  Recent experimental observations of current blockades in 2-D material
quantum-dot platforms have opened new avenues for spin and valley-qubit
processing. Motivated by experimental results, we construct a model capturing
the delicate interplay of Coulomb interactions, inter-dot tunneling, Zeeman
splittings, and intrinsic spin-orbit coupling in a double quantum dot structure
to simulate the Pauli blockades. Analyzing the relevant Fock-subspaces of the
generalized Hamiltonian, coupled with the density matrix master equation
technique for transport across the setup, we identify the generic class of
blockade mechanisms. Most importantly, and contrary to what is widely
recognized, we show that conducting and blocking states responsible for the
Pauli-blockades are a result of the coupled effect of all degrees of freedom
and cannot be explained using the spin or the valley pseudo-spin only. We then
numerically predict the regimes where Pauli blockades might occur, and, to this
end, we verify our model against actual experimental data and propose that our
model can be used to generate data sets for different values of parameters with
the ultimate goal of training on a machine learning algorithm. Our work
provides an enabling platform for a predictable theory-aided experimental
realization of single-shot readout of the spin and valley states on DQDs based
on 2D-material platforms.
