I am bit confused about the use of multiple t-tests vs ANOVA with Dunnett's post-hoc test (on normally distributed data).

Let's take the following made-up example:

A scientist tests the effect of substance A vs no treatment on n biological replicates. He then performs a t-test to find out if there is a significant effect (with p<0.05 considered to be significant) of substance A.

Independently, another scientist does the same experiments and statistical analysis for substance B, and again another scientist for substance C.

They all find that each substance has a statistically significant effect.

Now let's assume there hadn't been three scientists but only one scientist testing all three substances in the same way. He is not interested in differences between the substances but only whether they have a significant effect vs untreated control. Therefore, he uses ANOVA and Dunnett's post-hoc test to analyze his data. He does not get a statistically significant effect for substance A, B and C because of the corrections made for multiple comparisons.

How can this be? This does not appear logical to me.