Smart fingertip biosensor for food quality control

Maria Manuela Almeida Pereira de Carvalho

Thesis to obtain the Master of Science Degree in Bioengineering and Nanosystems

Supervisors: Prof. Susana Isabel Pinheiro Cardoso de Freitas Dra. Verónica C. Martins Romão

Examination committee Chairperson: Prof. Gabriel António Amaro Monteiro Supervisor: Prof. Susana Isabel Pinheiro Cardoso de Freitas Member of the committee: Prof. Diana Cristina Pinto Leitão

October 2019

i

ii

Preface

The work presented in this thesis was performed at Instituto de Engenharia de Sistemas e Computadores – Microsistemas e Nanotecnologias (INESC-MN) (Lisbon, Portugal), during the period February-October 2019, under the supervision of Prof. Susana Freitas and Dr. Verónica Romão.

iii

Declaration

I declare that this document is an original work of my own authorship and that it fulfills all the requirements of the Code of Conduct and Good Practices of the Universidade de Lisboa.

iv

Acknowledgements

First of all, I would like to thank my supervisors, Prof. Susana Freitas for providing me the opportunity to work in this project and for all the support, both scientific and motivational. I would also like to thank the vote of confidence you gave me, having the liberty to use all the equipment available at INESC-MN, required for the development of this work. Dra Verónica Romão, also my supervisor, for all the support and guidance throughout this project and for all the precious advices. To Pedro Ribeiro, who was an improvised mentor during the first months of the project, always available to help, giving great advices and ideas to overcome the obstacles encountered. To Ana Rita Soares for all the advices, incredible support and all the lunch break laughter. To all my amazing colleagues at INESC – MN, for the great work environment and the willingness to provide help. To the tireless process engineers Virgínia Soares, Fernando Silva e José Bernardo, for all the patience and help along with the formation in operating the machines. To Marília Silva and Fernando Franco for the guidance in sensor characterization and measurements. Thank you! Most importantly I want to thank my parents for providing me this opportunity, specially to my mother, for showing me that there is always strength to carry on. For all the advice, support and for always believing in me, thank you so much! Lastly but not least I want to thank my boyfriend, for the unconditional support and motivation.

v

vi

Resumo

Ao longo dos anos temos assistido a uma enorme evolução na área do controlo da qualidade na indústria alimentar. Em particular, há um esforço crescente em introduzir tecnologias automatizadas para manipulação e inspeção dos frutos. Nesta tese é desenvolvido um sensor de textura que permite uma avaliação rápida da qualidade do fruto para ser, futuramente, manuseado por uma mão robótica. Este sensor é baseado em tecnologias de pele eletrónica, de modo a combinar a capacidade táctil (sensores de pressão) com a perceção de textura mais sensível (através de estruturas ciliares artificiais). O sensor desenvolvido é baseado em estruturas ciliares, frequentemente encontradas na natureza, magnetizadas (cílios) que são depositadas sobre um sensor magnetoresistivo. Ao passar sobre a superfície dos frutos, os cílios reagem, deformando-se, o que varia o campo magnético por estes emitido. Esta mudança leva a uma variação da resistência do sensor, o que permite a medição elétrica da textura da pele e, consequentemente, do estado de maturação do fruto.

Palavras chave: Controlo de qualidade alimentar, Sensor de textura, Sensor Magnetoresistivo, Estruturas ciliares

vii

viii

Abstract

Over the years there has been a tremendous evolution in the area of quality control in the food industry. Particularly, there is a growing effort to introduce automated technologies for fruit handling and inspection. In this thesis a texture sensor is developed, that allows a quick quality evaluation of the fruit, to be handled, in the future, by a robotic hand. This sensor is based on e-skin technologies, combining tactile ability (pressure sensors) with a more sensitive texture perception (by artificial ciliary structures). The developed sensor is based on ciliary structures, often found in nature, magnetized, deposited on top of a magnetoresistive sensor. When passing over the fruits’ surface, the cilia react, deforming, which varies the magnetic field emitted by them. This change causes a variation in sensor resistance, allowing an electrical measurement of the fruits skin texture and, consequently, ripeness stage.

Key words: Food quality control, Giant magnetoresistive sensor, Texture sensor, Ciliary structures

ix

x

Contents

Preface...... iii Declaration...... iv Acknowledgements ...... v Resumo...... vii Abstract...... ix List of tables...... xiii List of figures...... xv List of acronyms...... xx

1 Introduction 22 1.1 Motivation and objectives ...... 22 1.2 State of the art...... 23 1.2.1 Existing texture sensors...... 24 1.2.2 Existing gas sensors...... 24

2 The system concept 2.1 Magnetic sensor...... 26 2.1.1 Magnetoresistance...... 27 2.1.2 Giant magnetoresistance...... 27 2.1.3 Spin valve...... 29 2.1.4 Linearization strategy...... 30 2.1.5 Sensor design...... 32 2.2 Artificial cilia structures...... 35 2.2.1 Nanocomposite...... 36 2.3 Towards a gas sensor integration in cilia...... 37

3 Device fabrication 38 3.1 Microfabrication techniques and equipments...... 40 3.1.1 Deposition of spin valve stack...... 40 3.1.2 Spin valve shape definition...... 40 3.1.3 Current lines and contact pads definition...... 44 3.1.4 Passivation...... 47 3.1.5 Annealing ...... 49 3.1.6 Dicing...... 49 3.1.7 Hard mask design and fabrication...... 50 3.1.8 SU-8 mold fabrication...... 52 3.1.9 Nanocomposite casting and peeling...... 54 3.1.10 Annealing...... 56

xi

3.1.11 Device assembly...... 56 3.2 Characterization methods and equipments...... 57 3.2.1 Magnetotransport curve...... 57 3.2.2 Profilometer...... 58

4 Results and discussion 59 4.1 Artificial cilia arrays ...... 59 4.1.1 Optimization...... 59 4.1.2 Cilia detachment ...... 61 4.2 Nanocomposite characterization...... 62 4.3 Magnetic sensor characterization...... 62 4.3.1 Optimization...... 62 4.3.2 Magnetic sensor ...... 63 4.4 Surface texture detection...... 66

5 Conclusion 69

Bibliography 70

A Run sheet– Full Wheatstone Bridge Spin valve sensors 73

B Run sheet– Artificial cilia fabrication and insertion over the GMR sensor 78

xii

List of Tables

2.1 Wheatstone bridge configurations [29] ...... 33

3.1 Read Nordiko 3000 etching process parameters...... 43

3.2 Read Nordiko 7000 metallization process parameters...... 46

3.3 Read UHV 2 and Alcatel passivation layer deposition process parameters...... 48

3.4 Read Nordiko 7000 process parameters for 3000 Å aluminum layer deposition...... 50

3.5 SU-8 mold fabrication conditions for thicknesses of 50 µm, 100 µm and 150 µm...... 53

4.1 Fabricated GMR sensors parameters...... 64

xiii

xiv

List of Figures

1.1 Magnetic tactile sensors. a) Photograph of the small force sensor. The GMR sensor is comprised by the whole area under the cilia. Inset: scanning electron microscope photograph of a cilium of the same sensor [5] © [2017] IEEE . b) Illustration of the Braille characters reading application [6] © [2016] IEEE ...... 23 2.1 Expected magnetotransport curve in response to cilia deformation for each direction. The spin valve’s free layer aligns antiparallel to the cilia magnetization orientation, originating a high or low resistance state which can be verified by supplying the device with a current (voltage) and measuring the output voltage (current)...... 26 2.2 Representation of the GMR effect. (a) Change in multilayers’ electrical resistance as a function of applied magnetic field. (b) Typical trilayer structure with a FM configuration (edges) and an antiferromagnetic (AFM) configuration (in the middle), magnetization direction indicated by the arrows. The magnetizations are aligned antiparallel at zero field. As the applied magnetic field is increased, the magnetization in the FM layers progressively rotates towards the field, until it

reaches saturation (HS) where the magnetization ends up in a configuration of parallel alignment. (c) The magnetization curve for the multilayer. Adapted from [22] ...... 28 2.3 Schematic representation of the GMR effect in a trilayer film of two identical FM layers sandwiching a NM layer. a) When the FM layers are parallel magnetized, the spin up electrons are weakly scattered whereas spin down electrons are strongly scattered, in both FM layers. This is simulated by two small resistors in the spin up channel and two large resistors in the spin down channel, in the equivalent resistor network. In this configuration, the spin up channel is preferred. b) When the FM layers are antiparallel magnetized, the spin up electrons are strongly scattered in the second FM layer, while the spin down electrons are strongly scattered in the first FM layer. This is modeled by a small and a large resistor for each channel. Therefore, there is no shorting and the total resistance in the AFM configuration is much higher than in the FM configuration. Adapted from [25] ...... 29 2.4 Schematic arrangement of a) bottom, b) top and c) symmetrical spin valve structures. In the bottom spin valve, the bottom FM layer is pinned by the adjacent AFM layer, while in the top FM layer is free to rotate; the opposite happens for the top spin valve. In the symmetrical spin valve, the central FM layer is free while the other two FM layers are pinned...... 30 2.5 Scheme of the developed spin valve configuration. a) Ideal magnetotransport response of the developed spin valve. b) Exploded top view of the spin valve spacer, free and pinned layers. c) spin valves’ sensitive direction defined upon deposition. Adapted from [23] ...... 31 2.6 Scheme of the top pinned spin-valve used in this thesis...... 31 2.7 Representation of a) the sensor’ circuit and b) the equivalent circuit...... 32 2.8 Schematic of a full bridge GMR sensor. R1 and R3 present ΔR/ΔH <0 and R2 and R4 ΔR/ΔH >0. Adapted from [30] ...... 34

xv

2.9 a) Illustration of the nanocomposite cilia tactile sensor. It is made of permanent magnetic nanocomposite cilia integrated on a magnetic sensor that mimic the neuron in natural cilia [32]. b) Illustration of the sensors’ working principle. The nanocomposite cilia have a stray field that affects the GMR sensor and biases it to an initial resistance value. A top view of the tactile sensor is shown (not to scale). c) When a force is applied and the cilia deflect, the stray field measured with the GMR sensor changes, hence changing the resistance [6]...... 35 2.10 a) Photograph of a flexible tactile sensor with an inset showing a SEM image of the cilia, and a photograph showing the flexible sensor attached to the skin. b) Dynamic response for texture measurement [32]...... 36 2.11 Stress vs strain curve for a) a ferrous alloy (structural steel). The various states the steel experiments, for different applied strains. Adapted from [34]. b) for an elastic material (paper for example) and a rubber-like hyperelastic material. In both plots, the blue dashed line represents the stress vs strain curve slope (Young Modulus) ...... 37 3.1 Schematic representation of the GMR sensor fabrication process...... 39 3.2 SVG coating and developing track...... 41 3.3 CAD mask used to define the spin valves shape...... 42 3.4 Schematic representation of the final photoresist pattern for all the combinations of mask and photoresist types...... 42 3.5 Schematic representation of the Nordiko 3000 internal structure for ion milling etch and ion beam deposition [36] ...... 43 3.6 Optical microscope photograph after resist strip...... 44 3.7 CAD mask used to define the current lines and contact pads for a) die A, b) die B and c) die C, where the blue arrows indicate the easy axis direction...... 45 3.8 Schematic representation of the Nordiko 7000 internal structure [37] ...... 46 3.9 Optical microscope photograph of die A after lift-off Optical microscope photograph of die A after lift-off...... 47 3.10 CAD mask used in the third lithography for die A...... 48 3.11 Photograph of the annealing setup...... 49 3.12 Hard mask design, dimensions of the cilia array in the left. On the middle is shown the CAD mask design used to fabricate the hard mask, each array containing 100 cilia, and on the right is specified d and s as cilium diameter and spacing between cilia, respectively...... 51 3.13 Optical microscope photograph of hard mask (non-inverted) after wet etch...... 51 3.14 Hard masks a) from the inverted mask design and b) from the non-inverted mask design. . . 52 3.15 SU-8 molds after development. a) using an inverted mask design, obtaining an SU-8 mold with cavities having the same dimensions as desired cilia. b) using a non-inverted mask design, resulting in SU-8 mold with ciliary structures, having the same dimensions as desired cilia. . 54 3.16 Schematic representation of the cilia array fabrication...... 54 3.17 Optical microscope photograph of the cilia array a) 100 cilia array with 100 µm diameter and 100 µm of spacing between cilia b) cilia array with 100 µm diameter and 150 µm of spacing between cilia, confirming the cilia top circular shape...... 56

xvi

3.18 Device wirebonding, a) wiring scheme for the 24-pin chip carrier, the same is used for the 28- pin chip carrier, with exception of the pin numbers. In this case the current source is connected to pin 5 (I+) and 17 (I-) and the voltage drop is measured between pin 6 (V+) and 19 (V-). The green arrows indicate the easy axis direction. b) Photograph of the assembled and wirebonded Full Wheatstone Bridge sensor with a cilia array on top, in a chip carrier...... 57 3.19 Photograph of the Magnetoreansport setup...... 58 4.1 Optical microscope photograph of four cilia cavities in SU-8 molds exposed to (a-c) time recommended by the manufacturer and (d-f) optimized exposure time. a) 50 µm thick SU-8 exposed for 33 s. b) 100 µm SU-8 exposed for 51 s. c) 150 µm SU-8 exposed for 70 s. d) 50 µm SU-8 exposed for 30 s. b) 100 µm SU-8 exposed for 45 s. b) 150 µm SU-8 exposed for 52 s...... 59 4.2 Optical microscope photograph of cilia arrays a) 50 µm thick SU-8 with 16 µm diameter cilia spaced by 7 µm and b) 100 µm thick SU-8 with 20 µm diameter cilia spaced by 30 µm. . . . . 60 4.3 a) Photograph of the PDMS mold with nanocomposite inside after baking, being impossible to separate the ciliary array from the mold. b) and c) optical microscope image of the nanocomposite that remained inside the SU-8 mold (darker cilia in the image), after cilia peeling. b) cilia array with 100 µm diameter and 150 µm between cilia. c) The smaller the cilia array dimensions, the higher number of cilia stuck in the mold...... 60 4.4 Nanocomposite magnetization curves obtained with a VSM for the a) cilia array with 150 µm diameter and 100 µm spacing between cilium. b) cilia array with 100 µm diameter and 150 µm spacing between cilium and c) cilia array with 100 µm diameter and 100 µm spacing between cilium. Legend: in blue measurements made parallel to the cilium symmetry axis and red made perpendicularly. d) The measurements were taken in the vertical (parallel) and horizontal (perpendicular) direction of the cilia array...... 61 4.5 Magnetoransport curve of individual spin valves with aspect ratio of a) 2 x 40 µm2, b) 3 x 40 µm2 and c) 3.5 x 40 µm2. The spin valves were supplied with a 1 mA DC current...... 63 4.6 CAD software mask of the three different layout designs: a) die A with 1 x 0.5 mm2 , b) die B, having 2 x 2 mm2 and c) die C for Full Wheatstone Bridge sensor, each one with 1.5 x 1.5 mm2, forming an active area of 3 mm2. Color legend: spin valves in red, metallic current lines in blue and contact pads in green...... 64 4.7 a-c) Magnetotransport curve of the three GMR sensor design layouts, with an external field applied in the sensitive direction and a DC current input of 1 mA. a) die A, b) die B and c) die C. Insets: Close-up from - 10 Oe to 10 Oe, showing the sensors coercivity. d) Voltage output response of a Full Wheatstone Bridge sensor to an applied magnetic field, without artificial ciliary structures on top of the sensor, feed by a DC current input of 1 mA. The voltage drop between the two arms of the bridge (between pin 6 and 19 for the 24-pin chip carriers; pin 7 and 22 for the 28-pin chip-carrier) shows a voltage offset of 8 mA at zero applied magnetic field...... 65 4.8 Full Wheatstone Bridge sensor response to cilia deflection, for each cilia array a) cilia with 100 µm diameter and spacing between cilia of 100 µm, b) 100 µm diameter and 150 µm spacing

xvii

and c) 150 µm diameter and 100 µm spacing (all dimensions nominal). d) Schematic representation of how the fruit skin roughness was measured, the fruit is swept parallel to the sensor sensitive direction. Legend: in red is the fruit; blue is the PDMS; blue with black dots is the nanocomposite; black is the sensor; grey wires are the wirebonding and in gold is the chip carrier...... 66 4.9 Skin roughness measurements of three fruits in different ripeness state, using the texture sensor for a) blueberries and b) strawberries. c) and d) show the amplitude of the four measured signals for each maturation state, indicated by the fruit image bellow (from left to right: green, ripe and overripe) ...... 68

xviii

xix

List of Acronyms

AFM Antiferromagnetic

DC Direct current

DI Deionized water

DWL Direct Wright Laser

FM Ferromagnetic

GMR Giant Magnetoresistance

HMDS Hexamethyldisilazane

IBD Ion Beam Deposition

IPA Isopropyl alcohol

MR Magnetoresistance

NM Non-magnetic

PDMS Polydimethylsiloxane

PGMEA Propylene glycol monomethyl ether acetate

PVA Poly (Vinyl alcohol)

RF Radio Frequency

SVG Silicon Valley Group

UHV Ultra high vacuum

UV Ultraviolet

UVO Ultraviolet Ozone

xx

xxi

1 Introduction

1.1 Motivation and objectives

Food is a valuable resource, and yet all around the world, a vast amount of food that could have been eaten is wasted every day. Fresh fruits and vegetables are amongst the most frequently wasted foods because of their high perishability and postharvest handling requirements [1]. Strawberry is a fruit that is mostly consumed fresh, which requires it to be pleasing in flavor, texture and appearance. However, due to their high perishable nature and mishandling, strawberries are one of the most often discarded fruits throughout the supply chain. One way of reducing this waste is the introduction of automatized technologies for the manipulation and quality inspection of fruits. With the automation of these processes, there will be less human contact with fruits, which leads to a lower probability of fruit damage and bruise [2]. Nowadays, strawberry grading is still performed manually by human operators which may lead to misclassifications, resulting in boxes with fruit in different maturity stages. The fruits in a more advanced maturation stage will accelerate the maturation of the others, which can lead to the over-maturing of the entire box, resulting in major food waste. Also, the defective, infective or contaminated fruits can spread the infection or contamination on sound fruits, even the whole batch, thus causing great food waste and economic losses, moreover safety problems [3]. The objective of this thesis is to combine two nondestructive techniques into a quality assessment and grading system, analyzing strawberries’ texture and ethylene emission, and incorporating it into a robot fingertip, so that it can evaluate and separate fruits according to their ripeness stage in real time, reducing fruit handling by humans and consequently reducing mechanical damage and bruising, leading to less fruit waste. The gas analysis is performed by a magnetic gas sensor, to differentiate the strawberries according to their maturation stage, as fruits in different ripeness stages emanate ethylene at different concentrations, while the texture analysis is performed by a magnetic tactile sensor, as green strawberries present a smother peel than ripe ones. The magnetic tactile sensor developed consists in a magnetic sensor, namely a series of spin valves, that detect changes in magnetic stray field generated by the cilia array, and an artificial cilia array composed by a highly elastic and permanent magnetic nanocomposite, which induces magnetic field perturbations over the sensor, according to the surface texture. Due to time constraints, the gas sensor was not developed.

22

1.2 State of the art

There are two ways to evaluate fruit quality, either by assessing its external or the internal attributes. External quality attributes relate to the appearance of the fruit and include properties such as color, shape, size and the absence of surface defects. These parameters determine the purchase behavior of the consumer as these properties may be inspected readily at naked eye. On the other hand, internal quality attributes include texture properties such as firmness and crispiness, taste, aroma and absence of internal defects. These are the attributes that will determine the organoleptic satisfaction of the costumers [4]. Quality attributes can be measured by both destructive and nondestructive techniques. Destructive measurements require precise sample preparation, specialized personnel, are labor intensive, time consuming, costly and usually only involve few representative samples on which quality of the fruit batch is based. This is a major disadvantage because growers stand the risk of delivering poor quality products to the market, due to fruit quality variation within a batch. The latest, nondestructive techniques, are preferred since they are often fast, reduce waste and have a major advantage, the measurement procedure does not affect the characteristics of the fruit. Therefore, as an immediate benefit, such techniques can be used for grading individual fruit with respect to quality prior to sale [4]. Traditionally, the primary method for evaluating the quality of fruit is sensory analysis, based on the use of human senses. The smell, taste and appearance of fruit is evaluated by a properly trained group of people. However, human perception can be fooled, inconsistent and it requires high labor costs which together accentuate the need for automatized measurement systems. As the purpose of this thesis is to develop a fast (real time) and low to moderate-cost technique for strawberry quality assessment, techniques that can only be applied in laboratory environment, are very slow and/or with very high cost, were excluded. For this reason, a gas and texture sensor were chosen to be developed.

a) b)

Figure 1.1: Magnetic tactile sensors. a) Photograph of the small force sensor. The Giant magnetoresistance (GMR) sensor is comprised by the whole area under the cilia. Inset: scanning electron microscope photograph of a cilium of the same sensor [5] © [2017] IEEE . b) Illustration of the Braille characters reading application [6] © [2016] IEEE .

23

1.2.1 Existing texture sensors

Texture is a key quality attribute used in fresh food industry to assess product quality and acceptability [7]. In the context of this thesis, by texture it is implied the rugosity of the fruit skin. Usually unripe fruits present a smooth and firm skin but as maturation occurs, it becomes more wrinkled and softer. Therefore, there is a relation between fruit skin texture and maturation stage. In the late 19th and early 20th centuries texture analysis was based on simple sensory evaluations to detect and eliminate defects. The combination of time and high cost associated with sensory perception has motivated the development of instrumental analysis, using empirical mechanical tests which correlate with sensory perceptions of food texture [7]. There are several destructive methods to evaluate fruit firmness, such as three-point bending test, puncture and penetration tests. All consist in the introduction of a cylindric head or a needle into the fruits’ flesh, measuring, for example, the penetration depth or the force needed to puncture the skin, which decreases and increases with increasing firmness [7] [8]. Methods such as quasi-static force-deformation, impact response, “finger” compression and bioyield detection are named non-destructive measurements as usually no visible damage is found. Nonetheless, they are still destructive in the micro-scale and the information obtained is not comprehensive [7] [9]. Szczesniak [10] defines texture as “a sensory property, and thus only a human can perceive and describe it”. The evolution in areas like robotics has led to the development of different technologies that can mimic the complex sense of touch in humans. Tactile sensor technology has already been used as a small force sensor for application in robotic platforms (figure 1.1 a) [5] and even as artificial skin for Braille characters reading (figure 1.1 b) [6], therefore it is a promising approach to assess fruit texture, similar to humans. These magnetic tactile sensors consist in permanent magnetic and highly elastic artificial cilia placed on top of magnetic micro sensing elements (spin valves). The operating principle of the sensor is based on detecting the change of the magnetic stray field, created by the permanent magnetic cilia, when deflected by an external force.

1.2.2 Existing gas sensors

Electronic noses are devices engineered to mimic the mammalian olfactory system within an instrument designed to obtain repeatable measurements, allowing identifications and classifications of aroma mixtures [11]. They present great benefits compared to the traditional gas analysis methods, such as gas chromatography mass spectrometry and Fourier transform infrared spectrometry, because they have the potential to be smaller, faster, less expensive, suitable for non-expert users and applicable to daily life [12]. These devices have been developed for numerous industry applications, where volatile

24 organic compounds can be regarded as indicators of food spoilage [13], presence of hazardous gases in the air [14] and even certain diseases, when found in biological samples [15]. Currently, conductometric semiconducting metal oxide gas sensors are the most studied group of gas sensors, however recent advances in the field of magnetic gas sensing have demonstrated that spintronics will allow to overcome the limitations of the present conductometric devices, such as the high working temperature (ranging between 250° C and 500° C) and consequent high power consumption [16] [17]. For this reason, a magnetic gas sensor was chosen to be developed.

Strawberry volatiles

Although strawberry has traditionally been classified as a non-climacteric fruit, based on its low endogenous production of ethylene compared with standard climacteric fruits and because of its inability to accelerate fruit ripening by the external application of ethylene. Recent studies report that, despite its low concentration, ethylene presents a characteristic pattern of production during different strawberry development stages, increasing in concentration as fruit decays [18]. The monitoring of ethylene concentration is of utmost importance in the horticultural industries. The internal ethylene concentration in fruit can serve as an indicator for determining the time of harvest, while the monitoring of the atmospheric ethylene level in storage facilities and during transportation is crucial for avoiding overripening of fruit [19]. Esser et al. [19] developed a chemoresistive gas sensor for ethylene detection, to be used as a method for determining fruit ripeness. For the selective recognition of ethylene, the authors employed a copper (I) complex, inspired by the nature, where CuI has been found to be an essential cofactor of the receptor ETR1. This transition metal cofactor can only be replaced by the other two group 11 metals (silver and gold) for high-affinity ethylene binding in ETR1 receptors [20].

25

2 The system concept

The device is composed of an active (magnetic sensor) and a passive (cilia) component: • A magnetic sensor, namely a series of spin valves, detects changes in the magnetic stray field, generated by the artificial cilia array; • An array of cylinders, composed of a highly elastic and permanent magnetic nanocomposite, induces magnetic field perturbations over its surroundings, depending on the surface texture. The magnetic particles embedded Polydimethylsiloxane (PDMS) nanocomposite is molded into an array of cylinders and orthogonally fixed over the magnetic sensor. When passing over the fruit skin, the cilia deform, according to the fruit texture, changing the magnetic stray field emitted by them. This is detected by the magnetic sensor, as its sensing layer orients in an opposite direction to the one of the magnetic stray field, which is translated into a change in resistance (figure 2.1). Therefore, by supplying the device with a constant current (voltage) while passing it over the fruit skin and measuring the output voltage (current), an electrical measurement of fruit texture is made.

R

Free FM layer

Pinned FM layer

and are the magnetization orientation H

Artificial cilia array

Magnetic sensor

Figure 2.1: Expected magnetotransport curve in response to cilia deformation for each direction. The spin valve’s free layer aligns antiparallel to the cilia magnetization orientation, originating a high or low resistance state which can be verified by supplying the device with a current (voltage) and measuring the output voltage (current).

26

2.1 Magnetic sensor

2.1.1 Magnetoresistance

The basic principle of magnetoresistance is the variation of the resistance of a material when exposed to a variable magnetic field. A magnetoresistive device is composed of a combination of magnetoresistive materials, whose magnetization will tend to align with the external field and are optimized to maximize their resistance variation (Rmáx – Rmin, being the maximum and minimum resistances respectively). The magnitude of the magnetoresistance effect (MR) can be expressed as a percentage and is defined as follows: 푅 −푅 MR (%) = 푚á푥 푚푖푛 × 100 (1) 푅푚푖푛 Three main thin film magnetic sensor technologies are based in MR: • Anisotropic magnetoresistance (AMR), in which the electrical resistance is a function of the angle between the material magnetization and the electrical current’s direction flowing through it; • Giant magnetoresistance (GMR), observed in thin film multilayered structures composed of alternating metallic ferromagnetic and metallic non-magnetic layers, where the change in electrical resistance depends on the relative magnetization of the ferromagnetic layers with each other (parallel or antiparallel); • Tunnel magnetoresistance (TMR), which occurs in multilayered structures, structurally similar to the GMR but instead of having a metallic non-magnetic layer, it has an insulating barrier sandwiched between two ferromagnetic layers, changing electrical resistance with the relative magnetization of the ferromagnetic layers with each other. For this thesis, a GMR sensor was chosen to be developed.

2.1.2 Giant magnetoresistance

GMR is a quantum mechanical MR effect observed in multilayered thin film structures consisting of a sequence of metallic ferromagnetic (FM) layers separated by metallic non-magnetic (NM) layers, as represented in figure 2.2 b). The observed effect is a significant change in the electrical resistance of such structures depending on whether the magnetization of consecutive FM layers are parallel or antiparallel aligned (figure 2.2 a) [21]. The phenomenon that gives rise to this effect is the spin- dependent scattering of conduction electrons within the FM layers and at their interfaces. Typically, the 3d-bands of FM materials are exchange split, so the density of empty states at the Fermi level is not

27

FM layer NM layer FM layer

Figure 2.2: Representation of the GMR effect. (a) Change in multilayers’ electrical resistance as a function of applied magnetic field. (b) Typical trilayer structure with a FM configuration (edges) and an antiferromagnetic (AFM) configuration (in the middle), magnetization direction indicated by the arrows. The magnetizations are aligned antiparallel at zero field. As the applied magnetic field is increased, the magnetization in the FM layers progressively rotates towards the field, until it reaches saturation (HS) where the magnetization ends up in a configuration of parallel alignment. (c) The magnetization curve for the multilayer. Adapted from [22] Copyright (2001), with permission from Elsevier. the same for spin up and spin down electrons, resulting in an electron scattering asymmetry which leads to different resistances for each spin dependent current [23] [21]. The GMR effect can be explained by the two current model (figure 2.3), proposed by Mott [24], in which the total conductivity is expressed as the sum of the conductivity of the spin up and spin down electrons. It is assumed that the electrical current flows in two channels, one corresponding to each spin orientation, and that scattering is strong for electrons with spin antiparallel to the magnetization direction. So, when the two FM layers are magnetized parallel, the spin up electrons can travel nearly unscattered, providing a conductivity shortcut and a low resistance, as one channel verifies a low resistance state in both resistive elements, figure 2.3 a. On the contrary, in the antiparallel case, both spin up and spin down electrons undergo collisions in one FM layer or the other, giving rise to a high resistance state, figure 2.3 b. There are two possible modes of current flowing through the spin valve: current-in-plane, in which the electric current is applied in the plane of the multilayer, and current-perpendicular-to-the-plane, where the current is applied perpendicular to the multilayers. For current-in-plane geometry, used in this work, although there is no electron transport in the direction perpendicular to the multilayers, the electrons are able to move from one magnetic layer to the other through the NM spacer, i.e. in the high resistance state the electrons are forced to conduct through the spacer layer, while on the low resistance state, the electrons from one channel can freely move through the layer [22].

28

a) b)

spin spin

Low resistance state High resistance state

Figure 2.3: Schematic representation of the GMR effect in a trilayer film of two identical FM layers sandwiching a NM layer. a) When the FM layers are parallel magnetized, the spin up electrons are weakly scattered whereas spin down electrons are strongly scattered, in both FM layers. This is simulated by two small resistors in the spin up channel and two large resistors in the spin down channel, in the equivalent resistor network. In this configuration, the spin up channel is preferred. b) When the FM layers are antiparallel magnetized, the spin up electrons are strongly scattered in the second FM layer, while the spin down electrons are strongly scattered in the first FM layer. This is modeled by a small and a large resistor for each channel. Therefore, there is no shorting and the total resistance in the AFM configuration is much higher than in the FM configuration. Adapted from [22] Copyright (2001), with permission from Elsevier.

2.1.3 Spin valve

Although the GMR effect can be observed in trilayered structures, it is very challenging to modify one of the layers magnetization using an external magnetic field without altering the other, resulting in a very low magnetoresistivity. Spin valves, introduced by Dieny et al. in 1991 [25], consist in a GMR based device structure, two metallic FM layers separated by a metallic NM spacer, with the addition of an AFM layer. The AFM layer is added to induce a permanent magnetization orientation on its adjacent FM layer, through exchange coupling. This way, one FM layer has a fixed direction of magnetization (pinned layer or reference system) while the other FM layers’ magnetization direction can freely align with the external magnetic field (free layer or sensing layer), acting as a sensing electrode. In order to let the free layer follow changes in the external magnetic field, the NM spacer layer has to be thick enough to ensure a minimal magnetic coupling of the magnetic layers [26]. To achieve a maximum stability of the reference system against external fields, the AFM layer (pinning layer) can be added in the top, bottom or both parts of the structure (figure 2.4). Hence, spin valve is a reliable and more sensitive magnetoresistive sensor, when compared to trilayered structures, also presenting maximum resistance when the FM layers magnetization are antiparallel and minimum when both are parallel aligned.

29

AFM layer

Pinned layer

Spacer layer

Free layer

Figure 2.4: Schematic arrangement of a) bottom, b) top and c) symmetrical spin valve structures. In the bottom spin valve, the bottom FM layer is pinned by the adjacent AFM layer, while in the top FM layer is free to rotate; the opposite happens for the top spin valve. In the symmetrical spin valve, the central FM layer is free while the other two FM layers are pinned.

2.1.4 Linearization strategy

Depending on the application, spin valve sensors can be fabricated to obtain either an hysteric (MRAM applications) or linear response (sensing applications), by inducing the free and pinned layer easy axis in a parallel or orthogonal configuration [27]. The behavior of the spin valves’ FM layers is explained by the macrospin energy equation for a 2D material: 1 퐸 = −µ 푉푀 ∙ 퐻 + 퐾푢푠푖푛2(휙) + 푉푀푁̂푀 − µ 퐻 ∙ 푀 (2) 푚 0 0 2 0 푁

Zeeman Demagnetizing Néel Magnetocristaline

Where H0 is the external field applied in the spin valve (in this work, it is the magnetic field emitted by the magnetized cilia), Ku is the magnetocristaline anisotropy constant, M is the magnetization moment of the spin valve, HN is the Néel field, 푁̂ is the demagnetization component, V is the volume of the magnetic domain and 휙 is the angle between the free FM layer magnetization orientation and the spin valve easy axis. All terms contribute for spin valve behavior however, the magnetocristaline term and the demagnetizing term play a major role on the spin-valve linearity. The magnetocristaline term describes the effect that allows the pinned layer to remain with its magnetization unchanged. It relates to the preferential magnetization direction (easy axis) to which dipoles tend to align, usually due to its crystallographic orientations. By controlling the growth direction of the deposited spin valve layers, this effect defines the crystallographic orientation of all the stack layers. The demagnetizing term describes the effect responsible for orienting the free layer magnetization in the absence of applied magnetic field. It relates to the direction to which the magnetization tens to align due to the shape of the magnetic material. Since the magnetization of any magnetic material, with a

30

a)

Free FM layer

Pinned FM layer

b) c)

Figure 2.5: Scheme of the developed spin valve configuration. a) Ideal magnetotransport response of the developed spin valve. b) Exploded top view of the spin valve spacer, free and pinned layers. c) spin valves’ sensitive direction defined upon deposition. Adapted from [23] © EDP Sciences, 2015. high aspect ratio, tends to align with its longer axis, this term increases as the total area of the material decreases and its aspect ratio increases. Hence, by patterning a spin valve with a high aspect ratio (typically ≈ 20:1) and reducing its area to dimensions of the order of µm2, its free layer will adopt the magnetization direction of the patterned spin valve long axis, when no magnetic field is applied. In the case of the spin valves developed for this work, the stack is deposited with a preferential magnetization direction (easy axis), to which the dipoles tend to align due to their crystallographic orientation. Afterwards the spin valves are patterned, defining their longest axis, according to which the free layer magnetization will be orientated parallel. This way free and pinned layer easy axis are set orthogonally, achieving a linear sensor response (figure 2.5) with two resistance plateaus. The free layer is oriented parallel or antiparallel to the pinned layer due to an external applied magnetic field, resulting in a low or high resistance state respectively. The absence of applied magnetic field corresponds, ideally, to the midpoint between these two resistance values.

50 Å Ta Buffer

70 Å MnIr AFM 26 Å CoFe Pinned FM

28 Å Cu NM spacer 28 Å CoFe Free FM

25 Å NiFe Soft FM 20 Å Ta Buffer

Si / SiO2 substrate

Figure 2.6: Scheme of the top pinned spin-valve used in this thesis.

31

Modern spin valves are fabricated with more stack layers than those used by Dieny et al. [25], in order to obtain different sensitivities and resistance ranges. These layers must be thin enough the for the material to be valid and have the ideal thickness for which the GMR effect is maximum. In this work, a seven layered spin valve was fabricated (figure 2.6). The function of each layer type and how they affect the magnetoransport curve is the following: Buffer layers: composed of metallic material, are the interfaces between the substrate and the stack, on the bottom, and between the stack and the metallic contacts, on the top. This layer is important as it ensures a good crystalline growth of the layers above it and improves the electrical contact of the stack with the metallic contacts. Soft FM layer: made from a soft FM material, is used to reduce the coercivity and improve the linear output of the sensor, through exchange bias. Free FM layer: made from a FM material, whose magnetization rotates with the external applied magnetic field. NM spacer: metallic NM material that separates both FM layers. As its thickness decreases the MR increases, however, it cannot be too thin otherwise the exchange bias between the two FM layers increases, therefore increasing the applied magnetic field necessary to change the resistance. Pinned layer: FM material, with magnetization pinned by the AFM layer, servs as the sensors’ reference layer. AFM layer: AFM material, whose interfacial spin magnetization orientation pins the one of the adjacent (pinned) FM layer, through exchange coupling.

2.1.5 Sensor design

The spin valve electrical resistivity is calculated by:

퐴 푑×ℎ 휌 = 푅 = 푅 (3) 푙 푙 Where 휌 is the resistivity, R is the minimal resistance, A is the spin valves’ area, l is length, d is width and h is height of the spin valve. The average resistivity of the spin valve stack was found to be of 0.5 Ωm. Therefore, the resistance of one 3 x 40 µm2 spin valve is 273.1 Ω. Once the sensor is meant to be used with a current of 1 mA and a voltage of 2.5 V, the ideal sensor resistance is of 2.5 kΩ.

a) b)

Figure 2.7: Representation of a) the sensor’ circuit and b) the equivalent circuit.

32

The device is composed by arrays of spin valves connected in series and in parallel, as represented in figure 2.7. Since all spin valves are similar, all resistors present the same value (R1 = R2 = … = RN). Being N the number of spin valves in series and M the number of spin valves in parallel the equivalent resistance of one array of spin valves is given by equation (4). The metallic current leads also present some resistance (Rcontacts) that must be considered, in this work it is assumed to be of 1 Ω.

1 1 1 = 푀 × ( ) = 푀 × ( ) + 푅푐표푛푡푎푐푡푠 푅푒푞. 푎푟푟푎푦 푅푒푞. 푠푒푟𝑖푒푠 푁 × 푅1

푁 ⇔ 푅 = × 푅 + 푅 (4) 푒푞. 푎푟푟푎푦 푀 1 푐표푛푡푎푐푡푠

Three different sensor designs were fabricated, one with 25 spin valves in series and 5 in parallel, another with 100 spin valves in series and 10 in parallel and the last one with 35 spin valves in series and 12 in parallel, being the equivalent resistance of the sensors of approximately 1.4 kΩ, 2.7 kΩ and 797.8 Ω, respectively.

Wheatstone Bridge-based spin valve sensors

The Wheatstone Bridge was originally developed by Charles Wheatstone to measure unknown resistance values by comparing them with well-defined resistances. The Wheatstone Bridge circuit consists in four resistors, two input terminals and two output terminals (table 2.1). The fundamental concept of the bridge is that it is formed by two voltage dividers, fed by the same input current, and that both outputs contribute to the circuit output (VO), which is given by equation (5). When balanced, the two voltage dividers have exactly the same ratio, R1/R3 = R2/R4.

푅3 푅4 푉푂 = ( − ) × 푉푏 (5) (푅1+푅3) (푅2+푅4)

Table 2.1: Wheatstone bridge configurations [28].

33

Figure 2.8: Schematic of a full bridge GMR sensor. R1 and R3 present ΔR/ΔH <0 and R2 and R4 ΔR/ΔH >0 [29].

Full Wheatstone Bridge configuration

Even though a unique resistance can be used as a sensing element, a Wheatstone bridge configuration is always a good recommendation as the starting step in the design of resistive sensors [28]. There are several bridge configurations (table 2.1), but from an applications point of view, the most interesting is the Full Wheatstone bridge, where all four resistive elements actively contribute for the output signal [30]. In this work, each resistive element consists in an array of 35 spin valves connected in series and 12 in parallel, with individual dimensions of 3 x 40 µm2. To make the bridge operational, four identical MR sensors are required, however two must exhibit ΔR/ΔH > 0 that is symmetric with respect to the other two, having ΔR/ΔH < 0 (figure 2.8) [29]. Meaning the reference layer of the two sensor types must be directed along the same direction but in opposite senses. This way, for example, a full scale positive (negative) output of the sensor is achieved when a magnetic field Hsat is applied, causing the free layer magnetization to rotate such that it is parallel (anti parallel) to the pinned layer magnetization in R1 and R3 and antiparallel (parallel) in R2 and R4 (from figure 2.8). The sensitivity of a Full Wheatstone Bridge made up of four identical MR sensors is the same as an individual element. However, if the resistance of the four elements is changed uniformly (as expected from temperature drifts), the contribution of such change to the bridge output is null, on the contrary, if a magnetic field is present, the four elements experience changes in resistance that are asymmetric. In this case, a differential output is obtained as a function of the resistance variation. Other advantages of using a Full Wheatstone Bridge are that it outputs a bipolar signal (instead of only positive), ideally centered in zero, which facilitates the integration with other electronic components and that it can be supplied with both current or voltage, being the response measured in voltage or current, respectively, also facilitating further electronic integration [30].

34

Figure 2.9: a) Illustration of the nanocomposite cilia tactile sensor. It is made of permanent magnetic nanocomposite cilia integrated on a magnetic sensor that mimic the neuron in natural cilia [31] © 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim. b) Illustration of the sensors’ working principle. The nanocomposite cilia have a stray field that affects the GMR sensor and biases it to an initial resistance value. A top view of the tactile sensor is shown (not to scale). c) When a force is applied and the cilia deflect, the stray field measured with the GMR sensor changes, hence changing the resistance [6] © 2016, IEEE.

2.2 Artificial cilia structures

Artificial ciliary structures are inspired in the extremely sensitive mechanosensorial hair-like cilia receptors found in nature, which consist in a passive organelle called cilium (an elongated hair-like protuberance) coupled to an active organelle, the dendrite, which is a nervous system ending that sends electric pulses whenever the cilium is actuated [32]. In nature, cilia are used, for instance, as touch and vibration sensing receptors on insect legs [32] and in the cochlea in the inner ear. They provide exquisite sensing performance, mainly due to the high aspect ratio and high surface to volume ratio, which ensures strong interaction with the environment [8] [34]. These structures can be mimicked to fabricate a tactile sensor that consists in slender protuberances, highly elastic and permanent magnetic nanocomposite artificial cilia, over a transduction medium, a magnetic sensing element (figure 2.9 a). The nanocomposite can be made of iron nanowires [8] [34] or magnetic particles [5] incorporated into PDMS. The working principle of the sensor is that when a force is applied or there is a change in the surface texture, the nanocomposite cilia bend, resulting in a change of its magnetic stray field (figure 2.9 b), which is detected by the GMR sensor, changing its resistance. Therefore, by measuring the voltage output, one can conclude about the applied force or rugosity of the surface (figure 2.10 b). The development of artificial cilia sensors has originated various applications. Alfadhel et al. [31] fabricated a giant magneto-impedance sensor with 1 mm long and 200 µm diameter cilia arrays with 9 and 24 cilia on top and concluded that the sensor was capable of detecting the texture of groovy objects (figure 2.10). Alfadhel et al. [6] developed a sensor, with an array of 9 cilia having the same dimensions as the previous, but placed it on top of four GMR sensors, capable of reading Braille characters. Ribeiro et al. [5] presented two tactile sensors, composed of an array of 5 cilia with 1 mm of height and 120

35

b) a)

Figure 2.10: a) Photograph of a flexible tactile sensor with an inset showing a SEM image of the cilia, and a photograph showing the flexible sensor attached to the skin. b) Dynamic response for texture measurement [31] © 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim.

µm and 200 µm diameter for each one on top of a GMR sensor, capable of measuring small forces down to 333 µN.

2.2.1 Nanocomposite

The cilia must be able to bend, according to the surface texture, and return to its original position, without suffering irreversible deformations, meaning they should present an elastic behavior. The deformation of a material is described by its strain vs stress relation, being the stress, the force applied on the material and the strain the deformation suffered by it, when a specific stress is applied. For most materials the strain vs stress plot presents two regions of interest, the elastic region, in which the deformation is reversible, and the plastic region, in which the deformation is irreversible (figure 2.11 a). Typically, the elastic region shows a linear strain vs stress relation, being its slope defined by the Young’s modulus. Materials such as rubber and polymers that present an almost non-existent plastic behavior region (figure 2.11 b), meaning they can be deformed under extreme stress without losing their ability to return to the original shape, are called hyperelastic materials. PDMS is included in this category, being that one of the reasons why it was chosen to integrate the cilia nanocomposite. One way to induce permanent magnetization on the cilia is by embedding it with magnetic particles which, in this case, are composed by a neodymium boron cobalt iron alloy, with diameter of 5 µm. After the application of a magnetic field of 1 T, the particles magnetization orientation will be parallel to each other.

36

a) b)

E

E

Figure 2.11: Stress vs strain curve for a) a ferrous alloy (structural steel). The various states the steel experiments, for different applied strains. Adapted from [33]. b) for an elastic material (paper for example) and a rubber-like hyperelastic material. In both plots, the blue dashed line represents the stress vs strain curve slope (Young Modulus).

2.3 Towards a gas sensor integration in cilia

The incorporation of the gas sensor would be done by depositing a thin gas (ethylene) sensing layer on top of the artificial ciliary structures, without compromising its elastic properties, inserted on top of the magnetic sensor. This layer would consist of copper ions (Cu+), or other group 11 transition metal (gold or silver) [20], for high affinity ethylene binding, embedded in FeO, NiO or CoO particles, which change their magnetic properties depending on the presence or absence of oxygen. These particles exhibit a non-magnetic (AFM) behavior in the presence of oxygen but become magnetic (FM) when it is released [34]. This alteration is then detected by the magnetoresistive sensor, located bellow the artificial ciliary structures, resulting in a change of its resistance. The magnetic gas sensor would behave as follows: in the absence of ethylene, the particles would not be magnetic (presence of oxygen), therefore the output signal would remain unchanged. In the presence of ethylene, it would bind to the copper ions, releasing the oxygen, which would give rise to a magnetic signal emitted by the particles. This signal would be detected by the magnetic sensor as a change in resistance. Therefore, by measuring the device resistance, one can conclude about the presence and concentration of ethylene bound to the sensing layer and thus, the fruit ripeness stage. Both the interactions between gas and the sensitive particles as well as the gas induced magnetic changes should be reversible, without the need for a cleaning process in between measurements, which is an essential property for practical sensors.

37

3 Device fabrication

In this thesis, the sensor developed consists in 4 resistive elements (R1 to R4) in a Full Wheatstone Bridge configuration, operating simultaneously, each composed of 35 spin valves in series and 12 in parallel, forming an active area of 3 mm2. Each GMR sensor is 40 μm long and 3 μm wide with sensitivity along the width direction. The artificial ciliary structures are made of 100-cylinder arrays, with 150 μm (nominal) height varying the diameter and spacing between cilia, inserted on top of the GMR sensor array. These structures are composed of a highly elastic and permanent magnetic nanocomposite. This chapter covers all the processes required for the fabrication of the device, the metrology and inspection parameters monitored, and the working principles of each machine used. The sensor fabrication is composed of two major steps: • Fabrication of the GMR sensor; • Fabrication of the artificial cilia and insertion over the GMR sensor. A brief summary of the GMR sensor fabrication run sheet is presented below (figure 3.1): 1. Deposition of spin valve stack. 2. Spin valve shape definition (a) 1st Lithography (b) Ion milling etch (c) Resist strip 3. Current lines and contact pads definition (a) 2nd Lithography (b) Metallization (c) Lift-off 4. Passivation (a) 3rd Lithography (b) Alumina deposition (c) Silicon oxide deposition (d) Lift-off 5. Annealing 6. Dicing A brief summary of the run sheet for the artificial cilia fabrication and insertion over the GMR sensor is presented below:

7. Hard mask design and fabrication (a) Metallization (b) Lithography (c) Wet etch (d) Resist strip

38

1.5 µm Photoresist

50 Å Ta 70 Å MnIr 26 Å CoFe 247 Å 28 Å Cu 28 Å CoFe 25 Å NiFe 20 Å Ta Si / SiO2 substrate

st Stack deposition 1 lithography Photoresist development

Ion milling etch 2nd lithography Photoresist development and resist strip

2000 Å SiO2 2000 Å Al2O3

3000 Å Al 150 Å TiW

Metal deposition 3rd lithography Passivation layer and lift-off deposition and lift-off

Figure 3.1: Schematic representation of the GMR sensor fabrication process.

8. SU-8 mold fabrication (a) Spin coat (b) Soft bake (c) Exposure (d) Post exposure bake (e) Develop 9. Nanocomposite casting and peeling (a) Nanocomposite preparation (b) PVA preparation and coating

39

(c) Cilia fabrication 10. Annealing 11. Device assembly (a) Plasma bonding (b) Wirebonding

3.1 Microfabrication techniques and equipments

3.1.1 Deposition of spin valve stack

The spin valve stack used in this thesis was deposited prior to the beginning of this work, therefore the deposition parameters are not available nor the machine where it was deposited. The method used for stack deposition is magnetron sputtering, consisting in the application of a strong electrical discharge, by DC, to argon atoms in a vacuum chamber. The removal of the valence electrons from these atoms (ionization of argon) generates the plasma that is concentrated in the area by a set of magnets. The positively charged argon particles are accelerated towards the negative electrode (cathode) located above the target containing the atoms of interest. The collision of the high energy argon cations against the target atoms causes their removal, sputtering. The ejected atoms fall and deposit on top of the substrate (located bellow the target), creating a thin film. The machine used has targets with different material composition, for different stack layers.

The stack is deposited over a Si substrate with a SiO2 layer, serving as a passivation layer to electrically isolate the stack from the Si. The spin valve stack consists in a multi-layer composed of the following thin films, from bottom to top (thickness in Å): Ta 20/ NiFe 25/ CoFe 28/ Cu 28/ CoFe 26/ MnIr 70/ Ta 50.

3.1.2 Spin valve shape definition

1st Lithography

Due to the dimensions of the features used to pattern the spin valve (rectangular spin valves with 3 x 40 µm2) Direct Write Laser (DWL) lithography was performed to define the spin valve shape. Before the lithography process, the substrate must be cleaned and subjected to a pre-treatment process called vapor prime, which consists in wafer dehydration, to remove adsorbed water from the surface, followed by hexamethyldisilazane (HMDS) coating to improve the adhesion of the photoresist to the substrate. For that, the sample is placed in the vapor prime oven, which heats it until at 130°C, and applies HMDS, that turns the sample’s surface hydrophobic. The overall photolithography process can be divided in three steps:

40

• Substrate spin coating with photoresist; • Exposure with DWL 2.0 laser system; • Photoresist development. First the substrate is coated with a positive photoresist, a polymer whose average molecular weight is reduced by a photochemical reaction that occurs during exposure at a certain wavelength, weakening the polymer and making it soluble to the developer solution, resulting in the removal of the exposed areas. A Silicon Valley Group (SVG) coating track (figure 3.2) was used to deposit a 1.5 µm thick (nominal) layer of photoresist. The sample is placed in the coating station, where the photoresist is dispensed while the sample is rotating at 800 rpm for 5 s, followed by spinning at 2500 rpm for 30 s, to ensure thickness uniformity. The sample is then passed to the heating station, where it is soft baked at 85°C for 60 s, to evaporate the solvents and harden the resist layer. The second step is exposing the sample, in the Heidelberg Direct Write Laser 2.0. It uses a static NeAr laser, with a wavelength of approximately 440 nm, to write the previously designed CAD mask (figure 3.3) on the sample, 200 µm at a time (corresponding to the respective .lic file) as the xyz motorized stage (where the sample is placed) moves the sample, creating the desired pattern. The CAD mask can be inverted, in which all the photoresist is exposed except inside the designed features, or non-inverted, in which the photoresist inside the features is exposed. To ensure the photoresist remains in the desired areas, one must take into account if the photoresist used is positive, the exposed areas are dissolved by the developer, as mentioned before, or negative, the unexposed areas are dissolved by the developer. In figure 3.4, a summary of how the sample looks, after development, for all the combinations of mask and photoresist types is presented. In this lithography, used to define the spin valve shape, an inverted mask is used in order to expose all the photoresist except inside the designed features (figure 3.3). The remaining photoresist has the function of a shield, protecting the covered areas from the following etching process. The Heidelberg Direct Write Laser 2.0 is capable of critical dimensions down to 0.8 µm, however the process as a whole has a minimum feature size of 1 µm. Two parameters are available to tune the laser exposure, laser focus and energy. Focus controls the distance at which the laser beam is focused relatively to the camera focus. As the camera is focused below the photoresist, a laser focus of -10 is used to focus the laser on the photoresist. Energy controls the percentage of laser energy used in the exposure, as low energies are not able to successfully break the polymer structures and high energies produce reflections in the substrate material that decrease the laser resolution and the sharpness of the structures. 65 % of the laser energy is used.

Figure 3.2: SVG coating and developing track.

41

40 µm

Spin valve stack

3 µm

40 µm

Figure 3.3: CAD mask used to define the spin valves shape.

Finally, the sample is loaded in the SVG development track (figure 3.2) for the photoresist development, concluding the lithography process. The sample is baked at 110°C for 60 s, to stop uncompleted resist reactions and remove stress, followed by cooling at room temperature for 30 s and lastly the developer is sprayed for 60 s, immediately followed by washing the sample with deionized (DI) water, to stop the development process, and rotation to dry. An optical inspection, using an optical microscope, is carried out to ensure that the lithography process was correctly done, meaning the photoresist is in the desired areas, and to perform a defect inspection, i.e. pattern defects and particulate contamination.

Ion milling etch

Defined the spin valve shape, it needs to be sculped. Since the spin valve stack is composed by various materials, a chemical or reactive etch is not appropriate, as it would lead to an uneven etching rate. Contrarily, a physical dry etch, that ensures a constant etching rate by using the kinetic energy of ions to remove the atoms from the sample, independent of material deposited, is preferred. This process, named ion beam milling, is performed in the Nordiko 3000.

Figure 3.4: Schematic representation of the final photoresist pattern for all the combinations of mask and photoresist types.

42

Figure 3.5: Schematic representation of the Nordiko 3000 internal structure for ion milling etch and ion beam deposition [35] © Springer-Verlag Berlin Heidelberg 2013.

Inside the machine (figure 3.5), the plasma is generated in the assist gun, by inducing an electrical discharge, by DC, to ionize argon atoms. Together the argon ions, the released valence electrons and the argon atoms form the plasma, which is concentrated in the area by a set of magnets. After generating the plasma, the argon cations are accelerated towards a negative electrode, located below the sample. The collision of argon cations against the atoms in the sample causes their removal, thus areas not protected by the photoresist are removed by sputtering. The photoresist film is also etched, however this layer is significantly thicker (1.5 µm) than the spin valve stack (247 Å), therefore, when the stack is completely etched there is still photoresist layer protecting the stack bellow. Even though this is an anisotropic process, in order avoid trenching and redeposition, the etch is executed with the sample rotated 70° relative to its initial position. When patterning spin valves, the maximum angle is used to ensure good etching uniformity over the whole substrate. Although a precise etching rate is defined, an overetching is preferred to ensure a good etching over the whole structures of the sample. Overetching implies etching deeper than the thickness of the structure to etch, usually 50 Å more. In this case, as the stack is 247 Å thick, an etch of 280 Å was executed. The etching parameters are presented in table 3.1. To ensure the etching process is successfully complete, a multimeter is used to measure the conductivity in the etched areas (if it presents some conductivity, the etch is not completed), an optical inspection is performed.

Table 3.1: Read Nordiko 3000 etching process parameters. Parameters Read values Etch rate (Å s-1) 1 Sub rotation (rpm) 30 RF Power (W) 53 Grid 1 Voltage (V) 488.3 Grid 2 Voltage (V) 194.5 Gas Flow (sccm) 7.9 I1 (mA) 29.7 I2 (mA) 1.7

43

Spin valve stack 40 µm

Figure 3.6: Optical microscope photograph after resist strip.

Resist strip

Concluded the etching, the photoresist used to protect the sample’s features has to be removed. For that, the sample is immersed in Fujifilm® Microstrip 3001, a positive photoresist stripper, and placed in hot bath, at 65°C, with ultrasounds. Removed the resist, the sample is rinsed with isopropyl alcohol (IPA) and DI water. To assure all the photoresist was properly removed, the sample is inspected with an optical microscope (figure 3.6).

3.1.3 Current lines and contact pads definition

2nd Lithography

To define the current lines and pads, a second photolithography process is performed. In this step a non-inverted mask is used (figure 3.7), so that after development the photoresist remains everywhere except inside the features, where it forms cavities for the metal deposition, in the following step. However, as the metal layer to deposit is significantly thick (3150 Å), a pre-development step is performed, to facilitate the lift-off process. Pre-develop consists in developing the photoresist coated sample, in the SVG development track (figure 3.2), for 20 s prior to the exposure, hardening the top of the photoresist layer and thus facilitating the separation of this layer from the substrate during the lift- off process. For this reason, 90 % of the laser energy is used. An optical inspection, using an optical microscope, is carried out to ensure that the lithography process was correctly done and to perform a defect inspection, i.e. pattern defects and particulate contamination.

44 a) 37 µm b) 12 µm

370 µm 1440 µm

Metallic current 150 µm lines c) 250 µm 150 µm

800 µm

Metallic contact pads

Figure 3.7: CAD mask used to define the current lines and contact pads for a) die A, b) die B and c) die C, where the blue arrows indicate the easy axis direction.

Metallization

Defined the current lines and pads, the next step is the deposition of a metal layer, aluminum, to create low resistivity contacts that connect the spin valve series and the pads. For this process, Nordiko 7000 system was used, located inside the cleanroom. The sample is placed in a wafer and introduced in the loadlock chamber, where a robotic arm transports the wafer to the dealer chamber and then delivers it to one of the four modules (figure 3.8): • Module 1: Flash annealing (not used in this case) • Module 2: Soft sputtering etch • Module 3: TiW deposition • Module 4: Al deposition

45

Figure 3.8: Schematic representation of the Nordiko 7000 internal structure [36].

The first step, prior to the deposition itself, consists in cleaning the substrate to ensure good adhesion of the metal film to the sample, and good ohmic contact between the metal and the previously patterned spin valves. This is achieved by a soft sputter etch (module 2) for 1 min, to remove traces of natural oxidation and small impurities from the sample. Completed the etching, the sample is moved to module 4 for the deposition of a 3000 Å (nominal) Al film, which is performed by DC magnetron sputtering. An Al98.5Si1.0Cu0.5 target serves as the anode while the substrate serves as the cathode of an argon plasma discharge. A magnet is placed behind the target, to confine the plasma next to it, thus increasing the ionization rate and the quantity of material removed from the target per second (and consequently increasing the deposition rate). The last step consists in the deposition of a 150 Å (nominal) TiW film. TiW is a hard and dense material used to protect the Al layer from physical and chemical damages. The module 3 works similar to module

4, with the exception of the target composition, Ti10W90. The metallization parameters are presented in table 3.2.

Lift-off

After metallization, the material deposited in undesired areas, meaning on top of the photoresist patterned by the lithography process, must be removed so that the metal remains only in the cavities for the contact areas. This is achieved by a lift-off process, in which the sample is immersed in Fujifilm® Microstrip 3001 and placed in a hot bath, at 65° C, with ultrasounds, similar to the resist strip process mentioned above. The microstrip dissolves the photoresist consequently removing the metal deposited over it.

Table 3.2: Read Nordiko 7000 metallization process parameters. Parameters Module 2 Module 4 Module 3 Power (W) 59 2000 500 Gas flow (sccm) 50.1 50 49.6 Pressure (mTorr) 4.4 3.1 2.9 Deposition rate (Å s-1) - 37.5 5.6

46

Spin valve stack Metallic current lines

Metallic contact pads

40 µm

Figure 3.9: Optical microscope photograph of die A after lift-off.

An optical microscope is used to confirm the success of the lift-off process (figure 3.9). If there is still metal in unwanted areas, another round of lift-off must be executed.

3.1.4 Passivation

3rd Lithography

In this lithography step an inverted mask is used (figure 3.10), so that the structures defined in the CAD mask remain protected by the photoresist after development. The structures consist in rectangles placed over the contact pads, which, after deposition of the passivation layer and lift-off, define cavities in those same places. In the end the whole sample is covered by the passivation layer, except over the pads (where the power will be injected). Once again, a pre-development step is executed to accelerate the lift-off process thus the same energy as in the previous lithography is used. An optical microscope is used to assess the success of the lithography process and to perform a defect inspection, i.e. pattern defects and particulate contamination.

Passivation layer deposition

Passivation involves the creation of an outer layer of shield material that is applied to reduce the environmental effects on the sensor and to ensure a good contact of the PDMS over the sensing area. This double layer consists in 2000 Å (nominal) of aluminum oxide (over the sensor) and 2000 Å (nominal) of silicon dioxide (over aluminum oxide), ensuring a high impedance between the environment and the sensitive components, and a flat surface for the nanopillars. Although alumina has better dielectric properties (better breakdown voltage and denser), the PDMS bonding surface must be made from a silicon alloy (silicon dioxide) so that an ozone cleaning process (plasma bonding) can be used to irreversibly bond to the PDMS cilia array.

47

370 µm Metallic contact pads

150 µm Figure 3.10: CAD mask used in the third lithography for die A.

Alumina deposition

The first passivation layer, aluminum oxide, is deposited in the Ultra High Vacuum (UHV) 2 setup. This consists in a RF magnetron sputtering system composed of only one chamber, containing the holder and a ceramic Al2O3 target above it. Since there is no loadlock, the chamber must be pressurized to atmospheric pressure and depressurized to UHV when placing and removing the sample. When the chamber reaches UHV, the RF gun generator is turned on, followed by the entrance of Argon in the chamber. The Argon atoms and valence electrons form the plasma, that is concentrated and kept in place by a set of magnets located on top of the target. After the plasma is generated, the positively charged Argon ions are accelerated towards the target, removing its atoms by momentum transfer. The removed atoms fall onto the sample.

Since the deposition rate in this machine can be more erratic, to ensure the desired Al2O3 thickness was deposited, a calibration sample, a piece of Si with two ink stripes, was inserted in the chamber alongside the sample. After deposition the ink was removed by acetone, and the thickness measured in the profilometer, presenting 1846 Å of alumina, which is bellow expected.

Silicon dioxide deposition

The second passivation layer, silicon dioxide, is deposited using the Alcatel SCM 650 RF magnetron sputtering system, which has a similar working method as UHV 2, that transfers the material from a ceramic SiO2 target to the substrate. This machine also has only one chamber, therefore it requires pressurization and depressurization when replacing the samples. The deposition parameters for both UHV 2 and Alcatel are presented in table 3.3.

Table 3.3: Read UHV 2 and Alcatel passivation layer deposition process parameters.

Parameters UHV 2 Alcatel Deposition rate (Å min-1) 12 25 Power (W) 200 140 Gas flow (sccm) 44.6 20 Pressure (mTorr) Sensor not working 2.6

48

Furnace Magnet

Vacuum turbo pump

Figure 3.11: Photograph of the annealing setup.

Lift-off

To release the passivation layer from the unwanted areas, the contact pads, a lift-off process is preformed, identical to the one in subsection 3.1.3 Lift-off. An optical microscope is used to confirm the success of the lift-off process.

3.1.5 Annealing

The annealing process is used to achieve the optimal properties of the sensors, through the application of temperature and magnetic field. It consists in heating the sample above the blocking temperature, at which the AFM layer becomes paramagnetic, followed by applying a magnetic field to define the new alignment direction for the samples’ magnetic moments, as it cools down. This process is performed in a setup (figure 3.11) composed of a furnace, a permanent magnet and vacuum pumps (rough and turbo). The sample is placed in the quartz tube and pulled into the furnace, where the temperature increases 6° C min-1 until it reaches 250° C. This temperature is chosen because it is above the MnIr blocking temperature [37]. After 30 min at 250° C, the sample is moved to the permanent magnet, where a magnetic field of 1 T is applied (in the easy axis direction) as the temperature naturally decreases to room temperature, defining the magnetic moments alignment direction.

3.1.6 Dicing

As all sensors are fabricated in the same substrate, they need to be cut into individual sensors to be further assembled in the Full Wheatstone bridge configuration. The cutting process, called dicing, is performed in the Disco DAD 321 automatic dicing system.

49

The sample is mounted on a metallic frame using a 150 µm thick photosensitive self-adhesive tape. The frame is placed in the machine where the die parameters, namely sample and dies size, tape thickness and blade height relative to the cutting table, and the operation parameters, meaning cutting speed and mode, must be defined. Usually, for silicon a speed cut of 20 mm s-1 ensures a smooth cut however, to ensure a good cutting quality 1 mm s-1 was used.

3.1.7 Hard mask design and fabrication

To fabricate the nanocomposite cilia arrays by soft lithography, the most common molds used are made from SU-8, which is patterned by UV contact lithography, requiring a hard mask with the desired pattern design. As transparency of the substrate is required for the hard mask, a glass substrate is used. This is properly cleaned by immersion in an Alconox solution in a 65° C water bath with ultrasounds, followed by rising with DI-water and drying with a N2 gun.

Metallization

The metallization step consists in the deposition of a 3000 Å (nominal) aluminum layer by Nordiko 7000. This metal layer covers the areas that are not meant to be exposed during SU-8 mold fabrication, as it is not penetrated by the UV rays used in contact lithography. Once the sample is introduced in the loadlock, the robotic harm moves it to the dealer chamber and then to module 4, as it is the one responsible for aluminum deposition. The deposition parameters are presented in table 3.4.

Lithography

Once the metal is deposited, a lithography step is required to define the areas where the photoresist will remain, and consequently the aluminum (after the following step), shaping the hard mask. The CAD mask design included 100 circular features arrays with diameter ranging from 150 µm to 16 µm, with different spacing between them (figure 3.12). The vast range of dimensions was chosen in order to study the limit of the features aspect ratio which was possible to peel from the SU-8 mold without damaging the features. Two different hard masks were fabricated, one with an inverted mask design, exposing the photoresist outside the features and thereby being removed after development, and a second one with a non- inverted mask design, so that the photoresist inside the features is exposed and consequently removed after development. The remaining photoresist serves as a shield to protect the covered areas from the following etch process.

Table 3.4: Read Nordiko 7000 process parameters for 3000 Å aluminum layer deposition. Parameters Power (kW) Gas flow (sccm) Pressure (mTorr) Deposition rate (Å s-1) Module 4 2 50.1 3 37.5

50

d = 150 d = 100 d = 100 d = 100 s = 100 s = 150 s = 100 s = 50 d = 70 d = 70 d = 65 d = 65 s = 70 s = 50 s = 70 s = 55 d = 50 d = 50 d = 45 d = 45 s = 70 s = 50 s = 50 s = 35

d = 20 d = 20 d = 20 d = 16 d s s = 30 s = 20 s = 10 s =7 * All in µm

Figure 3.12: Hard mask design, dimensions of the cilia array in the left. On the middle is shown the CAD mask design used to fabricate the hard mask, each array containing 100 cilia, and on the right is specified d and s as cilium diameter and spacing between cilia, respectively.

These two different hard masks create different SU-8 mold designs, for the first (inverted) the SU-8 forms cavities with the desired cilia dimensions and the second one (non-inverted) the SU-8 forms the desired ciliary structures. This is meant to study which configuration best allows the peeling of the structures from the mold without damaging them. Completed the lithography process, an optical microscope is used to verify its success and to perform a defect inspection, i.e. pattern defects and particulate contamination.

Wet etch

To remove the aluminum from undesired areas, a wet etch process is used. Wet etching takes advantage of the corrosive properties of some substances, usually acids, which do not react with the photoresist, as this is resistant to inorganic acids. The used chemical strongly depends on the material of the layer to be etched (chemically selective), in this case it is selective to aluminum, with an etching rate of 6 Å s-1. This is an aggressive and highly isotropic process. An optical microscope (figure 3.13) and a profilometer are used to ensure the etching process is complete.

Holes with desired cilia dimensions

Al

100 µm

Figure 3.13: Optical microscope photograph of hard mask (non-inverted) after wet etch.

51

a) b)

2 mm 2 mm

Figure 3.14: Hard masks a) from the inverted mask design and b) from the non-inverted mask design.

Resist Strip

After the etching is concluded, the photoresist that is protecting the substrate must be removed. For that, the same step as in 3.1.2 Resist Strip is used. Completed the hard masks fabrication process, they have the appearance shown in figure 3.14.

3.1.8 SU-8 mold fabrication

The first step in SU-8 mold fabrication is to clean the Si substrate, similar to the process used for the glass substrate in 3.1.7, with the addition of a 15 min final cleaning step performed in the UV Ozone (UVO) cleaner. The fabrication of the SU-8 molds takes place inside a laminar flow hood, to avoid major particle contamination. The photoresist used is SU-8 50 from MicroChem® as it is the only one available at INESC-MN that can reach film thicknesses of 50 µm, 100 µm and 150 µm. These three thicknesses are chosen to study how the aspect ratio of the cilia affects the output of the sensor, as the thickness of the SU-8 mold dictates the height of the cilia. Before photoresist coating, a dehydration bake at 100° C for 10 minutes must be done in order to remove all moisture on the surface and increase the adhesion of the photoresist to the substrate. The sample is left to cool to ambient temperature before the next step.

Spin coat

The spin coater is used to deposit a uniform layer of SU-8 photoresist. The rotation speed, the acceleration and the photoresist viscosity define the thickness of the SU-8 layer, and consequently the cilia height. Two spin cycles are executed, the first one at 500 rpm for 10 s with 100 rpm s-1, to spread the photoresist over the substrate, and the second one, table 3.5, to control the layer thickness. The parameters of the second cycle differ with the desired SU-8 thickness, spin speed curves are available for each SU-8 resist from the manufacturer. The coated substrate is placed on a leveled surface for 15 min to allow the SU-8 to level out.

52

Soft bake

The soft bake aims to evaporate the solvent to solidify the film, preparing it for the next step. The evaporation may slightly change the SU-8 thickness. The sample is pre-baked at 65° C, left on top of the heat plate until it reaches 95° C, and soft baked at 95° C (table 3.5), followed by letting it cool at room temperature. This temperature ramps must be followed to decrease the mechanical stress inside the SU-8 layer.

Exposure

The exposure process uses UV light to transfer a pattern to the substrate, by initiating the cross linkage, through the activation of the photoactive component, in some parts of the photoresist. This activation changes the local properties of the resin which, after the next step, becomes soluble, or not to a liquid developer. The hard mask is placed in contact with the substrate, with the aluminum layer facing the SU-8 to avoid spreading of the light and consequently a poor feature definition. Both are fixed in the holder and exposed to intense UV light (slot 1 with 11,4 mW.Cm-2), table 3.5. Since SU-8 is a negative photoresist, the exposed area becomes hard and the unexposed area will dissolve during the development step.

Post exposure bake

As mentioned above, the UV exposure enables the activation of the photoactive components in the SU- 8, however it requires energy to continue the reaction. This energy is provided by a baking step. The heating pattern is similar to the soft bake, a first plateau at 65° C and a second plateau at 95° C (table 3.5), followed by cooling the sample at room temperature.

Develop

The development step is where the non-linked (unexposed) SU-8 is diluted in the liquid developer. The mold is immersed in propylene glycol monomethyl ether acetate (PGMEA) from Sigma-Aldric® (table 3.5), rinsed with IPA and carefully dried. After this step, the SU-8 mold is finished and it is inspected at the optical microscope and at the profilometer to verify feature definition and thickness, respectively (figure 3.15).

Table 3.5: SU-8 mold fabrication conditions for thicknesses of 50 µm, 100 µm and 150 µm.

Soft Soft Exposition PEB 65 PEB 95 Thickness Time Acceleration Development Rpm bake 65 bake 95 time 1st slot °C °C (µm) (s) (rpm/sec) (min) °C (min) °C (min) (s) (min) (min) 50 1202 30 300 5.9 19 30 1 5 6.3 100 929 30 300 10 30 45 1 10 10 150 400 40 100 14.1 42 52 1 15 15.7

53

a) b)

2 mm 2 mm

Figure 3.15: SU-8 molds after development. a) using an inverted mask design, obtaining an SU-8 mold with cavities having the same dimensions as desired cilia. b) using a non-inverted mask design, resulting in SU-8 mold with ciliary structures, having the same dimensions as desired cilia.

3.1.9 Nanocomposite casting and peeling

Two different methods are developed to fabricate the cilia. One using the SU-8 mold with ciliary structures on it (non-inverted mask design), by making a negative copy of it using PDMS, where the nanocomposite is casted. And another where the SU-8 mold with cavities (inverted mask design) is used to directly cast the cilia nanocomposite (figure 3.16).

1.5 µm Photoresist

Inverted Non inverted mask design Lithography mask design

3000 Å Al

Hard mask Hard mask Glass

SU-8 Si

SU-8 mold with cavities SU-8 mold with the with the desired cilia desired cilia structures dimensions

PDMS

Nanocomposite 30 µm PDMS 1.7 µm PVA Cilia

Cilia Glass Figure 3.16: Schematic representation of the cilia array fabrication.

54

Nanocomposite preparation

The nanocomposite consists in magnetic particles embedded in PDMS. The PDMS is prepared by mixing Sylgard 184 silicone elastomer base and Sylgard 184 silicone elastomer curing agent by Dow Corning (Midland, MI) with a 1:15 weight ratio (curing agent to elastomer base). The magnetic particles are composed of a neodymium boron cobalt iron alloy, having a diameter of 5 µm (from Magnequench). These are embedded in the PDMS with a 1:5 weight ratio of PDMS to magnetic particles. A PDMS with a 1:10 weight ratio (curing agent to elastomer base) is also prepared to be used as a PDMS mold (a negative copy of the SU-8 mold) and as a thin membrane supporting the cilia array. Both are placed in the desiccator for 1 h to remove the air bubbles formed upon mixing, otherwise they would be trapped inside the PDMS.

PVA preparation and coating

The cilia must be fabricated on top of a substrate from which they can be easily peeled, without damage, and placed on top of the magnetoresistive sensor. Poly (vinyl alcohol) (PVA), a water-soluble polymer, is sandwiched between a glass substrate and a thin PDMS layer containing the cilia so that when cilia fabrication is complete, it is immersed in water, dissolving the PVA and freeing the PDMS/cilia layer. For that, a glass substrate is cleaned as mentioned in 3.1.7, spin coated with a PVA solution, obtaining a 1700 nm (nominal) thick layer, and baked at 70°C for 5 min. This solution must be previously prepared by mixing a 5:1 weight ratio of Mowiol 40-88 (from Aldrich®) to hot water, with a magnetic stirrer, and kept at 40°C, overnight. The PVA substrate is placed in the UVO cleaner to increase the adhesion of the PDMS. A PDMS (1:10) layer of 30 µm (nominal) is then spun on top of the PVA layer to further provide electrical isolation and, at the same time, enhance adhesion of the cilia to the GMR sensor.

Cilia fabrication

As mentioned before, two methods are used to fabricate the cilia. In the first one the PDMS (1:10) is poured into the SU-8 mold (non-inverted mask design) and baked at 70° C for 1 h. After which, the PDMS counter mold is peeled from the SU-8 mold and subjected to a 50 min HMDS silanization step, to decrease the PDMS-PDMS adhesion. Then, the nanocomposite (1:15) is poured onto the PDMS mold and pressed against the PDMS coated onto the PVA. In the second one, the SU-8 mold (inverted mask design) is subjected to a 50 min HMDS silanization step, to decrease the SU-8-PDMS adhesion. Followed by pouring the nanocomposite into the mold and pressing it against the PDMS/PVA/glass substrate. Both are placed in the oven to bake at 70° C for 1 h, followed by peeling off the cilia features and PDMS thin layer from the molds. The samples are then immersed in DI-water and placed in a 65°C water bath with ultrasounds, until the PVA Is dissolved, freeing the structures (figure 3.17). This way is easier to transfer the cilia structures to the sensor, without suffering any damage.

55

a) b) PDMS

Nanocomposite

150 µm 300 µm

Figure 3.17: Optical microscope photograph of the cilia array a) 100 cilia array with 100 µm diameter and 100 µm of spacing between cilia b) cilia array with 100 µm diameter and 150 µm of spacing between cilia, confirming the cilia top circular shape.

3.1.10 Annealing

After releasing the cured structures from the mold, the cilia are placed in the annealing setup (figure 3.11) to align the magnetic moment of the magnetic particles in the direction of the cilium symmetry axis. The same setup as in 3.1.5 is used, with different conditions. The sample is initially placed in the furnace, where the temperature increases 6° C min-1 until it reaches 100° C. After 1 h at 100° C, the sample is moved to the permanent magnet, where a magnetic field of 1 T is applied as the temperature naturally decreases to room temperature, defining a new alignment direction for the magnetic particles’ magnetic moments.

3.1.11 Device assembly

To achieve a Full Wheatstone Bridge configuration, the four individual sensors are assembled in a chip carrier, two pairs of spin valve arrays are required, having opposite ∆R/∆H. Meaning the reference layer of the two sensor types must be directed along the same direction but in opposite senses. The advantages of using a Full Wheatstone Bridge configuration are expressed in subsection 2.1.5 Full Wheatstone Bridge configuration. This simple solution has two major drawbacks: the mechanical assembly of individual components will always introduce alignment errors, which will limit the performance of the device and the mechanical assembly of individual elements is not cost-effective for mass-production [30]. In this case, each die is glued onto two 24-pin and one 28-pin chip carriers, resulting in three devices like the one presented in figure 3.18 b.

Plasma bonding

This process consists in making a plasma bonding between the PDMS and the sensor dies, using the Harrick Plasma PDC-002-CE. The plasma is created by the generation of a RF oscillating electric

56

Magnetic sensor Cilia array

a) b)

- + V Chip carrier I

+ V - I

Figure 3.18: Device wirebonding, a) wiring scheme for the 24-pin chip carrier, the same is used for the 28-pin chip carrier, with exception of the pin numbers. In this case the current source is connected to pin 5 (I+) and 17 (I-) and the voltage drop is measured between pin 6 (V+) and 19 (V-). The green arrows indicate the easy axis direction. b) Photograph of the assembled and wirebonded Full Wheatstone Bridge sensor with a cilia array on top, in a chip carrier. field through magnetic induction, which, at low pressure, partially ionizes the oxygen gas. This plasma creates Si-OH functional groups on the PDMS and sensor surface so that when they are pressed against each other strong and permanent Si-O-Si bonds are formed, effectively bonding the PDMS to the sensor.

3.2 Characterization methods and equipments

3.2.1 Magnetotransport curve

The magnetotransport characterization describes how the spin valves electrical resistance changes with the variation of an externally applied magnetic field. The magnetotransport setup (figure 3.19) used is composed of a pair of Helmholtz coils, that apply a magnetic field from -140 Oe to 140 Oe, a current source, a voltmeter and micropositioners (used to measure the magnetotransport curve of individual spin valves and dies). The sample is placed between the coils, which supply current to the sensor, measuring the voltage difference. The setup is connected to a computer that automatically sweeps the induced current in the coils and thus the induced magnetic field, and measures the voltage drop in the sample for each induced field step, instantly presenting the magnetotransport curve.

57

Current Source Voltmeter

Data acquisition PC

Micropositioner

Helmholtz Coils Figure 3.19: Photograph of the Magnetotransport setup.

3.2.2 Profilometer

As mentioned throughout section 3.1 a profilometer, Tencor Alpha Step 200, is used in several metrology steps to measure step heights, etch depths and coating thicknesses. It’s working principle consists in moving a diamond-tipped stylus in contact with the sample, with a small load. The stylus suffers vertical displacements proportional to the topography of the sample, if an unevenness is detected over the sample, it is translated to an electrical signal. Its minimum vertical sensitivity is of 20 Å to 50 Å.

58

4 Results and discussion

4.1 Artificial cilia arrays

4.1.1 Optimization

As the SU-8 molds are patterned by UV contact lithography, the only parameter that can be modified is the exposure time. The SU-8 was firstly exposed during the time recommended by the SU-8 manufacturer however, the structures formed presented poor definition, meaning they exhibited a conic shape instead of cylindric (figure 4.1 a-c). Due to this, an optimization of the UV exposure time, that allowed the best feature definition, for each SU-8 thickness was performed. The optimization was achieved by varying the exposure time from 20 s earlier than the time recommended by the SU-8 manufacturer until the recommended time. The exposure time was only reduced due to the fact that SU-8 is a negative photoresist, meaning the exposed area remains after development, therefore, as there was SU-8 inside the features (that were covered by the hard mask) it means that it was overexposed and not underexposed. The optimal exposure time for the SU-8 with thickness of 50 µm was 30 s, for 100 µm was 45 s and for 150 µm was 52 s (figure 4.1 d-f).

a) b) c)

150 µm 150 µm 150 µm

d) e) f)

Si SU-8

150 µm 150 µm 150 µm

Figure 4.1: Optical microscope photograph of four cilia cavities in SU-8 molds exposed to (a-c) time recommended by the manufacturer and (d-f) optimized exposure time. a) 50 µm thick SU-8 exposed for 33 s. b) 100 µm SU-8 exposed for 51 s. c) 150 µm SU-8 exposed for 70 s. d) 50 µm SU-8 exposed for 30 s. e) 100 µm SU-8 exposed for 45 s. f) 150 µm SU-8 exposed for 52 s.

59

a) b) Si

SU-8

50 µm 50 µm

Figure 4.2: Optical microscope photograph of cilia arrays a) 50 µm thick SU-8 with 16 µm diameter cilia spaced by 7 µm and b) 100 µm thick SU-8 with 20 µm diameter cilia spaced by 30 µm.

As the hard mask consisted in arrays with cilia presenting such a variety of dimensions, it was challenging to achieve an exposure time that allowed the same good feature definition to all the arrays’ dimensions. From figure 4.2 it can be seen that cilia arrays with smaller dimensions were poorly defined, being more affected by proximity effects. Based on this, a decision was made to use only the three major cilia arrays (diameter, spacing between them (in µm): 150,100; 100,150 and 100,100) as they presented the best definition. The SU-8 thickness achieved was always below expected, for 50 µm, 100 µm and 150 µm presented 44.6 ± 3 µm, 85.4 ± 5 µm and 128.6± 8 µm respectively. It can be due to the type of SU-8 used (SU- 8 50), which is recommended by the manufacturer to be used up to a maximum thickness of 120 µm. For a SU-8 thickness of 150 µm it would be more appropriate to use SU-8 100. Due to the difficulties inherent to the cilia fabrication and considering that the output signal emitted from smaller cilia is more affected by noise than higher cilia, it was decided to proceed only with the fabrication of the 150 µm height cilia.

Nanocomposite a) b) c)

Si

Nanocomposite SU-8

2 mm 100 µm 100 µm

PDMS

Figure 4.3: a) Photograph of the PDMS mold with nanocomposite inside after baking, being impossible to separate the ciliary array from the mold. b) and c) optical microscope image of the nanocomposite that remained inside the SU-8 mold (darker cilia in the image), after cilia peeling. b) cilia array with 100 µm diameter and 150 µm between cilia. c) The smaller the cilia array dimensions, the higher number of cilia stuck in the mold.

60

Summing, three different 150 µm height cilia arrays were fabricated, one with 150 µm diameter and the other two with 100 µm diameter, having a distance between cilia of 100 µm, 150 µm and 100 µm (nominal), respectively.

4.1.2 Cilia detachment

As mentioned in the fabrication methods on chapter 3, two methods were developed for cilia arrays fabrication. Both consisted in the use of SU-8 molds: one was patterned with the desired cilia shape and used to cast a PDMS inverted copy, that was in turn used to cast the nanocomposite and consequently fabricate the cilia, while the other SU-8 mold was patterned with cavities having the desired cilia shape, used to directly cast the nanocomposite (figure 3.16).

a) b)

c) d)

Parallel

Perpendicular

Nanocomposite

PDMS

Figure 4.4: Nanocomposite magnetization curves obtained with a VSM for the a) cilia array with 150 µm diameter and 100 µm spacing between cilium. b) cilia array with 100 µm diameter and 150 µm spacing between cilium and c) cilia array with 100 µm diameter and 100 µm spacing between cilium. Legend: in blue measurements made parallel to the cilium symmetry axis and red made perpendicularly. d) The measurements were taken in the vertical (parallel) and horizontal (perpendicular) direction of the cilia array.

61

The first method used to fabricate the cilia, the SU-8 mold with ciliary structures, was not successful because when the nanocomposite was casted in the PDMS mold and baked, bonds formed between the PDMS present in the nanocomposite and the one from the mold, which made it impossible to peel the cilia array from the PDMS mold (figure 4.3 a). Contrarily, when using the second method, the SU-8 mold with cavities, the nanocomposite was easily peeled except for a few cilia that got stuck inside it (figure 4.3 b and c). This is the major disadvantage because if the nanocomposite gets stuck inside the mold then it cannot be reused, meaning for each cilia array fabrication, a new SU-8 mold must be manufactured.

4.2 Nanocomposite characterization

To study the magnetic properties of the nanocomposite cilia and assess their permanent magnetic behavior, the magnetization curves along the cilia and in the perpendicular direction of each cilia array were obtained using the vibrating sample magnetometer (VSM) (figure 4.4). The results show that the applied magnetic field was not enough to saturate the magnetic moment of the nanocomposite nonetheless, at zero applied magnetic field the cilia present magnetic moment, confirming the permanent magnetic behavior of the nanocomposite.

4.3 Magnetic sensor characterization

4.3.1 Optimization

Prior to device fabrication, individual spin valves with different dimensions were fabricated (using the same stack) to ascertain which aspect ratio best suited the purpose of this work. The decision was made based on the magnetotransport curves of each aspect ratio, being desired a spin valve presenting a linear, hysteresis free curve, with good sensitivity. Figure 4.5 shows the three best magnetotransport curves obtained for aspect ratios of 2 x 40 µm2, 3 x 40 µm2 and 3.5 x 40 µm2. It was decided to proceed with the fabrication of the 3 x 40 µm2 spin valves because they presented the best compromise between coercivity and sensitivity, meaning lower coercivity and higher sensitivity.

62

a) b)

)

) 40 µm Ω Ω 40 µm

MR = 6.9 % 3 µm MR = 6.9 % Resistance( Resistance( 2 µm H = 2.4 Oe H = 1 Oe C C -1 -1 S = 0.1 % Oe S = 0.1 % Oe

Magnetic Field (Oe) Magnetic Field (Oe)

c)

) 40 µm Ω

MR = 5.7 % H = 2.9 Oe 3.5 µm C Resistance( -1 S = 0.1 % Oe

Magnetic Field (Oe)

Figure 4.5: Magnetoransport curve of individual spin valves with aspect ratio of a) 2 x 40 µm2, b) 3 x 40 µm2 and c) 3.5 x 40 µm2. The spin valves were supplied with a 1 mA DC current.

4.3.2 Magnetic sensor

The magnetic sensors developed in this thesis, according to the fabrication methods described in chapter 3, consisted in three different layout designs, varying the spin valve distribution (figure 4.6). Each GMR sensor type consists in arrays of spin valves connected in series and in parallel, being the array resistance the sum of each individual spin valve resistance. This improves not only the sensor sensitivity, as the magnetic signal common to all spin valves accumulates, but also the signal-to-noise ratio, as the localized noise over one spin valve is negligible over the sum of all spin valves. The sensor behavior is characterized by its transfer curve, which represents directly the output resistance dependence on field signal. The magnetotransport curves obtained for each sensor type are presented in figure 4.7 a-c. The expected difference between the magnetotransport curves of each die is the magnitude of the measured sensor resistance, as the quantity of spin valves varies for each die

63

a) b) c)

150 µm

250 µm 150 µm

Figure 4.6: CAD software mask of the three different layout designs: a) die A with 1 x 0.5 mm2 , b) die B, having 2 x 2 mm2 and c) die C for Full Wheatstone Bridge sensor, each one with 1.5 x 1.5 mm2, forming an active area of 3 mm2. Color legend: spin valves in red, metallic current lines in blue and contact pads in green.

Table 4.1: Fabricated GMR sensors parameters.

GMR sensor Spin valves in Spin valves in Array sensitivity Coercivity type series parallel (% Oe-1) (Oe) A 25 5 0.9 1.3 B 100 10 0.9 0.9 C 35 12 0.7 0.4 type. These sensors present a linear and hysteresis free curve, with two stable resistance plateaus. One key feature of a magnetic sensor response is its field sensitivity, which represents how reactive a sensor is to a field variation, being measured experimentally from the slope of the transfer curve. Commonly the sensitivity is presented normalized as in equation (6) [23]. The sensitivity and spin valve array size for each sensor type are presented in table 4.1.

1 퐷푅 푀푅 푆 = ( ) = (6) 푅푚푖푛 퐷퐻 푙𝑖푛푒푎푟 (퐷퐻)푙푖푛푒푎푟

Figure 4.7 a-c and table 4.2 show that the die presenting the best compromise between sensitivity and coercivity (meaning high sensitivity and low coercivity) is die C. For this reason, it was chosen to proceed only with the development of the Full Wheatstone Bridge configuration sensors, as they present several advantages compared to the other designs, such as the nullification of temperature drifts (which is important when dealing with fruit, as it can be subjected to different temperatures from cold storage rooms to ambient temperature, and this way the results are not affected); reduces the noise; it originates a bipolar output, ideally centered in zero (which transforms an output of only positive values into an output with a range of positive and negative values, simplifying its future integration with other electronic components) and it can either be feed by a current source or a voltage source, also simplifying its future electronic integration.

64

After the assembly of the dies on the chip carrier, ensuring a Full Wheatstone Bridge configuration, one of the devices was wirebonded, prior to the cilia array insertion over the sensor, to measure the Full Bridge response to a varying external magnetic field (figure 4.7 d). The results show that the Full Bridge has a voltage offset of 8 mV at zero applied magnetic field, corresponding to 21.6 % of the output voltage range. This is due to a bridge imbalance, caused by small resistance differences in between the four sensors.

a) b)

MR = 7 % H = 0.9 Oe C -1 S = 0.9 % Oe

MR = 7.3 % H = 1.3 Oe C -1 S = 0.9 % Oe

c) d)

MR = 6 % H = 0.4 Oe C -1 S = 0.7 % Oe

Figure 4.7: a-c) Magnetotransport curve of the three GMR sensor design layouts, with an external field applied in the sensitive direction and a DC current input of 1 mA. a) die A, b) die B and c) die C. Insets: Close-up from - 10 Oe to 10 Oe, showing the sensors coercivity. d) Voltage output response of a Full Wheatstone Bridge sensor to an applied magnetic field, without artificial ciliary structures on top of the sensor, feed by a DC current input of 1 mA. The voltage drop between the two arms of the bridge (between pin 6 and 19 for the 24-pin chip carriers; pin 7 and 22 for the 28-pin chip-carrier) shows a voltage offset of 8 mA at zero applied magnetic field.

65

4.4 Surface texture detection

Posterior to the bonding of the artificial cilia arrays to the Full Wheatstone Bridge sensors, the response of the sensors to the cilia deflection was measured. For that, the GMR sensor was supplied with a 1 mA DC current and the voltage drop between the bridge output terminals was measured, as the cilia were deflected with tweezers in different directions (from right to left, from left to right and from back to front, returning to back). Figure 4.8 shows the sensors voltage output, each with a different cilia array on top.

a) b)

c) d)

Fruit Nanocomposite PDMS Wirebond

Magnetic sensor

Chip carrier Sensitive direction

Figure 4.8: Full Wheatstone Bridge sensor response to cilia deflection, for each cilia array a) cilia with 100 µm diameter and spacing between cilia of 100 µm, b) 100 µm diameter and 150 µm spacing and c) 150 µm diameter and 100 µm spacing (all dimensions nominal). d) Schematic representation of how the fruit skin roughness was measured, the fruit is swept parallel to the sensor sensitive direction.

66

The results show that, regardless of the cilia array dimensions placed on top of the sensor, it is able to distinguish between a leftward and a rightward movement (parallel to the sensitive direction), however for forward and backward movements (perpendicular to the sensitive direction) the sensor detects the cilia deflection but cannot distinguish the direction. This agrees with what was expected, as the sensor only has one sensitive direction. To be able to sense in both directions, the sensor would have to be modified, in order to have both easy axis directions in the same substrate. From figure 4.8 a-c it can be seen that, in some cases, the baseline voltage is different in the beginning and in the end of the experiment. This is due to a collapse of some cilia or even to the detachment of the cilia array from the sensor, which is caused by misalignments in the four sensors forming the Full Wheatstone Bridge (when gluing them to the chip carrier) that originated an irregular surface leading to a less effective plasma bonding of the cilia array to the sensor. The results also show that, as expected (figure 2.1) when the cilia are bent in a direction that originates an increase in output voltage (figure 4.8 a red signal and b-c blue signal), it means that the sensor resistance increased due to an antiparallel alignment of the spin valves’ free layer relative to the pinned layer. The free layer is in turn aligned in the opposite sense of the cilia magnetization. On the contrary, when cilia deformation originates a decrease in output voltage (figure 4.8 a blue signal and b-c red signal), free and pinned layer are parallel aligned. Finally, a test was performed to assess the capacity of the sensor to detect fruit skin texture, meaning the ability to detect the variation of fruit skin roughness. Only one of the devices was used for this test, namely the one with 150 µm diameter (nominal) cilia, as the other devices were damaged during the experiment. The measurements were obtained by holding the fruit with tweezers and passing it over the sensor, parallel to the sensitive direction, as represented in figure 4.8 d. Two different types of fruit were measured: strawberries, as they are the main focus of this work, and blueberries, because its peel texture varies greatly with ripening. For each fruit type, three samples in different ripeness stage were measured four times, one green, other ripe and the last one overripe. The results are depicted in figure 4.9. From figure 4.9 a and b, it can be seen that the sensor is in fact capable of differentiating fruits with smoother skin from rougher ones, as the red signal (green fruit) has fewer variations than the others. However, the signals obtained for ripe (blue) and overripe (green) fruits are similar, making it difficult to differentiate these two stages. To differentiate ripe from overripe fruits it is necessary to increase device sensitivity, which is achieved by increasing the cilia array and optimizing their dimensions to the application. Figure 4.9 c and d show the maximum signal amplitude for each measurement performed. For blueberries the signal amplitude appears to be proportional to the ripeness stage. The same proportionality is not so clear for strawberries. This is due to the fact that overripe blueberries are more wrinkled than strawberries, which causes a more accentuated cilia deflection resulting in a larger signal. A limitation of this experiment is that it required an operator to hold the fruit and pass it over the sensor therefore, any tremor or even subtle movement (other than moving the fruit) performed by him is detected by the sensor. This may be the reason why all signals present noise interferences and may also justify the large variations in signal amplitudes obtained for the same fruit (figure 4.9 c and d). One

67 way to solve this is by immobilizing both the device and the fruits in two moving stages, so that the passage of the fruit over the sensor is made by the movement of the stages (always separated by the same distance), removing the operator interferences. Summing, the sensor was able to distinguish the evaluated fruits texture, presenting a relation between fruit skin texture and maximum signal amplitude. It would be interesting to further improve the device, as mentioned throughout this chapter, to confirm its potential.

a) b)

c) 1 d) 1,4 0,9 1,2 0,8 0,7 1 0,6 0,8 0,5 0,4 0,6 0,3 0,4

Signal Amplitude (mV) Amplitude Signal 0,2 Signal Amplitude(mV) Signal 0,2 0,1 0 0 1 2 3 1 2 3

Figure 4.9: Skin roughness measurements of three fruits in different ripeness states, using the texture sensor for a) blueberries and b) strawberries. c) and d) show the amplitude of the four measured signals for each maturation state, indicated by the fruit image bellow (from left to right: green, ripe and overripe).

68

5 Conclusion

The goal of this thesis was to develop a multiparametric biosensor for strawberry fruit quality control, capable of detecting fruit skin texture and the presence and concentration of ethylene emanated from the fruit, concluding about its ripeness state. The design of the device consisted in a biomimetic approach, inspired in the ciliary structures found in nature, resulting in highly elastic and permanent magnetic artificial cilia arrays, coated with a gas sensing layer, inserted on top of a GMR sensor, which detects signal variations caused by the change in magnetic stray field of the cilia upon deflection and gas binding. Due to time constrains the gas sensor was not developed. The decision of using GMR sensors was made based on their ability to detect very weak magnetic fields (down to nT) at room temperature [27], ensuring the detection of the weak magnetic field emitted by the cilia array. Also, it is an important improvement for the gas sensor, as the currently more used ones (based on metal oxide semiconductors sensors) operate at high temperatures. Cilia fabrication using SU-8 molds is a low-cost technic, however it must be optimized for each cilia array dimensions, to ensure good feature definition and consequently well-defined ciliary structures. Three devices were fabricated, with the sensors in a Full Wheatstone Bridge configuration, varying the cilia array dimensions (150 µm height with different diameter, spacing between them (in µm): 150,100; 100,150 and 100,100) inserted over the GMR sensor. The sensor characterization results show that they present the desired linear behavior, required for magnetic sensing, and a voltage offset of 8 mV, meaning that the bridge is not well balanced, due to some resistance variations of the four sensors composing the bridge. From the texture sensor, the results confirm its capacity for fruit skin roughness detection, presenting a relation between fruit skin texture and maximum signal amplitude. Further improvements for the texture sensor include improving the sensor architecture, by increasing the cilia array dimensions, number of cilia and size of sensing area, as they were very small for the desired application. Fixing the sensor and fruit in moving stages, to remove the operator interference on the results. Integration of the gas sensing layer on the ciliary structures, to enable ethylene detection, accomplishing the magnetic gas sensor. And lastly the insertion of the multiparametric biosensor in a robot fingertip, so that it could perform the fruit quality analysis, automating the process.

69

Bibliography

[1] M. C. N. Nunes, J. P. Emond, M. Rauth, S. Dea, and K. V. Chau, “Environmental conditions encountered during typical consumer retail display affect fruit and vegetable quality and waste,” Postharvest Biol. Technol., vol. 51, pp. 232–241, 2009. [2] Z. Hussein, O. A. Fawole, and U. L. Opara, “Harvest and Postharvest Factors Affecting Bruise Damage of Fresh Fruits,” Hortic. Plant J., pp. 1–28, 2019. [3] B. Zhang et al., “Principles , developments and applications of computer vision for external quality inspection of fruits and vegetables : A review,” Food Reasearch Int., vol. 62, pp. 326– 343, 2014. [4] B. M. Nicola et al., “Nondestructive Measurement of Fruit and Vegetable Quality,” Annu. Rev. Food Sci. Technol., pp. 285–312, 2014. [5] P. Ribeiro et al., “Bioinspired Ciliary Force Sensor for Robotic Platforms,” IEEE Robot. Autom. Lett., vol. 2, no. 2, pp. 971–976, 2017. [6] A. Alfadhel, M. A. Khan, S. Cardoso De Freitas, and J. Kosel, “Magnetic tactile sensor for Braille Reading,” IEEE Sens. J., vol. 16, pp. 8700–8705, 2016. [7] L. Chen and U. L. Opara, “Approaches to analysis and modeling texture in fresh and processed foods - A review,” J. Food Eng., vol. 119, no. 3, pp. 497–507, 2013. [8] A. Deving and F. Måge, “Methods of testing strawberry fruit firmness,” Acta Agric. Scand. Sect. B Soil Plant Sci., vol. 52, pp. 43–51, 2002. [9] F. J. García-Ramos, C. Valero, I. Homer, J. Ortiz-Cañavate, and M. Ruiz-Altisent, “Non- destructive fruit firmness sensors: a review,” Spanish J. Agric. Res., vol. 3, no. 1, p. 61, 2005. [10] A. S. Szczesniak, “Texture is a sensory property,” Food Qual. Prefer., vol. 13, no. 4, pp. 215– 225, 2002. [11] A. D. Wilson and M. Baietto, “Applications and Advances in Electronic-Nose Technologies,” Sensors, vol. 9, pp. 5099–5148, 2009. [12] S. W. Chiu and K. T. Tang, “Towards a chemiresistive sensor-integrated electronic nose: A review,” Sensors, vol. 13, pp. 14214–14247, 2013. [13] A. Berna, “Metal Oxide Sensors for Electronic Noses and Teir Applications to Food Analysis,” Sensors, vol. 10, pp. 3882–3910, 2010. [14] P. U. Kurup, “An electronic nose for detecting hazardous chemicals and explosives,” 2008 IEEE Int. Conf. Technol. Homel. Secur. HST’08, no. 978, pp. 144–149, 2008. [15] E. R. Thaler and W. Hanson, “Medical applications of electronic nose technology,” Expert Rev Med Devices, pp. 559–566, 2005. [16] K. Arshak, E. Moore, G. M. Lyons, J. Harris, and S. Clifford, “A review of gas sensors employed in electronic nose applications,” Sens. Rev., vol. 24, pp. 181–198, 2004. [17] R. Ciprian et al., “New strategy for magnetic gas sensing,” RSC Adv., vol. 6, no. 86, pp. 83399–83405, 2016. [18] D. Dong, C. Zhao, W. Zheng, W. Wang, X. Zhao, and L. Jiao, “Analyzing Strawberry Spoilage via its Volatile Compounds Using Longpath Fourier Transform Infrared Spectroscopy,” Sci. Rep., pp. 1–7, 2013. [19] B. Esser, J. M. Schnorr, and T. M. Swager, “Selective detection of ethylene gas using carbon nanotube-based devices: Utility in determination of fruit ripeness,” Angew. Chemie - Int. Ed., vol. 51, pp. 1–6, 2012. [20] B. M. Binder, “The ethylene receptors: Complex perception for a simple gas,” Plant Sci., vol.

70

175, pp. 8–17, 2008. [21] M. N. Baibich, J. M. Broto, A. Fert, F. Nguyen Van Dau, and F. Petroff, “Giant Magnetoresistance of (001) Fe/(001) Cr Magnetic Superlattices,” Phys. Rev. Lett., vol. 61, no. 21, pp. 2472–2475, 1988. [22] E. Y. Tsymbal and D. G. Pettifor, “Perspectives of Giant Magnetoresistance,” in Solid state physics, vol. 56, Academic Press, 2001, pp. 113–237. [23] A. V Silva, D. C. Leitao, J. Valadeiro, J. Amaral, P. Freitas, and S. Cardoso, “Linearization strategies for high sensitivity magnetoresistive sensors,” Eur. Phys. J. Appl. Phys., pp. 1–20, 2015. [24] N. F. Mott, “The Electrical Conductivity of Transition Metals,” Proc. R. Soc. London. Ser. A - Math. Phys. Sci., vol. 47, pp. 699–717, 1936. [25] B. Dieny, V. S. Sperious, S. S. P. Parkin, B. A. Gurney, D. R. Wilhoit, and D. Mauri, “Giant magnetoresistive in soft ferromagnetic mutilayers,” Phys. Rev. B, vol. 43, pp. 1297–1300, 1991. [26] I. Ennen, D. Kappe, T. Rempel, C. Glenske, and A. Hütten, “Giant Magnetoresistance: Basic concepts, microstructure, magnetic interactions and applications,” Sensors, vol. 16, no. 6, 2016. [27] P. P. Freitas, S. Cardoso, P. P. Freitas, R. Ferreira, S. Cardoso, and F. Cardoso, “Magnetoresistive Sensors,” J. Phys. Condens. Matter, vol. 19, pp. 1–21, 2007. [28] C. Reig, M. D. Cubells-Beltrán, and D. R. Muñoz, “Magnetic field sensors based on Giant Magnetoresistance (GMR) technology: Applications in electrical current sensing,” Sensors, vol. 9, no. 10, pp. 7919–7942, 2009. [29] S. Yan et al., “Design and Fabrication of Full Wheatstone-Bridge-Based Angular GMR Sensors,” Sensors, vol. 18, pp. 1–8, 2018. [30] P. P. Freitas, R. Ferreira, and S. Cardoso, “Spintronic Sensors,” Proc. IEEE, vol. 104, no. 10, pp. 1894–1918, 2016. [31] A. Alfadhel and J. Kosel, “Magnetic Nanocomposite Cilia Tactile Sensor,” Adv. Mater., vol. 27, no. 47, pp. 7888–7892, 2015. [32] T. A. Keil, “Functional morphology of insect mechanoreceptors,” Microsc. Res. Tech., vol. 39, pp. 506–531, 1997. [33] F. Beer, E. Johnston Jr., J. DeWolf, and D. Mazurek, Mechanics of Materials, 7th ed. McGraw Hill Education, 2014. [34] Z. A. Li et al., “Electrostatic doping as a source for robust ferromagnetism at the interface between antiferromagnetic cobalt oxides,” Sci. Rep., vol. 5, pp. 1–6, 2015. [35] D. Leitão, J. P. Amaral, S. Cardoso de Freitas, and C. Reig, “Microfabrication techniques,” in Giant Magnetoresistance (GMR) Sensors, Springer, Berlin, Heidelberg, 2013, pp. 31–45. [36] R. Varela, “Optimization of MR sensor Geometry Towards Picotesla Detection.,” Instituto Superior Técnico, 2015. [37] V. Gehanno et al., “Ion beam deposition of Mn-Ir spin valves,” IEEE Trans. Magn., vol. 35, pp. 4361–4367, 1999.

71

Appendix A Run sheets

Run sheet – Full Wheatstone Bridge Spin valve sensors

Run sheet – Artificial cilia fabrication and insertion over the GMR sensor

72

Run sheet – Full Wheatstone Bridge Spin valve sensors

User: Maria Carvalho

Smaple ID: SV_2079_WB_FQC

Process start: Process finish:

Step 1a: 1st Exposure – For spin-valve patterning Date:

Equipment: SVG track and DWL

Substrate: Silicon

Step 1a.1: (Vapor prime oven) Vapor Prime 30 min (Recipe - 0)

Wafer dehydration: Vacuum, 10 Torr for 2 min. N2 inlet, 760 Torr for 3 min. Heating to 130°C

Priming: Vacuum, 1 Torr for 3 min. HDMS, 6 Torr for 5 min.

Purge prime exhaust: Vacuum, 4 Torr for 1 min. N2 inlet, 500 Torr for 2 min. Vacuum, 4 Torr for 2 min.

Return to atmosphere: N2 inlet for 3 min.

Step 1a.2: (SVG track) Coating 1.5 µm PR (recipe – 6/2)

• Dispense PR on the sample and spinning at 800 rpm for 5 s; • Spin at 2500 rpm for 30 s to obtain ~ 1.5 µm thickness; • Soft bake at 85°C for 60 s.

Step 1a.3: (DWL) Exposure

Map: Amison

Mask: SV_WB_MC_L1 (Die size: X = 16600 µm; Y = 16600 µm) INV MASK

Edge clearance: 4000 µm

Energy: 65.m18

Power: 98 mW

Focus: -10

Step 1a.4: (SVG track) Development (Developer TMAW238WA)

• Bake at 110°C for 60 s; • Cool for 30 s; • Develop for 60 s.

Step 1a.5: Optical inspection: Resist inside the features

73

Step 1b: Spin valve patterning - etch Date:

Equipment: N3000

Etch rate: ~ 1 Å/s

Total thickness to etch: 247 Å Total etching time: 280 s (over etch)

Angle: 60° Rotation: 30 rpm

Machine: Nordiko 3000 Base Pressure = 9.5 x 10-7 Torr

Batch recipe: Junction etch

Wafer Recipe: Etch spin valve 70 pan

Process steps: Etch spin valve

RF Power V1 I1 V2 I2 Gas Flux Working Assist. Gun (W) (V) (mA) (V) (mA) (sccm) Pressure (T)

Set values 54 500 - 200 - 8 -

-4 Read values 53 488.3 29.7 194.5 1.7 7.9 1.8x10

Step 1b.1: Optical inspection and resistance inspection: Etch was successfully done.

Step 1 c: Resist strip Date:

Equipment: Wet bench Step 1c.1: Immerse the sample in Fujifilm® Microstrip 3001:

Solvent T (°C) Time (min) Notes Microstrip 3001 65 30 Ultrasounds

Step 1c.2: Wash the substrate with IPA, followed by rinsing in DI water and blow-dryed with compressed air gun.

Step 1c.3: Optical inspection. All resist removed

Step 2a: 2nd Exposure - Contact definition Date:

Equipment: SVG track and DWL

Step 2a.1: (Vapor prime oven) Vapor Prime 30 min (Recipe - 0)

Step 2a.2: (SVG track) Coating 1.5 µm PR (recipe – 6/2)

Step 2a.3: (SVG track) Pre-develop

• No bake; • Develop for 20 s

74

Step 2a.4: (DWL) Exposure

Map: Amison

Mask: SV_WB_MC_L2 (Die size: X = 16600 µm; Y = 16600 µm) NON-INV MASK

Edge clearance: 4000 µm

Energy: 90.m18

Power: 98 mW

Focus: -10

Step 2a.5: (SVG track) Development (Developer TMAW238WA)

Step 2a.6: Optical inspection: Resist all over except inside the features.

Alignement marks (L1)

1º cross (300, 300)

2º cross (4400, 300)

3º cross (8500, 300)

4ºcross (12600, 300)

Step 2b: Metallization Date:

Equipment: N7000

Sequence: Metalization:

• Module 2: Soft sputter etch for 1 s • Module 4: 3000 Å Al deposition for 1 min 20 s • Module 3: 150 Å TiW deposition for 27 s

Module 2 Run# Power1 (W) Power2 (W) Gas flux Ar (sccm) Pressure (mTorr)

Set values 40 60 50 3 21572 Read values 39 59 50.1 3

Module 4 Run# Power (kW) Voltage (V) Current (A) Gas flux Ar (sccm) Pressure (mTorr)

Set values 2 - - 50 3 21572 Read values 2 394 5.12 50 3.1

Module 3 Run# Power (kW) Voltage (V) Current (A) Gas flux (sccm) Pressure (mTorr)

Set values 0.5 - - 50 3 21572 Read values 0.5 418 1.2 49.6 2.9

75

Step 2 c: Metallization Lift-off Date:

Equipment: Wet bench

Step 2c.1: Immerse the sample in Fujifilm® Microstrip 3001:

Solvent T (°C) Time (min) Notes Microstrip 3001 65 60 Ultrasounds

Step 2c.2: Wash the substrate with IPA, followed by rinsing in DI water and blow-dried with compressed air gun.

Step 2c.3: Optical inspection. All metal removed from the undesired areas

Step 3a: 3rd Exposure – Passivation layer definition Date:

Equipment: SVG track and DWL Step 3a.1: (Vapor prime oven) Vapor Prime 30 min (Recipe - 0)

Step 3a.2: (SVG track) Coating 1.5 µm PR (recipe – 6/2)

Step 3a.3: (SVG track) Pre-develop for 20 s

Step 3a.4: (DWL) Exposure

Map: Amison

Mask: SV_WB_MC_L3 (Die size: X = 16600 µm; Y = 16600 µm) INV MASK

Edge clearance: 4000 µm

Energy: 90.m18

Power: 98 mW

Focus: -10

Step 3a.5: (SVG track) Development (Developer TMAW238WA)

Step 3a.6: Optical inspection: Resist all inside the features.

Alignement marks (L2)

1º cross (522, 300)

2º cross (4622, 300)

3º cross (8722, 300)

4ºcross (12822, 300)

Step 3 b: Passivation layer deposition Date:

Equipment: UHVII and Alcatel SCM 650

Step 3b.1: Alumina (Al2O3) deposition Deposition rate: 12 Å/min

Total to deposit: 2000 Å Total time: 2 h 47 min

76

Base Working Pressure before Turbo Pump Ar flux Power - pressure pressure plasma (mTorr) freq. (Hz) (sccm) Fwd/Ref (W) (Torr) (mTorr) Read Sensor not 4.1 x 10-7 2.6 544 44.6 200 values working

Step 3b.2: Silicon oxide (SiO2) deposition

Deposition rate: 25 Å/min

Total to deposit: 2000 Å Total time: 80 min

Base pressure Pressure before plasma Rotation Ar flux Power - Fwd/Ref

(Torr) (mTorr) (rpm) (sccm) (W) Read 1.23 x 10-6 2.6 x 10-3 4 20 140 values

Step 3 c: Passivation layer Lift-off Date:

Equipment: Wet bench Step 3c.1: Immerse the sample in Fujifilm® Microstrip 3001:

Solvent T (°C) Time (h) Notes Microstrip 3001 65 3 Ultrasounds

Step 3c.2: Wash the substrate with IPA, followed by rinsing in DI water and blow-dried with compressed air gun.

Step 3c.3: Optical inspection. All metal oxide from the undesired areas

Step 4: Annealing Date:

Equipment: Annealing setup

Step 3c.1: place the sample inside the annealing setup. Attention to the direction of the easy axis.

Conditions:

250°C for 30 min Cool with 1 kOe :

24°C (room tempe rature)

77

Run sheet – Artificial cilia fabrication and insertion over the GMR sensor

User: Maria Carvalho

Process start: Process finish:

Step 1a: Hard mask fabrication – Glass substrate cleaning Date:

Equipment: Wet bench

Substrate: Glass

Step 1a.1: Submerse the sample in Alconox

Solvent T (°C) Time (min) Notes Alconox 65 30 Ultrasounds

Step 1a.2: Rinse with DI water and blow-dry with the compressed air gun.

Step 1b: Hard mask fabrication – Aluminum deposition Date:

Equipment: N7000

Sequence: Al 3000 no etch:

• Module 4: 3000 Å Al deposition for 40 s

Module 4 Run# Power (kW) Voltage (V) Current (A) Gas flux Ar (sccm) Pressure (mTorr)

Set values 2 - - 50 3

Read values 2 392 5.1 50 3

Step 1c: Hard mask fabrication – Exposure Date:

Equipment: SVG track and DWL

Step 1c.1: (Vapor prime oven) Vapor Prime 30 min (Recipe - 0)

Step 1c.2: (SVG track) Coating 1.5 µm PR (recipe – 6/2)

Step 1c.3: (DWL) Exposure

Map: Amison

Mask: HMASK_MC (Die size: X = 15703.4 µm; Y = 11712.2 µm) NON-INV MASK

Edge clearance: 5000 µm

Energy: 85.m18

Power: 98 mW

Focus: -10

Step 1c.4: (SVG track) Development (Developer TMAW238WA)

78

Step 1c.5: Optical inspection: Resist everywhere except inside the features.

St ep 1d: Hard mask fabrication –Wet etch Date:

Equipment: Wet bench

Step 1d.1: (Use protective goggles, apron, thick gloves over the clean room gloves) Prepare 2 beakers, one with DI water and the other with Technic Aluminium Etchant Micropur MOS. Use a plastic tweezer to handle the sample in Aluminum etchant.

Step 1d.2: Immerse the sample in the aluminum etchant:

Etch rate Total to etch Solvent T (°C) Time (s) (Å/s) (Å) Technic Aluminum Etchant Micropur Room ~ 6 3000 500 MOS temperature

Step 1d.3: Stop etching by immersing the sample in DI water and dry.

Step 1d.4: Optical inspection. All metal oxide from the undesired areas

Step 1e: Hard mask fabrication – Resist strip Date:

Equipment: Wet bench

Step 1e.1: Immerse the sample in Fujifilm® Microstrip 3001:

Solvent T (°C) Time (min) Notes Microstrip 3001 65 30 Ultrasounds

Step 1e.2: Wash the substrate with IPA, followed by rinsing in DI water and blow-dried with compressed air gun.

Step 1e.3: Optical inspection. All photoresist removed.

Step 2a: 150 µm SU-8 mold for cilia – Substrate cleaning Date:

Equipment: Wet bench

Substrate: Silicon Step 2a.1: Submerse the sample in Fujifilm® Microstrip 3001, if it has photoresist residues.

Step 2a.2: Wash with IPA, followed by rinsing with DI water and blow drying.

79

Step 2a.3: Submerse the sample in Alconox.

Step 2a.4: Rinse with DI water and blow-dry with the compressed air gun.

Solvent T (°C) Time (min) Notes Microstrip 3001 65 15 Ultrasounds Alconox 65 30 Ultrasounds

Step 2a.5: Place the same in the UVO cleaner for 15 min (including 5 min exhaustion time) (1 – 5 min; 2 – 15 min).

Step 2b: 150 µm SU-8 mold for cilia – Substrate coating Date:

Equipment: Flow hood and spin coater Step 2b.1: Heat the sample in a hotplate at 100 °C for 10 min, prior to spinning (to increase adhesion). Cool down the sample to room temperature before spinning. (hot plate with aluminum foil + 5 °C) Step 2b.2: Place the sample in the spin coater. Step 2b.3: Pour PR (SU-8) manually over the silicon wafer, covering ¾ of the wafer and let it rest for 30 s before spinning. SU-8 must be poured carefully to avoid formation of air bubbles. Step 2b.4: Spread cycle (step 1): Spin @ 500 rpm for 10s, with 100 rpm/s acceleration Spin cycle (step 2):

SU-8 Thickness (µm) Step Rpm Time (s) Acceleration (rpm/sec)

50 50 2 1202 30 300 50 100 2 929 30 300 50 150 2 400 40 100

Step 2c: 150 µm SU-8 mold for cilia – Soft-baking Date:

Equipment: Flow hood Step 2c.1: Before soft-baking, pre-bake at 65°C; Step 2c.2: Increase the heat plate temperature to 95 °C with the substrate on top. When the 95°C are achieved, soft-bake at 95°C. Let the sample cool down until 45°C on top of the heat plate.

Thickness (µm) 65 °C (min) 95°C (min)

50 5.9 19

100 10 30

150 14.1 42

Step 2c.3: Cool down the sample for 10 min at room temperature on top of a glass.

80

Step 2d: 150 µm SU-8 mold for cilia – Exposure Date:

Equipment: Contact lithography system Note: turn ON UV light 30 min before exposure

Step 2d.1: Place the hard mask over the SU-8 with the aluminum surface facing down. Make contact between the hard mask and the sample, try to minimize the gap between them. (use yellow tape). Step 2d.2: Insert the UV filter in the slot near the lamp and insert the acrylic with the substrate in the other slot, closest to the lamp. Remove filter and start counting down:

Thickness (µm) 50 100 150

st Time 1 slot (s) 30 45 52

Step 2e: 150 µm SU-8 mold for cilia – Post exposure bake (PEB) Date:

Equipment: Flow hood Step 2e.1: Pre-bake at 65°C. Step 2e.2: Increase the heat plate temperature to 95 °C with the substrate on top. When the 95°C are achieved, PEB at 95°C. Let the sample cool down until 45°C on top of the heat plate.

Thickness (µm) 65°C (min) 95°C (min)

50 1 5

100 1 10

150 1 15

Step 2e.3: Cool down the sample for 10 min at room temperature on top of a glass.

Observations: Mask should be visible after 1 min of PEB. Otherwise there was insufficient exposure, heating or both.

Step 2f: 150 µm SU-8 mold for cilia – PR Development Date:

Equipment: Flow hood Step 2f.1: Prepare 2 beakers, one with PGMEA and other with IPA. Immerse the substrate in PGMEA with manual agitation. Thickness (µm) 50 100 150 Development (min) 6.3 10 15.7

Step 2f.2: To stop development, immerse the sample in IPA and dry well (but gently).

81

Observations: If a white residue is produced during IPA rinse, the substrate is under-developed, so immerse in PGMEA again. If the structures peel off during development, then either the exposure time or the PEB time were insufficient. Step 2f.3: Optical inspection: structures are not well defined; they present a conic shape instead of a cylinder.

Step 3a: PDMS mold (negative copy) –PDMS preparation Date:

Equipment: Analytical balance and desiccator Step 3a.1: Place the plastic cup in the analytical balance and tare (zero) the scale. Pour the PDMS into the plastic cup and weight. Tare the scale. Step 3a.2: The quantity of curing agent is added in: • PDMS (10:1) - 1:10 proportion of curing agent to PDMS. • Nanocomposite (15:1) - 1:15 proportion of curing agent to PDMS. Then add the magnetic particles in a 5:1 proportion of magnetic particles to PDMS + curing agent.

Remove from the balance and mix with a spatula, air bubbles will form with agitation.

PDMS Curing agent Magnetic particles 10:1 24.6 2.5 - mass (g) 15:1 3.7 0.2 0.8

Step 3a.3: Place the cup with the mixture in the desiccator for 1 h to remove the bubbles. If after 1 h there are still bubbles, leave the cup in the desiccator for another 30 min.

Step 3b: PDMS mold (negative copy) –PDMS (10:1) casting, baking and peeling Date:

Equipment: Analytical balance, oven and wet bench Step 3b.1: PDMS casting: Carefully pour the PDMS (10:1) onto the SU-8 mold, proceed gently to avoid the formation and trapping of bubbles. If bubbles are formed, place the mold with PDMS on the desiccator until they are removed.

Step 3b.2: PDMS baking: Place the mold filled with PDMS in the oven at 70°C for 1 h. Remove the mold from the oven and let it cool.

Step 3b.3: PDMS peeling: Peel the baked PDMS off from the SU-8 mold by using a scalpel and tweezers.

Step 3b.4: (wet bench) Clean the SU-8 mold with IPA (use a paper towel or cotton pad, if necessary). Make sure all PDMS residues are removed. Rinse with DI water and blow dry.

Step 3c: Cilia fabrication–PVA preparation (previous day) Date:

Equipment: Analytical balance, magnetic agitator with heat source Step 3c.1: Heat 50 mL of DI water at 80°C for 10 min, in a glass flask with lid;

Step 3c.2: Weight 2.5 g of Mowiol® 40-88 and mix it with the hot water (5:1 ratio of water to PVA). Stir with a magnet in a magnetic agitator.

Step 3c.3: The solution must be maintained on the magnetic agitator, at ~ 40°C, overnight. If the agitator has a source of light cover the flask with aluminum foil.

82

Step 3d: Cilia fabrication–PVA coating Date:

Equipment: Wet bench, flow hood, spin coater and heat plate Substrate: Glass

Step 3d.1: Submerse the glass sample in Alconox

Solvent T (°C) Time (min) Notes Alconox 65 30 Ultrasounds

Step 3d.2: Rinse with DI water and blow-dry with the compressed air gun.

Step 3d.3: Place the glass sample in the spin coater. Dispense a generous amount of PVA solution on top of the substrate using a pipette. Step 3d.4: Spread cycle (step 1): Spin @ 300 rpm for 5 s, with 100 rpm/s acceleration Spin cycle (step 2): spin @ 500 rpm for 50 s, with 750 rpm/s acceleration Step 3d.5: Place the substrate in the heat plate and bake at 70°C for 5 min.

Step 3e: Cilia fabrication – Cilia fabrication Date:

Equipment: UVO cleaner, flow hood, spin coater and oven Step 3e.1: Place PVA substrate in the UVO cleaner for 10 min (including 5 min exhaustion time) (1 – 5 min; 2 – 10 min).

Step 3e.2: Place the sample in the spin coater and pour PDMS manually over it. Step 3e.3: Spread cycle (step 1): Spin @ 500 rpm for 5 s, with 500 rpm/s acceleration Spin cycle (step 2): spin @ 2200 rpm for 20 s, with 1000 rpm/s acceleration

Step 3e.4: Place the PDMS (10:1) and the SU-8 molds in the UVO cleaner for 10 min. Followed by a silanization process: pour 6 µL of HMDS in a watch glass and place it together with the molds in the desiccator for 50 min. The structures (cilia holes) must be facing up.

Step 3e.5: Pour the magnetic particles embedded PDMS (15:1) on the structures, filling the holes. Press it against the glass/PVA/PDMS substrate, with both PDMS in contact. Bake in the oven at 70°C for 1 h. Step 3e.6: Peel the baked PDMS (cilia) off from the PDMS and SU-8 molds by using a scalpel and tweezers.

Step 3e.7: Immerse the glass/PVA/PDMS/mag. PDMS in DI water:

Solvent T (°C) Time (min) Notes DI water 65 Until PVA dissolves Ultrasounds

Step 3e.8: Rinse with DI water and blow-dry with the compressed air gun.

Step 3e.9: Place the sample in the annealing setup, with the following conditions:

Cool with

100°C for 1 h 1 kOe

24°C (room temperature) 83