Is entropy of a binomial distribution an increasing function of $n$?

I was thinking about the entropy of a binomial distribution. The Wikipedia page on Binomial distribution says that the entropy of the Binomial(n,p) is asymptotically $\frac{1}{2} \log _{2}(2 \pi e n p(1-p))+O\left(\frac{1}{n}\right)$.

I noted that in non-asymptotic regime, there exists lower bounds and upper bounds for the binomial entropy as can be seen here.

I was wondering whether Binomial entropy is an increasing (strictly speaking, non-decreasing) function of $n$ in general? My intuitive answer is yes. But, I can't quite prove this. Can someone help me prove this.

My attempt: $H(X+Y)=H(X)+H(Y)-H(X|X+Y)$ for $X,Y$ IID Bernoulli RVs. Also conditioning reduces entropy. Iterate this argument $n$ times to reach Binomial. Is this right?

That's right.

A Binomial $(n,p)$ can be expressed as the sum of $n$ Bernoulli $(p)$ variables. Hence it also can be expressed as the sum of a Binomial $(n-1,p)$ and a Bernoulli $(p)$.

Now, if $Z = X + Y$ (for independent $X,Y$) we have

$$H(Z,Y)= H(Y|Z) + H(Z) = H(Z | Y) + H(Y) \implies \\ H(Z)=H(X+Y)= H(X) + H(Y)-H(Y|Z) \ge H(X) $$

because $H(Y|Z) \le H(Y)$.

Then, letting $Z,X$ be the Binomials and $Y$ the Bernoulli, we get the desired result.

Notice that the inequality actually is strict, if $0<p<1$.