SERS-based sensors for bacteria detection

SERS-based sensors

for bacteria detection

Ana Isabel Fernández-Tresguerres Mata

Department of Physics and Astronomy 2019

Supervisor

Prof. Dra. Célia Tavares de Sousa, Faculty of Sciences of the University of Porto

Co-supervisor

Prof. Dr. Joaquim Agostinho Gomes Moreira, Faculty of Sciences of the University of Porto

Todas as correções determinadas pelo júri, e só essas, foram efetuadas. O Presidente do Júri,

Ana Isabel Fern´

andez-Tresguerres Mata

SERS-based sensors for bacteria

detection

Supervisor: C´elia Tavares de Sousa

co-Supervisor: Joaquim Agostinho Gomes Moreira

Master Degree in Medical Physics

Department of Physics and Astronomy

Faculty of Sciences of the University of Porto

Acknowledgments

Throughout this year of work and learning, there have been numerous people who collab-orated so that this work came to fruition. I would like to thank my supervisor, Professor C´elia Tavares de Sousa, for her enormous dedication and time invested in helping whenever necessary. I also thank my co-supervisor Professor Joaquim Agostinho Gomes Moreira for all his help, time and experience transmitted with the SERS measurements. I would like to highlight from both, my supervisor and my co-supervisor the good work environment in which they made me feel from the beginning, I appreciate that they made of my first contact with what research is, a real success. For making me enjoy thinking and hanging around in the head about how to solve the problems that arose, always wanting to find answers and leaving me curious craving for more.

I have to thank Professor Maria Jesus Matos Gomes for my collaboration with Uni-versidade do Minho, Physics Center of Universities of Minho and Porto (CF-UM-UP) and especially to Jos´e Pedro Basto da Silva for his excellent help with the samples made in Braga, help for which I am immensely grateful.

Thanks to the IFIMUP-IN group for all the work done in template-assisted methods and Raman spectroscopy. In particular, I am very grateful to Suellen Silveira Moraes for all the patience and time that she dedicates in the laboratory to teach all the techniques performed. I also want to thank Paula Quit´erio for always being available to land a hand, and Arlete Apolin´ario. Thanks to Rui Vilarinho Silva for teaching me at the Raman laboratory, and to all the IFIMIP-IN group for the good work environment.

I thank Professor Eulalia Carvalho Pereira for her support in assessing the results obtained by SERS with DTNB and Miguel Peixoto de Almeida for his help with the preparation of the DTNB, both from the Chemistry and Biochemistry Department of FCUP. I also thank Cl´audia Gomes Espinha for the support in the initial phase of working with DTNB.

I would like to thank the Universidade Cat´olica do Porto, Centre for Biotechnology and Fine Chemistry (CBQF) Faculty of Biotechnology, especially Ana Freita and Ana Maria Gomes for their advice and help, and also to Ruth Pereira from the Department of Biology of FCUP, Universidade do Porto.

Thanks to the coordinators of the Master in Medical Physics, Professor Joaquim Agostinho Gomes Moreira and Professor Carla Carmelo Rosa, as well as all people who intervened in my academic background, for the opportunity given. A special thanks also to all my classmates in the master, it was a pleasure.

In a more personal section, I want to thank my family for these two years. To my grandparents, “Yeya y Tot´o” and my parents, Olimpia y Jos´e Ram´on, “mam´a y pap´a”, for all the immense effort made, I am eternally grateful. Despite the separate time we spent, they always made me feel that support and incredible energy that unites us, thanks for being my treasure. Last but not least, thanks to Francisco Leonardo, the new component of my family that I met here, for taking care of me, for always being with me and for sharing my happiness and sadness, always grateful. For the past that unites us of these two incredible years, the present and the future that lies ahead, because I will see all the incredible things that you will achieve, proud of you.

Resumo

Doen¸cas transmitidas por alimentos associadas a pat´ogenos representam uma s´eria amea¸ca para a sa´ude humana. Al´em do grande esfor¸co para a implementa¸c˜ao de sistemas confi´aveis de controle de qualidade, os m´etodos convencionais de detec¸c˜ao dispon´ıveis para pat´ogenos s˜ao demorados e trabalhosos [1].

Atualmente, a Espectroscopia Raman amplificada por superf´ıcie (SERS) tem sido aplicada com sucesso para detec¸c˜ao r´apida e altamente seletiva de analitos, mesmo em pequenas concentra¸c˜oes ou na presen¸ca de contaminantes [1]. No entanto, essa t´ecnica anal´ıtica exige a produ¸c˜ao de substratos plasm´onicos de alta qualidade [2-8].

Neste trabalho, descrevemos o desenho, fabrica¸c˜ao e caracteriza¸c˜ao estrutural, ´optica e morfol´ogica de substratos SERS, constitu´ıdos por nanopart´ıculas de Ag depositadas em substratos de vidro por m´etodos de deposi¸c˜ao por laser pulsado e deposi¸c˜ao por feixe de i˜oes [2], bem como nanofios e dendrites de Au obtidos por eletrodeposi¸c˜ao assistida [8]. A caracteriza¸c˜ao do desempenho de SERS dos substratos de nanopart´ıculas de Ag, nanofius e dendrites de Au fabricados foi realizada atrav´es da an´alise dos espectros Raman e SERS do reagente Ellman (DTNB) e do anticorpo Verotoxin como analitos modelo.

Palavras chave: Surface Enhanced Raman Spectroscopy, Surface Plasmon Reso-nance, SERS Bacteria Sensors, Nanoparticles Deposition, Template Assisted Electrode-position.

Abstract

Foodborne illnesses associated with pathogens pose serious threat to human health. Be-sides the large effort towards the implementation of reliable quality control systems, the available conventional detection methods for pathogens are time consuming and laborious [1].

Nowadays, Surface Enhanced Raman Spectroscopy (SERS) has been successfully applied for rapid and high selective detection of analytes, even in small concentrations or in the presence of contaminants [1]. However, this analytic technique demands the production of high quality plasmonic substrates [2-8].

In this work, we describe the design, fabrication and structural, optical and morphological characterization of SERS substrates, consisting on Ag nanoparticles deposited onto glass substrates by pulsed laser deposition and ion beam deposition methods [2] as well as Au nanorods and dendrites obtained by template assisted electrodeposition [8]. The SERS performance characterization of the as-processed Ag nanoparticles, Au nanorods and dendrites substrates was done by analysing the Raman and SERS spectra of Ellman’s reagent (DTNB) and antibody Verotoxin as model analytes.

Key words: Surface Enhanced Raman Spectroscopy, Surface Plasmon Resonance, SERS Bacteria Sensors, Nanoparticles Deposition, Template Assisted Electrodeposition.

List of Figures

1.1 Bacterial quorum sensing, from low to high cell density. . . 4

1.2 Scheme of the EM field of SPPs propagating along the interface betweeen a metal and a dielectric [23]. . . 7

1.3 Scheme of plasmon oscillation for a sphere [28]. . . 7

1.4 Scheme of the interaction between a metallic sphere and an electric field [26]. 8 1.5 Absolute value (|α|) and phase (Arg(α)) of the polarizability as a function of the energy, fitting the dielectric function of silver [26]. . . 9

1.6 RS spectrum representing the vibrational frequencies of Rhodamine 6G. . . 11

1.7 Raman and Rayleigh phenomena depicted in the energy diagram. . . 11

1.8 Interaction between a molecule, placed close to a metallic nanostructure, with polarizability α and the exciting field E0 that gives rise to a scattered field ES [18]. . . 12

1.9 SERS spectra of Pyocyanin at different concentrations (0.1nM to 100µM ) [1]. . . 16

1.10 Optical properties of Au-NRs with different aspect-ratios (length/width) [27]. . . 17

1.11 PAA scheme, adapted from [46]. . . 19

1.12 Current density vs time and diagram of the four phases of PAA formation during anodization [47]. . . 20

1.13 Two-anodization process scheme [47]. . . 20

1.14 Scheme of plasmonic structures and nanoporous platform: (a) Porous an-odic alumina (PAA) + Au nanorods/Au dendrites (Au-NRs/Au-Ds) ob-tained by electrodeposition inside of the PAA; (b) PAA + Ag nanoparti-cles (Ag-NPs) obtained by Pulsed laser deposition (PLD) and Ion beam deposition (IBD), just joining both parts. . . 22

1.15 Chemical structure of Ellman’s reagent (DNTB). . . 23

1.16 SERS spectra of DTNB with concentrations ranging from 100 nM to 10 pM on: (a) ITO gratings; (b) Ag-NPs [55]. . . 23

1.17 Chemical structure of Shiga-toxin (Stx) receptor (Gb3) [58]. . . 24

2.1 PLD scheme. . . 27

2.2 IBD scheme. . . 28

2.3 Electropolishing set-up. . . 30

2.4 (a) Two-step anodization process for the first samples prepared by PAA technique; (b) Two-step anodization process for the second samples pre-pared by PAA technique. . . 31

2.6 (a) Sample electrodeposited; (b) First substrates by PAA without elec-trodeposition. . . 33 2.7 (a) Charge as a function of time from electrodeposition of the first

sub-strates by PAA, Au NRs PAA n (n=1 to 3); (b) Current as a function of time from electrodeposition of the first substrates by PAA, Au NRs PAA n (n=1 to 3). . . 34 2.8 (a) Charge as a function of time from electrodeposition of the second

substrates by PAA, Au NRs PAA n (n=4 to 7); (b) Current as a func-tion of time from electrodeposifunc-tion of the second substrates by PAA, Au

NRs PAA n (n=4 to 7). . . 34 2.9 Voltage behaviour during the deposition pulse at constant current for the

Ds substrates, Au Ds PAA n (n=1 to 4). . . 35 2.10 Schematic illustration of a Bragg reflection from a particular family of

lattice planes, separated by a distance d. Path difference: 2dhlksinθ [68]. . 36

3.1 (a) XRD pattern of Ag-NPs in substrates by IBD, Ag NPs IBD n (n=1 to 3); (b) XRD pattern of Ag-NPs in substrates by PLD, Ag NPs PLD n (n=3 to 5). . . 40 3.2 XRD spectra of Au-NRs in substrates by PAA, Au NRs PAA n (n=4 to 7). 41 3.3 SEM imaging and NPs size distribution of each sample made by PLD.

Deposition times for samples Ag NPs PLD n (n=1,3,4,5,6,7): 1-30s;

3-90s; 4-120s; 5-180s; 6-60s; 7-30s. . . 44 3.4 Mean NPs diameter and mean surface density evolution of Ag-NPs samples

by PLD for the different deposition times, Ag NPs PLD n (n=1,3,4,5,6,7). The black bars correspond to the standard error in the NPs diameter. . . . 46 3.5 SEM imaging and NPs size distribution of each sample made by IBD.

Deposition times for samples Ag NPs IBD n (n=1 to 3): 1-15s; 2-30s;

3-45s. . . 47 3.6 Mean NPs diameter and mean surface density evolution of Ag-NPs samples

by IBD for the different deposition times, Ag NPs IBD n (n=1 to 3). The black bars correspond to the standard error in the NPs diameter. . . 48 3.7 SEM images of a representative sample (Au NRs PAA 6) measured in

backscattering mode. Captures of: (a) Top view; (b) Enlargement over the top view. . . 49 3.8 SEM images of a representative sample (Au NRs PAA 6) measured in

backscattering mode. Captures of: (a) Bottom view; (b) Enlargement over the bottom view. . . 49 3.9 SEM images of representatives samples (Au NRs PAA 1 for (a), (b) and

(c)) and (Au Ds PAA 3 for (d)). Captures of: (a) Total thickness; (b) Au-NRs; (c) Pores; (d) Ds electrodeposited with Au. . . 50 3.10 Mean height distribution of Au-NRs in first and second samples by PAA,

Au NRs PAA n (n=1 to 7). . . 52 3.11 Mean height distribution of Au-Ds in samples by PAA, Au Ds PAA n (n=2

to 4). . . 52 3.12 AFM imaging and height line profile of each substrate prepared by PLD,

3.13 AFM imaging and height line profile of each substrate prepared by IBD, Ag NPs IBD n (n=1 to 3). . . 57 3.14 3D surface morphology of substrates prepared by PLD and IBD. . . 59 3.15 (a) UV-Vis absorbance spectra from samples made by PLD, Ag NPs PLD n

(n=1 to 7); (b) UV-Vis absorbance spectra from samples made by IBD, Ag NPs IBD n (n=1 to 3). The UV-Vis absorbance spectrum of the clean glass substrate is also shown in (a). . . 60 3.16 Comparison of size obtained by SEM with the UV-Vis spectra: (a) PLD

samples, Ag NPs PLD n (n=1,3,4,5,6,7) ; (b) IBD samples, Ag NPs IBD n (n=1 to 3). The black bars correspond to the standard error in the NPs diameter. . . 62 3.17 Absorbance maximum peaks vs deposition times for: (a) PLD samples,

Ag NPs PLD n (n=1 to 7); (b) IBD samples, Ag NPs IBD n (n=1 to 3). . 63 3.18 UV-Vis absorbance spectra from samples made by PAA, Au NRs PAA n

(n=1 to 3). The UV-Vis absorbance spectrum of the alumina substrate is also shown. . . 63 4.1 (a) Signal of the substrates prepared by PLD without analyte, Ag NPs PLD n

(n=1,2,3,5,6). Measurement on the NPs surface. (b) Signal of the sub-strates prepared by IBD without analyte, Ag NPs IBD n (n=1 to 3). Mea-surement on the NPs surface. . . 64 4.2 Signal of a representative sample of each method PLD and IBD techniques

without analyte. Measurement on the glass surface. . . 65 4.3 Raman signal of methanol [76]. . . 66 4.4 (a) SERS spectra of methanol over sample Ag NPs IBD 3, evolution while

evaporating. (b) SERS spectra of methanol over sample Ag NPs IBD 2, evolution while evaporating. . . 67 4.5 SERS spectra of methanol over sample Ag NPs IBD 1, evolution while

evaporating. . . 67 4.6 Representative unpolarized Raman spectrum of DTNB molecule deposited

onto a clean glass substrate. . . 68 4.7 Representative example of the best fit (equation 2.7) to the Raman

spec-trum of DTNB. . . 69 4.8 SERS and Raman spectra of DTNB [77]. . . 69 4.9 Two zones where the spectrum was measured to test response,

representa-tive sample. . . 71 4.10 (a) Comparison between samples prepared by PLD, Ag NPs PLD n (n=1,6,7)

and glass, DTNB concentration for both: 10mM . (b) Comparison between samples prepared by PLD, Ag NPs PLD n (n=4,5,7) and glass, DTNB con-centration for both: 10mM . . . 72 4.11 Comparison between IBD spectra, Ag NPs IBD n (n=1 to 3) for three

different DTNB concentrations: 10mM , 10µM and 10nM . . . 74 4.12 SERS spectra of the DTNB molecule onto sample Ag NPs IBD 3. DTNB

Concentration: 1mM . (a) Complete evolution. (b) Enlarge view of the spectra recorded over the wet stage. . . 75

4.13 SERS spectra of the DTNB molecule onto sample Ag NPs IBD 3. DTNB Concentration: 0.1mM . (a) Complete evolution. (b) Enlarge view of the spectra recorded over the wet stage. . . 75 4.14 SERS spectra of the DTNB molecule onto sample Ag NPs IBD 3. DTNB

Concentration: 0.1µM . (a) Complete evolution. (b) Enlarge view of the spectra recorded over the wet stage. . . 76 4.15 (a) Raman signal of clean Au-NRs substrate by PAA. (b) Not

electrode-posited PAA with bottom pores opened, PAA just on top of the different IBD substrates. Analyte DTNB over the PAA, concentration 10mM . . . . 77 4.16 (a) Au-NRs prepared by PAA technique from the second PAA batch, tested

with DTNB 10mM while solvent is still liquid. (b) Raman spectra of sample Au NRs PAA 6 tested with different concentrations while solvent is still liquid. . . 78 4.17 (a) Raman spectra of sample Au NRs PAA 6 tested with different

con-centrations while solvent is evaporating. (b) Raman spectra of sample Au NRs PAA 6 tested with different concentrations when solvent is evap-orated. . . 79 4.18 (a) Spectra comparison from samples Au NRs PAA 6 and Ag NPs IBD 2

when solvent evaporates. DTNB concentration: 10mM . (b) Spectra com-parison from samples Au NRs PAA 6 and Ag NPs IBD 2 when solvent evaporates. DTNB concentration: 1mM . . . 80 4.19 Spectra comparison from samples Au NRs PAA 6 and Ag NPs IBD 2 when

solvent evaporates. DTNB concentration: 0.1mM . . . 80 4.20 (a) Spectra of Ds substrates, Au Ds PAA n (n=1 to 4) without analyte; (b)

Spectra of Ds substrate, Au Ds PAA 4 with analyte, DTNB concentration: 10mM . . . 81 4.21 Spectra of Ds substrates, Au Ds PAA n (n=1 to 3). (a) With analyte while

solvent is still liquid, DTNB concentration: 10mM ; (b) With analyte when solvent evaporating, DTNB concentration: 10mM . . . 81 4.22 Spectra of Ds substrates, Au Ds PAA n (n=1 to 3) with analyte when

solvent is evaporated, DTNB concentration: 10mM . . . 82 4.23 Spectra of antibody Verotoxin over the samples prepared by IBD, Ag NPs IBD n

(n=1 to 3) and glass. (a) Antibody concentration: 1mg/ml; (b) Antibody concentration: 0.001mg/ml. . . 83 4.24 Crystal formed by the solution with the antibody after some minutes. . . . 84 4.25 Spectra of samples prepared by IBD, Ag NPs IBD n (n=1 to 3) and glass

substrate with antibody concentration: 0.001mg/ml. (a) Measured while solvent is still liquid; (b) Measured when evaporated (crystals). . . 84

List of Tables

2.1 Experimental parameters for the Ag-NPs substrates, fabrication by PLD. . 27

2.2 Experimental parameters for the Ag-NPs substrates, fabrication by IBD. . 29

2.3 Methods, materials and electrodeposition parameters for the substrates made by PAA, NRs and Ds. . . 33

3.1 Mean GS and crystal structure for samples made by PLD. . . 41

3.2 Mean GS and crystal structure for samples made by IBD. . . 41

3.3 Mean GS and crystal structure for samples made by PAA. . . 42

3.4 Data obtained from SEM images of samples made by PLD. . . 45

3.5 Data obtained from SEM images of samples made by IBD. . . 48

3.6 Data obtained from SEM images of samples made by PAA. . . 51

3.7 Difference between projected surface area (the scanned area) and the real surface area obtained from AFM for the different samples, and comparison with the effective areas obtained by SEM. . . 60

3.8 Absorbance maximum peaks and mean NPs diameter for samples made by PLD. . . 61

3.9 Absorbance maximum peaks and mean NPs diameter for samples made by IBD. . . 62

3.10 Absorbance maximum peaks and mean NRs height for samples made by PAA. . . 63

4.1 Vibration modes and frequencies for SERS and Raman spectra of DTNB [77]. . . 70

4.2 AEF for substrates by PLD in Figures 4.10 (a) and (b). . . 72

4.3 AEFs for the samples Ag NPs IBD 1, Ag NPs IBD 2 and Ag NPs IBD 3 with different concentrations. . . 74

4.4 AEF for the sample Au NRs PAA 6 with different concentrations when solvent evaporates. . . 79

4.5 AEFs for the best two Ds samples, Figures 4.20 (b) and 4.22. . . 82

List of Abbreviations

• SERS: Surface-Enhanced Raman Spectroscopy

• RS: Raman Scattering

• EM: Electromagnetic

• SPP: Surface Plasmon Polariton

• LSP: Localized Surface Plasmon

• EF: Enhancement Factor

• AEF: Analytical Enhancement Fac-tor

• QS: Quorum Sensing

• PLD: Pulsed Laser Deposition

• PVD: Physical Vapor Deposition

• IBD: Ion Beam Deposition

• PAA: Porous Anodic Alumina

• NPs: Nanoparticles

• NRs: Nanorods

• Ds: Dendrites

• DC: Direct Current

• AC: Alternating Current

• PED: Pulsed Electrodeposition

• GS: Grain Size

• DTNB: Ellman’s reagent

• XRD: X-Ray Diffraction

• UV-Vis: Ultraviolet-Visible spec-troscopy

• SEM: Scanning Electron Microscopy

• AFM: Atomic Force Microscopy

• LOD: Limit Of Detection

• CEMUP: “Centro de Materiais da Universidade do Porto”

• IFIMUP: “Instituto de F´ısica dos Materiais, Universidade do Porto”

Contents

1.2.1 Surface plasmons polaritons . . . 5

1.2.2 Localized surface plasmons . . . 7

1.2.3 Surface-enhanced raman spectroscopy . . . 10

1.2.3.1 Raman scattering . . . 10

1.2.3.2 SERS . . . 12

1.3 SERS bacteria sensors . . . 15

1.3.1 Literature review . . . 15

1.3.1.1 Porous anodic alumina: Au nanorods and dendrites . . . . 18

1.3.2 Substrate election . . . 22

1.3.3 Analyte election . . . 22

1.4 Objectives . . . 25

2 Experimental details 26 2.1 Substrate fabrication methods and materials . . . 26

2.1.1 Pulsed laser deposition . . . 27

2.1.2 Ion beam deposition . . . 28

2.1.3 Porous anodic alumina . . . 29

2.1.3.1 Aluminum pre-treatment . . . 29

2.1.3.2 PAA anodization . . . 30

2.1.3.3 Electrodeposition in PAA templates: Au-NRs and dendrites 32 2.2 Substrate characterization techniques . . . 36

2.2.1 X-Ray diffraction . . . 36

2.2.2 Scanning electron microscopy . . . 37

2.2.3 Atomic force microscopy . . . 38

2.2.4 Ultraviolet-Visible spectroscopy . . . 38

2.3 Substrate analyte detection measurements . . . 39

3 Results and discussion: plasmonic substrates 40

3.1 Substrate characterization techniques . . . 40

3.1.1 X-Ray diffraction . . . 40

3.1.2 Scanning electron microscopy . . . 43

3.1.3 Atomic force microscopy . . . 53

3.1.4 Ultraviolet-Visible spectroscopy . . . 60

4 Results and discussion: SERS performance 64 4.1 Ellman’s reagent . . . 67

4.1.1 SERS performance of the substrates prepared using PLD and IBD methods . . . 70

4.1.1.1 PLD prepared Ag-NPs based substrates . . . 70

4.1.1.2 IBD prepared Ag-NPs based substrates . . . 73

4.1.2 SERS performance of the substrates prepared using PAA method . 76 4.1.2.1 PAA prepared Au-NRs based substrates . . . 76

4.1.2.2 PAA prepared Au-Ds based substrates . . . 81

4.2 Verotoxin antibody . . . 83

4.2.1 Substrates made by physical methods . . . 83

4.2.1.1 Ag-NPs by IBD . . . 83

5 Conclusions and outlook 85

Chapter 1

Introduction

Sensor technology is an essential topic for healthcare, from diabetes monitoring to cancer and infectious diagnosis. The sensors help health care providers and patients monitor or detect health conditions and ensure that they can make informed decisions about treatment.

First of all, this chapter contains a brief motivation about “Bacteria sensors”, a theoreti-cal introduction to the technique used, Surface-Enhanced Raman Spectroscopy (SERS), based on Raman Scattering (RS) and plasmonic sensing, and it is also dedicated to the critical review of the state-of-the-art on “SERS bacteria sensors”.

1.1

Bacteria sensors

Performing stringent food safety and quality analysis to protect public health is a global issue that requires concerted efforts. More than 200 diseases, from diarrhea to cancers, are related to unsafe food, harmful bacteria, viruses, parasites or chemical substances. Each year, as many as 600 million, or almost 1 in 10 people in the world, fall ill after consuming contaminated food, of these, 420 000 people die, including 125 000 children [9].

Bacteria are one of the most common foodborne pathogens, affecting millions of people annually, they produce sometimes fatal outcomes. The most vulnerable are infants, young children, pregnant women, elderly and people with an underlying illness [10]. The final idea of this preparatory work is related to a quick, sensitive, reliable, and cheaper solution for early bacteria detection.

Harmful bacteria are present in food but also in drinking water, an enormous problem for the third world countries, where unfortunately water isn’t an asset shared by all the citizens, and in the hospitals, where they can produce which is known as a hospital-acquired infection, in a place with the most vulnerable groups and where most of the people are with a low immune system or immunosuppressed, this can be a death sentence. Bacteria reproduce quickly and give off chemicals called toxins that can damage our tissue and make us ill. Antibiotics are the usual treatment, leading to antibiotic resistance. Each time we take them, we increase the chance for them to resist the next infection.

Their overuse and misuse in veterinary and human medicine promoted resistant bacteria. Antimicrobial resistance is one of the main threats to modern medicine. Prevention and early detection are key points.

Infectious disease sensors are related to the rapid detection and diagnosis of several biomolecules. Its simplicity, higher sensitivity, and continuous development make them a powerful technology.

Figure 1.1: Bacterial quorum sensing, from low to high cell density.

To control its population density, bacteria use a communication ability, known as Quo-rum Sensing (QS) by producing and secreting signals called autoinducers, they detect the change in concentration of these autoinducers and respond to it by gene regulation at dif-ferent phenotype expressions, like biofilms formation, virulence factor, bioluminescence... The key to its survival and pathogenicity [1].

If we can detect, understand and control it, several medical and industrial applications can appear. This is how the idea of trying to measure these autoinducers or metabolites, specific of each kind of bacteria, appears.

1.2

Bacteria sensing

The most developed techniques for detecting pathogens include microscopy, nucleic acid, and immunoassay-based techniques, which usually require extensive sample preparation and long readout time, which can delay the pathogen detection and immediate preventive action. The detection methods for toxins produced by the pathogens include ELISA, Western blots, antibody microarrays and antibody-coated polystyrene microbeads, all of them having multiplex capability and sensitivity. These conventional detection methods for bacterial pathogens and toxins, are time-consuming and laborious, requiring certain sophisticated instruments and trained personnel, as well as homogeneous or purified sam-ples [11-14].

Sensor systems offer major advantages over current ones as they are versatile and af-fordable. Sensors with good selectivity, low cost, portable and usable at working sites, sufficiently rapid to be used at-line or on-line and with no sample preparation devices are required. One of the most promising analytical techniques for these proposes is SERS that combines three key parameters [15]:

• High molecular specificity of Raman spectroscopy

• Metal nanostructures supporting localized surface plasmon resonances • High sensitivity

SERS is a powerful vibrational spectroscopy technique that allows highly sensitive struc-tural detection of low concentration analytes through the amplification of electromagnetic fields generated by the excitation of localized surface plasmons [16]. The success of SERS is highly dependent on the interaction between adsorbed molecules and the surface of plasmonic nanostructures.

The Raman effect is weak, approximately 10−8 of the incident exciting radiation. Conven-tional Raman spectroscopy usually generates weak inelastically scattered signals and can only be used for measuring concentrated samples. With the help of several improvements over the years, like the new generation of lasers, the SERS phenomenon was discovered in the 70s, due to the adsorption of molecules in the roughened metallic surface, resulted in a significant enhancement of the Raman signals by many orders of magnitude [17]. En-hanced Raman signals were generated in highly localized optical fields of those metallic structures associated with electromagnetic field enhancement and chemical enhancement of signals. Although SERS phenomena was discovered in the 70s, with the rapid devel-opment of nanotechnology and nanomaterials, the interest in SERS was exponentially increased, it is a useful and versatile technique, with a wide range of applications.

1.2.1

Surface plasmons polaritons

Interaction of light with matter is the basis for a large number of applications, including spectroscopy. Plasmonics field is related to the study of the optical response from the interaction between metals and electromagnetic fields, whose main objective is to control light localization and propagation on subwavelength scales [18].

The electronic structure of metals is constituted by the valence band and the conduction band. The “free” electrons or quasi-freely, because there is electrical resistance that comes from collisions between the conduction electrons and the network ions, are in the conduction band, and the interaction of metals with the Electromagnetic (EM) radiation is largely governed by these free electrons in the metal [19]. The free electrons suffer a displacement because of the electric field of the incident EM radiation, this incident EM radiation induces a polarization in the metal due to all the free electrons. The optical response of the metal can be described by the dielectric function which relates the polarization of the metal (P ) with the electric field (E) [18]:

ε = 1 + |P | (ε0|E|)

(1.1) Drude-Sommerfeld model predicts the dielectric function from the free electron gas. It assumes that conduction electrons can move freely to almost the whole metal:

εDrude(ω) = εinf −

ω_p2

ω2_{+ iΓω}0 (1.2)

In equation (1.2) we have the expression for the dielectric function ε when applying an oscillating electric field E of frequency ω. The electrons respond with an oscillatory motion. ωp is the plasma frequency, Γ a damping term because of electron-electron and

electron-phonon scattering and εinf is the effect of the interband transitions [18]. Drude’s

model predicts the dependence of alternating current electrical conductivity on frequency. This gives rise to a complex permittivity which implies that the current intensity and the applied voltage are not in phase. The real part ε0 of the dielectric function is always negative (Hagen-Rubens region where we have a complex refractive index whose real and imaginary parts have practically equal modulus) due to the fast response of the free electrons to the incident electric field. The electrons screen the external fields to avoid penetration of light into the metal. This means that most noble metals have a negative dielectric constant at optical frequencies (high reflectivity). Experimental measurements of the optical properties of a range of solids can be found in the literature [20].

ε = ε0+ iε00; ε0 > ε00 (1.3)

Materials with a negative real and small positive imaginary dielectric constant, its metal’s plasma (free electron gas) can support collective charge-density oscillations, Surface Plas-mons Polaritons (SPPs). SPPs are EM surface modes at the interface between a dielectric and a metal [18]. The EM field of the SPPs decays exponentially from the interface (Fig-ure 1.2) the dispersion of SPPs can be found by solving Maxwell equations assuming surface waves and the appropriate boundary conditions [21,22]. In summary, if an EM field impinges on the surface of a metal, the electric field will generate a force on the conduction electrons leading to a formation of a plasma. When the electronic cloud is displaced, a recovered force appears (due to the crystalline network) to try to recover the lost balance. The system behaves like a damped harmonic oscillator, where every oscillation will be a SPP.

Figure 1.2: Scheme of the EM field of SPPs propagating along the interface betweeen a metal and a dielectric [23].

Consequently, SPPs can be used to confine fields to the surface, and this has spectroscopic applications [24,25].

1.2.2

Localized surface plasmons

Localized Surface Plasmons (LSP) are non-propagating excitations of the conduction elec-trons of metallic nanostructures coupled to the EM field [26]. If a metal nanoparticle (NP) is illuminated externally with light, the electric field of the light can induce coherent os-cillations in the conduction electrons. A resonance condition can be achieved at certain frequencies of the incident light, and this is known as LSP resonances. The LSP resonances convert the incident energy into subwavelength-scale localized fields that are strongly en-hanced in comparison to the incident light. They are strongly confined to the surface of the metal NP (“hot-spots”). Au and Ag NPs have their resonances at the visible range of the EM spectrum, so they are widely used for several applications [27].

Figure 1.3: Scheme of plasmon oscillation for a sphere [28].

In Figure 1.3 it can be seen the displacement of the conduction electron charge cloud relative to the nuclei when illuminating a metal NP, this displacement is induced by the electric field of the incident field and produces a polarization of the NP. It can be calculated as follows. Starting from a wavelength of visible light which is larger than NP’s diameter, is a good approximation to say that the phase of the harmonic oscillation of the

EM field is almost constant at the NP’s volume. The particle size must be much smaller than the wavelength of light (less than 100nm) so that the quasi-static approximation is reasonable, but it cannot be too small, otherwise important quantum effects arise. The calculation of the field distribution on a NP is made by assuming that the radiation field is uniform within its region at each moment of time, electrostatic field. The harmonic time dependence can be inserted at the end. If the NP is a sphere is also easier to get an analytical treatment [26].

Considering a sphere of radius a placed on a medium with a dielectric constant εm where

the electric field is uniform, ~E = E0~z, the electric permittivity of the metallic sphere is

described by ε(w) (complex number). At the electrostatic regime, we are looking for a solution of the Laplace equation for the potential ∇2_{Φ = 0 to later calculate the electric}

field E = −∇Φ.

Figure 1.4: Scheme of the interaction between a metallic sphere and an electric field [26].

The solution is constituted by the Legendre Polynomials (order l and angle θ between position vector r at point P in the z-axis) equation 1.4.

Φ(r, θ) =

∞

X

l=0

[Alrl+ Blr−(l+1)]Pl(cosθ) (1.4)

The potentials should be finite at the origin, so the solutions inside (equation 1.5) and outside (equation 1.6) the sphere are:

Φin(r, θ) = ∞ X l=0 AlrlPl(cosθ) (1.5) Φout(r, θ) = ∞ X l=0 [Blrl+ Clr−(l+1)]Pl(cosθ) (1.6)

Two boundary conditions are established, the first at r → ∞ that refers to the potential at infinity (distance much larger than the size of NP) where the potential must be that of a uniform field, and the second one r = a where we have to ensure continuity of potential, there is a discontinuity of the normal electric field component because we have an induced

charge distribution on the surface. Applying the equality of the tangential components of the electric field and equality of the normal components of the displacement field, it can be achieved the solution for the potentials inside and outside the sphere. The potential outside the sphere is formed by the superposition of the incident electric field and a dipole located at the particle center. We can introduce the dipole moment ~p and the result is the following (equation 1.7):

Φout = −E0rcosθ +

~ p · ~r 4πε0εmr3 (1.7) ~ p = 4πε0a3 ε − εm ε + 2εm ~ E0 (1.8)

The applied field induces a dipole moment on the sphere with magnitude proportional to |E0| . If ~p = ε0εmα ~E0 then:

α = 4πa3 ε − εm ε + 2εm

(1.9) This is the result of the polarizability (complex) of a small sphere in the quasi-static approximation. It depends on the NP size and the relative permittivity of the surrounding medium. Figure 1.5 shows the module and argument of the complex polarizability as a function of the energy [26].

Figure 1.5: Absolute value (|α|) and phase (Arg(α)) of the polarizability as a function of the energy, fitting the dielectric function of silver [26].

From equation 1.9, a maximum (resonant enhancement) for the polarizability is found at the frequency for which |εr+2εm| is minimum. If the imaginary part of the permittivity of

the metal is negligible or slowly variable in the vicinity of the resonance, the condition is the Fr¨ohlich condition and the associated mode is given by the dipole surface plasmon of the metal NP, so LSP resonances can be recognized in the polarizability α which diverges with the following condition which is satisfied for a specific frequency of the incident light:

LSP resonances depend on the size, shape, interparticle spacing and dielectric properties of the metal. In the case of a non-spherical NP, the polarizability is anisotropic, so changes in the shape of the NPs alters the field distribution near the NPs and consequently the resonance positions. As the distances between NPs decrease, we have stronger field confinement between adjacent NPs (unidimensional chain) but we also have to consider interactions between plasmonic modes (coupling) which become more intense. Decreasing NP radius of curvature produces an increase of surface density charge and we also get more confined fields (“hot-spots”). NPs with asymmetric shapes allow narrower resonances. LSP resonances of the NPs is highly dependent on the local environment, the resonance maximum will shift when the model analyte binds the NPs. All of these dependencies are of great interest, especially in SERS [29].

The nanorods (NRs) have an additional degree of freedom in comparison to spherical NPs, which is an advantage for tunning the optical properties in metallic structures [30]. Because of their shape, NRs support LSP resonances at different frequencies corresponding to the charge oscillations along the different symmetry axis [31]. The metal NRs reveal a strong longitudinal LSP resonance and also a transverse LSP resonance. The first one can be excited with incident light polarized along the NR long axis. The second one can be excited with the incident light being polarized perpendicular to the long axis. By changing its length, the longitudinal LSP resonance can be tuned as well as the transverse LSP resonance by changing the diameter of the NR, both over a wide frequency range [32]. Like the spherical metal NPs, the metal NRs can generate highly enhanced fields.

1.2.3

Surface-enhanced raman spectroscopy

1.2.3.1 Raman scattering

When light interacts with matter, several processes may occur, the photons may be ab-sorbed or scattered, another option is that light not interact with the material and pass straight through it [33]. Light can be scattered in two ways, depending on the relation between the energy of the incident and scattered photons [26]:

• Elastically scattered: incident and scattered photons have the same initial energy (Rayleigh scattering);

• Inelastically scattered: scattered photons have a different energy than the incident photons. (One form of inelastic scattering is the Raman Scattering (RS) by optical vibrations of the system);

RS refers to the spectroscopic process of the inelastic light scattering that arises from the modulation of the electric polarizability of the medium by the atomic vibrations. The time-harmonic optical field (carrier) is mixed with the molecular vibrations (signal) and the mixing process rises the scattered radiation that is frequency-shifted (also known as Raman shift) from the incident radiation w by an amount that corresponds to the vibrational frequencies of the molecules wvib [18]:

The vibrational frequencies originated from oscillations between the constituent atoms of the molecules, depend on the particular molecular structure, the vibrational spectrum constitutes a characteristic fingerprint of a molecule [18]. Representing the intensity of the inelastically scattered light as a function of the Raman shift, we have a Raman spectrum, so the measurement and analysis of the signals arising from the Raman effect is called Raman spectroscopy (Figure 1.6) [26].

Figure 1.6: RS spectrum representing the vibrational frequencies of Rhodamine 6G.

Figure 1.7: Raman and Rayleigh phenomena depicted in the energy diagram.

In Figure 1.7 we can see the RS process, the molecule absorbs a photon with frequency w and emits a photon at a different frequency wR. It is offset with respect to w by

a vibrational frequency of the molecule (equation 1.11). Absorption and emission are mediated by a virtual state (for example a vacuum state that does not match any molecular energy level). If w > wR then Stokes Raman scattering occurs. If w < wR, the process

is designated anti-Stokes Raman scattering. A small number of photons, approximately 1 of every 109, are inelastically scattered and undergo a change in energy [33].

Raman spectroscopy usually refers to Stokes RS (Figure 1.7); this is due to the greater probability of the incident photons losing energy to the molecules instead of gaining, be-cause at room temperature, most molecules are at the vibrational state known as ground, the lowest. The intensity of the RS light is about 10−6 to 10−9 of the incident energy, which is a very weak effect [18].

1.2.3.2 SERS

As referred to above, RS is an extremely weak effect. Plasmonics has been an interesting tool to enhance the EM field due to the interaction between the incoming radiation and the electronic plasma of the nanometric metallic structures. The field enhancement near metallic nanostructures (see sections 1.2.1 and 1.2.2) can be used to improve the efficiency of the RS process, namely when the probe molecule is adsorbed to the nanostructure surface. In 1974 a considerable enhancement of the RS intensity, as high as 106₋₁₀7_{, from}

molecules adsorbed on a roughened metallic surface was reported [17]. Using resonance conditions (see section 1.2.2) this factor increases until 1012, but a huge enhancement was discovered from the “hot-spots”, 1014 _{[34]. These points with very large enhancements}

are good for single-molecule SERS detection. Local field enhancements depend strongly on the exact position of the molecule at the surface.

Figure 1.8: Interaction between a molecule, placed close to a metallic nanostructure, with polarizability α and the exciting field E0 that gives rise to a scattered field ES [18].

In Figure 1.8, a molecule is located at r0 and close to a metallic nanostructure r0 (local

field enhancing device). The dipole moment associted with RS process comes from the interaction between the molecule and the incident field E0 [18]:

p(wR) = α(wR, w)[E0(r0, w) + ES(r0, w)] (1.12)

From equation 1.12, w is the frequency of the exciting radiation, wR a particular

vi-brationally shifted frequency, α is the polarizability of the molecule modulated at the frequency wvib of the molecule rising the frequency mixing. The molecule interacts with

the local field, composed by the sum of E0 (incident local field in the absence of the metal

nanostructure) and ES (scattered field, enhanced field from the interaction with the metal

nanostructure). ES depends linearly on E0, and can be defined as ES = f1(w)E0 where

f1 is the field enhancement factor [18].

E(r∞, wR) = w2 R 0c2 G(r∞, r0)p(wR) = w2 R 0c2 [G0(r∞, r0) + GS(r∞, r0)]p(wR) (1.13)

The electric field radiated at a distant point r∞ by the induced dipole (equation 1.13)

is represented by the Green function (a mathematical function used in the resolution of non-homogeneous differential equations with specified boundary conditions). The Green function is divided into a free-space part G0 and a scattered part GS. The intensity is

defined as I ∝ |E|2_{, so with the second enhancement factor (f}

2) then GS = f2(wR)G0 and the intensity is [35]: I(r∞, wR) = w4 R 2 0c4 |[1 + f2(wR)]G0(r∞, r0)α(wR, w)[1 + f1(w)]|2I0(r0, w) (1.14)

The Raman-scattered intensity scales linearly with I0 and depends on the factor [35]:

|[1 + f2(wR][1 + f1(w)]|2 (1.15)

Without metal nanostructure, f1 = f2 = 0. With a metallic nanostructure, f1, f2  1 so

the RS enhancement is [35]:

fRaman = |f2wR|2|f1(w)|2 (1.16)

We are ignoring the vectorial nature and tensorial properties of the polarizability, RS scales with the fourth power of the electric field, equation 1.16 [35]. How much the signal can be increased is the enhancement factor (EF). Different substrates (metal, structure and morphology, among others) mean different EFs, but also for the same substrates depending on how EF is calculated and measured, it changes, so is very difficult to com-pare. SERS EFs on the surface are highly non-uniform and for a given substrate is not possible to get one SERS EF, the good one depends on the application/experiment [18]. A unification of criteria should be done to clarify the EF term. EF is affected by two multiplicative contributions [35,36,37]:

• Electromagnetic enhancement factor: is the main contribution. It is due to the coupling of the incident and Raman EM fields with a SERS substrate. It is composed of the EF of the incident field and the EF of the re-emitted (Raman) field. To profit the field enhancements, the molecule should be at least at 10nm from the surface of the metallic nanostructure or directly adsorbed on the surface.

• Chemical enhancement factor: its contribution is much smaller than the previous one. Modifications of the electronic polarizability of the probe can induce resonant-RS with an enhanced signal at wavelengths where non-adsorbed molecules wouldn’t be resonant. The mechanism is based on charge-transfer and the molecule has to be chemically adsorbed on the surface.

The factors influencing SERS enhancements are [35]:

• Characteristics of laser excitation: like the wavelength, polarization or angle of incidence.

• Detection setup: scattering configuration, polarized or unpolarized detection. • SERS substrate: material, geometry, orientation concerning the incident beam

direction and polarization.

• Plasmonic structure: adsorption and efficiency in local field conversion.

• Intrinsic properties of the analyte: Raman polarizability tensors of the modes. • Analyte adsorption properties: adsorption efficiency, analyte concentration,

distance from the surface, adsorption orientation.

EF is defined for the non-SERS properties of the same molecule in the same environment as used for the SERS experiment. From an analytical point of view, we have a simple and intuitive approach [35]:

AEF = ISERS/CSERS IRS/CRS

(1.17) From equation 1.17, CRS is a given concentration of the analyte, with a Raman signal

IRS. Under identical experimental conditions and for the same preparation conditions,

the same analyte on a SERS substrate with a different concentration CSERS, gives a

SERS signal ISERS. The IRS scales linearly with the incident power density and molecule

1.3

SERS bacteria sensors

The protection of public health is a problem that is always contemplated. From the literature review, in the field of SERS bacteria detection, several problems arise from its limitations.

1.3.1

Literature review

The first time it was observed the enhancement of Raman signal in many orders of mag-nitude, was reported by M. Fleischmann et al. [17]. They reported the first high-quality Raman spectra of monolayer-adsorbed pyridine on an electrochemically roughened Ag electrode surface [38]. Jeanmaire [38] and Albrecht and Creighton [39] confirmed Fleish-man’s findings and hypothesized that this phenomenon was originated by strong electro-chemical electric fields at the metal surface (Jeanmaire) or by the formation of a molecule-metal complex (Albrecht). Moskovits [40] proposed that the large signal was originated by the optical excitation of collective oscillations of the electrons in the metallic nanosized features at the surface. Studies in the following years confirmed that the origin of SERS enhancement is two-fold and is related to the electromagnetic [36] and to the chemical effect [37].

The key characteristic of SERS substrates is the nanogaps between metal nanostructures which produce high EM field enhancement under resonant excitation (“hot-spots”). AEFs until 1014− 1015 _{were reported by S. Nie and S.R. Emory [34] using Ag-NPs prepared}

at room temperature and tested with Rhodamine 6G as analyte. Nowadays, various SERS substrates have been prepared for several studies using either the bottom-up or the top-down process. Anyhow, several problems arise during SERS measurements on different substrates. Lianming Tong et al. [41] reported that having a low SERS activity substrate, the laser power has to be high and the sample can be damaged. They also reported that photo-induced chemical reactions can occur due to the photochemical effect by the incident laser or because of the plasmonic effects. Finally, another problem is that molecules are usually irreversibly adsorbed on the metal surface, making the SERS substrates not reusable increasing costs.

Koppole Kamakshi et al. [2] reported a SERS substrate that can be able to detect bovine serum albumin (a serum albumin protein derived from cows) up to the concentration of 10−8M , which is improved compared to others previous results reported of lower limits (10−6M ). They studied the effect of substrate temperature on electrical conductance, surface plasmon resonance and SERS activity of Ag-NPs. The NPs were grown on glass substrates by PLD in a controlled Ar atmosphere.

C.D. Andrea et al. [3] described the production of a PLD substrate with Ag-NPs for SERS and all the parameters affecting the SERS for Rhodamine 6G at different concentrations. They detected until 5·10−8M . The substrates were prepared by PLD in an Ar atmosphere (Ag nanostructured thin films). NPs size is controlled by the Ar pressure and the surface morphology of the films by the laser pulse number. The other process parameters were fixed. The deposition was at room temperature and with no thermal treatment before SERS measurements. They got a reproducible and simple substrate (controlling just

the inert gas pressure and laser pulse number). The conclusions were that it was a cleaner method than chemical routes and faster and cheaper than lithography. SERS field continues growing, new materials for SERS substrates are reported regularly, for example, A Musumeci et al. [4] studied hybrid composites. X.Ling el al. [5] the possibilities of graphene as a SERS substrate.

In the case of SERS bacteria sensors, the advances on intense spectra which are selective, are enormous but is not all. It is necessary to simplify the spectra allowing for a more rigorous assignment and more efficient application for analysis, as reported L. Zeiri and S. Efrima [42]. W.R. Premasiri et al. [43] studied the Raman enhancements for Au-NPs (∼ 80nm) covered with SiO2 substrates and excited at 785 nm. Enhancements of 104 per bacterium were found on the SERS active substrates with positive and Gram-negative bacteria. The strategy shown seems to ease the data analysis of previous studies. Balaprasad Ankamwar et al. [44] described the use of biosynthesized Ag-NPs obtained from the leaf extract as a SERS active substrate to detect bacteria. EFs of 107 _{for E. coli}

bacteria were found. They presented a SERS substrate uniform and reproducible that provides very stable SERS data.

Figure 1.9: SERS spectra of Pyocyanin at different concentrations (0.1nM to 100µM ) [1].

All studies coincide about SERS detection method as a very useful analysis for slow-growing bacteria, which typically may take weeks during laboratory tests. From the limitation related to the detection in complex environments, where very difficult and contaminated signals are the usual result, for example, bacteria analytes in a medium like water or food, where several biomolecules are present in the samples apart from the analyte we want to measure, we found that G.Bodel´on et al. [1] reported an innovative method for avoiding these biomolecules that are irrelevant for the detection. Using nanostructured porous substrates for in situ plasmonic detections, avoiding the medium contribution. The analyte recorded spectra ranged from 0.1nM to 100µM varying from one substrate to the other (Figure 1.9). Three plasmonic substrates were prepared, in one of the plasmonic

substrates, they used micropatterned Au@SiO2, a super crystal array comprising Au nanorods organized in micrometer-sized pedestal-like structures coated with mesoporous silica. With a concentration lower than 0.1 nM they got a Limit of Detection (LOD) because of no homogeneity across all pillars and detection of molecular binding events. This led to ultrasensitive detection of Pyocyanin down to a LOD of 10−14M .

Despite the great results with the LOD for this analyte, it still can be observed that the result is highly dependent on the plasmonic substrate, difficulting the reproducibility and homogeneity to obtain consistent measurements independently of the measurement point or the substrate.

Xiaohua Huang et al. [27] made an exhaustive study of the plasmonic properties of gold high aspect-ratio NPs.

Figure 1.10: Optical properties of Au-NRs with different aspect-ratios (length/width) [27].

As it was seen in the theory, is interesting to have the peak of absorption closer to the laser wavelength to profit the maximum of the signal, maximum amplification. So we can choose the most interesting aspect-ratios from Figure 1.10. The gold particles are very interesting, they present facile surface modification, strongly enhanced and tunable optical properties as well as excellent biocompatibility. But also because of the strongly enhanced radiative properties such as absorption, scattering and plasmonic field for surface-enhanced Raman of adjacent molecules. The surface plasmonic resonance band is much stronger for noble metals, especially Au and Ag than other metals. The band intensity and wavelength depend on the factors affecting the electron. Gold, silver and copper NPs show strong surface plasmonic resonance bands in the visible region, while other metals show broad and weak bands in the UV region.

D. V. Yakimchuk et al. [6] reported another interesting plasmonic substrate made with dendrites (Ds) small pores in a porous matrix bottom. They describe this substrate as

very promising for biosensor applications, but difficult to control the resulting structures. They fabricated Ag dendritic structures from an electroless wet-chemical approach in a porous matrix of Si/SiO2 by self-assembly in a limited volume, the SERS EF achieved was around 108 _{and the analyte detection limit of 10}−15_{M which is at the level of}

single-molecule sensitivity. Ziqiang Cheng et al. [7] reported the limit at 10−14M . They prepared Ag dendrite fractal nanostructures by an electrochemical deposition method that exhibit multiple plasmon resonances, they used 1,4-benzenedithiol (1,4-BDT) as a probe molecule. This kind of plasmonic substrate is quite new and seems to have an attractive future. The literature review showed nanostructured porous substrates as an interesting tool to avoid biomolecules that are irrelevant for the detection. Next, a brief theoretical introduction to porous anodic alumina (PAA) is shown.

1.3.1.1 Porous anodic alumina: Au nanorods and dendrites

The development of the Aluminum anodizing process made possible new techniques and methods, because it allows very precise control of nanostructures such as NRs or Ds. Oxidation is a natural process for several metals when they are in contact with oxygen. They are chemically unstable and thermodynamically tend to form an oxide on the surface.

2Al(s) + 3/2O2(g) → Al2O3(s) (1.18)

A spontaneous electrochemical reaction occurs at the formation of aluminum oxide with air (equation 1.18). The reaction can be induced quicker by an electrical field-assisted movement of metal or oxygen ions. As the film thickness increases, the rate of oxidation decreases, due to the reduction of the electrostatic field at the metal-oxide interface [8]. In other words, this bottom-up approach consists of a simple physicochemical process, based on PAA film growth. The used procedure is an electrochemical oxidation process, anodization, which is a surface treatment of aluminum (or any other metal or semicon-ductor) that forms a layer of aluminum oxide in a controlled way. A direct current is passed through the surface of the aluminum, behaving like an anode in an acid medium. The result obtained with an acid electrolyte is a porous structure instead of a continuous film such as the case of neutral electrolytes.

2Al(s) + 3H2O(l) → Al2O3(s) + 6H+(aq) + 6e− (1.19)

Al2O3(s) + 6H+(aq) → 2Al3+(aq) + 3H2O (1.20)

6H+(aq) + 6e−→ 2H2(g) (1.21)

At the anodization process, hydrogen is formed at the cathode (equation 1.21) and the oxide grows (equation 1.19) and dissolves (equation 1.20) at the anode electrode. PAA has a high pore density in ordered close-packed hexagonal arrays. Varying the growth conditions like the electrolyte and anodization conditions, oxide morphology can be mod-ified. With the help of a two-step anodization process, it comes out a high degree of order [8].

It has been reported that the porosity for a hexagonal structure is given by: P = √2π 3( r Dint )2 (1.22)

In equation 1.22, r is the pore radius and Dintis the distance between the pores (measured

from center to center of two pores neighbors). _Dr

int is constant for self-ordered porous

alumina. The interpore distance, Dint, is linearly proportional to the applied potential U

with a proportionality constant k ∼ 2.5nm/V (equation 1.23). The optimum porosity is around 10%, [45].

Dint = kU (1.23)

Figure 1.11: PAA scheme, adapted from [46].

With a constant potential during the anodization process, the porous evolution passes through 4 stages that can be seen in Figure 1.12.

During phase I, the non-conducting oxide continuous barrier is formed so current density drops quickly. The barrier attains the minimum when the maximum thickness value is achieved and grows continuously, phase II. After phase II the current density increases rapidly because the pores start to growth (nucleation). In the end, it suffers a slight decline during the competition for the self-organizing process. Phase IV corresponds to continuous PAA growth.

Figure 1.12: Current density vs time and diagram of the four phases of PAA formation during anodization [47].

The two-anodization process discovered by Masuda and Fukuda (1995) [48] allows a higher degree of order and high aspect-ratio pores (length/pore diameter). This system has 3 stages, first anodization with the phases described above, the Alumina removal, to keep the periodic concave patterns already formed which act as the nucleation centers for the last stage. And this last stage, the second anodization.

Figure 1.13: Two-anodization process scheme [47].

A comparison between the first and second anodization will be shown in chapter 2 with the experimental data.

Templates with branched channels have been proved to be efficient for plasmonic effects. One of the approaches to get these nanostructures is the non-steady-state, an easy, re-producible and low-cost technique. This technique consists of reducing exponentially the second anodization potential, originating a reproducible tree-like branched structure known as Ds. They were first observed by Furneaux in 1989 [49]. There are few works for Ds but some interesting properties for gold nanotrees were observed [50].

The last step for filling the pores with the metallic NRs is made with an electrodeposition technique. The electrodeposition consists of the formation of a metallic layer on a sub-strate through electrochemical reduction of metal ions from an electrolyte. The membrane which acts as the cathode is immersed in the electrolyte with the Pt electrode (anode). The electrolyte contains ions of the metal we want to deposit, so applying a potential

between the electrodes, a current flow is created and the following generic reaction for metal formation occurs [51]:

(MxLy)z+ nxe → xM0+ yL (1.24)

In equation 1.24, L is (for example) a molecule or ion, bounded with the metal ion of interest, M forms complex species (MxLy)z. The complex species take part in the charge

transfer process, n is the net amount of electrons transferred during the complete process per deposited metal atom (positive). z is the electric charge of the electroactive species (intermediate compound) in electron units (can be positive, negative or zero). To get the formation of one mole of the metal requires NAne = nF Coulombs (C) of electricity.

Where NA = 6.022 · 1023mol−1 is the Avogadro number and F = NAe = 96485 C · mol−1

is the Faraday constant. This relationship is Faraday’s Law [51]:

m = QA/nF (1.25)

In equation 1.25, m is the metal mass deposited (g), Q the net charge passed through the circuit (C), and A the atomic weight of the metal. All at constant current Q = Iτ , if not Q = R Idτ . I is the current and τ the duration of electrolysis. This equation allows us to calculate the amount of metal deposited during electrolysis, to calculate the necessary time to achieve a determined thickness [51].

Two of the various types of electrodeposition are Direct Current (DC) and Pulsed Elec-trodeposition (PED). For the DC elecElec-trodeposition, a thin film of metal has to be de-posited at one of the surfaces to work as an electric contact for the electrodeposition process, this is the normal procedure. A thin film of metal is then deposited on one of the membrane surfaces to have an electrical contact to begin the electrodeposition process. By changing the deposition times the length of the NRs can be controlled. This is a complex process that can’t be exported to the industry because of the laborious template processing [52].

In PED, the PAA layer is kept on the Al substrate and the barrier layer is thinned, reducing the anodization potential and enabling the electrical conductivity. The elec-trodeposition is made using the Al substrate as the cathode [53]. PED works applying a modulated signal constituted by three consecutive pulses, first applying a positive current to deposit the metallic NRs. Then starts a short voltage pulse with negative polarity, and finally a delay time with current 0. The delay time helps to improve the homogeneity of the deposition [54].

1.3.2

Substrate election

Top-down and bottom-up, have been two manufacturing approaches to produce plas-monic nanostructured substrates. Between both, several differences can be found during fabrication and also on the resulting. At the end of this work, it will be presented the conclusions obtained, not only about the results of each substrate but, a comparative of all the processes involved until reaching the results. The best and worse aspects of each approach.

Figure 1.14: Scheme of plasmonic structures and nanoporous platform: (a) Porous anodic alumina (PAA) + Au nanorods/Au dendrites (Au-NRs/Au-Ds) obtained by electrodepo-sition inside of the PAA; (b) PAA + Ag nanoparticles (Ag-NPs) obtained by Pulsed laser deposition (PLD) and Ion beam deposition (IBD), just joining both parts.

In Figure 1.14 it can be seen the two approaches planned in this work for a SERS bacteria sensor. The first option (Figure 1.14 (a)) consists of a template of PAA where pores were filled by electrodepositing with Au-NRs. The other approach (Figure 1.14 (b)) relies on the preparation of plasmonic substrates with Ag-NPs by Pulsed Laser Deposition (PLD) and Ion Beam Deposition (IBD). This last option also can be joined with the PAA just by putting them in contact, by statistics lots of Ag-NPs are going to be at the bottom of the pores. Au and Ag were chosen because of their strong plasmonic response and resonances in the visible range that matches with our Raman lasers to get the higher enhancement of the signal, also because of their biocompatibility. The PAA template will act as a filter to avoid contamination with other biomolecules in future more complex samples.

1.3.3

Analyte election

The chemical DTNB or Ellman’s reagent (5,5-dithio-bis-(2-nitrobenzoic acid)) is highly studied and used for the determination of thiol groups in the analysis of clinical samples. DTNB is useful to measure small alterations and determine the concentration of these thiol groups in a sample.

The objective with the DTNB is the characterization of all substrates to check its per-formance. It was chosen because of its well-studied capabilities for low concentration detections, Jing Yang et al. [55] reported enhancements of 14 times from an ITO (indium tin oxide) grating substrate concerning the method with self-assembled Ag-NPs (Figure 1.16).

Figure 1.15: Chemical structure of Ellman’s reagent (DNTB).

Figure 1.16: SERS spectra of DTNB with concentrations ranging from 100 nM to 10 pM on: (a) ITO gratings; (b) Ag-NPs [55].

On the other hand, as analyte related to the bacteria sensing, which is the final objective, the antibody of the Anti-Shiga Toxin (protein toxins secreted by certain types of bacteria) from the Shiga toxins family, also known as Verotoxin, was chosen. Shiga toxin is produced by Shigella dysenteriae. It is secreted by specific strains of Escherichia coli such as E. coli O157:H7 (serotype, based on major surface antigens). This bacteria cause bloody diarrhea and hemorrhagic colitis in humans, which may lead to fatal systemic complications [56]. The experimental conditions that we have, do not allow to test toxins, very specific safety conditions are needed because of its dangerousness. But studies related to the antibody of this toxin are allowed (the hazard level is almost null). This toxin was chosen because it is a common one and not very complex. For future improvements, it can be tested easily, for example, testing this bacteria that growth in water, there, and after in a more complex medium. The other reason is that it is a common production metabolite bacteria (always produce) because some kind of bacteria produce the toxins just under stress conditions.

The Shiga toxins consist of two polypeptides, an A chain and a B chain, non-covalently associated [57].

Figure 1.17: Chemical structure of Shiga-toxin (Stx) receptor (Gb3) [58].

The B subunits of the toxin bind to a component of the cell membrane known as gly-colipid globotriaosylceramide (Gb3). This causes induction of narrow tubular membrane invaginations allowing the bacterial uptake into the cell [57]. Shiga toxins are a family of related toxins with two big groups, Stx1 and Stx2 (they only differ from each other in one amino acid). Our measurements were performed with Stx1.

1.4

Objectives

The main objective of this work is to develop an efficient, easy, reproducible, homoge-neous and low-cost substrate with a strong enhancement in SERS analysis for bacteria detection. Results obtained with these substrates should be always consistent. On the other hand, the enhancement achieved must be high enough to allow the SERS analysis of bacteria analytes with very low concentrations and avoiding signal contamination by other molecules.

In conclusion, the objectives of this work are the following:

• Produce 4 different SERS substrates and compare them, to check if, in future works, they will be useful and can be further developed for the bacteria sensing field, to replace the current methods allowing an increase in the detection limits of the analytes and simplifying the techniques.

• Test the produced substrates from high to low concentrations with the chemical reagent DTNB for characterization of the samples, and a final test with an antibody of a bacterial toxin.

Chapter 2

Experimental details

Chapter 2 presents a detailed description of the different methods and materials used for plasmonic substrate fabrication and characterization.

2.1

Substrate fabrication methods and materials

Throughout this Master thesis, two routes of substrate fabrication have been followed. A top-down and bottom-up approach, the first one implemented in collaboration with Universidade do Minho. The second one was developed at IFIMUP.

Plasmonic

substrates

As a top-down method, starting from a metallic target (large structure) we get micro or nanostructures. In this case, we are talking about NPs obtained by PLD and IBD. On the other hand, the bottom-up route is based on PAA fabrication and subsequent electrodeposition of the NRs or Ds.

2.1.1

Pulsed laser deposition

PLD works as a Physical Vapor Deposition (PVD) process, which is carried out in a vacuum atmosphere. The procedure involves a pulsed laser that is focused on a metallic target (of the material we want to deposit). Each laser pulse vaporizes or ablates a small amount of the metallic target, forming a plasma plume which provides the material flux for film growth at the sample. This material stripped from the target travels on a highly forward-directed plume to the sample. When the ablation plume impinges the substrate, it deposits material over the surface. With this method, we get high-quality samples with excellent precision [59].

Figure 2.1: PLD scheme.

Sample Target Energy (mJ) Temperaturesubstrate (o_C) Frequency (Hz) Pressure (mbar) Distancetarget−sample (cm) Deposition time (s) Ag NPs PLD 1 Ag >244 400 10 10−3 _{7 30} Ag NPs PLD 2 Ag 244 400 10 10−3 _{7 60} Ag NPs PLD 3 Ag 244 400 10 10−3 _{7 90} Ag NPs PLD 4 Ag 244 400 10 10−3 _{7 120} Ag NPs PLD 5 Ag 244 400 10 10−3 _{7 180} Ag NPs PLD 6 Ag 244 400 10 10−3 _{7 60} Ag NPs PLD 7 Ag 244 400 10 10−3 _{7 30}

Table 2.1: Experimental parameters for the Ag-NPs substrates, fabrication by PLD.

Table 2.1 summarizes all the important parameters used to fabricate the samples made by PLD. The substrate chosen was normal glass, due to its cheaper value, and almost unseen Raman signal, it is also true that glass has more roughness than Si, but we opted for a simple and cheaper substrate. For the Ag-NPs prepared by PLD it was used a commercially available Ag target (99.99% purity) in presence of vacuum of 1 × 10−3mbar. An excimer laser of wavelength 248nm, with energy of 244mJ (except for the first sample) and pulse rate of 10Hz, was focused onto the target. Substrates were placed at a distance of 7cm directly in front of the target. Silver thin films were grown at the same temperature of 400o.

Seven samples were prepared by changing deposition times from 30s to 180s, getting samples with different morphologies and resonance peaks (chapter 3). SERS response is going to be different based on each morphology, surface density or distance between NPs [2,60].

2.1.2

Ion beam deposition

IBD is also a PVD process that allows getting high quality and very precise samples. The system consists of a target, the substrate and the ion source, the atmosphere used in this case is Ar. The ion source focuses on the target to sputter it. The sputtered material is deposited onto a sample. For this to happen, it is necessary to apply a high voltage, which creates an electrostatic field inside the ion source (with the anode and cathode concentrically aligned) so the electrons are at the center. The Ar gas is injected and the high electric field ionizes the gas (the plasma appears inside the source). Electrons are accelerated from the anode to the cathode, producing a collimated ion beam. This ion beam, by momentum transfer with the target, sputters the material towards the substrate [61].

Figure 2.2: IBD scheme.

Table 2.2 contains the important parameters used to fabricate the substrates made by IBD. By using a commercially available Ag target (99.99% purity), the Ag thin films were grown, by IBD technique on top of the glass substrates. The system is equipped with a multi-target carousel that allows deposition of several layers successively, without breaking the vacuum. The vacuum chamber was first evacuated down to a low pressure of 1 × 10−6 mbar prior to the deposition. During the deposition, the substrate was kept at a temperature of 200o _{and at a distance of 87.3mm from the target. The gas pressure}

inside the chamber was maintained constant at 2.5 × 10−4mbar. A gas flow of 8.0ml/min of Ar was introduced into the ion beam gun and the atoms were ionized in the ion source with a radio frequency power of 100W . The ion beam was further accelerated at 500 V and the ion beam current was regulated to remain at 16 mA.

Three samples were prepared by changing deposition times from 15s to 45s. Significant differences were seen between PLD and IBD techniques and will be shown over the next chapters.