Development of a Gas Sensor for Eucalyptol Supervision: A Supporting Tool for Extreme Wildfire Management

Recent research on volatile organic compounds (VOC) released by the heated vegetation has shown that, under specific conditions (e.g., extreme heat, humidity, wind, and topography), VOC might foster wildfire ignition sources and explain sudden changes in fire behavior, particularly in the most susceptible and flammable forests (eucalypt forests). This work aims to develop an electronic nose (e-nose) based on a sensor’s array to monitor the concentration of eucalyptol, the major VOC compound of the Eucalyptus globulus tree. The detection of this target compound was achieved by measuring the impedance spectra of layer-by-layer developed thin films based on polyethyleneimine, poly(allylamine hydrochloride), and graphene oxide, by injecting the analyte into a custom-made vacuum chamber system. The obtained results were analyzed by the principal component analysis method. The developed e-nose sensor was able to distinguish different concentrations in a range from 411 to 1095 ppm.

Download Full-text

Detecting Traces of 17α-Ethinylestradiol in Complex Water Matrices

Sensors ◽

10.3390/s20247324 ◽

2020 ◽

Vol 20 (24) ◽

pp. 7324

Author(s):

Paulo M Zagalo ◽

Paulo A Ribeiro ◽

Maria Raposo

Keyword(s):

Principal Component Analysis ◽

Loss Tangent ◽

Electric Modulus ◽

Tap Water ◽

Principal Component ◽

Mineral Waters ◽

Layer By Layer ◽

Analysis Method ◽

Solid Supports ◽

Sensor Device

Hormones have a harmful impact on the environment and their detection in water bodies is an urgent matter. In this work, we present and analyze a sensor device able to detect traces of the synthetic hormone 17α-ethinylestradiol (EE2) below 10−9 M in media of different complexities, namely, ultrapure, mineral and tap waters. This device consists of solid supports with interdigitated electrodes without and with a polyethylenimine (PEI) and poly (sodium 4-styrenesulfonate) (PSS) layer-by-layer film deposited on it. Device response was evaluated through capacitance, loss tangent and electric modulus spectra and the data were analyzed by principal component analysis method. While the three types of spectra were demonstrated to be able to clearly discriminate the different media, loss tangent spectra allow for the detection of EE2 concentration, with a sensitivity of −0.072 ± 0.009 and −0.44 ± 0.03 per decade of concentration, for mineral and tap water, respectively. Detection limits values were found to be lower than the ones present in the literature and presenting values of 8.6 fM (2.6 pg/L) and of 7.5 fM (22.2 pg/L) for tap and mineral waters, respectively. Moreover, the obtained response values follow the same behavior with EE2 concentration in any medium, meaning that loss tangent spectra allow the quantification of EE2 concentration in aqueous complex matrices.

Download Full-text

Ionogels Based on a Single Ionic Liquid for Electronic Nose Application

Chemosensors ◽

10.3390/chemosensors9080201 ◽

2021 ◽

Vol 9 (8) ◽

pp. 201

Author(s):

Wellington B. Gonçalves ◽

Evelyn P. Cervantes ◽

Ana C. C. S. Pádua ◽

Gonçalo Santos ◽

Susana I. C. J. Palma ◽

...

Keyword(s):

Ionic Liquid ◽

Electronic Nose ◽

Electronic Devices ◽

Principal Component ◽

Solid Matrix ◽

Imidazolium Ionic Liquid ◽

Electronic Noses ◽

Custom Made ◽

Volatile Organic ◽

Supervised Classification Methods

Ionogel are versatile materials, as they present the electrical properties of ionic liquids and also dimensional stability, since they are trapped in a solid matrix, allowing application in electronic devices such as gas sensors and electronic noses. In this work, ionogels were designed to act as a sensitive layer for the detection of volatiles in a custom-made electronic nose. Ionogels composed of gelatin and a single imidazolium ionic liquid were doped with bare and functionalized iron oxide nanoparticles, producing ionogels with adjustable target selectivity. After exposing an array of four ionogels to 12 distinct volatile organic compounds, the collected signals were analyzed by principal component analysis (PCA) and by several supervised classification methods, in order to assess the ability of the electronic nose to distinguish different volatiles, which showed accuracy above 98%.

Download Full-text

Nonlinear analysis of electroencephalograms of healthy people during driving test based on symplectic principal component analysis method

PsycEXTRA Dataset ◽

10.1037/e573792014-017 ◽

2014 ◽

Author(s):

Min Lei ◽

Guang Meng ◽

Nilanjan Sarkar ◽

Jing Fan ◽

Josh Wade ◽

...

Keyword(s):

Principal Component Analysis ◽

Nonlinear Analysis ◽

Principal Component ◽

Component Analysis ◽

Healthy People ◽

Analysis Method ◽

Principal Component Analysis Method

Download Full-text

PENELITIAN DAN PENGEMBANGAN SENSOR AROMATIK SEBAGAI ALAT DETEKSI ALKOHOL PADA PARFUM DAN WEWANGIAN UNTUK AUTENTIKASI PRODUK PARFUM HALAL

Jurnal Penelitian Agama ◽

10.24090/jpa.v18i2.2017.pp302-322 ◽

2017 ◽

Vol 18 (2) ◽

pp. 302-322

Author(s):

Fajar Hardoyono

Keyword(s):

Sensor Array ◽

Principal Component ◽

Metal Oxide Semiconductor ◽

Oxide Semiconductor ◽

Response Patterns ◽

Data Recording ◽

Analysis Method ◽

Sample Group ◽

Array Pattern ◽

Group Data

Abstract: The development of aromatic sensor array instrument for the detection of alcohol in perfume. The research was conducted by developing the sensor array using 8 sensors made of metal oxide semiconductor. The sensor types used in this study consisted of TGS 813, TGS 822, TGS 2600, TGS 826, TGS 2611, TGS 2620, TGS 2612 and TGS 2602. Response patterns of 8 sensors formed a sensor array pattern used to detect the aroma of 2 groups of samples perfume made from the essential oil of ginger. The first sample group is pure ginger atsiri oil without mixed alcohol. The second sample group was made from the ginger atsiri oil mixed with alcohol with a level of 0.02 M. The results of the data recording show that the developed instrument is able to dissect the first sample group with the second sample group. Data analysis using principal component analysis method (PCA shows that the instrument is able to distinguish the contaminated alcohol perfume group 0.2 M with the alcohol-free perfume group with 100% accuracy. Keywords: Sensor Aroma, Perfume.

Download Full-text

Modeling, comparison and evaluation of one-DOF six-bar bioinspired jumping leg mechanisms

Advances in Mechanical Engineering ◽

10.1177/1687814021992954 ◽

2021 ◽

Vol 13 (2) ◽

pp. 168781402199295

Author(s):

Ziqiang Zhang ◽

Qi Yang ◽

Xingkun Liu ◽

Chuanzhong Zhang ◽

Jinnong Liao

Keyword(s):

Center Of Mass ◽

Principal Component ◽

Analysis Method ◽

Index Distribution ◽

Inertial Moment ◽

Structure Index ◽

Mean And Variance ◽

Research Objects ◽

Leg Mechanisms ◽

Selection Of

One degree-of-freedom (DOF) jumping leg has the advantages of simple control and high stiffness, and it has been widely used in bioinspired jumping robots. Compared with four-bar jumping leg, six-bar jumping leg mechanism can make the robot achieve more abundant motion rules. However, the differences among different configurations have not been analyzed, and the choice of configurations lacks basis. In this study, five Watt-type six-bar jumping leg mechanisms were selected as research objects according to the different selection of equivalent tibia, femur and trunk link, and a method for determining the dimension of the jumping leg was proposed based on the movement law of jumping leg of locust in take-off phase. On this basis, kinematics indices (sensitivity of take-off direction angle and trunk attitude angle), dynamics indices (velocity loss, acceleration fluctuation, and mean and variance of total inertial moment) and structure index (distribution of center of mass) were established, and the differences of different configurations were compared and analyzed in detail. Finally, according to the principal component analysis method, the optimal selection method for different configurations was proposed. This study provides a reference for the design of one DOF bioinspired mechanism.

Download Full-text

Study on the Effect Factors of Non-Perormance Loan Ratio of Chinese Commerical Banks

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.50-51.728 ◽

2011 ◽

Vol 50-51 ◽

pp. 728-732

Author(s):

Ping Li ◽

Ming Ying Zhuo ◽

Li Chao Feng ◽

Rui Zhang

Keyword(s):

Principal Component Analysis ◽

Commercial Banks ◽

Principal Component ◽

Component Analysis ◽

Analysis Method ◽

Analysis Model ◽

Principal Component Analysis Model ◽

Effect Factors ◽

Financial Indicator ◽

Commerical Banks

Non-performance loan ratio is one of the important assessment criteria of the security of credit assets. It is also an important financial indicator to evaluate the general strength of commercial banks. Using principal component analysis method and statistical software SPSS16.0 and based on the non-performance loan ratio and relative data of some commercial banks in China in 2007, this paper provided a principal component analysis model for the non-performance loan ratio of China’s commercial banks. The factors that affect the non-performance loan ratio were refined in this paper. Finally, the characteristics of effect factors of each bank were analyzed and compared in detail.

Download Full-text