Cover image for Optimal device design
Title:
Optimal device design
Publication Information:
New York : Cambridge University Press, 2010
Physical Description:
xi, 282 p. : ill. ; 25 cm.
ISBN:
9780521116602

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PSZ JB 30000010222023 TS171 O67 2010 Open Access Book
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Summary

Summary

Explore the frontier of device engineering by applying optimization to nanoscience and device design. This cutting-edge work shows how robust, manufacturable designs that meet previously unobtainable system specifications can be created using a combination of modern computer power, adaptive algorithms, and realistic device-physics models. Applying this method to nanoscience is a path to creating new devices with new functionality, and it could be the key design element in making nanoscience a practical technology. Basic introductory examples along with MATLAB code are included, through to more formal and sophisticated approaches, and specific applications and designs are examined. Essential reading for researchers and engineers in electronic devices, nanoscience, materials science, applied mathematics, and applied physics.


Author Notes

A. F. J. Levi is Professor of Electrical Engineering and of Physics and Astronomy at the University of Southern California. He joined USC after working for 10 years at ATT Bell Laboratories, New Jersey. Professor Levi is the author of the book Applied Quantum Mechanics, Second Edition (Cambridge University Press, 2006).
Stephan Haas is professor of Theoretical Condensed Matter Physics at the University of Southern California.


Table of Contents

Prefacep. ix
Acknowledgementsp. xi
1 Frontiers in device engineeringp. 1
1.1 Introductionp. 1
1.2 Example: Optimal design of atomic clustersp. 3
1.3 Design in the age of quantum technologyp. 6
1.4 Exploring nonintuitive design spacep. 14
1.5 Mathematical formulation of optimal device designp. 15
1.6 Local optimization using the adjoint methodp. 18
1.7 Global optimizationp. 21
1.8 Summaryp. 28
1.9 Referencesp. 29
2 Atoms-up designp. 32
2.1 Manmade nanostructuresp. 32
2.2 Long-range tight-binding modelp. 35
2.3 Target functions and convergence criterionp. 36
2.4 Atoms-up design of tight-binding clusters in continuous configuration spacep. 38
2.5 Optimal design in discrete configuration spacep. 42
2.6 Optimization and search algorithmsp. 45
2.7 Summaryp. 48
2.8 Referencesp. 49
3 Electron devices and electron transportp. 51
3.1 Introductionp. 51
3.2 Elastic electron transport and tunnel currentp. 57
3.3 Local optimal device design using elastic electron transport and tunnel currentp. 61
3.4 Inelastic electron transportp. 71
3.5 Summaryp. 85
3.6 Referencesp. 86
4 Aperiodic dielectric designp. 88
4.1 Introductionp. 88
4.2 Calculation of the scattered fieldp. 89
4.3 Optimizationp. 91
4.4 Resultsp. 93
4.5 Efficient local optimization using the adjoint methodp. 103
4.6 Finite difference frequency domain electromagnetic solverp. 104
4.7 Cost functionalp. 107
4.8 Gradient-based optimization using the adjoint methodp. 108
4.9 Results and comparison with experimentp. 109
4.10 Referencesp. 120
5 Design at the classical-quantum boundaryp. 123
5.1 Introductionp. 123
5.2 Non-local linear response theoryp. 124
5.3 Dielectric response of a diatomic moleculep. 126
5.4 Dielectric response of small clustersp. 129
5.5 Dielectric response of a metallic rodp. 135
5.6 Response of inhomogeneous structuresp. 137
5.7 Optimizationp. 141
5.8 Summary and outlookp. 147
5.9 Referencesp. 147
6 Robust optimization in high dimensionsp. 149
6.1 Introductionp. 149
6.2 Unconstrained robust optimizationp. 152
6.3 Constrained robust optimizationp. 170
6.4 Referencesp. 186
7 Mathematical framework for optimal designp. 189
7.1 Introductionp. 189
7.2 Constrained local optimal designp. 194
7.3 Local optimal design of an electronic devicep. 204
7.4 Techniques for global optimizationp. 228
7.5 Database of search iterationsp. 237
7.6 Summaryp. 244
7.7 Referencesp. 244
8 Future directionsp. 246
8.1 Introductionp. 246
8.2 Example: System complexity in a small laserp. 247
8.3 Sensitivity to atomic configurationp. 251
8.4 Realtime optimal design of moleculesp. 257
8.5 The path to quantum engineeringp. 258
8.6 Summaryp. 259
8.7 Referencesp. 260
Appendix A Global optimization algorithmsp. 262
A.1 Introductionp. 262
A.2 Tabu searchp. 262
A.3 Particle swarm algorithmp. 263
A.4 Simulated annealingp. 265
A.5 Two-phased algorithmsp. 268
A.6 Clustering algorithmsp. 269
A.7 Global optimization based on local techniquesp. 272
A.8 Global smoothingp. 273
A.9 Stopping rulesp. 274
A.10 Referencesp. 275
About the authorsp. 277
Indexp. 281