Systems Self-Assembly: Multidisciplinary SnapshotsElsevier, 2011 M09 22 - 304 páginas Systems Self-Assembly is the only book to showcase state-of-the-art self-assembly systems that arise from the computational, biological, chemical, physical and engineering disciplines. Written by world experts in each area, it provides a coherent, integrated view of both book practice examples and new trends with a clearly presented computational flavor. The unifying thread throughout the text is the computational nature of self-assembling systems. This book consists of 13 chapters dealing with a variety of topics such as the patterns of self-organised nanoparticle assemblies; biomimetic design of dynamic self-assembling systems; computing by self-assembly involving DNA molecules, polyominoes, and cells; evolutionary design of a model of self-assembling chemical structures; self-assembly as an engineering concept across size scales; and probabilistic analysis of self-assembled molecular networks. Other chapters focus on the programming language of dynamic self-assembly; self-assembled computer architectures; simulation of self-assembly processes using abstract reduction systems; computer aided search for optimal self-assembly systems; theoretical aspects of programmable self-assembly; emergent cooperativity in large-scale patterns; and automated self-assembling programming. Systems Self-Assembly is an ideal reference for scientists, researchers and post-graduate students; practitioners in industry, engineering and science; and managers, decision-makers and policy makers.
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Página viii
... Algorithm for Chemical Structures 83 4. Results 84 5. Discussion 96 6. Conclusion 97 Acknowledgements 98 References 98 Chapter 5. Self-Assembly as an Engineering Concept across Size Scales Sean Stauth, Christopher J. Morris and Babak ...
... Algorithm for Chemical Structures 83 4. Results 84 5. Discussion 96 6. Conclusion 97 Acknowledgements 98 References 98 Chapter 5. Self-Assembly as an Engineering Concept across Size Scales Sean Stauth, Christopher J. Morris and Babak ...
Página x
... Algorithms for Parameter and Structural Learning in SelfAssembly Model Systems 3. Self-Assembly Models for Unconventional Computing 4. Conclusions Acknowledgements References Index Colour Plate Section 229 233 241 243 243 245 246 250 ...
... Algorithms for Parameter and Structural Learning in SelfAssembly Model Systems 3. Self-Assembly Models for Unconventional Computing 4. Conclusions Acknowledgements References Index Colour Plate Section 229 233 241 243 243 245 246 250 ...
Página xii
... Dynamics simulation method that can cope with the formation and dissociation of strong bonds. They couple their DPD simulation environment to an evolutionary algorithm and they demonstrate how the latter can be xii Preface.
... Dynamics simulation method that can cope with the formation and dissociation of strong bonds. They couple their DPD simulation environment to an evolutionary algorithm and they demonstrate how the latter can be xii Preface.
Página xiii
Multidisciplinary Snapshots. evolutionary algorithm and they demonstrate how the latter can be used to automatically ... algorithms are they executing? and (2) if it was possible to understand the “programming language” of dynamic self ...
Multidisciplinary Snapshots. evolutionary algorithm and they demonstrate how the latter can be used to automatically ... algorithms are they executing? and (2) if it was possible to understand the “programming language” of dynamic self ...
Página 13
... algorithm to model the system dynamics. H = −ε l (1) ∑ ij lilj − εn ∑ ninj − εnl ∑ nilj − μ ∑ li. ij ij i This model reproduces many (though certainly not all—see below) of the types of patterns we [7,8] and others [3] observe ...
... algorithm to model the system dynamics. H = −ε l (1) ∑ ij lilj − εn ∑ ninj − εnl ∑ nilj − μ ∑ li. ij ij i This model reproduces many (though certainly not all—see below) of the types of patterns we [7,8] and others [3] observe ...
Contenido
1 | |
21 | |
49 | |
Chapter 4 Evolutionary Design of a Model of SelfAssembling Chemical Structures | 79 |
Chapter 5 SelfAssembly as an Engineering Concept across Size Scales | 101 |
Chapter 6 Probabilistic Analysis of SelfAssembled Molecular Networks | 123 |
Chapter 7 The Programming Language of Dynamic SelfAssembly | 153 |
Chapter 8 SelfAssembled Computer Architectures | 181 |
Chapter 9 Simulation of SelfAssembly Processes Using Abstract Reduction Systems | 199 |
Chapter 10 Computer Aided Search for Optimal SelfAssembly Systems | 225 |
Chapter 11 Programmable SelfAssemblyTheoretical Aspects and DNALinked Nanoparticles | 245 |
Chapter 12 From Microscopic Rules to Emergent Cooperativity in LargeScale Patterns | 259 |
Chapter 13 Automated SelfAssembling Programming | 281 |
Index | 309 |
Colour Plate Section | 311 |
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Términos y frases comunes
algorithm amphiphile architecture behavior binding sites bonds building blocks carbon nanotube Cayley graph cell cellular centrosome chapter chemical colloidal Colour Plate Section colour version complex components computation configuration connectivity counter crossbar dbDPD decrement defect mapping defined devices dimers DNA computing dynamic self-assembly DySA systems elements evolutionary evolutionary algorithm example fabrication finite function G.M. Whitesides glue Grzybowski implemented increment interactions interface kernel length scale ligation magnetic mechanism membrane micelles microtubules molecular molecules monomers motor proteins multiset nanofabric nanoparticle nanoscale nanostructured Nanotechnology nodes oligomers operations optimal P-systems parameters particles pattern Phys physical polymer polyominoes probabilistic problem proteins rectangle result rules scale-free self-assembly processes self-organisation sequence shown in Fig silicon simulation specific step sticky graphs strands structural redundancy substrate supertile symbols template tile system tion topology transformation Turing types unique wafer Wang tile Web graph
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Página v - What is a man, If his chief good and market of his time Be but to sleep and feed? a beast, no more. Sure he that made us with such large discourse, Looking before and after, gave us not That capability and god-like reason To fust in us unus'd.
Página 178 - Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000.
Página 32 - R'0 is the drag force per unit projected area of particle, d is the particle diameter, p, is the density of the particle, p is the density of the liquid, and g is the acceleration due to gravity Now, R...
Página 121 - Y. Tohmori, Y. Sakai, and H. Okamoto, "Hybrid integration of spot-size converted laser diode on planar lightwave circuit platform by passive alignment technique", IEEE Photon.
Página 201 - The rest of this chapter is organized as follows. The next section describes past movements in Japanese FDI.
Página 178 - This research was supported by the Division of Materials Sciences and Engineering. Office of Basic Energy Sciences, US Department of Energy under Contract No.
Página 197 - Logic gates and computation from assembled nanowire building blocks,
Página 100 - Treasurywala AM, Application of genetic algorithms to combinatorial synthesis: A computational approach to lead identification and lead optimization, J. Am. Chem. Soc., 118:1669-1676, 1996.
Página 120 - Positioning single atoms with a scanning tunneling microscope, Nature 344, 524-526 (1990).