Evidence map›Paper›PMID 40804131›Full record

ArticleScientific reports2025

The optimal substrate choice for effective biosensors based on THz metasurfaces.

Pradeep Tiwari, Deepak Kala, Maciej Sakowicz

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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.

Pradeep TiwariInstitute of High Pressure Physics PAS, CENTERA Laboratories, Sokolowska 29/37, 01-142, Warsaw, Poland.
Deepak KalaInstitute of High Pressure Physics PAS, CENTERA Laboratories, Sokolowska 29/37, 01-142, Warsaw, Poland.
Maciej SakowiczInstitute of High Pressure Physics PAS, CENTERA Laboratories, Sokolowska 29/37, 01-142, Warsaw, Poland. sakowicz@unipress.waw.pl.

Funding

Fundacja na rzecz Nauki Polskiej MAB/2018/9Narodowe Centrum Nauki 2020/38/E/ST7/00476
6 · The paper itself

Abstract

This article explores the impact of substrate choice on the sensitivity of sensors that utilize metallic terahertz metasurfaces as the actuating element. While terahertz metasurfaces represent a rapidly evolving field, fundamental research remains essential and highly impactful. A critical component of any metasurface is the dielectric substrate on which it is fabricated - a factor that holds significance across all spectral ranges. This work focuses specifically on metallic terahertz metasurfaces operating in transmission mode. It provides an overview of various substrates (Ge, Si, SiO₂, TPX) and discusses design principles for such metasurfaces, including magnetic and electric dipole surface plasmon resonances, Fano resonances, and quasi-bound states in the continuum. We initially simulated the structures using COMSOL Multiphysics software and then confirmed the results experimentally by detecting various concentrations of bovine serum albumin. Our study systematically examines how real-metal modeling and substrate selection influence the Q-factor and sensing performance, in contrast to earlier research that either fixed the substrate type or modeled the metal as a perfect electric conductor. This dual approach provides valuable guidance for designing high-Q, low-loss terahertz metasurface biosensors. Our results demonstrate that for all types of terahertz metasurfaces operating in transmission mode, using a low-refractive-index substrate enhances sensor sensitivity, making it the preferred choice for sensing applications. This opens new prospects for the design of high-sensitivity biosensors.

Indexed as

BiosensingBSAMetasurfaceSimulationsSubstrateTerahertz

Identifiers

PMID40804131
PMCPMC12350957

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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.