Universal Scaling and Real-Time Monitoring of the Production of Liquid Exfoliated Graphene

2020 ◽  
Author(s):  
Jason Stafford ◽  
Nwachukwu Uzo ◽  
Usmaan Farooq ◽  
Silvia Favero ◽  
Si Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Maximum Yield ◽  
Local Stress ◽  
Two Dimensional ◽  
Exfoliated Graphene ◽  
Precursor Material ◽  
Solvent Design ◽  
Wide Variability ◽  
Scalable Monitoring

<div>Shear-assisted liquid exfoliation is a primary candidate for producing defect-free two-dimensional materials from labs to industry. Diverse hydrodynamic conditions exist across production methods, and combined with low-throughput, high-cost characterization techniques, strongly contribute to the wide variability in performance and material quality. Through investigations on strikingly different flow regimes, and using graphene as the prototypical two-dimensional material, we find that scaling of production depends on local stress fi eld distributions and precursor residence time. We report a novel indirect diffuse reflectance method to measure graphene concentration in real-time, using low-cost optoelectronics and without the need to remove the precursor material from the heterogeneous dispersions. We show that this high-throughput, <i>in situ</i> approach has broad applicability by controlling the number of atomic layers on the fly, rapidly optimising green solvent design for maximum yield, and viewing live production rates. Combining insights on the hydrodynamics of exfoliation with this scalable monitoring technique, targeted process intensi fication, quality control, batch traceability and individually customisable materials on-demand are possible.</div>

Universal Scaling and Real-Time Monitoring of the Production of Liquid Exfoliated Graphene

2020 ◽  
Author(s):  
Jason Stafford ◽  
Nwachukwu Uzo ◽  
Usmaan Farooq ◽  
Silvia Favero ◽  
Si Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Maximum Yield ◽  
Local Stress ◽  
Two Dimensional ◽  
Exfoliated Graphene ◽  
Precursor Material ◽  
Solvent Design ◽  
Wide Variability ◽  
Scalable Monitoring

<div>Shear-assisted liquid exfoliation is a primary candidate for producing defect-free two-dimensional materials from labs to industry. Diverse hydrodynamic conditions exist across production methods, and combined with low-throughput, high-cost characterization techniques, strongly contribute to the wide variability in performance and material quality. Through investigations on strikingly different flow regimes, and using graphene as the prototypical two-dimensional material, we find that scaling of production depends on local stress fi eld distributions and precursor residence time. We report a novel indirect diffuse reflectance method to measure graphene concentration in real-time, using low-cost optoelectronics and without the need to remove the precursor material from the heterogeneous dispersions. We show that this high-throughput, <i>in situ</i> approach has broad applicability by controlling the number of atomic layers on the fly, rapidly optimising green solvent design for maximum yield, and viewing live production rates. Combining insights on the hydrodynamics of exfoliation with this scalable monitoring technique, targeted process intensi fication, quality control, batch traceability and individually customisable materials on-demand are possible.</div>

TWO-DIMENSIONAL STATIC AND DYNAMIC DISPLAY SYSTEM OF BOWEL SOUND MAGNITUDE MAP FOR EVALUATION OF INTESTINAL MOTILITY

2009 ◽  
Vol 21 (05) ◽  
pp. 333-342 ◽  
Author(s):  
Chia-Hung Chien ◽  
Hsiang-Ting Huang ◽  
Cheng-Yi Wang ◽  
Fok-Ching Chong
Keyword(s):  
Real Time ◽  
Intestinal Motility ◽  
Low Cost ◽  
Activity Level ◽  
Bowel Sound ◽  
Two Dimensional ◽  
Dynamic Display ◽  
Before And After ◽  
Abdominal Surface ◽  
A New Technique

The aim of this work is to develop a new technique of two-dimensional (2D) bowel sound magnitude map (BSMM) with multichannel electronic stethoscopes to evaluate the location, intensity, and track of intestinal motility from the abdominal surface in real time. The static BSMM, obtained from the interpolation of captured one-dimensional (1D) signals, demonstrated an activity level of intestinal motility with different colors. It enabled spatial visualization of the sound origin to locate the peristaltic position of bowels. The dynamic BSMM, displayed in either time series or continuous mode, clearly showed the tracking pattern of intestinal motility on the whole abdomen. Our results verified the validation of this system with a computer simulation and the specific detection of bowel sounds (BSs). The detection of physiologic intestinal motility, including that before and after meal or before defecation, is also available with BSMMs. A simple, noninvasive, low-cost, visualizable, and real-time device has been successfully developed in this work.

Ti3C2-MXene/Bismuth Ferrite Nanohybrids for Efficient Degradation of Organic Dye and Colorless Pollutant

2019 ◽  
Author(s):  
Ayesha Tariq ◽  
M. Abdullah Iqbal ◽  
S. Irfan Ali ◽  
Muhammad Z. Iqbal ◽  
Deji Akinwande ◽  
...  
Keyword(s):  
Surface Area ◽  
Low Cost ◽  
Bismuth Ferrite ◽  
Organic Dye ◽  
Two Dimensional ◽  
Electron Hole ◽  
Photocatalytic Application ◽  
Electron Hole Pair ◽  
Pair Generation ◽  
Photocatalytic Applications

<p>Nanohybrids, made up of Bismuth ferrites/Carbon allotropes, are extensively used in photocatalytic applications nowadays. Our work proposes a nanohybrid system composed of Bismuth ferrite nanoparticles with two-dimensional (2D) MXene sheets namely, the BiFeO<sub>3</sub> (BFO)/Ti<sub>3</sub>C<sub>2</sub> (MXene) nanohybrid for enhanced photocatalytic activity. We have fabricated the BFO/MXene nanohybrid using simple and low cost double solvent solvothermal method. The SEM and TEM images show that the BFO nanoparticles were attached onto the MXene surface and in the inter-layers of two-dimensional (2D) MXene sheets. The photocatalytic application is tested for the visible light irradiation which showed the highest efficiency among all pure-BFO based photocatalysts, i.e. 100% degradation in 42 min for organic dye (Congo Red) and colorless aqueous pollutant (acetophenone) in 150 min, respectively. The present BFO-based hybrid system exhibited the large surface area of 147 m<sup>2</sup>g<sup>-1</sup>measured via Brunauer-Emmett-Teller (BET) sorption-desorption technique, and is found to be largest among BFO and its derivatives. Also, the photoluminescence (PL) spectra indicate large electron-hole pair generation. Fast and efficient degradation of organic molecules is supported by both factors; larger surface area and lower electron-hole recombination rate. The BFO/MXene nanohybrid presented here is a highly efficient photocatalyst compared to other nanostructures based on pure BiFeO<sub>3</sub> which makes it a promising candidate for many future applications.</p>

LOW COST REAL TIME ROCKET TELEMETRY SYSTEM DESIGN

2019 ◽  
Author(s):  
Gabriel de Almeida Souza ◽  
Larissa Barbosa ◽  
Glênio Ramalho ◽  
Alexandre Zuquete Guarato
Keyword(s):  
System Design ◽  
Real Time ◽  
Low Cost ◽  
Telemetry System

Low-Cost High-Speed Techniques for Real-Time Simulation of Power Electronic Systems

2007 ◽  
Author(s):  
R. E. Crosbie ◽  
J. J. Zenor ◽  
R. Bednar ◽  
D. Word ◽  
N. G. Hingorani
Keyword(s):  
Real Time ◽  
High Speed ◽  
Low Cost ◽  
Electronic Systems ◽  
Power Electronic ◽  
Real Time Simulation ◽  
Time Simulation

CALCULATION OF THE DEPENDENCE OF THE DISTANCE TO THE LOCATED OBJECT FROM THE CORNER POSITION OF THE VEHICLE LINE

2018 ◽  
pp. 14-18
Author(s):  
V. V. Artyushenko ◽  
A. V. Nikulin
Keyword(s):  
Real Time ◽  
Statistical Physics ◽  
Angular Position ◽  
Three Dimensional ◽  
Line Of Sight ◽  
Two Dimensional ◽  
Radar Station ◽  
Flight Mode ◽  
Vector Algebra ◽  
Analytical Expressions

To simulate echoes from the earth’s surface in the low flight mode, it is necessary to reproduce reliably the delayed reflected sounding signal of the radar in real time. For this, it is necessary to be able to calculate accurately and quickly the dependence of the distance to the object being measured from the angular position of the line of sight of the radar station. Obviously, the simplest expressions for calculating the range can be obtained for a segment or a plane. In the text of the article, analytical expressions for the calculation of range for two-dimensional and three-dimensional cases are obtained. Methods of statistical physics, vector algebra, and the theory of the radar of extended objects were used. Since the calculation of the dependence of the range of the object to the target from the angular position of the line of sight is carried out on the analytical expressions found in the paper, the result obtained is accurate, and due to the relative simplicity of the expressions obtained, the calculation does not require much time.

scholarly journals Application of Deep Learning in Integrated Pest Management: A Real-Time System for Detection and Diagnosis of Oilseed Rape Pests

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yong He ◽  
Hong Zeng ◽  
Yangyang Fan ◽  
Shuaisheng Ji ◽  
Jianjian Wu
Keyword(s):  
Deep Learning ◽  
Integrated Pest Management ◽  
Pest Management ◽  
Real Time ◽  
Oilseed Rape ◽  
Data Augmentation ◽  
Low Cost ◽  
Response Speed ◽  
Original Model ◽  
Real Time System

In this paper, we proposed an approach to detect oilseed rape pests based on deep learning, which improves the mean average precision (mAP) to 77.14%; the result increased by 9.7% with the original model. We adopt this model to mobile platform to let every farmer able to use this program, which will diagnose pests in real time and provide suggestions on pest controlling. We designed an oilseed rape pest imaging database with 12 typical oilseed rape pests and compared the performance of five models, SSD w/Inception is chosen as the optimal model. Moreover, for the purpose of the high mAP, we have used data augmentation (DA) and added a dropout layer. The experiments are performed on the Android application we developed, and the result shows that our approach surpasses the original model obviously and is helpful for integrated pest management. This application has improved environmental adaptability, response speed, and accuracy by contrast with the past works and has the advantage of low cost and simple operation, which are suitable for the pest monitoring mission of drones and Internet of Things (IoT).

scholarly journals Low-Cost Embedded System Using Convolutional Neural Networks-Based Spatiotemporal Feature Map for Real-Time Human Action Recognition

2021 ◽  
Vol 11 (11) ◽  
pp. 4940
Author(s):  
Jinsoo Kim ◽  
Jeongho Cho
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Action Recognition ◽  
Processing Speed ◽  
Recognition Accuracy ◽  
Low Cost ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Data ◽  
Feature Maps

The field of research related to video data has difficulty in extracting not only spatial but also temporal features and human action recognition (HAR) is a representative field of research that applies convolutional neural network (CNN) to video data. The performance for action recognition has improved, but owing to the complexity of the model, some still limitations to operation in real-time persist. Therefore, a lightweight CNN-based single-stream HAR model that can operate in real-time is proposed. The proposed model extracts spatial feature maps by applying CNN to the images that develop the video and uses the frame change rate of sequential images as time information. Spatial feature maps are weighted-averaged by frame change, transformed into spatiotemporal features, and input into multilayer perceptrons, which have a relatively lower complexity than other HAR models; thus, our method has high utility in a single embedded system connected to CCTV. The results of evaluating action recognition accuracy and data processing speed through challenging action recognition benchmark UCF-101 showed higher action recognition accuracy than the HAR model using long short-term memory with a small amount of video frames and confirmed the real-time operational possibility through fast data processing speed. In addition, the performance of the proposed weighted mean-based HAR model was verified by testing it in Jetson NANO to confirm the possibility of using it in low-cost GPU-based embedded systems.

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