Before you call lsqcurvefit, you should call your function "func" with the initial guess values for the parameters to see what it returns. So insert the command
test = func(p,ydata)
before the line
f=lsqcurvefit(func, p, ydata, xdata, lb,ub);
Further it is usual that you have a function ydata = func(p,xdata). You reversed the roles of xdata and ydata: xdata = func(p,ydata). You should check whether this is really what you want.
Further your model depends on only one parameter, not three. The expression
2*p(1)*p(2)/(2*KbT*p(3))
can be seen as one parameter P you try to estimate. It's not possible to distinguish between p(1), p(2) and p(3) because they are subsummed in one expression.
To understand this, imagine you try to fit a model
ydata = p(1)*p(2)*xdata
If the optimizer returns p(1) = 2, p(2) = 5, would this in any way be better than p(1) = 1, p(2) = 10 or p(1) = 2.5, p(2) = 4 ?
