Localized corrosion in selective laser melted SS316L in CO2 and H2S brines at elevated temperatures.

In this work, the passivation and localized corrosion of selective laser melted (SLM) stainless steel 316 L when exposed to high pressures of CO2 with the presence of H2S and Cl- at 25 °C and 125 °C were studied. Depletion of Cr/Mo was observed at the cell interiors and melt-pool boundaries (MPBs) compared to the cell boundaries. Volta potential differences obtained from scanning Kelvin probe force microscopy (SKPFM) showed that the MPBs were 8-20 mV lower than the matrix, while the cell interiors were 20-50 mV lower than the cell boundaries. Electrochemical impedance spectroscopy (EIS) and Mott-Schottky tests indicated a more defective passive film at 125 °C, and X-ray photoelectron spectroscopy (XPS) confirmed the formation of a less protective film with an increased S/O ratio at 125 °C than 25 °C. Initiation of localized corrosion was observed at the MPBs and pits formed after a week of immersion were wider by an order of magnitude at 125 °C than 25 °C, with evidence of cell-interior dissolution. While passivity was observed even at elevated temperatures, local chemical heterogeneities compromised the stability of the film and contributed to localized corrosion in SLM SS316L.

In vitro and in vivo study on fine-grained Mg-Zn-RE-Zr alloy as a biodegradeable orthopedic implant produced by friction stir processing.

Magnesium alloys containing biocompatible components show tremendous promise for applications as temporary biomedical devices. However, to ensure their safe use as biodegradeable implants, it is essential to control their corrosion rates. In concentrated Mg alloys, a microgalvanic coupling between the α-Mg matrix and secondary precipitates exists which results in increased corrosion rate. To address this challenge, we engineered the microstructure of a biodegradable Mg-Zn-RE-Zr alloy by friction stir processing (FSP), improving its corrosion resistance and mechanical properties simultaneously. The FS processed alloy with refined grains and broken and uniformly distributed secondary precipitates showed a relatively uniform corrosion morphology accompanied with the formation of a stable passive layer on the alloy surface. In vivo corrosion evaluation of the processed alloy in a small animal model showed that the material was well-tolerated with no signs of inflammation or harmful by-products. Remarkably, the processed alloy supported bone until it healed till eight weeks with a low in vivo corrosion rate of 0.7 mm/year. Moreover, we analyzed blood and histology of the critical organs such as liver and kidney, which showed normal functionality and consistent ion and enzyme levels, throughout the 12-week study period. These results demonstrate that the processed Mg-Zn-RE-Zr alloy offers promising potential for osseointegration in bone tissue healing while also exhibiting controlled biodegradability due to its engineered microstructure. The results from the present study will have profound benefit for bone fracture management, particularly in pediatric and elderly patients.

Development of Test Methods to Evaluate the Printability of Concrete Materials for Additive Manufacturing.

This study proposes test methods for assessing the printability of concrete materials for Additive Manufacturing. The printability of concrete is divided into three main aspects: flowability, setting time, and buildability. These properties are considered to monitor the critical quality of 3DCP and to ensure a successful print. Flowability is evaluated through a rheometer test, where the evolution of shear yield strength is monitored at a constant rate (rpm), similar to the printer setup. Flowability limits were set based on the user-defined maximum thickness of a printed layer and the onset of gaps/cracks during printing. Setting time is evaluated through an ultrasonic wave pulse velocity test (UPV), where the first inflection point of the evolution of the UPV graph corresponds to the setting time of the concrete specimen. The results from this continuous non-destructive test were found to correlate with the results from the discrete destructive ASTM C-191 test for measuring setting time with a maximum difference of 5% between both sets of values. Lastly, buildability was evaluated through the measurement of the early-age compressive strength of concrete, and a correlation with the UPV results obtained a predictive model that can be used in real-time to non-destructively assess the material buildability. This predictive model had a maximum percentage difference of 13% with the measured values. The outcome of this study is a set of tests to evaluate the properties of 3D printable concrete (3DP) material and provide a basis for a framework to benchmark and design materials for additive manufacturing.

Multilevel Self-Healing Characteristics of Smart Polymeric Composite Coatings.

Smart polymeric composite coatings demonstrating multilevel self-healing characteristics were developed and characterized. The pH-responsive smart carriers were synthesized by loading halloysite nanotubes (HNTs) with the benzotriazole corrosion inhibitor (BTA) using the vacuum cycling method, referred to as (BTA-loaded HNTs). Similarly, mechanically triggered melamine urea-formaldehyde microcapsules encapsulated with the boiled linseed oil-self-healing agent (LO) denoted as (MUFMCs) having an average size of a ∼120 µm diameter with a wall thickness of ∼1.84 µm were synthesized by the in situ polymerization technique. The newly designed double-layered smart polymeric composite coatings (DLPCs) were developed by mixing 3 wt % BTA-loaded HNTs with epoxy and applying it on the clean steel substrate to form a primer layer. After its complete curing, a top layer of epoxy containing 5 wt % of MUFMCs was deposited on it. For an exact comparison, single-layer polymeric composite coatings (SLPCs) containing 3 wt % BTA-loaded HNTs were also developed. The Fourier transform infrared radiation spectra of MUFMCs and BTA-loaded HNTs indicate the existence of all desired functional groups, confirming the presence of loaded chemical species such as LO and BTA into the smart carriers. Thermogravimetric analysis (TGA) indicates that ∼18% BTA is successfully loaded into HNTs. Quantitative UV-spectroscopic analysis indicates a pH-responsive release of BTA from BTA-loaded HNTs, which is time-dependent, attaining its maximum value of ∼ 90% in an acidic medium after 30 h. Electrochemical impedance spectroscopy analysis conducted in 3.5 wt % NaCl solution at room temperature for different immersion times reveals that SLPC exhibits the maximum charge-transfer resistance (Rct) of 55.47 GΩ cm2 after the 7th day of immersion, and then, a declining trend is observed, reaching 26.6 GΩ cm2 after the 9th day. However, in the case of DLPC, the Rct values show a continuous increment, attaining a maximum value of 82.11 GΩ cm2 after the 9th day of immersion. The improved performance of DLPC can be ascribed to the efficient triggering of the individual carriers in the isolated matrices, resulting in the release of LO and BTA to form individual protective films at the damaged area due to the oxidative polymerization process and triazoles' ability of passive film formation on the substrate, respectively. The tempting self-healing properties of DLPCs justify their decent role for long-term corrosion protection in many industrial applications.

Face-Based Attention Recognition Model for Children with Autism Spectrum Disorder.

Attention recognition plays a vital role in providing learning support for children with autism spectrum disorders (ASD). The unobtrusiveness of face-tracking techniques makes it possible to build automatic systems to detect and classify attentional behaviors. However, constructing such systems is a challenging task due to the complexity of attentional behavior in ASD. This paper proposes a face-based attention recognition model using two methods. The first is based on geometric feature transformation using a support vector machine (SVM) classifier, and the second is based on the transformation of time-domain spatial features to 2D spatial images using a convolutional neural network (CNN) approach. We conducted an experimental study on different attentional tasks for 46 children (ASD n=20, typically developing children n=26) and explored the limits of the face-based attention recognition model for participant and task differences. Our results show that the geometric feature transformation using an SVM classifier outperforms the CNN approach. Also, attention detection is more generalizable within typically developing children than within ASD groups and within low-attention tasks than within high-attention tasks. This paper highlights the basis for future face-based attentional recognition for real-time learning and clinical attention interventions. Supplementary Information: The online version contains supplementary material available at 10.1007/s41666-021-00101-y.

Reality-Based Technologies for Children with Autism Spectrum Disorder: A Recommendation for Food Intake Intervention.

Food selectivity by children with autism spectrum disorder (ASD) is relatively high as compared to typical children and consequently puts them at risk of nutritional inadequacies. Thus, there is a need to educate children with ASD on food types and their benefits in a simple and interesting manner that will encourage food acceptance and enable a move toward healthy living. The use of technological intervention has proven to be an effective tool for educating children with ASD in maintaining attention and mastering new skills as compared to traditional methods. Some of the popularly used technologies are computer-based intervention and robotics which do not support ecological validity (i.e., mimicking natural scenario). Consideration of natural factors is essential for better learning outcomes and generalized skills which can easily be incorporated into reality-based technologies such as virtual reality, augmented reality, and mixed reality. These technologies provide evidence-based support for ecological validation of intervention and sustaining the attention of children with ASD. The main objective of this study is to review existing reality-based technology intervention for children with ASD and investigate the following: (1) commonly used reality-based technology, (2) types of intervention targeted with reality-based technology, and (3) what subjects' inclusion types are used in the reality-based interventions. These objective statements have guided our recommendation of reality-based technology that can support ecological validity of food intake intervention.

Photo-regenerable multi-walled carbon nanotube membranes for the removal of pharmaceutical micropollutants from water.

Pharmaceutical micropollutants fall in the category of "emerging contaminants" in water because of their prevalence and persistence in the aqueous environment, and because of a poor understanding of their low-dose exposure effects on human and animal populations. In this study, photo-regenerable multiwalled carbon nanotube membranes with variable water permeabilities were produced by embedding hierarchical TiO2 structures (having porous, spherical morphology) onto a pre-deposited bed of multi-walled carbon nanotubes (MWNTs) using a modified sol-gel technique. These MWNT-TiO2 composites and their constituent materials were characterized by analytical electron microscopy, surface charge measurement, thermogravimetric analysis, and hydrophobicity determination. The adsorption removal potential of MWNT-TiO2 membranes was demonstrated for three representative pharmaceuticals: acetaminophen, carbamazepine and ibuprofen. The peak initial removal percentages of the pharmaceuticals by the MWNT-TiO2 membranes were 80%, 45%, and 24% for carbamazepine, ibuprofen, and acetaminophen, respectively. The ability of the membranes to be regenerated, once they were saturated with the pharmaceutical compounds, was verified by repeating the adsorption removal experiment on the same membranes after exposure to UV light at 254 nm. Peak removal efficiencies after regeneration were 55%, 32%, and 19% for carbamazepine, ibuprofen, and acetaminophen, respectively, indicating some loss in sorptive capacity upon regeneration. Furthermore, the effect of pH on adsorption of ibuprofen, the pharmaceutical that attained the highest mass loading on the sorbent at equilibrium saturation, was studied and its mechanism of adsorption was proposed at pH below pKa.