Consider the Neumann eigenvalue problem
{−Δu=μuin Ω,∂u∂ν=0on ∂Ω,where Ω⊂R2 is a bounded convex domain. Recently, Filonov in [1] obtained the following lower bound on the eigenvalue counting function:
NN(Ω,μ)≥|Ω|λ2√3j20,where j20 is the first positive zero of the Bessel function J0.
Sketchily, the approach of [1] is the following: first we densely pack equal disks in R2, and then choose those whose centers lie in Ω. If a disk B is a subset of Ω, then we consider the first Dirichlet eigenfunction in B. If B∖Ω is nonempty, then we consider the restriction of the first Dirichlet eigenfunction in B to Ω∩B. Using these functions, we construct the test subspace and estimate μk(Ω) from above by a factor coming from the number of disks and the first Dirichlet eigenvalue λ1(B), which leads to a required lower bound for NN(Ω,μ).
The tricky point here is the consideration of the case when B∖Ω is nonempty. In this case, roughly speaking, one needs to justify that
τ1(Ω∩B)≤λ1(B),where τ1(Ω∩B) is the first eigenvalue in Ω∩B under the zero Dirichlet boundary conditions on ¯Ω∩∂B and zero Neumann boundary conditions on the remaining part of ∂(Ω∩B). This fact follows from Lemma 2.1 in [1] which states a certain integral property of Bessel functions. Here the convexity of Ω is employed. (Note that the fact remains true if Ω is merely star-shaped with respect to the center of B. However, it is hard to weaken the convexity in general, since the position of B with respect to Ω is not given constructively.)
It is tempting to anticipate that one could substitute disks by hexagons in the approach above, and hence improve the upper bound for μk(Ω), thereby improving the lower bound for NN(Ω,μ). To do it rigorously, one has to prove the inequality
τ1(Ω∩H)≤λ1(H),where H is a hexagon such that H∖Ω≠∅.
Unfortunately, it seems that the inequality cannot be true, in general. Let H be a hexagon with the side 1 centered at (0,0), and let Ω be a large triangle spanned on the points (0,0), (−20,−2), (20,−2), see figure below.

Mathematica gives the following values for the corresponding eigenvalues:
τ1(Ω∩H)≈7.20569andλ1(Ω)≈7.15548.I admit that calculations might be completely wrong for τ1(Ω∩H), but λ1(Ω) is calculated more-less ok. Playing with parameters (vertices of the triangle Ω), I also observe continuous dependence of τ1(Ω∩H) on them. The inequality holds for some parameters, and does not hold for others. This indirectly indicates that the calculation can be reliable.
Conclusion: it is not that easy to enhance the estimate from [1] using the same strategy.