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 |  موضوع: كتاب Automated Nanohandling by Microrobots الجمعة 01 ديسمبر 2023, 11:52 pm | |
| 
أخواني في الله
أحضرت لكم كتاب
Automated Nanohandling by Microrobots
Sergej Fatikow
و المحتوى كما يلي :
Editor
Contents
List of Contributors xv
1 Trends in Nanohandling . 1
1.1 Introduction 1
1.2 Trends in Nanohandling . 3
1.2.1 Self-assembly . 3
1.2.2 SPM as a Nanohandling Robot . 5
1.3 Automated Microrobot-based Nanohandling . 8
1.4 Structure of the Book . 11
1.5 References 13
2 Robot-based Automated Nanohandling 23
2.1 Introduction 23
2.2 Vision Sensors for Nanohandling Automation 25
2.2.1 Comparison of Vision Sensors for Nanohandling Automation 26
2.2.2 Zoom Steps and Finding of Objects . 29
2.2.3 SEM-related Issues . 31
2.2.3.1 Sensor Resolution and Object Recognition 31
2.2.3.2 Noise 33
2.2.3.3 Velocity and Image Acquisition Time . 33
2.3 Automated Nanohandling: Problems and Challenges 34
2.3.1 Parasitic Forces . 34
2.3.2 Contact Detection . 36
2.4 General Description of Assembly Processes 37
2.4.1 Description of the Single Tasks 38
2.4.2 General Flowchart of Handling Tasks 40
2.5 Approaches for Improving Reliability and Throughput . 40
2.5.1 Improving Reliability . 40
2.5.2 Improving Throughput . 41
2.6 Automated Microrobot-based Nanohandling Station 42
2.6.1 AMNS Components . 43
2.6.1.1 Setup 43viii Contents
2.6.1.2 Actuators 44
2.6.1.3 Mobile Microrobots . 45
2.6.1.4 Sensors . 46
2.6.1.5 Control Architecture 47
2.6.1.6 User Interface . 48
2.6.2 Experimental Setup: Handling of TEM Lamellae 49
2.7 Conclusions 52
2.8 References 54
3 Learning Controller for Microrobots . 57
3.1 Introduction 57
3.1.1 Control of Mobile Microrobots 57
3.1.2 Self-organizing Map as Inverse Model Controller . 58
3.2 Closed-loop Pose Control 62
3.2.1 Pose and Velocity . 62
3.2.2 Trajectory Controller 63
3.2.3 Motion Controller . 64
3.2.4 Actuator Controller . 65
3.2.5 Flexible Timing During Pose Control 65
3.3 The SOLIM Approach . 66
3.3.1 Structure and Principle . 66
3.3.2 Mapping . 68
3.3.2.1 Interpolation . 69
3.3.2.2 Influence Limits . 72
3.3.2.3 Extrapolation 74
3.3.3 Learning . 76
3.3.3.1 Approximation . 76
3.3.3.2 Self-organization in Output Space . 78
3.3.3.3 Self-organization in Input Space 82
3.3.4 Conclusions 83
3.4 SOLIM in Simulations . 83
3.4.1 Mapping . 83
3.4.2 Learning . 85
3.4.2.1 Procedure . 85
3.4.2.2 Inverse Kinematics . 87
3.5 SOLIM as Actuator Controller 89
3.5.1 Actuation Control . 89
3.5.2 Manual Training . 91
3.5.3 Automatic Training 93
3.6 Conclusions 96
3.6.1 Summary 96
3.6.2 Outlook . 97
3.6.2.1 Extrapolation 97
3.6.2.2 Computational Load . 97
3.6.2.3 Predefined Network Size . 98
3.6.2.4 Applications for SOLIM 98
3.7 References 99
Contents ix
4 Real-time Object Tracking Inside an SEM 103
4.1 Introduction 103
4.2 The SEM as Sensor 104
4.3 Integration of the SEM 106
4.4 Cross-correlation-based Tracking 107
4.5 Region-based Object Tracking 111
4.5.1 The Energy Functions . 111
4.5.2 Fast Implementation . 114
4.5.3 Minimization 116
4.5.4 Evaluation and Results . 119
4.5.4.1 Performance . 119
4.5.4.2 Robustness Against Additive Noise . 120
4.5.4.3 Robustness Against Clutter 121
4.5.4.4 Robustness Against Gray-level Fluctuations . 123
4.6 Conclusions 124
4.6.1 Summary 124
4.6.2 Outlook . 126
4.7 References 126
5 3D Imaging System for SEM . 129
5.1 Introduction 129
5.2 Basic Concepts . 130
5.2.1 General Stereoscopic Image Approach . 130
5.2.1.1 The Cyclopean View 131
5.2.1.2 Disparity Space 131
5.2.1.3 Vergence and Version 132
5.2.1.4 Vergence System . 134
5.2.2 Principle of Stereoscopic Image Approaches in the SEM 135
5.2.2.1 Structure of the SEM . 135
5.2.2.2 Generation of Stereoscopic Images in the SEM . 136
5.2.2.3 Influences on the Disparity Space 138
5.2.3 Mathematical Basics . 139
5.2.3.1 Convolution . 139
5.2.3.2 Frequency Analysis 139
5.2.3.3 Gabor Function 141
5.2.4 Biological Vision Systems 143
5.2.4.1 Neuron Models 143
5.2.4.2 Depth Perception in Biological Vision Systems 144
5.2.4.3 Energy Models . 144
5.3 Systems for Depth Detection in the SEM 145
5.3.1 Non-stereoscopic Image Approaches . 146
5.3.2 Stereoscopic Image Approaches . 147
5.4 3D Imaging System for Nanohandling in an SEM 148
5.4.1 Structure of the 3D Imaging System for SEM 148
5.4.2 Image Acquisition and Beam Control 149
5.4.3 The 3D Module . 151
.x Contents
5.4.3.1 Stereo System 152
5.4.3.2 Vergence System . 156
5.5 Application of the 3D Imaging System 158
5.5.1 Results of the 3D Imaging System . 158
5.5.2 Application for the Handling of CNTs . 160
5.5.3 Application for the Handling of Crystals 161
5.6 Conclusions 161
5.6.1 Summary 161
5.6.2 Outlook . 163
5.7 References 163
6 Force Feedback for Nanohandling 167
6.1 Introduction 167
6.2 Fundamentals of Micro/Nano Force Measurement 168
6.2.1 Principles of Force Measurement . 168
6.2.2 Types of Forces in Robotics . 170
6.2.2.1 Gripping Forces . 170
6.2.2.2 Contact Forces . 172
6.2.3 Characteristics of the Micro- and Nanoworld . 172
6.2.4 Requirements on Force Feeback for Nanohandling 174
6.2.5 Specific Requirements of Force Feedback for Microrobots . 177
6.3 State-of-the-art . 178
6.3.1 Micro Force Sensors . 178
6.3.1.1 Piezoresistive Micro Force Sensors . 178
6.3.1.2 Piezoelectric Micro Force Sensors . 180
6.3.1.3 Capacitive Micro Force Sensors 180
6.3.1.4 Optical Methods for Micro Force Measurement 181
6.3.1.5 Commercial Micro Force Sensors 183
6.3.2 Microgrippers with Integrated Micro Force Sensors 183
6.3.3 Robot-based Nanohandling Systems with Force Feedback 184
6.3.3.1 Industrial Microhandling Robots . 185
6.3.3.2 Microrobots Outside the Scanning Electron
Microscope . 188
6.3.3.3 Microrobots Inside the Scanning Electron
Microscope . 192
6.3.3.4 Mobile Microrobots . 193
6.3.4 AFM-based Nanohandling Systems . 195
6.3.4.1 Commercial and Custom-made AFMs for
Nanohandling . 195
6.3.4.2 AFMs combined with Haptic Devices and
Virtual Reality 196
6.3.4.3 AFMs integrated into Scanning Electron
Microscopes . 196
6.4 Conclusions 197
6.5 References 197
.
.
.
.Contents xi
7 Characterization and Handling of Carbon Nanotubes 203
7.1 Introduction 203
7.2 Basics of Carbon Nanotubes 204
7.2.1 Structure and Architecture 204
7.2.2 Electronic Properties . 205
7.2.3 Mechanical Properties 207
7.2.4 Fabrication Techniques . 208
7.2.4.1 Production by Arc Discharge . 208
7.2.4.2 Production by Laser Ablation 209
7.2.4.3 Production by Chemical Vapor Deposition (CVD) . 209
7.2.5 Applications 210
7.2.5.1 Composites . 211
7.2.5.2 Field Emission . 211
7.2.5.3 Electronics . 212
7.2.5.4 AFM Cantilever Tips . 212
7.3 Characterization of CNTs 213
7.3.1 Characterization Techniques and Tools 213
7.3.1.1 Microscopic Characterization Methods . 213
7.3.1.2 Spectroscopic Characterization Methods . 214
7.3.1.3 Diffractional Characterization Methods 215
7.3.2 Advantages of SEM-based Characterization of CNTs . 215
7.4 Characterization and Handling of CNTs in an SEM 216
7.5 AMNS for CNT Handling . 218
7.5.1 Experimental Setup 218
7.5.2 Gripping and Handling of CNTs 220
7.5.3 Mechanical Characterization of CNTs . 221
7.6 Towards Automated Nanohandling of CNTs 224
7.6.1 Levels of Automation . 224
7.6.2 Restrictions on Automated Handling Inside an SEM . 225
7.6.3 Control System Architecture 226
7.6.4 First Implementation Steps . 230
7.7 Conclusions 231
7.8 References 232
8 Characterization and Handling of Biological Cells 237
8.1 Introduction 237
8.2 AFM Basics . 239
8.2.1 Cantilever Position Measurement . 239
8.2.1.1 Optical: Laser Beam Deflection . 240
8.2.1.2 Self-sensing: Piezoelectric and Piezoresistive . 240
8.2.2 AFM Modes . 240
8.2.2.1 Contact Mode . 240
8.2.2.2 Dynamic Mode 241
8.2.2.3 Lateral Force Mode 242
8.2.2.4 Jumping Mode / Force Volume Mode and Force
Distance Curves . 242
8.2.3 Measurements of Different Characteristics 243
.xii Contents
8.2.3.1 Mechanical Characterization 243
8.2.3.2 Magnetic Force Measurements 245
8.2.3.3 Conductivity Measurements 245
8.2.3.4 Molecular Recognition Force Measurements 246
8.2.4 Sample Preparation . 247
8.2.5 Cantilevers 247
8.2.6 Video Rate AFMs . 248
8.2.7 Advantages and Disadvantages of AFM for Biohandling 248
8.3 Biological Background 249
8.3.1 Characteristics of Cells . 249
8.3.1.1 Mechanical Characteristics . 249
8.3.1.2 Electrical Characteristics 250
8.3.1.3 Chemical Characteristics 251
8.3.2 Escherichia Coli Bacterium 251
8.3.3 Ion Channels . 252
8.3.4 Intermolecular Binding Forces . 253
8.4 AFM in Biology – State-of-the-art 254
8.4.1 Imaging . 254
8.4.2 Physical, Electrical, and Chemical Properties 255
8.4.2.1 Elasticity and Stiffness Measurements . 255
8.4.2.2 Intermolecular Binding Forces . 256
8.4.2.3 Adhesion Forces 256
8.4.2.4 Cell Pressure 257
8.4.2.5 Virus Shell Stability . 257
8.4.2.6 Electrical Properties of DNA . 257
8.4.3 Cooperation and Manipulation with an AFM . 258
8.4.3.1 Stimulation and Recording of Mechanosenstive
Ion Channels 258
8.4.3.2 Cutting and Extraction Processes on Chromosomes 258
8.4.4 Additional Cantilever 259
8.5 AMNS for Cell Handling . 259
8.5.1 Experimental Setup 259
8.5.2 Control System . 260
8.5.3 Calculation of the Young’s Modulus 261
8.5.4 Experimental Results 262
8.6 Conclusions 263
8.6.1 Summary 263
8.6.2 Outlook . 263
8.7 References 264
9 Material Nanotesting 267
9.1 Instrumented Indentation . 267
9.1.1 Sharp Indentation 267
9.1.1.1 Introduction 267
9.1.1.2 Basic Concepts of Materials Mechanics . 270
9.1.1.3 Similarity Between Sharp Indenters of Different
Shape 270
.Contents xiii
9.1.1.4 Indentation Ranges: Nano-, Micro-, and
Macroindentation . 271
9.1.1.5 Analysis of Load Depth Curves . 271
9.1.1.6 Applications of the Sharp Instrumented Indentation 277
9.1.2 Spherical Indentation 279
9.1.2.1 Comparing Spherical and Sharp Instrumented
Indentation . 279
9.1.2.2 Analysis of Load Depth Curves Using Spherical
Indenters . 280
9.1.2.3 Applications of Spherical Instrumented Indentation 281
9.2 Microrobot-based Nanoindentation of Electrically
Conductive Adhesives . 281
9.2.1 Experiments 282
9.2.1.1 Material System . 282
9.2.1.2 Description of the Experimental Setup 283
9.2.1.3 The AFM Cantilever 285
9.2.1.4 Description of the NMT Module . 286
9.2.1.5 Experimental Procedure 286
9.2.2 Calibrations 287
9.2.2.1 Calibration of the Stiffness 287
9.2.2.2 Electrical Calibration . 288
9.2.3 Preliminary Results 288
9.2.3.1 Dependency on the Hardness of the ECA on the
Curing Time . 288
9.2.4 Discussion 289
9.2.4.1 Different Tip Shapes 289
9.3 Conclusions 292
9.4 References 293
10 Nanostructuring and Nanobonding by EBiD . 295
10.1 Introduction to EBiD . 295
10.1.1 History of EBiD 297
10.1.2 Applications of EBiD . 298
10.2 Theory of Deposition Processes in the SEM . 299
10.2.1 Scanning Electron Microscopy for EBiD . 299
10.2.1.1 Generation of the Electron Beam . 299
10.2.1.2 General SEM Setup 301
10.2.1.3 Secondary Electron Detector . 302
10.2.2 Interactions Between Electron Beam and Substrate . 303
10.2.2.1 Energy Spectrum of Emerging Electrons 303
10.2.2.2 Range of Secondary Electrons . 305
10.2.2.3 Results 309
10.2.3 Modeling the EBiD Process . 310
10.2.3.1 Rate Equation Model . 310
10.2.3.2 Parameter Determination for the Rate Equation
Model . 312
10.2.3.3 Influence of the SE . 314
xiv Contents
10.2.3.4 Heat Transfer Calculations . 315
10.3 Gas Injection Systems (GIS) 316
10.3.1 Introduction 316
10.3.2 The Molecular Beam 317
10.3.2.1 Modeling of the Mass Flow Between Reservoir
and Substrate 317
10.4 Mobile GIS 322
10.4.1 General Setup . 322
10.4.2 Position Control of the GIS 323
10.4.3 Pressure Control . 324
10.4.3.1 Constant Evaporation Systems . 324
10.4.3.2 Heating/Cooling Stages . 324
10.4.3.3 Control of the Molecular Flux . 325
10.4.3.4 Pressure Dependence of the Deposition Rate 326
10.4.4 Multimaterial Depositions 327
10.5 Process Monitoring and Control 329
10.5.1 Time-based Control (Open-loop Control) 329
10.5.2 Closed-loop Control of EBiD Deposits 330
10.5.2.1 Growth of Pin-like Deposits and SE-signal . 331
10.5.2.2 Application for 2D Deposits 332
10.5.3 Failure Detection 334
10.6 Mechanical Properties of EBiD Deposits 336
10.7 Conclusions 336
10.7.1 Summary 336
10.7.2 Outlook . 337
10.7 References 338
Index 341
3D structuring, 295, 298
3D vision, 37
accuracy
object recognition, 31, 34
positioning, 23, 30
active contour, 104
actuator, thermal, 35, 170, 256
additive noise, 120
adhesion forces,
AFM, 6
based force measurement, 195
cantilever 45, 169, 183, 204, 239,
277
end-effector cooperation, 258
probe, 11
sample preparation, 247
anodic oxidation, 6
aperture
angle, 301
diameter, 301
approximation
error, 78
learning rate, 78
arc discharge, 208
assembly, 317
assembly process, 37
atomic force microscope (AFM), 28
cantilever, 45
tip, 42
Auger electron, 303
augmented reality, 7
automated nanohandling, 7, 23, 224
automated microrobot-based
nanohandling station (AMNS),
10, 62, 218, 259
automation language, 232
automation sequence, 227
backscattering coefficient, 308
backscattered electron, 303
Bernoulli distribution, 112
biosensors, 250
black box design, 226
bonding technology, 299
calibration, 48, 98, 183, 222
cantilever position measurement, 239
capacitive force sensor, 180
capillary
conductance of, 318
forces, 4, 35, 240
outlet, blocking of, 317
carbon nanotube (CNT), 29, 103, 160,
190, 204
CCD camera, 43
cell adhesion, 256
cell pressure, 257
cell volume control, 255
challenges, 4
of nanoautomation, 34
characterization, 1342 Index
charging, 34, 174, 299
Chemical vapor deposition (CVD),
160, 209, 296
chromosome cutting, 241
chromosomal microdissection, 6
closed-loop control 31, 58, 62
closure
force, 39
form, 3
material, 39
clutter, 105
CNTs
applications, 203, 210
characterization techniques, 213
chirality, 206
electrical conductivity, 206
gripping and handling, 220
mechanical characterization, 221
SEM-based characterization, 215
Young’s modulus, 204
coarse positioning, 9, 29, 218, 259
coherence layer, 151
collision avoidance, 225
command interface, 227
conductivity of DNA, 245
conductivity measurements, 250
contact
detection, 24, 36
size, 38
contamination layer, 297
constant force, 241, 279
constant height, 241, 336
contact force, 172
contact mode, 240
control
architecture, 47
channel, 46, 58
closed-loop, 2, 58, 330
open-loop, 329
time-based, 329
control system architecture, 226
controller
actuator, 65
closed-loop, 58
error, 228
inverse model, 64
motion, 63
trajectory, 63
cosine emitter, 320
cross-correlation, 104, 107
crossover, 300
current density, 210, 299
cyclopean view, 131
cytoskeleton, 249
data retrieval models, 226
depth from focus, 36
depth of focus, 27, 303
deposited molecule volume, 313
diffusion-limited, 327
dip-pen lithography (DPN), 6
disorder, degree of, 80
disparity, 130
disparity estimation unit (DEU), 152
dissociation cross-section, 312
DNA hybridization, 4
drawback of AFM-based
nanohandling, 7
drift effects, 337
dynamic mode, 238, 241
E. coli, 251
edge-based minimization, 111
elasticity measurements, 247
electrical characteristics, 249
electrically conductive adhesive, 281
electron column, 137, 296
electrophoresis, 3
electrostatic
actuator, 35
forces, 4, 34, 173, 245
electrothermal nanogripper, 204
energy dispersive X-ray detector
(EDX detector), 26, 126
energy function, 112
energy-limited, 312
Energy Dispersive X-ray analysis
(EDX analysis), 329
energy models, 144
environmental challenges, 225
error rate, 228
escape depth, 308
estimation layer, 151
euclidean similarities, 110Index 343
evaporation system, 317
Everhardt–Thornley SE detector, 27
failure analysis with non-ambiguous
retrace, 41
failure detection, 335
field emission, 33, 211, 299
gun, 302
fine positioning, 9, 29, 191, 219, 259
flexible hinge, 13, 44, 173, 299
flowchart, 40
flux calculation algorithm, 321
focused ion beam (FIB), 24, 295
force
distance curve, 242
feedback, 9, 167, 263
measurement principles, 177
ranges, 177
volume mode, 242
frame
acquisition time, 33
rate, 27, 104
friction force, 171
full width at half maximum (FWHM),
307
Gabor function, 141
Gas injection system (GIS), 316
mobile, 322
global coordinate system, 25
graphical user interface (GUI), 9, 48
gravitational forces, 4
gray level fluctuations, 105
Green–Ostrogradsky theorem, 115
gripping force, 170
handling process, 23
haptic device, 11, 196
hardness, 267, 281, 336
heat transfer, 315
height control, 334
high-level control, 48, 225
high-vacuum chamber, 314
hull factor, 29
hydrophilic features, 4
hybrid approaches, 5
hydrophobic features, 4
image
acquisition time, 33, 104
artifacts, 35
dimensionality, 28
information, 26
processing resolution, 31
in-situ measurement, 216
influence limits, 71
intermittend mode, 241
intermolecular binding forces, 246
ion channel, 248
join, 39
jumping mode, 242
key-lock principle, 253
Knudsen number, 317
Lambert emitter, 320
laser ablation, 209
laser-beam deflection, 240
lateral force mode, 242
learning, 57
incremental, 83
performance, 83
levels of automation , 224
full-automation, 225
semi-automation, 224
tele-operation, 224
light microscope, 1, 23, 57, 104, 136,
188, 264
liquid films, 35
lithography, 6, 186, 204, 295
low-level control, 11
low-level controller, 48, 226
low-loss electron, 303
low-vacuum modus, 35
magnetic force measurements, 245
magnetic forces, 4
magnification, 10, 27, 107, 129, 301
manual manipulation, 8
mask-free nanolithography, 6
mean free path, 206, 317
mean stay time, 310
mechanical characteristics, 249
mechanical stress, 169344 Index
mechanosensitive ion channels, 255
micro force sensor, 174
microelectronics, 188, 292
microrobot-based nanohandling, 8
microrobotics, 9, 42, 98, 185, 225,
281
microrobots, 1
microsystem technology, 1
mobile microrobot, 10, 45, 177, 193
platform, 10
molecular beam, 317
molecular recognition force
measurements, 246
molecule density, 310
Monte-Carlo method, 305
multichannel array, 329
multimaterial deposition, 328
multiwall carbon nanotubes, 204
nanoassembly, 2
nanohandling, 1
approaches, 3
robot station, 216
nanoindentation, 268, 337
nanomachining, 6
nanomanipulation, 5
nanotechnology, 2
nanowire, 4, 27, 192 217
noise, 33, 65, 105, 139, 239, 300
non-contact, 241
object recognition, 31, 107, 261
accuracy, 29
occlusion, 106
optical force measurement, 181
optical tweezers, 3
orders of magnitude in scale, 26
out-of-plane position, 36
parallel approach, 23
parallel nano- and microfabrication, 3
parasitic forces, 24
path planning, 225, 261
peaking factor, 320
Peltier element, 320
penetration depth, 268, 303
performance, 83
piezoelectric force sensor, 188
piezoresistive AFM probe, 9, 218
piezoresistive force sensor, 189
piezoresitive position measurement,
239
planning, 24
Poisson distribution, 112
position sensor
on-board, 31
pre-, postconditions, 227
precursor, 143, 209, 295
pre-packaged orientation, 41
prescan, 334
pressure
control, 316
gage, 323
primary electron (PE), 296
primitive, 37,62
process, 23
control, 168, 330
feedback, 9
pump oil, 35, 297
Q factor, 240
quality assurance, 37
rate equation model, 310
real-time
processing, 106
visual feedback, 7
recognition force measurements, 246
region-based minimization, 104
region of interest (ROI), 106
release, 37
reliability, 37
resolution, 26
resonance frequency, 37, 184, 241,
287
scale domains, 173
scaling effects, 173
scanning electron microscope (SEM),
7
scanning probe microscope (SPM), 3
scanning speed, 33, 249
scanning tunneling microscope
(STM), 3Index 345
Schottky emission, 299
secondary electron (SE), 105, 136,
136, 296
absolute range, 307
range, 305
relative range, 307
SE1, 305
SE2, 305
spatial distribution, 306
self-assembled monolayers (SAM), 4
self-assembly, 3, 5
self-organization, 78
learning rate, 78
self-organizing locally interpolating
map, 61
self-organizing map, 58
semi-automated control, 2
sensor
feedback, 4, 33, 326
density, 25
resolution, 31, 120
server, 47, 226
system of the AMNS, 11
separation, 37
serial approach, 23
sharp indentation, 267
signal-to-noise ratio, 33, 300
simplex, 69, 97
single-wall carbon nanotubes, 204
snap-back point, 242
spherical indentation, 280
SPM–SEM hybrid system, 8
stationary microrobots, 10
statistical independent region model,
112
step width, 32
stereocilia, 252
sticking coefficient, 310
sticky finger effect, 225
stick–slip principle, 32, 46
strain, 168
strain gage, 169, 293, 328
subtask, 24
surface tension, 35, 173
teleoperated control, 2
teleoperated manipulation, 8
teleoperation, 11, 48, 58, 104, 193,
220
TEM lamellae, 24
temperature control, 326
tensile strength, 337
texture-based filter, 156
thermal conductivity, 283, 316
thermionic
electron gun, 299
emission, 299
thermocouple, 328
throughput, 24, 319
time-variance, 36
time-variant, 36
top-down approach, 3
topology, 59
growing/shrinking, 98
touchdown sensor, 39, 146
tracking, visual tracking, 111
transformation space, 116
transitional regime, 318
flow, 319
translation, 43
transport, 37
tungsten-hexacarbonyl, 314
update rate, 33, 65, 104, 226
vacuum
chamber, 316
gage, 326
Van der Waals forces. 4, 35, 173, 240
vapor pressure, 325
vergence, 131
system, 134
video rate AFM, 239
virtual source, 301
virus shell stability, 257
vision sensor, 25, 230
global, 25
comparison, 26
visual feedback, 2, 9346 Index
Wehnelt cup, 299
working distance, 301
X-rays, 303
yield factor, 307
Young’s modulus, 169, 243, 267, 337
zoom-and-center steps, 29
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