scholarly journals Surface/Interface Engineering for Constructing Advanced Nanostructured Photodetectors with Improved Performance: A Brief Review

Nanomaterials ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 362 ◽  
Author(s):  
Meng Ding ◽  
Zhen Guo ◽  
Xuehang Chen ◽  
Xiaoran Ma ◽  
Lianqun Zhou
Keyword(s):  
Signal To Noise Ratio ◽  
Response Speed ◽  
Detection Sensitivity ◽  
Interface Engineering ◽  
Spectral Selectivity ◽  
Photoelectric Performance ◽  
Photo Detectors ◽  
Improved Performance ◽  
Low Dimensional ◽  
Near Future

Semiconductor-based photodetectors (PDs) convert light signals into electrical signals via a photon–matter interaction process, which involves surface/interface carrier generation, separation, and transportation of the photo-induced charge media in the active media, as well as the extraction of these charge carriers to external circuits of the constructed nanostructured photodetector devices. Because of the specific electronic and optoelectronic properties in the low-dimensional devices built with nanomaterial, surface/interface engineering is broadly studied with widespread research on constructing advanced devices with excellent performance. However, there still exist some challenges for the researchers to explore corresponding mechanisms in depth, and the detection sensitivity, response speed, spectral selectivity, signal-to-noise ratio, and stability are much more important factors to judge the performance of PDs. Hence, researchers have proposed several strategies, including modification of light absorption, design of novel PD heterostructures, construction of specific geometries, and adoption of specific electrode configurations to modulate the charge-carrier behaviors and improve the photoelectric performance of related PDs. Here, in this brief review, we would like to introduce and summarize the latest research on enhancing the photoelectric performance of PDs based on the designed structures by considering their surface/interface engineering and how to obtain advanced nanostructured photo-detectors with improved performance, which could be applied to design and fabricate novel low-dimensional PDs with ideal properties in the near future.

Interface Engineering of Perovskite Solar Cells with Air Plasma Treatment for Improved Performance

ChemPhysChem ◽  
2017 ◽  
Vol 18 (20) ◽  
pp. 2939-2946 ◽  
Author(s):  
Xiao Ma ◽  
Peng Tang ◽  
Dong Liu ◽  
Jingquan Zhang ◽  
Lianghuan Feng ◽  
...  
Keyword(s):  
Solar Cells ◽  
Plasma Treatment ◽  
Perovskite Solar Cells ◽  
Air Plasma ◽  
Interface Engineering ◽  
Improved Performance ◽  
Air Plasma Treatment

scholarly journals Data Augmentation Through Monte Carlo Arithmetic Leads to More Generalizable Classification in Connectomics

2020 ◽  
Author(s):  
Gregory Kiar ◽  
Yohan Chatelain ◽  
Ali Salari ◽  
Alan C. Evans ◽  
Tristan Glatard
Keyword(s):  
Monte Carlo ◽  
Data Augmentation ◽  
Learning Models ◽  
Reduction Techniques ◽  
Numerical Noise ◽  
Numerical Instabilities ◽  
Dimensionality Reduction Techniques ◽  
Improved Performance ◽  
Low Dimensional ◽  
Machine Learning Models

AbstractMachine learning models are commonly applied to human brain imaging datasets in an effort to associate function or structure with behaviour, health, or other individual phenotypes. Such models often rely on low-dimensional maps generated by complex processing pipelines. However, the numerical instabilities inherent to pipelines limit the fidelity of these maps and introduce computational bias. Monte Carlo Arithmetic, a technique for introducing controlled amounts of numerical noise, was used to perturb a structural connectome estimation pipeline, ultimately producing a range of plausible networks for each sample. The variability in the perturbed networks was captured in an augmented dataset, which was then used for an age classification task. We found that resampling brain networks across a series of such numerically perturbed outcomes led to improved performance in all tested classifiers, preprocessing strategies, and dimensionality reduction techniques. Importantly, we find that this benefit does not hinge on a large number of perturbations, suggesting that even minimally perturbing a dataset adds meaningful variance which can be captured in the subsequently designed models.

scholarly journals An Order-Independent Algorithm for Learning Chain Graphs

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Mohammad Ali Javidian ◽  
Marco Valtorta ◽  
Pooyan Jamshidi
Keyword(s):  
Directed Acyclic Graphs ◽  
High Dimensional ◽  
P Values ◽  
Order Dependence ◽  
Error Measures ◽  
Acyclic Graphs ◽  
Simulation Results ◽  
Improved Performance ◽  
Low Dimensional ◽  
Chain Graphs

LWF chain graphs combine directed acyclic graphs and undirected graphs. We propose a PC-like algorithm, called PC4LWF, that finds the structure of chain graphs under the faithfulness assumption to resolve the problem of scalability of the proposed algorithm by Studeny (1997). We prove that PC4LWF is order dependent, in the sense that the output can depend on the order in which the variables are given. This order dependence can be very pronounced in high-dimensional settings. We propose two modifications of the PC4LWF algorithm that remove part or all of this order dependence. Simulation results with different sample sizes, network sizes, and p-values demonstrate the competitive performance of the PC4LWF algorithms in comparison with the LCD algorithm proposed by Ma et al. (2008) in low-dimensional settings and improved performance (with regard to error measures) in high-dimensional settings.

scholarly journals The High-Resolution Digital-Beamforming Airborne SAR System DBFSAR

2020 ◽  
Vol 12 (11) ◽  
pp. 1710 ◽  
Author(s):  
Andreas Reigber ◽  
Eric Schreiber ◽  
Kurt Trappschuh ◽  
Sebastian Pasch ◽  
Gerhard Müller ◽  
...  
Keyword(s):  
High Resolution ◽  
Signal To Noise Ratio ◽  
Digital Beamforming ◽  
Remote Sensing Technique ◽  
High Resolution Imagery ◽  
X Band ◽  
The Status ◽  
Airborne Sar ◽  
German Aerospace ◽  
Near Future

Synthetic Aperture Radar (SAR) is an established remote sensing technique that can robustly provide high-resolution imagery of the Earth’s surface. However, current space-borne SAR systems are limited, as a matter of principle, in achieving high azimuth resolution and a large swath width at the same time. Digital beamforming (DBF) has been identified as a key technology for resolving this limitation and provides various other advantages, such as an improved signal-to-noise ratio (SNR) or the adaptive suppression of radio interference (RFI). Airborne SAR sensors with digital beamforming capabilities are essential tools to research and validate this important technology for later implementation on a satellite. Currently, the Microwaves and Radar Institute of the German Aerospace Center (DLR) is developing a new advanced high-resolution airborne SAR system with digital beamforming capabilities, the so-called DBFSAR, which is planned to supplement its operational F-SAR system in near future. It is operating at X-band and features 12 simultaneous receive and 4 sequential transmit channels with 1.8 GHz bandwidth each, flexible DBF antenna setups and is equipped with a high-precision navigation and positioning unit. This paper aims to present the DBFSAR sensor development, including its radar front-end, its digital back-end, the foreseen DBF antenna configuration and the intended calibration strategy. To analyse the status, performance, and calibration quality of the DBFSAR system, this paper also includes some first in-flight results in interferometric and multi-channel marine configurations. They demonstrate the excellent performance of the DBFSAR system during its first flight campaigns.

Advanced Signal Processing Techniques for Guided Wave Corrosion Monitoring System in Secondary Circuits of Nuclear Power Plants

2018 ◽  
Author(s):  
Andrei Gribok ◽  
Vivek Agarwal
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Signal To Noise Ratio ◽  
Guided Wave ◽  
Detection Sensitivity ◽  
Complex Geometries ◽  
Corrosion Monitoring ◽  
Coherent Noise ◽  
Induced Defects

This paper describes the application of independent component analysis (ICA) to detect corrosion-induced defects in commercial nuclear power plants. This paper analyzes the applicability and benefits of ICA when applied to guided wave (GW) technology to detect corrosion in secondary circuits, as well as studying the potential for expanding the range of GW technology to include complex geometries and piping components. The ultrasonic GWs can inspect long stretches of straight piping; however, more complex geometries that include elbows, welds, and tees are causing spurious reflections and coherent noise, which significantly decreases the sensitivity of the GW systems. The potential of ICA to improve detection sensitivity is analyzed and practical recommendations are provided. It is demonstrated on GW data collected at one of the commercial nuclear power plants that ICA, under certain conditions, is capable of separating different coherent noise components and has potential for improving signal-to-noise ratio.

scholarly journals UV-Visible Photodetector Based on I-type Heterostructure of ZnO-QDs/Monolayer MoS2

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Yong Heng Zhou ◽  
Zhi Bin Zhang ◽  
Ping Xu ◽  
Han Zhang ◽  
Bing Wang
Keyword(s):  
Visible Spectrum ◽  
High Sensitivity ◽  
Response Speed ◽  
Contact Interface ◽  
Monolayer Mos2 ◽  
Hybrid Device ◽  
Spectral Selectivity ◽  
Uv Visible ◽  
Deep Uv ◽  
Zno Qds

AbstractMonolayer MoS2 has shown excellent photoresponse properties, but its promising applications in high-sensitivity photodetection suffer from the atomic-thickness-limited adsorption and band gap-limited spectral selectivity. Here we have carried out investigations on MoS2 monolayer-based photodetectors with and without decoration of ZnO quantum dots (ZnO-QDs) for comparison. Compared with monolayer MoS2 photodetectors, the monolayer ZnO-QDs/MoS2 hybrid device exhibits faster response speed (1.5 s and 1.1 s, respectively), extended broadband photoresponse range (deep UV-visible), and enhanced photoresponse in visible spectrum, such as higher responsivity over 0.084 A/W and larger detectivity of 1.05 × 1011 Jones, which results from considerable injection of carries from ZnO-QDs to MoS2 due to the formation of I-type heterostructure existing in the contact interface of them.

Enhanced Photoluminescence Properties of Low-Dimensional Eu3+-Activated Y4Al2O9 Phosphor Compared to Bulk for Solid-State Lighting Applications and Latent Fingerprint Detection-Based Forensic Applications

2019 ◽  
Vol 25 (6) ◽  
pp. 1422-1430
Author(s):  
Antika Das ◽  
Subhajit Saha ◽  
Karamjyoti Panigrahi ◽  
Uttam Kumar Ghorai ◽  
Kalyan Kumar Chattopadhyay
Keyword(s):  
Solid State ◽  
Bulk Material ◽  
Optical Excitation ◽  
Superior Performance ◽  
Solvothermal Reaction ◽  
Latent Fingerprint ◽  
Light Emitting ◽  
Enhanced Photoluminescence ◽  
Improved Performance ◽  
Low Dimensional

AbstractIn recent years, nanoscale phosphors have become vital in optoelectronic applications and to understand the improved performance of nanophosphors over bulk material, detailed investigation is essential. Herein, trivalent europium-activated Y4Al2O9 phosphors were developed by solid-state reaction and solvothermal reaction methods and their performance as a function of their dimension was studied for various applications. Under 394 nm optical excitation, the photoluminescence (PL) emission, excited state lifetime of the nanophosphor, exhibits greater performance than its bulk counterpart. The homogeneous spherical structure of the nanophosphors as compared with solid lumps of bulk phosphors is the basis for almost 40% of the enhancement in nanophosphors' intense red emission compared to the bulk. Moreover, the thermal stability of the nanophosphor is much better than the bulk phosphor, which clearly indicates a key advantage of nanophosphor. The superior performance of Eu3+-doped Y4Al2O9 nanophosphors over their bulk counterparts has been demonstrated for industrial phosphor-converted light-emitting diodes and visualization of latent fingerprint.

scholarly journals A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Maurice Lamb ◽  
Patrick Nalepka ◽  
Rachel W. Kallen ◽  
Tamara Lorenz ◽  
Steven J. Harrison ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction ◽  
Agent Interactions ◽  
Human Agent ◽  
Dinner Table ◽  
Pick And Place ◽  
Low Dimensional ◽  
High Level ◽  
Near Future ◽  
Simple Interaction

Interactive or collaborative pick-and-place tasks occur during all kinds of daily activities, for example, when two or more individuals pass plates, glasses, and utensils back and forth between each other when setting a dinner table or loading a dishwasher together. In the near future, participation in these collaborative pick-and-place tasks could also include robotic assistants. However, for human-machine and human-robot interactions, interactive pick-and-place tasks present a unique set of challenges. A key challenge is that high-level task-representational algorithms and preplanned action or motor programs quickly become intractable, even for simple interaction scenarios. Here we address this challenge by introducing a bioinspired behavioral dynamic model of free-flowing cooperative pick-and-place behaviors based on low-dimensional dynamical movement primitives and nonlinear action selection functions. Further, we demonstrate that this model can be successfully implemented as an artificial agent control architecture to produce effective and robust human-like behavior during human-agent interactions. Participants were unable to explicitly detect whether they were working with an artificial (model controlled) agent or another human-coactor, further illustrating the potential effectiveness of the proposed modeling approach for developing systems of robust real/embodied human-robot interaction more generally.

Novel electrochemiluminescent materials for sensor applications

2014 ◽  
Vol 174 ◽  
pp. 357-367 ◽  
Author(s):  
Lynn Dennany ◽  
Zahera Mohsan ◽  
Alexander L. Kanibolotsky ◽  
Peter J. Skabara
Keyword(s):  
Redox Reactions ◽  
Limit Of Detection ◽  
Signal To Noise Ratio ◽  
High Sensitivity ◽  
Radical Cations ◽  
Detection Sensitivity ◽  
Sensor Development ◽  
Sensor Applications ◽  
Sensor Devices ◽  
The Impact

Electrochemiluminescence (ECL) uses redox reactions to generate light at an electrode surface, and is gaining increasing attention for biosensor development due to its high sensitivity and excellent signal-to-noise ratio. ECL studies of monodisperse oligofluorene–truxenes (T4 series) have been reported previously, showing the production of stable radical cations and radical anions, generating blue ECL. The compound in this study differs from the original structures, in that there are 2,1,3-benzothiadazole (BT) units inserted between the first and second fluorene units of the quarterfluorenyl arms. It was therefore anticipated that the incorporation of these highly luminescent and ECL-active compounds into sensor development would lead to significant decreases in detection limits. In this contribution, we report on the impact of incorporating these novel complexes into sensor devices on the ECL efficiency, as well as the ability of these to improve the detection sensitivity and decrease the limit of detection using the reagent-free detection of model analytes. The real world impact of these compounds is elucidated through the comparison with more standard ECL materials such as ruthenium-based compounds. The potential for multiple applications is to be examined within this contribution.

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