Prioritizing Decomposition Methods for Measuring Small Amounts of Bismuth Using TOPSIS Scoring Technique Considering Economic, Environmental and Operational Indicators

Benyamin Chahkandi¹, Mohammad Gheibi^2* and Amir Takhtravan^3
*Correspondence: Mohammad Gheibi, Department of Civil Engineering, Ferdowsi University of Mashhad, Mashhad, Iran, Email:

Keywords

Bismuth • Decomposition methods • Economic indicators • Environmental indicators • TOPSIS

Introduction

Bismuth is a chemical element with the symbol Bi and atomic number 83 and atomic mass 208.98. It has a density of 10.05 grams per cubic centimeter and its melting and boiling points are 271 and 1564 degrees Celsius, respectively. Bismuthinite and bismite are the most important bismuth ores. Bismuth is a weak trivalent, white crystalline, heavy and brittle with a slight pink tinge, and is chemically similar to arsenic and antimony [1]. Bismuth has been known to mankind since ancient times but was often confused with lead and tin until 1753 when scientists could distinguish them. The origin of the word bismuth is not clear. It may be derived from the Arabic word (similar to kohl stone) or the German words "Weisse Masse" and "Wismuth" meaning white mass, which became the Latin, word Bisemutum in the 16th century. Bismuth is the most magnetic of all metals and has less thermal conductivity than all elements except mercury. Bismuth has unusually low toxicity compared to other heavy metals, and its alloys have been used as a substitute for lead since it is toxic to humans. However, several human and animal toxic effects of bismuth compounds have been reported. Recent studies have shown that excessive amounts of bismuth compounds affect the nervous system which convinced scientists to suggest toxicity of bismuth [2]. In recent years, bismuth has received much attention due to its chemical and physical properties. First, bismuth compounds became important in medicine. In 1786, bismuth was used to treat indigestion. In 1889, it was discovered that bismuth could be useful as an anti-syphilis agent. Its medicinal uses then spread to topical antacids and creams for the skin. Bismuth compounds are used in the manufacture of cosmetics, pigments and medicinal applications. It is also used in metallurgy, cast iron, electrochemistry, plastics, paints, oils and printing inks. The presence of small amounts of bismuth could have many effects on the magnetic, mechanical and physical properties of some materials. Bismuth improves the stability of iron carbide. The presence of small amounts of bismuth reduces the strength and brittleness of some alloys. Therefore, measuring small amounts of bismuth in different industries is of great importance. However, various methods have been proposed to detect and measure small amounts of bismuth. This research intends to use the TOPSIS decision-making system to evaluate different methods of measuring bismuth in terms of economic parameters, environment, feasibility, measurement speed and accuracy [3].

Materials and Methods

Bismuth measuring methods

There are several methods for measuring small amounts of bismuth, including electrochemical methods, molecular spectrophotometry, atomic absorption spectrometry, and Induced Coupled Plasma Spectrometry (ICP). Some of these methods are evaluated in this research, which is elaborated in Table 1.

TOPSIS prioritization system

The TOPSIS method was first proposed by Hwang and Yoon in 1981. This method is based on considering the distance of an option from the ideal and counter-ideal points. That is, the selected option should have the shortest distance from the ideal and at the same time farthest from the counter-ideal. Only when the indicators and their relative weights are definite numerical values, the TOPSIS method is applicable [4].

In this method, first after making the decision matrix scale less and assuming the weight vector of the indicators (W), the scale less weight matrix is calculated using equation (1).

In this equation, W is the diagonal matrix of the weight of the indicators whose only main elements are non-zero, ND is the decision matrix and V is the scale less weight matrix. Positive and negative ideal solutions are then calculated, based on Equation (2).

The relative proximity calculation i A to the ideal solution in which d_i⁺ and d_i⁻ are the amount of the distance is then calculated using Equation (3).

The closer the option size is to the ideal solution , the closer the value cl_i⁺ is to the unit. The above relationships are programmed and used in the MATLAB 2013b coding environment.

Results and Discussion

All the options mentioned in Table 1 are evaluated based on 5 economic, environmental, feasibility, measurement speed and accuracy indicators then have been balanced in a range of 0 to 20 using mathematical proportions which are presented in Figure 1. Also, according to importance, each of the five indicators was weighed. These weights are 0.25, 0.2, 0.1, 0.15 and 0.3 for economic, environmental, feasibility, measurement speed and accuracy indicators respectively.

 

Moreover, the data depicted in Figure 1 were operated as the input for the TOPSIS method equations. Each option is measured in terms of different indicators to the positive ideal or the best answer and also to the negative ideal or the worst answer. Finally, based on these distance measurements, the options are prioritized. The results of the positive and the negative ideal distances are shown in Figures 2 and 3 respectively.

As shown in Figure 2, Options A₇ (methylene blue-bismuth complex) and A₈ (ionic bismuth-iodide complex) have the shortest distance from the ideal positive answer, indicating their desirability.

Considering Figure 3, it can be concluded that the measurement options A₇ (methylene blue-bismuth complex) and A₈ (ionic bismuth-iodide complex) have the greatest distance from the negative ideal answer. Options A₁ (kaferron-bismuth ligand complex) and A₃ (bismuth sulfide nanoparticles and PVC membranes) have the highest distance from the positive ideal answer and the lowest distance from the negative ideal answer.

The TOPSIS analysis final results are shown in Figure 4. Options A₇ and A₈ with weight indices of 0.204 and 0.2 have the highest degree of importance and create the best conditions. Consequently, A₇ and A₈ methods are more common for measuring small amounts of bismuth in industries [5].

Comparing different methods indicates that spectrophotometric and spectroscopic measurement systems of atomic absorption have created better conditions and have better rankings in terms of economic, environmental and measurement accuracy than electrochemical and ICP methods [6].

Conclusion

Measuring small amounts of bismuth in industries considering two aspects including Industrial applications and epidemiological effects seems inevitable. From the epidemiological and environmental perspective, small amounts of mineral compounds accumulate in the living organisms' body which leads to destructive effects on health due to the biological magnification. In the present research, different methods and techniques of bismuth measurement were evaluated divided by four general methods including electrochemical, molecular spectrophotometry, atomic absorption spectroscopy and ICP in terms of economic, environmental, feasibility, speed and accuracy of measurement using the TOPSIS method. The results showed that the A₇ (methylene blue-bismuth complex) and A₈ (ionic bismuth-iodide complex) measurement methods have the highest distance from the negative ideal answer and the lowest distance from the positive ideal answer. Therefore, they were selected as the main options of the bismuth measurement system.

References

1. Reynolds, Paul T, Kathleen C Abalos1, Jennifer Hopp and Mark E Williams. “Bismuth Toxicity: A Rare Cause of Neurologic Dysfunction.” Inter J Clinical Med 3(2012): 46-48.
2. Parnell, RJG. "Bismuth in the Treatment of Syphilis." Proc R Soc Med 17 (1924): 19-26.
3. Xu, Ze-Shui, and Jian Chen. "An Interactive Method for Fuzzy Multiple Attribute Group Decision Making." Inf Sci 177 (2007): 248-263.
4. Hwang, CL and Yoon, K. “Multiple Attribute Decision Making: Methods and Applications: A State-Of-The-Art Survey.” Springer-Verlag, Berlin, US (1981).
5. Şahan, Serkan, Şerife Saçmacı, Uğur Şahin, and Ahmet Ülgen, et al. "An On-Line Preconcentration/Separation System for the Determination of Bismuth in Environmental Samples by Faas." Talanta 80 (2010): 2127-2131.
6. Naghizadeh, Matin, Mohammad Ali Taher, Mansoureh Behzadi, and Firouzeh Hassani Moghaddam. "Simultaneous Preconcentration of Bismuth and Lead Ions on Modified Magnetic Core–Shell Nanoparticles and Their Determination by Etaas." Chem Eng Sci 281 (2015): 444-452.