied carbon of the new sealant. We evaluated a series of force-triggered, bio-based, high strength, and fast curing sealants, consisting of a one-part heterogeneous system. These sealants are derived from formulations with ≥80% of biogenic carbon, consisting of a cardanol derived diepoxy that is microencapsulated in a polymer shell and embedded in a cardanol derived amine curing agent. The microcapsule shell allows separation of the reactive species in the one part sealant allowing shelf stability to an otherwise fast curing system. When the microcapsules are broken and activated by force, the highly reactive species mix and cure, exhibiting peel strengths up to 143 ppi. The shelf stability of these sealants and the on-demand triggering of the curing reactions enable installation on prefabricated components and storage prior to delivery and assembly at a jobsite, which could result in consistent sealant application with lower installation time than tapes and caulks at the construction site.

Cortes Guzman, Karen [ORNL] (ORCID:000000028793468↗
DOE OSTI2025

Factors controlling injection-induced rupture of intersecting faults during geological sequestration of CO 2

This study addresses coupled multiphase fluid flow and geomechanics effects on potential fault activation associated with subsurface CO 2 injection around intersecting faults. An enhanced fault-representation model is used to capture geomechanical responses of two intersecting faults with finite length during CO 2 injection. The faults are embedded in a strike-slip stress regime of a caprock-reservoir-basement system with the faults represented by zero-thickness interfaces with adjacent finite-thickness damage zones. A sensitivity analysis is conducted to study the effect of fault permeability, slip-weakening behavior, well location relative to the orientation of faults, and well placement (the number and location of injection wells). Five metrics (pressure, CO 2 plume, shear state on the fault, as well as shear displacement and stress path at selected fault monitoring points) are selected to assess CO 2 migration and reactivation of intersecting faults. The results show that induced ruptures are favored by low permeability faults due to high pressure buildup and by slip-weakening behavior resulting from fault strength reduction. The location of one injection well relative to fault orientation determines the magnitude of changes in effective normal stress and shear stress, affecting the location of induced ruptures. Well placement (two injection wells used in the paper) dominates pressure diffusion around the intersection and tips of faults. This redistributes changes in effective normal stress caused by each injection well, influencing the spatial distribution of ruptures along faults. A larger injection volume induces far-field ruptures that are controlled by stress transfer within the injection layer. The findings presented here can provide valuable insights into engineering operations for a long-term, safe, and reliable geologic CO 2 storage.

Fault permeability↗
DOE OSTI2026

Exploring the Feasibility of Modern Fiber Optics in Offshore Mooring Condition Monitoring

This project explored the feasibility of using fiber-optic sensing technologies for condition monitoring of offshore synthetic mooring lines used in marine renewable energy systems. The work focused on evaluating optical fiber materials, interrogation methods, and rope-embedment approaches capable of enabling distributed strain or elongation measurements along mooring lines.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Force-triggered, Bio-based, Sealants for Prefabricated Building Components: Towards Improved Efficiency, Performance and Sustainability

The prefabricated building construction industry has made extensive progress in expediting the manufacture of prefabricated components at offsite plants. However, this progress has not translated to the assembly of the prefabricated components at the construction site. Case in point, sealing the joints between components to prevent air leaks requires the manual application of tape, caulk, or spray foam at the jobsite, and performance is highly dependent on the skills of the installer. To reduce assembly time and improve the airtightness and waterproofness of prefabricated components, we developed a sealant that can be installed at the plant and have its curing reaction triggered at the jobsite. Additionally, we used this opportunity to explore the use of bio-based feedstocks that are abundant and not used for food. We evaluated a series of force-triggered, bio-based, high strength, and fast curing sealants, consisting of a one-part heterogeneous system. These sealants are derived from formulations with ≥80% of bio-based components, consisting of a cardanol derived diepoxy that is microencapsulated in a polymer shell and embedded in a cardanol derived amine curing agent. The microcapsule shell allows separation of the reactive species in the one-part sealant allowing a fast-curing system to remain unreacted until the right trigger is applied. When the microcapsules are activated and broken by force, the highly reactive species mix and cure, exhibiting peel strengths up to 143 ppi. The open-air shelf stability of the sealant complexes was demonstrated by peel strength values of ~16 ppi when triggering the curing reaction even after being exposed for 8 months to open air and humidity. The successful on-demand triggering of curing reactions and the shelf stability provide efficacy of these force-triggered sealants for installation on prefabricated components, storage for months prior to delivery, and assembly at the jobsite. These force-triggered bio-based sealants for prefabricated buildings could result in lower installation time and cost as well as better performance than tapes and caulks at the jobsite.

Cortes Guzman, Karen [ORNL] (ORCID:000000028793468↗
DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗
DOE OSTI2024

Experimentation on Finned-Tube Microchannel Heat Exchanger Incorporating Phase Change Material and R-410A

Integrating latent heat thermal energy storage, particularly phase change materials (PCM), in building heating, ventilation, air conditioning, and refrigeration (HVAC&R) systems, offers substantial benefits for peak load shifting and energy efficiency. While numerous studies explore PCM-embedded heat exchangers (PCM-HX) using single-phase heat transfer fluids, there needs to be more investigation regarding PCM-HX utilizing two-phase refrigerant flow. This gap is even more pronounced for microchannel heat exchanger (MCHX) configurations. In this study, an MCHX-based PCM-HX was built and tested to analyze and evaluate the performance of a PCM-HX operating with a two-phase refrigerant as the working fluid. A commercially available MCHX condenser unit was embedded with 2.6 kg of RT35 PCM and tested using R-410A as the working fluid, using an in-house test loop to control the refrigerant inlet conditions precisely. Thin and minimally invasive T-type thermocouples traced the temperature evolution along MCHX channels and tube banks. Additional larger T-type thermocouple probes at the refrigerant inlet and outlet measured the average power of the PCM-HX during condensing tests, ranging from 0.7 kW to 1.6 kW based on mass flow rates varying from 3.5 g/s to 8 g/s. This experimental study on MCHX-based PCM-HX with a two-phase refrigerant has the potential to offer practical design guidelines for the direct integration of PCM-TES in HVAC&R systems without the use of a secondary loop, while caution is advised to avoid a substantial increase in the refrigerant charge amount.

42 ENGINEERING↗
DOE OSTI2025

Dispatch Manager for NEML2 Constitutive Model Calculations Embedded in MOOSE

This report describes the extended capabilities of the NEML2 constitutive modeling library, including a flexible and efficient work dispatching system designed to leverage both CPU and GPU resources. This enhancement addresses one of the primary computational challenges in large-scale simulations: the ability to distribute and execute batches of material model evaluations across heterogeneous computing devices. The new dispatch system introduces a modular set of dispatcher and scheduler classes that coordinate the flow of data and execution between devices. The dispatcher is responsible for efficiently packaging work, managing device-specific memory operations, and synchronizing results. This modularity allows for extensibility, making it straightforward to integrate additional computing backends in the future. From an implementation standpoint, the dispatcher system interfaces seamlessly with NEML2's existing models. They handle device-aware tensor operations, optimize memory transfers, and support asynchronous execution when applicable. This design ensures that batches of material points can be evaluated concurrently, substantially improving throughput compared to previous single-device or serial implementations. These improvements not only enhance the raw performance of NEML2 but also improve its usability in multiscale and high-fidelity simulations, where the simultaneous evaluation of large material point batches is critical. Benchmarks included in the report demonstrate the system’s scalability, highlighting its effectiveness when leveraging modern GPU architectures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Efficient Simulation of Cascading Outages Using an Energy Function-Embedded Quasi-Steady-State Model

Here, this paper proposed an energy function-embedded quasi-steady-state model for efficient simulation of cascading outages on a power grid while addressing transient stability concerns. Compared to quasi-steady-state models, the proposed model incorporates short-term dynamic simulation and an energy function method to efficiently evaluate the transient stability of a power grid together with outage propagation without transient stability simulation. Cascading outage simulation using the proposed model conducts three steps for each disturbance such as a line outage. First, it performs time-domain simulation for a short term to obtain a post-disturbance trajectory. Second, along the trajectory, the system state with the local maximum potential energy is found and used as the initial point to search for a relevant unstable equilibrium by Newton's method. Third, the transient energy margin is estimated based on this unstable equilibrium to predict an out-of-step condition with generators. The proposed energy function-embedded quasi-steady-state model is tested in terms of its accuracy and time performance on an NPCC 140-bus power system and compared to a quasi-steady-state model embedding transient stability simulation.

Guo, Zhenping [Univ. of Tennessee, Knoxville, TN (↗
DOE OSTI2025

Novel artificial neural network model for instantaneous power losses and operational efficiency mapping of MW-scale vanadium redox flow battery for improved technoeconomic analysis

A novel data-driven, machine-learning-based method for modeling the instantaneous power losses of a distribution-sited 2 MW/8MWh vanadium redox flow battery (VRFB), a grid-scale electrochemical storage technology, is introduced and compared against benchmark empirical modeling approaches, including symmetric and asymmetric models, as well as a recent convex hull modeling approach. The novel loss modeling method introduces several advantages over the benchmark models and over simplistic efficiency estimates, the most significant of which is that the model can accurately reflect the stepwise and non-linear parasitic losses associated with the duty cycles of mechanical auxiliary systems like pump motor drives and blower fans. Residuals of the models are compared; the proposed data driven model features significantly improved accuracy over the benchmark models. The model's coefficient of determination is also improved relative to that of the benchmark models. Furthermore, a novel method for visualization of operational efficiency of the grid-scale storage technology is introduced. To demonstrate the benefits of the novel data-driven method for modeling the VRFB, the benchmark models and the proposed models are embedded into an Open DSS distribution network model to study two applications of the grid-scale electrical storage system: load leveling for grid support and energy arbitrage. This article demonstrates that the accuracy of the instantaneous power loss model significantly impacts the understanding of the state of charge of the VRFB. In turn, the accuracy of the efficiency modeling of the VRFB impacts the understanding of the potential economic value and technical benefits to the distribution network operators. In conclusion, the presented power loss modeling approach is, therefore, highly relevant for utility-stakeholders, battery asset owners, system engineers, system designers, and financial planners interested in evaluating or optimizing the operation of grid-scale VRFBs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Understanding Event Trajectories Across Massive Temporal Datasets with Word Embeddings and Visualization

In collaboration with researchers from Virginia Tech, Savannah River National Laboratory has continued development of a natural language processing pipeline to identify and extract events of interest from massive open data sources in the domain of worldwide state-sponsored civil nuclear energy. The foundation of the pipeline is built on compass aligned temporal word embedding models, whereby contextual shifts are automatically identified by comparing keyword embedding vectors across successive time windows. Within the approach, a contextual shift indicates the occurrence of a potential event of interest. However, in such a broad topical domain that captures events at a global scale, across various life cycle stages, and across numerous different technology types, a user that is monitoring events may have broad interests in capturing many different event types with varying degrees of signal. As such, the quantity of information that may be returned from an automated event extraction pipeline can be substantial, requiring manual effort to sift through the information to identify any relevant bits of information. Therefore, a more streamlined workflow that aids in directing a user toward specific information at different points in time is necessary. The workflow presented here has been developed with this concept in mind, built on top of the initial prototype event extraction pipeline, whereby a user can analyze temporal text-based data sources at multiple different contextual levels to isolate key points in time and key subdomains captured within a data corpus. Using multiple corpuses that consist of approximately 7 million Tweets and 7 million news articles, the team has extended compass aligned temporal word embedding models to establish an interconnected and hierarchical structure that relates known key words of interest to documents, local topics (i.e., within a time window), and global topics across the corpuses. All of this information is packaged into a visual analytics system that is linked to the information extraction pipeline and enables a user to identify contextual information that describes the evolution of a high dimensional embedding space across time to isolate changes of interest and explore associated events. This report demonstrates the use of these analytics and a means to fuse information across multiple datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Towards excitations and dynamical quantities in correlated lattices with density matrix embedding theory

Density matrix embedding theory (DMET) provides a framework to describe ground-state expectation values in strongly correlated systems, but its extension to dynamical quantities is still an open problem. We show one route to obtaining excitations and dynamical spectral functions by using the techniques of DMET to approximate the matrix elements that arise in a single-mode inspired excitation ansatz. We demonstrate this approach in the one-dimensional Hubbard model, comparing the neutral excitations, single-particle density of states, charge, and spin dynamical structure factors to benchmarks from the Bethe ansatz and density matrix renormalization group. Finally, our work highlights the potential of these ideas in building computationally efficient approaches for dynamical quantities.

1-dimensional systems↗
DOE OSTI2024

Copper and bismuth-based sorbent characterization in simulated iodine off-gas streams

The effective capture of volatile radioiodine, a fission product present in used nuclear fuel (UNF), is of paramount importance for development of used fuel reprocessing schemes to prevent release of radioiodine during unit operations and to meet regulatory standards for air emissions. A well-studied method for iodine capture in off-gas streams is the use of silver-functionalized zeolite phases (AgZ), which exploit chemisorption of I to Ag. Advances into other Ag-functionalized materials, including aerogels and metal organic frameworks (MOFs), are underway [1]. Additional metals with the capability to chemisorb iodine, including Cu, Bi, and Sn, [1] are being evaluated as alternatives to Ag for potential applicability to iodine management in off-gas systems. The design of novel functionalized sorbents with Cu and Bi, including composites with metal particles embedded in PAN substrates [2] and composites with metal sulfides embedded in PAN [3], is an ongoing area of study for improved iodine capture. Previously reported work on novel PAN-based metal sorbents has provided the synthesis, characterization, and iodine capture efficiency of this new class of sorbent. Specifically, the metal sulfide PAN composites are found to be easy to produce and reproduce, as well as having a high iodine loading potential under static conditions [3]. Due to the favorable testing previously performed with metal sulfide PAN composites, further testing into the performance of these composites under gas streams containing I2(g) in combination with NO2(g) and H2O(g) is needed. Humid streams of NO2(g) may arise from dissolver off-gas streams, when used fuel is dissolved in HNO3(aq) [4]. NO2(g) has been found to reduce AgZ sorption capacity for I because of oxidation of Ag, the chemisorbing agent, to Ag2O [5]. It follows that performance evaluation of novel sorbents under highly oxidizing conditions such as NO2(g) streams is critical. Therefore, the objective of this study is to determine the effect of flowing NO2(g) and H2O(g) streams on iodine sorption capacity and sorbent performance. This work utilizes custom-built gas handling capabilities for sorbent exposure along with solid-state characterization techniques to assess the physical and chemical properties of sorbents before and after exposure.

copper, bismuth, iodine capture, iodine sorbent, p↗
DOE OSTI2025

U-Surf: a global 1 km spatially continuous urban surface property dataset for kilometer-scale urban-resolving Earth system modeling

High-resolution urban climate modeling has faced substantial challenges due to the absence of a globally consistent, spatially continuous, and accurate dataset to represent the spatial heterogeneity of urban surfaces and their biophysical properties. This deficiency has long obstructed the development of urban-resolving Earth system models (ESMs) and ultra-high-resolution urban climate modeling, over large domains. Here, we present U-Surf, a first-of-its-kind 1 km resolution present-day (circa 2020) global continuous urban surface parameter dataset. Using the urban canopy model (UCM) in the Community Earth System Model as a base model for satisfying dataset requirements, U-Surf leverages the latest advances in remote sensing, machine learning, and cloud computing to provide the most relevant urban surface biophysical parameters, including radiative, morphological, and thermal properties, for UCMs at the facet and canopy level. Generated using a systematically unified workflow, U-Surf ensures internal consistency among key parameters, making it the first globally coherent urban canopy surface dataset. U-Surf significantly improves the representation of the urban land heterogeneity both within and across cities globally; provides essential, high-fidelity surface biophysical constraints to urban-resolving ESMs; enables detailed city-to-city comparisons across the globe; and supports next-generation kilometer-resolution Earth system modeling across scales. U-Surf parameters can be easily converted or adapted to various types of UCMs, such as those embedded in weather and regional climate models, as well as air quality models. The fundamental urban surface constraints provided by U-Surf can also be used as features for machine learning models and can have other broad-scale applications for socioeconomic, public health, and urban planning contexts. We expect U-Surf to advance the research frontier of urban system science, climate-sensitive urban design, and coupled human–Earth systems in the future. The dataset is publicly available at https://doi.org/10.5281/zenodo.11247598 (Cheng et al., 2024).

Cheng, Yifan [Univ. of Illinois at Urbana-Champaig↗
DOE OSTI2024

Elucidating and contrasting the mechanisms for Mg and Ca sulfate ion-pair formation with multi-level embedded quantum mechanics/molecular dynamics simulations

Here, solutions and minerals containing sulfate (SO 4 2- ), and Ca 2+ and Mg 2+ cations, are ubiquitous throughout the lithosphere and are significant components of seawater, thus presenting a prototypical system for the study of strong electrolytes and crystal nucleation mechanisms. However, despite their relative abundance, key questions remain unanswered about the most fundamental atomic-level steps of their mineralization pathways and aqueous dynamics. Here, we carry out enhanced sampling multi-level molecular dynamics (MD) embedded correlated wavefunction theory simulations to elucidate ion-pairing mechanisms for Mg–SO 4 and Ca–SO 4 in concentrated aqueous solution, accurately capturing effects arising from both structural dynamics and electron exchange–correlation. We predict contact-ion-pair formation to be barrierless and highly exoergic for Ca–SO 4 , in agreement with its minimal solubility, whereas for Mg–SO 4 , solvent-shared and contact ion pairs have similar free energies, qualitatively consistent with its higher solubility. Finally, we demonstrate that brief high-temperature pre-equilibration may be utilized to accelerate convergence of free energies in blue-moon-ensemble enhanced-sampling MD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

REFRACTORY COMPACT HEAT EXCHANGERS WITH EMBEDDED SENSORS ENABLED BY HYBRID ADVANCED SINTERING AND ADDITIVE APPROACH

Structural health monitoring (SHM) of compact heat exchangers (CHXs) operating in extreme environments is essential for ensuring system reliability, safety, and longevity. This study presents the development of high-temperature sensors fabricated via aerosol jet printing (AJP) using platinum ink, selected for its exceptional thermal stability, oxidation resistance, and electrical conductivity. AJP enables precise deposition of fine-feature sensor patterns onto complex geometries, making it well-suited for integration within CHX architectures. To enhance sensor durability, an alumina-based ceramic protective layer was printed over the platinum sensing elements. The sensors demonstrated stable, repeatable performance up to 900?°C during extended thermal cycling. A custom test setup was developed to evaluate sensor accuracy and robustness under steady-state and transient conditions. Substrate screening identified HG-1 ceramic-coated stainless steel as the most effective platform, offering strong adhesion and low resistance. Furthermore, electric field-assisted sintering (EFAS) was employed to embed the sensors into stainless steel 316L matrices without degrading their functionality. Post-embedding electrical tests confirmed sensor integrity, and initial characterization suggests strong potential for in-situ monitoring. This work provides a scalable strategy for integrating high-performance temperature sensors directly into refractory components, advancing embedded SHM technologies for harsh operating environments.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Experimental Investigation of Steel-Borne Acoustic Pulses for Fault Pinpointing in Pipe-Type Cable Systems: A Scaled-Down Model Approach

Pipe-type cable systems, including high-pressure fluid-filled (HPFF) and high-pressure gas-filled cables, are widely used for underground high-voltage transmission. These systems consist of insulated conductor cables within steel pipes, filled with pressurized fluids or gases for insulation and cooling. Despite their reliability, faults can occur due to insulation degradation, thermal expansion, and environmental factors. As many circuits exceed their 40-year design life, efficient fault localization becomes crucial. Fault location involves prelocation and pinpointing. Therefore, a novel pinpointing approach for pipe-type cable systems is proposed, utilizing accelerometers mounted on a steel pipe to capture fault-induced acoustic signals and employing the time difference of arrival method to accurately pinpoint the location of the fault. The experimental investigations utilized a scaled-down HPFF pipe-type cable system setup, featuring a carbon steel pipe, high-frequency accelerometers, and both mechanical and capacitive discharge methods for generating acoustic pulses. The tests evaluated the propagation velocity, attenuation, and pinpointing accuracy with the pipe in various embedment conditions. The experimental results demonstrated accurate fault pinpointing in the centimeter range, even when the pipe was fully embedded, with the acoustic pulse velocities aligning closely with the theoretical values. These experimental investigation findings highlight the potential of this novel acoustic pinpointing technique to improve fault localization in underground systems, enhance grid reliability, and reduce outage duration. Further research is recommended to validate this approach in full-scale systems.

Moutassem, Zaki↗
DOE OSTI2026

Radiative Electronic Bound States in the Continuum from Defects in Semiconductors

Continuum-buried defect states in semiconductors are generally expected to be optically inactive because of their strong coupling to continuum bands. Here, we show that such defects can instead host radiative electronic bound states in the continuum (BICs) using the silicon G center as a prototypical example. Hybrid functional first-principles calculations with a Hubbard U correction reveal that a localized defect state, initially buried below the valence band maximum (VBM) in the ground state, undergoes exchange-driven energy-level reordering under optical excitation and shifts above the VBM. This exchange-induced transition suppresses nonradiative decay and enables a robust radiative emission. By computing temperature-dependent nonradiative lifetimes and comparing them to experimental photoluminescence (PL) lifetimes, we quantitatively reproduce the observed temperature dependence of the emission. These results uncover a stabilization mechanism for continuum-embedded defect states and establish electronic BICs as a general paradigm for designing defect-based optical systems, including quantum emitters and qubits.

Hong, SeongYun↗