ReviewSmall (Weinheim an der Bergstrasse, Germany)2026
3D-Printed Metamaterial-Based Soft Sensors: Materials, Design, and Fabrications.
Review in Small (Weinheim an der Bergstrasse, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Additive manufacturing has enabled highly sophisticated three-dimensional soft bodies through material distribution, opening new possibilities for architected soft matter systems. In parallel, rapid development in soft robotics has intensified the necessity of compliant, distributed, and deformation-driven sensing solutions. Among possible solutions, 3D-printed metamaterial-based soft sensors are promising due to unprecedented mechano-sensing performances. Specifically, by integrating material design and structural topology into a unified functional entity, these metamaterial-based sensing solutions enable tunable stiffness, controlled instability, and efficient electromechanical transduction. With these promising findings in mind, this review aims to provide a comprehensive framework addressing additive manufacturing technologies, material systems, and sensing mechanisms in 3D-printed metamaterial-based sensors. In this work, available 3D printing technologies are discussed, highlighting trade-offs in resolution, multi-material capability, and structural fidelity. In parallel, a variety of 3D printing materials, including polymer-based, functional composite, and smart responsive materials, is examined, emphasizing material-structure interactions determining sensing performance. Subsequently, metamaterial-based transduction mechanisms are classified into resistive, capacitive, and inductive modalities, together with emerging multifunctional and multimodal sensing modality. Conclusively, by synthesizing fabrication technologies, material systems, and sensing architectures within an additive manufacturing perspective, this review provides design frameworks and outlooks for perceptive soft machines and their applications in real-world scenarios.
Indexed as
Identifiers
What Socratic 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 Socratic graph.