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عدد المساهمات : 19001 التقييم : 35505 تاريخ التسجيل : 01/07/2009 الدولة : مصر العمل : مدير منتدى هندسة الإنتاج والتصميم الميكانيكى
| موضوع: كتاب Automated Nanohandling by Microrobots الجمعة 01 ديسمبر 2023, 11:52 pm | |
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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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