Malaysian Journal of Analytical Sciences, Vol 27 No 5 (2023): 935 - 945

 

DEVELOPMENT OF A HOME-BUILT UV-VISIBLE SPECTROPHOTOMETER EMPLOYING ARDUINO MICROCONTROLLER SYSTEM FOR CHEMICAL ANALYSIS

 

(Pembangunan Spektrofotometer Ultraungu-Nampak Binaan Sendiri Menggunakan Sistem Pengawal Mikro Arduino untuk Analisis Bahan Kimia)

 

Anis Nur Shasha Abdul Halim1, Tam Yi Qian1, Aemi Syazwani Abdul Keyon 1,2*, and Nur Safwati Mohd Nor 3

 

1Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia

2Centre for Sustainable Nanomaterials, Ibnu Sina Institute for Scientific and Industrial Research, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia

3Department of Applied Mechanics and Design, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM, Johor Bahru, Johor, Malaysia.

 

*Corresponding author: aemi@utm.my

 

 

Received: 13 March 2023; Accepted: 22 August 2023; Published:  30 October 2023

 

 

Abstract

This work demonstrated the development and the application of a home-built spectrophotometer device employing Arduino microcontroller. Arduino UNO microcontroller was utilized as a data acquisition system. Arrangement of the system’s hardware was based on the working principle of a commercially available benchtop instrument. For the first time in the scope of Arduino-based spectrophotometer, the developed device consisted of double light sources and innovative monochromator design to cater the requirement of ultraviolet (UV) and visible ranges. A visible white LED and UV LED emitting between 190 and 600 nm spectrum were employed. Light dependent resistor (LDR) and GUVA-S12SD UV sensor were utilized as light detectors. Innovative monochromator system was incorporated with combination of stepper motor and DVD disc as a diffraction grating for wavelength selection. The effectiveness of the UV range in the device was tested using bisphenol A (BPA) and triclosan, while Reactive Orange 16 and Reactive Red 120 dyes for visible range. The device could detect BPA from 10 to 50 ppm concentration (obtained through external linear graph producing R2 = 0.9970), while triclosan from 1 to 5 ppm (R2 = 0.9971).  The limit of detection (LOD) and the limit of quantitation (LOQ) for BPA were 7.01 ppm and 23.38 ppm, respectively. The LOD and LOQ for triclosan were 0.60 ppm and 1.99 ppm, respectively. The results obtained from the device on all analytes were validated with a commercially available benchtop UV-vis spectrophotometer. The linearity of BPA from 10 to 50 ppm obtained a correlation of R2 = 0.9941. Triclosan showed R2 = 0.9965 for linearity from 1 to 5 ppm. The LOD and LOQ were 8.58 ppm and 28.61 ppm, respectively. The LOD and LOQ for triclosan were 0.66 ppm and 2.19 ppm respectively. As for visible range, the benchtop spectrophotometer could detect Reactive Orange 16 from 10 to 50 ppm concentration (R2 = 0.9967) while Reactive Red 120 (R2 = 0.9958).  The LOD and LOQ for Reactive Orange 16 were 6.76 ppm and 22.52 ppm, respectively. The LOD and LOQ for Reactive Red 120 were 6.94 ppm and 23.13 ppm, respectively. Nearly identical R2, LOD and LOQ were obtained for both home-built Arduino device and the benchtop UV-visible spectrophotometer. These data indicated positive outcomes with accuracy percentage 95% and 97.2% for BPA and triclosan, 98.6% and 93.5% for Reactive Orange 16 and Reactive Red 120 dye of the home-built Arduino spectrophotometer.

 

Keywords: arduino, home-built, UV-visible spectrophotometer, dye analysis, pollutant analysis

 

 

 

Abstrak

Kajian ini menunjukkan pembangunan dan aplikasi peranti spektrofotometer binaan sendiri yang menggunakan mikropengawal Arduino. Pengawal mikro Arduino UNO telah digunakan sebagai sistem pemerolehan data. Susunan perkakasan sistem adalah berdasarkan prinsip kerja instrumen komersil. Buat pertama kali dalam skop spektrofotometer berasaskan Arduino, peranti yang dibangunkan terdiri daripada sumber cahaya berganda dan reka bentuk monokromator yang inovatif untuk memenuhi keperluan julat ultraungu (UV) dan boleh dilihat. LED putih yang kelihatan dan LED UV yang memancarkan antara spektrum 190 dan 600 nm telah digunakan. Perintang bergantung cahaya (LDR) dan sensor UV GUVA-S12SD digunakan sebagai pengesan cahaya. Sistem monokromator yang inovatif telah digabungkan dengan gabungan motor pelangkah dan cakera DVD sebagai parut difraksi untuk pemilihan panjang gelombang. Keberkesanan julat UV dalam peranti telah diuji menggunakan bisphenol A (BPA) dan triclosan, manakala pewarna Reactive Orange 16 dan Reactive Red 120 untuk julat yang boleh dilihat. Peranti boleh mengesan BPA dari 10 hingga 50 ppm kepekatan (diperolehi melalui graf linear luaran yang menghasilkan R2 = 0.9970), manakala triclosan dari 1 hingga 5 ppm (R2 = 0.9971). Had pengesanan (LOD) dan had kuantiti (LOQ) untuk BPA ialah 7.01 ppm dan 23.38 ppm, masing-masing. LOD dan LOQ untuk triclosan ialah 0.60 ppm dan 1.99 ppm, masing-masing. Keputusan yang diperoleh daripada peranti pada semua analit telah disahkan dengan spektrofotometer UV-vis komersil. Kelinearan BPA dari 10 hingga 50 ppm memperoleh korelasi R2 = 0.9941. Triclosan menunjukkan R2 = 0.9965 untuk lineariti dari 1 hingga 5 ppm. LOD dan LOQ masing-masing ialah 8.58 ppm dan 28.61 ppm. LOD dan LOQ pula untuk triclosan masing-masing adalah  0.66 ppm dan 2.19 ppm. Bagi julat yang boleh dilihat, spektrofotometer komersil boleh mengesan Jingga Reaktif 16 daripada kepekatan 10 hingga 50 ppm (R2 = 0.9967) manakala Merah Reaktif 120 (R2 = 0.9958). LOD dan LOQ untuk Oren Reaktif 16 masing-masing ialah 6.76 ppm dan 22.52 ppm. LOD dan LOQ untuk Reactive Red 120 ialah 6.94 ppm dan 23.13 ppm, masing-masing. R2, LOD dan LOQ yang hampir sama diperolehi untuk kedua-dua peranti Arduino yang dibina sendiri dan spektrofotometer komersil. Data ini menunjukkan hasil positif dengan peratusan ketepatan 95% dan 97.2% untuk BPA dan triclosan, 98.6% dan 93.5% untuk Reactive Orange 16 dan Reactive Red 120 bagi pewarna spektrofotometer Arduino yang dibina sendiri.

 

Kata kunci: arduino, binaan sendiri, spektrofotometer UV-cahaya nampak, analisis pewarna, analisis bahan pencemar

 


References

1.       Copaciu, F., Opriş, O., Coman, V., Ristoiu, D., Niinemets, Ü., and Copolovici, L. (2013). Diffuse water pollution by anthraquinone and azo dyes in environment importantly alters foliage volatiles, carotenoids and physiology in wheat (Triticum aestivum). Water, Air, & Soil Pollution, 224(3): 1-11.

2.       Rafiq, A., Ikram, M., Ali, S., Niaz, F., Khan, M., Khan, Q., and Maqbool, M. (2021). Photocatalytic degradation of dyes using semiconductor photocatalysts to clean industrial water pollution. Journal of Industrial and Engineering Chemistry, 97: 111-128.

3.       Chen, S., Zhang, J., Zhang, C., Yue, Q., Li, Y., and Li, C. (2010). Equilibrium and kinetic studies of methyl orange and methyl violet adsorption on activated carbon derived from Phragmites australis. Desalination, 252(1-3): 149-156.

4.       Ray, S. C., and Jana, N. R. (2017). Application of carbon-based nanomaterials for removal of biologically toxic materials. In Carbon Nanomaterials for Biological and Medical Applications (pp. 43-86).

5.       Perez-Urquiza, M., Ferrer, R., and Beltran, J. L. (2000). Determination of sulfonated azo dyes in river water samples by capillary zone electrophoresis. Journal of Chromatography A, 883: 277-283.

6.       Carneiro, P. A., Umbuzeiro, G. A., Oliveira, D. P., and Zanoni, M. V. (2010). Assessment of water contamination caused by a mutagenic textile effluent/dyehouse effluent bearing disperse dyes. Journal Hazardous Materials, 174(1-3): 694-699.

7.       Rajabnejad, S.-H., Badibostan, H., Verdian, A., Karimi, G. R., Fooladi, E., and Feizy, J. (2020). Aptasensors as promising new tools in bisphenol A detection - An invisible pollution in food and environment. Microchemical Journal, 155: 104722.

8.       Zhang, Y., Causserand, C., Aimar, P., and Cravedi, J. P. (2006). Removal of bisphenol A by a nanofiltration membrane in view of drinking water production. Water Research, 40(20), 3793-3799.

9.       Boas, M., Feldt-Rasmussen, U., and Main, K. M. (2012). Thyroid effects of endocrine disrupting chemicals. Molecular Cellular Endocrinology, 355(2): 240-248.

10.    Oketola, A. A., and Fagbemigun, T. K. (2013). Determination of nonylphenol, octylphenol and bisphenol-a in water and sediments of two major rivers in Lagos, Nigeria. Journal of Environmental Protection, 4: 38- 45.

11.    Zheng, G., Yu, B., Wang, Y., Ma, C., and Chen, T. (2020). Removal of triclosan during wastewater treatment process and sewage sludge composting-A case study in the middle reaches of the Yellow River. Environmental International, 134: 105300.

12.    Kamińska, G., Marszałek, A., Kudlek, E., Adamczak, M., and Puszczało, E. (2022). Innovative treatment of wastewater containing of triclosan – SBR followed by ultrafiltration/adsorption/advanced oxidation processes. Journal of Water Process Engineering, 50: 103282.

13.    Han, M., Wang, Y., Tang, C., Fang, H., Yang, D., Wu, J., and Jiang, Q. (2021). Association of triclosan and triclocarban in urine with obesity risk in Chinese school children. Environmental International, 157: 106846.

14.    Nandikes, G., Pathak, P., Razak, A. S., Narayanamurthy, V., and Singh, L. (2022). Occurrence, environmental risks and biological remediation mechanisms of Triclosan in wastewaters: Challenges and perspectives. Journal of Water Process Engineering, 49: 103078.

15.    Dong, X., He, Y., Peng, X., and Jia, X. (2021). Triclosan in contact with activated sludge and its impact on phosphate removal and microbial community. Bioresource Technology, 319: 124134.

16.    Poh, J.-J., Wu, W.-L., Goh, N. W.-J., Tan, S. M.-X., and Gan, S. K.-E. (2021). Spectrophotometer on-the-go: The development of a 2-in-1 UV–vis portable arduino-based spectrophotometer. Sensors and Actuators A: Physical, 325: 112698.

17.    Morais, C. d. L. M. d., Carvalho, J. C., Sant’Anna, C., Eugênio, M., Gasparotto, L. H. S., and Lima, K. M. G. (2015). A low-cost microcontrolled photometer with one color recognition sensor for selective detection of Pb2+ using gold nanoparticles. Analytical Methods, 7(18): 7917-7922.

18.      Mabbott, G. A. (2014). Teaching electronics and laboratory automation using microcontroller boards. Journal of Chemical Education, 91(9): 1458-1463.

19.      Singh, H., Singh, G., Mahajan, D. K., Kaur, N., and Singh, N. (2020). A low-cost device for rapid ‘color to concentration’ quantification of cyanide in real samples using paper-based sensing chip. Sensors and Actuators B: Chemical, 322: 128622.

20.      Widiatmoko, E., Budiman, M., and Abdullah, M. (2011). A simple spectrophotometer using common materials and a digital camera. Physics Education, 46(3): 332.

21.      Zhang, X., Fang, Y., and Zhao, Y. (2013). A portable spectrophotometer for water quality analysis. Sensors & Transducers, 148(1): 47.