Mass and stiffness sensing performance of nanomechanical resonators: viability of infectious virus detection
Abstract We examine the performance of nanomechanical resonators for mass and stiffness sensing of nanoparticulate analytes with focus on their application for untargeted infectious virus detection. The characteristic narrow mass distributions of viruses, together with the existing correlations betw...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
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| Series: | Discover Nano |
| Online Access: | https://doi.org/10.1186/s11671-025-04295-7 |
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| Summary: | Abstract We examine the performance of nanomechanical resonators for mass and stiffness sensing of nanoparticulate analytes with focus on their application for untargeted infectious virus detection. The characteristic narrow mass distributions of viruses, together with the existing correlations between their stiffness and infectivity, point out to nanomechanical sensors as a particularly suited alternative to molecular detection techniques, constrained by limited processing speed, target-specificity, and the inability to directly assess infectivity. We present a theoretical analysis of the response of flexural beam resonators to the adsorption of nanoparticulate analytes, and derive analytical expressions for the mass and stiffness sensing responsivity, resolution and signal to noise ratio as a function of the beam characteristics and analyte adsorption parameters. We demonstrate that both the mass and stiffness of viruses can contribute to resonance frequency shifts that significantly exceed the fundamental detection limits of beams with plausible dimensions and for realistic adsorption parameters. Particularly, stiffness resolution can reach levels well below the stiffness variations observed in some viruses as a consequence of maturation, enabling an integrated approach for infectivity assessment. We conclude that the practical application of nanomechanical spectrometry for infectious virus detection is not limited by the performance of state-of-the-art sensor technology, but by the efficiency of analyte delivery methods, encouraging future research on optimizing their implementation. |
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| ISSN: | 2731-9229 |