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At least 775 records · Page 43

High Throughput Discovery of Thermoelectric Materials (Final Report)

New materials form the heart of advances in energy technologies; however, the actual synthesis and characterization of new materials remains an enormous bottleneck. In this award, the research team focused on developing new approaches overcome this bottleneck. The approach involved depositing at high (supersonic) velocity multiple crystalline materials at a substrate while controlling the resulting film composition. The film could then be annealed to create a homogeneous alloy that was suitable for characterization. High throughput characterization tools were developed in parallel. The research focused on thermoelectric materials, which convert the flow of heat into electrical power. The development of new thermoelectric materials with high power conversion efficiency could displace traditional mechanical heat engines (e.g. turbines).

30 DIRECT ENERGY CONVERSION↗

Computer vision models and advanced TEM imaging for microstructures of irradiated AM316 stainless steels

Advancements were made in automating microscopy-based material characterization, particularly in studying irradiation effects on additively manufactured (AM) materials using machine learning (ML) and computer vision (CV). These automation efforts address the challenges of analyzing complex microstructures, accelerating the detection of irradiation-induced defects. Two CV models were developed at Argonne National Laboratory (ANL) to enhance transmission electron microscopy (TEM) analysis of irradiated AM 316 stainless steel. The first model focused on the detection of irradiation-induced dislocation loops, which contribute to material hardening and embrittlement. These loops, categorized as faulted or perfect, were automatically detected and classified using a Mask R-CNN model trained on TEM images from both in-situ and ex-situ ion irradiation experiments. The model achieved high accuracy, with precision, recall, and F1 scores of 0.839, 0.734, and 0.776, respectively, demonstrating its effectiveness in analyzing dislocation loops in irradiated AM materials. The second CV model was developed to analyze the size and wall thickness of dislocation cells in laser powder bed fusion (LPBF) 316 stainless steel. Using a U-Net++ architecture with EfficientNet as the encoder, the model was trained on TEM images to segment and measure cell size and wall thickness.

36 MATERIALS SCIENCE↗

AGR-2 TRISO Shadow Imaging Archive

As a part of fuel quality control characterization, backlit shadow images of particles produced by the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program’s AGR-2 irradiation campaign were acquired at Oak Ridge National Laboratory (ORNL). These images may be of use for the development of image processing algorithms with the benchmark values measured at ORNL. This report provides those benchmark values, along with the raw images and data generated by the ORNL shadow imaging process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗

The Development of Catalysts for Upgrading of Pyrolysis Vapor for Refinery Feedstocks and Intermediates (CRADA Final Report)

Catalytic fast pyrolysis (CFP) is a versatile technology platform to convert biomass into fungible hydrocarbon transportation fuels and chemical co-products. Key technical barriers to reaching this goal include increasing the product yields and achieving the desired fuel properties for gasoline, diesel, and jet range fuels or blendstocks that would be suitable for introduction into existing refinery unit operations. Overcoming these barriers will require durable catalysts that are effective at upgrading and stabilizing biomass pyrolysis vapors. Towards these goals, this CRADA leveraged NREL experience as a leader in biomass pyrolysis research and Johnson Matthey's (JM) experience as a leader in the production of advanced catalytic materials. The scope spanned CFP catalyst development, characterization, multi-scale reaction testing, and computational modeling. CRADA benefits to DOE, Participant, and U.S. Taxpayer: Assists laboratory in achieving programmatic scope, Uses the laboratory’s core competencies. The purpose of this CRADA was to develop and deploy catalysts for biomass CFP to help achieve cost-competitive biofuels and bio-based products. This was accomplished through a close collaboration between biomass conversion researchers at NREL and catalyst development researchers at JM. Summary of Research Results: Focus Area 1. Foundational research on catalytic conversion and deactivation: Key interactions between pyrolysis vapors and heterogeneous catalysts were probed through catalyst characterization, model compound reaction testing, and atomistic-scale computational modeling. Catalyst development focused on multifunctional materials, which include zeolites, oxides, carbides, and nitrides. Computational modeling identified reaction mechanisms and elucidated surface chemistry to test hypotheses regarding mechanisms of deoxygenation, coupling, cracking, dehydration, coke formation, hydrogen transfer, and aromatic ring reactions. This information was used to design multifunctional catalysts to increase product yields, control product selectivity, and reduce deactivation during CFP and downstream processing steps. The results served to increase fundamental understanding of key catalyst attributes and durability features for the upgrading of biomass pyrolysis vapors. Model compound experiments confirmed the importance of metal-acid bifunctionality for the deoxygenation of lignin-derived phenolic species under hydrodeoxygenation conditions. This insight led to the development of catalysts such as Pt/TiO2 and Mo2C, which were confirmed as high-performing materials during subsequent bench-scale experiments using biomass-derived pyrolysis vapors. This focus area also led to the identification of important catalyst deactivation mechanisms associated with the deposition of inorganic contaminants such as potassium. The molecular-level insight from model compound experiments and computational modeling, shown in Figure 1, informed the development of regeneration procedures that have been shown to be effective for restoration of > 90% of initial catalyst activity. This understanding has subsequently been translated to other catalyst systems, including zeolite materials that can be operated without requirements for co-fed hydrogen.

09 BIOMASS FUELS↗

Analysis of temperature effects on self-powered neutron detectors in a gamma field

Self-powered neutron detectors (SPND) are small, robust, in-core radiation sensors that have the potential to operate in high temperature environments (above 600°C). However, previous experiments indicated temperature related effects in the form of displacement currents. Given the recent irradiation at The Ohio State University Research Reactor using a delayed-response rhodium-based SPND alongside a prompt-response tantalum-based SPND, it was concluded that only low-energy electrons from gamma interactions were the cause of these temperature effects. A series of heated gamma irradiations with temperatures up to 750°C of SPNDs were performed at the Advanced Test Reactor Gamma Facility in order to better characterize these displacement currents. The results from the experiments demonstrated a strong relation between the displacement currents that occurred during temperature ramps to thermoluminescence (TL) glow peaks—the SPND with Al2O3 insulation has one glow peak within 750°C and the SPND with MgO has three. A demonstration was performed to calculate the trap energy levels of the displacement currents through TL glow peak analysis. Unfortunately, the methods employed provided inconsistent results, requiring an updated model based on ongoing irradiation instead of post-irradiation measurements.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Solar Wind Turbulence from 1 to 45 au. III. Anisotropy of Magnetic Fluctuations in the Inertial Range Using Voyager and ACE Observations

We examine both Voyager and Advanced Composition Explorer magnetic field measurements at frequencies that characterize the inertial range and evaluate the anisotropy of the fluctuations as they relate to both the compressive component and underlying wavevector anisotropy of the turbulence. The magnetic fluctuation anisotropy as it relates to the compressive component is directly dependent upon both the plasma beta of the thermal proton component and the ratio of magnetic fluctuation magnitude to the strength of the mean magnetic field. This has been seen before at 1 au. The magnetic fluctuation anisotropy in the plane perpendicular to the mean magnetic field, which is a measure of the anisotropy of the underlying wavevector distribution, should depend on the angle between the mean magnetic field and the radial direction and should be confined to values between one and the index of the power spectrum, which is typically 5/3. Our results show that the average of this anisotropy exceeds the value of the spectral index and is out of bounds with the theory. Although the results are suggestive of past analyses, we find that spherical expansion of the turbulence may offer at least a partial explanation of the apparent amplification of this measured anisotropy.

heliosphere↗

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗

Characterization of radiation damage in 3D printed SiC

The SiC fuel matrix for advanced gas-cooled high temperature reactors as part of the Transformational Challenge Reactor program serves as the fuel particle container structure, a barrier to fission gas release, and a heat transfer medium. Its performance is particularly important because the fuel matrix must demonstrate good structural stability and thermal behaviors. An additive manufacturing methodology combining a binder jet 3D printing process with chemical vapor infiltration (CVI) for the production of SiC was recently developed. In this study, post irradiation examination by transmission electron microscopy shows that defect accumulation within the printed particles is very similar to other forms of high-purity SiC. However, damage accumulation was not directly observed in the CVI matrix because black spot damage and dislocation loops are difficult to image within the nanoscale highly faulted CVI matrix and because interstitial defects may rapidly annihilate at the stacking faults. Therefore, electron energy loss spectroscopy (EELS) analysis was used to analyze defect swelling in both the printed particles and the CVI matrix. The EELS analysis helped reveal that the radiation-induced swelling in the CVI matrix is similar to that of the printed SiC particles. This work shows that 3D printed SiC has behavior that is comparable to SiC processed by other means and that 3D printing could serve as a suitable processing technique for high-purity SiC for nuclear applications.

36 MATERIALS SCIENCE↗

Hyperspectral imaging for real-time waste materials characterization and recovery using endmember extraction and abundance detection

Hyperspectral imaging, combined with advanced spectral unmixing techniques and artificial intelligence, offers a powerful solution for improving material identification and classification. Here, this study evaluates the effectiveness of the pixel purity index and the sequential maximum angle convex cone algorithms in extracting and validating spectral signatures from pure samples of paper components (cellulose and lignin) and plastic (polypropylene). Principal-component analysis showed that both algorithms captured nearly all relevant variance for the tested materials. Spectral signatures were compared using the spectral angle mapper, revealing high similarity in the short-wave infrared region and greater variability in the visible near-infrared range. The methodology was then applied to a disposable coffee cup to detect and quantify mixed materials, accurately estimating material abundance and object area with less than 1% error. This approach enhances material classification, supporting product verification, quality control, and automated sorting for sustainable waste management and resource recovery.

36 MATERIALS SCIENCE↗

Radiative Heat Transport and Optical Characterization of High Temperature Molten Salts

The goal of this project was to advance the field of molten fluoride radiative heat transfer (RHT), through optical property measurements, heat transfer loop construction and operation, and computational fluid dynamics simulations. The following outcomes have been accomplished. A comprehensive review has been conducted to compile all available RHT-relevant optical absorption data for molten fluorides. The various measurement methods have also been compiled and critiqued. Thermal emission measurement methods have been refined and documented. A unique thermal emissivity measurement facility has been constructed and used to measure the emissivity of flowing FLiBe-exposed SS316 samples. A slight increase has been observed in the emissivity compared to unexposed SS316. A dual reflectance-emission setup was partially demonstrated for the purpose of molten fluoride absorption measurement. Preliminary infrared edge data for FLiNaK was obtained. A visible near-infrared (NIR) measurement setup has been constructed and will be used to measure absorption of corrosion products in FLiBe. A new multi-band thermal radiation method using blackbody-weighted spectral bands for the absorption-coefficient was deployed to investigate the thermal performance of the UW Natural Circulation FLiBe Loop under various power levels and operating conditions. The results showed an increasing and decreasing trend in the overall heat transfer with optical thickness with a maximum at optical thickness τ D ≈Ο(1). A forced convection FLiBe loop was constructed for the purpose of studying corrosion and thermal hydraulic phenomena. A vertical cantilever pump is used to achieve up to 5 gpm and 5 m/s flow velocity in hot and cold test sections. A methodology has been established for modeling radiative heat transfer (RHT) in molten salt coolants for the purpose of quantifying the contribution of thermal radiation in conditions relevant to FHR or MSR systems. The comparison between the results obtained for forced and mixed convection showed that in the studied ranges of optical thickness, the maximum effect of RHT on overall heat transfer was 60% improvement observed at z/D = 250 for forced convection; whereas for mixed convection, that value was higher at 170% observed at z/D = 30. The highest effect of RHT on the overall energy distribution was observed at τ D ≈3.4. Negligible effect (<20%) was observed above τ D =18 and below τ D ≈0.002. A CFD code-to-code comparison was conducted using COMSOL Multiphysics at UW-Madison and STAR-CCM at MIT, for a forced and mixed convection laminar flow for a grey medium in a vertical heated using both COMSOL Multiphysics at UW-Madison and STAR-CCM at MIT. The relative error was the largest at τ D =40 for the radiative heat flux, bulk temperature, and Nusselt number. On the other hand, the relative error was the least at τ D =0.002 for the conductive heat flux, bulk temperature, and Nusselt number.

Anderson, Mark↗

A Summary of the Microstructural Characterization Results for the A709 Commercial Heats

To improve high temperature strength for advanced nuclear reactors, it is necessary to qualify additional structural materials for introduction into the American Society of Mechanical Engineers (AMSE) Boiler and Pressure Vessel Code (BPVC). Specifically, Alloy 709 was identified as a material for Sodium-cooled Fast Reactors to enhance time-dependent mechanical properties compared to 316H stainless steel, a code qualified high temperature alloy. Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) performed initial microstructure and mechanical property testing on a third, commercial heat of Alloy 709 stainless steel. The Alloy 709 plate was produced by Allegheny Technology Inc. (ATI) and in the solution annealed condition. The chemical composition was within the limits for an American Society of Testing and Materials (ASTM) A213 specification for seamless tube for material UNS S31025. Grain size was measured as an average ASTM size of 6.5, which was larger than the ASTM 7 required according to ASTM A213 for seamless tube. The chemical composition was within the limits for an ASTM A213, and the room temperature tensile tests and hardness data met ASTM A213 specifications. Creep-fatigue results showed similar behavior to previous heats of Alloy 709.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Materials Characterization: A Primer for Solid Phase Processing Applications

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development (LDRD) Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). As a two-year LDRD investment requiring focused research, the MCPC project applied only a subset of the wide range of available destructive and nondestructive characterization methods to provide data to the predictive modeling and data analytics tasks. The purpose of this report is to review a wide range of destructive and nondestructive characterization methods that are relevant in solid-phase processing (SPP) applications, but not necessarily applied in the MCPC Project as a guide to the planning of characterization activities in future research. Particular attention is given to measured characteristics that can correlate to other material characteristics, with a particular interest in nondestructive evaluation (NDE) that can be applied to samples obtained in the MCPC Project. Destructive examinations include tensile tests, optical and electron microscopy, micro-hardness, and residual stress tests. NDE tests include surface visual inspection, eddy current examination for cracks, 4-point potential drop, ultrasound, x-ray, and computed tomography.

36 MATERIALS SCIENCE↗

Development and Application of In Situ Nanocharacterization to Photocatalytic Materials for Solar Fuel Generation

Photocatalytic materials offer an attractive approach for converting solar energy into chemical energy but the performance of the current generation of materials is insufficient to make a technology viable. To address this deficiency, it is necessary to develop a fundamental atomic level understanding of the functioning of such materials so that strategies can be developed to improve performance. This project was undertaken to explore the fundamental structure and properties of photocatalytic materials using atomic resolution imaging and spectroscopy techniques available on advanced transmission electron microscopy. Specifically, there is a need to develop an understanding of how atomic structures/defects and nanoparticle configurations regulate electronic, optical, and catalytic properties to facilitate the design of next generation photocatalysts for solar fuel production. The work focused on fundamental materials information that can be gained from advanced transmission electron microscopy study on novel and existing photocatalytic systems with an emphasis on the hydrogen evolution reaction (HER). Throughout the project, new instrumentation and microscopy characterization tools were developed. Two focus areas were: developing in situ TEM methods and advanced electron energy-loss spectroscopic for nanoscale analysis of catalysts. The work spanned a period of 12 years and for convenience, the report is divided into four phases, approximately corresponding to the four funding periods of the program. Most of the significant results are reported in archival journal publications.

36 MATERIALS SCIENCE↗

First Examination of Irradiated Fuel with Pulsed Neutrons at LANSCE (Preliminary Results)

We present preliminary results on the characterization of an irradiated U-lOZr-lPd fuel sample that was prepared from the irradiated AFC-3A-R5A sample. U-lOZr metallic fuels are researched as host materials for potential transmutation fuels and the addition of palladium strives to bind lanthanides, thus preventing fuel-cladding chemical interactions (FCCI). These interactions limit the lifetime of metallic fuels and are caused by migration of lanthanide fission products to the periphery of the fuel slug, where they start to interact with the D9 or HT9 steel cladding, ultimately leading to failure of the mechanical integrity of the cladding. Neutrons offer bulk characterization of irradiated materials for which X-ray tomography methods are not suitable due to the immense gamma background emitted from the samples. In particular pulsed neutrons provide information from the ability to resolve the neutron energy using their time-of-flight and thus the potential to utilize neutron absorption resonance to characterize the spatial distribution of isotopes. This, in turn, may allow to characterize the distribution of fission and neutron capture products non-destructively and may ultimately be applied to the bulk of an irradiation capsule prior to destructive post-irradiation examination to identify regions of interest. To allow the characterization of entire irradiation capsules, a cask is under development in the advanced post-irradiation work package at LANL and progress on this development was reported elsewhere. In parallel, an irradiated U-lOZr-lPd sample cut from the AFC-3AR5A irradiation was shipped to LANL and will be fully characterized with an NSUF funded rapid turnaround experiment (RTE) in the 2020 LANSCE run cycle. The sample emits at a dose rate of ~3R/hr on contact and is therefore manageable with remote handling, without requiring a cask. The disk-shaped material is larger than samples prepared for analysis using electron or X-ray methods and is therefore an intermediate step towards characterization of bulk samples at LANSCE. However, since it covers the full diameter of the irradiated fuel slug, some insight on redistribution of elements, spatially resolved information on microstructure, e.g. phase composition and texture, will be possible using the pulsed neutron-based methods developed for fuel characterization at LANSCE. This report describes the development of procedures to handle the sample at LANSCE as well as preliminary data and results from tests conducted in December 2019 on the energy-resolved neutron imaging (ERNI) beam line at flight path 5 and the high pressure-preferred orientation diffractometer (HIPPO) at LANSCE. This effort is a collaboration between LANL, INL, and ORNL. To compare our capabilities with prior work, we present an overview of previously reported bulk characterization of irradiated or spent fuels. The overview addresses neutron diffraction and neutron absorption resonance spectroscopy, both of which have only few reported applications on irradiated or spent nuclear fuel, as well as neutron radiography. This literature review was already described in a previous report but is repeated here to put our current efforts in context of previous work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Summary of Graphite Data Stored within NDMAS

The Graphite Technology Development Project provides data to support the design of graphite core components within specific reactor service conditions of the next generation of high-temperature, gas-cooled nuclear reactors. Physical, mechanical, and thermal properties of nuclear grade graphite were characterized for specimens that were unirradiated, irradiated, and irradiated under various stress conditions. The material properties include diameter, length, mass, density, compressive strength, tensile strength, flexural strength, modulus, resistivity, thermal diffusivity, and thermal expansion coefficient. Baseline graphite specimens are unirradiated from different grades (2114, IG-110, NBG-17, NBG-18, and PCEA) and different types used in different characterization tests (compressive, flexural, tensile, one-inch cylinder, and quarter-inch cylinder). The Advanced Graphite Creep (AGC) irradiation specimens are from a much larger number of grades and cylinder types (creep, piggyback, and pencil). For baseline graphite, characterization data for 7,756 specimens extracted from thirteen graphite billets were captured to the NDMAS database. For AGC experiments, four irradiation campaigns have been completed: AGC-1, AGC-2, AGC-3, and AGC-4. The ongoing HDG-1 (High-Dose Graphite) experiment, which began irradiation with Cycle 168B on August 26, 2020, includes specimens previously irradiated in AGC-2 in addition to the specimens originally destined for AGC-5.. Besides the characterization data, the AGC data includes irradiation monitoring and physics data representing the irradiation conditions of AGC specimens. Currently, all data for AGC-1, AGC-2, and AGC-3 have been captured to the NDMAS database. Only AGC-4 pre-irradiation and irradiation monitoring data have been captured, and HDG-1 pre-irradiation data are in process of being captured for unirradiated specimens. To date, a total of 38,149 material property records have been captured into NDMAS database for baseline and AGC specimens. All characterization data are qualified for use according to their perspective data verification reports. For the AGC irradiation campaigns, a total of 41,502 qualified physics calculation records were added for AGC-1, AGC-2, and AGC-3. Finally, a total of 173,698,505 AGC irradiation monitoring data records (thermocouple temperature, gas flow rate, gas pressure, gas moisture, applied load, and specimen displacement) have been captured to NDMAS; the majority of those records (~94%) are qualified data records.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Initial Fracture Propagation Modeling of Graphite Components with Grizzly

Graphite has historically been extensively used in power reactor cores and will be used in multiple types of advanced reactors currently under development. These graphite structural components can experience significant stresses due to nonuniform volumetric strains induced by irradiation and thermal expansion, which can lead to fracture. Robust tools for predicting fracture initiation and propagation in graphite structural components in nuclear reactors are important for evaluating component integrity, developing design standards, and interpreting experimental results to characterize graphite performance. The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program has been developing degradation models for other structural components in nuclear reactors within the Grizzly and BlackBear codes. This report documents an effort to develop initial capabilities for modeling graphite fracture within these codes, building on prior efforts to model fracture in other materials. Major elements of this effort include developing a new system for modeling fracture nucleation and growth in two dimensions using the extended finite element method and incorporating a damage and plasticity model. These capabilities are applied here to model a representative graphite component and a splitting disc experiment used to obtain tensile strength.

36 MATERIALS SCIENCE↗

A review of regulatory standard test methods for residential wood heaters and recommendations for their advancement

In many regions, residential wood heaters are a leading source of harmful air pollution but only satisfy a small portion of local heating demands. In response, standardized laboratory test methods have been developed to characterize and limit wood heater emissions. While these test methods are a key tool for advancing both wood heater technology and environmental regulations, many of the experimental procedures are outdated and provide few actionable insights for improving heater performance. Furthermore, these test methods vary widely around the world and may not adequately capture the performance of wood heaters operating in residences. This study presents a comprehensive review of standardized wood heater test methods to identify fundamental experimental objectives and regulated performance metrics. Using the results of this review, recommendations are provided to make the test methods more accessible and representative of residential performance, while generating actionable data to motivate heater design improvements. This study elucidates the current state of standard test methods, and the developments needed to advance clean wood heater technologies and public policies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗