Fabricated carbon from minimally processed coke and coal tar pitch as a carbon-sequestering construction material

We report the mechanical fracture strength and physical properties of fabricated carbons made from pulverized metallurgical coke bonded with coal tar pitch, followed by pyrolysis. Tensile strength from diametral compression of discs ranged from 9.7 ± 1.3 MPa for materials bonded with 13 wt% pitch to 63 ± 7.1 MPa for materials bonded with 40 wt% pitch. Materials made by dry mixing pulverized pitch with coke were comparable with materials made by mixing coke powder with a solution of pitch in toluene. Strength increased with pyrolysis temperature. Pyrolyzed pitch-bonded coke was significantly stronger and lighter than ordinary Portland cement concrete.     

Targeted disruption of fibroblast growth factor (FGF) receptor 2 suggests a role for FGF signaling in pregastrulation mammalian development

We disrupted the fibroblast growth factor (FGF) receptor 2 (FGFR2) gene by introducing a neo cassette into the IIIc ligand binding exon and by deleting a genomic DNA fragment encoding its transmembrane domain and part of its kinase I domain. A recessive embryonic lethal mutation was obtained. Preimplantation development was normal until the blastocyst stage. Homozygous mutant embryos died a few hours after implantation at a random position in the uterine crypt, with collapsed yolk cavity. Mutant blastocysts hatched, adhered, and formed a layer of trophoblast giant cells in vitro, but after prolonged culture, the growth of the inner cell mass stopped, no visceral endoderm formed, and finally the egg cylinder disintegrated. It follows that FGFR2 is required for early postimplantation development between implantation and the formation of the egg cylinder. We suggest that FGFR2 contributes to the outgrowth, differentiation, and maintenance of the inner cell mass and raise the possibility that this activity is mediated by FGF4 signals transmitted by FGFR2. The role of early FGF signaling in pregastrulation development as a possible adaptation to mammalian (amniote) embryogenesis is discussed.     

Analysis of nanofluid transport through a wavy channel

Laminar forced convection of heat transfer and pressure drop of Al₂O₃ and CuO/water nanofluids flow through a horizontal tube and wavy channel under constant wall temperature boundary condition is numerically investigated. Two different models were employed in our study: single phase (homogenous and dispersion) and two phase (Lagrangian–Eulerian model or discrete-phase model (DPM) and the mixture). The effects of various parameters, such as particle concentration, particle diameter, particle type, constant or temperature-dependent properties, wave amplitude, Reynolds number and Peclet number on the thermal, and flow field of the Nanofluids are analyzed. Our results revealed that variable properties assumption play a dominant role in horizontal tubes and provide better predictions for the heat transfer enhancement. The difference between constant and variable properties becomes insignificant and can be ignored in wavy channel due to the high mixing and generated recirculation zones, whereas the difference between the DPM and the single-phase variable properties diminish as Peclet number and volume fraction increases. However, dispersion model shows an excellent agreement with the experimental data; the absence of the reference values for the adjustable factor C_d in the open literature put it in a questionable position. Therefore, DPM and homogenous single-phase model with well-chosen thermal conductivity and viscosity correlations can be considered as an accurate way and more dependable in nanofluid simulations especially the homogenous single-phase model because it requires less time, CPU, and memory usage. As expected, it is found that the heat transfer increases as the Reynolds number and particle volume fraction increases, but it is accompanied by a higher pressure drop. The obtained results have been successfully validated and compared with the experimental and numerical data available in the literature.     

Hygrothermal Fracture Analysis of Orthotropic Materials Using J k -Integral

A new computational method based on the J _k -integral is put forward for the purpose of conducting fracture analysis of orthotropic materials subjected to hygrothermal stresses. By utilizing the constitutive relations of plane orthotropic hygrothermoelasticity, an alternative expression for the J _k -integral is derived to replace the general limit definition. A numerical procedure is developed and integrated into a finite element analysis software to implement the proposed form of the J _k -integral. Temperature and specific moisture concentration fields, which are required in fracture calculations, are also computed through finite element analysis. Numerical results are generated by considering an embedded crack in a polymer matrix fibrous composite laminate, that is subjected to steady-state hygrothermal loading. Comparisons of the mixed-mode stress intensity factors computed by the J _k -integral based method to those evaluated via the displacement correlation technique demonstrate that, the proposed form of the J _k -integral is domain independent and leads to numerical results of high accuracy. Presented parametric analyses illustrate the influences of the fiber volume fraction and the crack location on the modes I and II stress intensity factors, the energy release rate, and the T-stress.     

Development of an experimentally validated semi-empirical fully-coupled performance model of a PEM electrolysis cell with a 3-D structured porous transport layer

A semi-empirical non-isothermal model incorporating coupled momentum, heat and mass transport phenomena for predicting the performance of a proton exchange membrane (PEM) water electrolysis cell operating without flow channels is presented. Model input parameters such as electro-kinetics properties and mean pore size of the porous transport layer (PTL) were determined by rotating disc electrode and capillary flow porometry, respectively. This is the first report of a semi-empirical fully coupled model which allows one to quantify and investigate the effect of the gas phase and bubble coverage on PEM cell performance up to very high current densities of about 5 A/cm². The mass transport effects are discussed in terms of the operating conditions, design parameters and the microstructure of the PTL. The results show that, the operating temperature and pressure, and the inlet water flowrate and thickness of the PTL are the critical parameters for mitigating mass transport limitation at high current densities. The model presented here can serve as a tool for further development and scale-up effort in the area of PEM water electrolysis, and provide insight during the design stage.     

Microstructure and Optical Bandgap of Cobalt Selenide Nanofilms

Semiconductors - The purpose of this research is to explore the properties of CoSe nanostructured thin films on glass substrates prepared by a chemical solution deposition method. Special attention...     

Machine learning model for mapping of music mood and human emotion based on physiological signals

Emotion is considered a physiological state that appears whenever a transformation is observed by an individual in their environment or body. While studying the literature, it has been observed that combining the electrical activity of the brain, along with other physiological signals for the accurate analysis of human emotions is yet to be explored in greater depth. On the basis of physiological signals, this work has proposed a model using machine learning approaches for the calibration of music mood and human emotion. The proposed model consists of three phases (a) prediction of the mood of the song based on audio signals, (b) prediction of the emotion of the human-based on physiological signals using EEG, GSR, ECG, Pulse Detector, and finally, (c) the mapping has been done between the music mood and the human emotion and classifies them in real-time. Extensive experimentations have been conducted on the different music mood datasets and human emotion for influential feature extraction, training, testing and performance evaluation. An effort has been made to observe and measure the human emotions up to a certain degree of accuracy and efficiency by recording a person’s bio- signals in response to music. Further, to test the applicability of the proposed work, playlists are generated based on the user’s real-time emotion determined using features generated from different physiological sensors and mood depicted by musical excerpts. This work could prove to be helpful for improving mental and physical health by scientifically analyzing the physiological signals.

     

Incorporating microgrids coupling with utilization of flexible switching to enhance self-healing ability of electric distribution systems

Electric distribution networks have to deal with issues caused by natural disasters. These problems possess unique characteristics, and their severity can make load restoration methods impotent. One solution that can help in alleviating the aftermath is the use of microgrids (MGs). Employing the cumulative capacity of the generation resources through MG coupling facilitates the self-healing capability and leads to better-coordinated energy management during the restoration period, while the switching capability of the system should also be considered. In this paper, to form and schedule dynamic MGs in distribution systems, a novel model based on mixed-integer linear programming (MILP) is proposed. This approach employs graph-related theories to formulate the optimal formation of the networked MGs and management of their proper participation in the load recovery process. In addition, the Benders decomposition technique is applied to alleviate computability issues of the optimization problem. The validity and applicability of the proposed model are evaluated by several simulation studies.