Lubrication of polyether ether ketone (PEEK) surface by liquid ultrathin films for high wear durability

PEEK, an engineering polymer with many advantages such as lightweight, high thermal stability, high strength coupled with toughness, has often been used as a substitute for metals in applications such as bearings, piston parts, pumps and even biomaterials. However, it shows high coefficient of friction which results in high wear rate when used in tribological applications. This paper seeks to solve tribological problems of high friction and wear for PEEK by applying an ultrathin layer of perfluoropolyether (PFPE) and Multiply-Alkylated Cyclopentane (MAC) lubricants on the surface of PEEK. Results obtained from tribological tests conducted showed that for highly improved tribological performance, there is an optimal initial surface roughness of PEEK surface and lubricant concentration or the thickness of the coatings for both PFPE and MAC lubricant. Also, MAC performs better compared to PFPE for thinner films.     

Interconnected Hydroxyapatite Nanofibers in the Biomimetic Coating of a Bioinert Ceramic Substrate

A bioinert ceramic substrate, α-Al₂O₃, has been coated with hydroxyapatite (HAp) by the biomimetic route using simulated body fluid (SBF) solution at room temperature. The substrate was incubated at 37°C in SBF for 6 days with a periodic replacement with freshly prepared SBF at 48-h intervals. After 6 days, continuous nanofiber-like structures of HAp (5–35 μm in length, 0.05 μm diameter) were obtained, connecting the intra- and interglobular clusters, within the coated mineral layer on the substrate surface. This is a unique and new observation, and this phenomenon has been demonstrated by a simple fractal growth model.     

Simulation studies on the nature of fractal dimensions of glass-ceramics at percolation threshold

We simulate the fractal dimensions (D) of glass-ceramics resulting from different glass microstructures, at their percolation thresholds. We consider only crystallisation in glasses resulting from phase separation by nucleation. Phase separation may occur at a lower temperature or at the same temperature at which crystallisation takes place. We have studied both cases. The structure-property relationship of such glass-ceramics is dictated by the evolution of the structure of crystalline phase percolation cluster. At the percolation threshold the structure of the percolation path may be quantified by its fractal dimensionality (D). The value of D displays universal behaviour for a system in the thermodynamic limit. However, it deviates owing to finite size effects. Our simulations suggest that these deviations for a given system size depend on the nature of the glass microstructure. As the value of D reaches Euclidean dimension, the system attains more compact percolation cluster. This has invariably occurred in the present investigation for fine crystalline phase microstructure.     

Planning for the Subernarekha river system in eastern India

The study describes the systems studies carried out to plan a river basin in order to determine the nature and size of water storage facilities and releases for irrigation and industrial uses, and the associated cropping pattern. The model has been formulated in the framework of a linear programming model for a specific target year. This model is developed in the context of planning the Subernarekha river basin. The results are discussed and these provide information and insight suggesting the need for more disaggregated analysis of interaction between irrigation and related agroeconomic parameters.     

Near-optimal control using reduced-order models

Two theorems have been proved demonstrating that the tracking properties of low-order models obtained using the theory of partial realisations are unchanged under state or output feedback. It follows, therefore, that an optimal feedback law for the reduced-order model can be used for near-optimal control of the high-order system with similar tracking of the output as for the open-loop case.     

Prediction of burning rate of coal in fluidized-bed combustion

A theory has been proposed to evaluate the burning rate of a single carbon particle in a continuously operated coal-fired fluidized bed. Experimental verification was carried out in a laboratory scale 200 mm × 200 mm combustor. The burning rate increases with the increase of the fluidization velocity and the size of the bed material. The predicted data on burning rate agree fairly well with the experimental values. The gas concentration in the bed and freeboard has also been measured and it is seen that the consumption of oxygen mostly takes place in the bed.     

THERMAL STRESSES FOR AN INFINITE BODY WITH A SPHERICAL CAVITY WITH TWO RELAXATION TIMES

Thermoelastic interactions caused in a homogeneous and isotropic infinite body with a spherical cavity are considered for the two different theories of generalized thermoelasticity, that is, Lord, and Shulman's theory and Green and Lindsay's theory. Analytical expressions for the temperature, displacement, and thermal stress fields are obtained; and the results are compared with the classical dynamical coupled theory.     

Application of novel polar representation method for monitoring minor engine condition variations

In an earlier study, a Noval Polar Presentation (NPP) method has been suggested to detect the engine combustion-related faults for medium-speed diesel engines. The earlier proposed NPP method basically used the signature of the crankshaft torsional vibration to identify the faulty cylinder accurately. However, the detection of only a large fault like the cylinder misfiring for the 2 typical engines (16-cylinder and 20-cylinder engines) has been demonstrated in the earlier study. Now the usefulness of the NPP method in detection of even a very small level of the engine combustion fault like an earlier or later opening of the fuel injection valve by just a few degrees has been presented here.     

Modeling and simulation of temperature drift for ISFET-based pH sensor and its compensation through machine learning techniques

The paper presents modeling and simulation of ion-sensitive field-effect transistor (ISFET)-based pH sensor with temperature-dependent behavioral macromodel and proposes to compensate the temperature drift in the sensor using intelligent machine learning (ML) models. The macromodel is built using SPICE by introducing electrochemical parameters in a metal-oxide-semiconductor field-effect transistor (MOSFET) model to simulate ISFET characteristics. We account for the temperature dependence of electrochemical and semiconductor parameters in our macromodel to increase its robustness. The macromodel is then exported as a subcircuit element, which is used to design the readout interface circuit. A simple constant-voltage, constant-current (CVCC) topology is utilized to generate the data for temperature drift in ISFET pH sensor, which is used to train and test state-of-the-art ML-based regression models in order to compensate the drift behavior. The experimental results demonstrate that the random forest (RF) technique achieves the best performance with very high correlation and low error rate. Corresponding curves for output signal using the trained models show highly temperature-independent characteristics when tested for pH 2, 4, 7, 10, and 12, and we obtained a root mean squared error (RMS) variation of ΔpH ≤ 0.024 over a temperature range of 15°C to 55°C in comparison with ΔpH ≤ 1.346 for uncompensated output signal. This work establishes the framework for integration of ML techniques for drift compensation of ISFET chemical sensor to improve its performance.