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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Staged, Pressurized Oxy-Combustion Technology: Status and Application to Boiler Retrofits to Yield Carbon-Negative Power via Biomass

Recognizing the benefits of pressurization and fuel staging on the efficiency of oxy-combustion, the staged, pressurized oxy-combustion (SPOC) process was introduced in 2012. The combination of fuel staging and pressurized oxy-combustion results in a more compact plant, a higher plant efficiency and reduced costs for pollutant and greenhouse gas removal compared with plants equipped with conventional carbon capture. This approach to power generation enables a modular boiler design and optimizes the plant for flexible operation, which is essential to meet the demands of the modern grid when it contains intermittent power sources. Originally designed to burn coal, the SPOC process is well-suited for biomass because the combustion of biomass leads to a high moisture content in the flue gas and the SPOC process is able to recover the latent heat of this moisture, enhancing system performance over that of traditional biomass combustion at atmospheric pressure. The present work is focused on evaluating the potential for utilizing the SPOC process in retrofit applications wherein the boilers of an existing plant are replaced with the SPOC process, and woody biomass is used as the fuel to yield carbon-negative power. Two applications are considered: power generation and cogeneration (heat and power). Modeling these systems in Aspen Plus demonstrates that the SPOC process surpasses the performance of baseline plants with post-combustion capture (PCC) for both power generation and cogeneration. Specifically, compared to a PCC equipped plant, the SPOC power plant has 33% higher efficiency, and the SPOC cogeneration plant reaches 42% higher net energy. Experimentally, the existing SPOC facility was fired for the first time with 100% biomass and after minor improvements were made to the feeding system, the facility demonstrated excellent performance during startup, steady-state operation and turndown.

Carbon capture and storage↗
DOE OSTI2025

Storms Are an Important Driver of Change in Tropical Forests

Tropical forest dynamics and composition have changed over recent decades, but the proximate drivers of these changes remain unclear. Investigations into these trends have focused on increasing drought stress, CO 2 , temperature, and fires, whereas convective storms are generally overlooked. We argue that existing literature provides clear support for the importance of storms as drivers of forest change. We reanalyze the largest plot-based study of tropical forest carbon dynamics to show that lightning frequency—an indicator of storm activity—strongly predicts forest carbon storage and residence time, and its inclusion improves model fit and weakens evidence for the effects of high temperatures. Convective storm activity has increased 5%–25% per decade over the past half century. Extrapolating from historic trends, we estimate that storms likely contribute ca. 50% of the reported increases in biomass mortality across Amazonia, with all realistic combinations of assumptions indicating a possible range of 12%–118%. Spatial variation in storm activity shows weak relationships with drought, demonstrating that forests can experience high drought stress, high storm activity, or both. Accordingly, we hypothesise that convective storms are among the most important drivers of tropical forest change, and as such, they require significant research investment to avoid misguiding science, policy, and management.

biomass carbon↗
DOE OSTI2026

WHONDRS Surface Water and Sediment Geochemistry and Organic Matter Characterization Data from Streams across HJ Andrews Experimental Forest, Oregon (v2)

This dataset supports a broader study developing conceptual models for river corridor critical zone processes across spatial scales and was generated in collaboration with the HJ Andrews River Corridor Critical Zone Workshop in 2025. The dataset provides surface water geochemistry (dissolved organic carbon, total dissolved nitrogen) from 48 sites across the HJ Andrews Experimental Forest, Oregon (https://andrewsforest.oregonstate.edu). Some of the sites have been impacted by the Holiday Farm Fire and the Lookout Fire in 2020 and 2023, respectively. Related data were collected as part of the workshop and will be published separately in collaboration with other workshop attendees and available at http://www.hydroshare.org/resource/b274c4a234bf4b12b7cb8a54a696c629. Related genomic data can be found on the National Center for Biotechnology Information (NCBI) under BioProject PRJNA1503030 (see critical details section below for more information). Additional related data collected in 2016 from a similar effort can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3377027 and http://www.hydroshare.org/resource/ea6c0832885a46c3939e7bb22e48e754 and are described within https://doi.org/10.5194/essd-11-1-2019 (Ward et al., 2019). This data package was originally published in March 2026. It was updated in August 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos, (2) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data, (3) a data checks report, (4) a folder of sample data, (5) file-level metadata, (6) data dictionary, (7) field metadata, (8) readme, (9) international generic sample number (IGSN) mapping file; and (10) field protocol. The sample data subfolder contains surface water and sediment (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages, (2) total dissolved nitrogen data and averages, (3) methods codes, (4) FTICR-MS methods; and (5) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the CoreMS processed data and seven subfolders, thee containing .xml files for each sample type (sediment, surface water and blank samples), three containing the sediment CoreMS output files for each sample type (sediment, surface water and blank samples), and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .Rmd, .py, .cal, .json, .jpg, or .jpeg.

Biogeochemistry↗
DOE OSTI2025

Rapid characterization and failure analysis of 6276 rooftop-harvested photovoltaic connectors

Photovoltaic (PV) connectors, which link modules in series and connect PV strings in parallel, have increasingly been recognized as a primary contributor to PV system failures and a source of numerous fire incidents. However, publicly available data on the rates and types of connector failures are scarce, primarily due to the proprietary nature of the information and the need for comprehensive analysis. This study represents the first large-scale investigation of harvested PV connectors, drawing from a dataset of 6276 connectors from residential rooftop solar systems across the United States. The outcome of this work is twofold: 1) we have established a rapid characterization method for large populations of harvested connectors, incorporating visual inspection, resistance measurements, and X-ray imaging; and 2) the analysis made possible by our rapid-processing method has revealed, for a population of connector models provided by a single rooftop installer, failure statistics and insights for various connector makes and models, installation practices, operating currents, and internal component displacements. This research identifies common failure modes that could be considered in future connector designs standards, and operations and maintenance practices, to ultimately improve the reliability of this vital component of PV infrastructure.

MC4↗
DOE OSTI2025

Burning conditions and transportation pathways determine biomass-burning aerosol properties in the Ascension Island marine boundary layer

Abstract. African biomass-burning aerosol (BBA) in the southeast Atlantic Ocean (SEA) marine boundary layer (MBL) is an important contributor to Earth's radiation budget, yet its representation remains poorly constrained in regional and global climate models. Data from the Layered Atlantic Smoke Interactions with Clouds (LASIC) field campaign on Ascension Island (7.95° S, 14.36° W) provide insight into how burning conditions, fuel type, transport pathways, and atmospheric processing affect the chemical, microphysical, and optical properties of BBA between June and September 2017. A total of 10 individual plume events characterize the seasonal evolution of the BBA properties. Early-season inefficient fires, determined by low refractory black carbon to above-background carbon monoxide mixing ratios (rBC : ΔCO), led to enhanced concentrations of organic- and sulfate-rich aerosols. Mid-season efficient fires, determined by higher rBC : ΔCO values, led to rBC-enriched BBA. A mix of efficient and inefficient fires later in the season resulted in conflicting BBA properties. Prolonged transport (∼ 10 d) through the MBL and lower free troposphere (FT) facilitated chemical and aqueous-phase processing, which led to a reduction in organic aerosol mass concentrations. This resulted in lower organic aerosol (OA) to rBC (OA : rBC) mass ratios (2–5) in the MBL compared to higher values (5–15) in the nearby FT. These atmospheric and cloud oxidation processes yield more light-absorbing BBA and explain the notably low single-scattering albedo at 530 nm (SSA530) values (< 0.80) observed in the MBL. This study establishes a robust correlation between SSA530 and OA : rBC across the MBL and FT, underscoring the dependency of optical properties on chemical composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Impact of a Bluff Body on a Pressurized Oxy-fuel Flame

Designing an effective burner is vital for the development of pressurized oxy-fuel combustion technologies. In the present work, turbulent jet diffusion burners are adopted for a pressurized oxy-combustor, with a bluff-body employed to create a recirculation zone, thereby stabilizing the flame in such a combustor. The objective of this numerical study is to perform a systematic analysis of the characteristics of such a pressurized non-premixed flame. Specifically, a 15-bar pressurized oxy-fuel combustor of power 100 kWth is modeled by means of the Ansys FLUENT commercial platform, using the Reynolds-averaged Navier-Stokes (RANS) approach. The present work focuses on identifying the aerothermodynamic features of the pressurized oxy-fuel burner with a disk-shape bluff-body. It is shown that the fuel-to-oxidizer stream momentum ratio has a great impact on the temperature profile of the down-fired, co-axial, pressurized oxy-coal, diffusion flame. A parametric study of the blockage ratio of the burner identifies an optimal range for this pressurized burner.

Li, Lei↗
DOE OSTI2025

Cable/Antenna Bounds Connecting Field Levels To Personnel Safety And Electronic Upset Thresholds

We use bounding models to estimate the power delivered to interior ordnance as well as the pin level voltages along a cable at interior electronic components. The procedures underlying these estimates are described in some detail. Conservation of steady-state power in a linear passive system underpins the power estimate, whereas, losses and quality factor limits underpin the limits on voltage transformations. The final levels are compared to no-fire threshold power and to minimum upset voltage levels in an example using a canonical slot aperture and cavity to estimate interior fields.

42 ENGINEERING↗
DOE OSTI2025

Electric Vehicle Charging Data Falsification Attacks Utilizing Behavioral Models

A charging station (CS) and its associated electric vehicle supply equipment (EVSE) and charging electric vehicle (EV) interactions are potential targets for data falsification attacks since CSs are typically unmanned public facilities that are connected to the internet and EVs incorporate the vulnerable CAN bus network, which are both susceptible to remote attacks. The research question being addressed is how is the EV owner and CS negatively affected by CAN bus EV battery current sensor and battery temperature sensor data falsification attacks. Negative effects include economic losses from reduced life span of the battery, battery thermal runaway and fire (and potential loss of surrounding structure), and reduced utilization of the CS due to delayed departure time (longer charging times).

25 ENERGY STORAGE↗
DOE OSTI2024

Decarbonization of heat pump dual fuel systems using a practical model predictive control: Field demonstration in a small commercial building

In the transition from fossil fuel to electrified heating, a concerning trend is emerging in certain regions of the US. Owners of buildings with gas-based systems leave them in place after adding heat pumps (HPs). Existing control solutions for these hybrid (dual fuel) systems are rudimentary and fall short of realizing the full carbon reduction potential of these systems. Model predictive control (MPC) is often regarded as the benchmark for achieving optimal control in integrated systems. However, in the case of small-medium commercial buildings (SMCBs), the control and communication infrastructure required to facilitate the implementation of such advanced controls is often lacking. This paper presents a field implementation of easy-to-deploy MPC for a dual fuel heating system consisting of HPs and a gas-fired furnace (GF) for SMCBs. The control system is deployed on an open-source middleware platform and utilizes low-cost sensor devices to be used for real SMCBs without major retrofits. Here, we demonstrated this MPC in a real office building with 5 HPs and 1 GF for 2 months. The test results showed that MPC reduced 27% of cost while completely eliminating GF usage by shifting 23% of the thermal load from occupied-peak time to non-occupied-non-peak times.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

NEXT Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR Phase I & II)

The Ohio State University’s ARPA-E NEXTCAR project was a multi-phase, multi-year research, development, and demonstration program focused on improving the energy efficiency of connected and automated vehicles (CAVs). The team developed and validated advanced vehicle motion and powertrain control algorithms that coordinate propulsion and automation systems to optimize energy use. Key technologies included Dynamic Skip Fire engine control, predictive eco-driving functions such as Eco-Approach and Departure (Eco-AND) and Eco-Adaptive Cruise Control (Eco-ACC), and powertrain-agnostic optimization frameworks for hybrid, plug-in hybrid, and battery electric vehicles. The project successfully demonstrated up to 30% energy-efficiency improvement during real-world testing at the Transportation Research Center and the American Center for Mobility. The outcomes provide a foundation for scalable, cost-effective deployment of energy-optimized CAV technologies across the automotive industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2022-2023

Timelapse camera images from Council Mile Marker (MM) 71, Kougarok MM 64, Kougarok Fire Complex (KFC), and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from July 2022 to July 2023. Eight Wingscape Timelapse Pro cameras, and thirty-one Power-interval Camera Automation Modules (PiCAMs) designed by Brookhaven National Laboratory?s Terrestrial Ecosystem Science and Technology (TEST) group were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from Wingscape cameras were recorded at hourly intervals from 11 AM to 2 PM, and images from PiCAMs were recorded at 5 hourly intervals from 12 AM to 8 PM, continuously for 12 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Status of SPCA-ANL Software Development, Software Quality Assurance, and Application (FY2025)

SPCA-ANL is a simulation tool used to perform deterministic analyses of sodium spray and pool fires. Development of the SPCA-II (Spray Pool Combustion Analysis) code began in the mid- 1980s as part of the Clinch River Breeder Reactor (CRBR) Project. At that time, development of SPCA-II, which was led by Rockwell International, was focused on treatment of large-scale sodium spray, stream, and pool fires that were anticipated to be prototypic of the steam generator building cells in CRBR. Under more recent DOE NE programmatic activities, the SPCA-II code was recovered from existing literature and underwent minor modifications to generate a stable executable. This recovered version of the code was not formally released. As part of the Versatile Test Reactor (VTR) Project in the 2010s, the SPCA-II code underwent key modifications to improve stability, address modeling deficiencies, improve consistency between the code manual and software, and address numerous bugs. At this point, SPCA-II was renamed SPCA-ANL. Given that SPCA-II served as the original basis for SPCA-ANL, both codes share an integrated history. Following termination of the VTR Project, the DOE NE Fast Reactor Program resumed support of the software with the goal of building and maintaining software infrastructure that can enable commercial-grade dedication of SPCA-ANL by an end user. Version 1.0, the first external release of SPCA-ANL, was generated in June 2024. This report summarizes the development and maintenance activities completed for SPCAANL in FY2025. This year’s work was focused on improving quality and usability of the code. The provisional Software Quality Assurance (SQA) program has been established and was used to test the procedures for infrastructure improvements, code development, bug fixes, and code releases, as described in the following sections of this report. A code Version 1.0.1 was released in FY25, as described in Chapter 4.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Lahaina Energy Partnership: Technical Assistance Task Updates and Discussion Part 2

The Lahaina Energy Partnership (LEP) is an initiative funded by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) to support energy planning and rebuilding efforts in Hawaii's historic town of Lahaina on Maui as the community recovers from a devastating fire on August 8, 2023, with technical assistance provided by the National Laboratory of the Rockies. NLR has partnered with Hawaii-based community organizations to engage with Lahaina the community on energy priorities and inform the technical assistance scope. This virtual workshop presentation is the second in a two-part series to provide progress updates and request community input to guide next steps. Workshop 1 on November 18 focused on hydropower resource potential, building energy modeling, and workforce development. Workshop 2 on December 11 (this presentation) will focus on microgrids, electric grid hardening, policy and regulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Numerical modeling of plasma assisted deflagration to detonation transition in a microscale channel

Here, this work numerically studies the plasma assisted deflagration to detonation transition (DDT) of H 2 /O 2 mixtures in a microscale channel with detailed chemistry and transport. The results show that the DDT onset time is non-monotonically dependent on the discharge pulse number. The DDT is accelerated with small pulse numbers, whereas retarded with large ones. Two different DDT regimes, respectively at a small and large plasma discharge number, via acoustic choking of the burned gas and plasma-enhanced reactivity gradient without acoustic choking, are observed. Without plasma discharge, pronounced pressure and temperature gradients in front of the flame are generated by acoustic compression after the choking of the burned gas, triggering DDT via autoignition. With small plasma pulse numbers, the plasma-generated species enhance the ignition kinetics and lead to an increased reactivity in the boundary layer. After the choking of the burned gas, the plasma-enhanced reactivity advances the sequence of autoignition near the wall, strengthens ignition-shock wave coupling, and accelerates DDT. However, with a large discharge pulse number, a direct autoignition initiating DDT can occur without the acoustic choking of the burned gas due to the strongly accelerated reactivity and elevated temperature. In this case, DDT onset is retarded because the elevated temperature increases sonic velocity and the increased reactivity accelerates fuel oxidation in front of the flame, decelerating the formation of a leading shock and subsequent pressure buildup ahead of the flame. The present modeling reveals that no matter with or without plasma discharge, DDT is initiated by autoignition in thermal, pressure, and reactivity gradient fields via the Zel'dovich gradient mechanism. The acoustic choking of the burned gas may not be the necessary condition of DDT with strong plasma-enhanced reactivity gradient. This work provides an answer to the experimentally observed non-monotonic DDT onset time by plasma, which provides guidance to control DDT in advanced detonation engines and fire safety of hydrogen-fueled catalytic reactors in microchannels by non-equilibrium plasma discharge.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Shape Anisotropy-Dependent Leaking in Magnetic Neurons for Bio-Mimetic Neuromorphic Computing

Spiking neural networks seek to emulate biological computation through interconnected artificial neuron and synapse devices. Spintronic neurons can leverage magnetization physics to mimic biological neuron functions, such as integration tied to magnetic domain wall (DW) propagation in a patterned nanotrack and firing tied to the resistance change of a magnetic tunnel junction (MTJ), captured in the domain wall-magnetic tunnel junction (DW-MTJ) device. Leaking, relaxation of a neuron when it is not under stimulation, is also predicted to be implemented based on DW drift as a DW relaxes to a low energy position, but it has not been well explored or demonstrated in device prototypes. Here, in this work, we study DW-MTJ artificial neurons capable of leaky integrate-and-fire (LIF) behavior and demonstrate geometry-dependent leaking dynamics that results in repeatable, tunable LIF operation. Studying the behavior of five different device designs, we show tuning the geometry, stimulating fields and currents, and location of electrical contacts results in a wide range of neuron behavior. Additionally, implementation of an asymmetric notch allows for nonlinear pinning which increased expressivity without sacrificing leaking. The measured behavior is implemented in a simulated spiking neural network that outperforms a 1D model of continuous DW motion and approaches the performance of an ideal LIF activation function. The results show that the analog LIF capability of DW-MTJ neurons combines many desirable neuron functions into a single device, which can result in varied forms of multifunctional neuromorphic computing.

42 ENGINEERING↗
DOE OSTI2026

Lahaina Energy Partnership: Technical Assistance Task Updates and Discussion Part 1 [Slides]

The Lahaina Energy Partnership (LEP) is an initiative funded by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) to support energy planning and rebuilding efforts in Hawaii's historic town of Lahaina on Maui as the community recovers from a devastating fire on August 8, 2023, with technical assistance provided by the National Laboratory of the Rockies. NLR has partnered with Hawaii-based community organizations to engage with Lahaina the community on energy priorities and inform the technical assistance scope. This virtual workshop presentation is the first in a two-part series to provide progress updates and request community input to guide next steps. Workshop 1 on November 18 (this presentation) will focus on Hydropower resource potential, building energy modeling, workforce development. Workshop 2 on December 11 (presentation forthcoming) will focus on microgrids, electric grid hardening, policy and regulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Wireless Patch Antenna Characterization for Live Health Monitoring Using Machine Learning

Temperature monitoring in extreme environments, such as coal-fired power plants, was addressed by designing and testing wireless patch antennas for use in machine learning-aided temperature estimation. The sensors were designed to monitor the temperature and health of boiler systems. Wireless interrogation of the sensor was performed using a Vector Network Analyzer (VNA) and a pair of interrogation antennas to capture resonance behavior under varying thermal and spatial conditions with sensitivities ranging from 0.052 to 0.20 $\frac{𝑀𝐻𝑧}{°C}$. Sensor calibration was conducted using a Long Short-Term Memory (LSTM) model, which leveraged temporal patterns to account for hysteresis effects. The calibration method demonstrated improved performance when combined with an LSTM model, achieving up to a 76% improvement in temperature estimation error when compared with Linear Regression (LR). The experiments highlighted an innovative solution for patch antenna-based non-contact temperature measurement, which addresses limitations with conventional methods such as RFID-based systems, infrared, and thermocouples.

20 FOSSIL-FUELED POWER PLANTS↗