ReviewMicromachines2025
Recent Advances in the Design, Modeling, and Control of Flexure-Based Nanopositioning Stages.
Review in Micromachines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Nanowire Quantum Dot Emitters Evanescently Coupled On-Chip via Curved and Segmented SiN Waveguides.ACS photonics · 2026Article
- Design and Experimental Validation of a Flexible-Hinge-Based Manual Mechanism for Micro/Nano-Displacement Scaling.Micromachines · 2026Article
- Multitechnological integration advances musculoskeletal regeneration: synergistic progress of organoids, 3D/4D bioprinting, single-cell omics and artificial intelligence.Frontiers in bioengineering and biotechnology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Flexure-based nanopositioning stages have emerged as indispensable tools in advanced fields such as nanotechnology, semiconductor manufacturing, and biomedical engineering, where nanometer-scale precision is paramount. This paper presents a comprehensive review of the state-of-the-art in flexure-based nanopositioning, systematically examining the three critical and interconnected domains of geometric design, theoretical modeling, and advanced control strategies. This review begins by analyzing fundamental design principles, including motion decoupling, stiffness-range trade-offs, and various structural topologies (serial, parallel, and hybrid), highlighting how they achieve high precision and reject disturbances. It then delves into analytical and computational modeling techniques, from pseudo-rigid-body models and beam theory to finite element analysis, which are essential for predicting system behavior and guiding design optimization. A core section of this review is dedicated to control methodologies, providing a critical analysis of active resonant control for damping mechanical vibrations, classical and robust control for stability under uncertainties, and modern adaptive and learning-based techniques for handling nonlinearities and time-varying dynamics. Furthermore, this review addresses persistent challenges such as bandwidth limitations, performance trade-offs, and the integration of complex multi-axis systems. Finally, it outlines future research directions, emphasizing the promising potential of data-driven modeling, artificial intelligence-enhanced control, and a holistic mechatronic co-design approach to push the boundaries of precision, speed, and robustness in next-generation nanopositioning systems. This work aims to serve as a systematic reference and synthesis for researchers by integrating a vast body of literature and providing a clear perspective on the development of high-performance nanopositioning stages.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.