Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “custom devices”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

In-situ Characterizations of Microstructural Degradation of Perovskite Solar Cells

Rapid progress has been achieved in perovskite solar cells (PSCs), and their efficiencies have improved from 3.8 % to 24.2 % in less than a decade. With low-cost processing, PSCs have shown exciting photovoltaic (PV) properties, such as effective optical absorption, a long carrier lifetime, and unique defect tolerance. While recent studies demonstrated improved stability up to 100 days, PSC technology is still challenged to meet the stringent industry requirements for commercialization. Despite considerable efforts, the underlying physical mechanisms for the inferior stability of PSCs are not well understood. One reason for this divergence is that many established measurement techniques (e.g., quantum efficiency, photoluminescence) probe the properties on length scales far greater than that of electronic and/or structural inhomogeneity (i.e., < 1 μm near grain boundaries) and therefore characterize convoluted and/or averaged properties. Ion/electron beam-based techniques have been extensively used to access the microstructures of PSCs, enabling atomic/nanoscale structural, chemical, optical, and electrical characterizations. For example, focused ion beam (FIB) milling produces an atomically smooth surface that minimizes the artifacts attributed to the surface roughness. FIB techniques can also create a well-defined cross-section of PSCs without mechanical damage in a physical cleaving sample preparation. While powerful, there are some concerns about possible beam damage of inorganic-organic perovskites via chemical-bond breakage and local heating. This project aims to comprehensively understand how the microstructural/interfacial properties of PSCs (e.g., Methylammonium Lead Iodide [MAPbI 3 ]) are modified under the irradiating ion beams. Specifically, we investigate the sub-surface properties of PSCs before and after Ar-ion beam injections. Kelvin probe force microscopy (KPFM) measures the contact potential differences (CPDs). Photoluminescence (PL) microscopy in conjunction with Finite-Difference Time-Domain (FDTD) simulations infers the formation of a “dead layer” (< 15 nm) on the subsurface of MAPbI 3 during Ar+ milling processes while preserving the initial bulk properties. The x-ray photoemission spectroscopy (XPS) confirms this modified surface is a lead-rich and iodine-deficient surface. We initiate customizing in-situ measurement setup while measuring the local optical and electrical properties of PSC under thermal (cooling, heating) and light stressors. Our results provide in-depth knowledge of the ion-beam impact on metal-halide perovskites and how this modified sub-surface impacts their properties under accelerated stressors of light and heat. Intensive Monte Carlo simulations of an electron beam interacting with PSCs provide the beam energy distribution in PSCs, proposing possible measurement conditions of using e-beam with minimizing beam damage. Our in-situ measurement platform can accommodate the diverse architecture of PSC devices for studying deterioration mechanisms under mixed environmental stressors.

14 SOLAR ENERGY↗

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

bayesian structural time series↗

A Scalable and Distributed Algorithm for Managing Residential Demand Response Programs using Alternating Direction Method of Multipliers (ADMM)

For effective engagement of residential demand-side resources and to ensure efficient operation of distribution networks, we must overcome the challenges of controlling and coordinating residential components and devices at scale. To overcome this challenge, we present a distributed and scalable algorithm with a three-level hierarchical information exchange architecture for managing the residential demand response programs. First, a centralized optimization model is formulated to maximize community social welfare. Then, this centralized model is solved in a distributed manner with alternating direction method of multipliers (ADMM) by decomposing the original problem to utility-level and house-level problems. The information exchange between the different layers is limited to the primary residual (i.e., supply-demand mismatch), Lagrangian multipliers, and the total load of each house to protect each customer’s privacy. Simulation studies are performed on the IEEE 33 bus test system with 605 residential customers. The results demonstrate that the proposed approach can save customers’ electricity bills and reduce the peak load at the utility level without much affecting customers’ comfort and privacy. Finally, a quantitative comparison of the distributed and centralized algorithms shows the scalability advantage of the proposed ADMM-based approach, and it gives benchmarking results with achievable value for future research works.

24 POWER TRANSMISSION AND DISTRIBUTION↗

In-line, High-Throughput Quality Monitoring for Fuel Cell and Electrolyzer Components Based on Transmission and Reflection Imaging

During the manufacturing of fuel cell and electrolyzer membranes and membrane electrode assemblies (MEAs), real-time, in-line, high-throughput optical-based quality monitoring methods are essential for detecting defects and monitoring thickness variations, thus improving the performance and increasing the durability of fuel cell and electrolyzer in the hydrogen industry. For the MEAs with very opaque coatings, optical transmission-based imaging has been developed and applied in the Roll-to-Roll system using a flashlight and a high-sensitivity CCD camera. We observed high signal-to-noise ratio images while the Roll-to-Roll system ran at 5 ft/min. The entire sample image could quickly be recovered from the discrete frames using customized Python codes for automatic frame cropping and stitching. We detected significant non-uniformities in our experimental MEAs specimen. For fuel cell and low-temperature electrolysis (LTE) transparent membranes, we used optical reflectance hyperspectral imaging with interference fringe-based thickness mapping. We set up a hyperspectral camera to measure various rolls of commercial membranes. The measurement results are analyzed to find the thickness distribution of each roll and to check for defects. Transmission and reflection imaging-based quality monitoring techniques demonstrated in this project can be widely used in the mass production environment to improve the production yield and performance of hydrogen devices.

DIRECT ENERGY CONVERSION,ENGINEERING↗

Portable Distortion Free Large Solid Angle Coverage Detector

Neutron single crystal diffractometers require large solid angle coverage for optimum performance. This can be achieved by tiling flat detectors in a cylindrical or spherical geometry, but results in large gaps in detector coverage and parallax distortion. The detector edges exhibit degraded resolution, distortion, and gamma rejection. Since the detector edge regions are a significant fraction of the detector active area, they must be removed from the experimental data set, requiring extra beam time to collect enough analysis data. A spherical detector with a continuous surface would effectively address this issue while eliminating most boundary ‘dead’ areas. Here we report on the development of a novel hemispherical shaped neutron detector using seamlessly tiled readout modules to form the desired shape. The heart of the detector is a specially developed curved neutron scintillator coupled to high resolution silicon photomultiplier (SiPM) Anger cameras via custom made fiber optic tapers (FOTs). The detector has been assembled and initial tests have been conducted at the High Flux Isotope Reactor (HFIR) beamlines at Oak Ridge National Laboratory (ORNL). Here, in this work, we describe details of the scintillator design, fabrication and characterization, evaluation of individual detector modules, the details of the detector design implementation, and evaluation of the assembled detector at ORNL beamlines.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Challenges and Opportunities in Decarbonizing the U.S. Energy System

The United States has pledged to develop a 100% carbon-free electric power system by 2035 and a net-zero-emissions economy by 2050. While important advancements have been made in the scale, performance, and economics of clean energy technologies, meeting the nation's ambitious goals will not only require their deployment at scale, but also additional innovation and effective integration of different solutions. Technological developments across the broad suite of low-carbon energy solutions are advancing rapidly, with ongoing innovations in renewable electricity generation, industrial processes, and energy-saving technologies and services, including LED lighting, induction heating, electric vehicles, energy storage solutions, and mobility as a service, plus smart devices, controls, and more efficient and smart buildings. Combining renewable electricity with biotic and abiotic pathways to produce chemicals, fuels, and materials promises to deliver new solutions. Grid-interactive buildings and communities, integrating transportation infrastructure and vehicles, are likely to be significant components of any zero-carbon energy strategy. Low-carbon industrial manufacturing will also make strong contributions to a net-zero economy. While the technical prospects appear promising, variations in the state of infrastructure, jurisdictional and social equity, pollution, economic and socio-cultural constraints, energy resource availability, and supply chain dynamics found in different locations present a range of challenges and demand customized solutions. This paper provides a critical review and offers new insights into the technical, infrastructure, analytic, political, and economic challenges faced in translating the nation's ambitious net-zero-emissions goals into feasible and reliable implementation action plans.

circular economy↗

A Bilevel Voltage Regulation Operation for Distribution Systems With Self-Operated Microgrids

The emerging of microgrids in distribution systems has significantly enhanced the resilience of power grids. However, the operators of a distribution system and microgrids therein can be different and have accessibility to different devices. To model the operation of such a grid, this work proposes a bilevel formulation and probes into the voltage regulation operation, considering the interaction between different systems. The proposed bilevel formulation considers the cooperation of active energy resources (AER), transformer tap-changers, and capacitor banks that are controlled by different operators. To facilitate the solution time of the target bilevel optimization, the lower-level problems with different objectives are modeled using deep neural networks (DNNs) which are then converted into a set of constraints. Hence, the bilevel problem can be reformed to a single-level problem. Lastly, the proposed solution procedures are validated using a customized joint system constructed by the IEEE 123-bus system and a real distribution system in Iowa. According to the numerical validation results, the solution time of the proposed nonlinear activation function based DNN model is 69 times faster than other methods in solving voltage regulation with a bilevel structure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Preparation of Smart Materials by Additive Manufacturing Technologies: A Review

Over the last few decades, advanced manufacturing and additive printing technologies have made incredible inroads into the fields of engineering, transportation, and healthcare. Among additive manufacturing technologies, 3D printing is gradually emerging as a powerful technique owing to a combination of attractive features, such as fast prototyping, fabrication of complex designs/structures, minimization of waste generation, and easy mass customization. Of late, 4D printing has also been initiated, which is the sophisticated version of the 3D printing. It has an extra advantageous feature: retaining shape memory and being able to provide instructions to the printed parts on how to move or adapt under some environmental conditions, such as, water, wind, light, temperature, or other environmental stimuli. This advanced printing utilizes the response of smart manufactured materials, which offer the capability of changing shapes postproduction over application of any forms of energy. The potential application of 4D printing in the biomedical field is huge. Here, the technology could be applied to tissue engineering, medicine, and configuration of smart biomedical devices. Various characteristics of next generation additive printings, namely 3D and 4D printings, and their use in enhancing the manufacturing domain, their development, and some of the applications have been discussed. Special materials with piezoelectric properties and shape-changing characteristics have also been discussed in comparison with conventional material options for additive printing.

36 MATERIALS SCIENCE↗

Demonstrating Load-Shaping Capabilities of Cost Minimizing Heat Pump Water Heater Controls with Varying Price Profiles

Increased penetration of photovoltaics and electrification of traditionally gas appliances are exacerbating existing challenges in cost-effectively balancing electricity grid supply and demand. Decarbonization without incurring expensive transmission and distribution system capacity increases requires shifting building loads from peak demand times to peak renewable production times. Grid operators are evaluating new ways of encouraging load shifting, including using time-varying price structures to provide a financial incentive. If devices incorporate price-responsive controls, a price profile could be designed to yield a wide variety of load curves as needed to optimize grid functionality. Heat pump water heaters (HPWHs) are an ideal device for price-responsive controls because the storage tank enables them to optimize the timing of electricity consumption without impacting hot water delivery service. This paper presents work demonstrating how price-responsive controls for HPWHs can provide different load profiles, as needed to stabilize the grid, in response to different price profiles. HPWH manufacturers now include web API and CTA-2045 communication capabilities which enable sending load shaping control signals. Pilot studies and preliminary programs have utilized these capabilities with uniform control strategies to reduce 4-9 PM electricity consumption. However, no studies have developed flexible controls capable of both a) responding to constantly varying price profiles and b) customizing logic to match the needs of each HPWH. Berkeley Lab's CalFlexHub project is pioneering price-driven load flexibility by developing and deploying cost-minimizing controls utilizing setpoint setting signals for fleets of HPWHs in response to varying price profiles. Control development is based on simulations using the Flexible Heat Pump Water Heater Performance Predictor which captures the control decisions of a residential, integrated HPWH manufacturer’s on-board controller. The proposed cost-reducing controls respond to constantly changing price profiles, providing the ability to change the price profile to generate load curves as needed to maintain grid stability. Preliminary simulations studying the load shaping capabilities of price-responsive controls on a fleet of 60 HPWHs have demonstrated an average of a) 135.4% increases in load during low-price periods, b) >36.8% reductions in electricity peak-price period, and c) 6.2% electricity cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Equilibrium vapor pressure properties for absorbent and adsorbent materials

Sorption devices are important tools for the efficient utilization of fuels and waste heat. Amid a tremendous diversity of cycles and applications, all sorption systems have an equilibrium vapor pressure that depends on the sorbent temperature and composition. The vapor pressure properties of working fluids are reported in the literature in a variety of ways, which impedes wide-ranging cross comparisons or screening studies for novel applications. This work compiles equilibrium vapor pressure properties for 123 liquid absorbents with 31 absorbates and 139 solid adsorbents with 16 adsorbates. The adsorption pairs are represented with six functional forms. Additionally, most of the absorption pairs are represented with 10 functional forms, plus several that are represented with custom empirical equations. Because the functional forms used in the literature vary widely, in this work each functional form was generalized. This paper is designed to facilitate comparisons of working fluid properties for screening studies, provide a quick reference to existing research, and present a framework for standardizing the reportage of vapor pressure equilibrium data for existing and future working pairs.

36 MATERIALS SCIENCE↗

A custom 3D printed paddlewheel improves growth in flat panel photobioreactor

One of the main challenges with using flat panel photobioreactors for algal growth is uneven mixing and settling of cells in corners, especially when bubbling is the only method used for mixing. Here, in order to improve mixing in our flat panel reactor, we designed a custom paddlewheel. Paddlewheels are frequently used in outdoor algae raceway ponds to improve mixing and we are taking advantage of the same principle for mixing in the reactor. The paddlewheel is easily integrated into our PSI FMT150 1‐L flat panel photobioreactor and is printed on a 3D printer using high temperature poly lactic acid (HT‐PLA). With the inclusion of an annealing step, the paddlewheel is autoclavable. Addition of the paddlewheel in the reactor minimized cell settling and improved algal growth, as evidenced by a nearly 40% increase in oxygen production rates. Nutrient dispersion and utilization in the culture was also improved as evidenced by a corresponding 38% decrease in CO 2 concentration. The paddlewheel device presented here is a cost‐effective method for improving algal growth in a flat panel photobioreactor.

09 BIOMASS FUELS↗

Invited: Software defined accelerators from learning tools environment

Next generation systems, such as edge devices, will need to provide efficient processing of machine learning (ML) algorithms along several metrics, including energy, performance, area, and latency. However, the quickly evolving field of ML makes it extremely difficult to generate accelerators able to support a wide variety of algorithms. At the same time, designing accelerators in hardware description languages (HDLs) by hand is hard and time consuming, and does not allow quick exploration of the design space. In this paper we present the Software Defined Accelerators From Learning Tools Environment (SODALITE), an automated open source high-level ML framework-to-verilog compiler targeting ML Application-Specific Integrated Circuits (ASICs) chiplets. The SODALITE approach will implement optimal designs by seamlessly combining custom components generated through high-level synthesis (HLS) with templated and fully tunable Intellectural Properties (IPs) and macros, integrated in an extendable resource library. Through a closed loop design space exploration engine, developers will be able to quickly explore their hardware designs along different dimensions.

High-Level Synthesis, Accelerators, Hardware-Softw↗

The Orbitron: A crossed-field device for co-confinement of high energy ions and electrons

To explore the confinement of high-energy ions above the space charge limit, we have developed a hybrid magnetic and electrostatic confinement device called an Orbitron. The Orbitron is a crossed-field device combining aspects of magnetic mirrors, magnetrons, and orbital ion traps. Ions are confined in orbits around a high-voltage cathode with co-rotating electrons confined by a relatively weak magnetic field. Experimental and computational investigations focus on reaching ion densities above the space charge limit through the co-confinement of electrons. The experimental apparatus and suite of diagnostics are being developed to measure the critical parameters, such as plasma density, particle energy, and fusion rate for high-energy, non-thermal plasma conditions in the Orbitron. Initial results from experimental and computational efforts have revealed the need for cathode voltages on the order of 100–300 kV, leading to the development of a custom high voltage, ultra-high vacuum bushing rated for 300 kV.

Materials Science↗

Analysis of Reactive Power Load Modeling Techniques for PV Impact Studies [Slides]

The increasing availability of advanced metering infrastructure (AMI) data has led to significant improvements in load modeling accuracy. However, since many AMI devices were installed to facilitate billing practices, few utilities record or store reactive power demand measurements from their AMI. When reactive power measurements are unavailable, simplifying assumptions are often applied for load modeling purposes, such as applying constant power factors to the loads. The objective of this work is to quantify the impact that reactive power load modeling practices can have on distribution system analysis, with a particular focus on evaluating the behaviors of distributed photovoltaic (PV) systems with advanced inverter capabilities. Quasi-static time-series simulations were conducted after applying a variety of reactive power load modeling approaches, and the results were compared to a baseline scenario in which real and reactive power measurements were available at all customer locations on the circuit. Overall, it was observed that applying constant power factors to loads can lead to significant errors when evaluating customer voltage profiles, but that performing per-phase time-series reactive power allocation can be utilized to reduce these errors by about 6x, on average, resulting in more accurate evaluations of advanced inverter functions.

14 SOLAR ENERGY↗

Tamper-Indicating Enclosures with Visually Obvious Tamper Response (Final Project Report)

Sandia National Laboratories is developing a new method for detecting penetration of tamper - indicating enclosures (TIEs). This method incorporates the use of "bleeding" materials (analogous to visually obvious, colorful bruised skin that doesn't heal) into the design of TIEs. As designed, it will allow inspectors to use simple visual observation to detect attempts to penetrate the external surfaces of a TIE, without providing adversaries the ability to repair damage. A material of this type can enhance tamper indication of current TIEs used to support treaty verification regimes. Current TIE inspections are time - consuming and rely on subjective visual assessment by an inspector, equipment such as eddy current or camera devices, or involve approaches that may be limited due to application environment. The complexities and requirements that volumetric sealing methods (or TIEs) must address are: (1) enclosures that are non - standard in size/shape; (2) enclosures that may be inspectorate - or facility - owned; (3) finding tamper attempts that are difficult and time consuming for an inspector to locate; (4) enclosures that are reliable and durable enough to survive the conditions that exist in the operating environment (including facility handling); and (5) methods that prevent adversaries from repairing penetrations. Early project R&D [1] focused on encapsulated transition metals. Due to the challenges associated with the transition metal - based approach, a mitigation approach was investigated resulting in two separate research paths — one that involves fabricating custom TIE molds that meet the specific (size and shape) needs of safeguards equipment a nd one that can be deployed as a sprayed on or painted coating to an existing TIE or surface. The "custom mold" approach is based on creating thin layers of materials that , when penetrated, expose an inner material to O 2 which causes an irreversible color change. The "in-situ coating" approach is based on applying a sensor solution containing color changing microcapsules that bleed when the microcapsule is ruptured. The anticipated benefits of this work are passive, flexible, scalable, robust , cost-effective TIEs with visually obvious responses to tamper attempts. This provides more efficient and effective monitoring , as inspectors will require little or no additional equipment and will be able to detect tamper without extensive time - consuming visual examination. Applications include custom TIEs (cabinets , equipment enclosures or seal bodies ), or spray-coating/painting onto facility-owned items, walls or structures, or circuit boards. The paper describes research and testing completed to-date on the method and integration of select system components.

36 MATERIALS SCIENCE↗

SODA: a New Synthesis Infrastructure for Agile Hardware Design of Machine Learning Accelerators

Next generation systems, such as edge devices, will have to provide efficient processing of machine learning (ML) algorithms along several metrics, including energy, performance, area, and latency. However, the quickly evolving field of ML makes it extremely difficult to generate accelerators able to support a wide variety of algorithms. At the same time, designing accelerators in hardware description languages (HDLs) by hand is hard and time consuming, and does not allow quick exploration of the design space. This paper discusses the SODA synthesizer, an automated open source high-level ML framework-to-Verilog compiler targeting ML Application-Specific Integrated Circuits (ASICs) chiplets based on the LLVM infrastructure. The SODA synthesizers will allow implementing optimal designs by combining templated and fully tunable IPs and macros, and fully custom components generated through high-level synthesis. All these components will be provided through an extendable resource library, characterized with both commercial and open source logic design flows. Through a closed loop design space exploration engine, developers will be able to quickly explore their hardware designs along different dimension

Minutoli, Marco↗

Investigation of Nanoparticle Degradation in Hydrogen Fuel Cell Systems through Automated Electron Microscopy

Proton exchange membrane fuel cells (PEMFC) are promising devices for the deployment of hydrogen-powered heavy-duty vehicles, providing a higher efficiency for similar driving range and fueling time than the existing ones. However, PEMFCs still encounter durability challenges mainly due to catalyst degradation in the cathode. Mitigating these performance losses requires a better understanding of the degradation mechanisms under heavy-duty accelerated stress tests (ASTs) [1]. Scanning transmission electron microscopy (STEM) combined with energy dispersive X-ray spectroscopy (EDS) are key tools for the analysis of Pt and PtCo nanoparticle size, spatial distribution and composition [2]. Electron tomography is also used to determine the rate and type of degradation of catalyst nanoparticles as a function of their position on the carbon support. In this work, automated data acquisition software, paired with a custom Python code, have been used to study the effect of different accelerated stress tests (ASTs) on nanoparticle coarsening [2]. Figure 1 shows high-angle annular dark-field (HAADF)-STEM images and EDS maps comparing the cathodes of membrane electrode assemblies (MEAs) following an electrocatalyst AST performed under H2/N2 with that of the heavy-duty AST performed under H2/air. We will discuss how AST conditions affect considerably the spatial distribution of the nanoparticles across the electrode between the membrane and microporous layer. Although the median particle size increased more in the MEA aged under the heavy-duty AST, as determined using a high-throughput image analysis, the quantitative EDS measurements demonstrate that the electrocatalyst AST resulted in more Pt and Co dissolution from the cathode, which is another important indicator of electrocatalyst degradation. We will further present the impact of the relative humidity (% RH) on the degradation mechanisms demonstrated using the same approach. Electron tomography has been used to distinguish the Pt nanoparticles residing on the carbon support surface (exterior) from those within the pore structure (interior) in order to determine the relative stability of interior and exterior nanoparticles. As shown in Figure 2, we will compare the Pt catalyst particle size at the beginning of test (BOT) and end of test (EOT), and discuss the importance of automating the electron tomography workflow, i.e. acquisition, reconstruction, and visualization, to increase sampling and determine the standard deviation of these measurement. The outlook for utilizing low-dose cryo-tomography for limiting damage to the catalyst, support, and especially proton-conducting ionomer will also be discussed [3].

Amichi, Lynda↗

Characterization and differentiation of aluminum powders used in improvised explosive devices – Part 1: Proof of concept of the utility of particle micromorphometry

Abstract Aluminum (Al) powders are commonly used in improvised explosive devices as metallic fuels, a component of explosive mixtures. These powders can be obtained readily from industrial‐scale and consumer products, and produced using unsophisticated “kitchen chemistry” techniques. This research demonstrates the potential of automated particle micromorphometry for comparisons between known source and questioned Al powders recovered from IEDs, as well as for insight into the method of Al powder manufacture. Al powder samples were obtained from legitimate manufacturers, and 56 samples were produced “in‐house” from Al‐containing spray paints and ball‐milled Al foils. Transmitted light microscope images of Al powder particles were acquired using an automated stage with automated z‐focus; 17 size and shape parameters were measured for all particles. Approximately 37,000–2,500,000 particles/sample were analyzed using an open‐source statistical package with customized code. Dimensionality reduction was required for processing the large datasets: eight of the 17 measured variables were selected based on inspection of the correlation matrix. Data from four subsamples from each of the 56 samples produced using “in‐house” methods were analyzed using ANOVA to assess the within‐ and between‐sample variation. High within‐sample variation was noted; however, ANOVA and post‐hoc Tukey's honestly significant difference (HSD) tests demonstrated that the between‐sample variation was substantially larger than the within‐sample variation. Each sample could be differentiated from all other samples in the test set. Future experiments will focus on ways to reduce the within‐sample variation, and additional statistical and microanalytical methods to classify sources and confidently constrain the method of Al powder manufacture.

Baldaino, JenaMarie↗