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Simulation of Isotropic EPR Spectra Consisting of Several Components

Source: R/eval_sim_EPR_iso_combo.R
eval_sim_EPR_iso_combo.Rd

This is an extension of the "basic" EPR simulation provided by the eval_sim_EPR_iso function, where one can combine several simulated EPR spectra (components), even with (partial) overlay, into one spectrum corresponding to sum of all components. Such processing might be useful for the simulation of EPR spectra with satellites, especially of those consisted of naturally occurring isotopes, like the one presented in Examples.

Usage

eval_sim_EPR_iso_combo(
  g.iso.vec,
  instrum.params = c(Bcf = 3500, Bsw = 200, Npoints = 2048, mwGHz = 9.8),
  B.unit = "G",
  path_to_dsc_par = NULL,
  origin = NULL,
  nuclear.system,
  natur.abund.vec,
  lineSpecs.form = "derivative",
  lineGL.DeltaB,
  lineG.content.vec,
  Intensity.sim = "dIeprSim_over_dB",
  Intensity.sim.coeffs.vec,
  plot.sim.interact = NULL
)

Arguments

g.iso.vec

Numeric vector with all \(g_{\text{iso}}\) values fro each component.

instrum.params

Named numeric vector, containing instrumental parameters required for the simulation =>

Bcf"central field" (magnetic flux density, \(B_{\text{CF}}\))
Bsw"sweep width" (magnetic flux density recording region, \(B_{\text{SW}}\))
Npointsnumber of spectral points (corresponding to resolution) within the "sweep width"
mwGHzapplied microwave frequency in GHz to record the continuous wave (CW) EPR spectrum

Default values are chosen to cover the EPR spectra of common organic radicals. If instrum.params = NULL then parameters must be provided by the path_to_dsc_par as well as by origin arguments.

B.unit

Character string, pointing to unit of magnetic flux density which is to be presented on \(B\)-axis of the EPR spectrum, like "G" (Gauss) or "mT" (millitesla), default: B.unit = "G". THE UNIT MUST BE SHARED ACROSS ALL RELEVANT B-ARGUMENTS like cf and sw within the instrum.params AS WELL AS within THOSE IN lineGL.DeltaB !

path_to_dsc_par

Character string, path (can be also acquired by the file.path) to .DSC/.dsc or .par (depending on the OS, see origin argument) text files including all instrumental parameters from the EPR machine. Default: path_to_dsc_par = NULL in case if the instrum.params is already defined. IF the instrum.params = NULL then BOTH the path_to_dsc_par AS WELL AS the origin MUST BE DEFINED !

origin

Character string, corresponding to software which was used to obtain the EPR spectra on spectrometers, because the files are slightly different, whether they were recorded by the "WinEpr" (origin = "winepr") or by the "Xenon". Default: origin = NULL in case no file is used to extract the parameters (i.e. exactly if path_to_dsc_par = NULL).

nuclear.system

Nested list with the elements corresponding to considered interacting nuclei for each EPR spectral component. For example, the list(list("1H",2,24),NULL,list(list("14N",1,45),list("1H",4,15))) refers to the following components: 1. \(2\times A(\text{1H}) = 24\,\text{MHz}\), 2. single line spectrum without HF structure, 3. \(1\times A(\text{14N}) = 45\,\text{MHz} + 4\times A(\text{1H}) = 15\,\text{MHz}\).

natur.abund.vec

Logical vector, whether to consider natural abundance of the interacting nuclei within the components (see also Examples) like c(TRUE,FALSE,TRUE).

lineSpecs.form

Character string, describing either "derivative" (default) or "integrated" (i.e. "absorption" which can be used as well) line form of the analyzed EPR spectrum/data.

lineGL.DeltaB

Nested list of the Gaussian and Lorentzian linewidths for all individual components like list(list(1,NULL),list(3,NULL),list(1,NULL)).

lineG.content.vec

Numeric vector, corresponding to Gaussian line content for all individual components of the EPR spectrum like 1,1,1 (all spectral components are described by the pure Gaussian line).

Intensity.sim

Character string, pointing to column of simulated EPR intensity within the related output data frame. Default: Intensity.sim = "dIeprSim_over_dB".

Intensity.sim.coeffs.vec

Numeric vector of multiplication coefficients related to EPR component intensities like c(2,10,0.2).

plot.sim.interact

Character string, indicating the interactive plot outputs, to visualize either individual "components" or "sum" of all components. As default, the interactive plot is switched off (plot.sim.interact = NULL).

Value

List of the following data frames and plots in case of plot.sim.interact = NULL =>

df

Long-format data frame with the simulated EPR spectral components A, B, C, ... (e.g. representing the individual radicals) as a categorical variable + magnetic flux density, intensity as well as their sigmoid integral column/variable.

df.areas

Data frame with simulation components A, B, C ...and their corresponding double/single integrals (or areas) and their relative ratios to overall integral sum (weighted_areas).

df.sum

Data frame with the overall intensity (+ magnetic flux density) as well as integral sum from all simulation components.

plot.comps

Overlay plot object with all simulated components with their corresponding intensities defined by Intensity.sim.coeffs.vec.

plot.sum

Plot object displaying the sum of all simulation components.

If plot.sim.interact is activated (i.e. possesses either "components" or "sum" values) interactive plots (based on plotly) are presented either with all individual components or with the overall simulated EPR spectrum sum, respectively.

See also

Other Simulations and Optimization: eval_sim_EPR_iso(), eval_sim_EPR_isoFit(), optim_for_EPR_fitness(), quantify_EPR_Sim_series(), smooth_EPR_Spec_by_npreg()

Examples

## Simulation of EPR spectrum of TEMPO (aminoxyl)
## radical with 13C satellites and hyperfine coupling
## constants A(1 x 14N) = 48 MHz, A(1 x 13C) = 18.2 MHz,
## the latter 13C may appear on 4 different
## positions (methyl carbons) => therefore the overall
## probability to find them is approx. 4,4% (1.1% per one 13C),
## the additional two quaternary α-Carbons are not considered
## see e.g. https://doi.org/10.1016/j.mencom.2014.09.018
sim.tempo.13c <-
eval_sim_EPR_iso_combo(g.iso.vec = c(2.0059,2.0059),
                       nuclear.system = list(list("14N",1,48),
                                             list(list("14N",1,48),
                                                  list("13C",1,18.5)
                                               )
                                            ),
                       natur.abund.vec = c(FALSE,FALSE),
                       lineGL.DeltaB = list(list(1.3,NULL),
                                            list(1.3,NULL)
                                            ),
                       lineG.content.vec = c(1,1),
                       Intensity.sim.coeffs.vec = c(0.956/3,0.044/6))
#
## simulated spectrum/plot:
sim.tempo.13c$plot.sum +
ggplot2::coord_cartesian(xlim = c(3425,3550))

#
## ...and the corresponding data frame:
options(pillar.sigfig = 5) ## prevent rounding
#
tempo.df.sum <- sim.tempo.13c$df.sum
tempo.df.sum[1000:1005, ]
#> # A tibble: 6 × 4
#>   Bsim_mT Bsim_G Sim_sigmoid_Integ dIeprSim_over_dB_Sum
#>     <dbl>  <dbl>             <dbl>                <dbl>
#> 1  349.76 3497.6            2.0450          -1.0048e- 8
#> 2  349.77 3497.7            2.0450          -4.3104e- 9
#> 3  349.78 3497.8            2.0450          -1.8064e- 9
#> 4  349.79 3497.9            2.0450          -7.4638e-10
#> 5  349.80 3498.0            2.0450          -2.9859e-10
#> 6  349.81 3498.1            2.0450          -1.1670e-10
#
## data frame with all components:
sim.tempo.13c$df[1000:1005,]
#> # A tibble: 6 × 5
#> # Groups:   Sim_Components [1]
#>   Sim_Components Bsim_G Bsim_mT dIeprSim_over_dB Sim_sigmoid_Integs
#>   <fct>           <dbl>   <dbl>            <dbl>              <dbl>
#> 1 A              3497.6  349.76      -3.7180e-25             1.9550
#> 2 A              3497.7  349.77      -7.2914e-26             1.9550
#> 3 A              3497.8  349.78      -1.3975e-26             1.9550
#> 4 A              3497.9  349.79      -2.6633e-27             1.9550
#> 5 A              3498.0  349.80      -4.8771e-28             1.9550
#> 6 A              3498.1  349.81      -8.7289e-29             1.9550
#
## areas/integrals
sim.tempo.13c$df.areas
#> # A tibble: 2 × 3
#>   Sim_Components Sim_areas weighted_Sim_areas
#>   <fct>              <dbl>              <dbl>
#> 1 A                2.9327            0.95600 
#> 2 B                0.13497           0.044000