Ru nanoparticles are highly active catalysts for ammonia production, but strong hydrogen adsorption causes hydrogen poisoning, and conventional oversimplified coverage assumption of a 1ML in experiments overlook size and structure-dependant effects, leading to inaccurate particle size and dispersion measurements. To clarify these effects, we employed a multiscale framework integrating density functional theory (DFT), global minimum search, ab initio phase diagrams, ab initio molecular dynamics, and deep potential MD (DPMD) to predict stable morphologies and hydrogen coverage on 1– ~10 nm Ru nanoparticles. Our melting simulations reveal a size-dependent morphology transition of Ru nanoparticles: FCC-based-icosahedral (<1 nm), FCC-based-decahedral (1–5 nm), and HCP (>5 nm) [1]. Thought DFT, ab initio phase diagrams and DPMD predict different hydrogen coverage values but similar trend from low to high temperature and from small to large nanoparticles. DPMD simulations show that hydrogen coverage exceeds 1 ML for small particles (~2.4 ML at 1 nm, ~1.3 ML at 4.8 nm (323 K)) and decreasing hydrogen coverage values at higher temperatures (~2 ML at 1 nm, ~1 ML at 3.5 nm, and ~0.9 ML at 4.8 nm (673 K)) [2]. Notably, our study shows that hydrogen coverage scales with low-coordinated surface Ru atoms, not linearly with nanoparticle size, explaining why conventional assumptions overestimate dispersion and underestimate nanoparticle size. Furthermore, a size-dependant hydrogen adsorption model proposed: θ(d) = a + b/d where, θ is coverage, and d is particle diameter, and a and b are temperature-dependent constants. This framework bridges scales, challenges conventional assumptions, and provides insights for the design of Ru and other nanocatalysts.