ElectroHydroDynamic Atomisation
Unipolar and bipolar
characterisation and modelling
Sjaak Verdoold
ISBN 978-90-5335-532-9
ElectroHydroDynamic
Atomisation
Sjaak
V
erdoold
UitnoDiging
Voor het bijwonen van de
openbare verdediging
van mijn proefschrift.
Op maandag 2 april 2012
om 15.00 uur in de
Senaatszaal van de
Technische Universiteit
Delft, Mekelweg
5 te Delft.
Om 14.30 uur geef ik
een korte presentatie
over mijn
promotie-onderwerp.
Paranimfen:
Agnes Verdoold
Jos Verdoold
Sjaak Verdoold
Wilgenstraat 38,
2861 TP Bergambacht,
0182-351998
sjaak@verdoold.net
2012
Verdoold_omslag.indd 1 09-03-12 11:57Unipolar and bipolar characterisation and modelling
Proefschrift
ter verkrijging van de graad van doctor aan de Technische Universiteit Delft,
op gezag van de Rector Magnificus prof.ir. K.C.A.M. Luyben, voorzitter van het College voor Promoties,
in het openbaar te verdedigen op maandag 2 april 2012 om 15.00 uur
door
Sjaak VERDOOLD
Natuurkundig Ingenieur Technische Universiteit Delft
Copromotor:
Dr.ir. J.C.M. Marijnissen
Samenstelling promotiecommissie:
Rector Magnificus voorzitter
Prof.dr.ir. J.J. Heijnen Technische Universiteit Delft, promotor Dr.ir. J.C.M. Marijnissen Technische Universiteit Delft, copromotor Prof.dr. R.A. Roos Université de Maine, Frankrijk
Prof.dr. T. Ciach Warsaw University of Technology, Polen Prof.dr. A. Schmidt-Ott Technische Universiteit Delft
Prof.dr. J.J. Smit Technische Universiteit Delft Dr.ir. R. Hagmeijer Universiteit Twente
Prof.dr. E.J.R. Sudhölter Technische Universiteit Delft, reservelid
Copyright © 2012 by Sjaak Verdoold ISBN 978-90-5335-532-9
All rights reserved. No part of the material protected by the above copyright notice may be reproduced or utilised in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system without written permission from the author.
ElectroHydroDynamic Atomisation, often called electrospraying, is a way to dis-perse a liquid into droplets by exposing it to a strong electric field. Although the phenomenon that a liquid meniscus can deform into a conical shape under the influence of an electric field is already known for centuries, the interest in electrospraying grew substantially the last couple of decades. Especially the cap-ability to produce very small droplets with narrow size and charge distributions using electrospraying drew lots of attention. In addition, these droplets can be produced using relatively large nozzles (more than an order of magnitude larger than the droplet size) which reduces practical problems like clogging significantly and it was claimed that the technique is relatively energy efficient.
The particles created using EHDA are electrically charged and their polarity depends on the applied electric field. By using multiple EHDA-systems with dif-ferent polarities simultaneously, it becomes possible to create an aerosol of highly charged particles with different polarities. In such an aerosol particles with op-posite polarities will selectively attract and repel each other and selective coagu-lation will take place. This type of selective coagucoagu-lation is also called “bipolar coagulation”.
It has been shown in literature that bipolar coagulation can be used to cre-ate cocre-ated particles but also to have mixing and reactions within the resulting particles. Due to the small dimensions of the resulting droplets this enables to have materials mix or react with each other which on a larger scale do not mix or react. This offers unique new possibilities for many fields.
The goal of this thesis is to determine how the bipolar coagulation process can be scaled up. The main problem is that the liquid throughput of an electros-pray system is rather low and increasing it is not a real option because it changes the properties of the electrospray significantly. Hence the focus was on finding the best way to operate many electrospray systems simultaneously. It was also investigated whether the placement of the electrospray systems relative to each other had a significant influence on the final output. In order to be able to do this a numerical model was developed the results of which were validated using the results of measurements in an actual bipolar coagulation reactor.
During the process of designing and building the reactor to validate the nu-v
many electrosprays are to be monitored simultaneously. For this reason a new, generic classification was developed which does not exhibit this problem.
In order to obtain a generic classification for the various EHDA spray modes, a system was developed to analyse the current going through a spraying EHDA system. It was found that measurements of the current through an EHDA system provide valuable information of the actual situation of the spray system. Despite the simple measurement a clear correlation was observed between the current through the system and the behaviour of the liquid meniscus. It was also found that it is possible to classify spray modes up to and including the cone-jet mode by using at most 6 characteristic values based on the measured currents. Spray modes corresponding with higher field strengths were not investigated due to experimental limitations. Because the proposed classification does not depend on any material property of the sprayed liquid or on a specific geometry it can be considered a generic classification.
Extended measurements with different equipment and possibly with higher sampling rates may extend the classification to higher field strengths. The dis-charges that will start to gain importance will however most likely complicate the processing in that case.
The measured currents can also be used to determine the amount of energy fed to the spray system. These values were combined with the size and velocity data of the produced droplets (obtained through Phase Doppler measurements). Assuming the spray was axisymmetric an energy balance for the EHDA system was reconstructed for various heights below the nozzle. Overall it can be con-cluded that in most parts of the system the air drag is dominant and a surprising phenomenon is observed: the total amount of energy of the droplets seems to be slightly larger than the amount of energy put into the system. After a careful er-ror analysis, taking into account all measurement erer-rors and using a conservative approach in all cases, these results remain valid.
A 2D fixed-sectional population balance model was developed to model the development in time of the size and charge distribution of a charged aerosol. An existing approach was used for both dimensions and a coupling between the dimensions was added. The approach was also extended to be able to handle both positive, negative and zero values because in the charge dimension both polarities may occur. This resulted in a method in which the sections in both the size and the charge domain can be chosen freely.
The aerosol development inside a bipolar coagulation reactor was modelled us-ing a grid of coupled cells in each of which a 2D population balance was solved. By using knowledge about the sprays, the required computational time for a given resolution in the size and the charge domain could be reduced drastically. vi
agulation reactor. By using two fluorescent tracers for the different polarities, it was possible to use the colour content of the droplet as a marker for the polar-ity of the droplets. Using the colour content to separate the different polarities and the coagulated droplets and applying PIV to the result, it was possible to discriminate between the different “types” of particles using a single colour cam-era. The PIV results provide information about the dynamic behaviour of the droplets, information that cannot be obtained using the population balance mod-elling. Applying some simple averaging to the separated results yields results that can be compared with the modelling results. It was found that the charge on the droplets and the placement of the various nozzles had a significant influence on the results, especially on the coagulation rate. The model presented here is a good tool to optimise a bipolar coagulation reactor with respect to these factors.
ElectroHydroDynamic Atomisation (EHDA), ook wel electrospraying genoemd, is een methode om vloeistof te vernevelen door het in een sterk elektrisch veld te brengen. De laatste decennia is de aandacht voor electrospraying sterk toegeno-men, vooral omdat het met deze methode mogelijk is om aerosoldeeltjes te pro-duceren met een nauwe grootte- en ladingsverdeling. Bovendien kan er gebruik gemaakt worden van relatief grote spuitmonden waardoor praktische problemen zoals verstoppingen voorkomen kunnen worden en wordt er vaak gesteld dat de methode energie-efficiënt is.
De deeltjes die met EHDA worden gemaakt zijn elektrisch geladen, waarbij de polariteit afhankelijk is van het aangelegde veld. Door het gelijktijdig gebruik van meerdere systemen met verschillende velden is het daardoor mogelijk om een aerosol te creëren met sterk geladen deeltjes met verschillende polariteiten. De deeltjes met verschillende polariteiten zullen elkaar selectief aantrekken en afstoten waardoor er een selectieve coagulatie plaatsvindt. Deze selectieve coa-gulatie wordt ook wel aangeduid met de term “bipolaire coacoa-gulatie”.
Het is aangetoond dat het met behulp van bipolaire coagulatie ondermeer mo-gelijk is om gecoate druppels te maken en om menging en reacties te krijgen binnen de resulterende druppels. Vanwege de geringe afmetingen van de resulte-rende druppels is het hierdoor mogelijk om materialen te laten mengen en/of rea-geren die op grotere schalen niet mengen en/of rearea-geren, hetgeen unieke nieuwe mogelijkheden biedt.
Het doel van dit proefschrift is bepalen hoe het bipolaire coagulatie-proces het best opgeschaald kan worden. Probleem hierbij is dat de doorvoercapaciteit van een EHDA-systeem vrij klein is en dat deze niet eenvoudig te verhogen is zon-der de eigenschappen van de electrospray compleet te veranzon-deren. Daarom is er onderzocht hoe er op de beste manier zoveel mogelijk electrosprays tegelijkertijd gebruikt kunnen worden en of de plaatsing van de verschillende systemen ten opzichte van elkaar verschil maakt. Om efficiënt te kunnen optimaliseren is een model ontwikkeld. Dit model werd vervolgens gevalideerd met behulp van me-tingen in een bipolaire coagulatie-reactor.
Bij het ontwerpen en bouwen van deze reactor kwam naar boven en dat de meeste classificaties van de spray-modus van een electrospray zijn gedefinieerd ix
ontwikkeld die dit probleem niet heeft.
Om tot een generieke classificatie te komen voor de diverse EHDA spray-modes, is er een systeem ontwikkeld dat de stroom door een sproeiend EHDA systeem analyseert. Het is gebleken dat metingen van de stroom door een elec-trospray-systeem waardevolle informatie verschaffen over de actuele situatie van het systeem. Ondanks de eenvoudige metingen is er een duidelijke correlatie ge-vonden tussen de stroom door het systeem en het gedrag van het vloeistofop-pervlak in het systeem. Hierdoor is het mogelijk de stroom door het systeem te karakteriseren door middel van maximaal 6 kengetallen. Met deze kengetallen is het mogelijk gebleken om de uit de literatuur bekende spray-modes tot en met de cone-jet mode te classificeren. De spray-modes die optreden bij hogere veldsterk-tes zijn niet verder onderzocht vanwege experimentele beperkingen. De voor-gestelde classificatie is onafhankelijk van materiaaleigenschappen en gebruikte geometrieën en is derhalve een generieke classificatie.
Uitbreiding van de classificatie naar hogere veldsterktes is wellicht mogelijk. Hiervoor zijn dan wel vervolgmetingen met andere meetapparatuur en mogelijk hogere samplefrequenties nodig. Bovendien zal de dataverwerking waarschijn-lijk gecompliceerder worden doordat de ontladingen door de lucht een grotere invloed zullen krijgen.
De gemeten stromen kunnen ook gebruikt worden om de elektrische energie die aan het EHDA systeem wordt toegevoegd te bepalen. Door dit te combineren met de via Phase Doppler-metingen verkregen afmetingen en snelheden van de geproduceerde druppels is het mogelijk een energiebalans op te stellen voor het EHDA systeem. Omdat Phase Doppler-metingen puntmetingen zijn, zijn hierbij extra aannames noodzakelijk. In dit geval werd gebruik gemaakt van de axi-symmetrie in de onderzochte systemen. In de meeste delen van het systeem is de luchtweerstand dominant. Bovendien bleek dat in de meeste delen van het systeem de totale hoeveelheid energie van de druppels groter was dan de aan het systeem toegevoerde energie! Na een uitgebreide foutenanalyse, waarbij alle meet-onnauwkeurigheden werden meegenomen en in alle gevallen een conser-vatieve benadering werd gebruikt, bleven deze resultaten overeind. In de lite-ratuur wordt als mogelijke verklaring voor deze “energie-toename” gegeven het efficiënt verbreken van de waterstofbruggen in de vloeistof door het sterk ge-richte elektrische veld.
Om de ontwikkeling in de tijd van grootte- en ladingsverdeling van een gela-den aerosol te kunnen modelleren werd een 2D fixed-sectional-populatiebalans model ontwikkeld. Hierbij werd in beide dimensies gebruikgemaakt van een uit de literatuur bekend 1D fixed-sectional-model, waarbij echter een koppeling tussen beide dimensies noodzakelijk bleek. Daarnaast was een uitbreiding nood-x
(noodzakelijk wanneer sprays met beide polariteiten gemodelleerd worden). Dit resulteerde in een populatiebalans- model waarin de sectie-groottes in beide di-mensies vrij gekozen kunnen worden.
De ontwikkeling van een aerosol in een bipolaire coagulatie-reactor is gemo-delleerd door gebruik te maken van een 3D grid van gekoppelde modelleercel-len, waarbij in elke cel een 2D populatiebalans werd opgelost. Door gebruik te maken van kennis van de sprays die als input dienen voor de reactor, bleek het mogelijk de benodigde rekentijd drastisch te verlagen voor een gegeven resolutie in zowel het grootte- als het ladingsdomein.
Gecombineerde meerkleurige PIV-LIF-metingen zijn verricht in een daadwer-kelijke bipolaire coagulatie-reactor. Door voor beide polariteiten gebruik te ma-ken van verschillende fluorescerende tracers, bleek het mogelijk om de kleur van een druppel te gebruiken als markering voor de polariteit van die druppel. Op basis van de kleur bleek het mogelijk om onderscheid te maken tussen de diverse “druppeltypes” (positief, negatief en gecoaguleerd) waarbij de beelden van één kleurencamera voldoende waren. Het vervolgens toepassen van PIV op de indi-viduele druppeltypes binnen de beelden leverde informatie op over hun dyna-misch gedrag. Dit soort informatie kan niet verkregen worden door middel van populatiebalans-modellering en kan dan ook alleen indirect gebruikt worden bij de validatie van het model. Directe validatie van het model is wel mogelijk door te werken met gemiddelde waarden voor de verschillende druppeltypes.
De optimalisatiemogelijkheden zijn bekeken door verschillende geometrieën en verschillende spray-inputs te modelleren. Hieruit bleek dat de lading op de druppels en de plaatsing van de diverse sprays een grote invloed heeft op de uiteindelijke uitkomsten en in het bijzonder op de coagulatie-efficiëntie. Het ont-wikkelde model is dan ook zeer bruikbaar om een bipolaire coagulatie-reactor te optimaliseren.
Summary v
Samenvatting ix
List of Figures xix
List of Tables xxiii
1. Introduction 1
1.1. ElectroHydroDynamic Atomisation . . . 1
1.2. Bipolar coagulation . . . 2
1.3. Outline of the thesis . . . 3
Bibliography . . . 5
2. A generic electrospray classification 7 2.1. Introduction . . . 7
2.2. Experimental setup and techniques . . . 9
2.2.1. Current measurements . . . 11
2.2.1.1. Signal acquisition . . . 12
2.2.1.2. Signal correction . . . 12
2.2.2. Image acquisition . . . 13
2.3. Correlation between liquid meniscus and current characteristic . . 13
2.3.1. Stationarity . . . 14
2.3.2. Liquid meniscus vs measured current . . . 15
2.3.2.1. Pulsation stages . . . 15
2.3.2.2. Current characteristic interpretation . . . 18
2.3.3. Spray system vs measured current . . . 20
2.3.4. Irregular pulse shapes . . . 22
2.3.5. Overall correlation . . . 23
2.4. Influence of the experimental geometry . . . 24
2.4.1. Needle and nozzle with a plate as counter-electrode . . . 25
2.4.2. Needle and nozzle with a ring as counter-electrode . . . 30
2.4.3. Counter-electrode influence . . . 31
2.4.4. Polarity of the applied potential . . . 32 xiii
2.5. Current characteristics . . . 34
2.5.1. Time domain characteristic numbers . . . 36
2.5.1.1. DC-current, I . . . 36
2.5.1.2. (modified) Relative standard deviation, σ |I| . . . 36
2.5.1.3. Mean-median ratio,|I|| ˜I| . . . 37
2.5.1.4. Average development-relaxation ratios, CRand TR . . . 38
2.5.1.5. Average number of extrema per pulse, Nextr.,p . . . 39
2.5.2. Frequency domain characteristic numbers . . . 40
2.5.2.1. Normalised DC-power, PDC . . . 40
2.5.2.2. Offset of the linearly fitted cumulative spectrum, PLFCS . . . 40
2.5.3. Systematic overview . . . 41
2.5.3.1. DC-current . . . 42
2.5.3.2. (modified) Relative standard deviation RSDmod. . 44
2.5.3.3. Mean-median ratio,|I| |eI| . . . 47
2.5.3.4. Average development-relaxation ratios, CRand TR 48 2.5.3.5. Average number of extrema per pulse, Nextr.,p . . . 50
2.5.3.6. Normalised DC-power, PDC . . . 54
2.5.3.7. Offset of the linearly fitted cumulative spectrum, PLFCS . . . 55
2.6. Classification . . . 57
2.7. Conclusions . . . 59
List of Symbols . . . 63
Bibliography . . . 65
3. The efficiency of an EHDA system 69 3.1. Electrospray energy balance . . . 70
3.1.1. Spray model . . . 71 3.1.2. Energy input . . . 73 3.1.3. Energy output . . . 78 3.1.3.1. Kinetic energy . . . 78 3.1.3.2. Air drag . . . 79 3.1.3.3. Surface energy . . . 80 3.1.3.4. Ionisation . . . 81 3.1.4. Energy balance . . . 82 3.2. Experimental results . . . 83 3.2.1. Experimental setup . . . 83
3.2.2. Experimental data considerations . . . 85
3.2.3. Energy balance of a water spray . . . 87
3.2.4. Energy balance of an ethanol spray . . . 95 xiv
3.3. Conclusions . . . 98
List of Symbols . . . 99
Bibliography . . . 103
4. A 2D fixed-sectional approach to model the coagulation of (highly) charged aerosols 105 4.1. Introduction . . . 106
4.2. Previous work . . . 107
4.2.1. Solution of 1D PBE’s . . . 107
4.2.2. Solution of 2D PBE’s . . . 109
4.3. New formulation for solving 2D PBE’s . . . 110
4.3.1. Negative (pivot) values . . . 112
4.3.2. Coupling of the dimensions . . . 113
4.3.3. Discretization / efficiency . . . 114
4.3.3.1. Discretisation of the 2D system . . . 114
4.3.3.2. Boundary effect reduction . . . 115
4.3.4. Coagulation coefficient . . . 116
4.4. Validation and discussion . . . 116
4.4.1. Model validation . . . 116
4.4.2. Influence of section size on the results . . . 120
4.4.3. Boundary effect reduction . . . 121
4.4.4. Model efficiency . . . 121
4.4.5. Evolution of the volume-charge distribution . . . 122
4.5. Conclusions . . . 124
List of Symbols . . . 124
Bibliography . . . 127
5. Bipolar coagulation measurements 129 5.1. Introduction . . . 129
5.2. Particle Image Velocimetry . . . 131
5.2.1. The PIV approach . . . 131
5.2.2. Interrogation area size . . . 134
5.2.3. Measurement accuracy . . . 135
5.2.3.1. Particle losses . . . 135
5.2.3.2. Velocity gradients . . . 135
5.2.4. Increasing data yield . . . 136
5.2.4.1. Window offsetting . . . 136
5.2.4.2. Adaptive window sizing . . . 137
5.2.4.3. Image deformation . . . 137 5.2.5. Subpixel interpolation . . . 138 5.2.5.1. Peak-locking . . . 138 5.2.6. Data validation . . . 139 5.2.7. Data replacement . . . 140 xv
5.2.8. Data reduction . . . 141
5.3. Laser Induced Fluorescence . . . 141
5.3.1. Fluorescence . . . 142
5.3.2. Particle property dependency . . . 143
5.3.3. Planar laser induced fluorescence . . . 144
5.4. Image acquisition . . . 144 5.4.1. Tracer particles . . . 144 5.4.2. Illumination . . . 145 5.4.3. Optics . . . 146 5.4.4. Image recording . . . 148 5.4.4.1. Colour CCD’s . . . 148 5.4.4.2. White balance . . . 149 5.4.4.3. CCD data transfer . . . 150 5.5. Image processing . . . 150 5.5.1. Background subtraction . . . 151 5.5.2. Histogram stretching . . . 151 5.5.3. Colour separation . . . 152 5.6. Experimental . . . 154 5.6.1. Experimental approach . . . 156 5.6.1.1. Particle movement . . . 157 5.6.1.2. Particle polarity . . . 157 5.6.2. Fluorescent solutions . . . 158 5.6.2.1. Fluorescent tracers . . . 160 5.6.2.2. Spraying performance . . . 161 5.6.2.3. Surfactants . . . 163
5.6.2.4. Determining the optimal solutions . . . 164
5.6.3. Image separation . . . 173
5.6.3.1. Overexposure . . . 176
5.6.3.2. Overexposure correction . . . 176
5.6.4. Experimental setup . . . 179
5.6.5. Electric fields in the reactor . . . 185
5.6.5.1. Test setup . . . 186
5.6.5.2. Different nozzle settings . . . 190
5.6.6. Deposition . . . 194
5.6.7. Colour based image separation results . . . 197
5.7. Summary and conclusions . . . 200
List of Symbols . . . 202
Bibliography . . . 205
6. Modelling a bipolar-coagulation reactor using coupled population bal-ances 209 6.1. Introduction . . . 210 xvi
6.2. Modelling approach . . . 211
6.2.1. Spatial grid . . . 212
6.2.2. Coupling of the modelling cells . . . 214
6.2.2.1. Electric field . . . 215 6.2.2.2. Airflow . . . 216 6.2.2.3. Gravity . . . 216 6.2.2.4. Combined coupling . . . 217 6.2.3. Deposition . . . 217 6.2.4. Aerosol input . . . 218 6.3. Experimental validation . . . 219 6.4. Results . . . 221
6.4.1. Steady state results . . . 221
6.4.2. Particle concentrations . . . 222
6.4.3. Space charge / electric fields . . . 225
6.4.4. Deposition . . . 229
6.4.5. Optimisation . . . 231
6.4.5.1. Experimental spray conditions . . . 231
6.4.5.2. Cone-jet spray conditions . . . 233
6.5. Conclusions . . . 235
6.A. Experimental details . . . 236
6.A.1. Setup . . . 236 6.A.2. LIF . . . 237 6.A.3. PIV . . . 238 List of Symbols . . . 238 Bibliography . . . 241 7. Conclusions 243 A. Accuracy of the EHDA efficiency results 247 A.1. Measurement accuracies . . . 247
A.1.1. PDPA measurements . . . 247
A.1.2. Potential difference . . . 248
A.1.3. Measured current . . . 248
A.1.4. Liquid flow rate . . . 251
A.1.5. Capillary diameter . . . 252
A.1.6. Vertical positioning . . . 252
A.2. Accuracy of the energy inputs . . . 252
A.2.1. Electrical input power, Pel.,in. . . 252
A.2.2. Pump input power, Ppump . . . 253
A.2.3. Gravitational potential energy, Pgrav.,z . . . 254
A.2.4. Surface energy input power, Psurf.,in . . . 255
A.3. Accuracy of the energy outputs . . . 255
A.3.1. Measured liquid volume . . . 256 xvii
A.3.2. Measurement volume constant . . . 257
A.3.3. Kinetic power in a modelling region . . . 259
A.3.4. The total kinetic power . . . 261
A.3.5. Surface power in a modelling region . . . 263
A.3.6. The total surface power . . . 264
A.4. Accuracy of the system efficiency . . . 265
A.5. System efficiency accuracy using characteristic values . . . 268
List of Symbols . . . 268
List of Publications 273
Acknowledgements / Dankwoord 275
Curriculum Vitae 277
2.1. Schematic representation of the setup used to measure the current
through an electrospray system. . . 9
2.2. A schematic overview of the electrospray configuration types. . . . 10
2.3. Overlay of 650 triggered current pulses of a typical stationary elec-trospray together with the corresponding distribution of the inter-peak times. . . 14
2.4. The tip of the liquid meniscus at various moments during a current pulse together with the corresponding characteristic pulses. . . 16
2.5. The contours of the tip of the liquid meniscus of figure 2.4 for vari-ous moments during a pulsation. . . 17
2.6. The liquid flow as function of time assuming that the cone-jet dur-ing a pulsation is semi-steady and inverted scaldur-ing-laws can be used to determine the liquid flow rate from the measured currents. 19 2.7. The reconstructed spray system for various moments during a current-pulse. . . 21
2.8. Snapshots and corresponding current signal of salt water being sprayed in the dripping mode. . . 22
2.9. Irregular pulse shapes for the lower field strengths at the start of the pulsating behaviour. . . 23
2.10. Typical currents through a needle-plate system. . . 26
2.11. Typical currents through a nozzle-plate system. . . 27
2.12. Typical currents through a needle-ring system. . . 28
2.13. Typical currents through a nozzle-ring system. . . 29
2.14. Typical currents through a needle-ring system with a negative po-tential on the counter electrode. . . 33
2.15. Some characteristic currents through an electrospray system spray-ing ethanol and ethylene glycol. . . 35
2.16. The (cumulative) power spectrum density for the signal depicted in figure 2.11h. . . 41
2.17. The DC-current as function of the applied potential difference. . . . 43
2.18. The (modified) relative standard deviation, RSDmod., as function of the applied potential difference. . . 45
2.19. The |I| |eI| -ratio as function of the applied potential difference. . . 47
2.20. The average development-relaxation ratio CRas function of the
ap-plied potential difference. . . 49 2.21. Average number of extrema per pulse, Nextr.,p, as function of the
applied potential difference. . . 51 2.22. The normalised DC-power, PDC, as function of the applied
poten-tial difference. . . 53 2.23. PLFCSas function of the applied potential difference. . . 56
3.1. A schematic representation of the electrospray system and the mod-elling approach. . . 70 3.2. The system used to get an estimate of the surface energy input. . . 76 3.3. A schematic illustration of the measurement setup. . . 84 3.4. The average droplet diameter per measurement height. . . 86 3.5. The droplet velocity at various points in the water spray. . . 88 3.6. The droplet diameter at various positions in the water spray. . . 89 3.7. The evaporation characteristic of a 14 µm water droplet for a
num-ber of relative humidities at 293 K. . . 90 3.8. The diameter and velocity distributions of a point in the centre of
the spray. . . 91 3.9. The overall efficiency and the most important input and output
terms using both the characteristic values (“C.V.”) and the indi-vidual particle data (“I.P.”). . . 94 4.1. The treatment of particles formed due to aggregation which do not
coincide with one of the pivots according to the fixed pivot method. 108 4.2. Assignment of a new particle(u, p)formed by coagulation to the
surrounding pivots. . . 109 4.3. Assignment of a new particle(u, p)formed by coagulation to the
surrounding pivots in the new 2D approach. . . 111 4.4. The distribution factors a(u)and b(u)around the origin for
dimen-sions that deal with positive and negative values for the moment r1and r2. . . 112
4.5. The time evolution of the charge distribution given by equation 4.19 according to the current model and a number of results from literature. . . 118 4.6. The time evolution of various initial charge distributions for an
initially monodisperse aerosol of diameter 1 µm. . . 119 4.7. The effect of the section-size on the results of the model for two
different initial distributions. . . 120 4.8. The volume-charge distribution of an initially monodisperse
aero-sol with a charge distribution given by equation 4.21 with A=10 and B=10. . . 123 xx
5.1. A typical PIV set-up. . . 131 5.2. Illustrated example of how the cross-correlation plane values are
determined. . . 133 5.3. An implementation of determining the cross-correlation function
by using fast Fourier transforms. . . 134 5.4. Schematic illustration of the idea behind image deformation. . . 137 5.5. The effect of peak-locking on the distribution of subpixel values. . . 139 5.6. Fluorescence adsorption and emission spectrum of Rhodamine 6G
as function of the wavelength. . . 142 5.7. Sketch of a possible optical configuration to transform a laser beam
into a laser sheet. . . 146 5.8. Illustration of a typical Bayer mask and its corresponding virtual
pixels. . . 149 5.9. The HSL colour space and its relation with the RGB colour space. . 154 5.10. The colour content of an image from a spray doped with Fluorescein.155 5.11. The absorption and emission spectra of some fluorescent tracers
from table 5.1. . . 161 5.12. The conductivity of ethylene glycol as function of the
concentra-tion of fluorescent dye dissolved in it. . . 167 5.13. The colour content of images taken from sprays containing Tinopal
CBS-X and Riboflavin. . . 173 5.14. The colour content of images taken from sprays containing the
various tracers. . . 174 5.15. The effect of reducing the blue component on the hue and
satura-tion content of the image for several correcsatura-tion factors. . . 177 5.16. The hue histograms of an image containing Rhodamine 101 doped
aerosol for various reduction factors of the blue component in the image. . . 178 5.17. A schematic overview and a cross section of the setup used in the
experiments. . . 180 5.18. The average airflow in the reactor. . . 181 5.19. The size distributions of the aerosols used for the fluorescence
meas-urements, using the optimal Rhodamine 101 and Eosine Y solutions. 183 5.20. A schematic horizontal cross section of the reactor illustrating the
numbering scheme used in the experiments. . . 186 5.21. PIV results and calculated electric fields for a number of
configur-ations. . . 187 5.22. Numerical results including space charge for the configurations of
figure 5.21. . . 189 5.23. Experimental and numerical results for some configurations. . . 191 5.24. Contour lines and strength of the electric field in the reactor for the
configuration shown in 5.23a and 5.23c. . . 193 xxi
5.25. Deposition patterns on the the floor and the walls of the reactor taken in a so-called ”darkroom“. . . 196 5.26. Image separation based on the colour content of the image. . . 198 5.27. The PIV results for the images from figure 5.26. . . 199 6.1. The approach used to model a rectangular reactor using
rectangu-lar modelling cells of arbitrary dimensions. . . 212 6.2. The experimental setup used to validate the modelling results. . . . 219 6.3. Top view of the laser sheet in the experiments with the different
positions of the electrosprays. . . 220 6.4. Characteristic properties of the simulated reactor with 2 negative
particle sources and 1 positive particle source for 2 different air flows.221 6.5. Experimental, segmented and simulated results of the same
exper-iment. . . 224 6.6. Simulated coagulated-particle concentration. . . 226 6.7. Electric field strength and direction for both the externally applied
electric field and the space charge for the steady state experimental configuration. . . 227 6.8. PIV results illustrating the particle movement in the reactor due to
the influence of the externally applied electric field. . . 228 6.9. The deposition for the horizontal and vertical walls in the
simu-lated experimental configuration. . . 230
2.1. The used configurations. In each configuration the liquid, its flow rate and the applied potential can still be freely adjusted. . . 11 2.2. Overview of the proposed classification and a number of
classific-ations reported in literature. . . 60 3.1. Calculated number of droplets passing through the regions shown
in figure 3.1 at z=8 mm. . . 92 3.2. The input power for this system for the measurements at different
z positions. . . 93 3.3. The relative accuracies for the energy input terms of the water spray. 93 3.4. The energy input to the ethanol electrospray for z =6.5 mm, z =
8.5 mm and z=10.5 mm. . . 95 3.5. The relative accuracies for the energy input terms of the ethanol
spray. . . 95 3.6. The energy output terms for both the method using characteristic
values and the method using the properties of individual particles. 96 3.7. The efficiency of the ethanol electrospray at different heights for
the method using characteristic values. . . 97 3.8. The efficiency of the ethanol electrospray at different heights for
the method using individual particles. . . 97 4.1. The required computational times for the simulations depicted in
figures 4.5-4.7. . . 122 5.1. The various fluorescent tracers used in this research together with
some characteristic properties. . . 160 5.2. The solvents considered together with the corresponding density
(ρs), surface tension (γ), vapour pressure at T=293 K (ps) and
mo-lecular weight (MW). . . 162 5.3. The surfactants considered in this research. . . 163 5.4. Summary of the tested vegetable oil based solutions. . . 165 5.5. Summary of the test results for ethylene glycol based solutions. . . 169 5.6. Summary of the test results for glycerol based solutions. . . 171 xxiii
6.1. The composition of the reactor output and the deposition in the reactor for several configurations using the “experimental sprays”. 232 6.2. The composition of the reactor output and the deposition in the
reactor using “standard” electrosprays in the cone-jet mode. . . 234
1
Introduction
1.1. ElectroHydroDynamic Atomisation
ElectroHydroDynamic Atomisation, often called electrospraying, is a way to dis-perse a liquid into droplets by exposing it to a strong electric field. Although the phenomenon that a liquid meniscus can deform into a conical shape under the influence of an electric field is already known for centuries, the interest in electrospraying grew substantially the last couple of decades. Especially the cap-ability to produce very small droplets with narrow size and charge distributions using electrospraying drew lots of attention. In addition, these droplets can be produced using relatively large nozzles (more than an order of magnitude larger than the droplet size) which reduces practical problems like clogging significantly and it was claimed that the technique is relatively energy efficient.
Depending on the used geometry and the applied electric field, electrohydro-dynamic atomisation can take place in many forms and may be either stable or wildly fluctuating. To be able to compare the various experimental results and to distinguish between the various appearances of electrohydrodynamic atomisa-tion a number of classificaatomisa-tions have been proposed [7, 8, 14, 18, 19].
Most research about electrospraying has been focusing on the so-called cone-jet mode in which the meniscus has a conical shape (the so-called Taylor cone, named after Taylor who was the first to explain this rather special shape, [20]). The reason for this focus is twofold. First both the size and the charge distribu-tion of the produced particles is very narrow in this mode, which is desirable in 1
many applications. Second due to the stability of this mode analysing and char-acterising its behaviour becomes feasible. As a result, for the cone-jet mode so-called scaling-laws based on both experimental and numerical results have been determined [12, 16, 15, 11]. These scaling laws relate either the size of the pro-duced droplets or the current through the system to several material properties of the liquid being sprayed and the applied flow rate. Especially when develop-ing new applications, these scaldevelop-ing-laws can be very useful.
The liquid throughput of an electrospray system is relatively low, especially for the spray modes that have been studied most extensively. Increasing the liquid flow rate is not a real option as this will change the spray mode and as a res-ult the size and charge distribution of the produced droplets (which often is the main reason to consider electrospraying). Hence increasing the liquid through-put is generally done by increasing the number of spray systems. Although this approach seems really simple, a massive scale-up in this way is complicated by the charge on the individual droplets which is relatively high. For significant up-scaling, neutralisation equipment often is needed.
Electrospraying has been used in a wide variety of applications. It has for ex-ample been used to create pharmaceutical particles [22, 6, 10, 13] and tailor-made, reacting or encapsulated particles [3, 2, 4]. It was also used to create emulsions [1] and thin films [17]. These applications all use the the relatively narrow size and charge distribution of the produced droplets. Another important field of application is the use in mass spectrometry setups [9, 5, 21]. In these setups elec-trospraying is used as a mild ionisation technique which improves the efficiency of the setup. The droplet size is not crucial in such setups and neither is the exact spraying mode.
1.2. Bipolar coagulation
As already mentioned the particles produced using electrospraying are charged, and often they are relatively highly charged. The polarity of their charge depends on the field that was used to produce them. By using multiple spray systems pro-ducing particles with opposite polarities, the oppositely charged particles will selectively coagulate. This is the so-called bipolar coagulation technique. Com-bined with a smart choice of the liquids that are atomised, it enables to create coated particles [4, 6], hollow particles and particles that mix after they coagulate which may lead to reactions inside them [2].
In all these cases the resulting particles have a much lower charge than the ini-tial droplets because opposite charges are involved, so bipolar coagulation helps to neutralise the particles. This neutralisation is highly required in both med-2
ical and larger scale applications for several reasons. For medical applications a significant charge on the produced particles may for example change the de-position behaviour of inhaled medicine and the accompanied charge may lead to unexpected and unwanted side effects. For larger scale systems or reactors the high charge on the produced droplets will quickly lead to huge space charges if unipolar sprays are employed. Due to these space charges the spray systems may stop spraying or the setups may even physically break down. In such cases the produced particles are often discharged using a corona discharge (see for ex-ample [13]). This requires however a more complicated setup that may be very unpractical and difficult to optimise for larger scale systems. For such systems, bipolar coagulation can be a very simple, elegant and efficient way to neutralise the produced particles. However, optimisations regarding the placement of the various spray systems may be needed to obtain the best results.
Another reason to discharge the produced droplets is the fact that there is a maximum amount of charge, the so-called Rayleigh charge, a droplet can con-tain. This Rayleigh charge is a function of the droplet size: larger droplets can contain larger amounts of charge. When a charge larger than this maximum is present on a droplet, the droplet will become unstable and form multiple smal-ler droplets. As this changes the average droplet size and broadens the size and charge distributions, it is often attempted to neutralise the droplets before they reach their maximum charge due to evaporation.
1.3. Outline of the thesis
This research aims to develop an optimised scaled up bipolar coagulation reactor. To achieve that goal several problems had to be straightened out.
As mentioned above, scaling up an electrospray process to a large extent means increasing the number of spray systems if the advantageous properties of the electrospray results are to be preserved. For a small number of systems this is trivial, but for a larger number of systems the systems start to interact with each other through the space charge. This may lead to different spray modes for the various sprays and degraded size and charge distributions.
Small setups can easily be adjusted when a change in spray mode or an un-wanted spray mode is observed. For laboratory setups, the techniques used in literature can be employed to determine the spray mode. Due to the present clas-sifications in literature, the techniques do however often require optical access to the spray system and rather expensive equipment. Consequently in general only a few systems can be monitored simultaneously when a large number of systems are being operated and rather complicated setups are required to provide the op-tical access. Hence these techniques are not really useful in the current context.
In chapter 2 this problem is solved by focusing on the electric current through 3
a spray system. This requires a very simple measurement which can easily be applied simultaneously to a large numbers of systems and does not require any optical access. Based on the measured currents a new generic classification of the spray modes is proposed which encompasses the classifications presented before in literature to a large extent.
The current through the system can also be used to determine the amount of electrical energy put into the system. In chapter 3 this is used together with the results of Phase Doppler measurements to build an energy balance for the EHDA system. This made it possible to estimate the efficiency of an EHDA.
To determine the configuration for optimal bipolar coagulation a numerical model was used. The most detailed results would follow from tracking the in-dividual particles and their coagulation. The amount of droplets produced by a single EHDA system is however enormous and this only increases if the number of systems is increased. Hence a statistical approach, a population balance model, was used. For such a system the computational requirements do not depend on the number of particles that are being modelled but on the required resolution in each dimension. For bipolar coagulation a 2D population balance is needed because both the particle size and the particle charge need to be taken into ac-count. In addition, a single 2D population balance treats the complete system with all individual sprays as a single unit. This renders it impossible to optimise the complete system by changing the relative placement of the individual sprays, so a system of coupled population balances is needed . Because solving a stand-ard 2D population balance requires quite some computations, taking into account the available computing power leads to the conclusion that either the results are obtained with a very low spatial and/or charge resolution or an unacceptable large problem that has to be solved. Chapter 4 solves this by developing a 2D fixed-sectional approach to the 2D population balance. This approach makes it possible to reduce the amount of required processing power because it allows ar-bitrary sections in both dimensions. Using knowledge about the spray systems then makes it possible to reduce the amount of sections in both dimensions which reduces the required processing power considerably.
Multicolour PIV-LIF measurements were performed in an actual bipolar coagu-lation reactor to gain more insight in the bipolar coagucoagu-lation process. In chapter 5 these experiments are described together with the obtained experimental res-ults. In chapter 6 this reactor is modelled by an array of coupled 2D population balances using the 2D fixed-sectional approach developed in chapter 4. The nu-merical results are then compared with the experimental results.In this chapter the modelling results are also compared with experimental results of measure-ments in a bipolar coagulation reactor.
At the end of the thesis a summary of the results is presented.
[1] J. Abu-Ali and S.A. Barringer. Method for electrostatic atomization of emul-sions in an ehd system. Journal of Electrostatics, 63(5):361–369, May 2005. [2] J.-P. Borra, D. Camelot, K.-L. Chou, P. J. Kooyman, J. C. M. Marijnissen,
and B. Scarlett. Bipolar coagulation for powder production: Micro-mixing inside droplets. Journal of Aerosol Science, 30(7):945–958, 1998.
[3] J.-P. Borra, D. Camelot, J. C. M. Marijnissen, and B. Scarlett. A new produc-tion process of powders with defined properties by electrohydrodynamic atomization of liquids and post-production electrical mixing. Journal of elec-trostatics, 40&41:633–638, 1997.
[4] D. Camelot. The bipolar coagulation process for powder production. PhD thesis, Delft University of Technology, 1999.
[5] Nadja B. Cech and Christie G. Enke. Practical implications of some recent studies in electrospray ionization fundamentals. Mass Spectrometry Reviews, 20(6):362–387, 2001.
[6] Tomasz Ciach. Microencapsulation of drugs by electro-hydro-dynamic at-omization. International Journal of Pharmaceutics, 324(1):51–55, October 2006. [7] M. Cloupeau and B. Prunet-Foch. Electrostatic spraying of liquids: Main
functioning modes. Journal of Electrostatics, 25(2):165–184, October 1990. [8] M. Cloupeau and B. Prunet-Foch. Electrohydrodynamic spraying
function-ing modes: a critical review. J. Aerosol Sci, 25(6):1021–1036, September 1994. [9] Th. Dülcks and R. Juraschek. Electrospray as an ionisation method for mass
spectometry. Journal of Aerosol Science, 30(7):927 – 943, 1999.
[10] Marjan Enayati, Ming-Wei Chang, Felix Bragman, Mohan Edirisinghe, and Eleanor Stride. Electrohydrodynamic preparation of particles, capsules and bubbles for biomedical engineering applications. Colloids and Surfaces A: Physicochemical and Engineering Aspects, In Press, Corrected Proof:–, 2010. [11] Alfonso M. Gañán Calvo. The surface charge in electrospraying: its nature
and its universal scalings laws. Journal of Aerosol Science, 30(7):863–872, 1999.
[12] A.M. Gañán-Calvo, J. Dávila, and A. Barrero. Current and droplet size in the electrospraying of liquids. scaling laws. Journal of Aerosol Science, 28(2):249–275, 1997.
[13] K. B Geerse. Applications of electrospray: from people to plants. PhD thesis, Delft University of Technology, 2003.
[14] J. M. Grace and J. C. M. Marijnissen. A review of liquid atomization by electrical means. Journal of Aerosol Science, 25(6):1005–1019, 1994.
[15] R. P. A. Hartman, D. J. Brunner, D. M. A. Camelot, J. C. M. Marijnissen, and B. Scarlett. Electrohydrodynamic atomization in the cone-jet mode physical modeling of the liquid cone and jet. Journal of Aerosol Science, 30(7):823–849, 1999.
[16] R.P.A. Hartmann. Electrohydrodynamic atomization in the cone-jet mode, From Physical Modeling to powder production. PhD thesis, Delft University of Tech-nology, 1998.
[17] A. Jaworek. Electrospray droplet sources for thin film deposition. Journal of Materials Science, 42(1):266–297, January 2007.
[18] A. Jaworek and A. Krupa. Classicification of the modes of ehd spraying. Journal of Aerosol Science, 30(7):873–893, August 1999.
[19] R. Juraschek and F.W. Röllgen. Pulsation phenomena during electrospray ionization. International Journal of Mass Spectrometry, (177):1–15, april 1998. [20] Geoffrey Taylor. Disintegration of water drops in an electric field.
Proceed-ings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 280(1382):383–397, 1964.
[21] Junfei Wei, Wenqing Shui, Feng Zhou, Yu Lu, Kankai Chen, Guobing Xu, and Pengyuan Yang. Naturally and externally pulsed electrospray. Mass Spectrometry Reviews, 21:148–162, 2002.
[22] C.U. Yurteri, R.P.A. Hartman, and J.C.M. Marijnissen. Producing pharma-ceutical particles via electrospraying with an emphasis on nano and nano structured particles - a review. KONA Powder and Particle Journal, 28:91–115, 2010.
2
A generic electrospray
classification
One of the major unknown factors when working with electrosprays is the precise spray mode that is obtained when operating an electrospray. How-ever, as the spray mode determines to a significant extent the properties of the obtained particles, knowing the spray mode is crucial for many applic-ations. Currently the spray modes presented in literature are defined based on optical observations of the liquid meniscus. In a laboratory setup this approach works fine but in many other situations such an approach is not possible. In this chapter a different approach is developed which uses meas-urements of the current through an electrospray system to determine the spray mode of the system. These measurements are relatively simple and can be implemented cost effectively. Although not all spray modes can be distinguished using this approach, the spray modes used in most applica-tions can be identified.
2.1. Introduction
Due to its extraordinary properties the number of applications using Electro-Hydrodynamic Atomisation (EHDA) has increased dramatically during the last 7
decades. EHDA, which is sometimes also called electrospraying, is among many other things applied in crop spraying [19], the creation of emulsions [1], the cre-ation of thin films [23] and the production of particles with a very specific size and/or composition [6, 5, 8, 15, 13, 33, 10]. The technique is also widely used as a soft but efficient ionisation technique in mass spectrometry setups [9, 32, 14]. The wide variety in applications together with their rather different requirements illustrate the versatility of the technique. For correct operation of all applications it is however crucial that the electrospraying happens in a well-defined way.
It is well known that the behaviour of an electrospray depends strongly on the electric field it experiences, the material properties of the used liquid, the elec-trode geometry and other boundary conditions. In literature a number of classi-fications have been proposed to distinguish between the various spray situations [12, 11, 20, 24, 25]. These classifications are mainly based on visual observations of the liquid meniscus. Together with a mapping of the effect of experimental conditions like the applied liquid flow rate and the applied electric field, these classifications are helpful in getting the wanted electrospray behaviour. How-ever, even with those classifications, it remains necessary to check whether a cer-tain spraying “mode” was obcer-tained. For real-life and/or upscaled applications, this often becomes unpractical and expensive so a different approach is needed.
It was found that for the geometries and liquid flow rates used in mass spec-trometry setups, the current through the system and the behaviour of the liquid meniscus are correlated [25, 32, 9, 26]. A similar observation was made for un-forced nano-electrosprays [4, 28, 3]. These correlations seem to be specific for a given liquid and configuration. Hence they are not suitable to create a gen-eral mapping between the current through the system and the spraying mode. It should also be noted that both a mass spectrometry and an unforced nano-electrospray setup employ a relatively small nozzle and relatively low flow rates which results in relatively small spray systems. The effect of larger nozzle dia-meters and/or higher flow rates on the correlation remains to be investigated.
Here it is attempted to find a general mapping between the properties of the current through the system and the spray mode, that is independent of the ma-terial properties of the liquid, the electrode geometry and the other boundary conditions. To accomplish this, it is assumed that a change in the liquid meniscus is “directly” reflected as a change in the current through the system and that a change in the current reflects a change in the liquid meniscus. This assumption has already been shown to be valid for systems with a small nozzle diameter and relatively low flow rates, so for systems in which the amount of liquid close to the nozzle is low [25, 4, 26]. For systems with a relatively large amount of (semi-conducting) liquid close to the nozzle the validity of the assumption has not been shown yet. The electrical relaxation time, τe, defined as
τe= e
Kl (2.1)
Figure 2.1.:Schematic representation of the setup. Liquid was pumped through a metallic nozzle by a syringe pump. By applying a high potential to either the collector plate or an optional ring electrode an electrospray system was created. The current through the system was measured at the nozzle side and optionally used to trigger a camera system.
with e being the permittivity of the liquid and Klbeing the bulk liquid
conductiv-ity, is rather small for most liquids used in electrospraying. Together with the fact that the absolute liquid volumes used in electrospraying are always relatively small, it can be expected that even for the larger systems changes in the liquid meniscus are “directly” reflected in the currents through the system, especially when the currents are measured close to the liquid meniscus.
2.2. Experimental setup and techniques
The experimental setup used in this study is shown schematically in figure 2.1. In the experiments a syringe pump (Harvard, PHD2000) was used to pump li-quid through a nozzle at flow rates in the range of 0.1 mL h−1to 10 mL h−1. A number of different nozzles were used, all with outer diameters= 0.71 mm. In order to ensure that the measurements of the current were performed close to the liquid meniscus, all nozzles were made of conducting (metallic) materials and the current measurements were performed at the nozzle. At some distance from the nozzle a conducting collector plate was located onto which the created droplets deposited. In some experiments a ring electrode was placed between the nozzle 9
(a)Type I (b)Type II (c)Type III (d)Type IV
Figure 2.2.:A schematic overview of the electrospray configuration types used.
and the collector plate. An electric field was created by applying a high electric potential to either the collector or the ring electrode. When a ring electrode was used, the collector was kept at ground potential. Figure 2.2 gives an schematic overview of the various nozzle-ring-plate combinations that were used in this study. The main difference between the “needle type” (Type I and II, figures 2.2a and 2.2b) and the “nozzle type” (Type III and IV, figures 2.2c and 2.2d) nozzles is the ratio of the inner and outer diameter of the nozzle. For the needle type nozzles the inner diameter, dcap,in, is comparable to the outer diameter, dcap, whereas the
nozzle type nozzles have an inner diameter of 0.2 mm which is significantly smal-ler than dcapfor the nozzles used in the current experiments. This leads to rather
different situations regarding wettable surface, liquid flow etc. for both generic types. The different nozzle shapes also lead to slightly different electric fields at the liquid meniscus. Together with the extra ring electrode used in a number of configurations, it is clear that the electric fields in the configurations differ signi-ficantly, leading to a different spraying behaviour. In all configurations the devel-opment of the liquid meniscus will be reflected in the measured current through the system. A classification based on this current should therefore be valid for all configurations. Direct comparisons between results of the various configurations might not be completely justified. However, the physics will be the same in all situations and a possible general method should work for all configurations. For convenience table 2.1 gives an overview of the used configurations. It should be noted that depending on the liquid, the applied liquid flow rate and the applied 10
Config. Type dcap dcap,in Lp dring Lr Rmeas. G [mm] [mm] [mm] [mm] [mm] [Ω] [-] 1 II 0.91 0.61 11 20 70 11450 500 2 I 0.91 0.61 27 - - 11460 500 3 II 0.91 0.61 61 20 12 11460 500 4 III 2.00 0.20 15 - - 11460 100 5 IV 2.00 0.20 58 20 12 1147 500 6 IV 8.00 0.20 65 20 15 1147 500 7 I 0.71 0.41 24 - - 46800 10 8 I 0.91 0.61 22 - - 1147 500 9 II 1.83 1.55 47 20 12 1147 500 10 I 0.71 0.41 30 - - 1×106 1 11 II 1.65 1.37 47 20 12 11460 100
Table 2.1.:The used configurations. In each configuration the liquid, its flow rate and the applied potential can still be freely adjusted.
potentials, each configuration can be used for a variety of experiments.
In order to avoid liquid from building up on the flat collector, a thin sheet of tissue was draped over the collector to drain possible excess liquid.
2.2.1. Current measurements
The current through the spray system was measured by a differential ampli-fier (Burr-Brown, INA 110KP, ) monitoring the voltage across a resistor (Rmeas.)
placed between the nozzle and ground potential. This results in direct measure-ments of the complete current through the system. Applying the potential to the nozzle and measuring at the counter electrode results in similar measurements, but in such a situation the possible presence of ionisation requires extra simul-taneous measurements or extra assumptions. Both the amplifier gain (G) and the value of the measurement resistor could be changed in order to achieve an optimum regarding measurement accuracy and the introduced (and amplified) thermal noise (see appendix A). Moreover the measurement resistance was al-ways intentionally kept relatively small (<99.7 kΩ) to minimise its influence on
the spraying behaviour. Using conductive nozzles enabled to measure the cur-rent through the spray system effectively very close to the possibly fluctuating liquid meniscus. This minimised the influence of the resistance and capacitance of the liquid inside the “filled nozzle”.
2.2.1.1. Signal acquisition
The amplified signals were recorded by either a storage oscilloscope (LeCroy 9354) or a computer-based data acquisition card. The sample rates varied but were always > 5 kHz. Parvin et al. found that the frequencies in the current through an electrospray system can, at least for their experiments, roughly be estimated by a simple mechanical model describing the natural oscillation on a spherical drop due to capillary waves [29]. They found that the lowest excitation mode of such a drop, given by
f0= 1 2π· 8γ ρR3 12 (2.2) reasonably matches with their experimental results. In this equation f0 is the
frequency of the current-oscillations, ρ and γ are respectively the density and the surface tension of the liquid and R is the radius of the meniscus at the tip of the nozzle (so dcap,in < R < dcap). For a needle-type nozzle (Type I) with
dcap = 0.26 mm they reported principal frequencies of at most a few kilohertz.
Stachewicz et al. used a more fundamental approach and studied the electrical and hydrodynamic phenomena and their relaxation times for so-called single event electrospraying [30]. Taking into account the actual shape of the nozzle and liquid meniscus they obtained results that also resulted in frequencies of at most a few kilohertz. As the nozzle dimensions in this study are significantly larger than the nozzles used by Parvin et al. and Stachewicz et al., it was assumed that 5 kHz was sufficient to capture the most relevant parts of the current-signal. For small and fast fluctuations these sample rates will not be sufficient to capture all details of the signal, but such small fluctuations might not even be detectable us-ing very high sample rates due to the capacitance of the nozzle [30]. A number of experiments were performed at sample rates up to 2.5 MHz. These experiments were performed using a different storage oscilloscope (LeCroy WavePro 960XL) and a different differential amplifier (LeCroy DA1822A). The results from these experiments confirmed that sampling at 5 kHz is sufficient to capture the most relevant parts of the signal.
2.2.1.2. Signal correction
The used differential amplifier had a temperature dependent offset for each of its gains. To correct the recorded signal for a nonzero amplifier offset, an offset measurement was performed before each measurement series. The amplifier was always run at least 10 min to 15 min before an offset measurement was started to allow it to reach a steady operational temperature. The determined amplifier offset was afterwards subtracted from the recorded signal.
Shielding the measurements turned out to be very difficult and a significant 50 Hz component appeared in all measurements despite the shielding efforts. As 12
this could conceal other more interesting components of the signal the 50 Hz com-ponent was removed using a digital notch filter.
2.2.2. Image acquisition
In a part of the experiments the liquid meniscus was observed using an optical system consisting of a CCD camera (Kodak Megaplus ES 1.0), a long-distance microscope (Infinity, model K2 Long-Distance Microscope) and an illumination system (Oxford Laser, HSI1000 fast illumination system). The camera could be operated in “double exposure mode” in which it was possible to capture two consecutive images quickly after each other (∆t ' 1 µs). The time between two consecutive laser pulses of the illumination system was however significantly longer, resulting in a minimum time of approximately 11 µs between two con-secutive images. This enabled to gain some insight in the dynamic behaviour of the meniscus. Using the measured currents and a variable time delay to trigger the optical system enabled to visualise the liquid meniscus at various points in a pulsating current. For stationary signals this makes it possible to create a series of snapshots for a complete cycle, for other signals snapshots of the beginning of a cycle will not be available due to the small delay in the illumination (order of 5 µs) and the camera (order of 20 µs) see for example figures 2.4a and 2.4b. The electrospray setup was attached to a traversal system. By traversing the complete spray setup relative to the optical system, the snapshots could be taken at differ-ent distances from the nozzle. For stationary spray systems this made it possible to reconstruct multi-exposed, high resolution images of the complete spray situ-ation from nozzle to counter electrode at any given moment in the cycle of the liquid emission process (see for example figure 2.7a).
It is well known that it is not always possible for electrosprays to reach a steady state and even when it is possible to reach this state it may require some time. For this reason the system was always moved very slowly and smoothly and it was always allowed to stabilise for at least a minute after each change to the system and each traversal.
2.3. Correlation between liquid meniscus and
current characteristic
To investigate a correlation between the liquid meniscus and the simultaneously measured current through the system, the camera system described in section 2.2 was used. As this camera system was triggered by the measured current-signal a possible correlation was most easily determined for spray modes having a heavily pulsed current characteristic. For modes like the cone-jet mode the cur-rent characteristic is rather constant and reproducible triggering becomes difficult (see also [12, 20, 24]) . However, adjusting the triggering level in these cases does 13
(a)Overlay of 650 triggered current-pulses of a typical stationary electrospray.
(b)The interpeak time distribution for the
sys-tem that was used in figure 2.3a.
Figure 2.3.:Overlay of 650 triggered current pulses of a typical stationary electrospray to-gether with the corresponding distribution of the interpeak times.
enable to trigger “arbitrarily” which confirmed the reported observations that these modes exhibit a nearly constant meniscus and current-characteristic. For the pulsating systems the response time of the electronics made it impossible to determine the correlation at the beginning of a pulse. Assuming the signal to be stationary enables to get around this problem by triggering on a pulse and taking images of the next pulse. The validity of this assumption needs to be confirmed.
2.3.1. Stationarity
The camera system was operated with a short adjustable delay. Although this enabled to acquire images at well defined positions within a current-pulse, it also rendered it impossible to acquire images at the very onset of a pulse. Whether the pulses in such a situation can be compared with each other needs to be checked. Figure 2.3a shows a graph in which 650 triggered current pulses of a typical sta-tionary electrospray are plotted on top of each other based on the moment of trig-gering (0 ms). The electrospray system was a configuration 1 geometry spraying ethanol with an applied potential difference of∆V =4.50 kV. From this figure it is clear that for a stationary electrospray all pulses are nearly identical.
Figure 2.3b shows that the system was nearly stationary with a pulsation fre-quency of approximately 4.3 Hz. Extended measurement series revealed that dur-ing measurements spanndur-ing a couple of hours the pulsation frequency slowly changed from 3.5 Hz to 5 Hz. The timescale of this change is however much lar-ger than the time between two consecutive pulses.Hence triglar-gering on a certain pulse and using a relatively large delay to image the liquid meniscus at the onset of the next pulse is a valid way to gain insight in the development of the meniscus during the onset of a current pulse. The double spike around 9 ms is present in all pulses and originates from the flash light source needed for the image acquisition. 14
2.3.2. Liquid meniscus vs measured current
Figure 2.4 shows the tip of the liquid meniscus just below the nozzle outlet to-gether with the current through the system for a similar electrospray system as described in the previous section (configuration 1, spraying ethanol with∆V =
4.50 kV and a flow rate of 2 mL h−1). To some of the images the contour of a cone with an angle of 49.3° is added. Figures 2.4a and 2.4c show results for the largest part of the current-pulse. To accomplish this, the system was triggered on the preceding pulse which due to the stationary signal delivered reliable results. Figure 2.4b shows the results for the last part of the pulse. The corresponding current-pulse is shown in figure 2.4d for the complete pulse. Both 2.4b and 2.4d were obtained by triggering the image acquisition system on the very same pulse that was being imaged. This improved the accuracy of the results and is reflected in the different timings for both image sequences (0 ms represents the triggering moment).
Looking at figures 2.4c and 2.4d and comparing with figure 2.3a it is clear that although the same spray systems were used the pulse durations differ sig-nificantly. Within each separate measurement series the pulses match however closely, indicating that the systems were just spraying in a different spray mode. The cause of the different spray mode is not known. Most likely the different modes originate from slight differences in the operational history of the system and/or in minimal differences in the system geometry.
The double spikes in figures 2.4a and 2.4c originate from the firing of the flash light used in the camera system (which was operated in double exposure mode). Comparing the images with the current signal it can be seen that the current only increases significantly when liquid is emitted from the meniscus. Before the onset point (around 7.3 ms in this case) the shape of the meniscus does change but this is not reflected in the measured current. At the onset of the pulse the meniscus very rapidly transforms to a cone shape and liquid is emitted in a fine jet. The cone-angle differs from 49.3°, the Taylor angle (see [31]), denoted by the dashed lines in some of the images. This most likely is due to the applied liquid flow rate which was not considered by Taylor. Taylor also assumed an equipotential meniscus surface, which is also not completely true (see for example [22]).
2.3.2.1. Pulsation stages
As time progresses, the cone-shape gradually changes. To get a better overview of the development of the meniscus during a current-pulse it is illustrative to look at the contour of the meniscus at various moments. These contours for the results of figure 2.4a and 2.4c are depicted in figure 2.5. In this figure the contours are grouped together to emphasise the similarities and differences in the contours at various moments during a pulse. These similarities and differences can then be used to define a number of stages in the meniscus development and gain more 15
(a)The tip of the liquid meniscus at the start of the periodic current-pulse as shown in 2.4c. The optical system was triggered using the previous pulse. The dashed lines in some of the images depict the outline of a cone with the Taylor angle (49.3°).
(b)The tip of the liquid meniscus at the end of the periodic current-pulse as shown in 2.4d. The optical
system was triggered using the beginning of the pulse. The dashed lines in some of the images depict the outline of a cone with the Taylor angle (49.3°).
(c)The current-pulse following the trigger pulse
(corresponds with the images in 2.4a). The let-ters denote the various stages in the pulse de-velopment.
(d)Typical current-signal used for both triggering
the system and acquiring images of the liquid meniscus (corresponds with 2.4b).
Figure 2.4.:The tip of the liquid meniscus at various moments during a pulse in the current through the system together with the corresponding characteristic pulses.
(a) (b) (c) (d)
Figure 2.5.:The contours of the tip of the liquid meniscus of figure 2.4 for various mo-ments during a pulsation. The contours are grouped together to illustrate the meniscus behaviour at various moments during a pulse.
insight in the system. Each group contains a contour of the previous and the next group to make comparing consecutive groups easier.
Figure 2.5a shows the contours for the “pre-onset stage” (“A”,/7.3 ms in fig-ure 2.4c). In this region the meniscus changes significantly but no cone-jet like meniscus is observed and no significant current is measured. This is different for the “onset-stage” (“B”) for which the contours are shown in figure 2.5b. In this stage (/ 7.42 ms) a cone-jet is observed and the measured current through the system increases at a constant rate. After the relatively short “onset-stage” the “development stage” (“C”,/ 8.04 ms) starts in which the measured current keeps increasing. However, the rate with which the current increases decreases throughout the complete stage leading to a maximum measured current at the end of the stage. Looking at the corresponding contours (figure 2.5c) it can be seen that the increasing current is accompanied by an increase in the jet diameter. In the “reduction stage” (“D”,'8.04 ms) the opposite behaviour occurs: the jet becomes smaller as function of time and the current decreases (figure 2.5d). Just before the end of this stage the meniscus resembles the classical Taylor cone again. Looking at figure 2.4c it can be seen that the rate with which the current decreases at the end of the pulse varies considerably and exhibits a sudden change around 8.62 ms.
To investigate this sudden change more accurately, images of the tip of the meniscus at the end of the current pulse were made while triggering on the start 17
