An adaptive non-linear observer for the estimation of temperature distribution in the planar solid oxide fuel cell

Minimising the thermal gradients is extremely important in a planar solid oxide fuel cell (SOFC) for improving the cell life. The estimation of the temperature distribution in the cell is necessary to achieve this objective through suitable control, since they are not generally measurable. In this work, we have designed a non-linear adaptive observer for estimating the temperatures inside the hydrogen fed planar SOFC. The observer design is based on a lumped parameter model of the SOFC. The stability of the proposed observer is proven using the Lyapunov function method and is based on the concept of input-to-state stability for cascaded systems. The simulations show that the developed observer can track the temperature and species concentration profiles in the planar SOFC during step changes in the cell current. The adaptive observer presented is valid for a wide operating range, requires fewer variables to be measured, and is robust to fluctuations in the inlet flows.     

Dishing and nitride erosion of STI-CMP for different integration schemes

In this paper, we investigate the effects of integration schemes on the STI-CMP performance of two polishers, as well as the influence of consumables and process parameters. The experiment was based on both the blanket-oxide wafers and the patterned wafers processed using 0.18 μm technology. The polishing capability was evaluated, based on the results collected using metrology tools such as Opti-probe, Tencor profiler; atomic force microscope (AFM), and x-ray-scanning electron microscopy (X-SEM) analysis.     

Surfactant‐mediated synthesis of polyhydroxybutyrate (PHB) nanoparticles for sustained drug delivery

In this study, polyhydroxybutyrate (PHB) nanoparticles were synthesised following nanoprecipitation method having different solvents and surfactant (Tween 80) concentrations. In this study, PHB nanoparticles were encapsulated with curcumin and subjected for sustained curcumin delivery. Both the curcumin loaded and unloaded PHB nanoparticles were characterised using FTIR, SEM, and AFM. Sizes of the particles were found to be between 60 and 300 nm. The drug encapsulation efficiency and in vitro drug release of the nanoparticles were analysed. Antibacterial activity and anticancer activity were also evaluated. The LC₅₀ values of most of the nanoparticles were found to be between 10 and 20 µg/100 µl, anticancer activity of curcumin loaded PHB nanoparticles were further confirmed by AO/PI staining and mitochondrial depolarisation assay.Inspec keywords: encapsulation, cancer, scanning electron microscopy, nanoparticles, surfactants, drugs, nanofabrication, antibacterial activity, biomedical materials, drug delivery systems, polymers, nanomedicine, Fourier transform infrared spectra, precipitation (physical chemistry), atomic force microscopy, particle sizeOther keywords: surfactant‐mediated synthesis, polyhydroxybutyrate nanoparticles, sustained drug delivery, surfactant concentrations, PHB nanoparticles, sustained curcumin delivery, drug encapsulation efficiency, anticancer activity, in vitro drug release, nanoprecipitation method, Tween 80, FTIR spectra, SEM, AFM, particle sizes, antibacterial activity, AO‐PI staining, mitochondrial depolarisation assay     

Deep Learning Enabled Social Media Recommendation Based on User Comments

Nowadays, review systems have been developed with social media Recommendation systems (RS). Although research on RS social media is increasing year by year, the comprehensive literature review and classification of this RS research is limited and needs to be improved. The previous method did not find any user reviews within a time, so it gets poor accuracy and doesn’t filter the irrelevant comments efficiently. The Recursive Neural Network-based Trust Recommender System (RNN-TRS) is proposed to overcome this method’s problem. So it is efficient to analyse the trust comment and remove the irrelevant sentence appropriately. The first step is to collect the data based on the transactional reviews of social media. The second step is pre-processing using Imbalanced Collaborative Filtering (ICF) to remove the null values from the dataset. Extract the features from the pre-processing step using the Maximum Support Grade Scale (MSGS) to extract the maximum number of scaling features in the dataset and grade the weights (length, count, etc.). In the Extracting features for Training and testing method before that in the feature weights evaluating the softmax activation function for calculating the average weights of the features. Finally, In the classification method, the Recursive Neural Network-based Trust Recommender System (RNN-TRS) for User reviews based on the Positive and negative scores is analysed by the system. The simulation results improve the predicting accuracy and reduce time complexity better than previous methods.     

An evaluation of two-photon excitation versus confocal and digital deconvolution fluorescence microscopy imaging in Xenopus morphogenesis.

The ability to visualize cell motility occurring deep in the context of opaque tissues will allow many currently intractable issues in developmental biology and organogenesis to be addressed. In this study, we compare two-photon excitation with laser scanning confocal and conventional digital deconvolution fluorescence microscopy, using the same optical configuration, for their ability to resolve cell shape deep in Xenopus gastrula and neurula tissues. The two-photon microscope offers better depth penetration and less autofluorescence compared to confocal and conventional deconvolution imaging. Both two-photon excitation and confocal microscopy also provide improved rejection of "out-of-focus" noise and better lateral and axial resolution than conventional digital deconvolution microscopy. Deep Xenopus cells are best resolved by applying the digital deconvolution method on the two-photon images. We have also found that the two-photon has better depth penetration without any degradation in the image quality of interior sections compared to the other two techniques. Also, we have demonstrated that the quality of the image changes at different depths for various excitation powers.     

Compatibility of ZrN and HfN with molten LiCl-KCl-NaCl-UCl3

The reaction kinetics of ZrN and HfN immersed in a quaternary salt of composition of 28.5% LiCl-36.3% KCl-29.4% NaCl-5.8% UCl₃ (in weight percent) were assessed. Coupons of ZrN and HfN were exposed to the quaternary salt at 525-900 °C for 4-485 h. The reaction kinetics of the salt-refractory interactions were assessed through physical and microstructural characterization including scanning electron microscopy, X-ray diffraction and mass spectrometry. The results indicated that ZrN and HfN lose weight under all conditions investigated. While multiple mechanisms were evident, it is proposed that dissolution and oxidation were the dominant reactions that influence the weight loss. For the overall reaction, negative apparent activation energy values of −46 and −28 kJ/mol were observed in ZrN and HfN, respectively. These seemingly anomalous activation energies were associated with the simultaneous occurrence of electrochemical dissolution and surface oxide formation.     

An algorithm for hidden line ruled surface display using microprocessor

A simple algorithm for hidden line Ruled Surface graphics, typically used in Radio Astronomy is discussed using low cost microcomputer system built around Motorola 6800 processor and Matrox 256**2 graphics module of raster size 256 × 256 points. Resolution of the plot can be improved by displaying on a bigger raster like 1024 × 1024 points.     

Comparative study of room temperature control in buildings with and without the use of PCM in walls

The concept of thermal energy storage in building gains a specific importance in the present energy scenario related to energy consumption and indoor thermal comfort. The material used to store the thermal energy which undergoes a phase change referred as PCM and it is considered as a possible solution for reducing energy consumption in the building by storing and releasing heat within a certain temperature range; it raises the building inertia and also stabilizes indoor air temperature fluctuations. The room temperature is controlled by imposing PCM inside the walls. An attempt has been made to compare room air temperature with and without the use of PCM inside the walls of constructed modular building unit. The PCM imposed modular building shows the reduced temperature fluctuations in room, the PCM absorbs and liberates excess heat which is gained from the outer side of the room and maintains constant inner room temperature. The PCM imposed walls of modular building unit have an ability to reduce 10–30% of heat load in comparison with the plain wall. The results showed that reduction in room temperature is about 2–4°C and it has been concluded that the PCM imposed modular building unit has more energy saving opportunities than normal modular building unit.     

Statistical method‐based calibration and validation of a solid oxide fuel cell model

A 2‐stage model validation strategy for the previously developed solid oxide fuel cell model using the data from custom‐designed experiments is presented. The strategy is based on the identification of model structural and parametric errors. In the preliminary validation, the causes that can result in the voltage error during changing temperature and fuel flow rate conditions are analysed. It is identified that the convection heat transfer process contributes significantly towards the cell performance in a temperature controlled test environment. Rectification of this error results in the reduction of the maximum voltage error from 14% to 0.5%. Graphical methods for data visualisation are utilised to examine goodness of fit of the model. Input sensitivity analysis reveals that the air flow rate has negligible influence on the output quantities of current density, fuel utilisation, and cell temperature owing to temperature‐controlled conditions of the test. Parameter sensitivity analysis through the elementary effects method reveals that most of the electrochemical parameters in general and the activation energies in particular have dominant effects on the considered system outputs. Model validation is carried out through a classical statistical method of hypothesis testing by using the parameter uncertainty information obtained through nonlinear least squares fitting. The efficacy of the model validation strategy is demonstrated through the model acceptance with 8% maximum error in cell current.