a preview of the cpac fall meeting tutorialdepts.washington.edu/cpac/activities/cpac_webinar... ·...

September 25, 2008 CPΛC

Chemometric Peak Alignment ToolsA preview of the CPAC Fall Meeting Tutorial

Rob Synovec, UW Department of Chemistry, CPACCarl Rechsteiner, Jr., Chevron ETC

Brian Rohrback, Infometrix, Inc.

Moderator: Mel Koch, CPAC


Industry/Academic Cooperation

Mel KochCPAC Executive Director, University of Washington, Seattle, WA

September 25, 2008 Chemometric Peak Alignment 3CPΛC

Center for Process Analytical Chemistry

UNIVERSITY OF WASHINGTON,UNIVERSITY OF WASHINGTON, SEATTLESEATTLE


Welcome and Introduction

CPAC is a consortium of multi-industry sponsors, and government agencies

The objective of the Center is to address challenges in real-time analysis and process control

The Center provides a forum for multi-disciplinary and multi-university participation in developments in Process Analytical Technology (PAT)


CPAC Sponsor Focus Groups

Oil and Petrochemicals

Chemicals and Materials

Food and Consumer Products

Bio Tech and Pharmaceuticals

Instrument Companies


Focus Group Discussion Topic

As process analytical tools are being used at an increasing rate, there is concern about how to extract more useful data from the instruments in a shorter period of timePeak alignment was a critical need that was identified as an action itemFunding for Phase I and Phase II efforts was provided by the Washington Technology Center

A supplemental document is available for download. This is an abbreviated summary of information presented in previous CPAC meetings.


The Commercial Background of Chromatographic Alignment

Brian RohrbackPresident, Infometrix, Inc., Bothell, WA

CPAC Sponsor


Data-Information Value Hierarchy

Data

Information

Knowledge

Action

= Control Model

= Process Control

= Instrument or Sensor Output

= Database / Mining

Each layer above is a refinement of the layer below.

Effort is expended to distill the lower value component to a higher value one.

Informatics Division


GC: Improving the Data to Information Transition

Falcon MicroFast GCLineUp v. 2


Initial Commercial Driving Force

7.2 7.4 7.6 7.8 8 8.2 8.4

0

0.25

0.5

0.75

1

1.25

1985: Faced with a backlog, the CDC started a search for a more rapid diagnosis for M. tuberculosis, analyzing cell wall acids using HPLC. There are >60 related species.

TB or not TB?


54 samples of M. intracellulare (1 lab)

54 samples of M. intracellulare (1 lab)


38 samples of M. simiae (5 labs)


Commercial Software (LineUp version 1.0)

54 samples of M. intracellulare(1 lab)

Circa 1994

Waters HPLCLineUp v. 1

Journal of Chromatographic Science vol.32 1994


Poll of Process Users

1. Analytical failure prediction2. Result validation3. More process-specific information (timely, higher

quality, more focused)4. Simplification of procedures5. Reduction in the lifecycle cost (cost of ownership)

Driven in part by dwindling manpower, skill sets and capabilities !


C1 - C9 Before Alignment

Full Data;2

0 10 20 30 40Time Index (E +03)

0.0

0.1

0.2

Res

pons

e

Siemens Maxum II


C1 - C9 After Alignment

Full Data;2

0 10 20 30 40Time Index (E +03)

0.0

0.1

0.2

Res

pons

e

Siemens Maxum IILineUp v. 2


On-Line Process HPLC

Dionex ChromeleonLineUp v.3

Before Alignment

After Alignment


Quantitation of trans-fat

Agilent ChemStation


Quantitation of trans-fat

Agilent ChemStationLineUp v. 3


Biodegraded crude oil

Agilent ChemStationLineUp v. 3


Infometrix’ Commercial LineUp Software

Integrated Software SystemsAgilent ChemStationAgilent EZChrom ElitePerkinElmer TotalChromSiemens Maxum EZChrom

Supported Software SystemsDionex ChromeleonThermo Fisher AtlasWaters EmpowerJustice ChromPerfect

Companies Bundling SolutionsPAC/AC Analytical ControlsFalcon AnalyticalSiemens Maxum II & MicroSam

CPAC Associate Sponsors


Intermediate Review

Chromatography will always have peak or pattern identification problems resulting from retention time shift.

Sample handling, column and instrument maintenance, flow control and temperature programming precision can mitigate retention shift problems, but must be done preemptively.

Correlation optimized warping and like technology offers a generalized solution for processing chromatograms automatically,performing as well as a system built around coinjection of internal standards.

The technique opens the possibility of multi-year, multi-instrument global chromatographic databases.


Background on CPAC Technologies, and our Interest in Developing Chromatographic Alignment

Rob SynovecCPAC Faculty Director and Professor of Chemistry,

University of Washington, Seattle, WA


CPAC and the University of Washington

CPAC has been, and continues to be, a leading technology development arena and ideological forum for advancing the field of process analysis and process optimization.

CPAC has a rich history of developing key technology areas that will benefit significantly from a concerted effort in ALIGNMENT.

Rob Synovec – Faculty Director, [email protected]


CPAC Core Technologies

Chemometrics (data analysis with advanced performance and information content): pioneered by Kowalski and Callis, now Steve Brown and others

Chromatography, GC and LC: Synovec, and FIA, SIA: Ruzicka and Christian

Spectroscopy and Sensors: Marquardt, Burgess, McCarthy, Mann and others

New Sampling and Sensor Initiative: NeSSI™, key component ofProcess Optimization and Control


What is NeSSIWhat is NeSSI™™??

Industry-driven effort to define and promote a new standardized alternative to sample conditioning systems for analyzers and sensors

Standard fluidic interface for modular surface-mount components

Standard wiring and communications interfaces

Standard platform formicro analytics


Alignment…and CPAC Technologies

Goal:Enhance the performance of on-line, real-time,

process control analytics by optimally applying chemometrics to chromatographic and spectroscopic measurements.

Alignment is fundamental to success of this activity!


Alignment for GC separations with severe shifting

0 1 2 3 4 5 6 7 80

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Retention Time (minutes)

Sign

al (A

rb. U

nits

)

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Retention Time (minutes)

Data Set 1Data Set 2Data Set 3

Sign

al (A

rb. U

nits

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AFTER

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4 Data Set 1Data Set 2Data Set 3

Sign

al (A

rb. U

nits

)

BEFORE

Four gasolines (A, M, S, T)

60 replicates each

3 data sets: diff. temperature & flow programs

Severe non-linear shifting

September 25, 2008 Chemometric Peak Alignment 29CPΛC0.70 0.75 0.80

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0 1 2 3 4 5 6 7Retention Time (minutes)

Ret

entio

n Ti

me

Shift

(rel

ativ

e to

pea

k w

idth

)

Correction required to align two chromatogramsNot a simple scalar offset

Several peak widths Alignment is robust for different sample types

Retention Time

Retention Time

Retention Time

Sign

al Sign

alSi

gnal


Alignment improves retention time precision and classification via PCA

-2 -1 0 1 2

-1

0

1

2

A

A

A A

A

AA

AA

A

MMMMMMM

MMMSSS

S

SSS

S

SST

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T

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AA

A AAAA

A

AA M

M

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MMM SSS

S

SS

S

SS

S

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T

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T

AA

A AAA

A AA

A

MM

MMMM

MMMM

SS

S

SS

S

SSSST

TTTTTT

TT

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AAAA

AA

A

AAA

M

M

MM

MM

MMM MSSS

SSSS

SSS

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TTT

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A

AAA

AAAAAA

MMMMMMM

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MSSS

SSSSSS

S

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TTTTT

AAA

AAAAAAAMMMMMMMMMMSSSSSSSSS

STTTTTTTTTT

Scores on PC# 1 (10-2)

Scor

es o

n PC

# 2

A

-4 -2 0 2 4-2

-1

0

1

T M

S

Scores on PC# 1 (10-3)Sc

ores

on

PC#

2 (1

0-3)

Classification groupsbased on data set “conditions”

Classification groups based on fuel type

BEFORE: AFTER:


2.62 2.66 2.70 2.74x 104

0

1

2

3

x 10-4

Retention Time (points)

BEFORE

Overlaid sub-region of 4 raw chromatograms

2.62 2.66 2.70 2.74x 104

0

1

2

3x 10-4

Retention Time (points)

AFTER

Overlaid sub-region of same 4 chromatograms after piecewise

Chemical selectivity is preserved !

Alignment improves retention time precisionfor distillation fractions - Reformates


What is the nature and manifestation of the enhancement for chemometrics?

•Off-Line•Batch•Expert OftenRequired

•On-Line, Real-Time•Continuous and/or Batch

•Non-Expert Compatible


Current Research Thrust in Alignment

Concerted effort by research “team”:Infometrix, Synovec and Marquardt research groups, and various CPAC sponsors.

Optimization of real-time alignment strategies:(1) automated parameter selection with metrics(2) optimal target chromatogram (or spectrum)

selection (unattended)(3) provide data from alignment to control the

instrument (to reduce maintenance costs)


State-of-the-art, and how to learn more

Substantial advances have been made in addressing the goals on the previous slide, and much has been done to bring the alignment tools to useful fruition for implementation to NeSSI™ compatible systems.

Learn more by attending the upcoming CPAC meeting where we kick off the meeting with an entire morning devoted to a workshop on our latest advances for implementing on-line, real-time alignment. Additionally, learn from the research reports from on-going research projects.


Selected References (on CPAC Web Site)

(1) “Unsupervised Parameter Optimization for Automated Retention Time Alignment of Severely Shifted Gas Chromatographic Data using the Piecewise Alignment Algorithm,” K. M. Pierce, B. W. Wright and R. E. Synovec, J. Chromatogr. A, 2007,1141, 106-116.

(2) “Classification of High Speed GC-MS Data by PCA Coupled with Piecewise Alignment and Feature Selection,” N. E. Watson, M. M. VanWingerden, K. M. Pierce, B. W. Wright and R. E. Synovec, J. Chromatogr. A, 2006, 1129, 111-118.

(3) “Classification of Gasoline Data Obtained by Gas Chromatography using a Piecewise Alignment Algorithm combined with Feature Selection and Principal Component Analysis,” K. M. Pierce, J. L. Hope, K. J. Johnson, B. W. Wright and R. E. Synovec, J. Chromatogr. A, 2005, 1096, 101-110.

(4) “A Comprehensive Two-Dimensional Retention Time Alignment Algorithm to Enhance Chemometric Analysis of Comprehensive Two-Dimensional Separation Data,” K. M. Pierce, L. F. Wood, B. W. Wright and R. E. Synovec, Anal. Chem., 2005,77, 7735-7743.

(5) “Quantification of Naphthalenes in Jet Fuel with GC x GC/Tri-PLS and Windowed Rank Minimization Retention Time Alignment,” K. J. Johnson, B. J. Prazen, D. C. Young and R. E. Synovec, J. Sep. Sci., 2004, 27, 410-416.

(6) “High-Speed Peak Matching Algorithm for Retention Time Alignment of Gas Chromatographic Data for Chemometric Analysis,” K. J. Johnson, B. W. Wright, K. H. Jarman and R. E. Synovec, J. Chromatogr. A, 2003, 996, 141-155.


Customer PerspectiveImplementing Alignment with a Process GC Focus

Carl Rechsteiner, Jr.Chevron ETC, Richmond, CA

Chairman, CPAC Industrial Advisory Board


Future Trends That Impact Industry

Miniaturized instrumentationFast instrumentationRemote access to sample pointsAbundant data rich analyzersMore precise control needed

What WhyChanging regulationsChanging productsConvergence of labs and process analyticsResource limitations

Manpower,Skill sets,Materials, …


Solutions

Our future needs:to implement analyzers capable of measuring more critical process parameters;to extract more information from those analyzers;to better utilize computational advances; and

to put more smarts into our analyzers.

This will make our jobs manageable!


GC Systems for Process Monitoring(Agilent, Falcon Analytical, Siemens, SLS Micro)


Prototype System with Process Compatible Sample Handling System

Inlet

OutletWaste

Falcon MicroFast GC


Multifunction System

Expansion

Area

For

Additional

Analyzer(s)


Petrochemical Process GC Applications

Gas composition (including BTU value)Speciation of small hydrocarbon moleculesStream Fingerprints

HydrocarbonHeteroatom (Sulfur, Nitrogen)

Yield Curves


Attainable Product Yield Distribution

Crude Oil Composition MapTBP Curves

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1000

1200

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1800

0 10 20 30 40 50 60 70 80 90 100

Cumulative Yield from Crude, Wt%

Tru

e B

oilin

g Po

int,

°F

Naphtha

Middle Distillates

Deep-cut Vacuum Gas Oil

Deep-cut Vacuum Residue

G S

F

Y

F

Y

F

Y

Su

l

fur


The Alignment Advantage

Seeing process detail

that would otherwise be missed.


On-line Simulated Distillation

400 Samples Un-Aligned

Same Samples Aligned

Siemens Maxum II


Comparison of PCA scores

85% of all of the variation in the raw data is due to the misaligned peaks.

Correcting for this shows us that there are three different production regimes in these data.

Before alignment After alignment


SimDis is a GC simulation of physical distillation to provide yield as a function of boiling point.Sample is eluted on a boiling point column and the signal integrated.SimDis is faster and has better reproducibility than physical distillation.SimDis retains the data-richness of chromatographic methods, which can be exploited. SimDis performance is fairly well understood and measurable.

What is Simulated Distillation (SimDis)?

Full Data

19.990362 39.989296 59.985939 79.988678

Variable

0

20

40

Res

pons

e (E

+04

)


The case for alignment - 1

Unaligned Chromatograms

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Retention Tim e , m in

% o

f Sig

nal

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0.4

0.45

0.5

15 15.5 16 16.5 17 17.5 18 18.5 19 19.5 20Retention Time, min

% o

f Sig

nal

Agilent 6890 ChemStation



Chemometric Aligned Chromatograms

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its

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Agilent 6890 ChemStationLineUp v. 3



Data BiasAverage Yield Curve Comparison

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BPAligned



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BPAligned

Data Bias - Closeups

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770 780 790 800 810 820Boiling Point, deg. F

Yiel

d, w

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BPAligned

858687888990919293949596979899

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Yie

ld, w

t %

BPAligned


User Conclusions

Alignment is useful, of high value, and widely applicable.Alignment is generally applicable to any chromatographic or spectroscopic measurement.CPAC, UW, with CPAC sponsors provide high leverage to solve real-world problems for industry.CPAC/UW capabilities allow development of test beds, and can lead to commercial implementations of technology for the common good.


Conclusions and Questions

Brian RohrbackPresident, Infometrix, Inc., Bothell, WA

CPAC Sponsor


Fitting into the Current Process Environment


Acknowledgements

Russell Paez and the Washington Technology CenterPaul Vahey and the Boeing CompanyEef Klok and PAC/AC Analytical ControlsJohn Crandall and Falcon AnalyticalBob Farmer and SiemensJorn Smedsgaard and the Danish Technical UniversityChevron ETC, Infometrix and CPACCPAC Sponsoring CompaniesYou


The Presentation

Mel Koch, CPAC Executive Director, University of WashingtonCarl Rechsteiner, Jr., Senior Staff Scientist, Chevron ETCBrian Rohrback, President, InfoMetrix, Inc.Rob Synovec, CPAC Faculty Director and Professor of Chemistry, University of Washington

For information on the upcoming November meeting, please contact the Center for Process Analytical Chemistry

+1 206 685 2326 or http://www.cpac.washington.edu

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