The nanometer regime presents a fundamental paradox: classical mechanics that govern our macroscopic world break down at the scale of atoms, yet quantum descriptions become computationally prohibitive for systems larger than a few thousand atoms. Mathematics provides the essential bridge across this chasm. This paper presents a comprehensive examination of mathematical applications across six critical domains of nanotechnology: (1) nanomechanics theories based on nonlocal elasticity and strain gradient frameworks; (2) multiscale modeling architectures bridging atomic to continuum scales; (3) mesh-free numerical methods for nanoscale process simulation; (4) density functional theory as the quantum mathematical foundation of nanomaterials design; (5) machine learning as a meta-mathematical tool for property prediction and inverse design; and (6) mathematical modeling of nanorobots for targeted drug delivery. We demonstrate that each mathematical innovation directly translates into societal benefit: faster drug discovery, safer engineered nanomaterials, more efficient energy storage, and precise cancer therapeutics. The paper concludes that mathematics is not merely a tool for nanotechnology—it is the only language capable of speaking across the vast scales that separate quantum behavior from real-world applications.