Advancing MEMS/MOEMS Sensors: AI-Driven Optimization and Emerging Applications

Dear Colleagues,

MEMS/MOEMS (Micro-Electro-Mechanical Systems/Micro-Opto-Electro-Mechanical Systems) inertial sensors—encompassing accelerometers, gyroscopes, and inertial measurement units (IMUs)—have transformed navigation, motion sensing, and stabilization technologies across diverse sectors, ranging from consumer electronics and automotive systems to aerospace and biomedical applications. The escalating demand for enhanced precision, miniaturization, energy efficiency, and environmental resilience has exposed the limitations of conventional design paradigms in reconciling the intricate trade-offs among performance, reliability, and manufacturability. Emerging intelligent design methodologies, empowered by machine learning, topology optimization, multi-physics co-design, and bio-inspired strategies, hold transformative potential to surmount these challenges and usher in next-generation sensor capabilities.

Recent breakthroughs underscore the adoption of AI-driven optimization for dynamic performance enhancement, novel materials (e.g., metamaterials, 2D materials) for superior sensitivity, and hybrid MEMS/MOEMS architectures that synergize optical and mechanical sensing modalities. Nevertheless, persistent challenges include (1) the complexity of multiphysics coupling (mechanical, optical, thermal, electrical), which compromises modeling fidelity; (2) fabrication-induced variability that adversely affects production yield; and (3) environmental perturbations (e.g., temperature fluctuations, mechanical vibrations) that impair long-term stability. Additionally, transitioning intelligent design frameworks from simulation to real-world deployment necessitates resolving critical gaps in computational efficiency, experimental validation, and compatibility with industry standards.

This Special Issue seeks cutting-edge contributions on intelligent design innovations for MEMS/MOEMS inertial sensors. Topics of interest may include, but are not limited to, the following:

• AI/ML-aided design optimization and autonomous tuning;
• Multiphysics modeling, digital twins, and uncertainty quantification;
• Advanced materials (e.g., heterostructures, piezoelectrics) and their sensor integration;
• Noise suppression and drift compensation techniques;
• Self-calibrating and fault-tolerant architectures;
• System-level co-design for emerging applications (e.g., IoT, robotics, wearables).

Submissions emphasizing scalability, reliability validation, and experimental benchmarking of theoretical models are particularly encouraged.

Dr. Qianbo Lu
Guest Editor

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• intelligent design of MEMS/MOEMS: AI/ML-driven optimization, topology optimization, bio-inspired design
• multi-physics modeling: coupled mechanical-optical-thermal-electrical analysis, digital twins
• sensor architectures: accelerometers, gyroscopes, IMUs, hybrid MEMS/MOEMS
• advanced materials: metamaterials, 2D materials, piezoelectrics, nanocomposites
• performance enhancement: noise reduction, self-calibration, sensitivity optimization