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At least 325 records · Page 18

In-situ hydrogen microstructural characterization of Si heterojunction passivation: Addressing V OC degradation and mitigation pathways

Si heterojunction (SHJ) solar cells have demonstrated record efficiency >27%, approaching the theoretical limit of ≈ 29%, primarily due to best surface/interface defect passivation provided by deposited thin layers of hydrogenated amorphous silicon (a-Si:H). Such excellent surface/interface passivation reduces recombination loss and result in >100 mV improvement of cell open circuit voltage (V OC ) to ≈ 750 mV, thus the cell efficiency. However, fielded SHJ modules exhibit loss of V OC and hence efficiency over time in years, presumably due to degradation related to a-Si:H layers. This adversely affects the technology’s market acceptance, and levelized cost of energy (LCOE). It is hypothesized that the origin of a-Si:H degradation is somehow related to the presence of weak Si–Si bonds and hydrogen in a-Si:H films. The objective of this project is to test this hypothesis by directly measuring chemical and structural changes occurring within SHJ component layers and solar cells. This is achieved by developing an innovative in-situ Fourier transform infrared (FTIR) spectrometry apparatus to monitor hydrogen microstructural changes occurring within amorphous silicon and decipher hydrogen evolution kinetics over time when samples are exposed to heat and/or light stress. These in-situ measured hydrogen microstructural changes are correlated to the changes in effective minority carrier lifetime (τ eff ), implied V OC (iV OC ), surface recombination velocity (S), and cell V OC . These mechanistic understandings will provide critical guidance to mitigate the V OC -driven degradation of SHJ solar cell performance. Passivation optimization and degradation analysis of individual SHJ component structures were achieved through systematic deposition of three symmetric structures and the completed SHJ solar cell structure. The three symmetric structures used were intrinsic a-Si:H [(i)a-Si:H] layers in a bilayer structure, intrinsic and p-type doped stacked layers [(i-p)a-Si:H] representing the front heterojunction in the SHJ cell, and intrinsic and n-typed doped stacked layers [(i-n)a-Si:H] representing the back-side back surface field (BSF) in the SHJ cell. State-of-the-art passivation qualities are demonstrated by a champion iV OC of 740 mV for the (i)a-Si:H layers, and the (i-n)a-Si:H symmetric structure. A 725 mV iV OC is observed for the (i-p)a-Si:H symmetric structure. These symmetric passivated SHJ component structures were subsequently subjected to different accelerated lifetime (ALT) stressors to identify which conditions contribute the most to iV OC degradation. Degradation of the thin (10 nm) (i)a-Si:H passivation layers without any additional overlying layers is minimal; complexity of this study arises due to unavoidable surface oxidation of (i)a-Si:H layer during most of the stress application, which is likely irrelevant for a full SHJ cell configuration with overlying protective layers. The iV OC degradation of symmetric structures is found to occur primarily at the (i-p)a-Si:H passivation stack under dark heat stress with associated hydrogen loss from the (p)a-Si:H layer. An activation energy for increase in S (defect creation) of 0.65 eV can be correlated to the activation energy of ≈ 0.4 eV for hydrogen loss from the (i-p)a-Si:H stack. This also suggests the presence of weakly bonded hydrogen in the (p)a-Si:H films, which effuses out of the film stack at such low activation energy. When light and heat stress are applied together, similar hydrogen loss from (i-p)a-Si:H stack is observed, however, does not appreciably degrade iV OC or increase S. This is an important result and departure from direct correlation between hydrogen loss and defect creation. This perhaps indicates additional defect chemistries or annealing that might be occurring in the presence of light requiring further detailed defect measurements. The full SHJ cell structure used for this project is depicted in Fig.1(d). SHJ cells with an initial V OC ≈ 700 mV were fabricated and subjected to similar ALT stress conditions. Cell V OC is found to degrade the most under dark heat stress and is confirmed by observed hydrogen migration out of the (i-p)a-Si:H stack. However, hydrogen cannot escape from the cell stack, it accumulates near the (p)a-Si:H/ITO contact interface, where ITO acts as a barrier preventing hydrogen loss. Furthermore, light-heat combined stress does not degrade V OC appreciably, confirming the occurrence of a defect annealing process.

14 SOLAR ENERGY↗

Characterization of Build Parameters and Microstructure in Low Heat Input WAAM of Ni-Based Superalloy Haynes 282

Ni-based superalloy Haynes® 282® is being targeted for various applications in advanced power generation systems for its superior fabricability, weldability, and excellent high temperature creep and corrosion performance. This process optimization study aims to use a low heat-input, high deposition rate, controlled Gas Metal Arc Welding (GMAW) process, Cold Metal Transfer (CMT) by Fronius, attempting to achieve fully dense fabrication and possibly avoid the need for HIP. Twenty-one multilayer blocks (~25x100x40 mm3) were deposited to explore a large set of build parameters variations that focused on varying the travel speed from 14 to 42 inches per minute (ipm) and wire feed speed from 150 to 450 ipm. A strong correlation has been observed between arc energy – controlled primarily by travel and wire feed speed. Initial visual inspection, internal microstructural examination, and computed tomography (CT) have been used to determine the effects of built parameters on evolution of internal porosity and defects. Scanning electron microscopy techniques enabled structural and compositional imaging of heterogeneity and changes in microstructural properties.

additive manufacturing↗

Location-Specific Microstructures and Properties of Haynes 282 Alloy with Laser-Wire DED Processing

In this work, the location-specific microstructures in terms of grain morphology, texture, γ′ precipitates, carbides, and residual strains were investigated in a series of laser-wire direct energy deposition (LW-DED) Haynes 282 alloys with varied processing parameters. A bimodal grain distribution was found in these as-printed and heat-treated alloys with columnar grains within the layers and fine equiaxed grains at the interlayer regions. Dominant <001> texture along the build direction with more obvious <111> orientation preference exists at the bottom layers, compared to the top layers. The gradient γ′-precipitates size distribution contributes predominantly to the observed gradient hardness distribution in the as-printed samples. The heat-treated 282 exhibit comparable yield strengths to those conventionally-processed counterparts, while the observed small deviation in their yield strengths is attributed to the Hall-Petch effect. This work establishes the correlation between location-specific microstructures and mechanical properties, providing valuable insights into future printing parameters and heat-treatment optimization.

Haynes 282↗

Enhancing NDE Reliability for Grade 91 Steel Welds: Ultrasonic Imaging and Microstructural Correlations

Ensuring the integrity of Grade 91 (9Cr-1Mo-V) steel welds is vital for the safe and reliable operation of fossil fuel–fired and nuclear power plants. Here, this study applies an imaging technique for the ultrasonic characterization of two Grade 91 steel welds created with cold metal transfer and flux-cored arc welding processes. Ultrasonic immersion testing in the through-transmission configuration was employed to generate shear waves, which helped identify the weld metal, heat-affected zone, and base metal regions. These weld microstructures were also correlated to their ultrasonic images using metallography, ultrasonic amplitude, hardness measurements, and grain size. The findings from this study can assist practitioners in developing new nondestructive evaluation technologies, improving the inspection reliability of creep strength–enhanced ferritic steel welds by potentially identifying weld microstructure regions susceptible to creep-type failures.

Grade 91 steel↗

Location-Specific Microstructure and the Effect of Heat Treatment on Electron-Beam Melted Ni-Based Superalloy LSHR

Examine set-to-set variability with 4 build sets with the same layout Establish the effect of solutioning heat treatments (HT) on as-fabricated grain structure and microstructure – (gamma)’-solvus= 1156 ºC (1) As-fabricated (2) 2 hour subsolvus HT(-15 ºC) + conventional 2-step aging (3, 4, 5) 0.5 hour, 2 hours, 4 hours supersolvus HT (+18 ºC) + 2 step aging Gain insight into location-specific microstructure to correlate later to mechanical properties (tensile, creep, LCF behavior)

heat treatment↗

Microstructural, Strength, and Creep Characterization of Sylramic™, Sylramic™-iBN and Super Sylramic™-iBN SiC Fibers

The chemical composition, microstructure, strength, and thermal stability of polymer-derived Sylramic™ SiC fibers fabricated by Dow Corning and COI Ceramics, Inc., and nitrogen-treated Sylramic™ SiC fibers, referred to as Sylramic™-iBN and Super Sylramic™-iBN SiC fibers, were investigated and compared. The baseline Sylramic™ SiC fibers fabricated by both vendors as well as the nitrogen-treated Sylramic™ SiC fibers are composed mostly of β-SiC (~97 wt%) with small amounts of TiB2 (~2 wt%), amorphous carbon (~1 wt%) and trace amounts of B4C. Most of the amorphous carbon is segregated at the core/interior of the fibers. Both baseline and nitrogen-treated Sylramic™ SiC fibers have similar grain size and pore size distribution, except for a thin layer of in-situ grown crystalline BN (30 to 70 nm) on the surface of Sylramic™-iBN and Super Sylramic™-iBN fibers. Wide variation in strength within a batch as well as between batches is observed in both baseline and nitrogen-treated Sylramic™ SiC fibers but both types of fibers are microstructurally stable at temperatures to 1800°C in argon and nitrogen environments compared to Nicalon™-S and Tyranno®-SA SiC fibers. Under the same creep condition, Super Sylramic™-iBN fibers show better creep resistance compared to Sylramic™, Sylramic™-iBN, Hi-Nicalon™-S, and Tyranno®-SA fibers. Possible reasons for strength variability and the mechanism of in-situ BN formation on Sylramic™ SiC fibers are discussed.

SiC fibers↗

Artificial Generation of 2-D Fiber Reinforced Composite Microstructures with Statistically Equivalent Features

Fiber reinforced composites are used widely for their high strength and low weight advantages in various aerospace and automotive applications. While their use may be sought after, modeling of these material requires increasing fidelity at the lower scales to capture accurate material behavior under loading. The first steps in creating statistically equivalent models to real life cases is developing a method of rapid evaluation and artificial microstructure generation. The outlined work is capable of tracking microscale fiber positions and determining regions of localized volume fraction extrema (high and low end). Groupings of high and low volume fraction regions are called clusters and their geometry is used to characterize the microstructure. These cluster features can be evaluated for both artificial models and actual scans, allowing correlation to be established which can ultimately be used to regenerate statistically equivalent models. The results of this work show that if one feature is to be correlated, a model can be generated which matches almost exactly. But once more features are equally taken into account, the regeneration loses accuracy.

micromechanics↗

Comparative Analysis of Radial and Random Microstructures of Mesophase Pitch Carbon Fibers

Carbon fibers (CF) with radial and random microstructures are produced. Here, these fibers are subjected to identical treatment before being mechanically tested and analyzed with Weibull analysis, with the results revealing a statistically significant difference in tensile strengths of 2.23 GPa for random CF and 1.69 GPa for radial CF. Raman mapping probed the crystalline structure perpendicular to the fiber axis and found a uniform structure, while wide‐angle X‐ray diffraction showed a significant difference of 7.5 Å in the crystallites’ basal lengths parallel to the fiber. Small‐angle X‐ray scattering is completed parallel to the fiber for the first time. A cross‐section Guinier plot of the 1D azimuthal integration is generated assuming symmetric scattering, and the parallel scatterers are found to have a similar length scale to the crystallite's length, validating the testing method. Finally, transmission electron microscopy is completed on the longitudinal cross‐section of each fiber. The radial carbon fiber is found to have a core–shell structure, as evidenced further by fast Fourier transform images. Through all studies, it is shown that the structure developed during mesophase pitch spinning altered the microstructure, thus impacting the mechanical properties, confirming a direct relationship between processing, structure, and properties.

Scherschel, Alexander [Univ. of Virginia, Charlott↗

Effect of Thermal Oxidation on the Structure, Surface Texturing, and Microstructure Evolution in Nanocrystalline Ga-O-N Films

An extensive examination of the nanoscale, crystallographic growth dynamics of the system, which is impacted by the thermal energy given to the GaN, is carried out to derive a deeper understanding of the growth kinetics, morphology and microstructure evolution, chemical bonding, and optical properties of Ga-O-N films. Thermal annealing of GaN films is performed in the temperature range of 900–1200 °C. Crystal structure, phase formation, chemical composition, surface morphology, and microstructure evolution of Ga-O-N films are investigated as a function of temperature. Increasing temperature induces surface oxidation, which results in the formation of stable β-Ga2O3 phase in the GaN matrix, where the overall film composition evolves from nitride (GaN) to oxynitride (Ga-O-N). While GaN surfaces are smooth, planar, and featureless, oxidation induced granular-to-rod shaped morphology evolution is seen with increasing temperature to 1200 °C. The considerable texturing and stability of the nanocrystalline Ga-O-N on Si substrates can be attributed to the surface and interface driven modification because of thermal treatment. Corroborating with structure and chemical changes, Raman spectroscopic analyses also indicate that the chemical bonding evolution progresses from fully Ga-N bonds to Ga-O-N. While the GaN oxidation process starts with the formation of β-Ga 2 O 3 at an annealing temperature of 1000 °C, higher annealing temperatures induce structural distortion with the potential formation of Ga-O-N bonds. The structure-phase-chemical composition correlation, which will be useful for nanocrystalline materials for selective optoelectronic applications, is established in Ga-O-N films made by thermal treatment of GaN.

36 MATERIALS SCIENCE↗

Transport–Friendly Microstructure in SSC–MEA: Unveiling the SSC Ionomer–Based Membrane Electrode Assemblies for Enhanced Fuel Cell Performance

The significant role of the cathodic binder in modulating mass transport within the catalyst layer (CL) of fuel cells is essential for optimizing cell performance. This investigation focuses on enhancing the membrane electrode assembly (MEA) through the utilization of a short-side-chain perfluoro-sulfonic acid (SSC-PFSA) ionomer as the cathode binder, referred to as SSC-MEA. This study meticulously visualizes the distinctive interpenetrating networks of ionomers and catalysts, and explicitly clarifies the triple-phase interface, unveiling the transport-friendly microstructure and transport mechanisms inherent in SSC-MEA. The SSC-MEA exhibits advantageous microstructural features, including a better-connected ionomer network and well-organized hierarchical porous structure, culminating in superior mass transfer properties. Relative to the MEA bonded by long-side-chain perfluoro-sulfonic acid (LSC-PFSA) ionomer, noted as LSC-MEA, SSC-MEA exhibits a notable peak power density (1.23 W cm –2 ), efficient O 2 transport, and remarkable proton conductivity (65% improvement) at 65 °C and 70% relativity humidity (RH). These findings establish crucial insights into the intricate morphology-transport-performance relationship in the CL, thereby providing strategic guidance for developing highly efficient MEA.

25 ENERGY STORAGE↗

Data‐Efficient Generation of Synthetic Microstructures of Polymer‐Bonded Energetic Material With Fine‐Tuned Stable Diffusion

Among current deep learning approaches for synthetic image generation, diffusion-based models stand out in terms of algorithmic stability and ability to retain high-fidelity image features with detailed resolution. Here, in this work, we employ Dreambooth, a method for fine-tuning Stable Diffusion, on X-ray CT images of microstructure of the polymer-bonded form (PBX) of a commonly used high explosive, Pentaerythritol tetranitrate (PETN), which yields generative models for creating synthetic PBX images. The models developed here represent five classes (or ‘lots’) of microstructures and demonstrate successful generation of images of each class with high fidelity, as verified by computed classification accuracy of ∼ 94% or higher. Data augmentation afforded by such image synthesis can be used to more reliably decipher underlying statistics, build processing-structure correlations, recognize off-normal structural anomalies, and identify age-related changes. Ideas related to converting image data into appropriate density mapping and performing mesoscale simulation or surrogate modeling of detonation are also discussed.

Dreambooth↗

An Integrated High-Speed Microstructural Characterization Method Using Simultaneous XRD, Stereo-DIC, and PCI

High-speed characterization of the deformation mechanisms in polycrystalline metals requires the quantification of full strain fields and local microstructural evolutions simultaneously. In this paper, we present a novel experimental method to integrate phase-contrast imaging (PCI), stereographic digital image correlation (stereo-DIC), and full-ring X-ray diffraction (XRD) to allow for the simultaneous characterization of polycrystalline metals at 1MHz or higher. A Kolsky bar was integrated into the synchrotron X-ray source in Sector 32 ID-B at the Advance Photon Source (APS) at Argonne National Laboratory. When the sample is dynamically loaded, the diagnostic methods of full-ring XRD, PCI, and stereo-DIC are properly synchronized to record the deformation behavior at both continuum and microstructural scales as a function of the loading history. An advanced high-strength steel (AHSS) is used as a model material to demonstrate the capabilities of this new experimental method.

36 MATERIALS SCIENCE↗

Exploring the relationship between deposition method, microstructure, and performance of Nb/Si-based superconducting coplanar waveguide resonators

Superconducting quantum circuits (SQC) are one of the most promising hardware platforms for quantum computing, yet their performance is currently limited by the presence of various structural defects inside the circuit's structure. Despite impressive progress in the past decade, a precise understanding of the origin of these defects from various fabrication processes and their impact on coherence is still lacking. Here, in this study, we performed a comprehensive investigation on the microstructure, superconductivity, and resonator quality factor of Nb films deposited by high-power impulse magnetron sputtering (HiPIMS) and direct current (DC) magnetron sputtering. A suite of characterization techniques, including electron microscopy with spectroscopy, secondary ion mass spectrometry, magneto-optical microscopy, and pump-probe reflectivity spectroscopy is used. We reveal that niobium (Nb) resonators fabricated using HiPIMS exhibit a smaller average grain size, thicker surface oxide with larger thickness variations (rougher surface), and a thicker amorphous Nb/Si interface layer compared to samples deposited by DC sputtering. We identified that the amorphous Nb oxides (mainly located at the Nb surface and along the grain boundaries) and Nb-Si amorphous layers (at the Nb/Si interface) are major and potential sources of two-level system (TLS), while off-stochiometric oxides and suboxides of Nb close to the surface, crystalline defects (i.e., dislocations at grain boundary, point defects introduced during deposition) are main contributors of non-TLS sources. Our findings clarify the relationship between different defects and coherence loss mechanisms, highlighting the importance of material microstructure control on performance optimization in SQC.

36 MATERIALS SCIENCE↗

Correlating aluminum layer deposition rates, Josephson junction microstructure, and superconducting qubits’ performance

An ultra-thin aluminum oxide layer is a key component for Josephson junctions (JJ) in superconducting quantum bits (qubits). This layer serves as a barrier layer for Cooper pairs tunneling between the superconducting electrodes and significantly influences the overall performance of the junction. In this study, we investigate the impact of aluminum deposition rates on the microstructure and chemical variation of the aluminum oxide layer, as well as the device's yields and qubits’ lifetimes. Surprisingly, although the oxide layer roughness and thickness variation improve noticeably with an increasing Al deposition rate from 0.5 Å/s to 5 Å/s, the qubit's coherence time is almost unchanged. We attribute this to the fact that Cooper pairs tunnel only through the thinnest region of the barrier. Additionally, we revealed a stress-induced grain boundary sliding short-circuit failure mechanism in the JJ. Our discovery provides a vital understanding of oxide microstructure and JJ functionality, which are critical for improving the coherence time of superconducting qubits.

Coherence time↗

Informed unsupervised machine learning analysis of dislocation microstructure from high-resolution differential aperture X-ray structural microscopy data

This study leverages high-resolution differential-aperture X-ray structural microscopy (DAXM) to probe the local dislocation structure in deformed 304L-stainless steel at small strain, by measuring the lattice rotation and deviatoric elastic strain with a sub-micron resolution. For a single grain in a polycrystalline specimen, the measured lattice rotation field over the measured volume exhibited a multimodal distribution while the deviatoric elastic strain showed a single-mode distribution. An unsupervised Cauchy mixture machine learning model was developed to resolve the multimodal distribution of the lattice rotation. By mapping the lattice rotation data associated with each Cauchy peak in the model back onto the measured volume, we identify contiguous regions of the crystal rotated near the average values corresponding to the peaks of the overall rotation distribution. These regions represent the grain subdivision in the microstructure. Finally, the dislocation density tensor was also computed and its norm was laid over the rotation field to detect the subgrain boundaries. This step provided a validation of the Cauchy mixture model for the analysis of the lattice rotation distribution. The current study highlights the integration of advanced X-ray microscopy techniques with data-driven analysis methods to uncover detailed microstructure scales in deformed crystals.

Machine learning; Lattice rotation; High-energy X-↗

Viewing is understanding: Graphite microstructure effects on infiltrated molten salt distribution revealed by 3D neutron tomography

Molten salt infiltration in the pore network of nuclear graphite may cause unwanted changes to graphite's local structure and mechanical and thermal properties. A detailed and comprehensive understanding of molten salt intrusion (distribution across sample cross section and penetration depth) is needed to assess its effects. Here, in this work, we report on an improved methodology for the use of neutron imaging (computed tomography) to evaluate salt penetration and distribution of a wide range of graphite grades with diverse microstructures. Neutron tomography data were acquired on the same graphite sample before and after salt intrusion; the 3D reconstructed volumes were digitally co-registered and subtracted. The difference in neutron attenuation coefficient represents direct visualization of FLiNaK (LiF–NaF–KF) salt distribution in the salt-impregnated graphite samples. This improved methodology was applied to investigate the effect of exposure times (12 h and 336 h) and of graphite microstructure when exposed to FLiNaK at 750 °C and 3 bar (gauge) pressure, starting from flowing argon at near atmospheric pressure. The results show that medium-grained and fine-grained graphites evolve to equilibrium at significantly different rates: fast salt uptake in medium-grained graphites produces salt deposits throughout the volume of graphite specimens, whereas salt infiltration in fine-grained graphites is much slower and limited to exposed surfaces.

FLiNaK infiltration↗

Microstructural characterization and equibiaxial flexural strength of CeO 2 and Ti-doped CeO 2

In this study, the synthesis of CeO 2 and titanium dioxide (TiO 2 ) doped CeO 2 (TDC) monoliths are investigated, and their fracture strength is assessed using an equibiaxial flexure testing technique at room temperature. Pellets were synthesized using conventional powder processing and sintering methods to produce the desired characteristics. The TiO 2 dopant concentration was optimized at 0.1 wt % TiO 2 to obtain dense, solid-solution pellets with an enhanced grain microstructure. A ball-on-ring fixture was used to obtain the TRS and Weibull parameters of over 30 pellets for CeO 2 and 0.1 wt % TDC to compare fracture behavior. The TRS of CeO 2 pellets ranged from 88 to 160 MPa and the TRS of 0.1 wt % TDC pellets ranged from 102 to 171 MPa, both being consistent with published values. Weibull parameters, such as characteristic strength and Weibull modulus, were extracted as 129 MPa and 8.5 for CeO 2 and 150 MPa and 9.3 for 0.1 wt % TDC, respectively. Although Hertzian contact damage was observed on compressive surfaces, failure initiation occurred on the tensile surfaces of both types of samples. Fracture surface analysis for CeO 2 indicated a predominantly intergranular fracture while 0.1 wt % TDC had a predominantly transgranular fracture mode. Finally, the TRS of 0.1 wt % TDC resulted in increased Weibull parameters when compared to CeO 2 , indicating sample chemistry and microstructure impact mechanical behavior for these samples.

36 MATERIALS SCIENCE↗

Improving microstructures segmentation via pretraining with synthetic data

Image analysis of material microstructures through microscopy is an integral capability in the field of materials science. The topological and chemical information obtained through microscopy allow us to draw vital connections between material microstructures, properties, and processing. While scanning electron microscopy (SEM) is able to yield a considerable wealth of information interpretable by the intuition of experts, there has been considerable interest in using machine learning, convolutional neural networks (CNNs) in particular, for such image analysis task. Training CNNs for an image analysis task requires a large annotated dataset. However, in many materials science applications, obtaining a large annotated dataset is cost and labor intensive. In this work, we study the use of synthetic data to enlarge the available annotated experimental data of uranium oxide. We utilize a modified Potts model to simulate uranium oxide particles with morphologies similar to those observed experimentally. We then leverage an image-to-image translation model to synthesize the simulated particles as if they are acquired with SEM. Through this process, we obtain pairs of particle images and their corresponding SEM representations, which corresponds to pairs of annotations and images. Unlike previous works, we leverage synthetic data for pretraining a CNN model prior, and finetune that model further with experimental data. We experimentally demonstrate that using synthetic data as incremental learning process benefits the overall performance compared to training a model on combined synthetic and experimental data.

36 MATERIALS SCIENCE↗