plotting – Fitting two convoluted peaks


If I have the following data:

https://pastebin.com/ya03z9bP

which plotted as:

ListLinePlot(datawithnoliquidline, 
 PlotStyle -> Directive(Thick, Black), 
 PlotRange -> {{40, 110}, {-0.02, All}}, Frame -> True, 
 FrameStyle -> 14, Axes -> False, GridLines -> Automatic, 
 GridLinesStyle -> Lighter(Gray, .8), 
 FrameTicks -> {Automatic, Automatic}, 
 FrameLabel -> (Style(#, 20, Bold) & /@ {"T ((Degree)C)", 
     Row({"!(*SubscriptBox((C), (P)))", " (", " J/gK)"})}), 
 LabelStyle -> {Black, Bold, 14})

gives two peaks as in the picture:

image

Questions:
1)How can I correctly fit these two peaks?
2) How can I calculate the areas of the two fitted peaks?

My approach, using gaussian fit (which doesn’t seem correct) is as follows:

ff2(x_, areaa1_, areaa3_, siga1_, siga3_, meda1_, meda3_) := 
  areaa1 PDF(NormalDistribution(meda1, siga1), x) + 
   areaa3 PDF(NormalDistribution(meda3, siga3), x) ;


ma1guess = 6;
ma3guess = 1.3;
siga1guess = 4;
siga3guess = 3;
meda1guess = 82;
meda3guess = 97;

averagenematicarea = 1.2;(*Average nematic area from all three DSC 
runs*)
STDnematicarea = 0.2; (*Standard deviation of nematic 
area*)(*Aceptable shift above and below the nematic area where the 
fits will be constraint (e.g if shift is 0.2 and area=1.2, then the 
fits would be constraint between 1 J/g and 1.4 J/g)*)

averagesmecticarea = 1;(*Average smectic area from all three DSC runs*)


STDsmecticarea = 0.2; (*Standard deviation of smectic 
area*)(*Aceptable shift above and below the nematic area where the 
fits will be constraint (e.g if shift is 0.2 and area=1.2, then the 
fits would be constraint between 1 J/g and 1.4 J/g)*)

averagenematiconset = 88.2;(*Average nematic onset from all three DSC 
runs*)
STDnematiconset = 0.2; (*Standard deviation of nematic 
onset*)(*Aceptable shift above and below the nematic onset where the 
fits will be constraint (e.g if shift is 0.5 and onset=88, then the 
fits would be constraint between 87.5C and 88.5C)*)



nlm3 = NonlinearModelFit(
  datawithnoliquidline, {ff2(x, areaa1, areaa3, siga1, siga3, meda1, 
    meda3), areaa3 >= 0, areaa1 >= 0, 0 <= siga1 <= 20, 
   0 <= siga3 <= 20, 60 < meda1 < 85, 
   meda3 - 2*siga3 > 88.6}, {{areaa1, ma1guess}, {areaa3, 
    ma3guess}, {siga1, siga1guess}, {siga3, siga3guess}, {meda1, 
    meda1guess}, {meda3, meda3guess}}, x);

fp = nlm3("BestFitParameters");


p1 =(*Original data*)
  ListLinePlot(datawithnoliquidline, 
   PlotStyle -> Directive(Thick, Black), 
   PlotRange -> {{40, 110}, {-0.02, All}}, Frame -> True, 
   FrameStyle -> 14, Axes -> False, GridLines -> Automatic, 
   GridLinesStyle -> Lighter(Gray, .8), 
   FrameTicks -> {Automatic, Automatic}, 
   FrameLabel -> (Style(#, 20, Bold) & /@ {"T ((Degree)C)", 
       Row({"!(*SubscriptBox((C), (P)))", " (", " J/gK)"})}), 
   LabelStyle -> {Black, Bold, 14});
p2 = Plot({nlm3(x), 
    areaa3 PDF(NormalDistribution(meda3, siga3), x) /. 
     fp, +areaa1 PDF(NormalDistribution(meda1, siga1), x) /. fp}, {x, 
    40, 110}, 
   PlotStyle -> {Directive(Red, Dashing({0.02, 0.04}), 
      AbsoluteThickness(5)), Directive(Green, AbsoluteThickness(2)), 
     Directive(Orange, AbsoluteThickness(2)), 
     Directive(Blue, AbsoluteThickness(2)), Directive(Pink, Dashed), 
     Directive(Cyan, Dashed)}, PlotRange -> All);

Show(p1, p2)

which gives the following:

enter image description here

So, my problem is really fitting correctly the second peak, which I am not sure how to do.