scholarly journals Correlation of Defect-Related Optoelectronic Properties inZn5(OH)6(CO3)2/ZnO Nanostructures with Their Quasi-Fractal Dimensionality

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
J. Antonio Paramo ◽  
Yuri M. Strzhemechny ◽  
Tamio Endo ◽  
Zorica Crnjak Orel
Keyword(s):  
Crystal Morphology ◽  
Relative Concentration ◽  
Fractal Dimensionality ◽  
Optoelectronic Properties ◽  
Growth Time ◽  
Structure Property ◽  
Phase Crystal ◽  
Potential Applications ◽  
Subsurface Layers ◽  
The Relationship

Hydrozincite (Zn5(OH)6(CO3)2) is, among others, a popular precursor used to synthesize nanoscale ZnO with complex morphologies. For many existing and potential applications utilizing nanostructures, performance is determined by the surface and subsurface properties. Current understanding of the relationship between the morphology and the defect properties of nanocrystalline ZnO and hydrozincite systems is still incomplete. Specifically, for the latter nanomaterial the structure-property correlations are largely unreported in the literature despite the extensive use of hydrozincite in the synthesis applications. In our work, we addressed this issue by studying precipitated nanostructures of Zn5(OH)6(CO3)2with varying quasi-fractal dimensionalities containing relatively small amounts of a ZnO phase. Crystal morphology of the samples was accurately controlled by the growth time. We observed a strong correlation between the morphology of the samples and their optoelectronic properties. Our results indicate that a substantial increase of the free surface in the nanocrystal samples generates higher relative concentration of defects, consistent with the model of defect-rich surface and subsurface layers.

Structure-properties relationship for energy storage redox polymers: a review

2020 ◽  
Vol 40 (5) ◽  
pp. 373-393 ◽  
Author(s):  
Narendra Singh Chundawat ◽  
Nishigandh Pande ◽  
Ghasem Sargazi ◽  
Mazaher Gholipourmalekabadi ◽  
Narendra Pal Singh Chauhan
Keyword(s):  
Energy Storage ◽  
Cost Efficiency ◽  
Energy Storage Materials ◽  
High Scale ◽  
Chemical Structures ◽  
Redox Active ◽  
Potential Applications ◽  
Intelligent Clothing ◽  
The Relationship ◽  
Structure Properties

AbstractRedox-active polymers among the energy storage materials (ESMs) are very attractive due to their exceptional advantages such as high stability and processability as well as their simple manufacturing. Their applications are found to useful in electric vehicle, ultraright computers, intelligent electric gadgets, mobile sensor systems, and portable intelligent clothing. They are found to be more efficient and advantageous in terms of superior processing capacity, quick loading unloading, stronger security, lengthy life cycle, versatility, adjustment to various scales, excellent fabrication process capabilities, light weight, flexible, most significantly cost efficiency, and non-toxicity in order to satisfy the requirement for the usage of these potential applications. The redox-active polymers are produced through organic synthesis, which allows the design and free modification of chemical constructions, which allow for the structure of organic compounds. The redox-active polymers can be finely tuned for the desired ESMs applications with their chemical structures and electrochemical properties. The redox-active polymers synthesis also offers the benefits of high-scale, relatively low reaction, and a low demand for energy. In this review we discussed the relationship between structural properties of different polymers for solar energy and their energy storage applications.

scholarly journals Changes in Optical Properties upon Dye–Clay Interaction: Experimental Evaluation and Applications

Nanomaterials ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 197
Author(s):  
Giorgia Giovannini ◽  
René M. Rossi ◽  
Luciano F. Boesel
Keyword(s):  
Optical Properties ◽  
Hybrid Materials ◽  
High Performance ◽  
Fluorescent Properties ◽  
Chemical Mechanisms ◽  
Strong Electrostatic Interaction ◽  
Potential Applications ◽  
Photochemical Properties ◽  
Physical And Chemical ◽  
The Relationship

The development of hybrid materials with unique optical properties has been a challenge for the creation of high-performance composites. The improved photophysical and photochemical properties observed when fluorophores interact with clay minerals, as well as the accessibility and easy handling of such natural materials, make these nanocomposites attractive for designing novel optical hybrid materials. Here, we present a method of promoting this interaction by conjugating dyes with chitosan. The fluorescent properties of conjugated dye–montmorillonite (MMT) hybrids were similar to those of free dye–MMT hybrids. Moreover, we analyzed the relationship between the changes in optical properties of the dye interacting with clay and its structure and defined the physical and chemical mechanisms that take place upon dye–MMT interactions leading to the optical changes. Conjugation to chitosan additionally ensures stable adsorption on clay nanoplatelets due to the strong electrostatic interaction between chitosan and clay. This work thus provides a method to facilitate the design of solid-state hybrid nanomaterials relevant for potential applications in bioimaging, sensing and optical purposes.

scholarly journals Growth Parameters for Films of Hydrothermally Synthesized One-Dimensional Nanocrystals of Zinc Oxide

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Mohammad A. Mahmood ◽  
Sadaqat Jan ◽  
Ibrar A. Shah ◽  
Imran Khan
Keyword(s):  
Zinc Oxide ◽  
Growth Parameters ◽  
Precursor Solution ◽  
Synthesis Temperature ◽  
Growth Time ◽  
Material Research ◽  
Hydrothermal Route ◽  
Seeding Layer ◽  
Potential Applications

Zinc oxide has been the focus of material research due to its potential applications in a variety of novel fields. The material exhibits anisotropic growth in the form of single crystal rods/wires of length in microns and thickness in several tens of nanometers through a facile and low temperature hydrothermal route wherein size, morphology, orientation, and growth rate are strongly dependent on a number of synthesis parameters. In this review article we intend to present/discuss the effects of important growth parameters of zinc oxide that have been reported in the literature. These parameters include concentration of the precursor solution, growth time, role of hexamine, synthesis temperature, pH of the precursor, and seeding layer deposited on a substrate.

scholarly journals Modelling semi-continuous data using mixture regression models with an application to cattle production yields

2011 ◽  
Vol 150 (1) ◽  
pp. 109-121 ◽  
Author(s):  
E. J. BELASCO ◽  
S. K. GHOSH
Keyword(s):  
Regression Models ◽  
Continuous Variable ◽  
Continuous Variables ◽  
Multivariate Models ◽  
Mixture Regression ◽  
Potential Applications ◽  
Mixture Regression Models ◽  
Mixture Regression Model ◽  
The Relationship ◽  
Positive Half

SUMMARYThe present paper develops a mixture regression model that allows for distributional flexibility in modelling the likelihood of a semi-continuous outcome that takes on zero value with positive probability while continuous on the positive half of the real line. A multivariate extension is also developed that builds on past multivariate models by systematically capturing the relationship between continuous and semi-continuous variables, while allowing for the semi-continuous variable to be characterized by a mixture model. The flexibility associated with this model provides potential applications in many production system studies. The empirical model is shown to provide a more accurate measure of mortality rates in cattle feedlots, both independently and within a system including other performance and health factors.

Design of Multi-Resonant Cavities Based on Metal-Coated Dielectric Nanocylinders

2018 ◽  
Vol 73 (6) ◽  
pp. 559-563 ◽  
Author(s):  
Junyuan Dong ◽  
Guanxia Yu ◽  
Jingjing Fu ◽  
Min Luo ◽  
Wenwen Du
Keyword(s):  
Cross Section ◽  
Optical Sensors ◽  
Incident Light ◽  
Resonant Cavities ◽  
Storage Devices ◽  
Symmetrical Distribution ◽  
Integrated Devices ◽  
Potential Applications ◽  
The Relationship ◽  
Transmission And Reflection

AbstractIn this paper, the light scattering properties for multiple silver-coated dielectric nanocylinders with the symmetrical distribution were investigated. Based on the transfer matrix method, we derive the general transmission and reflection coefficient matrices for multiple dielectric nanocylinders. When the incident light frequencies are less than the plasma frequencies, the surface plasmons (SPs) appear in the interface between the silver and dielectrics. Numerical simulations show that there are three peaks of absorption cross-section (ACS) in the relationship between the ACS and the frequencies of the incident light, when the distance between the silver-coated dielectric nanocylinders is chosen properly. These SPs resonance peaks are characterised as resonances intrinsic to the cylindrically periodic system corresponding to different inner cavity structures. These multi-resonant cavities may have potential applications in integrated devices, optical sensors and optical storage devices.

scholarly journals PSXI-24 Rumen temperature, fermentation and microbial signatures are poorly associated with steer feed-efficiency profiles

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 382-382
Author(s):  
Obioha N Durunna ◽  
Daalkhaijav Damiran ◽  
John R Campbell ◽  
Jeffery A Carroll ◽  
Bart Lardner
Keyword(s):  
Feed Intake ◽  
Feed Efficiency ◽  
Screening Tool ◽  
Rumen Fluid ◽  
Microbial Populations ◽  
Environmental Footprint ◽  
Rumen Temperature ◽  
Potential Applications ◽  
Cost Implications ◽  
The Relationship

Abstract Breeding feed-efficient cattle can reduce the environmental footprint of beef operations but assessing all replacement candidates for feed-intake is not practical due to cost implications. The main objectives of this study were to evaluate if rumen temperature (RumT), measured with wireless rumen Thermobolus® can distinguish steers with different feed-efficiency profiles and whether steers with divergent efficiency profiles have different nutrient fermentation signatures. The study also validated the relationship between rectal temperature (RecT) and RumT measured with automatic thermistors. Residual feed intake (RFI) profiles of 160 steers were measured over two years. All steers were assessed for RFI profiles using high and moderate forage diets, respectively, over two successive periods each year. Each steer was fitted with a rumen Thermobolus® throughout each ~80-d test period while half of the steers wore an automatic temperature-logger rectal device for ~30d. The devices recorded the RumT and RecT every 5 minutes, respectively. Rumen fluid samples were collected from high-RFI (n = 5) and low-RFI (n = 5) steers to assess if differences in rumen fermentation and microbial profiles exist. Circadian-adjusted RumT and RecT for each steer were used for analysis. The within-period correlations between RumT and RecT ranged between 49 and 77%. There was a trend (P = 0.08) that differences exist for rhythm-adjusted temperatures among different RFI profiles with low-RFI steers (39.72±0.01oC) having lower average RumT than those in high (39.75±0.01oC) or medium (39.74±0.01oC) classes. The correlation between the two test-periods for rhythm-adjusted RumT was 65% while the correlation between RFI from both periods was 47%. There was no difference (P > 0.30) between high- and low-RFI animals for the total or individual volatile fatty acid fractions or microbial populations. The narrow temperature variation among RFI classes limits its use as screening tool but the higher across-period correlation encourages the need for further studies into alternative potential applications.

scholarly journals An introduction to learning algorithms and potential applications in geomorphometry and earth surface dynamics

2016 ◽  
Author(s):  
Andrew Valentine ◽  
Lara Kalnins
Keyword(s):  
Learning Algorithm ◽  
Learning Algorithms ◽  
Earth Surface ◽  
Surface Dynamics ◽  
Wide Range ◽  
Computational Implementation ◽  
Potential Applications ◽  
Abstract Learning ◽  
The Relationship

Abstract. "Learning algorithms" are a class of computational tool designed to infer information from a dataset, and then apply that information predictively. They are particularly well-suited to complex pattern recognition, or to situations where a mathematical relationship needs to be modelled, but where the underlying processes are not well-understood, are too expensive to compute, or where signals are over-printed by other effects. If a representative set of examples of the relationship can be constructed, a learning algorithm can assimilate its behaviour, and may then serve as an efficient, approximate computational implementation thereof. A wide range of applications in geomorphometry and earth surface dynamics may be envisaged, ranging from classification of landforms through to prediction of erosion characteristics given input forces. Here, we provide a practical overview of the various approaches that lie within this general framework, review existing uses in geomorphology and related applications, and discuss some of the factors that determine whether a learning algorithm approach is suited to any given problem.

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