A preview of the CPAC Fall Meeting Tutorial
Transcript of A preview of the CPAC Fall Meeting Tutorial
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
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Industry/Academic Cooperation
Mel KochCPAC Executive Director, University of Washington, Seattle, WA
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Center for Process Analytical Chemistry
UNIVERSITY OF WASHINGTON,UNIVERSITY OF WASHINGTON, SEATTLESEATTLE
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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)
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CPAC Sponsor Focus Groups
Oil and Petrochemicals
Chemicals and Materials
Food and Consumer Products
Bio Tech and Pharmaceuticals
Instrument Companies
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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.
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The Commercial Background of Chromatographic Alignment
Brian RohrbackPresident, Infometrix, Inc., Bothell, WA
CPAC Sponsor
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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
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GC: Improving the Data to Information Transition
Falcon MicroFast GCLineUp v. 2
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Initial Commercial Driving Force
7.2 7.4 7.6 7.8 8 8.2 8.4
0
0.25
0.5
0.75
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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?
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54 samples of M. intracellulare (1 lab)
54 samples of M. intracellulare (1 lab)
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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
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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 !
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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
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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
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On-Line Process HPLC
Dionex ChromeleonLineUp v.3
Before Alignment
After Alignment
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Quantitation of trans-fat
Agilent ChemStationLineUp v. 3
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Biodegraded crude oil
Agilent ChemStationLineUp v. 3
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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
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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.
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Background on CPAC Technologies, and our Interest in Developing Chromatographic Alignment
Rob SynovecCPAC Faculty Director and Professor of Chemistry,
University of Washington, Seattle, WA
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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]
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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
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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
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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!
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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
)
4.0 4.1 4.2 4.3 4.4 4.5 4.60
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Retention Time (minutes)
Data Set 1Data Set 2Data Set 3
Sign
al (A
rb. U
nits
)
AFTER
Retention Time (minutes)4.0 4.1 4.2 4.3 4.4 4.5 4.6
0
1
2
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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
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0
1
2
3
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7
8
6960 6980 7000 7020 7040 7060 70800
1
2
5320 5340 5360 5380 5400 5420 5440 5460
0
0.5
1
1.5
2
2.5-4
-2
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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
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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
T
T
TTTTTTT
AA
A AAAA
A
AA M
M
MMMMM
MMM SSS
S
SS
S
SS
S
TT
T
TTTTTT
T
AA
A AAA
A AA
A
MM
MMMM
MMMM
SS
S
SS
S
SSSST
TTTTTT
TT
T
AAAA
AA
A
AAA
M
M
MM
MM
MMM MSSS
SSSS
SSS
TTTTTT
TTT
T
A
AAA
AAAAAA
MMMMMMM
MM
MSSS
SSSSSS
S
TTTTT
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:
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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
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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
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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)
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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.
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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.
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Customer PerspectiveImplementing Alignment with a Process GC Focus
Carl Rechsteiner, Jr.Chevron ETC, Richmond, CA
Chairman, CPAC Industrial Advisory Board
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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, …
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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!
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GC Systems for Process Monitoring(Agilent, Falcon Analytical, Siemens, SLS Micro)
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Prototype System with Process Compatible Sample Handling System
Inlet
OutletWaste
Falcon MicroFast GC
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Multifunction System
Expansion
Area
For
Additional
Analyzer(s)
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Petrochemical Process GC Applications
Gas composition (including BTU value)Speciation of small hydrocarbon moleculesStream Fingerprints
HydrocarbonHeteroatom (Sulfur, Nitrogen)
Yield Curves
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Attainable Product Yield Distribution
Crude Oil Composition MapTBP Curves
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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
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The Alignment Advantage
Seeing process detail
that would otherwise be missed.
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On-line Simulated Distillation
400 Samples Un-Aligned
Same Samples Aligned
Siemens Maxum II
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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
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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
)
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The case for alignment - 1
Unaligned Chromatograms
0
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0.15
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0.35
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0.45
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0 5 10 15 20 25 30 35 40
Retention Tim e , m in
% o
f Sig
nal
0.2
0.25
0.3
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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
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The case for alignment - 2
Chemometric Aligned Chromatograms
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Re te ntion tim e , m in
Sig
nal,
arbi
trar
y un
its
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400
15 16 17 18 19 20Ret ent i on t i me, mi n
Agilent 6890 ChemStationLineUp v. 3
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The case for alignment - 3
Data BiasAverage Yield Curve Comparison
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400 500 600 700 800 900 1000 1100Boiling Point, deg. F
Yiel
d, w
t %
BPAligned
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The case for alignment - 4
0
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Yie
ld, w
t %
BPAligned
Data Bias - Closeups
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770 780 790 800 810 820Boiling Point, deg. F
Yiel
d, w
t %
BPAligned
858687888990919293949596979899
100
900 910 920 930 940 950 960 970 980 990 1000 1010 1020 1030 1040 1050Boiling Point, deg. F
Yie
ld, w
t %
BPAligned
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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.
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Conclusions and Questions
Brian RohrbackPresident, Infometrix, Inc., Bothell, WA
CPAC Sponsor
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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
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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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