add comparison to experiment

analyses/Makefile

@@ -5,6 +5,7 @@ all:
 	python plot_pot_DH.py -o ../Figure11.pdf
 	python  plot_cplx_Kx1.py -o ../Figure12.pdf
 	python  plot_cplx_Kx2.py -o ../Figure14.pdf
+	python  plot_pot_exp.py -o ../Figure15.pdf
 	python plot_DH.py -o ../FigureS1.pdf
 	python plot_CIP.py -o ../FigureS2.pdf
 	python plot_pairs.py -o ../FigureS3.pdf

analyses/plot_pot_er.py

@@ -58,7 +58,7 @@ def plot_corr_Er(ax, data: pandas.DataFrame, column: str):
 
     x = numpy.array([-.2, 1.5])
     ax.plot(x, result.slope*x + result.intercept, 'k--')
-    ax.text(1.2,  1.2*result.slope+result.intercept+.05, '$R^2$={:.3f}'.format(result.rvalue **2))
+    ax.text(1.2,  1.2*result.slope+result.intercept+.05, '$R^2$={:.2f}'.format(result.rvalue **2))
 
 def make_table(f, data: pandas.DataFrame, solvent: str):
     subdata = data[(data['solvent'] == solvent) & data['px'].notnull()]

analyses/plot_pot_exp.py

@@ -1,9 +1,9 @@
 import pandas
 import matplotlib.pyplot as plt
 import numpy
-import sys
 import pathlib
 import argparse
+import scipy
 
 from nitroxides.commons import dG_DH, AU_TO_ANG, LabelPositioner, AU_TO_EV, EPSILON_R, E_SHE
 
@@ -12,6 +12,8 @@
 LABELS_KWARGS = {'water': [], 'acetonitrile': []}
 LABELS_PATH = {'water': pathlib.Path('pot_exp_water.pos'), 'acetonitrile': pathlib.Path('pot_exp_acetonitrile.pos')}
 
+EXCLUDE = [57, 51, 59]
+
 def prepare_data(data: pandas.DataFrame, data_exp: pandas.DataFrame, solvent):
     subdata = data[data['solvent'] == solvent]
     subdata.insert(1, 'compound', [int(n.replace('mol_', '')) for n in subdata['name']])
@@ -25,15 +27,27 @@ def prepare_data(data: pandas.DataFrame, data_exp: pandas.DataFrame, solvent):
     return subdata[['compound', 'family', 'E_ox_theo_{}'.format(solvent), 'E_ox_exp_{}'.format(solvent)]]
 
 
-def plot_solv(ax, data: pandas.DataFrame, solvent: str, family: str, color: str):
+def plot_exp_vs_theo(ax, data: pandas.DataFrame, solvent: str, family: str, color: str):
     subdata = data[data['family'] == family]
-    ax.plot(subdata['E_ox_theo_{}'.format(solvent)], subdata['E_ox_exp_{}'.format(solvent)], 'o', color=color, label=family.replace('Family.', ''))
+
+    ax.plot(subdata[~subdata['compound'].isin(EXCLUDE)]['E_ox_theo_{}'.format(solvent)], subdata[~subdata['compound'].isin(EXCLUDE)]['E_ox_exp_{}'.format(solvent)], 'o', color=color, label=family.replace('Family.', ''))
+    ax.plot(subdata[subdata['compound'].isin(EXCLUDE)]['E_ox_theo_{}'.format(solvent)], subdata[subdata['compound'].isin(EXCLUDE)]['E_ox_exp_{}'.format(solvent)], '^', color=color)
 
     for name, etheo, eexp in zip(subdata['compound'], subdata['E_ox_theo_{}'.format(solvent)], subdata['E_ox_exp_{}'.format(solvent)]):
         LABELS[solvent].append(name)
         POINTS_POSITION[solvent].append((etheo, eexp))
         LABELS_KWARGS[solvent].append(dict(color=color, ha='center', va='center'))
 
+def plot_corr(ax, data: pandas.DataFrame, solvent: str):
+    x, y = data[~data['compound'].isin(EXCLUDE)]['E_ox_theo_{}'.format(solvent)], data[~data['compound'].isin(EXCLUDE)]['E_ox_exp_{}'.format(solvent)]
+    result = scipy.stats.linregress(x, y)
+
+    x = numpy.array( [x.min(), x.max()])
+    ax.plot(x, result.slope*x + result.intercept, 'k--')
+
+    x = .9 * x.min()+ .1 * x.max()
+    ax.text(x + .05, result.slope*x + result.intercept, '{:.2f} $\\times E^0_{{rel}}$ + {:.2f} ($R^2$={:.2f})'.format(result.slope, result.intercept,result.rvalue **2))
+
 parser = argparse.ArgumentParser()
 parser.add_argument('-i', '--input', default='../data/Data_pot.csv')
 parser.add_argument('-i2', '--input2', default='../data/Data_pot_ox_exp.csv')
@@ -50,10 +64,10 @@ def plot_solv(ax, data: pandas.DataFrame, solvent: str, family: str, color: str)
 
 subdata_wa = prepare_data(data, data_exp, 'water')
 
-plot_solv(ax1, subdata_wa, 'water', 'Family.P6O', 'tab:blue')
-plot_solv(ax1, subdata_wa, 'water', 'Family.P5O', 'black')
-plot_solv(ax1, subdata_wa, 'water', 'Family.IIO', 'tab:green')
-plot_solv(ax1, subdata_wa, 'water', 'Family.APO', 'tab:red')
+plot_exp_vs_theo(ax1, subdata_wa, 'water', 'Family.P6O', 'tab:blue')
+plot_exp_vs_theo(ax1, subdata_wa, 'water', 'Family.P5O', 'black')
+
+plot_corr(ax1, subdata_wa, 'water')
 
 positioner = LabelPositioner.from_file(
     LABELS_PATH['water'], 
@@ -70,10 +84,12 @@ def plot_solv(ax, data: pandas.DataFrame, solvent: str, family: str, color: str)
 
 subdata_ac = prepare_data(data, data_exp, 'acetonitrile')
 
-plot_solv(ax2, subdata_ac, 'acetonitrile', 'Family.P6O', 'tab:blue')
-plot_solv(ax2, subdata_ac, 'acetonitrile', 'Family.P5O', 'black')
-plot_solv(ax2, subdata_ac, 'acetonitrile', 'Family.IIO', 'tab:green')
-plot_solv(ax2, subdata_ac, 'acetonitrile', 'Family.APO', 'tab:red')
+plot_exp_vs_theo(ax2, subdata_ac, 'acetonitrile', 'Family.P6O', 'tab:blue')
+plot_exp_vs_theo(ax2, subdata_ac, 'acetonitrile', 'Family.P5O', 'black')
+plot_exp_vs_theo(ax2, subdata_ac, 'acetonitrile', 'Family.IIO', 'tab:green')
+plot_exp_vs_theo(ax2, subdata_ac, 'acetonitrile', 'Family.APO', 'tab:red')
+
+plot_corr(ax2, subdata_ac, 'acetonitrile')
 
 positioner = LabelPositioner.from_file(
     LABELS_PATH['acetonitrile'], 
@@ -89,7 +105,7 @@ def plot_solv(ax, data: pandas.DataFrame, solvent: str, family: str, color: str)
 positioner.add_labels(ax2)
 
 ax2.legend()
-[ax.set_xlabel('Computed $E^0_{rel}(N^+|N^\\bullet)$ (V)') for ax in (ax1, ax2)]
+[ax.set_xlabel('Computed $E^f_{rel}(N^+|N^\\bullet)$ (V)') for ax in (ax1, ax2)]
 [ax.set_ylabel('Experimental $E^0_{rel}(N^+|N^\\bullet)$ (V)') for ax in (ax1, ax2)]
 
 plt.tight_layout()

analyses/pot_exp_acetonitrile.pos

@@ -1,19 +1,18 @@
 ,label,x,y
-0,2,0.4680935077159968,0.8594418754324777
-1,3,0.6439545960905232,0.9210409552501769
-2,6,0.6036618186165716,0.8831986615267781
-3,12,1.0550136279645264,1.0439350103237066
-4,15,0.6913589245753096,0.9689001824640407
-5,58,0.6801081513917642,1.0669201314255197
-6,59,0.6169599394688117,1.1196364265892487
-7,23,0.7327546768346744,1.0489587543163594
-8,24,0.6997123735820899,1.0874421903982037
-9,25,0.6198603364371229,0.9866235026213223
-10,26,0.6612309560168483,1.0396392139706785
-11,27,0.7295318298715,1.0224152622354148
-12,33,0.7587245534809859,1.1324619587319071
-13,60,0.7319340873284088,1.108044942792472
-14,36,0.6294585922569756,1.0136200239602362
-15,51,0.5578921008197629,1.0978687639014926
-16,54,0.8277120644383962,1.1006498045499185
-17,55,0.9003717940513294,1.174913327540382
+0,2,0.4690266249288662,0.859081244166761
+1,3,0.6343912236494678,0.9157974678380149
+2,6,0.5992297345607707,0.8849237142051551
+4,15,0.6837604652279913,0.9674513602953603
+5,58,0.6797114400066084,1.0670537994468983
+6,59,0.6210885637215627,1.1191424222936612
+7,23,0.7325522988546151,1.0493883712399428
+8,24,0.7009509105263972,1.0871021588452765
+9,25,0.6211631429760444,0.9854917885641445
+10,26,0.6619975365945193,1.0396035871674212
+11,27,0.7288369184936319,1.0221615244457485
+12,33,0.7656753550588773,1.1317584301052221
+13,60,0.7331680892657321,1.1082271147017304
+14,36,0.6281568278773575,1.0122832478759587
+15,51,0.5656911426336507,1.095305148041645
+16,54,0.8233712020976975,1.102970580880633
+17,55,0.87724271534739,1.1840937215347163

analyses/pot_exp_water.pos

@@ -1,13 +1,13 @@
 ,label,x,y
-0,2,0.7949327362078152,0.7376816053671381
-1,3,0.8898290033605948,0.7952384213698037
-2,4,0.8380103476415318,0.8239135472829964
-3,6,0.9085014996557057,0.8194968402375304
-4,11,0.9874868767730546,0.8977130186435169
-5,12,1.0202732112554556,0.9096094338356219
-6,13,0.8552511446851506,0.7849584387222813
-7,15,0.9678577839521213,0.8606063310498585
-8,18,0.8715024756939583,0.8228390387477847
-9,56,0.9078762625552546,0.8736811364414723
-10,57,0.7905139321632375,0.8438830125519429
-11,58,1.0203076221477898,0.9647924240975598
+0,2,0.794674791650889,0.740220285621926
+1,3,0.8911611380622928,0.79538892618509
+2,4,0.8374360046205728,0.8231279014346508
+3,6,0.909627856140639,0.8216567188352355
+4,11,0.9881780343265377,0.8984453067635239
+5,12,1.0204190523174443,0.9096382200218576
+6,13,0.8501027693905805,0.7870820063601331
+7,15,0.961764890264702,0.8668855060419954
+8,18,0.874391737931688,0.8205484453858627
+9,56,0.9096947941871378,0.8706542754568355
+10,57,0.7960746568967588,0.8503775551674212
+11,58,1.029958564096185,0.9478428681455665

data/Data_pot.csv

@@ -2,7 +2,6 @@ name,family,z,hammet,r,px,Qxx,method,has_cation,has_anion,solvent_model,solvent,
 mol_02,Family.P6O,0,,2.87,-0.1172,-0.0856,wB97XD/6-311+G(d),False,False,SMD,acetonitrile,4.99063120812876,2.3210944512185,3.32916564365692,3.29958300239661,3.34822905687088
 mol_03,Family.P6O,0,0.45,2.866,0.7391,4.5213,wB97XD/6-311+G(d),False,False,SMD,acetonitrile,5.14774539378464,2.37074296708237,3.91778024431751,3.90516091331277,3.89547245951191
 mol_06,Family.P6O,0,-0.37,2.874,1.8435,-3.2481,wB97XD/6-311+G(d),False,False,SMD,acetonitrile,5.11303957390658,2.36762959889671,3.31005080550692,3.30092734535027,3.3459604053747
-mol_12,Family.P6O,0,0.5,2.833,3.2454,-1.9312,wB97XD/6-311+G(d),False,False,SMD,acetonitrile,5.58015858695805,2.44469293066752,3.33033116108693,3.31017703491598,3.34491793685276
 mol_15,Family.P5O,0,0.37,2.198,0.7393,2.9804,wB97XD/6-311+G(d),False,False,SMD,acetonitrile,5.20270985569746,2.3006833128675,3.58373884455652,3.80851721612492,3.73623533859462
 mol_23,Family.IIO,0,,2.186,0.4422,3.6909,wB97XD/6-311+G(d),False,False,SMD,acetonitrile,5.2363322641835,2.33018096854232,3.61257836978602,3.59645024506954,3.62134710511788
 mol_24,Family.IIO,0,,2.185,1.5472,10.5503,wB97XD/6-311+G(d),False,False,SMD,acetonitrile,5.27008279686026,2.36554193768737,4.58957688878232,4.57019988616966,4.62107425713651

nitroxides.tex

@@ -409,7 +409,7 @@ \subsection{Structure-activity relationships} \label{sec:sar}
 
 Regarding the impact of substituents, it is noteworthy that non-substituted nitroxides within each family (\textit{i.e.}, \textbf{2}, \textbf{14}, \textbf{23}, and \textbf{36}) generally have some of the lowest oxidation and reduction potentials within their respective groups. Several trends emerge based on the nature of the substituent: \begin{inparaenum}[(i)]
 	\item shielding the radical center with ethyl groups instead of methyl groups (\textbf{7}, \textbf{19}, and \textbf{28}) results in a decrease in potentials (particularly the reduction potential), likely due to changes in inductive effects,
-	\item protonation of \ce{NH2} increases the potentials, especially in P5O,
+	\item protonation of \ce{NH2} (\textit{e.g.}, \textbf{4} vs \textbf{11}) increases the potentials, especially in P5O,
 	\item multiple substitutions by COOH (\textit{e.g.}, \textbf{8} vs. \textbf{9} and \textbf{10}) also increase the potentials, though the effect is less pronounced in IIO and APO,
 	\item compounds with mesomeric donor substituents (\ce{NH2}, \ce{OH}, \ce{OMe}) have lower potentials than those with acceptor substituents (COOH, \ce{NO2}), particularly in aromatic systems (IIO and APO), and
 	\item compounds \textbf{56} and \textbf{58} have surprisingly low reduction potentials.
@@ -502,12 +502,22 @@ \subsection{Impact of the electrolytes} \label{sec:elect}
 \clearpage
 \subsection{Comparison to experiment} \label{sec:exp}
 
+A comparison between theoretical (including all corrections discussed above) and experimental oxidation potentials is shown in Fig.~\ref{fig:expvstheo}.\todo{that's not really $E^f$ for the moment ;)} Excluding compounds bearing an \ce{NH2} group (\textbf{51}, \textbf{57}, and \textbf{59}) results in an excellent linear correlation ($R^2>0.9$). The computed potentials for these compounds are higher (by $>\SI{0.1}{\volt}$) than the fit line, suggesting that the amine group might be protonated under the experimental measurement conditions. This is consistent with the other cases (\textit{e.g.}, \textbf{25} vs \textbf{35}) discussed in Section \ref{sec:sar}.
+
+
 \begin{itemize}
 	\item So one can drop $K_{x2}$,
 	\item Impact is small, isn't?
 	\item What about Matsui?
 \end{itemize}
 
+\begin{figure}[!h]
+	\centering
+	\includegraphics[width=\linewidth]{Figure15}
+	\caption{Comparison between experimental ($E^0_{rel} $ vs SHE, from Table S8) and computed relative oxidation potential ($E^f_{rel}$ vs SHE), as computed at the $\omega$B97X-D/6-311+G(d) level in water (left) and acetonitrile (right) using SMD and $[X]=\SI{0.1}{\mole\per\liter}$.  }
+	\label{fig:expvstheo}
+\end{figure}
+
 \clearpage
 \section{Conclusion} \label{sec:conclusion}