Evidence map›Paper›PMID 42332072›Full record

ArticleScientific reports2026

Impact of boundary conditions and geometric tolerances dynamics on MEMS double touch mode capacitance pressure sensor applying M-shaped silicon design.

Shabana S, Sumit Kumar Jindal

Abstract read
In one paragraph

Article in Scientific reports, 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

2 authors.

Shabana SSchool of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Sumit Kumar JindalSchool of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India. sumit.jindal@vit.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Micro-Electro-Mechanical Systems (MEMS) are extensively utilized in many different applications because of its compact design, low power consumption and greater sensitivity. Compared to piezoresistive alternatives, a MEMS- based Touch Mode Capacitive Pressure Sensor (TMCPS) is designed and simulated to achieve better sensitivity, stability and linearity. This work presents a Double Touch Mode MEMS-based Capacitive Pressure Sensor (DTMCPS) with a flexible circular diaphragm integrated into an M-shaped silicon substrate. By increasing the diaphragm-substrate contact area, the proposed M-shaped structural arrangement improves sensor linearity and sensitivity. The diaphragms deflection characteristics are modeled using small deflection theory to minimize nonlinearity. A comprehensive analysis of the sensors capacitive behavior is carried out. The analytical formulations for capacitance, capacitive sensitivity and mechanical sensitivity are derived and generated using MATLAB based simulations. The diaphragm deformation is further assessed through structural analysis using COMSOL Multiphysics. The goal is to improve the performance of the conventional DTMCPS by integrating a silicon (Si) circular diaphragm with an M-shaped silicon substrate. The position of the touch point is crucial in defining the overall sensitivity, hence the notch size have a considerable impact on the sensors operational properties. Small deflection theory is used to model the diaphragm behavior in order to minimize nonlinear effects. These results show the potential use in cutting edge medical, automotive, aerospace and industrial sensing applications by demonstrating the higher sensitivity, accuracy and durability of the preferred TMCPS design.

Indexed as

Capacitive sensingGeometric optimizationMEMS pressure sensorM-shaped diaphragm designMultiphysics simulation

Identifiers

PMID42332072
PMCPMC13574761

What OpenQuestion holds

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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.