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DOE OSTI2025

Robot-based Additive Manufacturing of Lego-type Modular Molds for Wind Blades

The objective of this project is to reduce the cost and lead time of horizontal wind turbine blade mold tooling and blade transportation, while maintaining the highest standards of blade quality. The solution involves a smart-design family of modular molds that are easily transportable to fabrication sites near the place of service. Key innovations include the use of additive manufacturing (AM) to integrate conformal thermal management channels, offering enhanced control over the thermal profiles tailored to specific blade materials. This approach enables in-situ quality assurance during mold fabrication, significantly improves mold life, and allows for reuse across multiple production cycles. Ultimately, the solution aims to optimize both tooling and transportation costs, contributing to the scalability of wind turbine blade production. A significant barrier to scaling up the production of large wind turbine blades lies in the high costs associated with tooling and the transportation of blades. Traditional molds are expensive, bulky, and difficult to transport, adding considerable lead time and cost to the overall manufacturing process. Additionally, transporting blades to distant locations for final assembly further exacerbates these challenges. The project aims to address these inefficiencies by demonstrating a modularized, additive-manufactured mold that meets all necessary blade specification requirements, specifically for blade lengths between 120m and 150m.

17 WIND ENERGY↗

DOE OSTI2025

Cluster Dynamics Modeling Needs for the Advanced Materials and Manufacturing Technologies Program

This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

In-situ sensor monitoring of multi-class gas porosity formation in laser powder bed fusion using convolutional neural network

In-situ monitoring of defect formation remains a significant challenge in the laser powder bed fusion (LPBF) process. Recent advances have enabled real-time defect detection with machine learning and in-situ sensing technologies; however, most studies focus on binary classification of keyhole pores, limiting nuanced multi-class pore differentiation and formation mechanisms. This work introduces a multi-class pore detection framework (no pore, small pores < 15 µm, and large pores > 15 µm) by leveraging photodiode sensor data alongside high-fidelity synchrotron X-ray imaging. The 15 µm threshold is selected to distinguish between two fundamentally different defect mechanisms, following the physical size-mechanism boundary established by prior high-resolution synchrotron X-ray characterization of Al6061 LPBF. Distinguishing these classes is critical because large keyhole pores are structurally detrimental, whereas small gas pores are often benign, requiring different process control strategies. Thermal emission monitoring data collected simultaneously with high-speed X-ray imaging at the Stanford Synchrotron Radiation Lightsource (SSRL), are correlated with subsurface melt pool dynamics to establish ground truth. Continuous Wavelet Transform (CWT) with optimized parameters converts the photodiode time-series signals into time–frequency images, facilitating feature extraction. Convolutional Neural Networks (CNN) are then applied for real-time multi-class pore classification in an average inference time of 1 ms per signal window. It achieves 79% accuracy and an Area Under the Receiver Operating Characteristic curve (AUC ROC) score of 0.89 with five-fold cross-validation. The results demonstrate that coupling CWT-based feature engineering with CNN architecture enables reliable multi-class pore detection in Al6061 builds using affordable in-situ sensors. This approach advances scalable and affordable quality assurance in additive manufacturing by moving beyond binary defect detection toward more nuanced classification of porosity mechanisms with in-situ sensors and machine learning.

Laser powder bed fusion, Multi-class pores, In-sit↗

DOE OSTI2025

Membrane Electrode Assembly Manufacturing Automation Technology for the Electrochemical Compression of Hydrogen: Cooperative Research and Development (Final Report)

Electrochemical compression has the possibility to outcompete mechanical compression for hydrogen end- use applications. While HyET has a compressor that can output JO kilograms (kg)/day (fully scalable from home-to-industrial application) at up to 700 bar, the energy demand and reliability require top-quality electrochemical hydrogen compression (EHC) membrane electrode assemblies (MEAs), preferably prepared by cost-effective high-capacity manufacturing. High pressure requires a special MEA design, deviating from typical proton exchange membrane fuel cell (PEMFC) MEAs with adapted catalyst layer substrates, asking for a modified coating process. The National Renewable Energy Laboratory (NREL) will help HyET by developing an automated catalyst coating process fit for EHC MEA manufacturing. In addition, inline quality inspection methods will be developed/selected to improve the MBA quality as it is used for EHC stack assembly. In a joint effort, NREL and HyET will even design an automated manufacturing process for the EHC MEA and approach potential United States (US) suppliers of manufacturing equipment.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2024

The Effect of Interlayer Delay on the Heat Accumulation, Microstructures, and Properties in Laser Hot Wire Directed Energy Deposition of Ti-6Al-4V Single-Wall

Laser hot wire directed energy deposition (LHW-DED) is a layer-by-layer additive manufacturing technique that permits the fabrication of large-scale Ti-6Al-4V (Ti64) components with a high deposition rate and has gained traction in the aerospace sector in recent years. However, one of the major challenges in LHW-DED Ti64 is heat accumulation, which affects the part quality, microstructure, and properties of as-built specimens. These issues require a comprehensive understanding of the layerwise heat-accumulation-driven process–structure–property relationship in as-deposited samples. In this study, a systematic investigation was performed by fabricating three Ti-6Al-4V single-wall specimens with distinct interlayer delays, i.e., 0, 120, and 300 s. The real-time acquisition of high-fidelity thermal data and high-resolution melt pool images were utilized to demonstrate a direct correlation between layerwise heat accumulation and melt pool dimensions. The results revealed that the maximum heat buildup temperature of the topmost layer decreased from 660 °C to 263 °C with an increase to a 300 s interlayer delay, allowing for better control of the melt pool dimensions, which then resulted in improved part accuracy. Furthermore, the investigation of the location-specific composition, microstructure, and mechanical properties demonstrated that heat buildup resulted in the coarsening of microstructures and, consequently, the reduction of micro-hardness with increasing height. Extending the delay by 120 s resulted in a 5% improvement in the mechanical properties, including an increase in the yield strength from 817 MPa to 859 MPa and the ultimate tensile strength from 914 MPa to 959 MPa. Cooling rates estimated at 900 °C using a one-dimensional thermal model based on a numerical method allowed us to establish the process–structure–property relationship for the wall specimens. The study provides deeper insight into the effect of heat buildup in LHW-DED and serves as a guide for tailoring the properties of as-deposited specimens by regulating interlayer delay.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Combining Deep Learning and scatterControl for High-Throughput X-ray CT Based Non-Destructive Characterization of Large-Scale Casted Metallic Components

X-ray computed tomography (XCT) is essential for nondestructive evaluation and quality control of large-scale metal components. XCT imaging, however, faces significant challenges from metal artifacts, particularly those caused by Compton scattering, which degrade image quality and obscure critical details. Hardware-based solutions (e.g. scatterControl) offer advancements by intercepting scattered photons and reducing artifacts, but they can be time-consuming and require additional processing. Here, we propose modifying and leveraging a novel deep learning (DL) framework, Simurgh, to enhance and accelerate scatter correction in XCT. By combining scatterControl with DL-based artifact removal, we demonstrate significant reduction in scan time while producing high-quality reconstructions. Through extensive evaluation on industrial XCT data, we show that our methods reduce scan time by up to more than 10 x while preserving flaw detectability. Quantitative analysis across multiple segmentation techniques confirms that Simurgh-based reconstructions consistently outperform traditional Feldkamp-Davis-Kress, model-based iterative reconstruction, and commercial DL models in both pixel-level and task-specific evaluations, enabling scalable, high-throughput XCT workflows for characterization of large scale components in applications such as casting and metal additive manufacturing.

Complex metal parts↗

DOE OSTI2024

Effect of Iron Contamination and Polysilicon Gettering on the Performance of Polysilicon‐Based Passivating Contact Solar Cells

Over the past decade, silicon solar cells with carrier-selective passivating contacts based on polysilicon capping an ultra-thin silicon oxide (commonly known as TOPCon or POLO) have demonstrated promising efficiency potentials and are regarded as an evolutionary upgrade to the PERC (passivated emitter and rear contact) cells in manufacturing. The polysilicon-based passivating contacts also exhibit excellent gettering effects that relax the wafer and cleanroom requirements to some extent. Here, in this work, we experimentally explore the impact of bulk iron contamination and polysilicon gettering on the passivation quality of the polysilicon/oxide structure and the resulting solar cells performance. Results show that both n- and p-type polysilicon/oxide passivating contacts are not affected by iron gettering, demonstrating robust and stable passivation quality. However, for a very high bulk iron contamination (1 × 10 13 cm −3 ), the accumulated iron in the p-type lightly boron-doped emitter in crystalline silicon would degrade the emitter saturation current density. This can cause a reduction in both open-circuit voltage and short-circuit current. Meanwhile, this very high iron content (1 × 10 13 cm −3 ) can further degrade the fill factor and temperature coefficient of the cells. On the other hand, for an initial iron content of 2 × 10 12 cm −3 , which should be well above the iron level in the current industrial Czochralski silicon wafers, the resulting cells demonstrate similar performance as the control group with no intentional iron contamination. This work brings attention to both the benefits of polysilicon gettering effects as well as the potential degradation due to the accumulation of metal impurities in the p-type emitter region.

14 SOLAR ENERGY↗

DOE OSTI2022

Towards Multilayered Coatings of 304L Stainless Steels Using Friction Surfacing

Abstract The objective of this work is to study friction surfacing process variability when depositing multilayered coatings. This is motivated by the need to maintain deposition quality when depositing multiple friction surfacing layers, whether for repair, remanufacturing, or new part creation using this solid-state metal additive manufacturing process. In this study, 10-mm-diameter 304L stainless steel rods were used to create up to five layers of 40-mm-long coatings on 304L substrates using a constant set of processing parameters. In-process measurement of forces (X, Y, Z), flash temperature, flash geometry, layer temperature, and post-process measurement of layer geometry, microhardness, and microstructure are used to characterize changes in the friction surfacing process as more layers are deposited. It was observed that with increasing layers: layer thickness and deposition efficiency decrease; offsetting of the deposition towards the retreating side, and temperature in the deposited layer increase; and flash temperature does not change. Metallurgical analyses of friction-surfaced cross-sections revealed fine grain refinement and transformation of base austenite to strain-induced martensite. It is concluded that the process parameters need to be adjusted even after the second or third layer is deposited, corrections to the tool path are required after a couple of layers, and the measured process forces, as well as deposited layer temperature, may be useful to monitor and control the process and its instabilities.

Engineering↗

DOE OSTI2026

Enabling Bipolar Membrane Manufacturing Using Microscopy

Bipolar membranes (BPMs) used for water treatment suffer from interface instabilities, causing premature failure and decreased performance. Recent research has highlighted the impacts of membrane morphology on mechanical behavior and performance. Improved material performance of thin film membranes requires enhanced transport properties coupled with better control of the mechanical characteristics to avoid premature failure of the film. Thus, morphology is a key parameter when developing and evaluating novel membrane materials. Microscopy offers unique advantages for nano-scale characterization of thin film membrane interfaces and morphologies. In this study, the interface junction of BPMs was evaluated using scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). BPMs were fabricated using (1) hot pressing lamination, (2) bench-scale solution casting, and (3) roll-to-roll sequential casting (R2R). Both commercial and in-house fabricated ion exchange membranes were used in the BPMs. The BPMs were comprised of a cation exchange membrane and an anion exchange membrane with a catalyst layer sandwiched in between. Cross sectional SEM and EDX images of the membrane interface junction were compared among the different fabrication techniques and materials. The bench cast catalyst layers were nonuniform compared to the R2R and hot pressed membranes, demonstrating the importance of precise catalyst application conditions. Different thicknesses of the BPMs and individual membrane layers revealed that polymer solution concentration needs to be optimized during manufacturing. This work shows that microscopy can identify key processing parameters that affect BPM interface junction quality at the microscale to enable manufacturing of high performance BPMs.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Enabling Roll-to-Roll Manufacturing of Bipolar Membranes Using Microscopy

36 MATERIALS SCIENCE↗

DOE OSTI2025

Advancing Reel-to-Reel Inspection Techniques for Long HTS Conductors: Comparison and Innovations

The continuous advancement of high-temperature superconductor (HTS) technologies has greatly accelerated the development and deployment of HTS applications. Among the critical tools supporting these advancements are reel-to-reel (R2R) critical current (I c ) measurement techniques, which are extensively used by both manufacturers and end users to characterize long-length REBCO conductors. These techniques play a vital role in quality assurance and quality control (QA/QC), ensuring the reliability and performance of HTS conductors and applications throughout the production cycle. We have developed a range of in-house devices for R2R measurements at the University of Houston and Princeton Plasma Physics Laboratory. These include one-dimensional (1D) scan using a magnetic circuit (MC) and two-dimensional (2D) magnetic field mapping systems based on scanning probe array microscope (SPAM) or scanning probe microscopy (SPM). Each technique offers distinct advantages: the MC system provides ultra-fast scanning speeds, ideal for rapid inspection in large-scale industrial production; the high-resolution SPM delivers detailed insights for conductor research and development; and the SPAM, with its simpler mechanical setup, can be upgraded for higher field and lower temperature conditions with a balanced 2D resolution. Here we compared the magnetization and detection capabilities of these techniques through experiments on rare-earth barium copper oxide (REBCO) coated conductor samples, with data analysis supported by numerical simulations. Based on our comprehensive comparative studies, we propose enhancements for each measurement system and provide guidelines for selecting the optimal technique combinations to meet specific application requirements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Efficient sensitivity analysis of the thermal profile in powder bed fusion of metals using hypercomplex automatic differentiation finite element method

Rapid cyclic temperature fluctuation occurring in powder bed fusion of metals using a laser beam (PBF-LB/M) influences the formation of flaws in printed parts. Consequently, there is a pressing need to enhance the quality of printed parts by developing innovative methodologies that can predict thermal histories and help uncover the intricate relationships between process parameters and thermal profiles. Sensitivity Analysis (SA) emerges as an essential tool for this, offering the potential for process optimization and enhanced quality control. Nonetheless, conventional SA methodologies often incur in excessive computational costs and potential numerical approximation errors. Here, to address this technical challenge, we present a novel method for SA that integrates the HYPercomplex-based Automatic Differentiation (HYPAD) technique with transient thermal simulations conducted via the finite element method (FEM). Leveraging this methodology, we efficiently and accurately perform SA for PBF-LB/M processes in a post-processing step. Compared to traditional methods like Finite Differences (FD), HYPAD-FEM required 96 % less computational time for obtaining sensitivities for 22 process parameters, under a comparative study conducted within the context of the 2018–02 AM benchmark of the National Institute of Standards and Technology. In summary, HYPAD-FEM offers superior efficiency and accuracy in SA over conventional methods, delivering the best sensitivity of a model without the need for step-size selection and problem or parameter-based implementations.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A methodology for selection of solid desiccants in energy recovery ventilators

Controlling indoor humidity levels is essential for maintaining acceptable indoor air quality in buildings. The use of energy recovery ventilators (ERVs) is an energy-efficient way to regulate indoor air humidity. Fixed-bed regenerators and rotary wheels are widely used ERVs because of their high sensible and latent effectiveness. These ERVs are made of desiccant-coated substrates, which enable them to transfer moisture between the supply and exhaust air streams. However, the moisture transfer ability of ERVs depends on the physiochemical and sorption properties of desiccants. Extensive, full-scale experiments are required to determine the best desiccant material for these systems. This paper presents a simplified method of selecting suitable desiccant materials for ERVs. The methodology involves important characterization methods, literature correlations for performance prediction, and cost-effective testing methods prior to full-scale testing, and full-scale test methods are discussed in detail. Furthermore, the performance of a few newly derived materials is evaluated and compared with that of conventional desiccants such as silica gel and molecular sieves. The highest latent effectiveness was obtained for composite of super absorbent polymer (SAP) with potassium formate (SAP-HCO2K-50 %), all-polymer porous solid desiccant (APPSD) and metal organic framework (MOF)–MIL–101 (Cr), followed by activated carbon fibre felt (ACFF) Silica sol-LiCl30, SAP, silica gel, MOF–303, and molecular sieve. Researchers and manufacturers would benefit from the proposed methodology and presented data in developing new desiccant materials for ERV applications.

Energy recovery↗

DOE OSTI2024

Atmosphere Effects in Laser Powder Bed Fusion: A Review

The use of components fabricated by laser powder bed fusion (LPBF) requires the development of processing parameters that can produce high-quality material. Manipulating the most commonly identified critical build parameters (e.g., laser power, laser scan speed, and layer thickness) on LPBF equipment can generate acceptable parts for established materials and moderately intricate part geometries. The need to fabricate increasingly complex parts from unique materials drives the limited research into LPBF process control using underutilized parameters, such as atmosphere composition and pressure. As presented in this review, manipulating atmosphere composition and pressure in laser beam welding has been shown to expand processing windows and produce higher-quality welds. The similarities between laser beam welding and laser-based AM processes suggest that this atmosphere control research could be effectively adapted for LPBF, an area that has not been widely explored. Tailoring this research for LPBF has significant potential to reveal novel processing regimes. This review presents the current state of the art in atmosphere research for laser beam welding and LPBF, with a focus on studies exploring cover gas composition and pressure, and concludes with an outlook on future LPBF atmosphere control systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Equipment List Comparing Balance of Plant Containing a Heat Pump against a Reference Electricity Generating Plant

Approximately two-thirds of U.S. energy consumption in the industrial and transportation sectors relies on fossil fuels. These sectors require high-quality heat, i.e., thermal energy at very high temperatures, for molecular transformation processes. The Integrated Energy Systems (IES) program aims to assess the economic potential of utilizing nuclear-grade heat from Advanced Reactors (ARs) to meet the high-quality heat demands. By having industrial processes (IPs) supplied with nuclear-generated heat, manufacturers could benefit from more stable and potentially lower energy costs, reducing reliance on volatile fossil fuel markets. The main outcome of the FY24 research was the thermodynamic assessment and gap analysis of steam generation for IP applications. The study completed in June 2024 demonstrated that the required steam temperatures could be achieved by integrating a heat pump into an AR power plant. After identifying the thermal demands of target IPs, multiple balance of plant configurations for the Xe-100 reactor by X-energy, incorporating a heat pump, were analyzed. Their technical feasibilities were assessed, including the design of suitable axial compressors for these applications. Comparative performance analysis showed that thermal efficiency alone is insufficient to evaluate system suitability. To address this, a new indicator (heat factor) was introduced in the report released in September 2024 to quantify the low-quality thermal power needed to produce one unit of high-quality heat for the IP. Results showed that integrating heat pumps into Rankine cycles enables higher steam temperatures, though at the expense of increased thermal energy input. This report builds upon and completes the foundational work previously undertaken. It focuses on the design of two Balance of Plant (BOP) configurations, both based on Rankine energy conversion cycles: “Case 1”, which involves electricity generation only, and “Case 2”, which combines electricity and high-temperature heat generation for industrial use. For each configuration, a comprehensive equipment list was developed, detailing all major components such as turbines, compressors, heat exchangers, pumps, and control systems. These lists will serve as the basis for future comparative cost analyses, with the goal of assessing the number and type of components required to integrate a heat pump into the Rankine cycle and to establish a heat transport system capable of delivering thermal energy from the nuclear plant to an industrial facility. Using the constitutive equations presented in the June 2024 milestone, the operating conditions of all BOP components for both “Case 1” and “Case 2” were evaluated. These parameters—such as temperature, pressure, mass flow rate, and steam quality—served as the basis for calculating the associated thermal and mechanical power flows. The net power required from the heat pump to raise the steam temperature to the target level was also determined. The thermodynamic performance of the configuration was then assessed using the heat factor metric. The key outcome of this analysis is a comparative table that presents the equipment that was used in the “Case 1” and “Case 2” configurations. This study offers a preliminary comparison of the two designs, providing insight into the impact of integrating a heat pump in terms of component requirements and thermal efficiency. This equipment list, together with the evaluated operating conditions, also serves as a foundation for the economic analyses scheduled for the current fiscal year.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Accelerated Aging Humidity Chamber for Nuclear Grade HEPA Filter Media

A unique accelerated aging humidity chamber for simulating the natural aging process of nuclear grade high efficiency particulate air (HEPA) filter media is being designed, implemented, and tested. The nuclear industry currently lacks information regarding the shelf life and service life of HEPA filter media. The Department of Energy recommends disposing of HEPA filters 10 years after the manufacture date for filters operated under dry conditions. Studies have shown the tensile strength and water repellency of HEPA filter media diminish with age. The chamber's principal function is to sustain an elevated relative humidity condition for an extended duration specified by the Arrhenius aging model. To accomplish this, various design parameters were established: (1) consistently achieve uniform humidity conditions within the chamber to equally expose media sheets, (2) ensure the chamber is sufficiently sealed to mitigate the uncontrolled infiltration of air, (3) confidently secure the media sheets to avert the introduction of unnecessary stressing/creasing, (4) fabricate the chamber from clear polycarbonate material to allow inspection of the media sheets, (5) provide a safe and ergonomic design for personnel, (6) ensure the chamber design is replicable and relatively easy to fabricate/assemble. A humidity source, fan, PID controller, humidity and temperature transmitters, and data loggers are required for proper operation and control of the chamber. The humidity source must accommodate target values up to 95% relative humidity throughout the chamber. The three humidity and temperature transmitters are strategically spaced throughout the chamber to ensure uniform conditions. The 10 cubic feet per minute (CFM) fan selected intends to accomplish the desired air change rate inside the chamber of approximately 20 air changes per hour (ACH). The 2 plenums on the upper and lower portions of the chamber utilize a perforated design to uniformly distribute air, promote air mixing, and control the air velocity entering the chamber. Industrial blueprint hanging clamps are being retrofitted to be seated within the chamber drawers and firmly secure the nuclear grade filter media. The aged media will be evaluated using autopsy methodology, and the results obtained intend to help clarify the useful life of nuclear grade HEPA filters. Nuclear grade high efficiency particulate air (HEPA) filters are defined as disposable, extended-media, dry-type filters with a rigid casing enclosing the full depth of the pleats and have a minimum particle removal efficiency of 99.97%. [1] - HEPA filters are constantly exposed to stressors and subsequently have been shown to degrade as the filter ages. Properties such as tensile strength and water repellency, along with others, are negatively impacted. [2] - Due to the scarcity of naturally aged HEPA filters available, it is crucial to develop accelerated aging methods which effectively mimic the natural degradation effects. - After accelerated aging, the filters are subject to testing in the Axial Flow Large Scale Test Stand (ALSTS) and other analysis techniques such as the same qualification tests performed directly after being manufactured. - Quality data is necessary for future decisions regarding the lifetime of nuclear grade HEPA filters. - The objective is to develop a prototype accelerated aging humidity chamber for nuclear grade HEPA filter media. The chamber should expose the media to commonly occurring stressors to expedite the degradation process caused by aging. PID yields reliable and reproducible results: - CFD model correlates well with actual performance; - Further analysis is needed to complete characterization; - Future work for the chamber is still to be completed. The data shown in Figure 5 and Table 1 indicate the system is functioning as designed. As can be determined from the system response evaluation in Table 1, the PID controller is yielding reliable and reproducible results at each set point. As the set point increases, the time constant and 20% settling time increase accordingly. From the results in Table 1, it stands to reason that the CFD model correlates well with the actual performance of the system. Each system response parameter for the 90%RH* CFD model is slightly lower than the parameters collected from the physical model tested at an equivalent set point. This is to be expected considering the inlet in the CFD model is a constant supply of water vapor, whereas the physical model uses a PID controller to monitor the amount of water vapor needed and reacts accordingly. More analysis is still to be done on the prototype chamber. A pressure test will be conducted in order to determine the hourly leak rate of the chamber. This test will involve constant air flow into the chamber until the desired pressure is reached. A uniformity test will also be conducted in order to ensure each filter medium is being exposed to equivalent relative humidity levels. This test will involve an array of humidity meters strategically oriented inside the chamber to record any possible gradients. Future work for the chamber includes dehumidification abilities, tests while fully loaded with filters, and temperature control. Once completed, the autopsy team at Institute of Clean Energy Technology will conduct necessary accelerated aging studies as needed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Performance of low-cost indoor air quality monitors for PM 2.5 and PM 10 from residential sources

Advances in particle sensor design and manufacturing have enabled the development of low-cost air quality monitors (LCMs). Here, the sensors use light scattering to estimate mass concentration and thus require evaluation for aerosols of varied composition and size distribution. We tested the performance of six LCMs designed for home use and having a retail price under US$300 in October 2018. We assessed their performance by comparing their output to reference PM 2.5 and PM 10 measurements from 21 common residential sources and from infiltrated outdoor PM 2.5 . Reference data were obtained by using gravimetric measurements to adjust time-resolved output from an aerosol spectrometer with both electrical mobility and optical particle sensors. Compared by linear regression to reference measurements, LCMs had negative intercepts and slopes of 1–2 for infiltrated outdoor PM 2.5 . Semi-quantitative responses (~50–200% of actual PM 2.5 ) were obtained for varied aerosols including minerals (ultrasonic humidifier, vacuuming, test dust); combustion products (incense, mosquito coil, extinguished candles); microwave popcorn; and cooking involving frying or grilling. LCMs had low or no response to sources for which all mass was in particles smaller than 0.25 μm, including steady candle flames and cooking without frying or grilling. PM 10 data from LCMs was more variable than PM 2.5 .

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Crowd-Sourced Data and Analysis Tools for Advancing the Chemical Vapor Deposition of Graphene: Implications for Manufacturing

Industrial production of graphene by chemical vapor deposition (CVD) requires more than the ability to synthesize large domain, high-quality graphene in a lab reactor. The integration of graphene in the fabrication process of electronic devices requires the cost-effective and environmentally friendly production of graphene on dielectric substrates, but current approaches can only produce graphene on metal catalysts. Sustainable manufacturing of graphene should also conserve the catalyst and reaction gases, but today the metal catalysts are typically dissolved after synthesis. Progress toward these objectives is hindered by the hundreds of coupled synthesis parameters that can strongly affect CVD of low-dimensional materials and poor communication in the published literature of the rich experimental data that exists in individual laboratories. We report here on a platform, "graphene recipes for synthesis of high quality material" (Gr-ResQ: pronounced graphene rescue), which includes powerful new tools for data-driven graphene synthesis. At the core of Gr-ResQ is a crowd-sourced database of CVD synthesis recipes and associated experimental results. The database captures similar to 300 parameters ranging from synthesis conditions such as a catalyst material and preparation steps, to ambient lab temperature and reactor details, as well as resulting Raman spectra and microscopy images. These parameters are carefully selected to unlock the potential of machine-learning models to advance synthesis. A suite of associated tools enable fast, automated, and standardized processing of Raman spectra and scanning electron microscopy images. To facilitate community-based efforts, Gr-ResQ provides tools for cyber-physical collaborations among research groups, allowing experiments to be designed, executed, and analyzed by different teams. Gr-ResQ also allows publication and discovery of recipes via the Materials Data Facility, which assigns each recipe a unique identifier when published and collects parameters in a search index. We envision that this holistic approach to data-driven synthesis can accelerate CVD recipe discovery and production control and open opportunities for advancing not only graphene but also many other 1D and 2D materials.

36 MATERIALS SCIENCE↗