scholarly journals Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis

Micromachines ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 597
Author(s):  
Saifur Rahman ◽  
Abdullah S. Alwadie ◽  
Muhammed Irfan ◽  
Rabia Nawaz ◽  
Mohsin Raza ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Gas Sensors ◽  
Chemical Engineering ◽  
Disease Diagnosis ◽  
Medical Diagnostics ◽  
Pollution Monitoring ◽  
Oxide Semiconductor ◽  
Food And Beverage ◽  
Critical Components ◽  
Mos Sensor

Gas sensors are critical components when adhering to health safety and environmental policies in various manufacturing industries, such as the petroleum and oil industry; scent and makeup production; food and beverage manufacturing; chemical engineering; pollution monitoring. In recent times, gas sensors have been introduced to medical diagnostics, bioprocesses, and plant disease diagnosis processes. There could be an adverse impact on human health due to the mixture of various gases (e.g., acetone (A), ethanol (E), propane (P)) that vent out from industrial areas. Therefore, it is important to accurately detect and differentiate such gases. Towards this goal, this paper presents a novel electronic nose (e-nose) detection method to classify various explosive gases. To detect explosive gases, metal oxide semiconductor (MOS) sensors are used as reliable tools to detect such volatile gases. The data received from MOS sensors are processed through a multivariate analysis technique to classify different categories of gases. Multivariate analysis was done using three variants—differential, relative, and fractional analyses—in principal components analysis (PCA). The MOS sensors also have three different designs: loading design, notch design, and Bi design. The proposed MOS sensor-based e-nose accurately detects and classifies three different gases, which indicates the reliability and practicality of the developed system. The developed system enables discrimination of these gases from the mixture. Based on the results from the proposed system, authorities can take preventive measures to deal with these gases to avoid their potential adverse impacts on employee health.

scholarly journals Nanostructured Chemiresistive Gas Sensors for Medical Applications

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 462 ◽  
Author(s):  
Noushin Nasiri ◽  
Christian Clarke
Keyword(s):  
Gas Sensors ◽  
Disease Diagnosis ◽  
Medical Diagnostics ◽  
Cost Of Treatment ◽  
Promising Candidate ◽  
Human Breath ◽  
Multi Scale ◽  
Chemiresistive Gas Sensors ◽  
The Cost ◽  
Nanostructured Sensors

Treating diseases at their earliest stages significantly increases the chance of survival while decreasing the cost of treatment. Therefore, compared to traditional blood testing methods it is the goal of medical diagnostics to deliver a technique that can rapidly predict and if required non-invasively monitor illnesses such as lung cancer, diabetes, melanoma and breast cancer at their very earliest stages, when the chance of recovery is significantly higher. To date human breath analysis is a promising candidate for fulfilling this need. Here, we highlight the latest key achievements on nanostructured chemiresistive sensors for disease diagnosis by human breath with focus on the multi-scale engineering of both composition and nano-micro scale morphology. We critically assess and compare state-of-the-art devices with the intention to provide direction for the next generation of chemiresistive nanostructured sensors.

Robust Environmental Sensing Using UAVs

2021 ◽  
Vol 2 (4) ◽  
pp. 1-20
Author(s):  
Ahmed Boubrima ◽  
Edward W. Knightly
Keyword(s):  
Air Pollution ◽  
Gas Sensors ◽  
High Performance ◽  
Weather Conditions ◽  
Ambient Air ◽  
Mission Planning ◽  
Pollution Monitoring ◽  
Compound Pollution ◽  
Planning Algorithm

In this article, we first investigate the quality of aerial air pollution measurements and characterize the main error sources of drone-mounted gas sensors. To that end, we build ASTRO+, an aerial-ground pollution monitoring platform, and use it to collect a comprehensive dataset of both aerial and reference air pollution measurements. We show that the dynamic airflow caused by drones affects temperature and humidity levels of the ambient air, which then affect the measurement quality of gas sensors. Then, in the second part of this article, we leverage the effects of weather conditions on pollution measurements’ quality in order to design an unmanned aerial vehicle mission planning algorithm that adapts the trajectory of the drones while taking into account the quality of aerial measurements. We evaluate our mission planning approach based on a Volatile Organic Compound pollution dataset and show a high-performance improvement that is maintained even when pollution dynamics are high.

scholarly journals Field Study of Metal Oxide Semiconductor Gas Sensors in Temperature Cycled Operation for Selective VOC Monitoring in Indoor Air

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 647
Author(s):  
Tobias Baur ◽  
Johannes Amann ◽  
Caroline Schultealbert ◽  
Andreas Schütze
Keyword(s):  
Air Quality ◽  
Metal Oxide ◽  
Gas Sensor ◽  
Gas Sensors ◽  
Indoor Air ◽  
Ambient Air ◽  
Quantitative Agreement ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
High Temporal Resolution

More and more metal oxide semiconductor (MOS) gas sensors with digital interfaces are entering the market for indoor air quality (IAQ) monitoring. These sensors are intended to measure volatile organic compounds (VOCs) in indoor air, an important air quality factor. However, their standard operating mode often does not make full use of their true capabilities. More sophisticated operation modes, extensive calibration and advanced data evaluation can significantly improve VOC measurements and, furthermore, achieve selective measurements of single gases or at least types of VOCs. This study provides an overview of the potential and limits of MOS gas sensors for IAQ monitoring using temperature cycled operation (TCO), calibration with randomized exposure and data-based models trained with advanced machine learning. After lab calibration, a commercial digital gas sensor with four different gas-sensitive layers was tested in the field over several weeks. In addition to monitoring normal ambient air, release tests were performed with compounds that were included in the lab calibration, but also with additional VOCs. The tests were accompanied by different analytical systems (GC-MS with Tenax sampling, mobile GC-PID and GC-RCP). The results show quantitative agreement between analytical systems and the MOS gas sensor system. The study shows that MOS sensors are highly suitable for determining the overall VOC concentrations with high temporal resolution and, with some restrictions, also for selective measurements of individual components.

scholarly journals Decoration of CuO NWs Gas Sensor with ZnO NPs for Improving NO2 Sensing Characteristics

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2103 ◽  
Author(s):  
Tae-Hee Han ◽  
So-Young Bak ◽  
Sangwoo Kim ◽  
Se Hyeong Lee ◽  
Ye-Ji Han ◽  
...  
Keyword(s):  
Gas Sensor ◽  
Gas Sensors ◽  
Sol Gel ◽  
Oxide Semiconductor ◽  
Zno Nps ◽  
X Ray ◽  
Semiconductor Gas Sensor ◽  
Initial Resistance ◽  
P Type ◽  
Sensing Characteristics

This paper introduces a method for improving the sensitivity to NO2 gas of a p-type metal oxide semiconductor gas sensor. The gas sensor was fabricated using CuO nanowires (NWs) grown through thermal oxidation and decorated with ZnO nanoparticles (NPs) using a sol-gel method. The CuO gas sensor with a ZnO heterojunction exhibited better sensitivity to NO2 gas than the pristine CuO gas sensor. The heterojunction in CuO/ZnO gas sensors caused a decrease in the width of the hole accumulation layer (HAL) and an increase in the initial resistance. The possibility to influence the width of the HAL helped improve the NO2 sensing characteristics of the gas sensor. The growth morphology, atomic composition, and crystal structure of the gas sensors were analyzed using field-emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy, and X-ray diffraction, respectively.

Novel quaternary oxide semiconductor for the application of gas sensors with long-term stability

2021 ◽  
Author(s):  
Chong Wang ◽  
Yiqun Zhang ◽  
Lianjing Zhao ◽  
Chenguang Wang ◽  
Fangmeng Liu ◽  
...  
Keyword(s):  
Gas Sensors ◽  
Oxide Semiconductor ◽  
Term Stability ◽  
Long Term Stability

scholarly journals Nanoprinted high-neuron-density optical linear perceptrons performing near-infrared inference on a CMOS chip

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Elena Goi ◽  
Xi Chen ◽  
Qiming Zhang ◽  
Benjamin P. Cumming ◽  
Steffen Schoenhardt ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Speed ◽  
Near Infrared ◽  
Single Layer ◽  
Infrared Region ◽  
Optical Devices ◽  
Medical Diagnostics ◽  
Oxide Semiconductor ◽  
Process Data ◽  
Neuron Density

AbstractOptical machine learning has emerged as an important research area that, by leveraging the advantages inherent to optical signals, such as parallelism and high speed, paves the way for a future where optical hardware can process data at the speed of light. In this work, we present such optical devices for data processing in the form of single-layer nanoscale holographic perceptrons trained to perform optical inference tasks. We experimentally show the functionality of these passive optical devices in the example of decryptors trained to perform optical inference of single or whole classes of keys through symmetric and asymmetric decryption. The decryptors, designed for operation in the near-infrared region, are nanoprinted on complementary metal-oxide–semiconductor chips by galvo-dithered two-photon nanolithography with axial nanostepping of 10 nm1,2, achieving a neuron density of >500 million neurons per square centimetre. This power-efficient commixture of machine learning and on-chip integration may have a transformative impact on optical decryption3, sensing4, medical diagnostics5 and computing6,7.

scholarly journals Silver Enhances Hematite Nanoparticles Based Ethanol Sensor Response and Selectivity at Room Temperature

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 440
Author(s):  
Daniel Garcia-Osorio ◽  
Pilar Hidalgo-Falla ◽  
Henrique E. M. Peres ◽  
Josue M. Gonçalves ◽  
Koiti Araki ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Gas Sensors ◽  
Room Temperature ◽  
Gas Sensing ◽  
Ethanol Vapor ◽  
Oxide Semiconductor ◽  
Charge Carrier Density ◽  
Ethanol Sensor ◽  
Volatile Organic

Gas sensors are fundamental for continuous online monitoring of volatile organic compounds. Gas sensors based on semiconductor materials have demonstrated to be highly competitive, but are generally made of expensive materials and operate at high temperatures, which are drawbacks of these technologies. Herein is described a novel ethanol sensor for room temperature (25 °C) measurements based on hematite (α‑Fe2O3)/silver nanoparticles. The AgNPs were shown to increase the oxide semiconductor charge carrier density, but especially to enhance the ethanol adsorption rate boosting the selectivity and sensitivity, thus allowing quantification of ethanol vapor in 2–35 mg L−1 range with an excellent linear relationship. In addition, the α-Fe2O3/Ag 3.0 wt% nanocomposite is cheap, and easy to make and process, imparting high perspectives for real applications in breath analyzers and/or sensors in food and beverage industries. This work contributes to the advance of gas sensing at ambient temperature as a competitive alternative for quantification of conventional volatile organic compounds.

Innovative Curriculum on Electronic Materials Processing and Engingeering

2001 ◽  
Vol 684 ◽  
Author(s):  
Jane P. Chang
Keyword(s):  
Semiconductor Manufacturing ◽  
Chemical Engineering ◽  
Materials Science ◽  
Semiconductor Device ◽  
Electronic Materials ◽  
Dynamic Environment ◽  
Complementary Metal Oxide Semiconductor ◽  
Device Fabrication ◽  
Oxide Semiconductor ◽  
Solid State Physics

Recognizing that the traditional engineering education training is often inadequate in preparing the students for the challanges presented by this industry's dynamic environment and insufficient to meet the empoyer's criteria in hiring new engineers, a new curriculum on Semiconductor Manufacturing is instituted in the Chemical Engineering Department at UCLA to train the students in various scientific and technologica areas that are pertinenet to the microelectronics industries. This paper describes this new mutidisciplinary curriculum that provides knowledge and skills in semiconductor manufacturing through a series ofcourses that emphasize on the application of fundamenta engineeering disciplines in solid-state physics, materials science of semiconductors, and chemical processing. The curriculum comprises three major components:(1)a comprehensive course curriculum in semiconductor manufacturing; (2) a laboratory for hands-on training in semiconductor device fabrication; (3) design of experiments. The capstone laboratory course is designed to strengthen students’ training in “unit operatins” used in semicounductor manufacturing and allow them to practice engineering principles using the state-of-the-art experimental setup. It comprises the most comprehensive training(seven photolithographic steps and numero0us chemical processes)in fabricating and testing complementary metal-oxide-semiconductor (CMOS) devices. This curriculum is recentyaccredited by the Accreditation Board for Engineering and Technology(ABET).

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