Evidence map›Paper›PMID 42513061›Full record

ArticleMicromachines2026

Microstructure-Driven Loss Mechanisms and Tensor-Based FEM Calibration.

Annamaria Muoio, Angela Garofalo, Francesco La Via

Abstract read
In one paragraph

Article in Micromachines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Annamaria MuoioInstitute for Microelectronics and Microsystems(IMM), National Research Council (CNR), Strada VIII, 5, 95121 Catania, Italy.ORCID 0000-0003-0837-187X
Angela GarofaloMaterials Science Department, Milano-Bicocca University, Via R. Cozzi 55, 20125 Milan, Italy.
Francesco La ViaInstitute for Microelectronics and Microsystems(IMM), National Research Council (CNR), Strada VIII, 5, 95121 Catania, Italy.ORCID 0000-0002-6842-581X

Funding

SAMOTHRACE ECS00000022WBG 101183211
6 · The paper itself

Abstract

Silicon carbide (SiC) is a key material for next-generation miniaturized devices and MEMS operating in harsh environments. This paper presents a comprehensive investigation of anisotropic damping mechanisms in heteroepitaxial 3C-SiC double-clamped beam resonators for MEMS applications. Unlike conventional isotropic loss-factor models, which assign a single scalar damping coefficient to all deformation directions, the proposed framework employs a full 6 × 6 loss-factor tensor expressed in Voigt notation, implemented within the COMSOL Multiphysics finite element environment. The tensor formulation enables the direction-dependent description of energy dissipation, capturing the coupling between shear and normal strain modes that arises from the (111) crystallographic orientation and from the heteroepitaxial defect structure of 3C-SiC grown on silicon substrates. The effects of film thickness, effective Young's modulus, and residual stress on elastic modulus, resonance frequency, and Q-factor are systematically analyzed across five wafers (w1-w5, thickness range 293-890 nm). Experimentally calibrated anisotropic loss-factor matrices are extracted via least-squares fitting to measured Q-factors, and their Frobenius norms are found to correlate negatively with resonance frequency. The anisotropic model reduces Q-factor prediction errors to below 1% for all wafers, significantly outperforming the isotropic approach, particularly for films thicker than 600 nm. These results demonstrate that an accurate treatment of directional dissipation is essential for the design of high-Q resonators and high-sensitivity strain sensors targeted at geophysical monitoring applications.

Indexed as

3C-SiCanisotropic dampingfinite element method (FEM)harsh environmentheteroepitaxial SiCmicroresonatorsquality factor (Q-factor)residual stressresonatorsSiC microsystemstrain sensors

Identifiers

PMID42513061
PMCPMC13413584

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Registered trials

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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.