diff --git a/mbtrack2/impedance/impedance_model.py b/mbtrack2/impedance/impedance_model.py
index 223b634f05d0812858cdaeb6f8f1421cfc30aef6..ebc7b09debed36521c310dd2884f296260d4cce7 100644
--- a/mbtrack2/impedance/impedance_model.py
+++ b/mbtrack2/impedance/impedance_model.py
@@ -5,6 +5,7 @@ Module where the ImpedanceModel class is defined.
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
+from matplotlib import colormaps
 import pickle
 from copy import deepcopy
 from scipy.integrate import trapz
@@ -249,11 +250,11 @@ class ImpedanceModel():
         # manage legend
         Ztype_dict = {"Zlong":0, "Zxdip":1, "Zydip":2, "Zxquad":3, "Zyquad":4}
         scale = [1e-3, 1e-6, 1e-6, 1e-6, 1e-6]
-        label_list =  [r"$Z_{long} \; [k\Omega]$",
-                       r"$\frac{1}{\beta_0} \sum_{j} \beta_{x,j} Z_{x,j}^{Dip} \; [M\Omega/m]$",
-                       r"$\frac{1}{\beta_0} \sum_{j} \beta_{y,j} Z_{y,j}^{Dip} \; [M\Omega/m]$",
-                       r"$\frac{1}{\beta_0} \sum_{j} \beta_{x,j} Z_{x,j}^{Quad} \; [M\Omega/m]$",
-                       r"$\frac{1}{\beta_0} \sum_{j} \beta_{y,j} Z_{y,j}^{Quad} \; [M\Omega/m]$"]
+        label_list =  [r"$Z_\mathrm{long} \; (\mathrm{k}\Omega)$",
+                       r"$\frac{1}{\beta_0} \sum_{j} \beta_{x,j} Z_{x,j}^\mathrm{Dip} \; (\mathrm{M}\Omega/\mathrm{m})$",
+                       r"$\frac{1}{\beta_0} \sum_{j} \beta_{y,j} Z_{y,j}^\mathrm{Dip} \; (\mathrm{M}\Omega/\mathrm{m})$",
+                       r"$\frac{1}{\beta_0} \sum_{j} \beta_{x,j} Z_{x,j}^\mathrm{Quad} \; (\mathrm{M}\Omega/\mathrm{m})$",
+                       r"$\frac{1}{\beta_0} \sum_{j} \beta_{y,j} Z_{y,j}^\mathrm{Quad} \; (\mathrm{M}\Omega/\mathrm{m})$"]
         leg = Ztype_dict[Z_type]
         
         # sort plot by decresing area size        
@@ -277,13 +278,14 @@ class ImpedanceModel():
             legend.append("Spectral density for sigma = " + str(sigma) + " s")
         
         # Main plot
+        colorblind = colormaps['tab10'].colors
         for index in  sorted_index:
             attr = attr_list[index]
             # Set all impedances with common indexes using + zero_impedance
             try:
                 sum_imp = getattr(getattr(self, attr), Z_type) + zero_impedance
                 ax.fill_between(sum_imp.data.index*1e-9, total_imp, 
-                                total_imp + sum_imp.data[component]*scale[leg])
+                                total_imp + sum_imp.data[component]*scale[leg], edgecolor=colorblind[index%10], color=colorblind[index%10])
                 total_imp += sum_imp.data[component]*scale[leg]
                 if attr[:4] == "sum_":
                     legend.append(attr[4:])
@@ -297,8 +299,8 @@ class ImpedanceModel():
             spect = spect/spect.max()*total_imp.max()
             ax.plot(sum_imp.data.index*1e-9, spect, 'r', linewidth=2.5)
         
-        ax.legend(legend, loc="upper left", ncol=3)            
-        ax.set_xlabel("Frequency [GHz]")
+        ax.legend(legend, loc="upper left", ncol=2)            
+        ax.set_xlabel("Frequency (GHz)")
         ax.set_ylabel(label_list[leg] + " - " + component + " part")
         ax.set_title(label_list[leg] + " - " + component + " part")
         
@@ -315,13 +317,13 @@ class ImpedanceModel():
                 try:
                     sum_imp = getattr(getattr(self, attr), Z_type) + zero_impedance
                     in_ax.fill_between(sum_imp.data.index*1e-3, total_imp, 
-                                    total_imp + sum_imp.data[component]*1e-9)
+                                    total_imp + sum_imp.data[component]*1e-9, edgecolor=colorblind[index%10], color=colorblind[index%10])
                     total_imp += sum_imp.data[component]*1e-9
                 except AttributeError:
                     pass
             in_ax.set_xlim([0, 200])
-            in_ax.set_xlabel("Frequency [kHz]")
-            in_ax.set_ylabel(r"$[G\Omega]$")
+            in_ax.set_xlabel("Frequency (kHz)")
+            in_ax.set_ylabel(r"$[\mathrm{G}\Omega]$")
                 
         return fig