PeakFit & PeakLab
Explore product guidance, troubleshooting, FAQs, workflows, and practical solutions for PeakFit and PeakLab.
Explore PeakFit & PeakLabBoth PeakLab and TableCurve Studio serve distinct analytical needs within each industry. Explore their applications separately to discover how each product supports your field.
Product Support
Find product documentation, practical guidance, troubleshooting tips, and answers to common questions.
Explore product guidance, troubleshooting, FAQs, workflows, and practical solutions for PeakFit and PeakLab.
Explore PeakFit & PeakLabFind product guidance, troubleshooting information, FAQs, and useful solutions for TableCurve products.
Explore TableCurveFrom pharmaceutical research to environmental analysis, R²N Software supports a wide range of analytical workflows. Select your industry to explore relevant applications for PeakLab and TableCurve Studio.
Analyze experimental measurements, characterize analytical peaks, and evaluate mathematical relationships in pharmaceutical and biotechnology research.
Analyze experimental peaks and model measured signals in laboratory research.
Fit mathematical equations to experimental measurements and evaluate quantitative relationships.
Work with measured signals, characterize analytical peaks, and fit mathematical relationships to spectroscopy datasets.
Support peak analysis and mathematical modeling of measured analytical signals.
Evaluate mathematical equations and fit curves to measured spectroscopy data.
Examine chromatographic peaks, model analytical signals, and develop mathematical fits for measured laboratory data.
Investigate peak shapes and analyze measured analytical signals.
Develop mathematical relationships from measured chromatographic datasets.
Analyze environmental measurements, identify patterns in experimental signals, and model relationships in scientific data.
Analyze measured signals and characterize peaks in environmental research datasets.
Evaluate mathematical relationships in environmental measurements and experimental datasets.
Explore measured material properties, analyze experimental signals, and fit mathematical models to laboratory data.
Characterize peaks and investigate experimental signals in materials research.
Fit equations to measured material properties and evaluate mathematical relationships.
Work with experimental food-science measurements, characterize analytical signals, and evaluate quantitative relationships.
Analyze measured signals and investigate peak characteristics in laboratory experiments.
Develop mathematical fits for experimental food-science and beverage-analysis datasets.
Evaluate process measurements, analyze experimental signals, and fit mathematical equations to measured process data.
Characterize measured peaks and analyze experimental signals from laboratory workflows.
Fit mathematical equations to process measurements and investigate relationships between variables.
Support scientific investigations through experimental signal analysis, curve fitting, and mathematical modeling of research datasets.
Explore peak characteristics and fit mathematical models to experimental signals.
Fit mathematical equations to research data and evaluate relationships between measured variables.