scholarly journals Using a Novel Approach to Estimate Packing Density and Related Electrical Resistance in Multiwall Carbon Nanotube Networks

Nanomaterials ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2350
Author(s):  
Usha Philipose ◽  
Yan Jiang ◽  
Gavin Farmer ◽  
Chris Howard ◽  
Michael Harcrow ◽  
...  
Keyword(s):  
Complex Network ◽  
Electrical Resistance ◽  
Mass Density ◽  
Areal Density ◽  
Multiwall Carbon Nanotube ◽  
High Concentration ◽  
Multi Wall Carbon Nanotubes ◽  
Novel Approach ◽  
Dimensional Network ◽  
Percolation Behavior

In this work, we use contrast image processing to estimate the concentration of multi-wall carbon nanotubes (MWCNT) in a given network. The fractal dimension factor (D) of the CNT network that provides an estimate of its geometrical complexity, is determined and correlated to network resistance. Six fabricated devices with different CNT concentrations exhibit D factors ranging from 1.82 to 1.98. The lower D-factor was associated with the highly complex network with a large number of CNTs in it. The less complex network, having the lower density of CNTs had the highest D factor of approximately 2, which is the characteristic value for a two-dimensional network. The electrical resistance of the thin MWCNT network was found to scale with the areal mass density of MWCNTs by a power law, with a percolation exponent of 1.42 and a percolation threshold of 0.12 μg/cm2. The sheet resistance of the films with a high concentration of MWCNTs was about six orders of magnitude lower than that of less dense networks; an effect attributed to an increase in the number of CNT–CNT contacts, enabling more efficient electron transfer. The dependence of the resistance on the areal density of CNTs in the network and on CNT network complexity was analyzed to validate a two-dimension percolation behavior.

scholarly journals CNFE-SE: a novel approach combining complex network-based feature engineering and stacked ensemble to predict the success of intrauterine insemination and ranking the features

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sima Ranjbari ◽  
Toktam Khatibi ◽  
Ahmad Vosough Dizaji ◽  
Hesamoddin Sajadi ◽  
Mehdi Totonchi ◽  
...  
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Semen Quality ◽  
Intrauterine Insemination ◽  
Machine Learning Algorithms ◽  
Semen Parameters ◽  
Feature Engineering ◽  
Operating Characteristics ◽  
Scoring Method ◽  
Novel Approach

Abstract Background Intrauterine Insemination (IUI) outcome prediction is a challenging issue which the assisted reproductive technology (ART) practitioners are dealing with. Predicting the success or failure of IUI based on the couples' features can assist the physicians to make the appropriate decision for suggesting IUI to the couples or not and/or continuing the treatment or not for them. Many previous studies have been focused on predicting the in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) outcome using machine learning algorithms. But, to the best of our knowledge, a few studies have been focused on predicting the outcome of IUI. The main aim of this study is to propose an automatic classification and feature scoring method to predict intrauterine insemination (IUI) outcome and ranking the most significant features. Methods For this purpose, a novel approach combining complex network-based feature engineering and stacked ensemble (CNFE-SE) is proposed. Three complex networks are extracted considering the patients' data similarities. The feature engineering step is performed on the complex networks. The original feature set and/or the features engineered are fed to the proposed stacked ensemble to classify and predict IUI outcome for couples per IUI treatment cycle. Our study is a retrospective study of a 5-year couples' data undergoing IUI. Data is collected from Reproductive Biomedicine Research Center, Royan Institute describing 11,255 IUI treatment cycles for 8,360 couples. Our dataset includes the couples' demographic characteristics, historical data about the patients' diseases, the clinical diagnosis, the treatment plans and the prescribed drugs during the cycles, semen quality, laboratory tests and the clinical pregnancy outcome. Results Experimental results show that the proposed method outperforms the compared methods with Area under receiver operating characteristics curve (AUC) of 0.84 ± 0.01, sensitivity of 0.79 ± 0.01, specificity of 0.91 ± 0.01, and accuracy of 0.85 ± 0.01 for the prediction of IUI outcome. Conclusions The most important predictors for predicting IUI outcome are semen parameters (sperm motility and concentration) as well as female body mass index (BMI).

A Novel Approach to Determine Minimal Tie-Sets of Complex Network

2004 ◽  
Vol 53 (1) ◽  
pp. 61-70 ◽  
Author(s):  
M. Fotuhi-Firuzabad ◽  
R. Billinton ◽  
T.S. Munian ◽  
B. Vinayagam
Keyword(s):  
Complex Network ◽  
Novel Approach

Electrodes made of multi-wall carbon nanotubes on PVDF-filters have low electrical resistance and are able to record electrocardiograms in humans

2016 ◽  
Vol 166 ◽  
pp. 10-14 ◽  
Author(s):  
Juan Bernal-Martínez ◽  
Alberto Seseña-Rubfiaro ◽  
Rafael Godínez-Fernández ◽  
Alfredo Aguilar-Elguezabal
Keyword(s):  
Carbon Nanotubes ◽  
Electrical Resistance ◽  
Multi Wall Carbon Nanotubes

A Novel Approach of Fabricating Monodispersed Spherical MoSiBTiC Particles for Additive Manufacturing

2021 ◽  
Author(s):  
Zhenxing Zhou ◽  
Suxia Guo ◽  
Weiwei Zhou ◽  
Naoyoki Nomura
Keyword(s):  
Additive Manufacturing ◽  
Melting Process ◽  
Industrial Applications ◽  
Elemental Distribution ◽  
Drying Process ◽  
High Concentration ◽  
Novel Approach ◽  
Composition Ratios ◽  
Mesh Structures ◽  
Ejection Method

Abstract It is very challenging to fabricate spherical refractory material powders for additive manufacturing (AM) because of their high melting points and complex compositions. In this study, a novel technique, freeze-dry pulsated orifice ejection method (FD-POEM), was developed to fabricate spherical MoSiBTiC particles without a melting process. Elemental nanopowders were dispersed in water to prepare a high-concentration slurry, which was subsequently extruded from an orifice by diaphragm vibration and frozen instantly in liquid nitrogen. After a freeze-drying process, spherical composite particles with arbitrary composition ratios were obtained. The FD-POEM particles had a narrow size range and uniform elemental distribution. Mesh structures were formed within the FD-POEM particles, which was attributed to the sublimation of ice crystals. Furthermore, owing to their spherical morphology, the FD-POEM particles had a low avalanche angle of 42.6°, exhibiting good flowability. Consequently, the combination of FD-POEM and additive manufacturing has great potential for developing complex refractory components used in industrial applications.

scholarly journals GABAA Receptor/STEP61 Signaling Pathway May Be Involved in Emulsified Isoflurane Anesthesia in Rats

2020 ◽  
Vol 21 (11) ◽  
pp. 4078 ◽  
Author(s):  
Xingkai Zhao ◽  
Guangjun Chang ◽  
Yan Cheng ◽  
Zhenlei Zhou
Keyword(s):  
Gamma Aminobutyric Acid ◽  
High Concentration ◽  
Messenger Ribonucleic Acid ◽  
Novel Approach ◽  
Nociceptive Stimulus ◽  
Mrna And Protein Expression ◽  
Ion Channel Proteins ◽  
Polymerase Chain ◽  
The Brain ◽  
Α1 Subunit

(1) Background: Emulsified isoflurane (EISO) is a type of intravenous anesthetic. How emulsified isoflurane works in the brain is still unclear. The aim of this study was to explore whether epigenetic mechanisms affect anesthesia and to evaluate the anesthetic effects of emulsified isoflurane in rats. (2) Methods: Rats were randomly divided into four groups (n = 8/group): The tail vein was injected with normal saline 0.1 mL·kg−1·min−1 for the control (Con) group, with intralipid for the fat emulsion (FE) group, with EISO at 60 mg·kg−1·min−1 for the high-concentration (HD) group, and 45 mg·kg−1·min−1 for the low-concentration (LD) group. The consciousness state, motor function of limbs, and response to nociceptive stimulus were observed after drug administration. (3) Results: Using real-time polymerase chain reaction (PCR) to assess the promoter methylation of ion channel proteins in the cerebral cortex of rats anesthetized by EISO, we demonstrated that the change in the promoters’ methylation of the coding genes for gamma-aminobutyric acid A receptor α1 subunit (GABAAα1), N-methyl-D-aspartate receptor subunit 1 (NMDAR1), and mu opioid receptor 1 (OPRM1) was accompanied by the change in messenger ribonucleic acid (mRNA) and protein expression by these genes. (4) Conclusion: These data suggest that the epigenetic factors’ modulation might offer a novel approach to explore the anesthetic mechanism of EISO.

Penetrating Resistance of the Laminated Composite with Stepwise Graded Foam

2010 ◽  
Vol 139-141 ◽  
pp. 72-75
Author(s):  
Feng Huan Sha
Keyword(s):  
Mass Density ◽  
Laminated Composite ◽  
Areal Density ◽  
Equal Mass ◽  
Composite Target ◽  
Perfectly Plastic ◽  
Cellular Target ◽  
Expansion Theory ◽  
The Difference ◽  
Cavity Expansion Theory

The present study focuses on the penetrating resistance of the laminated composite with stepwise graded foam target struck normally by conical-nosed projectiles. The dynamic cavity expansion theory is applied to formulate analytical model. Experimental results verify that this model on account of rigid-perfectly plastic-locking model is suitable for analyzing penetration depth of the projectile into a cellular target. The difference types of foam configurations, with identical areal density, were arranged according to the density of the respective foam. The penetrating process can be divided into 7 stages. Penetrating depth; the effect of mass density and the change of graded/layered core structures of the difference configurations are analyzed. It is found that composite target have a higher penetrating resistance than the monolithic foam material target of equal mass. The analytical results show great potential to reasonable structures for absorbing the dynamics energy and improving the overall penetrating resistance.

scholarly journals Anodic Performance of BaO-Added Ni/SDC for Solid Oxide Fuel Cell Fed With Dry CH4

2021 ◽  
Vol 9 ◽  
Author(s):  
Yoshiteru Itagaki ◽  
Syuhei Yamaguchi ◽  
Hidenori Yahiro
Keyword(s):  
Electrical Resistance ◽  
Carbon Deposition ◽  
Solid Oxide ◽  
Carbon Deposit ◽  
Anode Surface ◽  
Oxide Fuel ◽  
Electrical Resistance Measurement ◽  
High Concentration ◽  
Anode Films ◽  
Co Gas

SOFCs fed with dry H2 and CH4 fuels were examined using 20 wt% Ni/SDC and 0.2 wt% BaO-added 20 wt% Ni/SDC [Ni(BaO)/SDC] anodes. The i–v characteristics of the cells in H2 and CH4 resulted in a higher output produced by CH4 fuel compared to that produced by H2 fuel in both anodes. In both fuels, better anode characteristics were obtained for Ni(BaO)/SDC. Consequently, the anodic performance was in the order of Ni(BaO)/SDC in CH4 > Ni/SDC in CH4 > Ni(BaO)/SDC in H2 > Ni/SDC in H2. A significant carbon deposition was observed in the Ni/SDC anode in CH4, but the carbon deposition observed in Ni(BaO)/SDC was less. From the DC electrical resistance measurement of the anode films, a remarkable decrease in resistance was observed in Ni/SDC due to the carbon deposition after CH4 exposure. The resistance of Ni(BaO)/SDC was higher than that of Ni/SDC and did not change even after CH4 exposure because of the less carbon deposit. The high dispersibility of Ni particles was confirmed in both anodes and was particularly remarkable in Ni(BaO)/SDC. The highest anodic performance in Ni(BaO)/SDC was attributed to the high Ni dispersibility which might promote CH4 decomposition by producing less carbon deposit. It was speculated that the higher cell output in CH4 than that in H2 is due to the locally high concentration of H2 and/or CO gas on the anode surface by the promotion of CH4 decomposition.

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