"Detection of Metal Ions Using Pinto Bean Synthesized Carbon..." by Alyss Rollins & Justin Novoa

Detection of Metal Ions Using Pinto Bean Synthesized Carbon Quantum Dots Alyss Rollins and Justin Novoa, Stevenson University



Abstract: As the world population increases at an exponential rate, the availability of clean drinking water continues to dwindle. Since the inception of the industrial revolution, the planet has exhibited a substantial decrease in water quality due to pollution, especially in developing countries. There is a heightened urgency to find an affordable and accessible way of identifying deadly toxins in drinking water. Carbon-based quantum dots (CQDs) have chemical groups on their surface that give them fluorescent properties, mainly carbon-oxygen double bonds (Fig. 1). When particular metal ions encounter these dots, they bind to the surface, decreasing their fluorescence (Liu et al., 2012). By using a spectrophotometer, the fluorescence of these dots can be measured to determine if and what metal ions successfully bind to the CQDs. If a significant decrease in fluorescence is recorded for one of these samples, it is presumed that the CQDs have successfully detected the metal toxins and therefore can be used to test for contaminated water.


The purpose of this experiment was to use pinto beans- a novel source of these dots- to successfully detect metal toxins in drinking water. To do this, pinto bean synthesized CQDs were combined with different metal ion solutions and the fluorescence of each sample was recorded. After experimentation, it was concluded that this preparation of CQDs did not behave to a close enough degree of previous experiments to definitively say that they are a reliable way of detecting metal toxins in water.




Figure 1. Carbon Quantum Dot Molecular Structure Sample (Lim et al., 2015)

Introduction


According to the 2017 United Nations’ World Water Development Report, over 80% of the world’s wastewater is released, untreated, to the environment. In some least developed countries, this number can reach over 95% (Fig. 2). In these impoverished regions, clean water is a rare commodity in which individuals must travel long distances to access. Water contamination also affects the United States. In 2014, a Government Accountability Report conducted by the GAO found that 40 out of 50 state water managers expect their water quality to drop under EPA-regulated conditions in some portion of their states over the next decade. Metal ion contaminants such as copper, zinc, nickel, and cobalt, all pose a threat to public health if they are present over a certain amount in drinking water. It is key to note that water containing small amounts of these metal ions is common in all public water systems and does not pose a threat to the health of the population. Only when in large amounts are these metals dangerous. Because of this threat, the EPA has established certain limits for each of these contaminants in which any amount exceeding these limitations would be dangerous to the consumer. For example, copper has an EPA-regulated action level of 1.3 mg per liter (MN Dept. of Health, 2018). This common yet potentially deadly toxin found in drinking water has been recorded to induce systematic ailments such as liver cirrhosis and kidney disease if consumed in amounts exceeding regulation standards (Eife et al., 1999).




Figure 2. 2015 World Clean Water Availability (Wessel, 2019)

Based upon data from the 2017 Progress on Drinking Water, Sanitation and Hygiene Report conducted by the World Health Organization and UNICEF, this map shows the greatest disparity in sub-Saharan Africa, India, and Southeast Asia.


Carbon quantum dots (CQDs) are small carbon nanoparticles that were first discovered in 2004 by a team of scientists while purifying single-walled carbon nanotubules (Xu et al., 2004). These fluorescent dots have gained the interest of many scientists due to their impressive array of chemical and physical properties including high crystallization, good dispersibility, photoluminescence, superconductivity, and rapid electron transfer (Wang et al., 2019). Additionally, the surface of CQDs contain many functional groups that allow them to bind and react with nearby molecules. Although these nanoparticles are not found in nature, their synthesis is a simple and relatively affordable process. Because of this, experts are using these nanoparticles to make outstanding strides in areas such as nanomedicine and bioimaging.


Using Carbon Quantum Dots (CQDs) to Detect Metal Toxins in Water


Due to their fluorescent properties, scientists have discovered that carbon quantum dots (CQDs) can be used to detect metal ions in drinking water. As CQDs bind to metal ions, the fluorescence of the sample for that particular metal will decrease. Because of the wide variety of source material used for their synthesis, CQDs have a wide variety of structures and have the ability to bind to many different molecules. As a preliminary experiment, the research conducted by Liang et al. (2013) was replicated using egg white as the source of carbon. This experiment provided the baseline data from which the novel experiment would be compared.​ Data collected showed that the CQDs synthesized from the egg successfully detected nickel ions via a decrease in fluorescent intensity below the control in that particular sample (Fig. 3, 4).





Figure 3. Egg CQD and Metal Ion Solution Fluorescence




Figure 4. Egg CQD and Metal Ion Solution Fluorescence at 482.75nm Wavelength

Pinto Beans as a Source of CQDs


As the ever-expanding research of CQDs have been explored through various types of carbon-based substances, multiple types of beans have been the source for CQD synthesis. Research was conducted with the goal of finding a novel and easily accessible source of CQDs. Carbohydrates are macromolecules containing a large ratio of carbon in their molecular structures. To find the best possible novel candidate for the synthesis of these carbon-based dots, we searched for beans containing a high amount of carbohydrates. Pinto beans were selected as source material with the assumption that their high concentration of carbs would be more successful at synthesizing carbon-rich CQDs (Fig. 5). Pinto beans are also an affordable and accessible commodity. According to the USDA, pinto beans have an average price of around $1.07 per pound. As a hearty plant, they are grown in almost every region, and this source of CQDs can be bought and cultivated all over the world.



Figure 5. Bean Nutrition Chart Based on ½ Cup Measurement (NBGA, 2020)


In this figure, pinto beans are identified as one of the highest sources of carbohydrates, with around 22 grams per ½ cup serving. Other beans in this chart have previously been researched for CQD synthesis.


CQD Synthesis and Metal Solutions Preparation


For this experiment, a top-down approach was used to synthesize the carbon dots. Techniques from a similar study with black beans conducted by Jia et al. (2019) were referenced when designing this experiment. About 5 dried pinto beans were placed into a mortar and pestle and ground into small pieces. These pieces were divided into two crucibles and placed in a muffle furnace at 200°C for 4 hours. After being cooled to room temperature, the samples were placed back into a mortar and pestle and ground into a fine powder. 1.0g of each fine powder was then dissolved in 10mL of water using a magnetic stirrer. Using filter paper and a funnel, the solids were separated from the liquid CQD solutions.

To represent metal toxins in drinking water, metal ion solutions were created with the following metal salts: copper (Cu2+), zinc (Zn2+), cobalt (Co2+), and nickel (Ni2+). Using a micropipette, 100µl of CQD stock solution, 100µl of each metal salt solution (Cu2+, Zn2+, Co2+, Ni2+), and 800µl of buffer solution were dispersed into separate test vials. A control sample was created by replacing the 100µl of metal salt with H2O.



Figure 6. Crushed Bean Samples After Pyrolyzation


After both samples were pyrolyzed, there was a noticeable difference in shade between the two. This discrepancy could possibly be attributed to their difference in placement in the muffle furnace.



Figure 7. Final CQD Stock Solutions


After synthesis and extraction, the CQD stock solutions exhibited a color difference with respect to which bean sample they were synthesized from.


This particular trial of the experiment yielded two different shades of powder after pyrolyzation (Fig. 6), which in turn yielded two different shades of CQD stock solution (Fig 7). The lighter solution was derived from the darker bean sample, and vice versa. These samples were labeled as light (L) or dark (D) respectively. Because both samples were placed in the furnace at the same time and duration, reasons for this difference in color could be attributed to the crucibles’ placement in the furnace or the variation in particle sizes resulting from being ground by hand in the mortar and pestle.


Fluorescence Spectroscopy



Figure 8. Basic Illustration of Spectrophotometer Structure (Shim, 2021)

A spectrophotometer is a device that measures how much light is absorbed by a liquid sample (Fig. 8). First, a collimator transmits a beam of light through a monochromator which splits the light into several component wavelengths. Then a wavelength selector transmits only the desired wavelengths through the sample. The light that passes through the sample is picked up by a detector on the other side. The particular instrument used in this experiment was a SpectroVis® Plus spectrophotometer. Using Logger Pro® software, the intensity of the fluorescence was quantified and graphed for further analysis.


Determining Optimal Concentration



Figure 9. Dark (D) and Light (L) CQD Sample Dilutions

In this graph, the blue plots represent Sample D and the green plots represent Sample L before and after dilution. Both show a decrease in intensity from 100% to 75% concentration.



Before the metal solutions could be tested, it was important to ensure that each of the samples were at their optimal concentrations. To do this, both Samples L and D were measured at 100% concentration and at a diluted 75% concentration. It was determined that both samples were at optimal concentration because the intensity of both decreased after dilution (Fig. 9).


Results



Figure 10. CQD and Metal Solutions Fluorescence (Sample D)



Figure 11. CQD and Metal Solutions Fluorescence (Sample L)

After graphing the Logger Pro® data for both light and dark stock samples (Fig. 10, 11), the peak intensity was determined to be at the wavelength 491.65nm. Each value at this wavelength is converted to be proportional to the control by dividing the intensity value of the particular metal by that of the control sample. The values of each sample at this wavelength were graphed to determine if the CQDs successfully bonded to any of the metal ions, decreasing the intensity below that of the control (Fig. 12, 13).




Figure 12. CQD and Metal Solutions Fluorescence at 491.65nm (Sample D)



Figure 13. CQD and Metal Solutions Fluorescence at 491.65nm (Sample L)

Comparing the results found in this experiment with that of a similar experiment conducted by Liu et al. (2012), it is apparent that the CQDs behaved differently when binding to metal ions.​ In their experiment, the intensity of copper decreased 0.23 units from the control (Fig. 14). The results for Sample D show that none of the metal samples decreased in intensity below that of the control. This is in contrast with the baseline experiment conducted as well as previous research conducted. The graph for Sample L, however, did show that multiple metal ions decreased in intensity when bonded to the CQDs, most notably copper and zinc. The intensity of copper decreased 0.059 units from the control and the zinc decreased 0.076 units. ​To determine if CQDs from pinto beans are reliable in detecting metal ions, the value for copper was compared from this experiment to the previous experiment mentioned.​ Our sample displays a behavior that is approximately 26% of the previously recorded data for copper.



Figure 14. Reference Experiment CQD Fluorescence Data (Liu et al., 2012)

This experiment conducted by Liu and colleagues uses CQDs synthesized from grass. In their experiment, they saw their dots bind particularly well to copper, which decreased in fluorescence by approximately 0.23 units from the control.



Discussion


When compared to existing research, it was concluded that our CQDs did not behave within a close enough range for us to positively say that they are a reliable method for identifying these particular metal toxins in drinking water. Although we were able to successfully synthesize fluorescent CQDs from the pinto beans, we determined that these CQDs were not able to definitively detect the metals tested. This does not necessarily mean that the CQDs are defective, but rather it could mean that they bind well with different metal ions that were not tested in this experiment. As previously stated, CQDs can be made from a wide variety of sources and subsequently have a wide variety of structures. These structures all have different chemical compositions which will naturally bind to different molecules. We can see the effect of these structural differences with the light (L) and dark (D) samples. Because of the obvious difference in physical properties between the two, the samples must have variations both in overall dot size and/or surface chemistry. This in turn effects if and how the metal ions bind to the CQDs, and likely explains the variation between our experiment and the reference. It also provides a potential explanation as to why some samples increased in fluorescence above the control. It is possible that the structural and chemical differences between the L and D samples caused the metal ions to bond or react with them in a way that would increase the reflectivity of the light beam off of the molecules. This being said, there is a possibility that our CQDs exhibited this behavior because of the differences in procedure between our experiment and the others. Liu and colleagues, whose experiment we used as our main reference, likely had access to technologies with higher accuracy than the ones we had available to us. Additionally, our procedure was created by researching and compiling information from multiple CQD synthesis procedures and therefore was not identical to the reference procedure. These differences, however minor, could have contributed to the disparities seen between our results and theirs. Although we could not prove the efficacy of these CQDs in this experiment, pinto beans are a cheap and easily accessible source material, and it would be beneficial to explore further research into their usability in detecting other toxins in drinking water.



References


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