{"title":"远距离表面等离子体共振传感器的优化介电-等离子体界面","authors":"Rajeev Kumar, Shivam Singh, Rachana Arya, Mayank, Abdullah Saad Alsubaie, Amrindra Pal, Arshdeep Singh, Lalit Garia","doi":"10.1007/s10825-025-02403-5","DOIUrl":null,"url":null,"abstract":"<div><p>In this seminal work, we propose a novel-guided wave long-range surface plasmon resonance (GW-LRSPR) sensor. The multilayer sensor structure combines 2S2G prism, cytop, BaTiO<sub>3</sub>, and silver (Ag). The inclusion of barium titanate (BaTiO<sub>3</sub>: perovskite material), a material with high permittivity and piezoelectric properties, significantly enhances the imaging sensitivity (<i>S</i><sub>imag</sub>) of the proposed GW-LRSPR sensor as it allows for the tuning of the plasmonic response through electrical or mechanical stimuli. Additionally, the use of a Cytop layer as an insulating and protective dielectric layer further enhances the sensor’s durability and optical performance. By incorporating the BaTiO<sub>3</sub> layer, the sensor achieves a maximum <i>S</i><sub>imag</sub> of 73,031 RIU<sup>−1</sup>, significantly higher than the 44,542 RIU<sup>−1</sup> obtained without the layer. Hence, the GW-LRSPR sensor demonstrated strong capability in analyte detection. The sensor also exhibits a figure of merit (FoM) of 7.3 × 10<sup>6</sup> RIU<sup>−1</sup>, with detection accuracies (DA) of 169.49/° and 185.18/° for the LRSPR and GW-LRSPR sensors, respectively. Overall, the proposed GW-LRSPR sensor improves imaging sensitivity by nearly 64% compared to the LRSPR sensor.</p></div>","PeriodicalId":620,"journal":{"name":"Journal of Computational Electronics","volume":"24 5","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimized dielectric-plasmonic interfaces for long-range surface plasmon resonance sensors\",\"authors\":\"Rajeev Kumar, Shivam Singh, Rachana Arya, Mayank, Abdullah Saad Alsubaie, Amrindra Pal, Arshdeep Singh, Lalit Garia\",\"doi\":\"10.1007/s10825-025-02403-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this seminal work, we propose a novel-guided wave long-range surface plasmon resonance (GW-LRSPR) sensor. The multilayer sensor structure combines 2S2G prism, cytop, BaTiO<sub>3</sub>, and silver (Ag). The inclusion of barium titanate (BaTiO<sub>3</sub>: perovskite material), a material with high permittivity and piezoelectric properties, significantly enhances the imaging sensitivity (<i>S</i><sub>imag</sub>) of the proposed GW-LRSPR sensor as it allows for the tuning of the plasmonic response through electrical or mechanical stimuli. Additionally, the use of a Cytop layer as an insulating and protective dielectric layer further enhances the sensor’s durability and optical performance. By incorporating the BaTiO<sub>3</sub> layer, the sensor achieves a maximum <i>S</i><sub>imag</sub> of 73,031 RIU<sup>−1</sup>, significantly higher than the 44,542 RIU<sup>−1</sup> obtained without the layer. Hence, the GW-LRSPR sensor demonstrated strong capability in analyte detection. The sensor also exhibits a figure of merit (FoM) of 7.3 × 10<sup>6</sup> RIU<sup>−1</sup>, with detection accuracies (DA) of 169.49/° and 185.18/° for the LRSPR and GW-LRSPR sensors, respectively. Overall, the proposed GW-LRSPR sensor improves imaging sensitivity by nearly 64% compared to the LRSPR sensor.</p></div>\",\"PeriodicalId\":620,\"journal\":{\"name\":\"Journal of Computational Electronics\",\"volume\":\"24 5\",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational Electronics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10825-025-02403-5\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Electronics","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s10825-025-02403-5","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Optimized dielectric-plasmonic interfaces for long-range surface plasmon resonance sensors
In this seminal work, we propose a novel-guided wave long-range surface plasmon resonance (GW-LRSPR) sensor. The multilayer sensor structure combines 2S2G prism, cytop, BaTiO3, and silver (Ag). The inclusion of barium titanate (BaTiO3: perovskite material), a material with high permittivity and piezoelectric properties, significantly enhances the imaging sensitivity (Simag) of the proposed GW-LRSPR sensor as it allows for the tuning of the plasmonic response through electrical or mechanical stimuli. Additionally, the use of a Cytop layer as an insulating and protective dielectric layer further enhances the sensor’s durability and optical performance. By incorporating the BaTiO3 layer, the sensor achieves a maximum Simag of 73,031 RIU−1, significantly higher than the 44,542 RIU−1 obtained without the layer. Hence, the GW-LRSPR sensor demonstrated strong capability in analyte detection. The sensor also exhibits a figure of merit (FoM) of 7.3 × 106 RIU−1, with detection accuracies (DA) of 169.49/° and 185.18/° for the LRSPR and GW-LRSPR sensors, respectively. Overall, the proposed GW-LRSPR sensor improves imaging sensitivity by nearly 64% compared to the LRSPR sensor.
期刊介绍：
he Journal of Computational Electronics brings together research on all aspects of modeling and simulation of modern electronics. This includes optical, electronic, mechanical, and quantum mechanical aspects, as well as research on the underlying mathematical algorithms and computational details. The related areas of energy conversion/storage and of molecular and biological systems, in which the thrust is on the charge transport, electronic, mechanical, and optical properties, are also covered.
In particular, we encourage manuscripts dealing with device simulation; with optical and optoelectronic systems and photonics; with energy storage (e.g. batteries, fuel cells) and harvesting (e.g. photovoltaic), with simulation of circuits, VLSI layout, logic and architecture (based on, for example, CMOS devices, quantum-cellular automata, QBITs, or single-electron transistors); with electromagnetic simulations (such as microwave electronics and components); or with molecular and biological systems. However, in all these cases, the submitted manuscripts should explicitly address the electronic properties of the relevant systems, materials, or devices and/or present novel contributions to the physical models, computational strategies, or numerical algorithms.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
