Blog #3

Ever since December, I have been able to make progress with my research. Every single week, I was able to come in and run my four fluoroquinolone drugs. I have been testing them constantly with the same power at 50 and multiplier factor at 50. I’ve tested the samples at 3 different times: 1,3, and 5. Using the scans, I was able to produce spectras for each drug using Igor software. Igor allows me to open up excel files and label the graphs with its peaks accordingly. Since I was able to do run my samples every single week, I took the average of my runs at the different times. This helps to improve the signal to noise ratio and produce accurate results. Seeing all the progress I have made so far makes me feel a lot better about my research because I was struggling a bit in the beginning. I was able to however overcome my issues with the laser Raman and produce results.

From my research so far, I was able to print out a poster of my work and present at the annual Dyson Society of Fellows this past March. It felt good to see my hard work on display for others to understand. I was able to tell those who came up to my poster all of the accomplishments I have achieved thus far. I also was able to answer questions and take in advice that I could use for future work with my fluoroquinolone drugs.

Looking back at the results produced so far, I have been able to obtain accurate spectras for the four fluoroquinolone drugs. Sarafloxacin, norfloxacin, and ciprofloxacin produced peaks using the laser Raman that were similar to its Raman spectras from before. However, enrofloxacin’s spectra produced no peaks that can be used to identify the drug. I find this interesting because the laser Raman was able to produce spectras for the other three types, just not this one. For the rest of my time doing this research, I want to continue running my samples to see if taking the average for all of my trials help my results. I also want to investigate why in particular enrofloxacin only produces peaks with the original Raman, not the laser Raman used.

Discrimination of fluoroquinolone antibiotics using vibrational spectroscopy – Blog 2

During my Fall semester under the UGRI, I have been able to make some progress with my project. First off, I was able to obtain new samples of the four types of fluoroquinolones. The trials I have been running has been with the portable Raman, which is located in the science department. I had to begin by testing the portable Raman on other samples. I tested Aspirin and analyzed the spectra produced. I was able to see that the portable Raman still produces spectras of samples that we know are accurate.

From this, I was able to move on to my own fluoroquinolone samples. The first one I tested was enrofloxacin. I was confused about the spectras produced originally because the peaks did not reach the level of energy I needed. This made me wonder what was wrong with the Raman machinery. Because of this, I had to take some time playing with the variables of the program. One thing I switched was how long it took for the program to analyze the drug. I changed the settings from 1 minute to 30 minutes. However, this still produced a weak spectra compared to my past results. Also, I had one spectra that showed so much noise, that it was impossible to analyze.

My problems with the portable Raman so far made me realize that not every experiment will go smoothly. However, this brings up a bunch of questions that could help me fix these incidents. First off, I am wondering if it’s the drug itself that is reading abnormally or if it’s the portable Raman? For my next set up, I can try taking a sample of the drug and place it in a separate container for analysis. I am also wondering why changing the time slot for analysis did not help the spectras being produced? What will help my spectras gain power? Hopefully, I will be able to fix these problems in the future, in order to get an accurate reading of my fluoroquinolone samples.

Discrimination of fluoroquinolone antibiotics using vibrational spectroscopy Blog #1


The title of my research is “Discrimination of fluoroquinolone antibiotics using vibrational spectroscopy”. The goal of this whole project is to differentiate between four fluoroquinolones that I will be testing. The four fluoroquinolones I am working with are sarafloxacin, enrofloxacin, norfloxacin, and ciprofloxacin. Through my research, I will be able to analyze their chemical bonds and compounds.

From this project, I hope to learn different computational techniques that I can apply to schoolwork and other classes that involve lab. The main component of this project is computational software called Gaussian. Gaussian helps analyze chemical bounds of a compound. This program will be able to help me past this project. I will be able to analyze angles and vibrational movement for any compounds that need analyzing in the future. There will also be vibrational spectroscopy techniques that I might apply with my future job. I hope this UGRI project helps build laboratory skills that will help turn me into a better researcher.

In order to differentiate between the four fluoroquinolones, I will be using vibrational spectroscopy. Vibrational spectroscopy includes the usage of Raman and IR. The spectras produced from the data will show where the drug vibrates at different wavelengths. Each peak on the spectra corresponds with a vibrational movement of the atom. By looking at these peaks of the four fluoroquinolones, I will be able to make a differentiation. Gaussian, the computing software described above, will also help me with this analysis. Gaussian will help with the analysis of peaks and being able to distinguish where each compounds moves at an exact wavelength. Using vibrational spectroscopy and computational software, I will be able to make a clear distinction between the four fluoroquinolones.