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Laser powder bed fusion (LPBF) enables fabrication of complex metal components but remains limited by residual stress accumulation and part deformation. Most existing scan sequence generation strategies for LPBF rely on heuristic rules or empirical optimizations that are suboptimal, difficult to generalize across geometries, and insensitive to the underlying physics of the problem. The SmartScan framework was developed to overcome these limitations through model-based and optimization-driven scan sequence generation. SmartScan 1.0 employed a thermal model to optimize temperature uniformity, leading to significant reductions in residual stress and distortion compared to state-of-the-art heuristic approaches. However, its formulation ignored the mechanical aspects of residual stress and deformation. To address this deficiency, a preliminary study introduced SmartScan 2.0 (Pre) which utilized a decoupled linear thermomechanical formulation for scan sequence optimization for 2D geometries. Building on this foundation, this paper proposes SmartScan 2.0 based on a sequentially coupled linear thermoelastic model that simultaneously solves temperature and displacement fields to minimize thermally induced elastic deformation in 3D geometries. The computational efficiency of SmartScan 2.0 is enhanced through nondimensional scaling. Experimental validation on 3D LPBF specimens shows that SmartScan 2.0 achieves up to 69.0% reduction in residual stress and 17.4% reduction in deformation relative to SmartScan 1.0, and up to 60.6% reduction in residual stress and 12.8% reduction in deformation compared with SmartScan 2.0 (Pre). This work establishes the superiority of scan sequence optimization using coupled linear thermomechanical models over the existing thermal-only or decoupled thermomechanical approaches, without significantly sacrificing computational efficiency.