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

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "A:Physics".

Deadline for manuscript submissions: 20 February 2026 | Viewed by 719

Special Issue Editor

Institute of Flexible Electronics (IFE), Northwestern Polytechnical University, Xi'an 710072, China
Interests: sensors; optics; MEMS; ‪MOEMS‬; ‪flexible electronics‬‬‬

Special Issue Information

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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2100 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • 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

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Review

42 pages, 4490 KiB  
Review
Continuous Monitoring with AI-Enhanced BioMEMS Sensors: A Focus on Sustainable Energy Harvesting and Predictive Analytics
by Mingchen Cai, Hao Sun, Tianyue Yang, Hongxin Hu, Xubing Li and Yuan Jia
Micromachines 2025, 16(8), 902; https://doi.org/10.3390/mi16080902 - 31 Jul 2025
Viewed by 582
Abstract
Continuous monitoring of environmental and physiological parameters is essential for early diagnostics, real-time decision making, and intelligent system adaptation. Recent advancements in bio-microelectromechanical systems (BioMEMS) sensors have significantly enhanced our ability to track key metrics in real time. However, continuous monitoring demands sustainable [...] Read more.
Continuous monitoring of environmental and physiological parameters is essential for early diagnostics, real-time decision making, and intelligent system adaptation. Recent advancements in bio-microelectromechanical systems (BioMEMS) sensors have significantly enhanced our ability to track key metrics in real time. However, continuous monitoring demands sustainable energy supply solutions, especially for on-site energy replenishment in areas with limited resources. Artificial intelligence (AI), particularly large language models, offers new avenues for interpreting the vast amounts of data generated by these sensors. Despite this potential, fully integrated systems that combine self-powered BioMEMS sensing with AI-based analytics remain in the early stages of development. This review first examines the evolution of BioMEMS sensors, focusing on advances in sensing materials, micro/nano-scale architectures, and fabrication techniques that enable high sensitivity, flexibility, and biocompatibility for continuous monitoring applications. We then examine recent advances in energy harvesting technologies, such as piezoelectric nanogenerators, triboelectric nanogenerators and moisture electricity generators, which enable self-powered BioMEMS sensors to operate continuously and reducereliance on traditional batteries. Finally, we discuss the role of AI in BioMEMS sensing, particularly in predictive analytics, to analyze continuous monitoring data, identify patterns, trends, and anomalies, and transform this data into actionable insights. This comprehensive analysis aims to provide a roadmap for future continuous BioMEMS sensing, revealing the potential unlocked by combining materials science, energy harvesting, and artificial intelligence. Full article
Show Figures

Figure 1

Back to TopTop