This S/O post has a helpful explanation of the warning message. Without a reprex (see the FAQ, there's not much helpful that can be said about your design except to say that it is often helpful to start with the simplest case and only add complications stepwise. Thus, start with the first example in help(lmer)
library(lme4)
#> Loading required package: Matrix
## linear mixed models - reference values from older code
(fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy))
#> Linear mixed model fit by REML ['lmerMod']
#> Formula: Reaction ~ Days + (Days | Subject)
#> Data: sleepstudy
#> REML criterion at convergence: 1743.628
#> Random effects:
#> Groups Name Std.Dev. Corr
#> Subject (Intercept) 24.741
#> Days 5.922 0.07
#> Residual 25.592
#> Number of obs: 180, groups: Subject, 18
#> Fixed Effects:
#> (Intercept) Days
#> 251.41 10.47
summary(fm1)
#> Linear mixed model fit by REML ['lmerMod']
#> Formula: Reaction ~ Days + (Days | Subject)
#> Data: sleepstudy
#>
#> REML criterion at convergence: 1743.6
#>
#> Scaled residuals:
#> Min 1Q Median 3Q Max
#> -3.9536 -0.4634 0.0231 0.4634 5.1793
#>
#> Random effects:
#> Groups Name Variance Std.Dev. Corr
#> Subject (Intercept) 612.10 24.741
#> Days 35.07 5.922 0.07
#> Residual 654.94 25.592
#> Number of obs: 180, groups: Subject, 18
#>
#> Fixed effects:
#> Estimate Std. Error t value
#> (Intercept) 251.405 6.825 36.838
#> Days 10.467 1.546 6.771
#>
#> Correlation of Fixed Effects:
#> (Intr)
#> Days -0.138
Created on 2023-04-16 with reprex v2.0.2
and from that base model, add the additional complications.