Development of Electronic Nose for Qualitative and Quantitative Monitoring of Volatile Flammable Liquids

A real-time electric nose (E-nose) with a metal oxide sensor (MOS) array was developed to monitor 5 highly flammable liquids (ethanol, tetrahydrofuran, turpentine, lacquer thinner, and gasoline) in this work. We found that temperature had a significant impact on the test results and temperature control could efficiently improve the performance of our E-nose. The results of our qualitative analysis showed that principal component analysis (PCA) could not efficiently distinguish these samples compared to a back-propagation artificial neural network (BP-ANN) which had a 100% accuracy rate on the test samples. Quantitative analysis was performed by regression analysis and the average errors were 9.1%–18.4%. In addition, through anti-interference training, the E-nose could filter out the potential false alarm caused by mosquito repellent, perfume and hair jelly.

Analisis Kadar Air dan Aroma Blending Kopi Arabika (Coffea arabica L) dan Robusta(Coffea canephora L) Selama Penyimpanan Dengan Principal Component Analisys (PCA)

Kopi merupakan komoditas pertanian yang menyumbang devisa terbesar bagi Indonesia dan menjadi komoditas perdagangan nomor dua di dunia. Ekspor kopi Indonesia masih terbatas pada kopi kering gelondongan, belum diolah menjadi barang jadi berupa kopi bubuk. Proses pengolahan menjadi kopi bubuk melalui serangkaian proses penyangraian yang didalamnya terjadi proses fisik dan kimia yang sangat komplek yang mempengaruhi cita rasa dan aroma. Terdapat dua jenis kopi yang berkembang di Indonesia yakni Kopi Arabika dan Robusta dengan karakteristik yang berbeda. Arabika memiliki rasa yang kuat sedangkat robusta memiliki kelebihan dari segi aroma. Jika kedua jenis kopi ini dipadukan maka akan menghasilkan cita rasa dan aroma yang kuat. Penelitian ini bertujuan untuk mengidentifikasi kadar air dan aroma blending kopi arabika dan robusta menggunakan Principal Component Analisys (PCA). PCA pada dasarnya bertujuan untuk menyederhanakan variabel yang diamati dengan cara menyusutkan (mereduksi) dimensinya. Hal ini dilakukan dengan cara menghilangkan korelasi diantara variabel bebas melalui transformasi variabel bebas asal ke variabel baru yang tidak berkorelasi.Identifikasi Aroma blending kopi Arabika dan Robusta dilakukan menggunakan empat buah sensor aroma (electric Nose) yang dipasang secara bersamaan yakni sensor TGS822, TGS825, TGS826 dan TGS2602. Hasil analisis menujukkan PCA mampu mereduksi data dan mengklasifikasi kopi sesuai input kadar air dan aroma selama penyimpanan.

A Room Temperature VOCs Gas Sensor Based on a Layer by Layer Multi-Walled Carbon Nanotubes/Poly-ethylene Glycol Composite

Sensitive detection of volatile organic compounds (VOCs) is significant for environmental monitoring and medical applications. In this work, multi-walled carbon nanotubes (MWCNTs) and polyethylene glycol (PEG) that have good adsorption for VOCs, were sprayed layer by layer on an interdigitated electrode (IDE) to build a sensitive VOCs gas sensor. The relative resistance change (△R/R) when the sensor was exposed to VOCs was measured. The sensor showed high sensitivity to acetone, ethanol, isopropanol and isoprene with fast response (110 ± 5 s) and recovery (152 ± 5 s) at room temperature, and the lower detection limit (LDL) of the sensor reached 9 ppm. With the micro-fabricated IDE structure, the sensor can be easily built into an electric nose for VOC recognition and measurement.