Transistor arrays for the direct interfacing with electrogenic cells [Elektronische Ressource] / vorgelegt von Sven Meyburg

Dipl.-Phys. Dipl.-Biol. Sven Meyburg

Sujets

• Biologie

Informations

• Publié par: rheinisch-westfalischen_technischen_hochschule_-rwth-_aachen
• Publié le: 01 janvier 2005
• Nombre de lectures: 6
• Langue: English
• Poids de l'ouvrage: 15 Mo

Extrait

“Transistor Arrays for the Direct Interfacing
with Electrogenic Cells”
Von der Fakult¨at fur¨ Mathematik, Informatik und Naturwissenschaften
der Rheinisch-Westf¨alischen Technischen Hochschule Aachen
zur Erlangung des akademischen Grades eines Doktors der
Naturwissenschaften genehmigte Dissertation
vorgelegt von
Diplom-Physiker, Diplom-Biologe
Sven Meyburg
aus Karlsruhe
Berichter: Universit¨atsprofessor Dr.rer.nat. Andreas Offenh¨ausser
Universit¨atsprofessor Dr.rer.nat. Hans Luth¨
Tag der mundlic¨ hen Prufung:¨ 12. Dezember 2005
Diese Dissertation ist auf den Internetseiten der Hochschulbibliothek online verfugba¨ r.‘Hey, Dave,’ said Hal. ‘What are you doing?’ [...]
A dozen units had been pulled out, yet thanks to
the multiple redundancy of its design—another feature,
Bowman knew, that had been copied from the human
brain—the computer was still holding its own.
Arthur C. Clarke, 2001 a space odyssey, 1968Contents
1 Introduction 7
2 Basics of the Bioelectronic Signal Transduction 11
2.1 Cell Membrane and Membrane Potential . . . . . . . . . . . . . . . . . . 11
2.1.1 Ion Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.2 Active Transport Proteins . . . . . . . . . . . . . . . . . . . . . . 12
2.1.3 Resting Potential . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.1.4 Action Potential . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.1.5 Patch Clamp Recording . . . . . . . . . . . . . . . . . . . . . . . 16
2.2 Synaptical Transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2.1 Electrical Synapses . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2.2 Chemical Synapses . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.3 Cell Systems Used for Transistor Couplings . . . . . . . . . . . . . . . . . 20
2.3.1 Rat Cardiac Myocytes . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3.2 Human Embryonic Kidney Cells . . . . . . . . . . . . . . . . . . . 21
2.4 Metal Oxide Semiconductor Field Effect Transistors . . . . . . . . . . . . 22
2.4.1 The Field Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.4.2 Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.4.3 Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.5 Signal Acquisition in Aqueous Solutions . . . . . . . . . . . . . . . . . . 28
2.5.1 Electrolyte-Oxide-Semiconductor Interface . . . . . . . . . . . . . 29
2.5.2 Stern Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.3 Point-Contact Model . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.5.4 Extension of the Point-Contact Model . . . . . . . . . . . . . . . 34
3 Materials and Methods 37
3.1 Chip Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.1.1 Sensor Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.1.2 Fabrication Process . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3Contents
3.1.3 Chip Encapsulation . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.1.4 Chip Cleaning and Coating . . . . . . . . . . . . . . . . . . . . . 44
3.2 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.2.1 Setup for Chips of the First Fabrication Process . . . . . . . . . . 45
3.2.2 Setup for Chips of the Second Fabrication Process . . . . . . . . . 47
3.3 Cell Culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.3.1 Rat Cardiac Myocytes . . . . . . . . . . . . . . . . . . . . . . . . 51
3.3.2 Human Embryonic Kidney Cells . . . . . . . . . . . . . . . . . . . 51
4 Characterisation of the Devices 53
4.1 n-Channel Floating Gate Transistors . . . . . . . . . . . . . . . . . . . . 53
4.1.1 First Fabrication Process . . . . . . . . . . . . . . . . . . . . . . . 53
4.1.2 CMOS Fabrication Process . . . . . . . . . . . . . . . . . . . . . . 67
4.2 p-Channel Floating Gate Transistors . . . . . . . . . . . . . . . . . . . . 69
4.3 Combined n- and p-Channel Sensors . . . . . . . . . . . . . . . . . . . . 71
4.4 Addressable Sensor Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.4.1 Row-Column Arrays . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.4.2 Decoder Controlled Row-Column Arrays . . . . . . . . . . . . . . 77
4.5 Stimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.6 Long-Term Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5 Interfacing Electronic Devices with Cells 87
5.1 Focussed Ion Beam Section of a Cell on a Sensor . . . . . . . . . . . . . . 87
5.2 Individually Contacted FETs . . . . . . . . . . . . . . . . . . . . . . . . 90
5.2.1 n-Channel Floating Gate Transistors . . . . . . . . . . . . . . . . 90
5.2.2 p-Channel Floating Gate Transistors . . . . . . . . . . . . . . . . 94
5.2.3 Combined n- and p-Channel Sensors . . . . . . . . . . . . . . . . 100
5.3 Addressable Sensor Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . 102
5.4 Stimulation with the Floating Gate . . . . . . . . . . . . . . . . . . . . . 105
6 Conclusions and Outlook 109
Appendices 113
A Process Overview 113
A.1 Well Implantations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
A.2 Field Implantations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
A.3 Punchthrough and Threshold Adjustment Implantations . . . . . . . . . 115
A.4 Gate Oxidation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
A.5 Capacitor Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
4Contents
A.6 Source and Drain Implantations . . . . . . . . . . . . . . . . . . . . . . . 117
A.7 Interconnections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
A.8 Passivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
A.9 Metallisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
B Chemicals and Buffer Solutions 121
B.1 Chemicals for Cell Culture . . . . . . . . . . . . . . . . . . . . . . . . . . 121
B.2 Buffer Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
B.2.1 Cardiac Myocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
B.2.2 HEK293 Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
B.2.3 Other Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
C Software Description 125
C.1 Software for Characterisation . . . . . . . . . . . . . . . . . . . . . . . . 125
C.2 Software for Cell Couplings . . . . . . . . . . . . . . . . . . . . . . . . . 126
D Abbreviations 129
D.1 Formula Signs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
D.2 Technical Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
Bibliography 135
Acknowledgements / Danksagung 145
Zusammenfassung 147
Lebenslauf 151
5Contents
61 Introduction
In millions of years, nature has developed complex systems in order to process sensory
input: from single cells, over diffuse neuronal networks up to central nervous systems.
The following examples underline the importance of a better understanding of biological
sensingsystems,neuronalnetworksandtheinterfacebetweentechnicaldevicesandnerve
tissue.
Biosensing systems in nature have evolved to the most sensitive detectors known.
Male silkworm moths (Bombyx mori) are able to detect with their antennae single
molecules of the sex pheromone Bombykol released by female moths [Kaissling and
Priesner, 1970]. Rod cells of the human retina carry an amplification system, that signals
the detection of a single photon [Berg et al., 2002].
In 1950 Alan Turing proposed a test to evaluate the intelligence of a machine [Turing,
1950]. The criterium was, if a real person communicating with both a machine and a
human – no visual nor acoustical information – is able to distinguish between the two.
Up to now, no machine has passed the test. To explain this result, the different ways of
information processing of brains and current computers have to be considered.
The first fully implanted neural prosthesis, the cardiac pacemaker, was developed by
Elmquist and Senning [1959]. The first multi-electrode cochlear implant was developed
by Clark et al. [1977] and successfully implanted in 1978. Today’s cochlear implants have
about 22−24 electrodes using the tonotopic organisation of the basilar membrane of the
inner ear. Attempts to apply these principles of stimulation to vision or motor control
face the complexity of these systems and the lack of a “language” for communication
between cellular tissue and technical devices so far.
∞
The prerequisite to better understand information processing in biological systems is
to investigate signalling at cellular level. Widespread methods such as patch-clamp or
intracellular recordings are invasive and therefore limit the lifetime of contacted cells
to a few hours. In contrast, extracellular recordings in a biocompatible surrounding are
limited only by the cells’ lifetime on the sensor chips. Spinal monolayers still showed
vigorous electrical activity after 9 months in vitro [Gross, 1994].
71. Introduction
For extracellular multi-site signal recordings, two main concepts were developed in
the past: multi-electrode arrays (MEAs) [P