Preparation of low-dimensional materials for plasmonic bio-sensing

Nano-bio-photonics is a unique blend of three primary disciplines namely nanotechnology, biological sciences and optics. Surface plasmons are free electron density waves that are a result of the photons interacting with the free electrons that reside on the surface of noble plasmonic metals like Gol...

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Main Author: Das, Chandreyee Manas
Other Authors: Poenar Daniel Puiu
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/154742
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Institution: Nanyang Technological University
Language: English
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institution Nanyang Technological University
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continent Asia
country Singapore
Singapore
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language English
topic Science::Physics::Optics and light
spellingShingle Science::Physics::Optics and light
Das, Chandreyee Manas
Preparation of low-dimensional materials for plasmonic bio-sensing
description Nano-bio-photonics is a unique blend of three primary disciplines namely nanotechnology, biological sciences and optics. Surface plasmons are free electron density waves that are a result of the photons interacting with the free electrons that reside on the surface of noble plasmonic metals like Gold (Au) and Silver (Ag). The field of plasmonic bio-sensing falls under this domain. Plasmonic bio-sensors offer unique advantages over other sensors based on different methodologies like real-time, label-free detection, reusability of sensor chips and high accuracy results that are repeatable in nature. These sensors work on the basis of basic principle of Surface Plasmon Resonance (SPR) which is a physical phenomenon that occurs with the interaction between electromagnetic (EM) light wave and nano-sized plasmonic metals like Au and Ag. Bio-molecular interactions that occur at the sensor surface have the ability to change the R.I. of the analyte medium. The change in this parameter produces a change in the optical parameter like the resonance angle, the phase shift of the reflected p-polarised light w.r.t. the s-polarised light or Goos-Hanchen (GH) shift between p and s polarised reflected light waves. Thus, a change in these optical parameters can be used to detect bio-molecular interactions occurring at the sensor surface. The sensitivity of these SPR sensors play an important role in the precision and accuracy of detection of bio-molecular ligand-analyte or protein-protein interactions. Sensitivity in general can be defined as the differential change in optical parameter viz. the SPR angle, phase or GH shift w.r.t the change in the R.I. of the analyte medium. Conventional sensors employ the Kretschmann configuration which is 50 nm Au coated on a high R.I. prism. A lot of research has been carried out on simulation that involves proposal of multi-layered SPR structures. However, most of these works propose structures that give good sensitivity results. In reality, simulation can be used only for preliminary assessment of multiple models where the output parameters can be compared for the sake of better understanding. Actual development of the proposed model will have many uncertain conditions like the quality of the nanomaterials fabricated, closeness and compactness of the SPR senor packing, variation of refractive indices and thicknesses with temperature, pressure and mechanical stress that can lead to loss of sensitivity. During the entire research duration of two and a half years, we focused on the use of simulation methods in predicting the sensitivity of SPR structures made of hybrid multi-layer low dimensional materials. We particularly focused on ARC materials like titania and silica and Transition Metal Dichalcogenides (TMDC) materials like WS2, MoS2, WSe2 and MoSe2. Although we use similar methods as given in previous related research works, we present a broader analysis where we evaluate the titania and silica sensor model at various wavelengths. Our Si-ARC-TMDC sensor model discussed in chapter 5 is an extension of a previously proposed Si-TMDC model. With an in-depth analysis of multiple sensor configurations, we highlight the importance of simulation as a basic step towards the realization and development of efficient sensors. Also, when the thickness of the dielectric layer(s) above and/or below the SPR metal film is below a threshold value of 3 nm, the non-locality effect comes into picture where the metal can no longer be represented by a bulk permittivity. In these cases, the evaluation method needs to be modified so that the non-local effect can be considered. Work that had been previously published did not consider such restrictions that are placed on the conventional method. Here, in this work, in addition to evaluating the sensitivity of multi-layered models, we also present a method by which the conventional procedure can be modified so that the sensitivity of plasmonic structures having extremely thin-layered dielectric coatings can be evaluated. Additionally, using commercial SPR sensor Biacore 3000, we evaluated the plasmonic capabilities of TMDC coated Au chips to detect protein-protein interactions. Many earlier research works have focused on the development of their own custom-made SPR sensors using TMDC materials like graphene and MoS2. Many such works promised functionalization-free sensing of bio-molecules. With such inspiration, with the help of commercial sensors we performed an initial assessment of multiple TMDC based arrangements to arrive at the best configuration that we used further for functionalization-free sensing of protein-protein interactions. With this our motive was to show how TMDC based functionalization-free SPR sensors can also be realized in the domain of commercial sensing platforms. Lastly, we performed some optical experiments (GH shift sensitivity) to compare the sensitivities of pure Au and graphene coated Au chips. Very few researchers have focused on actual GH shift sensing experimental works and hence with this we intend to setup some initial basic work in this area that can be further utilized and developed in a better way in terms of experiment protocol and system design in order to realize effective GH shift based SPR sensors. To conclude, our research work focuses on two aspects. The first is the theoretical approach where we use simulation in designing plasmonic sensor schemes and consecutively predict the sensitivities of those sensor layouts and the second part is where we focus on the experimental side where we perform both biological and optical experiments to evaluate the efficiency of plasmonic sensitivity enhancement capabilities of two-dimensional (2D) materials. To conclude the entire research work and highlight the main achievements, following are the milestones that were achieved during the duration of the research period: A Titania and Silica-based SPR structure was proposed and the performance of the sensor was done using the Transfer Matrix Method (TMM). The best sensitivity of 214 deg/RIU was obtained at 532 nm for 40 nm Au, 3 nm SiO2 and 9 nm TiO2. An Anti-Reflective coating (ARC) and Transition Metal Dichalcogenides (TMDC)-based SPR structure was proposed that gave the best sensitivity of 284 deg/RIU at 633 nm for 50 nm Au, 95 nm TiO2, 20 nm SiO2 and 1.4 nm of WSe2. A plasmonic structure using Au and Au + Graphene was realized that could be used for the detection of human respiratory viruses. The performance was anlayzed at 690 nm, 780 nm and 930 nm. With the Au only layout, a minimum detection limit of 0.0669 HAU can be obtained at 690 nm and a maximum sensitivity of 500 deg/RIU and an average sensitivity of 122.4±38.68 deg/RIU can be obtained at 780 nm. With additional 15 layers of 0.34 nm Graphene, a minimum detection limit of 0.0188 HAU, maximum sensitivity of 1428.6 deg/RIU and an average sensitivity of 172.04±86.04 deg/RIU can be obtained at 690 nm. A Au nanorod-based sandwich type plasmonic structure scheme was proposed for the detection of SARS-CoV-2 virus. The electric field distribution was analyzed for various configurations of the Au NR. As compared to the Au only structure, the Au NR-based structure gave a maximum enhancement of 10.2 times when the aspect ratio of Au NR was four and it was located 2 nm from the Au nanosheet. A plasmonic performance comparison for various configurations of two-dimensional (2D) materials – Graphene, MoS2 and WS2 was studied using commercial SPR Biacore T200 sensor. The configuration of Au + Graphene + WS2 gave maximum sensitivity enhancement of 4.66% as compared to only Au. Protein-protein interaction study between Bovine Serum Albumin (BSA) and Anti-BSA was studied using Biacore 3000 for Graphene-WS2 modified Au chips. Functionalization-free bio-sensing of proteins could be achieved with a minimum detection limit of 0.44 μg/mL. Goos-Hanchen shift SPR sensing method was used to compare the sensitivities of Au and Au + Graphene sensors. The Graphene modified SPR chip gave a sensitivity enhancement of 2.35 times.
author2 Poenar Daniel Puiu
author_facet Poenar Daniel Puiu
Das, Chandreyee Manas
format Thesis-Doctor of Philosophy
author Das, Chandreyee Manas
author_sort Das, Chandreyee Manas
title Preparation of low-dimensional materials for plasmonic bio-sensing
title_short Preparation of low-dimensional materials for plasmonic bio-sensing
title_full Preparation of low-dimensional materials for plasmonic bio-sensing
title_fullStr Preparation of low-dimensional materials for plasmonic bio-sensing
title_full_unstemmed Preparation of low-dimensional materials for plasmonic bio-sensing
title_sort preparation of low-dimensional materials for plasmonic bio-sensing
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/154742
_version_ 1772829003178049536
spelling sg-ntu-dr.10356-1547422023-07-04T17:41:55Z Preparation of low-dimensional materials for plasmonic bio-sensing Das, Chandreyee Manas Poenar Daniel Puiu School of Electrical and Electronic Engineering CINTRA EPDPuiu@ntu.edu.sg Science::Physics::Optics and light Nano-bio-photonics is a unique blend of three primary disciplines namely nanotechnology, biological sciences and optics. Surface plasmons are free electron density waves that are a result of the photons interacting with the free electrons that reside on the surface of noble plasmonic metals like Gold (Au) and Silver (Ag). The field of plasmonic bio-sensing falls under this domain. Plasmonic bio-sensors offer unique advantages over other sensors based on different methodologies like real-time, label-free detection, reusability of sensor chips and high accuracy results that are repeatable in nature. These sensors work on the basis of basic principle of Surface Plasmon Resonance (SPR) which is a physical phenomenon that occurs with the interaction between electromagnetic (EM) light wave and nano-sized plasmonic metals like Au and Ag. Bio-molecular interactions that occur at the sensor surface have the ability to change the R.I. of the analyte medium. The change in this parameter produces a change in the optical parameter like the resonance angle, the phase shift of the reflected p-polarised light w.r.t. the s-polarised light or Goos-Hanchen (GH) shift between p and s polarised reflected light waves. Thus, a change in these optical parameters can be used to detect bio-molecular interactions occurring at the sensor surface. The sensitivity of these SPR sensors play an important role in the precision and accuracy of detection of bio-molecular ligand-analyte or protein-protein interactions. Sensitivity in general can be defined as the differential change in optical parameter viz. the SPR angle, phase or GH shift w.r.t the change in the R.I. of the analyte medium. Conventional sensors employ the Kretschmann configuration which is 50 nm Au coated on a high R.I. prism. A lot of research has been carried out on simulation that involves proposal of multi-layered SPR structures. However, most of these works propose structures that give good sensitivity results. In reality, simulation can be used only for preliminary assessment of multiple models where the output parameters can be compared for the sake of better understanding. Actual development of the proposed model will have many uncertain conditions like the quality of the nanomaterials fabricated, closeness and compactness of the SPR senor packing, variation of refractive indices and thicknesses with temperature, pressure and mechanical stress that can lead to loss of sensitivity. During the entire research duration of two and a half years, we focused on the use of simulation methods in predicting the sensitivity of SPR structures made of hybrid multi-layer low dimensional materials. We particularly focused on ARC materials like titania and silica and Transition Metal Dichalcogenides (TMDC) materials like WS2, MoS2, WSe2 and MoSe2. Although we use similar methods as given in previous related research works, we present a broader analysis where we evaluate the titania and silica sensor model at various wavelengths. Our Si-ARC-TMDC sensor model discussed in chapter 5 is an extension of a previously proposed Si-TMDC model. With an in-depth analysis of multiple sensor configurations, we highlight the importance of simulation as a basic step towards the realization and development of efficient sensors. Also, when the thickness of the dielectric layer(s) above and/or below the SPR metal film is below a threshold value of 3 nm, the non-locality effect comes into picture where the metal can no longer be represented by a bulk permittivity. In these cases, the evaluation method needs to be modified so that the non-local effect can be considered. Work that had been previously published did not consider such restrictions that are placed on the conventional method. Here, in this work, in addition to evaluating the sensitivity of multi-layered models, we also present a method by which the conventional procedure can be modified so that the sensitivity of plasmonic structures having extremely thin-layered dielectric coatings can be evaluated. Additionally, using commercial SPR sensor Biacore 3000, we evaluated the plasmonic capabilities of TMDC coated Au chips to detect protein-protein interactions. Many earlier research works have focused on the development of their own custom-made SPR sensors using TMDC materials like graphene and MoS2. Many such works promised functionalization-free sensing of bio-molecules. With such inspiration, with the help of commercial sensors we performed an initial assessment of multiple TMDC based arrangements to arrive at the best configuration that we used further for functionalization-free sensing of protein-protein interactions. With this our motive was to show how TMDC based functionalization-free SPR sensors can also be realized in the domain of commercial sensing platforms. Lastly, we performed some optical experiments (GH shift sensitivity) to compare the sensitivities of pure Au and graphene coated Au chips. Very few researchers have focused on actual GH shift sensing experimental works and hence with this we intend to setup some initial basic work in this area that can be further utilized and developed in a better way in terms of experiment protocol and system design in order to realize effective GH shift based SPR sensors. To conclude, our research work focuses on two aspects. The first is the theoretical approach where we use simulation in designing plasmonic sensor schemes and consecutively predict the sensitivities of those sensor layouts and the second part is where we focus on the experimental side where we perform both biological and optical experiments to evaluate the efficiency of plasmonic sensitivity enhancement capabilities of two-dimensional (2D) materials. To conclude the entire research work and highlight the main achievements, following are the milestones that were achieved during the duration of the research period: A Titania and Silica-based SPR structure was proposed and the performance of the sensor was done using the Transfer Matrix Method (TMM). The best sensitivity of 214 deg/RIU was obtained at 532 nm for 40 nm Au, 3 nm SiO2 and 9 nm TiO2. An Anti-Reflective coating (ARC) and Transition Metal Dichalcogenides (TMDC)-based SPR structure was proposed that gave the best sensitivity of 284 deg/RIU at 633 nm for 50 nm Au, 95 nm TiO2, 20 nm SiO2 and 1.4 nm of WSe2. A plasmonic structure using Au and Au + Graphene was realized that could be used for the detection of human respiratory viruses. The performance was anlayzed at 690 nm, 780 nm and 930 nm. With the Au only layout, a minimum detection limit of 0.0669 HAU can be obtained at 690 nm and a maximum sensitivity of 500 deg/RIU and an average sensitivity of 122.4±38.68 deg/RIU can be obtained at 780 nm. With additional 15 layers of 0.34 nm Graphene, a minimum detection limit of 0.0188 HAU, maximum sensitivity of 1428.6 deg/RIU and an average sensitivity of 172.04±86.04 deg/RIU can be obtained at 690 nm. A Au nanorod-based sandwich type plasmonic structure scheme was proposed for the detection of SARS-CoV-2 virus. The electric field distribution was analyzed for various configurations of the Au NR. As compared to the Au only structure, the Au NR-based structure gave a maximum enhancement of 10.2 times when the aspect ratio of Au NR was four and it was located 2 nm from the Au nanosheet. A plasmonic performance comparison for various configurations of two-dimensional (2D) materials – Graphene, MoS2 and WS2 was studied using commercial SPR Biacore T200 sensor. The configuration of Au + Graphene + WS2 gave maximum sensitivity enhancement of 4.66% as compared to only Au. Protein-protein interaction study between Bovine Serum Albumin (BSA) and Anti-BSA was studied using Biacore 3000 for Graphene-WS2 modified Au chips. Functionalization-free bio-sensing of proteins could be achieved with a minimum detection limit of 0.44 μg/mL. Goos-Hanchen shift SPR sensing method was used to compare the sensitivities of Au and Au + Graphene sensors. The Graphene modified SPR chip gave a sensitivity enhancement of 2.35 times. Doctor of Philosophy 2022-01-10T03:28:38Z 2022-01-10T03:28:38Z 2021 Thesis-Doctor of Philosophy Das, C. M. (2021). Preparation of low-dimensional materials for plasmonic bio-sensing. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/154742 https://hdl.handle.net/10356/154742 10.32657/10356/154742 en NRF2017-NRF-ANR002 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University