#' AVS -> SHE #' #' Converts from absolute vacuum scale (AVS) to SHE scale #' #' @param avs Potential in AVS scale #' #' @return potential in SHE scale (numeric) #' @export AVS2SHE <- function(avs) { .Deprecated("as.SHE") she <- -(4.5 + avs) return(she) } #' SHE -> AVS #' #' Converts from SHE scale to absolute vacuum (AVS) scale #' #' @param she Potential in SHE scale #' #' @return potential in AVS scale (numeric) #' @export SHE2AVS <- function(she) { .Deprecated("as.SHE") avs <- -(4.5 + she) return(avs) } #' Get standardised name of reference electrode #' #' Given a reference electrode label, this function returns its canonical name #' (as defined by this package). #' This function tries to match against as many variations as possible for each #' reference electrode. #' The entire point of this function is to decrease the mental load on the user #' by not requiring them to remember a particular label or name for each reference #' electrode, instead almost any sufficiently distinct label or string will still #' be correctly identified. #' #' @param refname string or a vector of strings #' #' @return vector with corresponding "canonical" name or empty string (if none found) #' @export RefCanonicalName <- function(refname) { # scale names electrode.system <- list() electrode.system[["SHE"]] <- c("SHE", "Standard hydrogen", "Standard hydrogen electrode") electrode.system[["AgCl/Ag"]] <- c("AgCl/Ag", "Ag/AgCl", "AgCl", "Silver-Silver chloride", "Silver chloride", "SSC") # saturated silver-silver chloride is sometimes abbreviated SSC electrode.system[["Hg2Cl2/Hg"]] <- c("Hg2Cl2/Hg", "Hg/Hg2Cl2", "Hg2Cl2", "Calomel-Mercury", "Mercury-Calomel", "SCE") electrode.system[["AVS"]] <- c("AVS", "Vacuum", "Vacuum scale", "Absolute", "Absolute scale", "Absolute vacuum scale") electrode.system[["Li"]] <- c("Li", "Li/Li+", "Lithium") # defining refname in this manner makes sure to get all possible combinations # but there might be a number of duplicates, but those we can # get rid of in the next step electrode <- data.frame(refname = # here we create lower-case version of electrode.system, # and version with symbols (-/) subbed with spaces c(unname(unlist(electrode.system)), tolower(unname(unlist(electrode.system))), gsub("[-/]", " ", unname(unlist(electrode.system)))), refcanon = rep(sub("[0-9]$", "", names(unlist(electrode.system))), 3), stringsAsFactors = FALSE) # detect and remove duplicates electrode <- electrode[!duplicated(electrode$refname),] # reset row numbering in dataframe just for good measure row.names(electrode) <- 1:dim(electrode)[1] # pre-allocate the return vector refcanon <- rep("", length(refname)) # now all we have to do is check each user-submitted refname against # electrode$refname and return the value on the same row but next column for (i in 1:length(refname)) { refcanon[i] <- electrode$refcanon[which(electrode$refname == refname[i])] } return(refcanon) } #' Potentials as SHE #' #' This function just outputs a tidy dataframe with potential vs SHE for #' different scales, electrolytes, concentrations, and temperatures. #' Using data from literature. #' #' @return tidy dataframe with the following columns #' \tabular{ll}{ #' \code{electrode} \tab reference electrode \cr #' \code{electrolyte} \tab electrolyte \cr #' \code{conc.num} \tab concentration of electrolyte, mol/L \cr #' \code{conc.string} \tab concentration of electrolyte, as string, may also note temperature at which conc \cr #' \code{temp} \tab temperature / degrees Celsius \cr #' \code{SHE} \tab potential vs SHE / volt \cr #' \code{sid} \tab set id, just for housekeeping inside this function \cr #' \code{reference} \tab BibTeX reference \cr #' \code{dEdT} \tab temperature coefficient / volt/kelvin \cr #' } #' @export potentials.as.SHE <- function() { # scale name should be one of canonical (see RefCanonicalName) # follow the convention of "each row one observation" (at different temperatures) # all potentials vs SHE potentials <- as.data.frame(matrix(data = # electrode # electrolyte # conc/M # conc label # temp # pot vs SHE # set id # ref c("AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "10", "0.215", "1", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "15", "0.212", "1", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "20", "0.208", "1", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "25", "0.205", "1", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "30", "0.201", "1", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "35", "0.197", "1", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "40", "0.193", "1", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "4.2", "saturated", "10", "0.214", "2", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "4.2", "saturated", "15", "0.209", "2", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "4.2", "saturated", "20", "0.204", "2", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "4.2", "saturated", "25", "0.199", "2", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "4.2", "saturated", "30", "0.194", "2", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "4.2", "saturated", "35", "0.189", "2", "Sawyer1995", "AgCl/Ag", "KCl(aq)", "4.2", "saturated", "40", "0.184", "2", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "10", "0.336", "3", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "15", "0.336", "3", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "20", "0.336", "3", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "25", "0.336", "3", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "30", "0.335", "3", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "35", "0.334", "3", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "40", "0.334", "3", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "1.0", "1.0M at 25C", "10", "0.287", "4", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "1.0", "1.0M at 25C", "20", "0.284", "4", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "1.0", "1.0M at 25C", "25", "0.283", "4", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "1.0", "1.0M at 25C", "30", "0.282", "4", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "1.0", "1.0M at 25C", "40", "0.278", "4", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "10", "0.256", "5", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "15", "0.254", "5", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "20", "0.252", "5", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "25", "0.250", "5", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "30", "0.248", "5", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "35", "0.246", "5", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "40", "0.244", "5", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "10", "0.254", "6", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "15", "0.251", "6", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "20", "0.248", "6", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "25", "0.244", "6", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "30", "0.241", "6", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "35", "0.238", "6", "Sawyer1995", "Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "40", "0.234", "6", "Sawyer1995", "AVS", "", "", "", "25", "-4.44", "7", "Trasatti1986"), ncol = 8, byrow = TRUE), stringsAsFactors = FALSE) colnames(potentials) <- c("electrode", "electrolyte", "conc.num", "conc.string", "temp", "SHE", "sid", "reference") # convert these columns to type numeric potentials[, c("conc.num", "temp", "SHE")] <- as.numeric(as.character(unlist(potentials[, c("conc.num", "temp", "SHE")]))) # make room for a dE/dT column potentials$dEdT <- as.numeric(NA) # calculate temperature coefficient (dE/dT) for each scale and concentration (ie. set id) for (s in 1:length(unique(potentials$sid))) { # sid column eas added to data just to make this calculation here easier subspot <- potentials[which(potentials$sid == unique(potentials$sid)[s]), ] # a linear fit will give us temperature coefficient as slope lm.subspot <- stats::lm(SHE ~ temp, data = subspot) potentials[which(potentials$sid == unique(potentials$sid)[s]), "dEdT"] <- lm.subspot$coefficients[2] } return(potentials) } #' Convert from electrochemical or electronic scale to SHE #' #' Convert an arbitrary number of potentials against any known electrochemical #' scale (or the electronic vacuum scale) to potential vs SHE. #' #' @param potential potential in volt #' @param scale name of the original scale #' @param concentration of electrolyte in mol/L, or as the string "saturated" #' @param temperature of system in degrees Celsius #' @param as.SHE.data dataframe with dataset #' #' @return potential in SHE scale #' @export as.SHE <- function(potential, scale, concentration = "saturated", temperature = 25, as.SHE.data = potentials.as.SHE()) { # if the supplied temperature does not exist in the data, this function will attempt to interpolate # note that concentration has to match, no interpolation is attempted for conc # make this work for arbitrary-length vectors of potential and scale # make sure potential and scale args have the same length if (length(potential) == 0 | length(scale) == 0) { stop("Arguments potential or scale cannot be empty!") } else if (length(potential) != length(scale)) { stop("Arguments potential and scale must have equal number of elements") } arglength <- length(potential) # make the concentration and temperature args to this same length, # unless the user supplied them (only necessary for > 1) if (arglength > 1) { # handle two cases: # 1. user did not touch concentration or temperature args. # Assume they forgot and reset their length and print a message # 2. user did change concentration or temperature, but still failed to # ensure length equal to arglength. In this case, abort. # note: we can get the default value set in the function call using formals() if (identical(concentration, formals(as.SHE)$concentration) & identical(temperature, formals(as.SHE)$temperature)) { # case 1 # message("NOTE: default concentration and temperature values used for all potentials and scales.") message(paste0("Default concentration (", formals(as.SHE)$concentration, ") and default temperature (", formals(as.SHE)$temperature, "C) used for all supplied potential and scale values.")) concentration <- rep(concentration, arglength) temperature <- rep(temperature, arglength) } else { # case 2 stop("Arguments concentration and temperature must have same number of elements as potential and scale!") } } ## we can now safely assume that length() == arglength # place args into a single dataframe # this way, we can correlate columns to each other by row df <- data.frame(potential = potential, scale = RefCanonicalName(scale), concentration = concentration, temperature = temperature, stringsAsFactors = FALSE) # add column to keep track of vacuum scale df$vacuum <- as.logical(FALSE) # add column to hold calc potential vs SHE df$SHE <- as.numeric(NA) # AVS scale special considerations # 1. concentration is meaningless # 2. direction is opposite of electrochemical scales, requiring change of sign if (any(df$scale == RefCanonicalName("AVS"))) { # concentration is meaningless for AVS (no electrolyte) # so for those rows, we'll reset it df$concentration[which(df$scale == RefCanonicalName("AVS"))] <- "" df$vacuum[which(df$scale == RefCanonicalName("AVS"))] <- TRUE } # now just work our way through df, line-by-line to determine potential as SHE # all necessary conditions should be recorded right here in df for (p in 1:dim(df)[1]) { if (is.character(df$concentration[p])) { subset.SHE.data <- subset(subset(as.SHE.data, conc.string == df$concentration[p]), electrode == df$scale[p]) } else { subset.SHE.data <- subset(subset(as.SHE.data, conc.num == df$concentration[p]), electrode == df$scale[p]) } # temperature # either happens to match a temperature in the dataset, or we interpolate # (under the assumption that potential varies linearly with temperature) if (!any(subset.SHE.data$temp == df$temperature[p])) { # sought temperature was not available in dataset, check that it falls inside if ((df$temperature[p] < max(subset.SHE.data$temp)) && (df$temperature[p] > min(subset.SHE.data$temp))) { # within dataset range, do linear interpolation lm.subset <- stats::lm(SHE ~ temp, data = subset.SHE.data) # interpolated temperature, calculated based on linear regression # (more accurate than simple linear interpolation with approx()) pot.interp <- lm.subset$coefficients[2] * df$temperature[p] + lm.subset$coefficients[1] ### CALC POTENTIAL vs SHE df$SHE[p] <- ifelse(df$vacuum[p], pot.interp - df$potential[p], pot.interp + df$potential[p]) } } else { # requested temperature does exist in dataset ### CALC POTENTIAL vs SHE df$SHE[p] <- ifelse(df$vacuum[p], subset(subset.SHE.data, temp == df$temperature[p])$SHE - df$potential[p], subset(subset.SHE.data, temp == df$temperature[p])$SHE + df$potential[p]) } } return(df$SHE) } #' ConvertRefPotEC #' #' This function does the heavy lifting. #' Converts from an electrochemical reference scale into another. #' SHE: standard hydrogen electrode #' Ag/AgCl: silver silver-chloride electrode (3M KCl) #' SCE: saturated calomel electrode #' #' @param argpotential potential (numeric) #' @param argrefscale input reference scale (character string) #' @param valuerefscale output reference scale (character string) #' #' @return potential in output reference scale (numeric) ConvertRefPotEC <- function(argpotential, argrefscale, valuerefscale) { .Deprecated("as.SHE") ##### Add more reference electrodes here >> refpotatSHEzero <- c( 0, -0.21, -0.24, 3) refrownames <- c( "SHE", "Ag/AgCl", "SCE", "Li/Li+") refcolnames <- c("SHE0", "AgCl0", "SCE0", "Li0") ##### Add more reference electrodes here << # SHE0 <- data.frame(matrix(refpotatSHEzero, ncol = length(refpotatSHEzero), byrow = T)) refpotmtx <- matrix(NA, length(SHE0), length(SHE0)) refpotmtx[,1] <- matrix(as.matrix(SHE0), ncol = 1, byrow = T) for (c in 2:length(SHE0)) { # loop over columns (except the first) for (r in 1:length(SHE0)) { # loop over rows refpotmtx[r, c] <- refpotmtx[r, 1] - refpotmtx[c, 1] } } refpotdf <- as.data.frame(refpotmtx) names(refpotdf) <- refcolnames row.names(refpotdf) <- refrownames ## So far we have made a matrix of all the possible combinations, ## given the vector refpotatSHEzero. The matrix is not strictly necessary, ## but it may prove useful later. It does. # # Match argrefscale to the refrownames argmatch <- match(argrefscale, refrownames, nomatch = 0) # Match valuerefscale to the refrownames valuematch <- match(valuerefscale, refrownames, nomatch = 0) # We simply assume that the match was well-behaved valuepotential <- argpotential + refpotdf[valuematch, argmatch] # Check that arg and value electrodes are within bounds for a match if (argmatch == 0 || valuematch == 0) { # No match # Perform suitable action message("Arg out of bounds in call to ConvertRefPot") valuepotential <- NA } return(valuepotential) } #' Convert from one electrochemical scale to another #' #' @param argpotential potential (numeric) #' @param argrefscale input reference scale (char string) #' @param valuerefscale output reference scale (char string) #' #' @return potential in output reference scale (numeric) #' @export ConvertRefPot <- function(argpotential, argrefscale, valuerefscale) { .Deprecated("as.SHE") # You should check that argpotential is valid numeric # IDEA: make a matrix out of these (scale names and flags) # Valid scales scale.names <- list() scale.names[["SHE"]] <- c("SHE", "NHE", "she", "nhe") scale.names[["AgCl"]] <- c("Ag/AgCl", "AgCl", "ag/agcl", "agcl") scale.names[["SCE"]] <- c("SCE", "sce") scale.names[["Li"]] <- c("Li/Li+", "Li", "Li+", "li", "li+", "li/li+") scale.names[["AVS"]] <- c("AVS", "avs") # Set flags bool.flags <- as.data.frame(matrix(0, nrow = length(scale.names), ncol = 2)) names(bool.flags) <- c("argref", "valueref") row.names(bool.flags) <- names(scale.names) # argrefscale # Check that argrefscale is valid character mode # ... # steps through all scale names, "row-by-row", # looking for any cell matching "argrefscale" string # if found, save the position of that refelectrode (in scale.names) to # that row and "argref" column of bool.flags for (j in 1:length(row.names(bool.flags))) { if (any(scale.names[[row.names(bool.flags)[j]]] == argrefscale)) { bool.flags[row.names(bool.flags)[j], "argref"] <- j } } # valuerefscale # Check that valuerefscale is valid character mode # ... for (k in 1:length(row.names(bool.flags))) { if (any(scale.names[[row.names(bool.flags)[k]]] == valuerefscale)) { bool.flags[row.names(bool.flags)[k], "valueref"] <- k } } # Depending on which flags are set, call the corresponding function decision.vector <- colSums(bool.flags) # Check if both scales are the same (no conversion needed). If so, abort gracefully. # ... if (decision.vector["argref"] == 5 || decision.vector["valueref"] == 5) { # AVS is requested, deal with it it if (decision.vector["argref"] == 5) { # Conversion _from_ AVS rnpotential <- ConvertRefPotEC(AVS2SHE(argpotential), "SHE", scale.names[[decision.vector["valueref"]]][1]) } if (decision.vector["valueref"] == 5) { # Conversion _to_ AVS rnpotential <- SHE2AVS(ConvertRefPotEC(argpotential, scale.names[[decision.vector["argref"]]][1], "SHE")) } } else { rnpotential <- ConvertRefPotEC(argpotential, scale.names[[decision.vector["argref"]]][1], scale.names[[decision.vector["valueref"]]][1]) } return(rnpotential) }