scholarly journals Growth of Carbon Nanocoils by Porous α-Fe2O3/SnO2 Catalyst and Its Buckypaper for High Efficient Adsorption

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Yongpeng Zhao ◽  
Jianzhen Wang ◽  
Hui Huang ◽  
Tianze Cong ◽  
Shuaitao Yang ◽  
...  
Keyword(s):  
High Purity ◽  
Large Scale ◽  
Blue Dye ◽  
Adsorption Efficiency ◽  
Promising Alternative ◽  
Practical Applications ◽  
Key Points ◽  
High Efficient ◽  
Reported Data ◽  
Efficient Adsorbent

AbstractHigh-purity (99%) carbon nanocoils (CNCs) have been synthesized by using porous α-Fe2O3/SnO2 catalyst. The yield of CNCs reaches 9,098% after a 6 h growth. This value is much higher than the previously reported data, indicating that this method is promising to synthesize high-purity CNCs on a large scale. It is considered that an appropriate proportion of Fe and Sn, proper particle size distribution, and a loose-porous aggregate structure of the catalyst are the key points to the high-purity growth of CNCs. Benefiting from the high-purity preparation, a CNC Buckypaper was successfully prepared and the electrical, mechanical, and electrochemical properties were investigated comprehensively. Furthermore, as one of the practical applications, the CNC Buckypaper was successfully utilized as an efficient adsorbent for the removal of methylene blue dye from wastewater with an adsorption efficiency of 90.9%. This study provides a facile and economical route for preparing high-purity CNCs, which is suitable for large-quantity production. Furthermore, the fabrication of macroscopic CNC Buckypaper provides promising alternative of adsorbent or other practical applications.

scholarly journals Estimating the Capacity of Urban Transportation Networks with an Improved Sensitivity Based Method

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Muqing Du ◽  
Xiaowei Jiang ◽  
Lin Cheng
Keyword(s):  
Sensitivity Analysis ◽  
Large Scale ◽  
Transportation Network ◽  
Network Capacity ◽  
Combined Model ◽  
Practical Applications ◽  
Large Scale Problems ◽  
Capacity Model ◽  
High Efficient ◽  
Equilibrium Constraint

The throughput of a given transportation network is always of interest to the traffic administrative department, so as to evaluate the benefit of the transportation construction or expansion project before its implementation. The model of the transportation network capacity formulated as a mathematic programming with equilibrium constraint (MPEC) well defines this problem. For practical applications, a modified sensitivity analysis based (SAB) method is developed to estimate the solution of this bilevel model. The high-efficient origin-based (OB) algorithm is extended for the precise solution of the combined model which is integrated in the network capacity model. The sensitivity analysis approach is also modified to simplify the inversion of the Jacobian matrix in large-scale problems. The solution produced in every iteration of SAB is restrained to be feasible to guarantee the success of the heuristic search. From the numerical experiments, the accuracy of the derivatives for the linear approximation could significantly affect the converging of the SAB method. The results also show that the proposed method could obtain good suboptimal solutions from different starting points in the test examples.

scholarly journals Roadmap for advanced aqueous batteries: From design of materials to applications

2020 ◽  
Vol 6 (21) ◽  
pp. eaba4098 ◽  
Author(s):  
Dongliang Chao ◽  
Wanhai Zhou ◽  
Fangxi Xie ◽  
Chao Ye ◽  
Huan Li ◽  
...  
Keyword(s):  
Large Scale ◽  
Cost Effective ◽  
Material Design ◽  
Advanced Materials ◽  
Promising Alternative ◽  
Practical Applications ◽  
Limited Output ◽  
Key Issues ◽  
Fundamental Research ◽  
Aqueous Batteries

Safety concerns about organic media-based batteries are the key public arguments against their widespread usage. Aqueous batteries (ABs), based on water which is environmentally benign, provide a promising alternative for safe, cost-effective, and scalable energy storage, with high power density and tolerance against mishandling. Research interests and achievements in ABs have surged globally in the past 5 years. However, their large-scale application is plagued by the limited output voltage and inadequate energy density. We present the challenges in AB fundamental research, focusing on the design of advanced materials and practical applications of whole devices. Potential interactions of the challenges in different AB systems are established. A critical appraisal of recent advances in ABs is presented for addressing the key issues, with special emphasis on the connection between advanced materials and emerging electrochemistry. Last, we provide a roadmap starting with material design and ending with the commercialization of next-generation reliable ABs.

scholarly journals New Limits for Stability of Supercapacitor Electrode Material Based on Graphene Derivative

Nanomaterials ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1731
Author(s):  
Veronika Šedajová ◽  
Petr Jakubec ◽  
Aristides Bakandritsos ◽  
Václav Ranc ◽  
Michal Otyepka
Keyword(s):  
Large Scale ◽  
Electrode Materials ◽  
High Current Density ◽  
Rate Capability ◽  
Cycling Stability ◽  
Supercapacitor Electrode ◽  
Promising Alternative ◽  
Practical Applications ◽  
High Durability ◽  
Graphene Derivatives

Supercapacitors offer a promising alternative to batteries, especially due to their excellent power density and fast charging rate capability. However, the cycling stability and material synthesis reproducibility need to be significantly improved to enhance the reliability and durability of supercapacitors in practical applications. Graphene acid (GA) is a conductive graphene derivative dispersible in water that can be prepared on a large scale from fluorographene. Here, we report a synthesis protocol with high reproducibility for preparing GA. The charging/discharging rate stability and cycling stability of GA were tested in a two-electrode cell with a sulfuric acid electrolyte. The rate stability test revealed that GA could be repeatedly measured at current densities ranging from 1 to 20 A g−1 without any capacitance loss. The cycling stability experiment showed that even after 60,000 cycles, the material kept 95.3% of its specific capacitance at a high current density of 3 A g−1. The findings suggested that covalent graphene derivatives are lightweight electrode materials suitable for developing supercapacitors with extremely high durability.

Non-Blind Image Deconvolution Based on “Ringing” Removal Using Convolutional Neural Network

2020 ◽  
Vol 2020 (10) ◽  
pp. 181-1-181-7
Author(s):  
Takahiro Kudo ◽  
Takanori Fujisawa ◽  
Takuro Yamaguchi ◽  
Masaaki Ikehara
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Network Architecture ◽  
Large Scale ◽  
Blind Deconvolution ◽  
Training Dataset ◽  
Image Deconvolution ◽  
Classic Problem ◽  
Key Points ◽  
Blind Image

Image deconvolution has been an important issue recently. It has two kinds of approaches: non-blind and blind. Non-blind deconvolution is a classic problem of image deblurring, which assumes that the PSF is known and does not change universally in space. Recently, Convolutional Neural Network (CNN) has been used for non-blind deconvolution. Though CNNs can deal with complex changes for unknown images, some CNN-based conventional methods can only handle small PSFs and does not consider the use of large PSFs in the real world. In this paper we propose a non-blind deconvolution framework based on a CNN that can remove large scale ringing in a deblurred image. Our method has three key points. The first is that our network architecture is able to preserve both large and small features in the image. The second is that the training dataset is created to preserve the details. The third is that we extend the images to minimize the effects of large ringing on the image borders. In our experiments, we used three kinds of large PSFs and were able to observe high-precision results from our method both quantitatively and qualitatively.

Bullying, School Violence, and Climate in Evolving Contexts

2018 ◽  
Author(s):  
Ron Avi Astor ◽  
Rami Benbenisthty
Keyword(s):  
School Violence ◽  
School Safety ◽  
Media Coverage ◽  
Large Scale ◽  
Ecological Model ◽  
Empirical Studies ◽  
Practical Applications ◽  
Teacher Student ◽  
Area Of Interest ◽  
New Research

Since 2005, the bullying, school violence, and school safety literatures have expanded dramatically in content, disciplines, and empirical studies. However, with this massive expansion of research, there is also a surprising lack of theoretical and empirical direction to guide efforts on how to advance our basic science and practical applications of this growing scientific area of interest. Parallel to this surge in interest, cultural norms, media coverage, and policies to address school safety and bullying have evolved at a remarkably quick pace over the past 13 years. For example, behaviors and populations that just a decade ago were not included in the school violence, bullying, and school safety discourse are now accepted areas of inquiry. These include, for instance, cyberbullying, sexting, social media shaming, teacher–student and student–teacher bullying, sexual harassment and assault, homicide, and suicide. Populations in schools not previously explored, such as lesbian, gay, bisexual, transgender, and queer students and educators and military- and veteran-connected students, become the foci of new research, policies, and programs. As a result, all US states and most industrialized countries now have a complex quilt of new school safety and bullying legislation and policies. Large-scale research and intervention funding programs are often linked to these policies. This book suggests an empirically driven unifying model that brings together these previously distinct literatures. This book presents an ecological model of school violence, bullying, and safety in evolving contexts that integrates all we have learned in the 13 years, and suggests ways to move forward.

Efficient Schedule of Energy-Constrained UAV Using Crowdsourced Buses in Last-Mile Parcel Delivery

2021 ◽  
Vol 5 (1) ◽  
pp. 1-23
Author(s):  
Yan Pan ◽  
Shining Li ◽  
Qianwu Chen ◽  
Nan Zhang ◽  
Tao Cheng ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Load Capacity ◽  
Scheduling Algorithm ◽  
Cost Effective ◽  
Promising Alternative ◽  
Logistics Industry ◽  
Last Mile ◽  
Delivery Scheduling ◽  
Schedule Approach

Stimulated by the dramatical service demand in the logistics industry, logistics trucks employed in last-mile parcel delivery bring critical public concerns, such as heavy cost burden, traffic congestion and air pollution. Unmanned Aerial Vehicles (UAVs) are a promising alternative tool in last-mile delivery, which is however limited by insufficient flight range and load capacity. This paper presents an innovative energy-limited logistics UAV schedule approach using crowdsourced buses. Specifically, when one UAV delivers a parcel, it first lands on a crowdsourced social bus to parcel destination, gets recharged by the wireless recharger deployed on the bus, and then flies from the bus to the parcel destination. This novel approach not only increases the delivery range and load capacity of battery-limited UAVs, but is also much more cost-effective and environment-friendly than traditional methods. New challenges therefore emerge as the buses with spatiotemporal mobility become the bottleneck during delivery. By landing on buses, an Energy-Neutral Flight Principle and a delivery scheduling algorithm are proposed for the UAVs. Using the Energy-Neutral Flight Principle, each UAV can plan a flying path without depleting energy given buses with uncertain velocities. Besides, the delivery scheduling algorithm optimizes the delivery time and number of delivered parcels given warehouse location, logistics UAVs, parcel locations and buses. Comprehensive evaluations using a large-scale bus dataset demonstrate the superiority of the innovative logistics UAV schedule approach.

scholarly journals Prenatal Nutritional Strategies to Reduce the Risk of Preterm Birth

2021 ◽  
pp. 1-9
Author(s):  
Karen Patricia Best ◽  
Judith Gomersall ◽  
Maria Makrides
Keyword(s):  
Preterm Birth ◽  
Large Scale ◽  
Cochrane Review ◽  
Cost Effective ◽  
Omega 3 ◽  
Promising Alternative ◽  
Nutritional Interventions ◽  
Dietary Nutrients ◽  
Preterm Babies ◽  
Nutritional Strategies

Worldwide, around 15 million preterm babies are born annually, and despite intensive research, the specific mechanisms triggering preterm birth (PTB) remain unclear. Cost-effective primary prevention strategies to reduce PTB are required, and nutritional interventions offer a promising alternative. Nutrients contribute to a variety of mechanisms that are potentially important to preterm delivery, such as infection, inflammation, oxidative stress, and muscle contractility. Several observational studies have explored the association between dietary nutrients and/or dietary patterns and PTB, often with contrasting results. Randomized trial evidence on the effects of supplementation with zinc, multiple micronutrients (iron and folic acid), and vitamin D is promising; however, results are inconsistent, and many studies are not adequately powered for outcomes of PTB. Large-scale clinical trials with PTB as the primary outcome are needed before any firm conclusions can be drawn for these nutrients. The strongest evidence to date for a nutritional solution exists for omega-3 long-chain polyunsaturated fatty acids (LCPUFAs), key nutrients in fish. In 2018, a Cochrane Review (including 70 studies) showed that prenatal supplementation with omega-3 LCPUFAs reduced the risk of PTB and early PTB (EPTB) compared with no omega-3 supplementation. However, the largest trial of omega-3 supplementation in pregnancy, the Omega-3 to Reduce the Incidence of Prematurity (ORIP) trial (<i>n</i> = 5,544), showed no reduction in EPTB and a reduction in PTB only in a prespecified analysis of singleton pregnancies. Exploratory analyses from the ORIP trial found that women with low baseline total omega-3 status were at higher risk of EPTB, and that this risk was substantially reduced with omega-3 supplementation. In contrast, women with replete or high baseline total omega-3 status were already at low risk of EPTB and additional omega-3 supplementation increased the risk of EPTB compared to control. These findings suggest that determining an individual woman’s PUFA status may be the most precise way to inform recommendations to reduce her risk of PTB.

scholarly journals 2D Nanomaterials for Effective Energy Scavenging

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Md Al Mahadi Hasan ◽  
Yuanhao Wang ◽  
Chris R. Bowen ◽  
Ya Yang
Keyword(s):  
Large Scale ◽  
Waste Heat ◽  
Material Selection ◽  
Power Supplies ◽  
Small Scale ◽  
Energy Scavenging ◽  
Power Sources ◽  
Practical Applications ◽  
2D Nanomaterials ◽  
Self Powered

AbstractThe development of a nation is deeply related to its energy consumption. 2D nanomaterials have become a spotlight for energy harvesting applications from the small-scale of low-power electronics to a large-scale for industry-level applications, such as self-powered sensor devices, environmental monitoring, and large-scale power generation. Scientists from around the world are working to utilize their engrossing properties to overcome the challenges in material selection and fabrication technologies for compact energy scavenging devices to replace batteries and traditional power sources. In this review, the variety of techniques for scavenging energies from sustainable sources such as solar, air, waste heat, and surrounding mechanical forces are discussed that exploit the fascinating properties of 2D nanomaterials. In addition, practical applications of these fabricated power generating devices and their performance as an alternative to conventional power supplies are discussed with the future pertinence to solve the energy problems in various fields and applications.

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