# Development and Optimization of a SPME-GC-FID Method for Ethanol Detection
## 4 Conclusions  
Based on the parameters investigated, it is possible to infer that ethanol detection through SPME-GC-FID was optimized by careful control of the extraction conditions (fiber selection, temperature and time of extraction, and salt addition). The fiber coating was a crucial element to consider because it influenced the extraction's selectivity and sensitivity. Furthermore, the temperature and duration of extraction were crucial criteria that affected the extraction process's efficiency. The salt concentration improved extraction efficiency by changing the solubility of the target analyte in the sample matrix. As such, optimizing these parameters resulted in a more accurate and reliable detection of ethanol in varied matrices. Overall, this work emphasizes the necessity of knowing the influence of various factors on the performance of SPME/GC-FID for ethanol detection and gives useful insights for future research in this sector. A technique for quantifying ethanol in aqueous samples using gas chromatography was developed and verified. To replicate the ethanol content in human fluids for forensic analysis using the SPME/GC-FID technology, tests using an artificial sweat matrix and a PBS matrix were undertaken. The improved SPME/GC-FID technique for ethanol detection was shown to have lower LOQ values in aqueous samples compared to PBS and sweat samples, presumably due to sample matrix composition variations. The approach was accurate for aqueous samples but less so for the PBS and sweat samples, indicating that additional improvements are required for assessing biological materials. Nonetheless, all the LOQ values produced were within acceptable limits, demonstrating that the approach is sensitive enough for a variety of applications. Our study sets the stage for further research, providing a foundation for improved methodologies in ethanol detection. It is important to recognize the dynamic nature of this field and the need for iterative improvements to meet the diverse challenges posed by different sample matrices, offering valuable insights for researchers in biochemistry and forensics. The method, while accurate for water samples, may require additional improvements for assessing biological materials like sweat and PBS, as indicated by the variation in LOQ values. Therefore, future studies should include a more in-depth investigation into the method's performance across a broader range of matrices, especially those relevant to clinical and forensic applications, which would enhance the study's applicability, considering the complexities of different sample matrices. This would involve a comprehensive investigation into the impact of matrix components on the method's performance. Additionally, conducting comparative studies with alternative methodologies or existing techniques for ethanol detection mentioned before would provide valuable insights into the strengths and weaknesses of different approaches, which could contribute to establishing the method's superiority in specific applications. It is noteworthy that this methodology has some limitations, such as: matrix dependency: the method's performance may be influenced by variations in sample matrices, such as water, phosphate-buffered saline (PBS), and artificial sweat; sample complexity: the presence of interfering compounds in biological samples may affect the method's performance; temperature and extraction time sensitivity: while the lower temperature and shorter extraction time are advantageous, they may compromise sensitivity and precision, particularly in matrices with diverse compositions. The decision to extend the analysis time was driven by considerations of energy efficiency and the necessity for a gradual temperature decrease during the cleaning process of the fiber. In complex matrices, it is crucial to ensure thorough fiber cleaning to prevent contaminations in subsequent readings and mitigate the risk of yielding false results.