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PROBLEMS IN ANALYTICAL CHEMISTRY CHEM 824, Spring 2015 MWF 9:30-10:20, Rm 130, Hamilton Hall

PROBLEMS IN ANALYTICAL CHEMISTRY CHEM 824, Spring 2015 MWF 9:30-10:20, Rm 130, Hamilton Hall COURSE OUTLINE Instructor: Dr. Robert Powers Office Labs Address: 722 HaH 721 HaH Phone: 472-3039 472-5316 e-mail:rpowers3@unl.edu web page: http://bionmr.unl.edu/

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PROBLEMS IN ANALYTICAL CHEMISTRY CHEM 824, Spring 2015 MWF 9:30-10:20, Rm 130, Hamilton Hall

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  1. PROBLEMS IN ANALYTICAL CHEMISTRY • CHEM 824, Spring 2015 • MWF 9:30-10:20, Rm 130, Hamilton Hall • COURSE OUTLINE • Instructor: Dr. Robert Powers • OfficeLabs • Address: 722 HaH 721 HaH • Phone: 472-3039 472-5316 • e-mail:rpowers3@unl.edu • web page: http://bionmr.unl.edu/ • Office Hours: 10:30-11:30 am MWF or by Special Appointment. • Required Items: • (i) CHEM 821 is a prerequisite • Text: No official text, but some recommendations are: • “Principles of Instrumental Analysis" by D. A. Skoog, J. F. Holler and T. A. Nieman • "Instrumental Analysis" by G. D. Christian and J. E. O'Reilly • “Analytical Chemistry and Quantitative Analysis” by D. S. Hage and J. D. Carr • (iii) Calculator for exams (TI-89 style or a simpler model)

  2. Course Outlined (cont.) Course Work: Exam 1: 100 pts. (Tues., Sept. 22) Exam 2: 100 pts. (Fri., Oct. 16) Exam 3: 100 pts. (Wed., Nov. 18) Final: 100 pts. (10-12, Tues., Dec. 15) Problem Sets: 150 pts. (various due dates) Total: 550 pts. The due dates for problem sets will be announced when the problem sets are handed out. ALL PowerPoint presentations, and answer keys for the problem sets and exams will be posted on BlackBoard. Grading scale: A+=95%; A=90%; A-=85%; B+=80%; B=75%; B-=70%; C+=65%; C=60%; C-=55%; D=50%; D-=45%; F=40% As an 800 level course, a final grade of “C” or greater is needed for this class to count towards a graduate degree.

  3. Course Outlined (cont.) • Class Participation • Reading assignments should be completed prior to each lecture. • You are expected to participate in ALL classroom discussions • Exams • All exams (except the final) will take place at 6 pm in Rm 130, Hamilton Hall on the scheduled date. • The length of each exam will be open-ended. You will have as much time as needed to complete the exam. • Bring TI-89 style calculator or a simpler model, approved translator and text book (you will be able to use certain charts, tables and appendix) • A review session will take place during the normal class time. • ALWAYS SHOW ALL WORK!!!!

  4. Course Outlined (cont.) • Problem Sets • ~11 Problem sets are worth between 5 to 20 points each for a total of ~150 points • You may work together in groups, but everyone must submit their own set of answers to the problem set. • Please feel free to visit me during office hours for assistance in answering the problem sets. • You must show all work to receive full credit. • Due dates will be announced when problem sets are distributed. • Problem sets are due at the beginning of class on the due dates. • Late Problem sets will not be accepted.

  5. Lecture Topics • Date Lecturer Topic • I. Introduction to Analytical Chemistry • Aug 24 Powers Basic Principles of Chemical Analysis Aug 26 “ Data Handling & Statistical Methods • Aug 28 “ • II. Elemental Analysis • a. Classical Methods • Aug 31 Powers Combustion/Classic Screening Methods • Sep 2 “ Titrations/Gravimetry/Colorimetry • b. Electrochemical methods • Sep 4 Powers Overview of Electrochemical Methods • Sep 9 “ • Sep 10 (9:30 am) “ Potentiometry/Polarography • Sep 14 “ Voltammetry/Coulometry • c. Spectroscopic Methods • Sep 16 Morin Atomic Spectroscopy • Sep 18 “ • Sep 22 (6:00 pm)EXAM 1 (Tues) • Sep 23 Morin X-Ray Analytical Methods • Sep 25 “ • III. Structure & Molecular Weight Determination • a. Mass Spectrometry • Sep 28 Dodds Overview of Mass Spectrometry • Sep 30Dodds Ionization & Analyzers • Oct 2 “ • Oct 5Cerny Molecular Weight Measurements • Oct 7 Cerny Structure Determination • Oct 9 Cerny Tour of mass spec facility • b. Infrared/Raman Spectroscopy • Oct 12 Powers Overview of Infrared Spectroscopy • Oct 14 Powers Overview of Raman Spectroscopy • Oct 16 (6:00 pm)EXAM 2 (Fri)

  6. Lecture Topics • Date Lecturer Topic • c. Nuclear Magnetic Resonance • Oct 21 Morton Overview of NMR • Oct 32 Powers • Oct 26 “ • Oct 28 “ • Oct 30 “ • Nov 2 Morton Tour of NMR facility • IV. Compound Isolation & Separation • a. Chromatography • Nov 4 Hage Overview of Chromatography • Nov 6 “ Gas Chromatography • Nov 9 “ • Nov 11 “ Liquid Chromatography • Nov 13 “ • Nov 16 Morton Tour of Research Instrument Facility • Nov 18 (6:00 pm)EXAM 3 (Wed.) • Nov 20 Snow LC/MS & Environmental Analysis • V. Analysis of Mixtures & Special Topics • Nov 23 HageHyphenated Techniques • Nov 30 Cerny • Dec 2 Powers Immunoassays • Dec 4 Lai Biosensors • Dec 7 (6:00 pm)SinitskiScanning Electron Microscopy • Dec 9 Cheung Scanning Electron Microscopy • Dec 11 Powers Course Evaluation & Review • Dec 15 (10: 00 am)Final Exam (Tues.)

  7. Introduction to Analytical Chemistry Background A.) ANALYTICAL CHEMISTRY: The Science of Chemical Measurements. B.) ANALYTE: The compound or chemical species to be measured, separated or studied C.) TYPES of ANALYTICAL METHODS: 1.) Classical Methods (Earliest Techniques) a.) Separations: precipitation, extraction, distillation b.) Qualitative: boiling points, melting points, refractive index, color, odor, solubilities c.) Quantitative: titrations, gravimetric analysis 2.) Instrumental Methods (~post-1930’s) a.) separations: chromatography, electrophoresis, etc. b.) Qualitative or Quantitative: spectroscopy, electrochemical methods, mass spectrometry, NMR, radiochemical methods, etc.

  8. Introduction to Analytical Chemistry Application Examples 1.) Determination of Physiochemical Properties a.) Electromagnetic properties b.) Solubility, Viscosity, etc. c.) Reaction Rates d.) Equilibrium Constants 2.) Determination of Compound Structure a.) Elemental Composition b.) Functional Group Analysis c.) Structure Determination 3.) Separation of Compounds a.) Solute Purification b.) Mixture Analysis 4.) Analysis and Quantitation of Samples a.) Quantitative Analysis b.) Qualitative Analysis

  9. Choosing an Analytical Method Defining the Experimental Problem (what factors to consider): 1.) Questions regarding the type of information desired: a.) Compound structure (elemental composition, 3D structure, etc.) b.) Physiochemical properties (mass, solubility, etc.) c.) Purity, amount, stability, reactivity, etc. d.) What compounds are present? 2.) Questons regarding the nature of the sample: a.) How much or how little sample is required? b.) How much or how little analyte can be detected? c.) What types of samples can the method be used with? d.) Will other components of the sample cause interference? 3.) Questions regarding the analytical method to be used: a.) What type of information does the method provide? b.) What are the advantages or disadvantages of the technique versus other methods? c.) How reproducible and accurate is the technique? d.) Other factors: speed, convenience, cost, availability, skill required. How Do We Answer or Address These Questions?

  10. CHARACTERISTICS OF ANALYTICAL METHODS Accuracy: The degree to which an experimental result approaches the true or accepted answer. Ways to Describe Accuracy: Error: An experimental measure of accuracy. The difference between the result obtained by a method and the true or accepted value. Absolute Error = (X – m) Relative Error (%) = 100(X – m)/m where: X = The experimental result m = The true result

  11. CHARACTERISTICS OF ANALYTICAL METHODS Accuracy: The degree to which an experimental result approaches the true or accepted answer. Ways of Measuring Accuracy: All Methods, except counting, contain errors – don’t know “true” value Two types of error: random or systematic With multiple measurements (replicates), we can then apply simple statistics to estimate how close the measured values would be to the true value if there was no systematic error in the system. 

  12. CHARACTERISTICS OF ANALYTICAL METHODS Random Error: results in a scatter of results centered on the true value for repeated measurements on a single sample. Systematic Error: results in all measurements exhibiting a definite difference from the true value Random Error Systematic Error plot of the number of occurrences or population of each measurement (Gaussian curve)

  13. CHARACTERISTICS OF ANALYTICAL METHODS Precision: The reproducibility of results. The degree to which an experimental result varies from one determination to the next. Precision is related to random error and Accuracy is related to systematic error. Illustrating the difference between “accuracy” and “precision” Low accuracy, high precision Low accuracy, low precision High accuracy, low precision High accuracy, high precision

  14. CHARACTERISTICS OF ANALYTICAL METHODS Ways to Describe Precision: Range: a list of the high to low values measured in a series of experiments. Standard Deviation: describes the distribution of the measured results about the mean or average value. Absolute Standard Deviation (SD): Relative Standard Deviation (RSD) or Coefficient of Variation (CV): where: n = total number of measurements Xi = measurement made for the ith trial = mean result for the data sample

  15. CHARACTERISTICS OF ANALYTICAL METHODS Response: The way in which the result or signal of a method varies with the amount of compound or property being measured. Ways to Describe Response: Calibration Curve: A plot of the result or signal vs. the known amount of a known compound or property (standard) being measured.

  16. CHARACTERISTICS OF ANALYTICAL METHODS Sensitivity:The change in the response of the calibration curve at a given property or amount of compound; a measure of the smallest change in the amount or property that can be detected Ways to Measure Sensitivity: Calibration Sensitivity: The slope of the calibration curve at a given value of the independent variable (x) Example – for a linear curve: y = mx + b or S = mc + Sbl where: m = slope or calibration sensitivity b – Intercept or Sbl – instrument signal for blank x – Independent variable or c – analyte concentration y – Dependent variable or S – measured signal

  17. CHARACTERISTICS OF ANALYTICAL METHODS Ways to Measure Sensitivity: Analytical Sensitivity (g): The calibration sensitivity (slope) at a given value for the independent variable (x) divided by the standard deviation of the signal obtained at the same x value g = m/SD where: g = Analytical sensitivity m = Slope at given analyte level or property SD = Standard deviation of the response at the given property or level for the analyte

  18. CHARACTERISTICS OF ANALYTICAL METHODS Example: calibration curve for determination of lead S = 1.12cpb + 0.312. Ten replicate measurements for a 1.00 and 10.0 ppm Pb samples yielded 1.12 ± 0.025 and 11.62 ± 0.15, respectively. calibration sensitivity = m = 1.12 analytical sensitivity = m/SD g = 1.12/0.025 = 45 at 1.00 ppm g = 1.12/0.15 = 7.5 at 10.0 ppm Analytical sensitivity is typically concentration dependent – reason why not commonly reported But, analytical sensitivity independent of amplification factors or measurement units

  19. CHARACTERISTICS OF ANALYTICAL METHODS Which Method has a higher sensitivity? Method A Method B

  20. CHARACTERISTICS OF ANALYTICAL METHODS Selectivity: The ability of a method to measure the analyte of interest vs. its ability to measure other compounds. The degree to which the method is free from interference by other species in the sample No method is totally free from interference from other species. Selectivity coefficient (k): kB,A = mB/mA Relative slopes of calibration curves indicate selectivity: S = mA(cA + kB,Acb) + Sbl Species A Species B Interested in detecting species A, but signal will be a combination of signal from the presence of species A and species B.

  21. CHARACTERISTICS OF ANALYTICAL METHODS Limits of Detection (cm ): The lowest (or highest) value of x that can be reliably determined by an analytical method. Lower Limit of Detection: The minimum value of the independent variable (x) that can be reliably determined. Upper Limit of Detection: The maximum value of the independent variable (x) that can be reliably determined. ? Which are the real peaks?

  22. CHARACTERISTICS OF ANALYTICAL METHODS Ways to Measure Limit of Detection: Signal-to-noise Ratio (S/N): Noise: random variation in signal or background that is associated with the response of a method Signal: net response recorded by a method for a sample Signal-to-Noise Ratio: The ratio of the response produced by a sample divided by the noise level S/N = 3 Note: a value of S/N = 2 or 3 is considered to be the minimum ratio needed for the reliable detection of a true signal from a sample Signal Noise

  23. CHARACTERISTICS OF ANALYTICAL METHODS Ways to Estimating Signal-to-Noise Ratios: 1.) Multiple determination of blank samples and samples containing analyte levels or properties approaching the detection limit 2.) Estimation from best-fit lines to calibration curves cm = (minimum analyte signal(Sm) - mean blank signal( ))/slope(m) Use best-fit line to determine the amount of analyte (c) that will give a minimum signal (Sm) that is equal to the signal at the intercept plus three or two times the standard deviation (sbl) of the intercept’s value (i.e., S/N = 2 or 3) Signal (S) Sm = + 3sbl Concentration (c)

  24. CHARACTERISTICS OF ANALYTICAL METHODS Ways to Characterize a Calibration Curve: Assay range: The range of analyte levels or properties over which the method gives a reliable response Linear range: The range of x values that produces a linearchange in the response Found by determining what range gives a response that falls within ± 5% (or some other fixed value) of that predicted by a best-fit line through the data Linear range

  25. CHARACTERISTICS OF ANALYTICAL METHODS Ways to Characterize a Calibration Curve: Dynamic range: The range of x values that produces anychange in the response Found by determining the upper and lower limits of the detection for the assay. The dynamic range always includes the linear range Additional analyte does not result in an increase in response

  26. Example: The data in the table below were obtained during a colorimetric determination of glucose in blood serum. A serum sample gave an absorbance of 0.350. Find the glucose concentration and its standard deviation, calibration sensitivity, detection limit and dynamic range.

  27. CHARACTERISTICS OF ANALYTICAL METHODS • Learning Objectives: • The student should be familiar with the general definition of “Analytical Chemistry” and some examples of the application of this field. • The student should be able to discuss various questions and items that need to be considered in the design, selection, and comparison of analytical methods • The student should be able to define and describe various terms used in the characterization of analytical methods, including: • Accuracy Precision Sensitivity Limits of Detection • Error Response Selectivity Calibration Curves • The student should be familiar with common formulas and parameters used in • quantitating the above properties of analytical methods, including: • Absolute Error Relative Error Standard Deviation • Relative Standard Deviation Range Coefficient of Variation • Lower Limit of Detection Upper Limit of Detection Calibration Sensitivity • Analytical Sensitivity Signal-to-Noise Ratio Linear Range • Dynamic Range • The student should know how to use the above procedures and parameters in the characterization of results from analytical methods

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