The integrand seems extremely easy:
$$I_n=\int_0^1\exp(x^n)dx$$
I want to determine the asymptotic behavior of $I_n$ as $n\to\infty$. It's not hard to show that $\lim_{n\to\infty}I_n=1$ follows from Lebesgue's monotone convergence theorem. However, when I try to obtain more precise results, I confront difficulties. Since it's not of the canonical form of Laplace's method, I have no powerful tools to estimate $I_n$.
Is there any good approach for that? I will be pleased if we can obtain the asymptotic expansion of $I_n$. Thanks!
You can expand the exponential in a Taylor series quite accurately:
$$\exp{\left ( x^n \right )} = 1 + x^n + \frac12 x^{2 n} + \ldots$$
Because $x \in [0,1]$, this series converges rapidly as $n \to \infty$.
Then the integral is
$$1 + \frac{1}{n+1} + \frac12 \frac{1}{2 n+1} + \ldots = \sum_{k=0}^{\infty}\frac{1}{k!} \frac{1}{k n+1}$$
We can rewrite this as
$$\begin{align}I_n&=1+\frac{1}{n} \sum_{k=1}^{\infty} \frac{1}{k \cdot k!} \left ( 1+\frac{1}{k n} \right )^{-1}\\ &= 1+\frac{1}{n} \sum_{m=0}^{\infty} \frac{(-1)^m}{n^m} \: \sum_{k=1}^{\infty} \frac{1}{k^{m+1} k!}\\ &= 1+\sum_{m=1}^{\infty} (-1)^{m+1}\frac{K_m}{n^m} \end{align}$$
where
$$K_m = \sum_{k=1}^{\infty} \frac{1}{k^{m} k!}$$
To first order in $n$:
$$I_n \sim 1+\frac{K_1}{n} \quad (n \to \infty)$$
where
$$K_1 = \sum_{k=1}^{\infty} \frac{1}{k\, k!} = \text{Ei}(1) - \gamma \approx 1.3179$$
This checks out numerically in Mathematica.
BONUS
As a further check, I computed the following asymptotic approximation:
$$g(n) = 1+\frac{K_1}{n} -\frac{K_2}{n^2} $$
where
$$K_2 = \sum_{k=1}^{\infty} \frac{1}{k^2 k!} \approx 1.1465$$
I computed
$$\log_2{\left[\frac{\left|g\left(2^m\right)-I_{2^m}\right|}{I_{2^m}}\right]}$$
for $m \in \{1,2,\ldots,9\}$ The results are as follows
$$\left( \begin{array}{cc} 1 & -4.01731 \\ 2 & -6.56064 \\ 3 & -9.26741 \\ 4 & -12.0963 \\ 5 & -15.0028 \\ 6 & -17.9538 \\ 7 & -20.9287 \\ 8 & -23.916 \\ 9 & -26.9096 \\ \end{array} \right)$$
Note that the difference between successive elements is about $-3$; because this is a log-log table, that means that this error is $O(1/n^3)$ and that the approximation is correct.