IR-LC Deposition and Detection System. Polymer Deformulation and Additive Analysis by a Single GPC-IR Run

Similar documents
ANALYSIS OF POLYMER BLENDS BY GPC-FTIR

Deposition and Detection System. Trace Level Analysis of Chemical Warfare Agents (CWAs) Related Chemicals by GC-IR Solid Phase System

Inks, Lubricants, Adhesives, Coatings How To Find Your Competitor s Recipe!

Use of High Speed/High Resolution Size-Based Chromatographic Separation of Polymeric Mixtures with Offline Infrared Detection

Determination of Polymer Modifier in Asphalt

Tips & Tricks GPC/SEC: Quantify and Get More Than Molar Mass Averages

GPC/SEC An essential tool for polymer analysis

Scheme 1: Reaction scheme for the synthesis of p(an-co-mma) copolymer

GPC/SEC Practical Tips and Tricks. Thomas Dent Applications Scientist Agilent Technologies. October, 2011 Gulf Coast Conference

One-pot polymer brush synthesis via simultaneous isocyanate coupling chemistry and grafting from RAFT polymerization

Polymer analysis by GPC-SEC. Technical Note. Introduction

Characterization of polyphenylene sulphide using the Agilent PL-GPC 220 High Temperature GPC System with triple detection

[application note] ACQUITY UPLC/SQD ANALYSIS OF POLYMER ADDITIVES. Peter J. Lee, and Alice J. Di Gioia, Waters Corporation, Milford, MA, U.S.A.

Size Exclusion Chromatography: Method Development

Hyphenated Spectroscopy Techniques

OVERVIEW INTRODUCTION. Michael O Leary, Jennifer Gough, Tanya Tollifson Waters Corporation, Milford, MA USA

We don t have anything against mass spectrometry. We just think it s time for a worthy alternative.

HYPHENATED TECHNOLOGY GUIDE

December 19, November 10, 2011

ACD/Labs Software Impurity Resolution Management. Presented by Peter Russell

Research Article Polymer Characterization by Combined Chromatography-Infrared Spectroscopy

HYPHENATED TECHNOLOGY GUIDE

Varian Galaxie Chromatography Data System for Preparative HPLC

An Introductions to Advanced GPC Solutions

The Theory of HPLC. Quantitative and Qualitative HPLC

Advanced GPC. GPC On Tour, Barcelona, 28 th February The use of Advanced Detectors in GPC

3) In CE separation is based on what two properties of the solutes? (3 pts)

Differentiation of polymer branching and composition using the Mark Houwink plot

Spectroscopy Databas s &

LC and LC/MS Column Selection Flow Chart

Molecular weight of polymers. Molecular weight of polymers. Molecular weight of polymers. Molecular weight of polymers. H i

Chapter 14. Molar Mass Distribution.

AN INTEGRATED SYSTEM USING TEMPERATURE BASED SAMPLING FOR POLYMER CHARACTERIZATION

How to use GPC/SEC for compositional analysis

Quick guide to selecting columns and standards for Gel Permeation Chromatography and Size Exclusion Chromatography SELECTION GUIDE

Analysis of Fluorofentanyl Isomer Compounds by Gas-Chromatography Coupled with Solid Phase Infrared Detector IR_AN_047

Clearing the Confusion: GPC, SEC, GFC What, When, Why, and How?

SUPPLEMENTARY INFORMATION

Maximizing Performance Through GPC Column Selection

Evaluation of Several Columns and Solvents for Post-Extraction Gel Permeation Chromatography (GPC) Clean-up of Fish Tissue Prior to PCB Analysis

Accurate Mass Measurement for Intact Proteins using ESI-oa-TOF. Application Note. Donghui Yi and Christine Miller Agilent Technologies

Supporting Information

Aziridine in Polymers: A Strategy to Functionalize Polymers by Ring- Opening Reaction of Aziridine

Magnetic Iron Oxide Nanoparticles as Long Wavelength Photoinitiators for Free Radical Polymerization

Chromatographic Separation

Analysis of Trace (mg/kg) Thiophene in Benzene Using Two-Dimensional Gas Chromatography and Flame Ionization Detection Application

Analysis of Stachydrine in Leonurus japonicus Using an Agilent ZORBAX RRHD HILIC Plus Column with LC/ELSD and LC/MS/MS

Molecular Weight Distribution of Living Chains in Polystyrene Pre-pared by Atom Transfer Radical Polymerization

Analysis of Star Polymers Using the Agilent 1260 Infinity Multi-Detector GPC/SEC System

The ph-responsive behaviour of aqueous solutions of poly(acrylic acid) is dependent on molar mass

Gel Permeation Chromatography

Selective Formation of Benzo[c]cinnoline by Photocatalytic Reduction of 2,2 Dinitrobiphenyl with TiO 2 and UV light irradiation

Analysis of Sulfur-Containing Flavor Compounds By GC/MS With A PFPD

Agilent J&W PoraBOND Q PT Analyzes Oxygenates in Mixed C4 Hydrocarbon Streams by GC/FID and GC/MSD

Techniques useful in biodegradation tracking and biodegradable polymers characterization

BRIEFING. (EXC: K. Moore.) RTS C Propylparaben C 10 H 12 O Benzoic acid, 4 hydroxy, propyl ester; Propyl p hydroxybenzoate [ ].

Advanced GPC Technology as a Part of Solving Complex Polymer Problems

Chemistry Instrumental Analysis Lecture 15. Chem 4631

Luna 2.5 µm C18(2)-HST. Advantages of 2.5 µm for increasing the speed of analysis while maintaining high efficiency

CASE STUDY. Degradation of Polyethylene by FTIR and High Temperature GPC

How switching mobile phases can improve your OMNISEC results

Advanced GPC Technology as a Part of Solving Complex Polymer Problems

Benchtop NMR Combined with GC/MS Confirms Identity of Forensic Case Sample

The Analysis of Organophosphate Pesticides by LC/MS Application

Agilent 385-ELSD Evaporative Light Scattering Detector

HPLC Preparative Scaleup of Calcium Channel Blocker Pharmaceuticals Application

Prep 150 LC System: Considerations for Analytical to Preparative Scaling

Marine bio-inspired underwater contact adhesion

Online Reaction Monitoring of In-Process Manufacturing Samples by UPLC

Quality control analytical methods- Switch from HPLC to UPLC

Mass Spectral Studies of Polypropylene Chromatographic Well Plates

Advantages of Agilent AdvanceBio SEC Columns for Biopharmaceutical Analysis

Accurate Mass Analysis of Hydraulic Fracturing Waters

Introduction. Chapter 1. Learning Objectives

Gel Permeation Chromatography Basics and Beyond eseminar March 13, Jean Lane Technical and Applications Support LSCA, Columns and Supplies

FTIR Spectrometer. Basic Theory of Infrared Spectrometer. FTIR Spectrometer. FTIR Accessories

Waters GPC User Guide and Tutorial for Using the GPC in the Reynolds Research Group 2 nd Edition: April 2012

We don t have anything against mass spectrometry. We just think it s time for a worthy alternative.

Chemistry 3200 High Performance Liquid Chromatography: Quantitative Determination of Headache Tablets

Comprehensive Polymer Analysis Strategies

On-line LC(GPC/SEC)-NMR of Complex Mixtures

A TTFV pyrene-based copolymer: synthesis, redox properties, and aggregation behaviour

Agilent 385-ELSD Evaporative Light Scattering Detector

SEAMLESS INTEGRATION OF MASS DETECTION INTO THE UV CHROMATOGRAPHIC WORKFLOW

GPC/SEC standards. Product guide

A Strategy for an Unknown Screening Approach on Environmental Samples using HRAM Mass Spectrometry

Application Note. Author. Abstract. Pharmaceutical QA/QC. Siji Joseph Agilent Technologies, Inc. Bangalore, India

The Analysis of Residual Solvents in Pharmaceutical Products Using GC-VUV and Static Headspace

Chapter 31 Gas Chromatography. Carrier Gas System

Chemistry Gas Chromatography: Separation of Volatile Organics

ACD/AutoChrom Assisted Method Development for Challenging Separations. Vera Leshchinskaya February 7, 2018

Rapid and Accurate Forensics Analysis using High Resolution All Ions MS/MS

The Epidemic is coming (Tucson News KOLD/KMSB)

Mixture Analysis Made Easier: Trace Impurity Identification in Photoresist Developer Solutions Using ATR-IR Spectroscopy and SIMPLISMA

MassHunter METLIN Metabolite PCD/PCDL Quick Start Guide

Chromatography- Separation of mixtures CHEM 212. What is solvent extraction and what is it commonly used for?

ADVANTAME (TENTATIVE)

Open Column Chromatography, GC, TLC, and HPLC

VUV ANALYTICS VGA-100 GC DETECTOR Gas Chromatograph Agilent 6890 equipped with a 7683 model autosampler Restek 30m x 0.25mm x 0.

VALLIAMMAI ENGINEERING COLLEGE SRM Nagar, Kattankulathur

Transcription:

DiscovIR-GPC DiscovIR-L IR-LC Deposition and Detection System Application Note 42 Polymer Deformulation and Additive Analysis by a Single GPC-IR Run ABSTRACT This application note describes the use of a single GPC-IR run to identify both the polymer components and the low molecular weight (MW) additives in a complex polymer formulation. Following a 40-minute GPC separation, solid phase IR spectra of each polymer component and low MW additives are obtained near real-time. IR spectra from any part of the GPC chromatograph can be examined and library searched to identify high MW polymer components; whereas, mass spectroscopy (MS) is limited to outside proteins and low MW additives. As a case study, a complex adhesive sample was quickly deformulated by GPC-IR to three polymer components and three mid-low MW additives giving significant insight into the formulation design that delivers the unique end-use properties. There is an enormous gain in productivity when compared to the classical methods of sample preparations with extraction, fraction collection and drying followed by Nuclear Magnetic Resonance (NMR) or IR batching runs. The same techniques described herein can be applied to various complex polymer mixtures in coatings, adhesives, inks, sealants, elastomers, plastics, rubbers and composites for competitive analysis, IP protection and analytical troubleshooting. INTRODUCTION Many formulated polymer systems such as adhesives, coatings, inks, elastomers, etc. consist of multiple polymeric components and low MW additives. The reverse-engineering of such complex formulas typically take two analytical approaches: polymer deformulation (green path) and additive analysis (red path), as highlighted in Figure 1 below. The traditional method in identifying the individual polymer components involves many sample preparation steps (green path) and is very time consuming (days). The steps are: 1. dissolve the polymer sample with a proper solvent and run through a preparative GPC; 2. collect many fractions for the multiple polymeric components; 3. remove the solvent from each fraction; 4a. prepare KBr sample for each dried fraction and run IR one fraction at a time (batching); or 4b. add a deuterated solvent to each dried fraction and run NMR one fraction at a time (batching); and 5. identify the individual polymeric components (e.g. A, B and C) from an IR or NMR database search. High MW Polymers Collect Fractions Low MW Additives Extract Additives Remove Solvents Run HPLC-MS Run IR or NMR MS ID: X, Y & Z ID: A, B & C A B C X Y Z Figure 1 - The typical way to deformulate complex polymer mixtures involves many sample preparation steps in identifying the individual polymer components (green path for A, B and C) and low MW additives (red path for X, Y and Z). The Leader in GC-IR and LC-IR Instrumentation www.spectra-analysis.com

The typical analytical approach in identifying low MW additives such as antioxidants, UV stabilizers, surfactants, plasticizers, property modifiers, processing aids, etc. involves solvent extraction and filtration followed by HPLC-MS, as highlighted with the red path in Figure 1 (previous page). The process is to: 1. extract the additive components from the polymer sample (sometimes the sample must be ground up and/or ultrasonically assisted); 2. filter out the polymer solid and fillers, if any; 3. develop an HPLC method to separate the additive peaks, typically with a reverse phase solvent gradient method; 4. run HPLC-MS of the extract sample; and 5. identify each additive (e.g. X, Y and Z) from an MS database search. A GPC-IR coupled system is capable of identifying all the polymer components and low MW additives in a single run with a simple sample preparation such as: 1. dissolving the whole polymer formula in a proper solvent or solvent blend; 4. running GPC-IR to collect IR spectra of each separated polymer component and additive; and 5. searching IR database to identify each polymeric component (e.g. A, B and C) and additive (e.g. X, Y and Z). There is a significant gain in productivity when compared to the traditional methods of sample preparations that involve extraction, fraction collection and drying. Coupling an on-line infrared detector with Gel Permeation Chromatography (GPC) makes it possible to take an FTIR snapshot spectra of each polymer component and additive in a complex polymer mixture and then identify them by IR an database search. GPC separates the complex polymer mixture into high MW polymer components and low MW additives according to their hydrodynamic sizes. The GPC-IR system removes the solvent and then deposits the chromatographic eluents as a continuous track on an IR-transparent ZnSe disc. The built-in interferometer simultaneously captures a set of time-ordered transmission IR spectra every 0.5 seconds from the solidphase deposit. The DiscovIR software system controls the data collection and performs the data processing (e.g. plotting selected band chromatograms related to polymer functional groups) and an IR spectral search. The snapshot IR spectra from any part of the GPC chromatogram can be used for the IR database search to identify the chemical compositions. Since mid-infrared spectroscopy is such a popular analytical technique for characterizing the chemical composition of individual polymers and additives, there are many large-size commercial IR libraries available and in-house IR databases collected from various bench-top FTIR spectrometers through the decades. Recently new online IR search services with a pay-as-you-go fee schedule make IR spectral matching convenient, more exhaustive and cost effective without the need of purchasing an IR library. Due to the vast number of existing polymer formulations and the continued effort of new formulation development in expanding endless polymer applications, there is a routine need to deformulate various complex polymer systems in coatings, adhesives, inks, elastomers, plastics, foams, composites, etc. for competitive analysis, IP protection and analytical troubleshooting. This application note will demonstrate the use of the DiscovIR-LC for the GPC-IR single run deformulation of a complex hot-melt adhesive and will identify three polymer components and three low MW additives by an IR database search. EXPERIMENTAL Materials and Sample Preparation A hot melt adhesive sample was obtained from a major adhesive manufacturer. The adhesive sample was dissolved in tetrahydrofuran (THF) at 5 mg/ml concentration and the solution was filtered through a 0.45 µm PTFE filter before GPC injection. GPC Conditions LC System: Agilent 1200 Series Column: 2 x Jordi Gel DVB Mixed Bed, 25 x 1 cm ID Column Temp: Ambient (25 C) Mobile Phase: THF Flow Rate: 1.0 ml/min Injection Volume: 100 µl Run Time: 40 minutes FTIR Detection Discover-LC Solvent-Removing Direct-Deposition Solid-Phase FTIR Nebulizer Power: 5 watts Cyclone Temp: 150 C Carrier Gas (N2): 315 ml/min Condenser Temp: 5 C Disk Temp: 15 C Disk Speed: 3 mm/min Chamber Vacuum: 5.0 torr IR Det. Resolution: 8 cm -1 2

RESULTS AND DISCUSSIONS The adhesive sample was analyzed by GPC-FTIR using two Jordi Gel DVB Mixed Bed columns to separate the high MW polymer components and the low MW additives. The eluant from the column was continuously desolvated and deposited as a track on the ZnSe sample disk through which FTIR spectra of the deposited analytes were acquired every 0.5 seconds during the course of the run. The DiscovIR-LC collected time-ordered IR spectra through the whole chromatographic separation. As a default, the DiscovIR-LC creates a max band chromatogram using the highest intensity of all IR bands across the mid-ir range (4000-650 cm -1 ) at each elution time, which is similar to the response of conventional detectors such as UV. Figure 2 below displays the max band chromatogram (blue) of the adhesive sample showing six separated peaks labeled as A, B, C, X, Y and Z. The early eluting peaks A, B and C are high MW polymer components and are all well separated. The middle peaks X and Y are medium-low MW components and are partially separated. The late eluting peak Z is likely to be the low MW additive which is sitting on the tailing portion of Peak Y. High MW Polymers Low MW Additives [y] [a] [b] [c] [x] [z] A B C X Y Z Figure 2 - GPC-IR chromatogram of the adhesive sample showing three polymer peaks (A, B and C) and three additive peaks (X, Y and Z). Six snapshot IR spectra were taken from the six red markers for component identification. Using the Data Workup software from the DiscovIR-LC system, the user can scroll through the time-ordered set of IR spectra (collected every 0.5 seconds) and can closely examine the IR band pattern changes in order to identify the most representative snapshots for each component. In some cases, the leading or tailing edge of the overlapped peaks is more likely representative of a single component with less influence from another component and is more useful for the IR spectra library matching. In the following pages, we will identify the six components (listed below) found in the sample using screenshots from the library search. 1. Component A is the main component under Peak A whose leading edge appears to be a single component (relatively pure A) before its overlap with Peak B. An IR spectrum was extracted at 18.60 min at red marker [a] and was used for an IR library match. 2. Component B is the main component under Peak B whose tailing edge appears to be a single component (relatively pure B) with minimal tailing effect from Peak A. An IR spectrum was extracted at 20.25 min at red marker [b] and was used for an IR library search. 3. Component C is the main component under Peak C which is almost baseline resolved. It is well represented by its apex at 21.05 min at red marker [c]. 4. Component X is the main component under Peak X and is overlapped with some leading portion of Peak Y. An IR spectrum was extracted at 25.60 min at red marker [x] and was used for an IR database matching. 5. Component Y is the main component under Peak Y and is overlapped with some tailing portion of Peak X. An IR spectrum was extracted at 27.06 min at red marker [y] and was used for an IR database match. 6. Component Z is the main component under Peak Z and is heavily overlapped with the long tailing portion of Peak Y. All the IR spectra under the Peak Z area (30-37 min) appear to be very similar. An IR spectrum was extracted at 32.40 min at red marker [z] and was used for an IR database match with a multiple-component search capability. 3

In order to identify all the components (A, B, C, X, Y and Z), six snapshot IR spectra were taken from the six red marker positions, baseline corrected and searched against BioRad Lab s commercial IR database with about 237,000 IR spectra. In the low MW region (< 2000 Dalton) where most additives (e.g. X, Y and Z) come out at similar elution times, the snapshot IR spectra from the multiple elution positions in the highly overlapped peak region can be used for multiple-component searches to identify each additive component. BioRad s KnowItAll software can identify multiple components and up to four subcomponents. The alternate way is to use spectral subtraction to find the IR spectra for single subcomponents before performing the IR library matching. Principle Component Analysis (PCA) with multiple IR spectra from multiple elution times in the overlapped peak region can also be used to confirm the number of the subcomponents and their identification if needed. All commercial transmission IR libraries, online IR search services and in-house IR databases can be used to identify various polymers, copolymers, additives, impurities, degradants and many other organic compounds. 1. Identification of Polymeric Component A in the Adhesive Sample Component A in the adhesive sample is best represented by the leading edge of Peak A. Its IR spectrum (red), shown in Figure 2 on the previous page, is at 18.60 min at red marker [a] and identified below in Figure 3 with its top match (black) having 878 HQI high matching rate. Hit quality index (HQI) is used to rate the library matching with a higher number indicating a closer match (1000 indicating a perfect match). BioRad s IR database search identified Component A (red) as poly(styrene/isoprene) copolymer (black). The next three matches listed below with 834-781 HQI also led to the same identification with the specific product information (Kraton Polymer s KRATON D-1111 and 1107) available from the IR database. The grayed areas are the excluded IR regions where there were only flat baselines or no data available below 650 cm -1 for the improved IR database matching. Figure 3 - The commercial IR database search identified Component A (red) as Styrene/Isoprene Copolymer (black). 4

2. Identification of Polymeric Component B Component B in the adhesive sample is well represented by the tailing edge of Peak B. Its IR spectrum (red) at 20.25 min at red marker [b] in Figure 2, Page 3 is displayed below in Figure 4 with its top match (black) having 919 HQI high match rate. The IR database search identified Component B (red) as poly(styrene/ butadiene) copolymer (black) with specific product information (Europrene 1707). The second match listed is not a good one because it lacks the IR band at 967 cm -1 which is unique for Component B. The last two matches listed with 887-893 HQI also led to the same identification: poly(styrene/ butadiene) copolymer. Figure 4 - The commercial IR database search identified Component B (red) as Styrene/Butadiene Copolymer (black). 3. Identification of Polymeric Component C Component C is best represented at the apex of Peak C. Its IR spectrum (red) at 21.05 min at red marker [c] in Figure 2, Page 3 is displayed on the next page in Figure 5 with its two-component matching from the IR database: styrene/butadiene copolymer (green, same as Component B) and styrene/isoprene copolymer (black, same as Component A). The chemical composition of Component C is mostly like Component B with some Component A but at lower MW. 5

-Peak C Figure 5 - The commercial IR database search identified Component C (red) as a mixture of Styrene/ Butadiene Copolymer (green) and Styrene/Isoprene Copolymer (black). 4. Identification of Additive Component X Component X in the adhesive sample is well represented by the leading edge of Peak X. Its IR spectrum (red) at 25.60 min at red marker [x] in Figure 2, Page 3 is displayed on the next page in Figure 6 with its top match (black) having 696 HQI matching rate. The IR database search identified Component X (red) as pentaerythritol ester of rosin (black, Ester Gum-P.E.). The next four matches listed with 693-695 HQI also led to the identification of Rosin Ester with some product information available from the IR database. 6

-Peak X--Leading Edge Figure 6 - The commericial IR database search identified Component X (red) as Pentaerythritol Ester of Rosin (black). The DiscovIR-LC software is designed to process GPC-IR data in many different ways such as plotting selected band chromatograms, which shows MW distributions of the selected functional group corresponding to the IR absorption. Component X has an ester functional group with a unique IR absorption at 1735 cm -1. The following screenshot shown on the next page in Figure 7 is of the DiscovIR-LC monitor displaying the selected band chromatogram (MW distribution) of Component X in the top panel based on the X-specific band 1735 cm -1. The middle panel displays the snapshot IR spectrum (red) of Component X at the apex of Peak X at the red marker while the lower panel shows the snapshot IR spectrum (blue) of Component Y at the blue marker (Component Y showed no absorption at 1735 cm -1 in the top panel). 7

Figure 7 - The selected band chromatogram at 1735 cm -1 for Component X (top panel) and two snapshot IR spectra (middle and lower panels) corresponding to the red and blue markers (Components X and Y). 5. Identification of Additive Component Y Component Y is well represented at the apex of Peak Y. Its IR spectrum (red) at 27.06 min at red marker [y] in Figure 2, Page 3 is displayed on the next page in Figure 8 with its top match (black) having a 923 HQI high matching rate. The IR database search identified Component Y (red) as mineral oils/hydrocarbons (black). The next three matches listed in the following table with 895-918 HQI also led to similar identification with some product information available from the IR database. It appears that the major peak (Peak Y) is mainly a simple hydrocarbon paraffin/mineral oil with only simple IR bands at 2960 cm -1 (CH 3), 2930/2870 cm -1 (CH 2), 1462 cm -1 (CH 2), 1375 cm -1 (CH 3). Peak Y extends its long tailing edge under Peak Z, making the identification of Component Z more complicated. 8

-LA #1841; SUNISO 3GS -Peak Y--Apex 2--RT27.1 Figure 8 - The commercial IR database search identified Component Y (red) as Mineral Oils/Hydrocarbons (black). 6. Identification of Component Z Component Z in the adhesive sample is well represented by the tailing edge of Peak Z. The snapshot IR spectrum (red) at 32.40 min at red marker [e] in Figure 2, Page 3 is displayed on the next page in Figure 9 with its top match (blue, composite spectrum) having a 866 HQI high matching rate. Direct library matching did not give a satisfactory result (single component answer) with a good HQI. Instead the multiple component search was used with BioRad s KnowItAll software and led to two component identifications: SUNISO mineral oil (black, similar to Component Y already identified above) and NILOX (green, hydrogenated rosin acid) which is Component Z. The composite spectrum (blue) is the addition of those two components. 9

-Peak Z Figure 9 - The multiple component search by BioRad s KnowItAll software led to two component identifications at red marker [e] in Figure 2, Page 3: NILOX (green, hydrogenated rosin acid as Component Z) and SUNISO mineral oil (black, Component Y tailing background). Figure 10 on the next page overlays all the six IR spectra from the six red marker positions in Figure 2 on Page 3 used to quickly identify the six Components A, B, C, X, Y and Z by IR spectral search. The color-coded letters (upper cases) indicate the unique IR bands for the component which can be used to plot the selected band chromatograms to map out the MW distributions of that component. 10

[a] Component A [b] Component B [c] Component C [x] Component X [y] Component Y [z] Components Z + Y Z X B A B C Figure 10 - Overlay of the six snapshot IR spectra from the six red marker positions in Figure 2, Page 3 used to quickly identify the three polymeric components (A, B and C) and the three additive components (X, Y and Z) by IR spectral search. CONCLUSION The coupled GPC-IR system separated the complex adhesive sample by hydrodynamic sizes, acquired high quality IR spectra of the separated peaks and identified three polymer components and three mid-low MW additives by a commercial IR database search. High MW Polymer Components in Descending Order: (1) Component A was identified as Poly(Styrene/Isoprene) Copolymer. (2) Component B was identified as Poly(Styrene/Butadiene) Copolymer. (3) Component C was identified as low MW portions of Components B & A. Medium - Low MW Additives in Descending Order: (4) Component X was identified as Pentaerythritol Ester of Rosin (MW~1342). It has a unique IR band at 1735 cm -1 which can be used to map out its MW distribution by the selected band chromatogram. (5) Component Y was identified as Hydrocarbon Paraffin / Mineral Oil with a long tailing. (6) Component Z was identified as Hydrogenated Rosin Acid (MW ~302). It has a unique IR band at 1698 cm -1 with carboxylic acid functionality. GPC-IR enables analytical scientists to rapidly identify all the polymer components and low MW additives in a single run with a simple sample preparation. There is a significant gain in productivity when compared to the traditional methods of sample preparations with extraction, fraction collection and drying followed by NMR or IR batching runs. This powerful reverseengineering tool enables formulation scientists and engineers to gain significant insight into formulation design, intellectual property and marketing competitiveness of rival companies in polymer-related industries. ACKNOWLEDGMENT Bio-Rad Laboratories Informatics Division For more information, please contact: Spectra Analysis Instruments, Inc. 257 Simarano Drive Marlborough, MA 01752 508-281-6232 info@spectra-analysis.com