scholarly journals Ultrafast Laser Applications in Low Dimensional Systems

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Prem B. Bisht
Keyword(s):  
Simple Technique ◽  
Research Work ◽  
Ultrafast Laser ◽  
Laser Applications ◽  
Graphene Derivatives ◽  
Laser Facility ◽  
Carbon Nano Tubes ◽  
Optical Phenomena ◽  
Nonlinear Optical Phenomena ◽  
Low Dimensional

Among several laser applications, nonlinear optical phenomena have emerged as a new area of research. Nonlinear optics of low dimensional systems such as quantum dots (0D), carbon nano tubes (1D) and graphene derivatives (2D) has been under intense scrutiny. In the present manuscript we present some of our research work in these topics carried out with a simple technique of z-scan. This technique is useful for the studies of novel materials and can be replicated in a laboratory that has a pulsed (ns or shorter duration) laser facility.

scholarly journals Ultrafast Laser Applications in Low Dimensional Systems

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Prem B. Bisht
Keyword(s):  
Simple Technique ◽  
Research Work ◽  
Ultrafast Laser ◽  
Laser Applications ◽  
Graphene Derivatives ◽  
Laser Facility ◽  
Carbon Nano Tubes ◽  
Optical Phenomena ◽  
Nonlinear Optical Phenomena ◽  
Low Dimensional

Among several laser applications, nonlinear optical phenomena have emerged as a new area of research. Nonlinear optics of low dimensional systems such as quantum dots (0D), carbon nano tubes (1D) and graphene derivatives (2D) has been under intense scrutiny. In the present manuscript we present some of our research work in these topics carried out with a simple technique of z-scan. This technique is useful for the studies of novel materials and can be replicated in a laboratory that has a pulsed (ns or shorter duration) laser facility.

scholarly journals MXene Core-Shell Nanosheets: Facile Synthesis, Optical Properties, and Versatile Photonics Applications

Nanomaterials ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1995
Author(s):  
Yunjia Wang ◽  
Shunxiang Liu ◽  
Feng Zhu ◽  
Yiyu Gan ◽  
Qiao Wen
Keyword(s):  
Gold Nanoparticles ◽  
Research Work ◽  
Mode Locking ◽  
Single Frequency ◽  
Core Shell ◽  
Complex Structures ◽  
Facile Synthesis ◽  
Laser Applications ◽  
Saturable Absorbers ◽  
Frequency Laser

In recent years, the transition metal carbonitrides(MXenes) have been widely applied to photoelectric field, and better performance of these applications was achieved via MXene complex structures. In our work, we proposed a MXene core-shell nanosheet composed of a Ti2C (MXene) phase and gold nanoparticles, and applied it to mode-locked and single-frequency fiber laser applications. The optoelectronic results suggested that the performances of these two applications were both improved when MXene core-shell nanosheets were applied. As a result, we obtained a mode-locking operation with 670 fs pulses, and the threshold pump power reached to as low as 20 mW. Besides, a single-frequency laser with the narrowest linewidth of ~1 kHz is also demonstrated experimentally. Our research work proved that MXene core-shell nanosheets could be used as saturable absorbers (SAs) to promote versatile photonic applications.

Nonlinear optical phenomena in bulk dielectric media with few optical cycle mid-IR pulses

2014 ◽  
Author(s):  
A. Dubietis ◽  
N. Garejev ◽  
V. Jukna ◽  
G. Tamošauskas ◽  
I. Gražulevičiūtė ◽  
...  
Keyword(s):  
Nonlinear Optical ◽  
Dielectric Media ◽  
Optical Cycle ◽  
Optical Phenomena ◽  
Nonlinear Optical Phenomena

Nonlinear optical phenomena in the Al2O3-P2O5, Er- and Yb-doped silica glasses

1999 ◽  
Vol 2 (1) ◽  
pp. 43-47 ◽  
Author(s):  
M Makowska-Janusik ◽  
I V Kityk ◽  
J Berdowski ◽  
J Matejec ◽  
I Kasik ◽  
...  
Keyword(s):  
Nonlinear Optical ◽  
Silica Glasses ◽  
Optical Phenomena ◽  
Nonlinear Optical Phenomena

Large Enhancement of Nonlinear Optical Phenomena by Plasmonic Nanocavity Gratings

Nano Letters ◽  
2010 ◽  
Vol 10 (12) ◽  
pp. 4880-4883 ◽  
Author(s):  
Patrice Genevet ◽  
Jean-Philippe Tetienne ◽  
Evangelos Gatzogiannis ◽  
Romain Blanchard ◽  
Mikhail A. Kats ◽  
...  
Keyword(s):  
Nonlinear Optical ◽  
Large Enhancement ◽  
Optical Phenomena ◽  
Nonlinear Optical Phenomena

scholarly journals A Novel Density-based Technique for Outlier Detection of High Dimensional Data Utilizing Full Feature Space

2021 ◽  
Vol 50 (1) ◽  
pp. 138-152
Author(s):  
Mujeeb Ur Rehman ◽  
Dost Muhammad Khan
Keyword(s):  
Data Mining ◽  
Outlier Detection ◽  
High Dimensional Data ◽  
Research Work ◽  
Feature Space ◽  
High Dimensional ◽  
Data Set ◽  
Data Points ◽  
Low Dimensional ◽  
Intrinsic Feature

Recently, anomaly detection has acquired a realistic response from data mining scientists as a graph of its reputation has increased smoothly in various practical domains like product marketing, fraud detection, medical diagnosis, fault detection and so many other fields. High dimensional data subjected to outlier detection poses exceptional challenges for data mining experts and it is because of natural problems of the curse of dimensionality and resemblance of distant and adjoining points. Traditional algorithms and techniques were experimented on full feature space regarding outlier detection. Customary methodologies concentrate largely on low dimensional data and hence show ineffectiveness while discovering anomalies in a data set comprised of a high number of dimensions. It becomes a very difficult and tiresome job to dig out anomalies present in high dimensional data set when all subsets of projections need to be explored. All data points in high dimensional data behave like similar observations because of its intrinsic feature i.e., the distance between observations approaches to zero as the number of dimensions extends towards infinity. This research work proposes a novel technique that explores deviation among all data points and embeds its findings inside well established density-based techniques. This is a state of art technique as it gives a new breadth of research towards resolving inherent problems of high dimensional data where outliers reside within clusters having different densities. A high dimensional dataset from UCI Machine Learning Repository is chosen to test the proposed technique and then its results are compared with that of density-based techniques to evaluate its efficiency.

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