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:

Slides:



Advertisements
Similar presentations
Instrumental Analysis
Advertisements

Calibration methods Chemistry 243.
Design of Experiments Lecture I
MWF 11:30-12:20, Rm 108, College of Business Administration
Errors in Chemical Analyses: Assessing the Quality of Results
CHEMISTRY ANALYTICAL CHEMISTRY Fall
Selectivity, Sensitivity, Signal to Noise, Detection Limit
Calibration Methods Introduction
Chapter 1 Introduction Analytical Chemistry deals with methods for determining the chemical composition of samples. Qualitative Analysis (identification)
Chemical Analysis Qualitative Analysis Quantitative Analysis Determination “Analyze” a paint sample for lead “Determine” lead in a paint sample.
World Health Organization
Quality Control Procedures put into place to monitor the performance of a laboratory test with regard to accuracy and precision.
Biomedical Tracers Biology 685 University of Massachusetts at Boston created by Kenneth L. Campbell, PhD.
Quality Assurance.
Chem. 133 – 1/27 Lecture. Introduction - Instructor: Roy Dixon Educational Background in Analytical Chemistry and Environmental Chemistry Most of my research.
Instrumental Chemistry Chapter 1 Introduction. Classical Methods Early years of chemistry  Separation of analytes by precipitation, extraction, or distillation.
CHEM-3245 Quantitative Analysis
Chemometrics Method comparison
Method Comparison A method comparison is done when: A lab is considering performing an assay they have not performed previously or Performing an assay.
Statistics Introduction 1.)All measurements contain random error  results always have some uncertainty 2.)Uncertainty are used to determine if two or.
Lecture 1 INTRODUCTION TO INSTRUMENTAL ANALYSIS Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display.
Quality Assurance.
Instrumental Analysis
CH915: Elemental Analysis
Handling Data and Figures of Merit Data comes in different formats time Histograms Lists But…. Can contain the same information about quality What is meant.
1 Spectroscopic Analysis Part 1 – Introduction Chulalongkorn University, Bangkok, Thailand January 2012 Dr Ron Beckett Water Studies Centre School of Chemistry.
The following minimum specified ranges should be considered: Drug substance or a finished (drug) product 80 to 120 % of the test concentration Content.
Analytical chemistry MLAB 243 Level 4 Lecture time: every WED 8 -10
Introduction to Analytical Chemistry Dr M. Abd-Elhakeem Faculty of Biotechnology General Chemistry Lecture 7.
Version 2012 Updated on Copyright © All rights reserved Dong-Sun Lee, Prof., Ph.D. Chemistry, Seoul Women’s University Chapter 5 Errors in Chemical.
LECTURER PROF.Dr. DEMIR BAYKA AUTOMOTIVE ENGINEERING LABORATORY I.
Chapter 5 Errors In Chemical Analyses Mean, arithmetic mean, and average (x) are synonyms for the quantity obtained by dividing the sum of replicate measurements.
Quality Control Lecture 5
Introduction: Matter & Measurement AP Chemistry Chapter 1 (Day 2)
Syllabus for CHEM 3281 Fall Semester, 2003 Faculty:Dr. Richard F. Browner Boggs Chemistry & Biochemistry, Rm. B-20 (404)
Instrumental Analysis Instructors: Upali Siriwardane, CTH 311, Phone: ) Frank Ji, CTH 343/IfM 218, Phone: /5125 Dale L. Snow, Office:
Budi Hastuti, S.Pd., M.Si.. INTRODUCTION  Two step analysis: 1. Identify  Qualitative Analysis 2. Estimation  Quantitative Analysis Method  Classical.
Students should be able to: 1. Define and differentiate the following terms: Qualitative analysis, Quantitative analysis & Analytes. 2. Define the role.
Quality Assurance How do you know your results are correct? How confident are you?
Lecture 3 Mechanical Measurement and Instrumentation MECN 4600 Department of Mechanical Engineering Inter American University of Puerto Rico Bayamon Campus.
Data Analysis: Quantitative Statements about Instrument and Method Performance.
Principles of Instrumental Analysis
Module 1: Measurements & Error Analysis Measurement usually takes one of the following forms especially in industries: Physical dimension of an object.
RESEARCH & DATA ANALYSIS
Validation Defination Establishing documentary evidence which provides a high degree of assurance that specification process will consistently produce.
Quality Control: Analysis Of Data Pawan Angra MS Division of Laboratory Systems Public Health Practice Program Office Centers for Disease Control and.
BME 353 – BIOMEDICAL MEASUREMENTS AND INSTRUMENTATION MEASUREMENT PRINCIPLES.
ERT 207 Analytical Chemistry ERT 207 ANALYTICAL CHEMISTRY Dr. Saleha Shamsudin.
Chapter 1: Introduction Analytical Chemistry Analytical Chemistry Qualitative analysis Qualitative analysis Quantitative analysis Quantitative analysis.
Chapter 1: Introduction 1. Type of instrumental methods Radiation Electrical method Thermal properties Others 2. Instruments for analysis Non-electrical.
Quality Control Internal QC External QC. -Monitors a test's method precision and analytical bias. -Preparation of quality control samples and their interpretation.
Lecture 8 Peak Parameters and Quantitative chromatography
Chapter 6: Random Errors in Chemical Analysis. 6A The nature of random errors Random, or indeterminate, errors can never be totally eliminated and are.
Chapter 5: Errors in Chemical Analysis. Errors are caused by faulty calibrations or standardizations or by random variations and uncertainties in results.
Chapter 1: The Nature of Analytical Chemistry
SEMINAR ON PRESENTED BY BRAHMABHATT BANSARI K. M. PHARM PART DEPARTMENT OF PHARMACEUTICS AND PHARMACEUTICAL TECHNOLGY L. M. COLLEGE OF PHARMACY.
1 Analytical Chemistry II Somsak Sirichai Lectures: Tuesday p.m. Friday a.m. C
Volumetric and Gravimetric analysis
ANALYTICAL CHEMISTRY deals with methods for determining the chemical composition of samples. Dr Seemal Jelani ENVR-303 6/16/2018.
Instrumental Chemistry
Practical clinical chemistry
Analytical Method Validation
Introduction to Instrumentation Engineering
Choice of Methods and Instruments
Introduction To Medical Technology
Satish Pradhan Dnyanasadhana College, Thane. Department of Chemistry S
Volumetric and Gravimetric analysis
Introduction to Analytical Chemistry
Quality Assessment The goal of laboratory analysis is to provide the accurate, reliable and timeliness result Quality assurance The overall program that.
Measurements & Error Analysis
Presentation transcript:

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 HaH721 HaH Phone: web page: Office Hours: 10:30-11:30 am MWF or by Special Appointment. Required Items: (i) CHEM 821 is a prerequisite (ii)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)

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.

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!!!! 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.

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

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

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.

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

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?

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 –  ) Relative Error (%) = 100(X –  )/  where: X = The experimental result  = The true result

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.

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)

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. Low accuracy, low precision Low accuracy, high precision High accuracy, low precision High accuracy, high precision Illustrating the difference between “accuracy” and “precision”

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 X i = measurement made for the ith trial = mean result for the data sample

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.

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 + S bl where: m = slope or calibration sensitivity b – Intercept or S bl – instrument signal for blank x – Independent variable or c – analyte concentration y – Dependent variable or S – measured signal

CHARACTERISTICS OF ANALYTICAL METHODS Ways to Measure Sensitivity: Analytical Sensitivity (  ): 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  = m/SD where:  = 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

CHARACTERISTICS OF ANALYTICAL METHODS Example: calibration curve for determination of lead S = 1.12c pb Ten replicate measurements for a 1.00 and 10.0 ppm Pb samples yielded 1.12 ± and ± 0.15, respectively. calibration sensitivity = m = 1.12 analytical sensitivity = m/SD  = 1.12/0.025 = 45 at 1.00 ppm  = 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

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

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 Species A Species B No method is totally free from interference from other species. Selectivity coefficient (k): k B,A = m B /m A Relative slopes of calibration curves indicate selectivity: S = m A (c A + k B,A c b ) + S bl Interested in detecting species A, but signal will be a combination of signal from the presence of species A and species B. CHARACTERISTICS OF ANALYTICAL METHODS

Limits of Detection (c m ): 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? ?

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 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 S/N = 3

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 Signal (S) Concentration (c) Use best-fit line to determine the amount of analyte (c) that will give a minimum signal (S m ) that is equal to the signal at the intercept plus three or two times the standard deviation (s bl ) of the intercept’s value (i.e., S/N = 2 or 3) S m = + 3s bl c m = (minimum analyte signal (S m ) - mean blank signal( ))/slope(m)

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 linear change 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

CHARACTERISTICS OF ANALYTICAL METHODS Ways to Characterize a Calibration Curve: Dynamic range: The range of x values that produces any change 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

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 Find the glucose concentration and its standard deviation, calibration sensitivity, detection limit and dynamic range. Glucose Concentration, mM Absorbance, A

CHARACTERISTICS OF ANALYTICAL METHODS Learning Objectives: 1.The student should be familiar with the general definition of “Analytical Chemistry” and some examples of the application of this field. 2.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 3.The student should be able to define and describe various terms used in the characterization of analytical methods, including: AccuracyPrecisionSensitivity Limits of Detection ErrorResponseSelectivityCalibration Curves 4.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 DetectionUpper Limit of Detection Calibration Sensitivity Analytical SensitivitySignal-to-Noise Ratio Linear Range Dynamic Range 5.The student should know how to use the above procedures and parameters in the characterization of results from analytical methods