Abstract
Micro-nano additive-enhanced lubricating greases are pivotal for extreme-condition tribology, yet optimizing synergistic additive concentrations remains constrained by conventional experimental designs. This study employs a central composite design (CCD) coupled with MATLAB response surface methodology to precisely determine optimal concentrations of nano-graphite (N-G), graphene (GN), and potassium borate (PB) in titanium complex grease. Fifteen formulations were tested under progressive loads (98-598 N) via four-ball tribometry, with SEM/XPS characterizing wear mechanisms. The synergistic grease (G-MX: 0.83 wt% N-G, 0.05 wt% GN, 2.59 wt% PB) reduced the average friction coefficient by 45.3% and wear scar diameter by 23.3% versus base grease, surpassing single-additive variants. The CCD-MATLAB framework addressed sampling limitations of prior orthogonal methods, enabling optimization beyond discrete testing points. Mechanistic analysis revealed a dual lubrication regime: physically adsorbed films (soap molecules and refined PB particles) dominated at low loads, while chemically bonded tribofilms (Fe₃C, B₂O₃, TiO₂) ensured wear resistance under extreme pressures.