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6 MODELING AND SIGNAL PROCESSING STRATEGIES FOR MICROACOUSTIC CHEMICAL SENSORS&G.Fischerauer F.Thalmayr 231

1 Sensing Principles of Microacoustic Chemical Sensors 231

1.1 Introduction 231

1.2 Microacoustic Chemical Sensors 233

2 Simulation and Modeling of Acoustic Wave Propagation,Excitation,and Detection 234

2.1 Analytical Solution to the Undisturbed Wave Propagation Problem 235

2.2 Analytical Solution to the Wave Excitation and Detection Problem 239

2.3 Finite-Element Method 242

2.4 Equivalent-Circuit Models 245

3 Sensor Steady-State Response 248

3.1 Perturbation Approaches 248

3.2 Temperature Effects 253

4 Sensor Dynamics 254

4.1 Linear Model 255

4.2 State-Space Description 262

5 Sensor Signal Processing 266

5.1 Suppression of Temperature Effects 266

5.2 Signal Processing Based on Linear Analytical Model 268

5.3 Wiener Deconvolution 269

5.4 Kalman Filter 274

5.5 Discussion of State-Space-Based Signal Processing 277

6 Summary 281

7 Nomenclature 281

References 286

7 HIERARCHICAL SIMULATION OF CARBON NANOTUBE ARRAY-BASEDCHEMICAL SENSORS WITH ACOUSTIC PICKUP&V.Barkaline A.Chashynski 289

1 Introduction 289

2 Simulation Levels of Nanodesign 291

3 Prototype of Hierarchical Simulation System for Nanodesign 294

4 Continual Simulation of SAW Propagation in a Layered Medium 297

5 Structure of Carbon Nanotubes and Adsoption Properties of CNT Arrays 312

5.1 Atomic Structure of Single-and Multiwalled Nanotubes 313

5.2 Quantum Mechanical Study of the Adsorption of Simple Gases on Carbon Nanotubes 315

5.3 Molecular Mechanics of Physical Adsorption of the Individual Molecules on the CNT 324

6 Simulation of a Carbon Nanotube Array-Based Chemical Sensor with an Acoustic Pickup 332

6.1 Molecular Dynamics Calculation of the Elastic Moduli of Individual Carbon Nanotubes 335

6.2 Molecular Dynamics Study of Distribution of Adsorbed Molecules in CNT Array Pores and Calculation of Acoustic Parameters of CNT Arrays 339

6.3 SAW Phase Velocity Change Due to Molecular Adsorption on CNT Arrays in SAW-Based Chemical Sensors 341

7 Conclusion 343

References 346

8 MICROCANTILEVER-BASED CHEMICAL SENSORS&S.Martin G.Louarn 349

1 Introduction 349

2 Natural Frequencies and Normal Modes of Vibration 352

3 Experimental Procedure 352

4 Natural Frequencies of Free Rectangular Cantilevers 353

4.1 Analytical Calculations 354

4.2 Simulation with Finite-Element Method 356

4.3 Experimental and Modelling Results on a Rectangular Beam 361

5 Natural Frequencies of V-Shaped Microcantilevers 361

6 Natural Frequencies of V-Shaped Coated Cantilevers 366

7 Conclusion and Prospects 368

8 Acknowledgments 368

References 368

9 MODELING OF MICROMACHINED THERMOELECTRIC GAS SENSORS&S.Udina M.Carmona C.Calaza 371

1 Principles of MTGS Modeling 371

1.1 Introduction to the Theory of Heat Transfer 372

1.2 Key Thermal Contributions and Parameters Involved in Sensor Operation and Modeling 374

1.3 Influence of the Packaging 379

2 Modeling and Simulation Methods 379

2.1 Complexity Model Levels 379

2.2 Analytical Models 380

2.3 Finite-Element Method 384

2.4 Thermal Conductivity of Gases 388

3 Application to Thermoelectric Gas Sensors 390

3.1 Case Study 390

3.2 Analytical Model 392

3.3 Static FEM 396

3.4 Dynamic FEM 402

3.5 Device Optimization 405

Acknowledgments 407

Nomenclature 407

References 408

10 MODELING,SIMULATION,AND INFORMATION PROCESSING FOR DEVELOPMENT OF A POLYMERIC ELECTRONIC NOSE SYSTEM&R.D.S.Yadava 411

1 Introduction 411

2 Sensor Array Approach 414

2.1 System Characteristics 416

2.2 Sensing Platform and System Design 417

3 Sensor Transient Approach 419

4 Design and Modeling of SAW Sensing Platform 422

4.1 Generic Sensor Model 422

4.2 Designing a SAW Platform for Mass Sensitivity 426

4.3 Designing a SAW Platform for Multifrequeney Sensing 438

5 Vapor Solvation,Diffusion,and Polymer Loading 444

5.1 Solvation Model and Data Processing 445

5.2 Sorption Kinetics and Transient Signal Model 449

6 Data Mining and Simulation for Polymer Selection 453

6.1 Case Study of Explosive Vapor Detection 454

6.2 Case Study of Body-Odor Detection 456

7 Optimizing Data Processing Methods 462

7.1 Transient Signal Analysis 462

7.2 Steady-State Sensor Array Response Analysis 477

7.3 Enhancing Sensor Intelligence by Information Fusion 479

7.4 Simultaneous Recognition and Quantitation 481

8 Conclusion 485

Acknowledgments 488

References 488

INDEX 503