Design and simulation of a graphene-integrated SPR biosensor for malaria detection
This work presents the theoretical design and optimization of a surface plasmon resonance (SPR) biosensor incorporating graphene, silicon nitride, and a thiol-tethered ssDNA layer for malaria detection and stage differentiation. Two configurations (Sys3 and Sys4) were simulated using the transfer ma...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-06-01
|
| Series: | Frontiers in Bioengineering and Biotechnology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2025.1580344/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849720326620971008 |
|---|---|
| author | Talia Tene Fabian Arias Arias Karina I. Paredes-Páliz Juan Carlos González García Nataly Bonilla García Cristian Vacacela Gomez |
| author_facet | Talia Tene Fabian Arias Arias Karina I. Paredes-Páliz Juan Carlos González García Nataly Bonilla García Cristian Vacacela Gomez |
| author_sort | Talia Tene |
| collection | DOAJ |
| description | This work presents the theoretical design and optimization of a surface plasmon resonance (SPR) biosensor incorporating graphene, silicon nitride, and a thiol-tethered ssDNA layer for malaria detection and stage differentiation. Two configurations (Sys3 and Sys4) were simulated using the transfer matrix method to determine optimal material thicknesses. The final designs were evaluated against three malaria stages—ring, trophozoite, and schizont—based on their refractive index variations. Sys3 achieved sensitivities of 353.14, 291.14, and 263.26°/RIU, while Sys4 reached 315.71, 294.81, and 268.65°/RIU, respectively. These values exceed those reported in comparable SPR platforms. Sys3 showed enhanced optical performance with a higher quality factor and lower detection limit, whereas Sys4 offered improved biomolecular recognition. Although limited to simulation, the proposed configurations demonstrate potential for label-free, stage-specific malaria diagnostics, supporting future development toward point-of-care applications. |
| format | Article |
| id | doaj-art-8a96be5d3e2f476ba08e032a8e9567c7 |
| institution | DOAJ |
| issn | 2296-4185 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj-art-8a96be5d3e2f476ba08e032a8e9567c72025-08-20T03:11:57ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852025-06-011310.3389/fbioe.2025.15803441580344Design and simulation of a graphene-integrated SPR biosensor for malaria detectionTalia Tene0Fabian Arias Arias1Karina I. Paredes-Páliz2Juan Carlos González García3Nataly Bonilla García4Cristian Vacacela Gomez5Department of Chemistry, Universidad Técnica Particular de Loja, Loja, EcuadorDepartment of Chemistry and Chemical Technologies, University of Calabria, Arcavacata, ItalyGrupo de Investigación en Salud Pública, Facultad de Ciencias de la Salud, Universidad Nacional de Chimborazo, Riobamba, EcuadorFacultad de Ciencias, Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, EcuadorFacultad de Ciencias, Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, EcuadorINFN-Laboratori Nazionali di Frascati, Frascati, ItalyThis work presents the theoretical design and optimization of a surface plasmon resonance (SPR) biosensor incorporating graphene, silicon nitride, and a thiol-tethered ssDNA layer for malaria detection and stage differentiation. Two configurations (Sys3 and Sys4) were simulated using the transfer matrix method to determine optimal material thicknesses. The final designs were evaluated against three malaria stages—ring, trophozoite, and schizont—based on their refractive index variations. Sys3 achieved sensitivities of 353.14, 291.14, and 263.26°/RIU, while Sys4 reached 315.71, 294.81, and 268.65°/RIU, respectively. These values exceed those reported in comparable SPR platforms. Sys3 showed enhanced optical performance with a higher quality factor and lower detection limit, whereas Sys4 offered improved biomolecular recognition. Although limited to simulation, the proposed configurations demonstrate potential for label-free, stage-specific malaria diagnostics, supporting future development toward point-of-care applications.https://www.frontiersin.org/articles/10.3389/fbioe.2025.1580344/fullsurface plasmon resonancekretschmann configurationtransfer matrix methodsilicon nitridegraphenebiosensors |
| spellingShingle | Talia Tene Fabian Arias Arias Karina I. Paredes-Páliz Juan Carlos González García Nataly Bonilla García Cristian Vacacela Gomez Design and simulation of a graphene-integrated SPR biosensor for malaria detection Frontiers in Bioengineering and Biotechnology surface plasmon resonance kretschmann configuration transfer matrix method silicon nitride graphene biosensors |
| title | Design and simulation of a graphene-integrated SPR biosensor for malaria detection |
| title_full | Design and simulation of a graphene-integrated SPR biosensor for malaria detection |
| title_fullStr | Design and simulation of a graphene-integrated SPR biosensor for malaria detection |
| title_full_unstemmed | Design and simulation of a graphene-integrated SPR biosensor for malaria detection |
| title_short | Design and simulation of a graphene-integrated SPR biosensor for malaria detection |
| title_sort | design and simulation of a graphene integrated spr biosensor for malaria detection |
| topic | surface plasmon resonance kretschmann configuration transfer matrix method silicon nitride graphene biosensors |
| url | https://www.frontiersin.org/articles/10.3389/fbioe.2025.1580344/full |
| work_keys_str_mv | AT taliatene designandsimulationofagrapheneintegratedsprbiosensorformalariadetection AT fabianariasarias designandsimulationofagrapheneintegratedsprbiosensorformalariadetection AT karinaiparedespaliz designandsimulationofagrapheneintegratedsprbiosensorformalariadetection AT juancarlosgonzalezgarcia designandsimulationofagrapheneintegratedsprbiosensorformalariadetection AT natalybonillagarcia designandsimulationofagrapheneintegratedsprbiosensorformalariadetection AT cristianvacacelagomez designandsimulationofagrapheneintegratedsprbiosensorformalariadetection |