Iron foams are potential materials for the production, purification, and recuperation of hydrogen through redox systems. They are inexpensive, recyclable, and environmentally friendly. Nevertheless, iron foams cannot be employed repeatedly for redox cycling at high temperatures because the structure suffers morphological changes and a decrease in the effective porosity. In this work, two different pore structures of Fe-foams fabricated by freeze-casting have been produced: constant (CP) and gradient (GP) pore size. CP Fe-foams were obtained by employing a double-sided cooling technique to minimize gradients in pore width that result when using one-sided, constant cooling solidification techniques. GP Fe-foams were manufactured using a fixed-temperature cold plate. Optical microscopy and X-ray tomography were employed to characterize the pore structure and, for GP Fe-foams, to investigate the effect of redox cycling. After redox cycling, GP Fe-foams exhibited significant pore degradation.

At GE Research, we are combining “physics” with artificial intelligence and machine learning to advance manufacturing design, processing, and inspection, turning innovative technologies into real products and solutions across our industrial portfolio. This article provides a snapshot of how this physical plus digital transformation is evolving at GE.

The study of the relationship among the manufacturing process, the structure and the property of materials can help to develop the new materials. The material images contain the microstructures of materials, therefore, the quantitative analysis for the material images is the important means to study the characteristics of material structures. Generally, the quantitative analysis for the material microstructures is based on the exact segmentation of the materials images. However, most material microstructures are shown with various shapes and complex textures in images, and they seriously hinder the exact segmentation of the component elements. In this research, machine learning method and complex networks method are adopted to the challenge of automatic material image segmentation. Two segmentation tasks are completed: on the one hand, the images of the titanium alloy are segmented based on the pixel-level classification through feature extraction and machine learning algorithm; on the other hand, the ceramic images are segmented with the complex networks theory. In the first task, texture and shape features near each pixel in titanium alloy image are calculated, such as Gabor filters, Hu moments and GLCM (Gray-Level Co-occurrence Matrix) etc.. The feature vector for the pixel can be obtained by arraying these features. Then, classification is performed with the random forest model. Once each pixel is classified, the image segmentation is completed. In the second task, a complex network structure is built for the ceramic image. Then, a clustering algorithm of complex network is used to obtain network connection area. Finally, the clustered network structure is mapped back to the image and getting the contours among the component elements. The experimental results demonstrate that these methods can accurately segment material images.

Selective Laser Melting (SLM) involves numerous fabrication parameters, the interaction between those parameters determine the final characteristics of the resulting part and because of the latter, it is considered a complex process. Low-density components is one of the main issues of the SLM process, due to the incorrect selection of process parameters. These defects are undesired in high specialized applications (i.e. aerospace, aeronautic and medical industries). Therefore, the characterization of the defects (pores) found in aluminum parts manufacture by SLM and the relationship with fabrication parameters was performed. A robust orthogonal design of experiments was implemented to determine process parameters, and then parts were manufactured in SLM. Relative density of the samples was then characterized using the Archimedes principle and microscopy; the data was then statistically analyzed in order to determine the optimal process parameters. The main purpose of the present research was to establish the best processing parameters of an in-house SLM system, as well as to characterize the pore geometry in order to fully eliminate pores in a future research.

To eliminate the effect of subjective factors during manually determining the pearlite spheroidization grade of steel by analysis of optical metallography images, a novel method combining image mining and artificial neural networks (ANN) is proposed. The four co-occurrence matrices of angular second moment, contrast, correlation, and entropy are adopted to objectively characterize the images. ANN is employed to establish a mathematical model between the four co-occurrence matrices and the corresponding spheroidization grade. Three materials used in coal-fired power plants (ASTM A315-B steel, ASTM A335-P12 steel, and ASTM A355-P11 steel) were selected as the samples to test the validity of our proposed method. The results indicate that the accuracies of the calculated spheroidization grades reach 99.05, 95.46, and 93.63%, respectively. Hence, our newly proposed method is adequate for automatically detecting the pearlite spheroidization grade of steel using optical metallography.

Continuous fiber reinforced composites (RFC) are hierarchal and complex at multiple scales. In this work, tools are developed to automate the 3D characterization and quantification of the overall microstructure. Structure quantification enables accurate representation for material simulation and property prediction for the integrated computation materials engineering (ICME) of RFC based components. Relationships are developed to describe the key attributes of the microstructure at multiple scales including the individual fibers, tows, weave, porosity, and secondary matrix phases, which are treated as 'gestalts' of the structure. Here gestalt refers to the essence of shape or complete form of key features of the microstructure such as those of the tow architecture of the textile. Visualization tools are developed based on an artificial color scheme that allow the visual recognition of whole tows instead of just the collection of simple lines and curves representative of the fibers, which provides means whereby the gestalt of the microstructure can be visualized at the tow scale. These tools are demonstrated using a 3D dataset of the SiNC/SiC S200 ceramic matrix composite material (CMC) obtained via automated serial sectioning. Methods are then demonstrated to generate microstructure models representative of the characterized material for finite element analyses (FEA).

In this work we compare two different detection schemes that are sensitive to the focus shift of a probe beam due to induced surface curvature. The technique on which both detection schemes are based is called ThERM (Thermal Expansion-Recovery Microscopy) and allows the retrieval of the thermal diffusivity at microscopic levels, hence mapping such magnitude over a sample surface. The induced thermal expansion defocuses the probe beam due to the surface deformation (curvature). The dependence of the defocusing with the pump modulation frequency yields the thermal diffusivity of the sample at the impinging location. The explored depth is controlled by the pump beam size. By scanning both beams, a complete map of the thermal diffusivity can be retrieved.

In this paper was study the effect of heat treatment on mechanical properties of an API X-60 steel used for storage and transportation of hydrocarbons.In the first stage evaluation are mechanical properties of steel heat treated by the technique of the three-point test according to ASTM 399-90 was carried out. In the second stage, characterization of the type of failure and microstructure through optical microscopy (OM) was determined; also heat treated samples were then mechanically tested for hardness (HRC) and nano-indentation. The presence of alloying elements by scanning electron microscopy (SEM) and the fracture surfaces generated in the steel with varying times, temperatures and cooling medium generated by different modes of solicitation (Bending), likewise with loading rates were determined. The results revealed a ductile fracture and microstructures (PF) ferrite-pearlite (DP), bainite -ferrite (BF) and martensite-retained and martensite/retained austenite (MA). Finally, this article discusses the effect of heat treatment followed by precipitation hardenable of steel API X-60 on the mechanical properties

In this research we studied the fracture of a cast iron drum for 3.5 ton trucks, and it seeks to determine the causes that led to a series of cracks in different areas of the part of drum brake during the manufacturing process, casting or machining. The work followed the methodology usually used in failure analysis; we used the following analytical techniques: visual inspection, penetrating liquids, fractography, metallography, chemical analysis and mechanical testing of hardness. The analysis of the automotive part surface is divided into four sections which are the flange, track, belt and covers powders which were evaluated by the above techniques to determine the failure of the piece. Metallography analysis in each section of the piece showed different microstructure on gray cast iron; showing that pieces works with different cooling conditions during manufacture, giving a mechanism of failure-prone fragile.

Titanium alloys are among the most used metallic biomaterials, particularly for orthopedic applications. Ever since the pioneer titanium alloy (Ti6Al4V) has been used as biomaterial, lack of biocompatibility has been extensively reported and propelled research on improved materials with appropriate mechanical behavior and adequate biocompatibility. Studies have indicated that vanadium produces oxides harmful to the human body; in order to replace vanadium containing Ti alloys, Ti-6Al-7Nb was developed. Today this alloy is the preferred choice for cementless total joint replacements. It is very important to produce a nanostructured bioactive metal implant with appropriate mechanical properties and we applied a chemical and thermal treatment that converts the surface of titanium alloy into bioactive surface. Therefore, bioactive Ti6Al7Nb might represent an alternative for advanced orthopedic implants under load-bearing conditions.

Eleven mini-pigs weighting around 50 kg, with free access to food pellets and water, were the experimental animals for this study. Ten of these pigs (one is the control) were anesthetized and after shaving, disinfection and draping, a straight 3 cm incision was made and the implants (plate and pin) were implanted into the epiphyses of the tibiae. Surgical procedures were performed bilaterally. At 6 months after implantation, the mini-pigs were sacrificed.

After sacrifice, the segments of the proximal tibia epiphyses containing the implanted plates and pins were cut of, fixed in phosphate-buffered formalin and dehydrated in serial concentrations of ethanol after which they were embedded in polyester resin and then cutted and grounded to a thickness of 75-100 μm. With these samples a lot of observations were made: Scanning Electron Microscopy observations, histological examination at implant surface and histological examination of the bone-implant surface and SEM-EDX examinations were also made.

All the results revealed that the plates and pins are in direct contact with newly formed bone without any intervening soft tissue layer. We regard osteoinductive ability of nanostructured Ti6Al7Nb as one of the advantages of this implant in consideration for clinical applications.

In this work were evaluated the microestructural characteristics by Optical Microscopy (OM) and Scanning Electron Microscopy (SEM) of the intermetallic γ'(liquation, coarsening and decomposition) in the Inconel 939 alloy after 40000 hours and 850–900°C aging operation conditions. The alloy was vacuum conventional cast. The results show that the liquation phenomena take place in eutectics γ-γ' which are present mainly in the core of the dendritic arms and in the coarse films of carbides along the grain boundaries (GB), the γ' particles change their original morphology of ordered cuboids of 320nm to disordered and coarse cuboids of 1.2μm, carbides show a morphology change from the original dispersed particles into a coarse continuous films and particles Chinese script type, this affects adversely the mechanical properties such as creep. The results of this evaluation allow to determine the main microestructural damage mechanisms which experiment some components such as blades at high temperatures in industrial conditions.

Three nickel-base austenitic alloys, namely Alloy C-22, Alloy C-276 and Waspaloy have been tested for evaluation of their corrosion resistance in an acidic solution at ambient and elevated temperatures. The results of stress corrosion cracking studies indicate that none of these materials did exhibit any failure at constant load. The cracking susceptibility determined by the slow strain rate technique was gradually enhanced at higher temperatures showing reduced ductility and true failure stress. The critical potentials determined by the polarization technique, became more active (negative) with increasing temperature. The fractograpic evaluations by scanning electron microscopy (SEM) revealed ductile failure in Alloys C-22 and C-276. However, Waspaloy showed brittle failure at elevated temperature.

A variety of α, α'-subtituted quaterthiophenes containing ester, amide and polymerizable side chains have been synthesized and fully characterized. The self-assembly properties of these oligothiophenes were studied as function of the side chain. Introduction of amide functionalities highly promotes the self-assembly via π-stacking and hydrogen bond interactions, while the lack of amides prevent aggregate formation. Initial experiments show that by introducing a sorbyl moiety as a polymerizable group it is possible to achieve covalent fixation of the oligothiophene units in the self-assembled state.

The degree of undercooling of Sn in near eutectic, SnAgCu solder balls upon cooling at a rate of 1 °C/s from the melt was examined and found to increase linearly with inverse nominal sample diameter (for balls of radius between 100 and 1000 μm). The mean undercooling for SnAgCu solder balls in a flip chip assembly was 62 °C. The microstructures of these different samples were examined by means of scanning electron microscopy. The Sn dendrite arm width was observed to monotonically increase with ball diameter, indicating a possible dependence of the mechanical response of such solder balls upon size.