Modern analytical techniques used to characterize organic compounds. Birbhum Pharmacy School.

Modern analytical techniques used to characterize organic compounds. Birbhum Pharmacy School.

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  BACHELOR OF PHARMACY Presentedby AYAN HOSSAIN B. Pharm (4th Year, Semester : 8th) Project Work (PT-833) Registration No. 213530201910009 OF 2021-2022 University Roll No. 35301921002 UNDER THE SUPERVISION & GUIDANCE OF PROJECT SUPERVISOR MRS. SUSMITA DHAR ASSOCIATE PROFESSOR DEPARTMENT OF PHARMACEUTICAL CHEMISTRY PROJECT CO-SUPERVISOR MR. SOUVIK BHANDARY ASSISTANT PROFESSOR DEPARTMENT OF PHARMACEUTICAL CHEMISTRY MODERN ANALYTICAL TECHNIQUE FOR CHARACTERIZATION OF ORGANIC COMPOUNDS
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  CONTENT SL NO TOPICPAGE NO 1. Introduction to Modern Analytical Techniques 1 2. Liquid Chromatography (LC) 2 3. Gas Chromatography(GC) 3 4. Nuclear Magnetic Resonance (NMR) Spectroscopy 4 5. Infrared (IR) Spectroscopy 5 6. Mass Spectrometry(MS) 6 7. UV-Visible Spectroscopy 7 8. X-ray Crystallography 8 9. Applications of Modern Analytical Techniques 9 10. Conclusion and Future Trends 10
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  1 Introduction to ModernAnalytical Techniques • Analytical techniques are essential for the characterization of organic compounds. • These methods provide detailed information about molecular structure, composition, and purity. • Advances in technology have significantly enhanced the sensitivity and accuracy of these techniques.
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  2 Liquid Chromatography (LC) •Liquid chromatography separates compounds based on their interactions with a stationary phase. • This technique is highly effective for analyzing complex mixtures of organic compounds. • High-Performance Liquid Chromatography (HPLC) is a widely used form of LC that offers improved resolution.
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  3 Gas Chromatography (GC) •Gas chromatography is utilized for the separation and analysis of volatile organic compounds. • It operates by vaporizing the sample and passing it through a column with an inert carrier gas. • Coupled with mass spectrometry (GC-MS), it provides both qualitative and quantitative data.
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  4 Nuclear Magnetic Resonance(NMR) Spectroscopy • NMR spectroscopy is a powerful technique for determining the structure of organic molecules. • It provides information about the number and type of atoms in a compound, as well as their environment. • Advances in NMR technology allow for the analysis of smaller samples with greater resolution.
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  5 Infrared (IR) Spectroscopy •Infrared spectroscopy is used to identify functional groups in organic compounds. • It measures the absorption of infrared light, resulting in a characteristic spectrum for each compound. • Modern FTIR (Fourier Transform Infrared) spectrometers enhance sensitivity and speed of analysis.
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  6 Mass Spectrometry (MS) •Mass spectrometry is a technique for determining the mass-to-charge ratio of ions. • It provides information about the molecular weight of organic compounds. • Coupling MS with other techniques, such as GC or LC, enhances analytical capabilities.
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  7 Ultraviolet-Visible (UV-Vis) Spectroscopy •UV-Vis spectroscopy measures the absorption of ultraviolet or visible light by organic compounds. • It is particularly useful for analyzing conjugated systems and determining concentrations. • Modern UV-Vis spectrophotometers offer high precision and are user-friendly.
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  8 X-ray Crystallography • X-raycrystallography is a definitive technique for determining the three-dimensional structure of organic compounds. • It involves analyzing the diffraction patterns produced when X-rays are directed at crystalline samples. • This technique is crucial for understanding molecular interactions and solid-state properties.
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  9 Applications of ModernAnalytical Techniques • Structure determination • Functional group identification • Molecular weight determination • Purity testing • Elemental composition analysis
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  10 Conclusion and FutureTrends • Modern analytical techniques play a vital role in the characterization of organic compounds. • Continuous technological advancements promise improved accuracy, sensitivity, and efficiency. • Future trends may include the integration of AI and machine learning for data analysis and interpretation.