The product features for PeakFit are detailed below in the following categories:
Data Input
- ASCII
- Excel®
- Lotus 123®
- Quattro Pro®Windows®
- SigmaPlot®
- AIA Chromatography
- dBase ® III+, IV
- DIF
- ASCII and Spreadsheet – like Editors
- Averaging Digital Filter
Data Preparation
- Gaussian Deconvolution to remove Spectrophotometer Instrument Response smearing
- Exponential Deconvolution to remove Chromatographic Detector Response smearing
- Smoothing (Savitsky Golay, FFT Filter, Loess, Gaussian Convolution)
- Real – time FFT/Time Domain Graphical Editor
- Dual Graph Data Sectioning with Graphical data point exclusion
- Non – Parametric Digital Filter to Filter or augment data
- Compare with Reference
- Subtract Baseline Imported from File
- Data Transforms
- Area Normalization
- Inspect Second and Fourth Derivatives
- Data Weighting
Peak Autoplacement
- Automatic by Local Maxima and Residuals
- Automatic by Second Derivatives
- Automatic by Deconvolved Local Maxima
- Graphical Placement and Adjustments
- Manual Parameter Adjustments
- Share and Lock Parameters
- Constant or V ariable Widths and/or Shape in a single step
Non-Linear Curve Fitting
- Marquardt – Levenburg Algorithm
- 83 built-in nonlinear peak models
- Least – Squares and 3 Robust (Maximum Likelihood) methods
- Up to 100 Peaks and 1000 Parameters
- Intelligent Constraints to insure Fit Integrity
- Sparse Curvature Matrix for Faster Fitting
- Both Numeric and Graphical Fitting Options
- Zoom – in or Toggle Points during Fitting
Output and Export Options
- File Export with full Generated Data: Lotus 123, Excel, Quattro Pro Windows, SigmaPlot, and ASCII
- Graphs to clipboard or file in BMP or WMF formats
- All Numeric data in Graph to Clipboard in Spreadsheet Format
PeakFit uses three procedures to automatically place hidden peaks; while each is a strong solution, one method may work better with some data sets than others.
The Residuals procedure initially places peaks by finding local maxima in a smoothed data stream. Hidden peaks are then optionally added where peaks in the residuals occur.
The Second Derivative procedure searches for local minima within a smoothed second derivative data stream. These local minima often reveal hidden peaks.
The Deconvolution procedure uses a Gaussian response function with a Fourier deconvolution / filtering algorithm. A successfully deconvolved spectrum will consist of “sharpened” peaks of equivalent area. The goal is to enhance the hidden peaks so that each represents a local maximum.
Academia Sinica Institute of Chemistry
Academia Sinica Institute of Plant and Microbial Biology,
DuPont Taiwan Limited , Hsinchu Branch Electronics and Communications
National Atomic Research Institute
National Atomic Research Institute Chemical Engineering Division
National Chung Cheng University Department of Earth and Environmental Sciences
National Chung Hsing University Department of Electrical Engineering
National Chin-Yi University of Technology Department of Chemical and Materials Engineering
National Pingtung University of Science and Technology
National Changhua University of Education Department of Physics
National Cheng Kung University Department of Earth Sciences
National Cheng Kung University Faculty of Physical Therapy
National Cheng Kung University Dept. of Environmental Engineering
National Dong-Hwa University Department of Physics
National Dong-Hwa University Department of Natural Resources and Environmental Studies
National Tsing Hua University Department of Applied Chemistry
National Taipei University of Technology Department of Materials and Mineral Resources Engineering
National Taiwan University Joint Center for Instruments and Researches
Industrial Technology Research Institute
Macronix International Co., Ltd. Computer & Communication Dept.
Food Industry Research and Development Institute
Fu Jen Catholic University Department of Physics
Kaohsiung Medical University Department of Medical Imaging and Radiological Sciences
