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

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Material Compatibility of 3D Printed Polymer Composites with Low GWP Refrigerants

The recent development of 3D printing brings numerous opportunities to develop polymer heat exchangers with desired configurations and allows access to the new complex engineering design for better performance. To be used in the HVAC&R system, the compatibility of these materials to refrigerants needs to be thoroughly investigated and understood. This study tested the material compatibility of the printed polymer composites according to the ASHRAE Guideline 38 using metal pressure vessels. These printed parts were tested with R-134A, R-1234YF, R-1234ZE, R-1233ZD(E), and 32-3 MAF POE (10 wt.%) was used as the lubricants. The change in volume, mass, hardness, and mechanical properties was studied in detail. Different compatibility of the composites with refrigerants was observed when the composition of the composite changed. After exposure to refrigerants, the morphological and thermal properties were studied with the scanning electron microscope, thermogravimetric analysis, and differential scanning calorimetry to further reveal the influence of these refrigerants.

Li, Kai↗
DOE OSTI2022

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Image analysis reveals differences in tumor multinucleations in Black and White patients with human papillomavirus‐associated oropharyngeal squamous cell carcinoma

Background Understanding biological differences between different racial groups of human papillomavirus (HPV)‐associated oropharyngeal squamous cell carcinoma (OPSCC) patients, who have differences in terms of incidence, survival, and tumor morphology, can facilitate accurate prognostic biomarkers, which can help develop personalized treatment strategies. Methods This study evaluated whether there were morphologic differences between HPV‐associated tumors from Black and White patients in terms of multinucleation index (MuNI), an image analysis‐derived metric that measures density of multinucleated tumor cells within epithelial regions on hematoxylin–eosin images and previously has been prognostic in HPV‐associated OPSCC patients. In this study, the authors specifically evaluated whether the same MuNI cutoff that was prognostic of overall survival (OS) and disease‐free survival in their previous study, T TR , is valid for Black and White patients, separately. We also evaluated population‐specific cutoffs, T B for Blacks and T W for Whites, for risk stratification. Results MuNI was statistically significantly different between Black (mean, 3.88e–4; median, 3.67e–04) and White patients (mean, 3.36e–04; median, 2.99e–04), with p = .0078. Using T TR , MuNI was prognostic of OS in the entire population with hazard ratio (HR) of 1.71 ( p = .002; 95% confidence interval [CI], 1.21–2.43) and in White patients with HR of 1.72 ( p = .005; 95% CI, 1.18–2.51). Population‐specific cutoff, T W , yielded improved HR of 1.77 ( p = .003; 95% CI, 1.21–2.58) for White patients, whereas T B did not improve risk‐stratification in Black patients with HR of 0.6 ( p = .3; HR, 0.6; 95% CI, 0.2–1.80). Conclusions Histological difference between White and Black patient tumors in terms of multinucleated tumor cells suggests the need for considering population‐specific prognostic biomarkers for personalized risk stratification strategies for HPV‐associated OPSCC patients.

Koyuncu, Can F.↗
DOE OSTI2022

Adsorbate chemical environment-based machine learning framework for heterogeneous catalysis

Abstract Heterogeneous catalytic reactions are influenced by a subtle interplay of atomic-scale factors, ranging from the catalysts’ local morphology to the presence of high adsorbate coverages. Describing such phenomena via computational models requires generation and analysis of a large space of atomic configurations. To address this challenge, we present Adsorbate Chemical Environment-based Graph Convolution Neural Network (ACE-GCN), a screening workflow that accounts for atomistic configurations comprising diverse adsorbates, binding locations, coordination environments, and substrate morphologies. Using this workflow, we develop catalyst surface models for two illustrative systems: (i) NO adsorbed on a Pt 3 Sn(111) alloy surface, of interest for nitrate electroreduction processes, where high adsorbate coverages combined with low symmetry of the alloy substrate produce a large configurational space, and (ii) OH* adsorbed on a stepped Pt(221) facet, of relevance to the Oxygen Reduction Reaction, where configurational complexity results from the presence of irregular crystal surfaces, high adsorbate coverages, and directionally-dependent adsorbate-adsorbate interactions. In both cases, the ACE-GCN model, trained on a fraction (~10%) of the total DFT-relaxed configurations, successfully describes trends in the relative stabilities of unrelaxed atomic configurations sampled from a large configurational space. This approach is expected to accelerate development of rigorous descriptions of catalyst surfaces under in-situ conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Effect of PVD-coated chromium on the subcooled flow boiling performance of nuclear reactor cladding materials

Here we elucidate the separate effect of a thin Cr coating deposited by physical vapor deposition (PVD) on the subcooled flow boiling performance of zircaloy-4. First, we run flow boiling experiments on prototypical zircaloy-4 surfaces mimicking the scratch pattern and surface roughness of nuclear reactor claddings. Then, we PVD-coat a 0.3 µm thick chromium layer on the same exact surface and repeat the same flow boiling investigations. All experiments are run using deionized water at atmospheric pressure, flowing on a 1 × 3 cm 2 rectangular cross section channel at a rate of 1000 kg/m 2 /s and a subcooling of 10 K. We measure the average temperature of the boiling surface at increasing surface heat fluxes, covering a wide range of heat transfer regimes, from single-phase forced convection to the boiling crisis. We also record high-speed videos of the boiling process, which we postprocess to measure bubble nucleation site density, growth time, departure diameter and frequency. The surface analysis reveals that, while the chromium coating does not seem change the surface roughness and morphology, it improves surface wettability. However, it decreases the critical heat flux. The chromium coating causes an increase of nucleation temperature, bubble departure diameter and growth time, and a reduction of the nucleation site density. The concurrence of these observations indicates that a size reduction of the nucleation sites, conformally covered by the chromium coating, may be the cause of the boiling performance deterioration. We confirm this hypothesis repeating the same analysis on a FeCrAl sample prepared and tested using the same protocol as the zircaloy-4 sample, but with a different initial surface texture.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Morphological descriptors of nanoparticles: The link between atomistic structures and x-ray absorption spectra

Understanding and quantifying the morphology of nanoparticles are essential for linking their atomic structure to diverse applications and verifying theoretical models. While experimental information on the structure of nanoparticles in the size range below ∼5 nm can be extracted from x-ray absorption spectroscopy using a small number of descriptors—most commonly coordination numbers—developing an understanding of morphology descriptors from experimental data remains a challenge. Here, in this study, we introduce NanoGene, a genetic algorithm-based method for generating structurally diverse nanoparticle models guided by user-defined descriptors. We establish correlations among structural, size-related, and morphological descriptors and demonstrate how experimentally accessible parameters, such as coordination numbers, can be leveraged to infer otherwise inaccessible ones, such as the generalized coordination number or particle oblateness. Principal component and clustering analyses reveal the relative importance of descriptors, with the number of atoms emerging as a key discriminant of the nanoparticle structure. By providing both the methodology and an extensive dataset of nanoparticle geometries, this work offers a practical foundation for descriptor-based analysis and interpretation of experimental observations, bridging the gap between local atomic coordinates and global morphological characterization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Evaluation of methods for characterizing the fine particulate matter emissions from aircraft and other diffusion flame combustion aerosol sources

The U. S. Environmental Protection Agency in collaboration with the U. S. Air Force Arnold Engineering Development Complex conducted the VAriable Response In Aircraft nvPM Testing (VARIAnT) 3 and 4 test campaigns to compare nvPM emissions measurements from a variety of diffusion flame combustion aerosol sources (DFCASs), including a Cummins diesel engine, a diesel powered generator, two gas turbine start carts, a J85-GE-5 turbojet engine burning multiple fuels, and a Mini-CAST soot generator. The VARIAnT research program has conducted four test campaigns to date with the VARIAnT 3 and 4 test campaigns focusing on BC mass instrument performance, use of gas turbine engine sources for BC mass instrument calibration, and the characterization of the aerosols produced from the combustion sources. Results from both campaigns revealed agreement of about 20% between the AVL Micro-Soot Sensor, the Cavity Attenuated Phase Shift (CAPS PMSSA) monitor and the thermal-optical reference method for elemental carbon (EC), independent of the calibration source used. For the Artium LII-300, the measured mass concentrations in VARIAnT3 fall within 18% and in VARIAnT4 fall within 32% of the reference EC mass concentration when calibrated on a combustor rig in VARIAnT3 and on a LGT-60 start cart in VARIAnT4, respectively. It was also found that the three mass instrument types (MSS, CAPS PMSSA, and LII-300) can exhibit different BC to reference EC ratios depending on the emission source that appear to correlate to particle geometric mean mobility diameter, morphology, or some other parameter associated with particle geometric mean diameter (GMD) with the LII-300 showing a slightly stronger apparent trend with GMD. Systematic differences in LII-300 measured mass concentrations have been reduced by calibrating with a turbine combustion source (combustor or turbine engine). With respect to the particle size measurements made, the sizing instruments (TSI SMPS, TSI EEPS, and Cambustion DMS 500) were found to be in general agreement in terms of size distributions and concentrations with some exceptions. Teflon filter measurements of the total aerosol mass produced by the various DFCASs differed from the reference EC, BC, and integrated particle sized distribution measured aerosol masses. The Teflon filter measured mass was 30 to 40% greater than the reference EC and 50 to 60% greater than the BC mass for the J85 in both test campaigns. The measurements of particle size distributions and single particle analysis by miniSPLAT indicated the presence of large particles (>100 nm) having more compact morphologies, higher effective density, and a composition dominated by OC and ash. This increased large particle fraction is also associated with higher values of single scattering albedo measured by the CAPS PMSSA instrument and higher OC/EC measurements. These measurements indicate gas turbine engine emissions can be a more heterogeneous mix of particle types beyond the original E31 assumption that it is mainly composed of black carbon.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Segmentation of tomography datasets using 3D convolutional neural networks

Dendritic microstructures are ubiquitous in nature and are the primary solidification morphologies in metallic materials. Techniques such as X-ray computed tomography (XCT) have provided new insights into dendritic phase transformation phenomena. However, manual identification of dendritic morphologies in microscopy data can be both labor intensive and potentially ambiguous. The analysis of 3D datasets is particularly challenging due to their large sizes (terabytes) and the presence of artifacts scattered within the imaged volumes. Here, in this study, we trained 3D convolutional neural networks (CNNs) to segment 3D datasets. Three CNN architectures were investigated, including a new version of FCDenseNet which we extended to 3D. We show that using hyperparameter optimization (HPO) and fine-tuning techniques, both 2D and 3D CNN architectures outperform the previous state of the art. The 3D U-Net architecture trained in this study produced the best segmentations according to quantitative metrics (intersection-over-union of 95.56% and a boundary displacement error of 0.58 pixels), while 3D FCDense produced the smoothest boundaries and best segmentations according to visual inspection. The trained 3D CNNs are able to segment entire 852 × 852 × 250 voxel 3D volumes in only ~60 s, thus hastening the progress towards a deeper understanding of phase transformation phenomena such as dendritic solidification.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Deep learning of structural morphology imaged by scanning X-ray diffraction microscopy

Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. One of the critical challenges in experimental nanodiffraction data analysis is posed by the convergence angle of nanoscale focusing optics which creates simultaneous dependency of the far-field scattering data on three independent components of the local strain tensor-corresponding to dilation and two potential rigid body rotations of the unit cell. All three components are in principle resolvable through a spatially mapped sample tilt series; however, traditional data analysis is computationally expensive and prone to artifacts. In this study, we implement NanobeamNN, a convolutional neural network specifically tailored to the analysis of scanning probe X-ray microscopy data. NanobeamNN learns lattice strain and rotation angles from simulated diffraction of a focused X-ray nanobeam by an epitaxial thin film and can directly make reasonable predictions on experimental data without the need for additional fine-tuning. We demonstrate that this approach represents a significant advancement in computational speed over conventional methods, as well as a potential improvement in accuracy over the current standard.

Luo, Aileen [Cornell Univ., Ithaca, NY (United Sta↗
DOE OSTI2020

SDSS-IV MaNGA: The link between bars and the early cessation of star formation in spiral galaxies

ABSTRACT Bars are common in low-redshift disc galaxies, and hence quantifying their influence on their host is of importance to the field of galaxy evolution. We determine the stellar populations and star formation histories of 245 barred galaxies from the Mapping Nearby Galaxies at APO (MaNGA) galaxy survey, and compare them to a mass- and morphology-matched comparison sample of unbarred galaxies. At fixed stellar mass and morphology, barred galaxies are optically redder than their unbarred counterparts. From stellar population analysis using the full spectral fitting code starlight, we attribute this difference to both older and more metal-rich stellar populations. Dust attenuation however, is lower in the barred sample. The star formation histories of barred galaxies peak earlier than their non-barred counterparts, and the galaxies build up their mass at earlier times. We can detect no significant differences in the local environment of barred and unbarred galaxies in this sample, but find that the H i gas mass fraction is significantly lower in high-mass ($\rm {M}_{\star } \gt 10^{10}~\rm {M}_{\odot }$) barred galaxies than their non-barred counterparts. We speculate on the mechanisms that have allowed barred galaxies to be older, more metal-rich and more gas-poor today, including the efficient redistribution of galactic fountain byproducts, and a runaway bar formation scenario in gas-poor discs. While it is not possible to fully determine the effect of the bar on galaxy quenching, we conclude that the presence of a bar and the early cessation of star formation within a galaxy are intimately linked.

Fraser-McKelvie, Amelia↗
DOE OSTI2022

Studying the Suitability of Nineteen Lignins as Partial Polyol Replacement in Rigid Polyurethane/Polyisocyanurate Foam

In this study, nineteen unmodified lignins from various sources (hardwood, softwood, wheat straw, and corn stover) and isolation processes (kraft, soda, organosolv, sulfite, and enzymatic hydrolysis) were used to replace 30 wt.% of petroleum-based polyol in rigid polyurethane/polyisocyanurate (PUR/PIR) foam formulations. Lignin samples were characterized by measuring their ash content, hydroxyl content (Phosphorus Nuclear Magnetic Resonance Spectroscopy), impurities (Inductively Coupled Plasma), and pH. After foam formulation, properties of lignin-based foams were evaluated and compared with a control foam (with no lignin) via cell morphology, closed-cell content, compression strength, apparent density, thermal conductivity, and color analysis. Lignin-based foams passed all measured standard specifications required by ASTM International C1029-15 for type 1 rigid insulation foams, except for three foams. These three foams had poor compressive strengths, significantly larger cell sizes, darker color, lower closed-cell contents, and slower foaming times. The foam made with corn stover enzymatic hydrolysis lignin showed no significant difference from the control foam in terms of compressive strength and outperformed all other lignin-based foams due to its higher aliphatic and p-hydroxyphenyl hydroxyl contents. Lignin-based foams that passed all required performance testing were made with lignins having higher pH, potassium, sodium, calcium, magnesium, and aliphatic/p-hydroxyphenyl hydroxyl group contents than those that failed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Manufacturing Bulk Nanocrystalline Al-3Mg Components Using Cryomilling and Spark Plasma Sintering

In the current study, pure aluminum (Al) powders were cryomilled with and without 3 wt.% pure magnesium (Mg) dopant for varying durations followed by spark plasma sintering (SPS) of powders to prepare bulk components with superior mechanical properties. The crystallite sizes were determined for powders and the bulk components by analyzing the X-ray diffraction (XRD) spectrum. The calculations indicated a reduction in crystallite size with the increase in the cryomilling duration. The results also showed a more significant decrease in the crystallite sizes for Al-3Mg samples than that of pure Al. The changes in the surface morphology of powders were characterized using scanning electron microscopy (SEM). The elemental mapping analysis at nanoscale was carried out using Energy-dispersive X-ray spectroscopy (EDX) in Scanning transmission electron microscopy (STEM). The mechanical properties of the bulk components were assessed using a Vickers Microhardness tester. The test results demonstrated an improvement in the hardness of Mg-doped components. Higher hardness values were also reported with an increase in the cryomilling duration. This article discusses the mechanisms for the reduction in crystallite size for pure Al and Al-3Mg and its subsequent impact on improving mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Laboratory Accelerated Cyclic Corrosion Testing and On-Road Corrosion Testing of AA6××× Coupled to Carbon Fiber-Reinforced Plastics

Structures made from a combination of aluminum alloy (AA) and carbon fiber-reinforced plastic (CFRP) are susceptible to galvanic corrosion of the AA in harsh atmospheric conditions, such as might exist for closure panels in automotive applications. It is important to understand the galvanic corrosion behavior of these materials under laboratory conditions as that might allow prediction of performance in real environments. This work tested specially designed AA6×××-CFRP coupons, including AA6111 and AA6022, connected to CFRP made from two different carbon fiber fabrics (twill and random) with the aim of understanding the corrosion behaviors in a laboratory cyclic exposure chamber and during on-road exposure. The extent of corrosion was assessed by galvanic current measurements, optical profilometry, cross-sectional area analysis, and microscopic analysis. Based on the results, it was determined that the corrosion susceptibilities and morphologies observed in CFRP/AA couples tested in an environmental chamber for 12 weeks were in correspondence with those of the coupons subjected to on-road testing for 1 y in Columbus, OH.

Materials Science↗
DOE OSTI2020

Linking the Dynamic Response of the Carbon Dioxide-Concentrating Mechanism to Carbon Assimilation Behavior in Fremyella diplosiphon

ABSTRACT Cyanobacteria use a carbon dioxide (CO 2 )-concentrating mechanism (CCM) that enhances their carbon fixation efficiency and is regulated by many environmental factors that impact photosynthesis, including carbon availability, light levels, and nutrient access. Efforts to connect the regulation of the CCM by these factors to functional effects on carbon assimilation rates have been complicated by the aqueous nature of cyanobacteria. Here, we describe the use of cyanobacteria in a semiwet state on glass fiber filtration discs—cyanobacterial discs—to establish dynamic carbon assimilation behavior using gas exchange analysis. In combination with quantitative PCR (qPCR) and transmission electron microscopy (TEM) analyses, we linked the regulation of CCM components to corresponding carbon assimilation behavior in the freshwater, filamentous cyanobacterium Fremyella diplosiphon . Inorganic carbon (C i ) levels, light quantity, and light quality have all been shown to influence carbon assimilation behavior in F. diplosiphon . Our results suggest a biphasic model of cyanobacterial carbon fixation. While behavior at low levels of CO 2 is driven mainly by the C i uptake ability of the cyanobacterium, at higher CO 2 levels, carbon assimilation behavior is multifaceted and depends on C i availability, carboxysome morphology, linear electron flow, and cell shape. Carbon response curves (CRCs) generated via gas exchange analysis enable rapid examination of CO 2 assimilation behavior in cyanobacteria and can be used for cells grown under distinct conditions to provide insight into how CO 2 assimilation correlates with the regulation of critical cellular functions, such as the environmental control of the CCM and downstream photosynthetic capacity. IMPORTANCE Environmental regulation of photosynthesis in cyanobacteria enhances organismal fitness, light capture, and associated carbon fixation under dynamic conditions. Concentration of carbon dioxide (CO 2 ) near the carbon-fixing enzyme RubisCO occurs via the CO 2 -concentrating mechanism (CCM). The CCM is also tuned in response to carbon availability, light quality or levels, or nutrient access—cues that also impact photosynthesis. We adapted dynamic gas exchange methods generally used with plants to investigate environmental regulation of the CCM and carbon fixation capacity using glass fiber-filtered cells of the cyanobacterium Fremyella diplosiphon . We describe a breakthrough in measuring real-time carbon uptake and associated assimilation capacity for cells grown in distinct conditions (i.e., light quality, light quantity, or carbon status). These measurements demonstrate that the CCM modulates carbon uptake and assimilation under low-C i conditions and that light-dependent regulation of pigmentation, cell shape, and downstream stages of carbon fixation are critical for tuning carbon uptake and assimilation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Enabling quantitative analysis of complex polymer blends by infrared nanospectroscopy and isotopic deuteration

Atomic-force microscopy coupled with infrared spectroscopy (AFM-IR) deciphers surface morphology of thin-film polymer blends and composites by simultaneously mapping physical topography and chemical composition. However, acquiring quantitative phase and composition information from multi-component blends can be challenging using AFM-IR due to the possible overlapping infrared absorption bands between different species. Isotope labeling one of the blend components introduces a new type of bond (carbon-deuterium vibration) that can be targeted using AFM-IR and responds at wavelengths sufficiently shifted toward unoccupied regions (around 2200 cm –1 ). In this project, AFM-IR was used to probe the surface morphology and chemical composition of three polymer blends containing deuterated polystyrene; each blend is expected to exhibit various degrees of miscibility. AFM-IR results successfully demonstrated that deuterium labeling prevents infrared spectral overlap and enables the visualization of blend phases that could not normally be distinguished by other scanning probe techniques. The nanoscale domain composition was resolved by fast infrared spectrum analysis. Overall, we presented isotope labeling as a robust approach for circumventing obstacles preventing the quantitative analysis of multiphase systems by AFM-IR.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Editors’ Choice—Examining Performance and Durability of Anion Exchange Membrane Fuel Cells with Novel Spirocyclic Anion Exchange Membranes

A series of spirocyclic copolymer membranes with varying ion exchange capacities (IECs) were investigated to probe the impact of polymer properties on in situ fuel cell performance and stability. In-situ electrochemical tests and post-mortem electron microscopy analysis of cross-sectioned membrane electrode assemblies (MEAs) have been combined with voltage loss breakdown analysis to evaluate the performance and degradation of different MEAs, and to probe the catalyst morphology and electrode structure at different stages of operation. Voltage loss breakdown results show that membrane degradation and kinetic losses played only a minor role in observed performance degradation and that performance losses were primarily related to increasing mass transport losses. From microscopy studies, carbon corrosion and Pt nanoparticle growth were identified at both the cathode and anode although more pronounced on the cathode resulting in significant structural changes. The membrane with the lowest IEC (1.3 mmolg −1 ) demonstrated the lowest peak power density ~ 1.16 W cm −2 , however, it showed the most stable performance (constant 0.6 A cm −2 hold) with ~ 5% degradation over 540 h. Isolation of performance losses and microscopic analysis of electrodes for anion exchange membrane fuel cells has not been reported previously, and these results help identify critical performance degradation concerns.

25 ENERGY STORAGE↗
DOE OSTI2026

Iron Oxide Reduction Rate Affects Iron Product Morphology

Magnetite concentrates from different parts of the Mesabi Range, exhibiting varying tendencies to encapsulate, were reduced using thermogravimetric analysis (TGA) and a high-temperature confocal scanning laser microscope (CSLM). Gas-phase mass-transfer conditions were intentionally varied by employing two reactors with different geometries: the TGA produced significantly slower reduction, whereas the CSLM setup yielded reduction rates up to 20 times faster under mass-transfer-controlled conditions. A preliminary mechanism is proposed to explain the transition from a porous iron product to a dense encapsulating layer. Encapsulation is interpreted as the outcome of competition between pore creation, driven by the reduction rate, and pore elimination, driven by surface diffusion. When pore formation is insufficient to counteract pore coarsening, a dense iron layer develops and restricts further reduction.

encapsulation↗