Investigation of in vitro bone cell adhesion and proliferation on Ti using direct current stimulation

Our objective was to establish an in vitro cell culture protocol to improve bone cell attachment and proliferation on Ti substrate using direct current stimulation. For this purpose, a custom made electrical stimulator was developed and a varying range of direct currents, from 5 to 25 μA, was used to study the current stimulation effect on bone cells cultured on conducting Ti samples in vitro. Cell–material interaction was studied for a maximum of 5 days by culturing with human fetal osteoblast cells (hFOB). The direct current was applied in every 8 h time interval and the duration of electrical stimulation was kept constant at 15 min for all cases. In vitro results showed that direct current stimulation significantly favored bone cell attachment and proliferation in comparison to nonstimulated Ti surface. Immunochemistry and confocal microscopy results confirmed that the cell adhesion was most pronounced on 25 μA direct current stimulated Ti surfaces as hFOB cells expressed higher vinculin protein with increasing amount of direct current. Furthermore, MTT assay results established that cells grew 30% higher in number under 25 μA electrical stimulation as compared to nonstimulated Ti surface after 5 days of culture period. In this work we have successfully established a simple and cost effective in vitro protocol offering easy and rapid analysis of bone cell–material interaction which can be used in promotion of bone cell attachment and growth on Ti substrate using direct current electrical stimulation in an in vitro model.     

Sustainable hydrogen production by catalytic hydrolysis of alkaline sodium borohydride solution using recyclable Co-Co2B and Ni-Ni3B nanocomposites

In this article, we report Co-Co₂B and Ni-Ni₃B nanocomposites as catalyst for hydrogen generation from alkaline sodium borohydride. Kinetic studies of the hydrolysis of sodium borohydride with Co-Co₂B and Ni-Ni₃B nanocomposites reveal that the concentration of NaBH₄ has no effect on the rate of hydrogen generation. Hydrolysis was found to be first order with respect to the concentration of catalyst. The catalytic activity of Co-Co₂B was found to be much higher than that of Ni-Ni₃B as inferred from the activation energies 35.245 KJ/mol and 55.810 kJ/mol, respectively. Co-Co₂B nanocomposites were found to be more magnetic than Ni-Ni₃B. These catalysts showed superior recyclability with almost the similar catalytic activities for several hydrolytic cycles supporting the principles of sustainability. Co-Co₂B catalyst showed hydrogen generation rate of about 4300 mL/min/g which is comparable to most of the reported good catalysts till date.     

Hardystonite improves biocompatibility and strength of electrospun polycaprolactone nanofibers over hydroxyapatite: A comparative study

The aim of this study was to compare physico-chemical and biological properties of hydroxyapatite (HA) and hardystonite (HS) based composite scaffolds. Hardystonite (Ca₂ZnSi₂O₇) powders were synthesized by a sol–gel method while polycaprolactone–hardystonite (PCL–HS) and polycaprolactone–hydroxyapatite (PCL–HA) were fabricated in nanofibrous form by electrospinning. The physico-chemical and biological properties such as tensile strength, cell proliferation, cell infiltration and alkaline phosphatase activity were determined on both kinds of scaffolds. We found that PCL–HS scaffolds had better mechanical strength compared to PCL–HA scaffolds. Addition of HA and HS particles to PCL did not show any inhibitory effect on blood biocompatibility of scaffolds when assessed by hemolysis assay. The in vitro cellular behavior was evaluated by growing murine adipose-tissue-derived stem cells (mE-ASCs) over the scaffolds. Enhanced cell proliferation and improved cellular infiltrations on PCL–HS scaffolds were observed when compared to HA containing scaffolds. PCL–HS scaffolds exhibited a significant increase in alkaline phosphatase (ALP) activity and better mineralization of the matrix in comparison to PCL–HA scaffolds. These results clearly demonstrate the stimulatory role of Zn and Si present in HS based composite scaffolds, suggesting their potential application for bone tissue engineering.     

Synthesis of copper-ferrous (CuFe) nanowires via electrochemical method and its investigations as a fluid sensor

The special behaviour of nanowires with respect to electrical conductivity makes them suitable for sensing application. In this paper, we present a copper-ferrous (CuFe) nanowires based sensor for detection of chemicals. CuFe nanowires were synthesized by template-assisted electrochemical method. By optimizing the deposition parameters, continuous nanowires on a copper substrate were synthesized. The morphological and structural studies of the synthesized CuFe nanowires were carried out using scanning electron microscope (SEM) and X-ray diffraction (XRD). Substrates containing CuFe nanowires were moulded to form a capacitor. Different chemicals were used as dielectric in the capacitor which showed that the capacitance was a nonlinear function of the dielectric constant of fluid unlike the linear relation shown by conventional capacitors. This unique property of the nanowires based capacitors may be utilized for developing fluid sensors with improved sensitivity.     

3D study of temperature drop behavior of subsonic rarefied gas flow in microchannel

3D Numerical study of temperature variation for subsonic rarefied gas flow in a microchannel is carried out using an in-house MPI-based parallelized DSMC code. The temperature drop in the microchannel decreases with an increase in the aspect ratio whereas it increases with an increase in the pressure ratio, the cross-aspect ratio (CAR), and the Knudsen number. 3D and 2D simulations results are compared and effect of the CAR and Knudsen number are brought out. Finally, a correlation that predicts the temperature drop is formulated along with a list of conditions that ensures a near isothermal flow.     

Continuous prediction of manufacturing performance throughout the production lifecycle

We describe methods for continual prediction of manufactured product quality prior to final testing. In our most expansive modeling approach, an estimated final characteristic of a product is updated after each manufacturing operation. Our initial application is for the manufacture of microprocessors, and we predict final microprocessor speed. Using these predictions, early corrective manufacturing actions may be taken to increase the speed of expected slow wafers (a collection of microprocessors) or reduce the speed of fast wafers. Such predictions may also be used to initiate corrective supply chain management actions. Developing statistical learning models for this task has many complicating factors: (a) a temporally unstable population (b) missing data that is a result of sparsely sampled measurements and (c) relatively few available measurements prior to corrective action opportunities. In a real manufacturing pilot application, our automated models selected 125 fast wafers in real-time. As predicted, those wafers were significantly faster than average. During manufacture, downstream corrective processing restored 25 nominally unacceptable wafers to normal operation.