Fix parameters for missing levels of grouping factor

I would like to fit the following model

m <-brm(dead | trials(n) ~ log10(dose)*insect*platform  + (log10(dose)*platform | experiment),
        data=dff , family=binomial(link=probit), save_pars = save_pars(all=TRUE),
        cores = getOption("mc.cores",4), iter=10000, warmup=2000,
        control = list(adapt_delta = 0.95, max_treedepth=15), backend = "cmdstanr")

where insect and platform are factors. platform takes on 2 possible values. Almost every experiment is run on both platforms, but there are a couple for which I have data on just one platform. The model fits just fine, and the experiment specific platform effects are just very diffuse for those experiments for which I have missing data.

Is it possible (also is it reasonable?) for me to specify that the experiment specific platform effects for those experiments with missing data are 0? How do I specify that?

What do you hope to gain by fixing these effects to zero?