We characterized manufacturing-induced defects in 316L stainless steels - fabricated by direct metal laser sintering (DMLS) - and investigated their roles in the fatigue behavior of steel parts. The primary defects targeted are porosities, inner cracks, and edge cracks. We used Convolutional Neural Networks (CNNs) to detect and classify these defects and moved toward a machine vision-based metrology technique for metal additive manufacturing (AM). The Moore cyclic loading method was applied to characterize the fatigue behavior of 316L samples. The results indicate a strong correlation between the quality of additive manufacturing, defect levels, and the fatigue properties of the steel samples. Specifically, samples with lower defect levels exhibited significantly higher load endurance and longer life cycles. To further explore the influence of defects on mechanical behavior, we applied image processing techniques to measure the density, size, morphology, and location of defects in the steels. The quantification of AM defects features paves the way for a deeper understanding of microstructure – macro-behavior relations and enhanced fatigue prediction models in additively manufactured steels.
Understanding how inducing molecular alignment can influence pyrolytic carbon microstructure and functionality is consequential for carbon MEMS microfabrication and applicability. We present a comparative analysis on the effects of compressive stress versus standard tensile treatment of carbon precursors. Different characterization techniques reveal that while subjecting precursor molecules to both types of mechanical stresses will induce graphitization in the pyrolytic carbon, this effect is more pronounced in compressive stress. MEMS functionality of the two carbons was evaluated by characterizing the electrochemical performance of their electrodes. Both carbons exhibited enhanced electrochemical performances. However, the heterogeneous electron transfer rate derived from CV diagrams reveals compression-activated electrode to have remarkably faster kinetics. The results show the versatility of pyrolytic nanocarbons and a synthesis route to tailor functionality for MEMS and Sensors.
Iodine is an essential micronutrient in modulating critical functions of the body, such as producing thyroid hormones. A deficiency of iodine can cause severe thyroid-related disorders [2], while high doses of iodine can trigger overproduction of thyroid hormones, increasing the risk of developing thyroid dysfunction [1,2]. Therefore, it is critical to assess the iodine concentration in body fluids to monitor and diagnose early signs of diseases. Here we report on a simple, rapid, and highly-sensitive electrochemical detection of urinary iodine (UI) by exploiting the exceptional electrocatalytic capabilities of stress-activated pyrolytic carbon nanofibers (SAPCs). SAPCs are synthesized by stress-induced molecular alignment and subsequent low-temperature pyrolysis of organic carbon precursors. The resulting carbon possesses highly-graphitic structures that are characteristically rich in nitrogen heteroatoms and edge planes [3,4]. The tunable surface of SAPCs can also enhance the sensitivity and specificity of iodide ions in human urine. Furthermore, the high macroporosity of SAPCs increases surface area, creating a large liquid-carbon junction in aqueous solutions, providing efficient ion transport and adsorption capacity. The sensitivity and limit of detection (LoD) of SAPCs were evaluated by obtaining the linearity of molar concentration of iodide ions (I-) vs. current. The sensor specificity of SAPCs electrode for iodide ions was also investigated by adding a series of competitive anions such as F-, Cl-, PO43-, HPO42-, and H2PO4- into the solution and evaluating the effect of interference substances electrochemically. Additionally, the reproducibility of SAPCs for iodide ion detection was assessed by measuring the inter- and intra- coefficients of variability (CV%).
Carbon nanomaterials have shown promise as biocompatible, conductive scaffolds that direct neural tissue regeneration. The goal is to influence stem cell fate by engineering a controlled micro- and macro- environment that imitates living tissue, while simultaneously monitoring cell metabolites. To approach this goal, we synthesized a highly porous, pyrolitic nanofiber carbon material through a stress-induced graphitization process [1]. The carbon macrostructure was synthesized to have either a random or aligned orientation by controlling nanofiber deposition using an electrospinning technique. The resulting carbon has ideal conductive properties for electrical stimulation, a microstructure allowing for mechanical stimulation, and a controlled, porous 3D geometry mimicking the extracellular matrix (ECM) of mature cells. The unique graphitic structure is abundant in nitrogen heteroatoms and edge planes, which not only improves its electrochemical kinetics (with heterogeneous electron transfer rate of koapp = 0.2 cm/s in dopamine) but also promotes cellular adhesion by increasing nucleation sites for stem cells to attach and form neural networks. The compatibility of the carbon material as a stem cell scaffold was assessed by successfully growing and differentiating mouse neural stem cells (NSCs) on the untreated material without the addition of any ECM proteins or adhesion factors. The influence of fiber alignment on stem cell fate was also studied by growing NSCs on the carbon material with both aligned and randomly oriented nanofibers. Finally, the ability of the material to act as a simultaneous scaffold and sensor was assessed by measuring extremely low concentrations (<1μM) of dopamine in cell media.
[1] Ghazinejad, Maziar, et al. "Graphitizing non-graphitizable carbons by stress-induced routes." Scientific reports 7.1 (2017): 16551.
Owing to its superb thermal and electrical attributes, as well as electrochemical stability, carbon is emerging as an attractive material for fabrication of many bioelectrochemical devices such as biosensors and biofuel cells. However, carbon’s inert nature makes it difficult to functionalize with biocatalysts; often requiring harsh chemical treatment, such as nitric acid oxidation, to attach reactive amines and carboxylic acids to its surface. Recent studies, however, points toward a self-assembly approach for fabricating well organized layers of carbon loaded with arrays of metallic nanoparticles patterned by block-copolymers (BCP) templates. Herein, we demonstrate an effective method for developing carbon nanofibers meshes embedded with metal nanoparticles, by incorporating a BCP self-assembly approach into our C-MEMS fabrication technique. The main phase of this hybrid method includes electrospinning metal salt-loaded BCP into nanofiber meshes, and subsequently reducing the metal salts into metal nanoparticles prior to pyrolysis. This cost-effective process will pave the way for fabricating scalable advanced 3-D carbon electrodes that can be applied to biosensors and biofuel cells devices.
Porous fibrous membranes having multiple scales geometries and tailored properties have become attractive microfabrication materials in recent years. Due to the feasibility of incorporating graphene in electrospun nanofibres and the growing interest on these nanomaterials, the present paper focuses on the electrospinning of Poly (ε-Caprolactone) (PCL) solutions in the presence of different amounts of Graphene platelets. Electrospinning is a process whereby ultrafine fibers are formed in a high-voltage electrostatic field. The morphological appearance, fiber diameter, and structure of PCL nanofibers produced by the electrospinning process were studied in the presence of different concentration of graphene. Moreover, the effect of a successful incorporation of graphene nanosheets into PCL polymer nanofibers was analyzed. Scanning electron microscope micrographs of the electrospun fibers showed that the average fiber diameter increases in the presence of graphene. Furthermore, the intrinsic properties developed due to the interactions of graphene and PCL improved the mechanical properties of the nanofibers. The results reveal the effect of various graphene concentrations on PCL and the strong interfacial interactions between the graphene platelets phase and the polymer matrix. The functional complexity of the electrospun fibers provides significant advantages over other techniques and shows the promise of these fibers for many applications including air/water filters, sensors, organic solar cells, smart textiles, biocompatible scaffolds for tissue engineering and load-bearing applications. Optimizing deposition efficiency, however, is a necessary milestone for the widespread use of this technique.
We investigate the application of fluorescence quenching microscopy (FQM) for visual characterization of graphene quality, number of layers and uniformity over its landscape. The method relies on the fact that pristine, modified and multi-layer graphene regions quench fluorescence with different rates. Steady-state and time-resolved emission spectroscopy are used to comparatively characterize the photophysical behavior of pristine graphene relative to unquenched dye on bare substrate. The results demonstrate that with premeditated choice of Fluorescence dye, the interaction between fluorophores and graphene provides valuable tools for identifying the chemical structure and thickness of graphene. Fluorescence quenching metrology can be implemented as the basis for a microscopy based metrology for 2D materials.
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