Prerequisite: Load The Molecule From ChemrytIQ

Before opening ChemrytRAM, search the molecule in ChemrytIQ by SMILES, InChI, molecule name, or CAS number. Confirm the correct molecule on the ChemrytIQ page, then open the required Chemryt app from that same molecule context so the selected structure is loaded into the app automatically.

What ChemrytRAM Does

ChemrytRAM uses molecule input and Raman acquisition parameters to generate a simulated Raman spectrum, input summary, predicted peak table, and printable output.

Molecule editor

Draw, load, clear, import ChemrytIQ context, or paste molecular data before prediction.

Measurement parameters

Set laser wavelength, sample state, mode, substrate, normalization, exposure, laser power, range, resolution, accumulations, concentration, temperature, broadening, and solvent.

Output

Review input summary, simulated Raman spectrum, predicted peaks table, and print/PDF output.

Quick Workflow

Load or draw a molecule and confirm the extracted SMILES and molecule summary.
Choose the laser wavelength, sample state, measurement mode, substrate, and normalization method.
Enter exposure time, laser power, spectral range, resolution, accumulations, concentration, temperature, broadening, and solvent.
Run the Raman prediction and review the input summary first for parameter mistakes.
Inspect the simulated spectrum and predicted peak table for diagnostic bands.
Print or export the result for comparison with lab spectra.

Main Areas

Area	What to enter or review	When to use it
Structure	Molecule editor, generated SMILES, formula, mass, and summary.	Use to define the molecule being modeled.
Acquisition	Laser, state, mode, substrate, normalization, exposure, power, range, resolution, and environment.	Use to describe the Raman measurement.
Interpretation	Spectrum, peak table, intensities, and summary.	Use to identify likely Raman-active features.

Tutorial Notes

Choose a laser wavelength commonly used for your sample class, then adjust power to avoid unrealistic heating.
Use broadening and resolution settings to mimic the expected instrument output.
Compare predicted peak positions with measured data as ranges, not exact one-to-one guarantees.
Record sample state and substrate because Raman response can change with crystal form, surface, and matrix.

ML Model / Computation Used

Model or method	What it predicts	Implementation details
Rule-based Raman simulation	Approximate Raman peak positions, intensities, and display-ready spectra.	No deployed ML artifact was found in the ChemrytRAM module. Current documentation should treat output as structure/method-driven simulation and heuristic interpretation.

Good Practice

Use Raman prediction for planning and interpretation. Confirm identity, polymorph, and material decisions with measured Raman spectra and appropriate controls.

Reference Used

This Tutorial page was prepared from the ChemrytLabs reference module: ChemrytRAM.