Plot Molecular Weight Distribution

Creates a molecular weight distribution (MWD) plot showing differential or cumulative distribution.

Usage

plot_sec_mwd(
  data,
  mw_col = "mw",
  concentration_col = NULL,
  sample_id = NULL,
  type = c("differential", "cumulative", "both"),
  show_averages = TRUE,
  log_mw = TRUE,
  x_label = NULL,
  y_label = NULL,
  ...
)

Arguments

data

A data frame containing SEC results with calibrated MW data.

mw_col

Name of the molecular weight measure column. Default is "mw".

concentration_col

Name of the concentration/signal column used for weighting. If NULL, uses the first available measure column.

sample_id

Column name containing sample identifiers.

type

Type of distribution to plot:

• "differential": dW/d(log M) vs log M (default)

• "cumulative": Cumulative weight fraction vs log M

• "both": Both on faceted plot

show_averages

Logical. Show vertical lines for Mn, Mw, Mz? Default is TRUE. Requires these columns to be present in data.

log_mw

Logical. Use log10(MW) on x-axis? Default is TRUE.

x_label

Label for x-axis. Default is auto-generated based on log_mw.

y_label

Label for y-axis. Default is auto-generated based on type.

...

Additional arguments passed to ggplot2::geom_line().

Value

A ggplot2 object.

Details

The MWD plot is the standard way to visualize polymer molecular weight distributions. The differential distribution (dW/d log M) shows the weight fraction of polymer at each molecular weight.

When show_averages = TRUE, vertical dashed lines are added for:

• Mn (number-average): leftmost

• Mw (weight-average): middle

• Mz (z-average): rightmost

See also

Other sec-visualization: autoplot.sec_results(), plot_sec(), plot_sec_calibration(), plot_sec_chromatogram(), plot_sec_composition(), plot_sec_conformation(), plot_sec_multidetector(), sec_results()

Examples

if (FALSE) { # \dontrun{
# After SEC processing with calibration
plot_sec_mwd(processed_data)

# Cumulative distribution
plot_sec_mwd(processed_data, type = "cumulative")

# Without MW average lines
plot_sec_mwd(processed_data, show_averages = FALSE)
} # }