NMR Spectrum
Chart overview
NMR spectrum plots display signal intensity against chemical shift in parts per million, enabling structural elucidation of organic and inorganic compounds.
Key points
- Researchers annotate multiplet patterns, coupling constants, and integration regions to confirm molecular identity and purity.
- These figures are standard in synthetic chemistry, metabolomics, and pharmaceutical characterization workflows.
Example Visualization
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Generate publication-ready nmr spectrums with AI in seconds. No coding required – just describe your data and let AI do the work.
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"Create an NMR spectrum plot from my data. Plot chemical shift (ppm) on the x-axis (reversed, high to low) and signal intensity on the y-axis. Annotate the tallest peaks with their ppm values, add integration curves above the baseline, and use journal formatting with Arial font, no top or right spines, and a clean baseline at zero."
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Python Code Example
Console Output
Figure saved: plotivy-nmr-spectrum.png
Common Use Cases
- 1Confirming the structure and purity of synthesized organic compounds
- 2Quantifying metabolite concentrations in NMR-based metabolomics studies
- 3Characterizing pharmaceutical active ingredients and impurity profiling
- 4Monitoring reaction progress and conversion rates in real-time NMR experiments
Pro Tips
Reverse the x-axis so chemical shift decreases left to right, matching standard NMR convention
Add a flat baseline subtraction before plotting to reduce baseline drift artifacts
Use scipy.signal.find_peaks to automatically annotate significant peaks with their ppm values
Include a solvent residual peak marker and reference standard (TMS at 0 ppm) for reproducibility
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.