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Raw SEC Unknown Samples with Known Molecular Weights

Source: R/data.R
sec_raw_unknowns.Rd

A dataset containing raw SEC chromatograms of polymer samples with known true molecular weight values for validation. Includes challenging cases like bimodal distributions and high molecular weight aggregates.

Usage

sec_raw_unknowns

Format

A tibble with approximately 65,000 rows and 8 columns:

sample_id

Character. Sample identifier

description

Character. Sample description and type

true_mw

Numeric. Known weight-average MW in Da (NA for bimodal)

true_mn

Numeric. Known number-average MW in Da

true_mz

Numeric. Known z-average MW in Da

true_dispersity

Numeric. Known dispersity (Mw/Mn)

time_min

Numeric. Elution time in minutes

ri_mv

Numeric. RI detector signal in millivolts (raw)

Source

Synthetic data generated for package tutorials.

Details

This dataset provides unknown samples with known "true" MW values, enabling validation of the complete SEC workflow from raw data to final results.

Sample Types:

  • Unknown-A: Broad distribution (dispersity ~2.0)

  • Unknown-B: Medium dispersity (~1.3)

  • Unknown-C: Narrow distribution (~1.1) for accuracy check

  • Unknown-Bimodal: Two-peak mixture (50K + 200K)

  • Unknown-HMW: Very high MW (~1.5M) with aggregate shoulder

  • Unknown-LMW: Low MW oligomers (~3.5K)

Educational Value: Students can compare their calculated MW values against the true values to validate their analysis workflow and understand sources of error.

See also

sec_raw_standards for calibration standards step_sec_mw_averages for MW calculation

Other sec-data: sec_branched, sec_calibration_standards, sec_copolymer, sec_pmma_standards, sec_protein, sec_ps_standards, sec_raw_multidetector, sec_raw_standards, sec_system_suitability, sec_triple_detect

Other sec-raw: sec_raw_multidetector, sec_raw_standards

Examples

data(sec_raw_unknowns)

# View sample information
unique(sec_raw_unknowns[,
  c("sample_id", "description", "true_mw", "true_dispersity")])
#> # A tibble: 6 × 4
#>   sample_id       description                   true_mw true_dispersity
#>   <chr>           <chr>                           <dbl>           <dbl>
#> 1 Unknown-A       Broad distribution PMMA-like    45000            2.05
#> 2 Unknown-B       Medium dispersity PS-like      125000            1.32
#> 3 Unknown-C       Narrow distribution reference   82000            1.09
#> 4 Unknown-Bimodal Bimodal mixture (50K + 200K)       NA           NA   
#> 5 Unknown-HMW     Very high MW with aggregates  1500000            1.25
#> 6 Unknown-LMW     Low MW oligomer region           3500            1.25

# Plot the bimodal sample
if (requireNamespace("ggplot2", quietly = TRUE)) {
  library(ggplot2)
  library(dplyr)

  sec_raw_unknowns |>
    filter(sample_id == "Unknown-Bimodal") |>
    ggplot(aes(time_min, ri_mv)) +
    geom_line() +
    labs(
      x = "Time (min)",
      y = "RI Signal (mV)",
      title = "Bimodal Distribution",
      subtitle = "Mixture of 50K and 200K components"
    ) +
    theme_minimal()
}