Explanation of Data Reported by Microtrac Instruments

Similar documents
Descriptive Statistics

Descriptive Statistics. Purpose of descriptive statistics Frequency distributions Measures of central tendency Measures of dispersion

MBA 611 STATISTICS AND QUANTITATIVE METHODS

Week 1. Exploratory Data Analysis

Measures of Central Tendency and Variability: Summarizing your Data for Others

Chapter 1: Looking at Data Section 1.1: Displaying Distributions with Graphs

SECTION 2-1: OVERVIEW SECTION 2-2: FREQUENCY DISTRIBUTIONS

1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number

Universitätsstrasse 1, D Düsseldorf, Germany 3 Current address: Institut für Festkörperforschung,

Statistics. Measurement. Scales of Measurement 7/18/2012

The right edge of the box is the third quartile, Q 3, which is the median of the data values above the median. Maximum Median

Exercise 1.12 (Pg )

GRADISTAT: A GRAIN SIZE DISTRIBUTION AND STATISTICS PACKAGE FOR THE ANALYSIS OF UNCONSOLIDATED SEDIMENTS

Frequency Distributions

SKEWNESS. Measure of Dispersion tells us about the variation of the data set. Skewness tells us about the direction of variation of the data set.

Data exploration with Microsoft Excel: univariate analysis

FREE FALL. Introduction. Reference Young and Freedman, University Physics, 12 th Edition: Chapter 2, section 2.5

CAMI Education linked to CAPS: Mathematics

Data analysis and regression in Stata

MEASURES OF VARIATION

Directions for Frequency Tables, Histograms, and Frequency Bar Charts

Scatter Plots with Error Bars

A Picture Really Is Worth a Thousand Words

Perthometer. Surface Texture Parameters New Standards DIN EN ISO / ASME

In mathematics, there are four attainment targets: using and applying mathematics; number and algebra; shape, space and measures, and handling data.

Exploratory Data Analysis. Psychology 3256

6 3 The Standard Normal Distribution

Imaging Systems Laboratory II. Laboratory 4: Basic Lens Design in OSLO April 2 & 4, 2002

UNDER DRAINAGE AND FILTER DESIGN

DESCRIPTIVE STATISTICS AND EXPLORATORY DATA ANALYSIS

CA200 Quantitative Analysis for Business Decisions. File name: CA200_Section_04A_StatisticsIntroduction

Module 4: Data Exploration

Pie Charts. proportion of ice-cream flavors sold annually by a given brand. AMS-5: Statistics. Cherry. Cherry. Blueberry. Blueberry. Apple.

Data Exploration Data Visualization

Cabri Geometry Application User Guide

Lesson 4 Measures of Central Tendency

Scientific Graphing in Excel 2010

DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses.

Probability and Statistics Prof. Dr. Somesh Kumar Department of Mathematics Indian Institute of Technology, Kharagpur

HowTo Rhino & ICEM. 1) New file setup: choose Millimeter (automatically converts to Meters if imported to ICEM)

Algebra Academic Content Standards Grade Eight and Grade Nine Ohio. Grade Eight. Number, Number Sense and Operations Standard

CHAPTER THREE. Key Concepts

GeoGebra Statistics and Probability

seven Statistical Analysis with Excel chapter OVERVIEW CHAPTER

Electrical Resonance

Pre-Algebra Academic Content Standards Grade Eight Ohio. Number, Number Sense and Operations Standard. Number and Number Systems

business statistics using Excel OXFORD UNIVERSITY PRESS Glyn Davis & Branko Pecar

ModuMath Basic Math Basic Math Naming Whole Numbers Basic Math The Number Line Basic Math Addition of Whole Numbers, Part I

Datum > Curve KIM,ME,NIU

Algebra 1 Course Title

Describing Data: Measures of Central Tendency and Dispersion

McDougal Littell California:

Data Analysis. Using Excel. Jeffrey L. Rummel. BBA Seminar. Data in Excel. Excel Calculations of Descriptive Statistics. Single Variable Graphs

MATHS LEVEL DESCRIPTORS

Introduction to Quantitative Methods

Chapter 3. The Normal Distribution

Using Excel (Microsoft Office 2007 Version) for Graphical Analysis of Data

Summarizing and Displaying Categorical Data

GeoGebra. 10 lessons. Gerrit Stols

Exploratory data analysis (Chapter 2) Fall 2011

Engineering Problem Solving and Excel. EGN 1006 Introduction to Engineering

DESCRIPTIVE STATISTICS & DATA PRESENTATION*

DYNAMIC LIGHT SCATTERING COMMON TERMS DEFINED

Variables. Exploratory Data Analysis

Geometric Optics Converging Lenses and Mirrors Physics Lab IV

MATH BOOK OF PROBLEMS SERIES. New from Pearson Custom Publishing!

Evaluating System Suitability CE, GC, LC and A/D ChemStation Revisions: A.03.0x- A.08.0x

Probability and Statistics Vocabulary List (Definitions for Middle School Teachers)

Name Class. Date Section. Test Form A Chapter 11. Chapter 11 Test Bank 155

STATS8: Introduction to Biostatistics. Data Exploration. Babak Shahbaba Department of Statistics, UCI

1.3 Measuring Center & Spread, The Five Number Summary & Boxplots. Describing Quantitative Data with Numbers

Introduction to COMSOL. The Navier-Stokes Equations

Generating ABI PRISM 7700 Standard Curve Plots in a Spreadsheet Program

Copyright 2011 Casa Software Ltd. Centre of Mass

Data exploration with Microsoft Excel: analysing more than one variable

Descriptive statistics Statistical inference statistical inference, statistical induction and inferential statistics

AP STATISTICS REVIEW (YMS Chapters 1-8)

Investment Statistics: Definitions & Formulas

Skewness and Kurtosis in Function of Selection of Network Traffic Distribution

Expression. Variable Equation Polynomial Monomial Add. Area. Volume Surface Space Length Width. Probability. Chance Random Likely Possibility Odds

XI / PHYSICS FLUIDS IN MOTION 11/PA

determining relationships among the explanatory variables, and

Petrel TIPS&TRICKS from SCM

CHAPTER 2 HYDRAULICS OF SEWERS

Biostatistics: DESCRIPTIVE STATISTICS: 2, VARIABILITY

An Introduction to Point Pattern Analysis using CrimeStat

Data Analysis Tools. Tools for Summarizing Data

Data Visualization. Prepared by Francisco Olivera, Ph.D., Srikanth Koka Department of Civil Engineering Texas A&M University February 2004

Formulas, Functions and Charts

Years after US Student to Teacher Ratio

Diffusion and Fluid Flow

Learning Module 4 - Thermal Fluid Analysis Note: LM4 is still in progress. This version contains only 3 tutorials.

Pro/ENGINEER Wildfire 4.0 Basic Design

Coins, Presidents, and Justices: Normal Distributions and z-scores

Statistics Revision Sheet Question 6 of Paper 2

What Do You Think? for Instructors

Characterization of surfaces by AFM topographical, mechanical and chemical properties

SAS Analyst for Windows Tutorial

Version 1.0. A guide to quantitative methods Almquist, Ashir & Brännström

Understand the Sketcher workbench of CATIA V5.

Transcription:

Explanation of Data Reported by Microtrac Instruments (Terminology, abbreviations and calculations shown on reports) Philip E. Plantz, PhD Applications Note SL-AN-16 Rev F Provided By: Microtrac, Inc. Particle Size Measuring Instrumentation

Microtrac data include many values that are essential to developing particle size distribution specifications and evaluating data. Each of these items is explained as well as changes to be expected. The display provides a quick look at values while actual printed reports and exported data are developed in the Reports section. For more detailed information, please refer to the User s Manual in the HELP section of Microtrac FLEX software or contact the Microtrac, Inc at 727 507 9770 in Largo, FL. PARTICLE SIZE DATA and INFORMATION Sizes The default unit for size is micrometers (microns). The sizes in this table are not customizable and are determined by the optical of the instrument. Customized sizes are selectable in the SETUP portion of the software and are displayed in Size Percent Data Percentiles Software selectable Percentile Points in microns, show the percentage of the volume (or weight if the density for all the particles is the same) that is smaller than the size indicated. Percentiles can be shown as percent larger and indicates the volume percent larger than the size shown. The 50 percent point is the median diameter or D50 and represents one type of average particle size. SL-AN-16 Rev F 2

Summary Data MV Mean diameter in microns of the volume distribution represents the center of gravity of the distribution. Mie or modified Mie calculations are used to calculate the distribution. Implementation of the equation used to calculate MV will show it to be weighted (strongly influenced) by a change in the volume amount of large particles in the distribution. It is one type of average particle size or central tendency. MI (Nanotrac only) Mean diameter of the intensity distribution. Intensity distribution is not calculated using Mie theory or Modified Mie theory. Molecular Weight (MW) A calculation to provide molecular weight (grams/mole). See equation below for details. MN Mean diameter, in microns, of the number distribution is calculated using the volume distribution data and is weighted to the smaller particles in the distribution. This type of average is related to population or counting of particles. MA Mean diameter, in microns, of the area distribution is calculated from the volume distribution. This area mean is a type average that is less weighted (also less sensitive) than the MV to changes in the amount of coarse particles in the distribution. It represents information on the distribution of surface area of the particles of the distribution. CS - Calculated surface Provided in units of M 2 /cc, the value provides an indication of the specific surface area. The CS computation assumes smooth, solid, spherical particles. It may be converted to classical units for SSA of M 2 /g by dividing thru value by the density of the particles. It should not be interchanged with BET or other adsorption methods of surface area measurement since CS does not take into effect porosity of particles, adsorption specificity or topographical characteristics of particles. SD Standard Deviation in microns, also known as the Graphic Standard Deviation (σ g ), is one measure of the width of the distribution. It is not an indication of variability for multiple measurements. Equation to calculate is: (84% - 16%)/2. SDg or Ai Often known as σ i - Inclusive Graphic Standard Deviation. Includes more than 90% of the distribution and includes tails of distributions. The SD includes only 67% of the distribution. SD g Value Terminology 0.35 Very well sorted (Very narrow) 0.35-0.5 Well sorted 0.50 0.710 Moderately well sorted 0.71 1.0 Moderately sorted 1.0 2.0 Poorly sorted 2.0 4.0 Poorly sorted > 4.0 Extremely poorly sorted (very broad) K G - Often known as SKg - Kurtosis (peakedness) of a distribution is taken from sedimentology and uses phi values for calculation. It measures the departure from normality of a curve. Peakedness refers to how sharp a peak is. Terms exist to describe the magnitude of kurtosis or how sharp the peak is. Platykurtic (from the Greek meaning fat ) describes a distribution having low kurtosis while leptokurtic (Greek meaning slim ) describes a distribution having high kurtosis. The following describes values for K G K G Value Terminology < 0.67 Very Platykurtic 0.67 0.90 Platykurtic 0.90 1.11 Mesokurtic 1.11 1.50 Leptokurtic 1.50 3.00 Very leptokurtic > 3.00 Extremely leptokurtic SL-AN-16 Rev F 3

Ski Inclusive Graphic Skewness Skewness is a measure of how asymmetrical a curve is and how it varies from a normal, bell-shaped curve. Ski includes 90% of the distribution and includes the tails of the distribution. A symmetrical curve has a Ski value of 0.00. Values of 1.00 to 0.30 show fines influencing the skew. Values of -0.30 to -1.00 show coarse particles as influencing the skew. Mz Graphic Mean provides a less coarse-particle weighted mean particle size than MV. While it includes the median value, it can provide a different and possibly better control value since both small particles and large particles are included in the calculation. Units are microns. Peaks Summary Microtrac software automatically provides information on multi-modal distributions. The Dia, vol% and width identify individual modes. Dia The 50% (D50) of each mode is calculated after determining the minimum and maximum sizes contributing to the specific peak under consideration. For two modes, each will have a separate 50%. When only one mode is present, the Dia will equal the 50% of the particle distribution. Width Indicates the width of the peak under consideration. For two modes, each will have a calculated width given in microns. When only one mode is present in the distribution, the width = 2 (SD) = 84% - 16%. Vol The calculated contribution in percent of each peak to the total volume of the distribution. RMS Residual (Root mean square) Microtrac performs calculations to provide particle size distributions. The calculation is completed when software-decided least error is attained. The RMS is presented as percent. UDEF Name and UDEF Data Microtrac software allows the user to perform special calculations to suit a customized need. Each calculation is given a name (UDEF Name) by the user. The result is presented as the data (UDF Data). Percent Passing, Percent Retained and Percent Channel Data Percentiles - Values are selectable over the range 1% to 99% in 1% increments. They are calculated and then located in the table. Use SETUP command to access selections. Tabular Data - The measuring range of the instrument is divided into fixed channel or particle sizes. Particles sizes are identified on the left column in units of microns or sieve sizes as selected by the operator. Cumulative data values are on the same line as the particle size and are read as percent smaller (passing) than. The data may also be displayed as percent larger (retained) than. For data presented as percent smaller than, volume percent-in-channel (%-CHAN) values are read as volume percent between the particle size on the same line and the line below. For data presented as percent larger than or %RETN, the volume percent between sizes is read as the amount between the size on the same line and the size above. Example: In the data display shown (percent smaller than), 24.06% of the volume is smaller than 44 microns. The percent between adjacent sizes for percent passing format is shown beside the larger size, e.g., 5.19% lies between 44.00 microns and 40.35 microns. When data are presented in the PERCENT RETAINED format, as indicated at the top of the data column, the percent between sizes would be located beside 40.35 microns Size Percent Data Operator may enter up to 100 desired particle sizes. Microtrac will calculate the associated volume percentile. Cumulative Graph A cumulative graph, with %PASSING (pass) or %RETAINED (Ret) tabular data are presented as a line graph or in 3-D as selected by the 3D button part of the GRAPH TOOLBAR. Graph may be modified by using scrolling arrows and icons located in the graph area. The values used to produce the graph are those in the tabular data identified as %Smaller or % Larger. The percent point for a specific size may be found by determining the point of intersection of the desired SL-AN-16 Rev F 4

size and the cumulative curve for any size interest and then determining the volume percent from the vertical axis on the left. See above for information on percentile calculation and display. Microtrac only presents data within the particle size range of a given model or instrument set-up. Particles larger than or smaller than the instrument measuring range are not included as part of the distribution or other data. For this reason, percent smaller or larger than data begin with 100% at the largest or smallest size measured in a sample, even though some particles may exist outside the measuring range Relative Graph (%CH) - When bar graphs are printed or displayed, midpoints of channel sizes are used. Line graphs are automatically developed by connecting the midpoints. Graphical data provide an opportunity to view the distribution at a glance. In the example data display, 5% (using the right axis) of the volume is indicated at approximately 90 microns. Best quantitative data are obtained from the numerical data in the tables. Volume percent in channel data are used to produce the graph. Sediments Optional Feature Sediments Optional Feature The optional feature is designed for those interested in soils and sediment particle size analysis. To compute the values it employs phi (Φ) values which are widely used in sediments science. Size values in Φ units are calculated from Φ = (-) log size/log 2. The sediments feature uses all data including information included that may be included beyond the normal range of Microtrac. Note that the values for Mz, Ski, Kg, Sg on the main Microtrac FLEX screen uses only Microtrac data and the values, where units are appropriate, are in microns. The data values on the sediments feature screen are in phi values. MV = ΣV i d i / ΣV i MN = Σ(V i /d i 2 ) / Σ(V i /d i 3 ) MA = ΣV i / Σ(V i / d i ) MI = ΣI i d i / ΣI i MW = ρn A (π/6)d 3 SD = (84%-16%)/2 CS = K / MA Width = 84% - 16% Where: V = Volume percent between sizes. d = Size represented by the center (geometric progression) between any 2 sizes. I = Intensity percent between sizes Ρ = Density of the particles K = Ratio of Area to Volume of sphere ρ = Specific gravity N A = Avogadro s number Lower case i refers to individual channel or bin sizes. Σ = Symbol meaning that each operation is added to the next in the series to achieve a sum of all. Mz = (16% + 50% + 84%) / 3 SDg = [(84% - 16%) / 4] + [(95% - 5%) / 6.6] Kg = (95% - 5%) / [2.44(75% - 25%)] Ski = {[16%+84%- 2(50%)] / 2(84%-16%)} + {[5% +95%- 2(50%)] / 2(95%-5%)} SL-AN-16 Rev F 5

Zetatrac Lower Right Corner of Zetatrac Data Display Zeta Potential Measurement Section Optional Information Section Optional Information Section Zeta potential measurements are subject to many influences. The list provided shows several of the most important aspects of parameters that require control to achieve repeatable measurements. The values requested are voluntary and are not required for zeta potential measurements to be conducted successfully. The values become a permanent record with any saved data and allow easy record keeping of conditions imposed for the measurement. Zeta Potential Stability Behavior (millivolts) 0 - +/- 5 Coagulation +/- 10 to +/- 30 Incipient instability +/- 30 to +/- 40 Moderate stability +/- 40 to +/- 60 Good stability +/- 61 and greater Excellent stability Charge Charge and polarity at the surface. Polarity Provides the identification of the positivity or negativity of zeta potential value. Conductivity Provided in units of microsiemans per cm Zeta Potential Measurement Section - The values presented are measured by the Zetatrac. Mobility Provides the direction of travel of the particles when exposed to the Zetatrac imposed electric field. Negative sign indicates that the particle is moving towards the anode (+). SL-AN-16 Rev F 6

Zeta Potential From Henry s Formula for mobility: The value represents the potential difference between the dispersion medium and the stationary layer of fluid attached to the particle. Zeta potential is related to colloidal dispersion stability. Zeta potential values greater than 25mvolts are an indication of stability. The chart above may be used as an approximate guide. The value can be either positive or negative. Henry s formula: μ D = ζ 2ε ƒ(κa)/3 η ζ = 3ημ D /2εƒ(κa) = q/2πεd ε= dielectric constant; μ=mobility; η=viscosity; q=charge; d=diameter ƒ(κa) = Debye Huckel parameter (depends upon concentration and size. Where κ represents inverse distance of surface from the shear plane). For Microtrac zeta potential, assume Smoluchowski approximation where ƒ(κa) = 3/2 and zeta potential is calculated as: ζ = ημ D /ε Charge A calculated value equal to a sphere having a charge distribution which is the same as the mobility of the particles being measured q = 3π μ D η d SL-AN-16 Rev F 7