Microstructure Map Research Articles

DIMOND: DIffusion Model OptimizatioN with Deep Learning.

Diffusion magnetic resonance imaging is an important tool for mapping tissue microstructure and structural connectivity non-invasively in the in vivo human brain. Numerous diffusion signal models are proposed to quantify microstructural properties. Nonetheless, accurate estimation of model parameters is computationally expensive and impeded by image noise. Supervised deep learning-based estimation approaches exhibit efficiency and superior performance but require additional training data and may be not generalizable. A new DIffusion Model OptimizatioN framework using physics-informed and self-supervised Deep learning entitled "DIMOND" is proposed to address this problem. DIMOND employs a neural network to map input image data to model parameters and optimizes the network by minimizing the difference between the input acquired data and synthetic data generated via the diffusion model parametrized by network outputs. DIMOND produces accurate diffusion tensor imaging results and is generalizable across subjects and datasets. Moreover, DIMOND outperforms conventional methods for fitting sophisticated microstructural models including the kurtosis and NODDI model. Importantly, DIMOND reduces NODDI model fitting time from hours to minutes, or seconds by leveraging transfer learning. In summary, the self-supervised manner, high efficacy, and efficiency of DIMOND increase the practical feasibility and adoption of microstructure and connectivity mapping in clinical and neuroscientific applications.

The anaerobic soil volume as a controlling factor of denitrification: a review

AbstractDenitrification is an important component of the nitrogen cycle in soil, returning reactive nitrogen to the atmosphere. Denitrification activity is often concentrated spatially in anoxic microsites and temporally in ephemeral events, which presents a challenge for modelling. The anaerobic fraction of soil volume can be a useful predictor of denitrification in soils. Here, we provide a review of this soil characteristic, its controlling factors, its estimation from basic soil properties and its implementation in current denitrification models. The concept of the anaerobic soil volume and its relationship to denitrification activity has undergone several paradigm shifts that came along with the advent of new oxygen and microstructure mapping techniques. The current understanding is that hotspots of denitrification activity are partially decoupled from air distances in the wet soil matrix and are mainly associated with particulate organic matter (POM) in the form of fresh plant residues or manure. POM fragments harbor large amounts of labile carbon that promote local oxygen consumption and, as a result, these microsites differ in their aeration status from the surrounding soil matrix. Current denitrification models relate the anaerobic soil volume fraction to bulk oxygen concentration in various ways but make little use of microstructure information, such as the distance between POM and air-filled pores. Based on meta-analyses, we derive new empirical relationships to estimate the conditions for the formation of anoxia at the microscale from basic soil properties and we outline how these empirical relationships could be used in the future to improve prediction accuracy of denitrification models at the soil profile scale.

Spherical convolutional neural networks can improve brain microstructure estimation from diffusion MRI data.

Diffusion magnetic resonance imaging is sensitive to the microstructural properties of brain tissue. However, estimating clinically and scientifically relevant microstructural properties from the measured signals remains a highly challenging inverse problem that machine learning may help solve. This study investigated if recently developed rotationally invariant spherical convolutional neural networks can improve microstructural parameter estimation. We trained a spherical convolutional neural network to predict the ground-truth parameter values from efficiently simulated noisy data and applied the trained network to imaging data acquired in a clinical setting to generate microstructural parameter maps. Our network performed better than the spherical mean technique and multi-layer perceptron, achieving higher prediction accuracy than the spherical mean technique with less rotational variance than the multi-layer perceptron. Although we focused on a constrained two-compartment model of neuronal tissue, the network and training pipeline are generalizable and can be used to estimate the parameters of any Gaussian compartment model. To highlight this, we also trained the network to predict the parameters of a three-compartment model that enables the estimation of apparent neural soma density using tensor-valued diffusion encoding.

Mapping tissue microstructure of brain white matter in vivo in health and disease using diffusion MRI

Abstract Diffusion magnetic resonance imaging offers unique in vivo sensitivity to tissue microstructure in brain white matter, which undergoes significant changes during development and is compromised in virtually every neurological disorder. Yet, the challenge is to develop biomarkers that are specific to micrometer-scale cellular features in a human MRI scan of a few minutes. Here, we quantify the sensitivity and specificity of a multicompartment diffusion modeling framework to the density, orientation, and integrity of axons. We demonstrate that using a machine learning-based estimator, our biophysical model captures the morphological changes of axons in early development, acute ischemia, and multiple sclerosis (total N = 821). The methodology of microstructure mapping is widely applicable in clinical settings and in large imaging consortium data to study development, aging, and pathology.

Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging

Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches.

Effects of Ti doping on the magnetic and microstructure properties of the lower magnetic anisotropy CoCrPtRu-oxides layer in a perpendicular recording media

Areal density capacity is constrained by linear and track density, and the recent advancements in magnetic layer structures have led to the development of segmented media. This configuration incorporates a graded magnetic anisotropy layer introduced through a non-magnetic exchange control layer. Optimizing this structural design yielded improvements in the signal-to-noise ratio (SNR) and an elevation in areal density capacity. To comprehensively investigate the magnetic properties and microstructure of the lower magnetocrystalline anisotropy constant (Ku) CoCrPtRu-oxides magnetic capping layer individually, we deposited the (0002) textured magnetic capping layer CoCrPtRu-oxides on (0002) Ru/NiW/NiTa underlayers. Additionally, metallic Ti was introduced into CoCrPtRu targets, replacing half of Ru, resulting in the deposition of the (0002) textured CoCrPtRuTi-oxides film was also deposited and compared to CoCrPtRu-oxides film. A comparative analysis was conducted between the CoCrPtRu-oxides and CoCrPtRuTi-oxides films. Microstructural image mapping and chemical composition analysis revealed that the introduced Ti in core grains diffused to the grain boundaries, enhancing grain separation. This diffusion was facilitated by the more negative formation energy of TiO2 (-3.512 eV/atom) compared with other oxides in the film. Consequently, the CoCrPtRuTi-oxides film exhibited slightly larger grain boundary areas (52%) and smaller grain sizes. Moreover, perpendicular coercivity (243.50 kA/m) and anisotropy were higher. This insight suggests a potential strategy for improving segregation by doping metallic elements, such as Ti, into the core grains, emphasizing the importance of not merely increasing the oxide content (e.g., TiO2).

Formation of multistage garnet grains by fragmentation and overgrowth constrained by microchemical and microstructural mapping

AbstractGarnet is an exceptionally useful mineral for reconstructing the evolution of metamorphic rocks that have experienced multiple tectonic or thermal events. Understanding how garnet crystallizes and its mechanical behaviour is important for establishing a petrological and temporal record of metamorphism and deformation and for recognizing multiple geologic stages within the growth history of an individual crystal. Here, we integrate fine‐scale microstructural (electron backscatter diffraction [EBSD]) and microchemical (Laser Ablation Inductively Coupled Plasma Mass Spectrometry [LA‐ICP‐MS] mapping) data obtained on a polycyclic garnet‐bearing micaschist from the Alpine belt. Results suggest that fragmentation of pre‐Alpine garnet porphyroblasts occurred during the late pre‐Alpine exhumation and/or the onset of the Alpine burial, such that the older pre‐Alpine garnet fragments were transported/redistributed during Alpine deformation and acted as nucleation sites for Alpine garnet growth. These processes produced a bimodal garnet size distribution (millimetre‐ and micrometre‐sized grains). Thermodynamic modelling indicates that Alpine garnet grew during the final stage of burial (from 1.9 GPa 480°C to 2.0 GPa 520°C) and early exhumation (down to 1.6 GPa 540°C) forming continuous idioblastic rims on and sealing fractures in pre‐Alpine garnet grains. We propose that fragmentation–overgrowth processes in polycyclic rocks, coupled with ductile deformation, may produce a bimodal garnet size distribution in response to fragmentation and re‐distribution of pre‐existing grains; these clasts can act as new nucleation sites during a subsequent orogenic cycle.

Effects of temperature and strain amplitude on low-cycle fatigue behavior of 12Cr13 martensitic stainless steel

12Cr13 martensitic stainless steel has been selected as the structural material for steam turbine blade which is frequently subjected to low-cycle fatigue (LCF) damage. The study involved conducting low-cycle fatigue (LCF) tests under strain control at various temperatures (25 °C, 250 °C, 350 °C, 450 °C) and strain amplitudes (±0.3 %, ±0.4 %, ±0.5 %, ±0.6 %). The cyclic deformation behavior, primarily indicating cyclic stress response and the Massing effect is thoroughly analyzed based on the characterization of dislocation microstructure and electron backscatter diffraction maps. The mechanism of crack initiation and the propagation behavior are discussed based on the SEM observations of microcracks on the specimen surface and the fracture surface morphology. The influence of temperature and strain amplitude on fatigue life behavior is determined, and the underlying mechanisms are revealed. Moreover, the life prediction is performed by using the classical Basquin-Coffin-Manson model at ambient temperature.

Exfoliation of an extruded Mg-4Li-1Ca alloy in presence of glucose and bovine serum albumin

Exfoliation corrosion (EFC) on extruded Mg-4Li-1Ca alloys as bone implant materials has not been reported. This study aimed to elucidate the degradation mechanism of a corrosion type-exfoliation occurred on an extruded Mg-4Li-1Ca alloy under the interaction of glucose (Glu) and bovine serum albumin (BSA) in Hank’s solution. The alloy microstructure, chemical composition, texture, stress distribution and Volta potential maps were characterized using metallographic microscopy, scanning electron microscopy and electron backscattered diffraction, and scanning Kelvin Probe. The alloy corrosion behavior was investigated via electrochemical testing and hydrogen evolution rate methods. X-ray diffraction, Fourier transform infrared spectrometry, X-ray photoelectron spectrometer, and fluorescence microscopy were used to analyze the corrosion products and the adsorption of the organic molecules. The experimental results indicated that the anodic second phase (Mg2Ca) were distributed in lamellar and rod-like patterns along the extrusion direction of the alloy, a lower Volta potential for Mg2Ca, texture and residual stresses also promote EFC. An increase in Glu concentration exacerbated the EFC, whereas BSA inhibited the EFC of the alloy. Higher Glu concentrations in BSA in turn inhibited EFC since Glu can complex with amino acids in proteins to form Glu-amino acid amides, which promoted protein adsorption and thereby forming a dense protective film on the alloy surface. The preferential dissolution of the Mg2Ca phase particles led to the complexation and adsorption of Glu and protein. This study enriches the understanding of the corrosion types in biomedical Mg-4Li-1Ca alloy and paving the way for enhancing the EFC resistance of the alloy.

Brain microstructure mapping in major depressive disorder: a pilot MR study

INTRODUCTION: Major depressive disorder is a common mental health disorder. Alterations in cortical structures have been identified in this disease, but findings have been variable and inconsistent. Previous studies have illustrated that the cingulate and prefrontal gyrus, along with the amygdala, are involved in emotional processing and the development of abnormal emotional responses in depression.OBJECTIVE: Our research aims to investigate the neurological structural differences and alterations in ACC, bilateral amygdala, and dmPFC regions in patients with MDD using quantitative MRI (MPF and Diffusion parameters mapping (DPM), including diffusion kurtosis).MATERIALS AND METHODS: In this study, we utilized advanced quantitative MRI techniques, specifically Diffusion Tensor Imaging, Diffusion Kurtosis Imaging, and Мacromolecular Proton Fraction Mapping, to investigate microstructural differences and alterations in the specific regions in patients diagnosed with major depressive disorder. RESULTS: Our findings revealed no significant interaction between Мacromolecular proton fraction Mapping with depressive disorder. However, patients with major depressive disorder exhibited a statistically significant increase in apparent mean, axial and radial diffusivity (F=6.3, p=0.01, F=5.0, p=0.03, F=7.08, p=0.01, respectively) in the bilateral amygdala compared to healthy controls, as well as in mean and radial diffusivity in the anterior cingulate cortex (F=5.61, p=0.02, F=7.08, p=0.01, respectively).DISCUSSION: These findings suggest that altered molecular diffusion characteristics in the amygdala and the anterior cingulate cortex may be specifically associated with major depressive disorder.CONCLUSIONS: The importance of using new quantitative MRI methods to assess structural changes at the molecular level in the brain is shown, which, ultimately, expands the fundamental understanding of the pathophysiology of depression.

A simple, static and stage mounted direct electron detector based electron backscatter diffraction system

To engineer the next generation of advanced materials we must understand their microstructure, and this requires microstructural characterization. This can be achieved through the collection of high contrast, data rich, and insightful microstructural maps. Electron backscatter diffraction (EBSD) has emerged as a popular tool available within the scanning electron microscope (SEM), where maps are realized through the repeat capture and analysis of Kikuchi diffraction patterns. Typical commercial EBSD systems require large and sophisticated detectors that are mounted on the side of the SEM vacuum chamber which can be limiting in terms of widespread access to the technique. In this work, we present an alternative open-hardware solution based upon a compact EBSD system with a simple, static geometry that uses an off-the-shelf direct electron detector co-mounted with a sample. This simple stage is easy to manufacture and improves our knowledge of the diffraction geometry significantly. Microscope and detector control is achieved through software application programming interface (API) integration. After pattern capture, analysis of the diffraction patterns is performed using open-source analysis within AstroEBSD. To demonstrate the potential of this set up, we present two simple EBSD experiments using a line scan and area mapping. We hope that the present system can inspire simpler EBSD system design for widespread access to the EBSD technique and promote the use of open-source software and hardware in the workflow of EBSD experiments.

Evaluating backscattering polarized light imaging microstructural mapping capabilities through neural tissue and analogous phantom imaging.

Knowledge of fiber microstructure and orientation in the brain is critical for many applications. Polarized light imaging (PLI) has been shown to have potential for better understanding neural fiber microstructure and directionality due to the anisotropy in myelin sheaths surrounding nerve fibers of the brain. Continuing to advance backscattering based PLI systems could provide a valuable avenue for in vivo neural imaging. To assess the potential of backscattering PLI systems, the ability to resolve crossing fibers, and the sensitivity to fiber inclination and curvature are considered across different imaging wavelengths. Investigation of these areas of relative uncertainty is undergone through imaging potential phantoms alongside analogous regions of interest in fixed ferret brain samples with a five-wavelength backscattering Mueller matrix polarimeter. Promising phantoms are discovered for which the retardance, diattenuation and depolarization mappings are derived from the Mueller matrix and studied to assess the sensitivity of this polarimeter configuration to fiber orientations and tissue structures. Rich avenues for future study include further classifying this polarimeter's sensitivity to fiber inclination and fiber direction to accurately produce microstructural maps of neural tissue.

Autism spectrum disorder-specific changes in white matter connectome edge density based on functionally defined nodes.

Autism spectrum disorder (ASD) is associated with both functional and microstructural connectome disruptions. We deployed a novel methodology using functionally defined nodes to guide white matter (WM) tractography and identify ASD-related microstructural connectome changes across the lifespan. We used diffusion tensor imaging and clinical data from four studies in the national database for autism research (NDAR) including 155 infants, 102 toddlers, 230 adolescents, and 96 young adults - of whom 264 (45%) were diagnosed with ASD. We applied cortical nodes from a prior fMRI study identifying regions related to symptom severity scores and used these seeds to construct WM fiber tracts as connectome Edge Density (ED) maps. Resulting ED maps were assessed for between-group differences using voxel-wise and tract-based analysis. We then examined the association of ASD diagnosis with ED driven from functional nodes generated from different sensitivity thresholds. In ED derived from functionally guided tractography, we identified ASD-related changes in infants (pFDR ≤ 0.001-0.483). Overall, more wide-spread ASD-related differences were detectable in ED based on functional nodes with positive symptom correlation than negative correlation to ASD, and stricter thresholds for functional nodes resulted in stronger correlation with ASD among infants (z = -6.413 to 6.666, pFDR ≤ 0.001-0.968). Voxel-wise analysis revealed wide-spread ED reductions in central WM tracts of toddlers, adolescents, and adults. We detected early changes of aberrant WM development in infants developing ASD when generating microstructural connectome ED map with cortical nodes defined by functional imaging. These were not evident when applying structurally defined nodes, suggesting that functionally guided DTI-based tractography can help identify early ASD-related WM disruptions between cortical regions exhibiting abnormal connectivity patterns later in life. Furthermore, our results suggest a benefit of involving functionally informed nodes in diffusion imaging-based probabilistic tractography, and underline that different age cohorts can benefit from age- and brain development-adapted image processing protocols.

Revealing microstructures evolution and dynamic recrystallization mechanisms of Mg–Sn–Mn alloy during compressive deformation at elevated temperature

The flow behavior of as-extruded Mg–3Sn-1.5Mn (wt.%) alloy was systematically researched via isothermal compression tests. The compressive temperatures (T) were from 250 °C to 400 °C, the strain rates were from 0.001 s−1 to 1s−1 and the true strain reached 0.69. Based on compression curves, flow stress apparently rose with increasing strain rate and/or decreasing temperature. Combined with the analysis of microstructure and processing map, the optimum working parameter was determined in the range of 350–400 °C, 0.01–1 s−1. According to electron backscatter diffraction (EBSD) analysis results, texture intensity significantly decreased and the basal (0001)//ED texture had transformed to basal <0001>//CD texture after compressive deformation obviously. Furthermore, the typical discontinue dynamic recrystallization (DDRX) and continue dynamic recrystallization (CDRX) were largely believed to be the major DRX mechanisms in Mg–3Sn-1.5Mn alloy. Both increasing temperature and decreasing strain rate had obvious influence on the degree of DRX. The activated slip systems in deformed grains were determined by the analysis of the in-grain misorientation axis (IGMA). As deformation temperature elevated, pyramidal <c+a> slip greatly activated and dominated compressive deformation.

Friction stir powder additive manufacturing of Al 6061/FeCoNi and Al 6061/Ni metal matrix composites: Reinforcement distribution, microstructure, residual stresses, and mechanical properties

Fusion based additive manufacturing (FBAM) of second, sixth, and seventh series Al alloys and their metal matrix composites (MMC) is difficult due to their higher thermal conductivity and solidification related problems namely porosity, cracks, thermal distortion, and formation of undesired phases. This paper presents friction stir powder additive manufacturing (FSPAM) process as a promising alternative to overcome these problems in producing multi-layer depositions of Al 6061 based MMCs namely Al 6061/6 wt%FeCoNi and Al 6061/6 wt%Ni. Their microstructure, distribution and elemental mapping of reinforcement particles, phase analysis, residual stresses of the MMCs and their correlation with microhardness, tensile strength, and fretting wear characteristics are investigated. Material accumulation on their advancing side was minimized by changing tool rotation direction in consecutive layers which produced smoother surfaces on both sides of their deposition. FSPAM made multi-layer depositions of Al 6061/FeCoNi and Al 6061/Ni MMCs have uniform distribution of reinforcement particles, good bonding between layers without cracks and defects, refined and equiaxed grains facilitated by dynamic recrystallization and pinning effect of reinforcement particles, compressive residual stresses of 39 and 48 MPa, no formation of deleterious intermetallic compounds due to absence of melting of matrix and reinforcement, and bowl-shaped substrate-deposition interface. Microhardness and ultimate tensile strength of the MMCs improved by 11.3% and 22.3%, and 30.5% and 31.5% respectively than Al 6061 alloy depositions, their wear resistance enhanced significantly, but % elongation reduced. This study proves FSPAM to be a potential alternative to FBAM processes for better quality multi-layer deposition of Al alloy-based MMCs.

Dual-encoded magnetization transfer and diffusion imaging and its application to tract-specific microstructure mapping

Abstract We present a novel dual-encoded magnetization transfer (MT) and diffusion-weighted sequence and demonstrate its potential to resolve distinct properties of white matter fiber tracts at the sub-voxel level. The sequence was designed and optimized for maximal MT ratio (MTR) efficiency. The resulting whole brain 2.6 mm isotropic protocol to measure tract-specific MTR has a scan time under 7 minutes. Ten healthy subjects were scanned twice to assess repeatability. Two different analysis methods were contrasted: a technique to extract tract-specific MTR using Convex Optimization Modeling for Microstructure Informed Tractography (COMMIT), a global optimization technique; and conventional MTR tractometry. The results demonstrate that the tract-specific method can reliably resolve the MT ratios of major white matter fiber pathways and is less affected by partial volume effects than conventional multi-modal tractometry. By reducing the contamination due to partial volume averaging of tracts, dual-encoded MT and diffusion may increase the sensitivity to microstructure alterations of specific tracts due to disease, aging, or learning, as well as lead to weighted structural connectomes with more anatomical specificity.

Microstructures, geochemistry, and geochronology of mica fish: Review and advances

Shear zones are one of the most conspicuous structures in orogenic and rifting settings, accommodating high strain, rock displacement and influencing magma emplacement and fluid flow. Since shear zones may be simultaneously or sequentially affected by multiple processes involving mineral reactions, variations in pressure-temperature conditions, fluid-rock interaction, and diffusion, determining the timing of such structures has been one of the major challenges for modern geochronology. Although low- (up to lower greenschist facies) and high-temperature shear zones (above amphibolite facies) are well-dated through low- and high-closure temperature minerals, medium-temperature shear zones developed within the critical temperature window of ∼450–550 °C, in which conventional chronometers such as 40Ar/39Ar and Rb–Sr applied to mica fish may or may not record the timing of deformation for multiple reasons (e.g., grain size, cooling rate, mineral composition, fluid activity, deformation, neo- and recrystallization). Here, we review the current knowledge on the evolution of mica fish and the effect of deformation on its chemical and isotopic systems. We evaluate the effect on the widely deployed in situ 40Ar/39Ar technique. Furthermore, we demonstrate the potential to assess mica fish evolution applying high-spatial resolution microstructural and chemical mapping techniques such as electron backscatter diffraction (EBSD), time-of-flight secondary ion mass spectrometry (ToF–SIMS) and in situ Rb–Sr via triple quadrupole inductively coupled plasma mass spectrometry (TQ-ICP-MS) to a case study of medium-temperature mylonites from the well-characterized Taxaquara shear zone, SE Brazil. We show that mica fish display complex microstructures with variable strain intensity, commonly with low strain inner cores and high strain edges and along kink planes. Strain shadows in mica fish are commonly characterized by low-strain fine-grained muscovite, suggesting recrystallization coeval with ductile deformation. Despite being intensely deformed, muscovite fish Rb–Sr retain the protolith age (c. 600 Ma), whereas recrystallized fine-grained muscovite yields the timing of deformation (c. 550–540 Ma). Synthetic shear bands cross-cutting coarse-grained muscovite fish induce muscovite recrystallization consistent with their distinct chemistry, with recrystallized muscovite characterized by higher Fe–Mg and lower Na suggesting fluid-assisted recrystallization under lower temperature compared to the muscovite fish host. We propose that these shear bands across mica fish play an important role by accommodating grain size reduction and subsequent deformation, leading to the formation of smaller individual mica fish. Grain size reduction, likely enhanced by dynamic precipitation (i.e., coeval crystal-plastic deformation and dissolution-precipitation creep), appears as the key recrystallization mechanism that allows low strain muscovite in strain shadows and shear bands to record the timing of deformation in medium-temperature shear zones, consistent with qualitative Sr diffusion modelling.

Novel Powder Feedstock towards Microstructure Engineering in Laser Powder Bed Fusion: A Case Study on Duplex/Super Duplex and Austenitic Stainless-Steel Alloys

Additive manufacturing of Duplex Stainless Steels (DSS) and Super Duplex Stainless Steels (SDSS) has been successfully demonstrated using LPBF in recent years, however, both alloys feature an almost fully ferritic microstructure in the as-built condition due to the fast cooling rates associated with the Laser Powder Bed Fusion (LPBF) process. Blends of DSS and SDSS powders were formulated with austenitic stainless-steel 316L powder, aiming to achieve increased austenite formation during in the LPBF as-built condition to potentially minimize the post heat treatments (solution annealing and quenching). Powder characteristics were investigated and process parameters were optimized to produce near fully dense parts. Nanoindentation (NI) tests were conducted to measure, not only the local mechanical properties and correlate them with the as-built microstructure, but also to gain a deeper understanding in the deformation behavior of individual phases that cannot be studied directly by macroscopic tensile tests. Scanning Electron Microscopy (SEM) and Electron Backscatter Diffraction (EBSD) were employed for microstructural analysis and phase quantification. The microstructural analysis and EBSD phase maps revealed an increase in austenite in the as-built microstructures. Blend 1 resulted in a duplex microstructure consisting of 10% austenite at the XY plane and 20% austenite at the XZ plane. The austenite content increased with increasing proportion of 316L stainless steel in the powder blends. The DSS blend required a much higher volumetric energy density for the fabrication of near fully dense parts. This imposed a slower solidification and a higher melt pool homogeneity, allowing for adequate diffusion of the austenite stabilizing elements. The presented workflow and findings from this study provide valuable insights into powder mixing for the development of custom alloys for rapid material screening in LPBF.

Effect of cobalt addition on wear behaviour of TiB2 coating produced by TIG cladding process

In this paper, the mechanical and tribological characteristics of TiB2 ceramic coating with and without cobalt (Co) addition developed using tungsten inert gas (TIG) cladding process on AISI 304 stainless steel (SS) were investigated. The effect of TIG process conditions as well as cobalt (Co) content on the microstructure, microhardness and resistance to wear were investigated systematically. The phase identification, microstructure, and elemental distribution map of the clad layer formed on the surface of an AISI 304SS substrate were characterized by x-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS), respectively. Vickers microhardness testing apparatus and a pin-on-disc tribometer were used to evaluate the microhardness, resistance to wear, and coefficient of friction (COF), respectively. The result demonstrates that a dense and defect-free composite coating with a strong metallurgical bond to the substrate is possible. The average microhardness of the TiB2 ceramic coating without Co addition was 1704 HV, and the average wear rate was 15.1576 × 10−9 g N−1-m−1. In contrast, the TiB2 ceramic coating with Co addition exhibited an improved average microhardness of 1860 HV and a reduced average wear rate of 22.7364 × 10−9 g N−1-m−1, while the AISI 304SS substrate had an average microhardness of 216 HV and an average wear rate of 200.45×10−9 g N−1-m−1. The conclusion is that the TiB2 ceramic coating with Co addition exhibited superior mechanical and tribological characteristics, demonstrating its suitability for use in wear-resistant components. The higher microhardness of the TiB2 ceramic with Co-added coating indicates enhanced hardness and potential resistance to deformation, while the lower wear rate suggests improved durability and the ability to withstand frictional forces. Therefore, the TiB2 ceramic coating with Co addition shows promise for applications where wear resistance is crucial.

Influence of Lanthanum oxide on AZ31 magnesium composite properties

Magnesium metal matrix composites are used for wear-resistance applications such as engine liners, cylinder blocks, and friction materials. In this study, AZ31+(0.5 to 2 wt%) La2O3 composites are prepared through a powder metallurgy process. Notably, when the percentage of La2O3 increase, the density of reinforced composites increases by 3%, and hardness increase by 25%. The microstructure mapping shows the homogeneous distribution of Mg, Al, Zn, La, and O elements throughout the composites. AZ31 + 1.5 wt% La2O3 composite has the lowest friction coefficient of 0.20 and lower wear rate of 2.73 × 10-3 mm3/m at 20 N. The worn surface of this composite has minor grooves, plows, and fewer wear particles compared to other composites.