Layerwise Stratification and Band Reordering in Twisted Multilayer MoTe₂

We present a physics-guided framework for constructing transferable machine-learning force fields capable of capturing moiré lattice energetics across a wide range of structural configurations. Applied to multilayer twisted transition-metal dichalcogenides (TMDs), this approach uncovers an unexpected structural and electronic stratification that persists deep into the bulk, leading to emergent electronic textures and topology-sensitive band rearrangements under modest external tuning. These findings highlight a new regime of structural-electronic decoupling beyond bilayer moiré systems.