Advanced Magnetoresistive Sensors for Industrial Applications

Tiago Costatscosta94@gmail.com

Instituto Superior Tecnico, Lisboa, Portugal

October 2017

Abstract

Advanced MR sensors - the magnetic tunnel junctions - were implemented in a system alongsidemagnets aimed to magnetize and read MI patterns. The development of this system was done intwo main stages. First the search for the best magnet-sensor configuration using both simulationwith finite element modeling (FEM) and measurements. Then the validation of different sensorarray configurations. This validation was done through measurements of well-defined structures of ahard ferromagnetic alloy, micro-fabricated in a clean-room environment, and comparison with a 2Dsimulation.Keywords: Magnetic tunnel junctions, Magnetic ink, Magnetic encoder, Stray field measurement,Magnetic field simulation

1. IntroductionMetrology and accurate positioning is of major rel-evance for industry. Nowadays there is competitivedemand for small size devices with the lowest costpossible and capable of performing even in harshenvironments. Currently, the most widespread usedtechnology is optical detection, which allow high ac-curacy, resolution and reliability. However, in harshenvironments such systems become bigger, more ex-pensive and more fragile. Precision encoding cantherefore benefit from the use of magnetic technol-ogy.

Magnetic encoder systems are capable of convert-ing mechanical rotational or linear movement intoan analog or digital signal using magnetic technol-ogy. They are comprised of a reading head and atrack that encodes the position through the creationof stray magnetic fields. Nowadays the most widelyused magnetic sensing technology used is hall-effectbased [10]. However, other magnetic technologies,and in particular magnetoresistance (MR) based,offer clear advantages when compared to optical de-tection and also to the other magnetic technologies.MR sensors - in particular state of the art MagneticTunnel Junctions (MTJs) - can be produced in mi-crometic dimensions at massive scale, at low costand capable of high sensitivity to weak magneticfields [7, 9].

State-of-the-art magnetic tracks for positioningsystems, such as the ones produced by Bogen Elec-tronic GmbH are hard magnetic and made of anelastomer filled with ferrite [1]. Fabricating trackswith Magnetic Ink allows a great improvement both

in cost and complexity of the production. The useof magnetic ink is already widely used for securitypurposes such as banknotes and checks, such as us-ing Magnetic Ink Character Recognition (or MICR)[8]. However, for positioning applications there isstill development to be made.

This work is done in the scope of the projectGePos, a partnership between INESC-MN and Bo-gen Electronic GmbH, that a precise magnetic en-coder system using magnetoresistance technologyand in particular state-of-the-art MTJs. The mainobjective of the project is the development of a sys-tem capable of measuring positions using magneticink, allowing a higher versatility in today’s industryapplications. This work is focused on the develop-ment of the reading head with the goal of measuringpatterns printed with magnetic ink.

2. Theoretical Background2.1. Magnetostatics and Magnetic Materials

The magnetic H-field is an indispensible auxiliaryfield when dealing with magnetic materials . Themagnetization of a solid reflects the local value ofH [5, 3]. In free space, both the B and H are re-lated by the magnetic permeability µ0 as B = µ0H.Therefore, in free space, the derivation of both fieldsis interchangeable and immediate. In magnetic ma-terials however, the H-field relates to the B-fieldthrough the constitutive relation:

H =B

µ0−M, (1)

1

where M is the magnetization. This field is notdivergenceless (∇ · H = −∇ · M), so comparingwith the electric field, a calculation of this field canbe done by considering the existence of fictitiousmagnetic charges, both in the bulk ρm = −∇ ·Mand on the surface σm = M · en. So the stray fieldcan be integrated using the relation:

H(r) =− 1

4π

∫V

d3r′ (∇ ·M(r′))r− r′

|r− r′|3

+1

4π

∫S

d2r′ (M(r′) · en)r− r′

|r− r′|3,

(2)

where the integration for the bulk charges is madeon the bulk volume V , and the surface charges onthe charged surface S, where r′ is the position vec-tor of the fictitious charge and r the position vectorwhere the field is calculated.

There are four main classifications for magneticmaterials: diamagnetic, paramagnetic, ferromag-netic and anti-ferromagnetic.

By reducing the size of a ferromagnetic material,a critical size may be reached, on which only one do-main can be sustained. This phenomenon is calledsuperparamagnetism [2]. The magnetization curveof a material with this phenomenon resembles theferromagnetic curve in a sense that it has a satu-ration magnetization, however, both the coercivityand remanence are zero, i.e., at zero applied field,the material is perfectly non-magnetic.

2.2. Magnetic InkMagnetic ink is no more than a fluid media withmagnetic properties. The ink is usually made ofmainly four types of ingredients [13]: the colorants,or magnetic pigments, which present the ink withcolor and the magnetic properties. They are usu-ally magnetic nanoparticles of some ferromagneticalloy; the vehicles or binders, which have multiplefunctions in the ink such as dispersing and bindingthe particles modifying the mechanical properties,and also presenting some other special properties;the solvent, which dissolves all the other compo-nents and adjusts the viscosity of the ink; and otheradditives which are specific for each ink and are de-signed to enhance properties of the ink.

Although real nanoparticles can have a complexmagnetic structure, an assembly of noninteractingsingle-domain isotropic nanoparticles behaves likethe above described superparamagnetism. At atemperature T in an applied field H, the averagemagnetization of the assembly is given by [8]:

M = MS

[coth

(µ0mpH

kT

)− kT

µ0mpH

], (3)

where mp is the individual magnetic moments of

the particles and k the Boltzmann’s constant. Thisequation is a Langevin-like function.

2.3. Magnetic Tunnel JunctionsMagnetic Tunnel Junctions (MTJs) are structuresbased on the Tunnel Magnetoresistance (TMR),which is defined as the change in electrical resis-tance as a function of an external applied magneticfield. It is described by the equation

TMR =Rmax −Rmin

Rmin,

with Rmin and Rmax the minimum and the max-imum electrical resistance, respectively [7]. MTJsare structures based on a multilayer structure withtwo ferromagnetic (FM) layers separated by an in-sulator (I), typically aluminum oxide (Al2O3) ormagnesium oxide (MgO) [12], in a configurationFM-I-FM. One of the FM layers has a fixed mag-netization and the other is free to rotate with theexternal magnetic field. When the FM layers haveanti-parallel magnetization, the junction has itshigh resistance state. The low resistance for paralleldirection magnetization. The ideal transfer curve ofa TMR sensor is presented in Figure 1.

Figure 1: Ideal transfer curve of a MTJ sensor.

Using the physical factors obtained from thetransfer curve, one can define the sensor field sen-sitivity, which is defined as the variation of the re-sistance (output) with respect to the magnetic fieldvariation (input), or how reactive the sensor is toa field variation. For the ideal linear response, theMTJ sensor sensitivity S can be expressed by theslope o the linear region, normalized to its minimumresistance, taking into account the TMR ratio:

S =1

Rmin

(∆R

∆H

)linear

=TMR

(∆H)linear[%/Oe] .

(4)

2

A sensor can achieve a high sensitivity by reduc-ing the saturation fields and increasing the TMRratio.

In the linear region of the sensor’s response, thesensor resistance can be described as the sum of anominal resistance R0, at zero magnetic field, and avariation ∆R that, looking at equation 4 is directlyrelated to the variation of the applied magnetic field(with zero magnetic field) H and the sensor sensi-tivity S(Vb):

R(H) = R0 + ∆R = R0 + S(Vb)RminH (5)

Consequently, the voltage output variation ∆Vdue to an external magnetic field variation ∆H =H2−H1, and the current bias I that flows throughthe MTJ due to the bias voltage applied can bewritten as:

∆V = (R (H2)−R (H1)) I = S(Vb)RminI∆H (6)

3. System Description and Character-ization

The studied system is a magnetic encoder, there-fore it has two main different units: the sensinghead with the magnetic sensor alongside the inte-grated electronics; and a track, which encodes theinformation.

As an interdisciplinary project, the developmenthas input from the different parts: the magnetic inkis provided by BOGEN Electronics GmbH1, whois also responsible for printing the magnetic inkstructures and developing the integrated electron-ics as well as the future casing and packaging; andINESC-MN is responsible for both the characteriza-tion of the ink and the development of the sensinghead configuration for the system.

3.1. ConfigurationsTo read the MI a constant magnetization of the pat-terns is needed to saturate its magnetization. Themagnetization of the ink creates stray fields betweenthe poles created on the structures. The magneticsensor is able to measure these stray fields. Thestrategy to magnetize the ink in this work is to im-plement the magnets alongside the sensor on thereading head.

In total, six different configurations were consid-ered. However, the requirements for the system leftout all except for configuration standards Std 1 andStd 3 (Figures 2 and 3). These requirements are:a) the sensing head must be able to measure in bothdirections of movement, which is not met by Std 5and Std 6; b) the sensor must be placed so that itcan be as close as possible to the samples (bottom

1http://www.bogen-electronic.com/en/

of the sensing head); and c) the magnetic ink struc-tures must be magnetized in-plane in order to createalternating poles in the direction of the movement,which is not met by Std 2 and Std 4.

Figure 2: Std 1.

Figure 3: Std 3.

According to the two considered configurations,two different magnets were used. Both magnetshave the same dimensions, and only the magneti-zation direction differs. The parameters are as fol-lows:

ConfigurationGeometry

µr−→Br (T)

(mm3)

Std 1 1×10×4 1.05 1.43 −→exStd 3 1×10×4 1.05 1.43 −→ez

Table 1: Physical parameters of the magnets used.

3.2. Simulations of the Magnets Configura-tions

Simulations were done on both configurations Std 1and Std 3. In the configurations, one of the goals isto have minimum influence from the magnets’ strayfield on the sensor in order to maintain its highsensitivity characteristic. So, no field componentson the sensitive plane (y0z) of the sensor can bepresent.

3

Simulations on the magnetic field created by themagnets were done using the simulation softwareCOMSOL Multiphysics 5.0. From the simulationsof both configuration standards, it is evidenced ahigh variation of the z component of the field in thepoint where the sensor is placed. This leads to arequirement for very high precision in the placementof the sensor between the magnets.

Further simulations showed that for Std 3, plac-ing the sensor 0.5 mm (a = 0.5 mm) below thebase line of the magnets would greatly decrease thez component variation. In fact, where the sensoris placed, no variation from this component of thefield happens.

3.3. Magnetic Sensor CharacterizationIn this work, two TMR sensors with different ge-ometries were considered:

• Sensor S1 is an array of 72 sensing elements(MTJs) with an individual area of 50×50 µm2

distributed along 8 columns and 9 rows occu-pying a total area of 525×570 µm2 to maximizethe SNR [4];

• Sensor S2 is an array of 4 sensing elements(MTJs) with an individual area of 10×4 µm2

distributed along 4 columns and 1 row occupy-ing a total area of 58.5×4 µm2.

The MTJs on the two sensors have the same stack,which has a soft pinned sensing layer, with both aSAF and a SF. The stack is resented on Figure 4.

Figure 4: Thin film structure of the used MTJ pil-lar.

The magnetic behavior of both sensors was stud-ied by measuring the transfer curve, making use ofa magnetotrasport measuring tool. This tool makesa sweep of the field between -14 mT and 14 mT, andmeasures the resistance of the sensor. A bias cur-rent is applied in a CPP (current perpendicular tothe plane) configuration: 100 µT for sensor S1 and50 µT for sensor S2. The voltage measurement isdone directly on the PCB with the mounted sensor.

The transfer curves were measured for the systemwith no magnets present and for both Std 1 andStd 3.

On Figure 5 the transfer curve measured for sen-sor S1 with Std 1 was measured. Notice the pres-ence of the blue curve, taken as a reference, whichis the transfer curve of the sensor with no magnetson the system.

Figure 5: Set of transfer curves obtained for sensorS1 in a Std 1 configuration, alongside the referencecurve.

As expected from the simulations previouslymade, the transfer curve on the Std 1 configurationis not easily reproducible. The configuration, andin specific the relative position between the mag-nets and sensor, is very sensitive to outer factors.Therefore, different curves were measured for dif-ferent measurements, and the resulting parameterspresented in Table 2. The effect of Std 1 on sen-sor S2 is usually just a shift of the linear region ofthe curve (the other parameters do not change sig-nificantly), which means that the influence is beingmade in the sensitive direction of the sensor, whichis z, as it was expected from simulations.

MR Rmin S0 µ0Hf µ0Hc

(%) (Ω) ( %/mT) (mT) (mT)

Ref 129 542 27.7 0.4 0.1

1 129 % 546 19.2 1.3 0.1

2 129 % 546 16.6 1.8 0.1

3 128 % 551 13.9 2.1 0.1

4 127 % 552 11.9 2.6 0.1

Table 2: Physical parameters derived from thetransfer curves of sensor S1, without magnets andwith configuration Std 1.

Sensor S2 was always saturated in a Std 1 con-figuration, due to its low area and thus being moreprone to residual cross field from the magnets.

4

For Std 3, with a = 0.5 mm, the system is notso sensitive to changes in the positions, making thetransfer curve reproducible, and for every measure-ment the same parameters were applicable, for sen-sor S1 and S2. Figures 6 and 7 show the curvesalongside the reference curve for Std 3 using sen-sors S1 and S2 respectively. The important valuesfor measurements derived from the transfer curvesare presented on Table 3.

Figure 6: Sensor S1. a = 0.5 mm.

Std 3 has the effect of increasing the linear rangeof the curve of sensor S1, maintaining the TMRratio, resulting in a lower sensitivity. This effectarises not from components in the sensing direction(z) of the sensor, but from components perpendicu-lar to it, but still on the sensing plane of the sensor(y). The influence from this component was not ex-pected on simulations, meaning that in the regionwhere the sensor is located, the y component of thefield is not zero.

Figure 7: Sensor S2. a = 0.5 mm.

On sensor S2 however, the main effect is the shiftof the curve, which arises from the influence of the

z component of the cross field from the magnets.This shift has however, the effect of increasing thesensitivity.

MR Rmin S0 µ0Hf µ0Hc

(%) (Ω) ( %/mT) (mT) (mT)

S1

Ref 129 542 27.7 0.4 0.1

Std 3 131 542 14.3 0.8 0.1

S2

Ref. 156 1187 -22.2 0.4 0.2

Std 3 159 1161 -24.4 1.3 0.3

Table 3: Physical parameters derived from thetransfer curves of sensors S1 and S2, without mag-nets and with configuration Std 3 and a = 0.5 mm.

3.4. Magnetic Ink CharacterizationThe magnetic ink received from Bogen was alsocharacterized through profilomenter and vibratingsample magnetometer techniques. It allows theevaluation of the magnetic properties and also theprediction of the MI structures behavior.

4. Hard Magnetic CoCrPt StructuresFor validation of the sensor, hard ferromagneticstructures using micro-fabrication techniques aredeveloped. The material used was a magnetic al-loy composed of Cobalt Chromium and Platinum:CoCrPt. A simulation of the samples as well assome measurements are also performed. The geom-etry of the samples is represented in Figure 8, wherethe length of each structure and the separation isdenominated as the pole-pitch, the width is always3 mm and the thickness 1000 A, and the substrateis glass. The samples vary in pole-pitch and num-ber of structures N : 240 µm, 320 µm and 1000 µmwith 35, 26 and 8 structures respectively.

Figure 8: Structure of the micro-fabricated CoCrPtstructures.

4.1. Micro-FabricationThe micro-fabrication of the structures is done infour steps: alloy deposition, pole definition, excessmaterial etching and finally setting of the magneti-zation.

5

The first step of the fabrication is the depositionon glass substrates of CoCrPt alloy, a magnetic al-loy. This is done using sputter deposition, and inspecific DC magnetron deposition using the tool Al-catel SCM450. Two samples were deposited. Onecalibration sample to confirm the deposition rateof 6.48 A/min [11]. After being confirmed, the finalsample for the process with thickness of 1000 A wasalso deposited.

The second step is the first part of the transferof the designed pattern to the film that was de-posited. It is a lithography and it leaves protectedby a photo-resist (PR) just the structures that willultimately make up the structures.

The unprotected material resulting from the laststep is then etched by ion milling, with an etch rateof 0.8 A/s. The PR is then removed using a micro-strip. At the end, only the desired structures of themagnetic alloy are left.

Finally, in this work the magnetization of thestructures was set using a magnetic annealing witha temperature of 350C for 2 hours and an ap-plied field of 0.5 T. However, there was no need fortemperature in this step. Being a magnetic alloy,only applying a strong field on the desired directionwould result in the desired magnetization, as it wasdone before for the same material deposited in thesame conditions in [11].

After this last step, the hysteresis curve (magne-tization vs. applied field) was taken using a VSMtechnique. Figure 9 shows the resulting curve andthe derived physical properties.

Figure 9: Hysteresis loop of magnetization vs. ap-plied field for the deposited magnetic alloy CoCrPt.

4.2. SimulationsThe simulations were done taking into account thecharacterization of the fabricated CoCrPt samples.In particular, taking the thickness and the satura-tion magnetization.

The simulation takes into account a 2D model

of the structures and considers a uniformly magne-tized media, with no currents. Taking into accountthe Coulomb approach to the magnetic field calcu-lation, the 2D field created by superficial charges isgiven by the integral:

H(r) =1

2π

∫P

dr′ (M(r′) · en)r− r′

|r− r′|2, (7)

where r − r′ is the vector between a point in themagnetized material (r′) and the point where thefield is calculated (r). And σm = (M(r′) · en) isthe superficial charge density. For a plane surface(or a line in 2D), the integration of this equationbecomes

H (r, θ) = −σm2π

(∆θ + i log

(r2r1

))= Hn + iHt,

(8)yielding a normal (Hn) and tangential (Ht) field tothe magnetized surface. And being r1 and r2 thedistances to the corners of the surface line, and ∆θthe subtended angle.

For the CoCrPt structures, the surfaces of inter-est lie on the z axis, and since the sensors are sen-sitive on the z direction the tangential componentis considered for the field calculation in the model.Let N denote the number of structures on the sam-ple (and k = 0, ..., (N − 1) the index of the struc-ture), t the thickness of the structures (in z) and ppthe Pole Pitch length (in x). The magnetic field atany point r = (x, z) is calculated by summing thecontributions from all structures, each having twocharged surfaces with opposing charges:

Hz (x, z) =MR

2π

N−1∑k=0

(− log

rk2rk4

+ logrk1rk3

), (9)

being rk2 and rk4 the magnitudes of the vectors be-tween the point of the calculated field and the cor-ners of the positively charged surface; and rk1 and rk3the magnitudes of the vectors between the point ofthe calculated field and the corners of the negativelycharged surface. The corresponding vectors takinginto account Figure 10, are given for any (x, z) by:

rk1 =

(x− 2k ∗ pp, z − t

2

),

rk2 =

(x− 2k ∗ pp, z +

t

2

),

rk3 =

(x− pp− 2k ∗ pp, z − t

2

),

rk4 =

(x− pp− 2k ∗ pp, z +

t

2

).

(10)

6

Figure 10: Scheme of the contributions to the calcu-lation of the field of just one PM CoCrPt structure.The red arrow indicate the direction of the magne-tization of the structure.

To perform the simulation, the software MAT-LAB is used. After the parameters such as the PP,RD, t and MR are defined, the program computesthe vectors as given in 10 and applies the equationfor the z component of the field 9.

5. MeasurementsThe measurement setup is composed of an XYZautomated scanner with a micrometric resolution.Some electronic instruments are also present to gen-erate the required signals and to demodulate thesensor’s output. For more information about themeasurement system the reader can consult refer-ence [6].

Each measurement performed in this work con-sisted on a magnetic scan over a a sample with mag-netic structures, whether made with MI or CoCrPt,using the above described system. In specific forCoCrPt samples, the raw measurements were takenso that some values could be more accurately cal-culated. First, each scanning is done over an areawhere no magnetic signal is expected (where nomagnetic bits are present), so to provide an accu-rate offset value (voltage at zero field), this area istaken 2 mm before the first structure on the x direc-tion. The number of structures to be scanned wasalways chosen as to incorporate at least 6 consecu-tive poles. When only a curve is represented (andnot the entire 2D scan), it is chosen as the centerline of the scan, at W/2 where the field is expectedto be stronger and more uniform. Figure 11 showsa scheme of the scanned areas and also the centerline. Each measurement has also a specific resolu-tion in x and y, which correspond the size of thestep between consecutive measurements. The stepin x is always smaller than the step in y, since thesought after behavior happens on the movement onx.

Figure 11: A scheme of the scanning measurementsdone on the different CoCrPt samples.

The uncertainty of the position in z was esti-mated to be of 14µm, due to the method of findingz =0 and the resolution of the motor.

The voltage output from the setup is then con-verted to the magnetic amplitude by using the equa-tion:

H =V − VoffRS0Ib

, (11)

where H is the magnetic field magnitude in mT, Vthe output voltage from the sensor in V, Voff theoffset voltage of the measurement in V, Rmin theminimum resistance in Ω, S0 the sensitivity of thesensor in %/mT and Ib the bias current fed to thesensor in A.

5.1. Measurements on Magnetic Ink SamplesMeasurements on MI samples with sensor S1 us-ing both Std 1 and Std 3 allowed the evaluation ofthe best solution for the system. The use of Std 3resulted in a higher effective magnetization of theink during measurements, which was already ex-pected with the simulations of the magnets config-urations, due to the presence of the x component ofthe field in the region right below where the sensoris measuring. Using both configurations resultedalso in similar spatial-resolutions, since the samesensor was used. However, the higher magnetiza-tion of the ink yields higher magnetic signal, thusmore distinguishable measuremets using Std 3.

Sensor S2, which has a greater spatial resolutionthan sensor S1, was tested on the same samples anddoing the same studies as with sensor S1. SensorS2 resulted in higher spatial resolution, allowing themeasurement of smaller structures. It measures alsohigher magnetic signals from the samples, due to itslower effective reading distance. However, this sen-sor has a lower SNR, resulting in worst performancereading smaller magnetic signals.

5.2. Sensor S1 Validation with CoCrPt Sam-ples

The validation with sensor S1 was done using themicro-fabricated CoCrPt samples. The simulationof sensor S1 took into account the span of the sen-sor of 570 µm on the z axis, by doing an average ofthe field calculated over 10 points on this line. The

7

reading distance (RD) on the simulations is also acorrected RD, which is the nominal RD plus con-tribution from the uncertainty and the distance be-tween the sensor itself and the bottom of the PCB.

The measurements were done on the three sam-ples with a reading distance of half the pole pitch.The samples have pole-pitches of 240µm, 320µmand 1000µm.

Figure 12: Sensor S1 in a Std 3 configuration. PP= 240 µm.

Figure 13: Sensor S1 in a Std 3 configuration. PP= 1000 µm.

Of each measurement and simulation, the denom-inated large and small average amplitudes are cal-culated. From a tendency comparison, such as inFigures 12 and 13, it is evidenced that the sensor ismeasuring in fact the field created by the magneticstructures. It is also seen on the measurement thatsome offset signal is measured, which is not con-stant, meaning that the measurements have somebackground field.

However, the amplitudes don’t quite match withthe expected values. The plot on Figure 14 shows

the comparison between simulation and measure-ments. The large amplitude increases for smallerpole-pitch structures since we are putting the sen-sor gradually closer to the sample as the PP de-creases, the small amplitude on the other end tendsto decrease, this is due to the fact that the polesare getting closer together, closing the stray fieldforce lines at a closer scale resulting in a graduallyweaker z component of the field.

Figure 14: Average amplitudes measured both inthe measurements and simulations for sensor S1 foreach sample at a RD of half the PP.

The fact that the amplitudes don’t match maycome from different factors. First, an underesti-mation of the uncertainty in the RD of the mea-surements. 14 µm was considered as the uncer-tainty, however, this values may be higher, and if so,the difference between simulation and measurementcould be explained. On the other hand, the modelfor the simulation is a 2D approximation, where anaverage is performed over the span of the sensor.This approximation may, however be faulty, and isnot considering the full extent of the field variationalong the sensor. Other factor may come from themodel itself, since we are considering perfect mag-netization uniformity within the material.

Due to the closeness in tendency of the measure-ments in relation to the simulation, one can saythat sensor S1 is reliable, and makes reliable mea-surements in terms of magnetic signal form. There-fore, making reliable measurements on magnetic inksamples.

5.3. Sensor S2 Validation with CoCrPt Sam-ples

For sensor S2 the simulation simplifies since thesensing region is much smaller, being of just 4µm.Therefore, the field calculated in the simulation forthis sensor is done on just one point at the correctedRD, which is calculated as it was done in the previ-ous section. The samples measured are the same as

8

the used for the validation of sensor S1. The mea-surements are also done at half the pole-pitch foreach sample.

Figure 15: Sensor S2 in a Std 3 configuration. PP= 240 µm.

Figure 16: Sensor S2 in a Std 3 configuration. PP= 1000 µm.

Of each measurement and simulation, the denom-inated large and small average amplitudes are cal-culated. From a tendency comparison, such as inFigure 15 and 16, it is evidenced that the sensoris measuring in fact the field created by the sam-ples. In terms of the closeness of the amplitudesto the simulation, sensor S2 seems to have a betterperformance. It is noticed also that the magneticsignal read is higher than for sensor S1, due to thefact that since sensor S1 performs an average overits area, the effective reading distance is lower forsensor S2, however the measurements with sensorS2 show lower Signal-to-Noise Ratio (SNR).

A comparison is then performed between the dif-ferent amplitudes measured on the samples, andsimulated. On Figure 17 this comparison is shown.

Figure 17: Amplitudes measured both in the mea-surements and simulations for sensor S2 for eachsample at a RD of half the PP.

Overall the behavior predicted by the simulation isfollowed by the measurements, noticing in specificthat the decrease in the small amplitude betweenthe 320µm sample and 240µm also happens in themeasurement, even if at a bigger scale. As alreadyseen for sensor S1, the increase of the large am-plitude as the pole-pitch decreases has to do withgetting gradually closer to the sample. However,the predicted behavior for the small amplitude isdifferent from the predicted behavior for sensor S1.It must be present here that sensor S1 is averag-ing over an area that spans 570µm over z, thisresults in an effective reading distance of the halfpole-pitch plus around 200µm which is of 700µmfor 1000µm PP, 360µm for 320µm PP and so on.While 200µm is just a relatively small fraction of1000µm, it makes already a big portion of 320µmadn 240µm. Therefore, with sensor S2 the sensor issignificantly closer to the sample, and so, the mag-netic field from the smaller pole pitches is higherthan for 1000µm sample. Then, comparing thelower PP sizes, the explanation given for sensor S1holds, since the structures are much closer to eachother, the stray field closes in a smaller scale, de-creasing the signal.

Sensor S2, even though having a lower SNR, ina Std 3 configuration its sensitivity and spatial res-olution are higher than for sensor S1. Resultingin a much better expected performance in terms ofresolution for this sensor. This comes as a great ad-vantage for reading magnetic ink. The closeness ofthe measurements to the simulations validates alsothis sensor, and the procedure used, making it areliable sensor for reliable measurements.

6. ConclusionsThe aim of this work has been to develop a read-ing head based on the TMR sensor technology for

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reading magnetic ink patterns, in particular for po-sitioning application. This system should be able tomagnetize the ink as well as measure it with highaccuracy and sensitivity.

From two considered configurations (Std 1 andStd 3), Std 3 has been proven to be the most effi-cient in magnetizing the magnetic ink through mea-surements of printed magnetic ink patterns, and soreading higher magnetic field signal. The magnetsin the best configuration has also reduced influenceon the sensors and thus allowing maintenance of ahigh sensitivity for measurements.

A strategy to validate the sensors was also de-veloped, comprising on the micro-fabrication in aclean-room environment of well-defined structuresof a CoCrPt hard ferromagnetic alloy. The simu-lation of this scales compared with measurementsshowed that the measurements for both sensors arereliable, and that their response is very close to thesimulations, showing the same tendency on bothsensors. Tendency apart, the values of the ampli-tude still didn’t exactly correspond, showing the re-sults of the approximations taken in the simulationperformed. It was a 2D model, therefore leavingout some 3D geometrical features that would in-fluence the signal. These measurements allowed aswell a good comparison between the two sensorsused. Even though having a lower SNR, sensor S2is capable of measuring higher amplitudes and hasa better spatial resolution than sensor S1.

With this work, we were therefore able to find aconfiguration with a very good performance in mag-netizing the magnetic ink, as well as validating thestate-of-the-art TMR sensors for this application.Furthermore, the foundations for a future develop-ment of the system has been set.

Future work in this project should include theoptimization of the sensors for this configuration.Even though a high spatial resolution sensor wasfound, the SNR is still low, requiring some futureimprovement. The CoCrPT scales, which proved tobe a good validation tool for the sensors can also beoptimized by fabricating higher thicknesses of alloyand therefore measuring higher signals, making amore versatile tool for different kind of studies.

AcknowledgementsThe author would like to thank Prof. Susana Fre-itas for the opportunity and the INESC-MN col-leagues for the incredible work environment, in spe-cific Karla for all the help.

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