Polyalphaolefin (PAO)-based magnetic fluids are widely used in precision transmission systems for their excellent rheological and lubricating properties, but their stability and magnetic controllability under high-temperature and high-shear conditions remain a key challenge. In this work, a PAO2-based magnetic fluid was prepared via coprecipitation using a sequential modification strategy involving oleic acid and alkenyl succinimide. An energy competition model under multi-field coupling was established using the magnetothermal energy ratio ($\lambda$) and Mason number ($Mn$) to elucidate the system’s rheological behavior. The fluid shows significant shear-thinning behavior under zero magnetic field; a 60 kA/m magnetic field increases the relative viscosity by over 4 times at 5 s⁻¹, while the magnetoviscous effect becomes weak at shear rates over 500 s⁻¹ (corresponding approximately to $Mn$= 1). With increasing temperature, the field-induced viscosity enhancement decreases progressively as thermal disturbance becomes increasingly important. This work reveals the multi-field coupling rheological mechanism, and the results suggest that the OA/T154 modification strategy is a feasible route for obtaining a PAO-based magnetic fluid that remains dispersible and magnetically responsive under the tested conditions. The study provides theoretical and experimental support for the design of intelligent lubricating materials.

To address the low production efficiency and insufficient cross-enterprise collaboration in wallboard outsourcing for coating equipment manufacturing, this study proposes a wallboard manufacturing service composition optimization method based on an improved NSGA-III algorithm. First, the service composition optimization problem in wallboard manufacturing is analyzed, and a mathematical model for wallboard outsourcing service composition optimization is established. Next, an improved NSGA-III method integrating Latin hypercube sampling, greedy local search, and Lévy flight-based global search strategies is proposed, alongside a similarity measurement method for the objective-space structure based on statistical features and distribution differences, which is used to select benchmark functions that closely match the characteristics of actual business data. Finally, comparative experiments using benchmark functions and real-world business data are conducted to verify the effectiveness and superiority of the proposed method in solving service composition optimization problems. The experimental results demonstrate that the proposed method achieves excellent performance in both solution quality and computational efficiency, significantly improving the utilization of wallboard outsourcing manufacturing resources across enterprises and facilitating efficient business process flows.

Magnetic fluids are smart materials that fall under the category of magnetic materials and possess the property of fluidity. Nevertheless, conventional modifications using a monolayer surfactant are limited due to poor thermal stability and insuffici...