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<p>Topology optimization (TO) has emerged as a powerful computational design methodology for synthesizing compliant mechanisms, enabling the systematic generation of structures that achieve prescribed motion, force transmission, and multifunctional performance while satisfying material and manufacturing constraints. This review presents a comprehensive assessment of the development of topology optimization for compliant mechanisms, covering theoretical foundations, optimization methodologies, and emerging applications, with particular emphasis on micro-nano-manufacturing systems. Classical density-based, level-set, evolutionary, and geometry-based approaches are critically examined alongside recent advances in nonlinear, stress-constrained, reliability-based, multi-material, and multi-objective optimization frameworks. Particular attention is devoted to fabrication-aware design strategies, including additive manufacturing constraints, minimum feature-size control, thin-film anisotropy, residual stress effects, and manufacturability considerations relevant to MEMS/NEMS devices. The review further discusses scale-dependent phenomena, surface-force interactions, and multiphysics coupling requirements that influence the performance and reliability of micro-nano-scale compliant mechanisms. Recent progress in experimentally validated designs, technology readiness, and commercialization challenges is analyzed to bridge the gap between computational optimization and practical implementation. Emerging developments in artificial intelligence, machine learning, digital twins, and physics-informed optimization are also reviewed as promising pathways to accelerate design exploration and improve design robustness. Based on a critical synthesis of the available literature, key research trends, limitations, and future opportunities are identified. The review highlights the continuing evolution of topology optimization from a computational design tool to a mature framework that increasingly links mechanics, manufacturing, uncertainty quantification, and intelligent design, thereby reinforcing its potential as a key design paradigm for next-generation compliant mechanisms and advanced micro/nano manufacturing technologies.</p>

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Topology optimization of compliant mechanisms for micro/nano manufacturing: from theoretical foundations to emerging research frontiers

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月21日

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  • Vijay Dilip Kolate,
  • Pradipkumar Dudhajirao Darade,
  • Adik Yadao,
  • Manoj Kumar Chaudhary

摘要

Topology optimization (TO) has emerged as a powerful computational design methodology for synthesizing compliant mechanisms, enabling the systematic generation of structures that achieve prescribed motion, force transmission, and multifunctional performance while satisfying material and manufacturing constraints. This review presents a comprehensive assessment of the development of topology optimization for compliant mechanisms, covering theoretical foundations, optimization methodologies, and emerging applications, with particular emphasis on micro-nano-manufacturing systems. Classical density-based, level-set, evolutionary, and geometry-based approaches are critically examined alongside recent advances in nonlinear, stress-constrained, reliability-based, multi-material, and multi-objective optimization frameworks. Particular attention is devoted to fabrication-aware design strategies, including additive manufacturing constraints, minimum feature-size control, thin-film anisotropy, residual stress effects, and manufacturability considerations relevant to MEMS/NEMS devices. The review further discusses scale-dependent phenomena, surface-force interactions, and multiphysics coupling requirements that influence the performance and reliability of micro-nano-scale compliant mechanisms. Recent progress in experimentally validated designs, technology readiness, and commercialization challenges is analyzed to bridge the gap between computational optimization and practical implementation. Emerging developments in artificial intelligence, machine learning, digital twins, and physics-informed optimization are also reviewed as promising pathways to accelerate design exploration and improve design robustness. Based on a critical synthesis of the available literature, key research trends, limitations, and future opportunities are identified. The review highlights the continuing evolution of topology optimization from a computational design tool to a mature framework that increasingly links mechanics, manufacturing, uncertainty quantification, and intelligent design, thereby reinforcing its potential as a key design paradigm for next-generation compliant mechanisms and advanced micro/nano manufacturing technologies.