✍ Scribed by Katz E. (Ed.)
No coin nor oath required. For personal study only.
Edited by a renowned and much cited chemist, this book covers the whole span of molecular computers that are based on non-biological systems. The contributions by all the major scientists in the field provide an excellent overview of the latest developments in this rapidly expanding area.
A must-have for all researchers working on this very hot topic.
Perfectly complements Biomolecular Information Processing, also by Prof. Katz, and available as a two-volume set.
Cover
Half Title
Related Titles
Molecular and Supramolecular Information Processing: From Molecular Switches to Logic Systems
Copyright
Contents
Preface
List of Contributors
1. Molecular Information Processing: from Single Molecules to Supramolecular Systems and Interfaces – from Algorithms to Devices – Editorial Introduction
References
2. From Sensors to Molecular Logic: A Journey
2.1 Introduction
2.2 Designing Luminescent Switching Systems
2.3 Converting Sensing/Switching into Logic
2.4 Generalizing Logic
2.5 Expanding Logic
2.6 Utilizing Logic
2.7 Bringing in Physical Inputs
2.8 Summary and Outlook
Acknowledgments
References
3. Binary Logic with Synthetic Molecular and Supramolecular Species
3.1 Introduction
3.1.1 Information Processing: Semiconductor Devices versus Biological Structures
3.1.2 Toward Chemical Computers?
3.2 Combinational Logic Gates and Circuits
3.2.1 Basic Concepts
3.2.2 Bidirectional Half Subtractor and Reversible Logic Device
3.2.3 A Simple Unimolecular Multiplexer–Demultiplexer
3.2.4 An Encoder/Decoder Based on Ruthenium Tris(bipyridine)
3.2.5 All-Optical Integrated Logic Operations Based on Communicating Molecular Switches
3.3 Sequential Logic Circuits
3.3.1 Basic Concepts
3.3.2 Memory Effect in Communicating Molecular Switches
3.3.3 A Molecular Keypad Lock
3.3.4 A Set–Reset Memory Device Based on a Copper Rotaxane
3.4 Summary and Outlook
Acknowledgments
References
4. Photonically Switched Molecular Logic Devices
4.1 Introduction
4.2 Photochromic Molecules
4.3 Photonic Control of Energy and Electron Transfer Reactions
4.3.1 Energy Transfer
4.3.2 Electron Transfer
4.4 Boolean Logic Gates
4.5 Advanced Logic Functions
4.5.1 Half-Adders and Half-Subtractors
4.5.2 Multiplexers and Demultiplexers
4.5.3 Encoders and Decoders
4.5.4 Sequential Logic Devices
4.5.5 An All-Photonic Multifunctional Molecular Logic Device
4.6 Conclusion
References
5. Engineering Luminescent Molecules with Sensing and Logic Capabilities
5.1 Introduction
5.2 Engineering Luminescent Molecules
5.3 Logic Gates with the Same Modules in Different Arrangements
5.4 Consolidating AND Logic
5.5 ‘‘Lab-on-a-Molecule’’ Systems
5.6 Redox-Fluorescent Logic Gates
5.7 Summary and Perspectives
References
6. Supramolecular Assemblies for Information Processing
6.1 Introduction
6.2 Recognition of Metal Ion Inputs by Crown Ethers
6.3 Hydrogen-Bonded Supramolecular Assemblies as Logic Devices
6.4 Molecular Logic Gates with [2]Pseudorotaxane- and [2]Rotaxane-Based Switches
6.5 Supramolecular Host-Guest Complexes with Cyclodextrins and Cucurbiturils
6.6 Summary
Acknowledgments
References
7. Hybrid Semiconducting Materials: New Perspectives for Molecular-Scale Information Processing
7.1 Introduction
7.2 Synthesis of Semiconducting Thin Layers and Nanoparticles
7.2.1 Microwave Synthesis of Nanoparticles
7.2.2 Chemical Bath Deposition
7.2.2.1 Sulfide Ion Precursors
7.2.2.2 Commonly Used Ligand
7.3 Electrochemical Deposition
7.3.1 Nanoheterostructure Preparation
7.3.2 Nanoparticles Directed Self-Assembly
7.4 Organic Semiconductors–toward Hybrid Organic/Inorganic Materials
7.4.1 Self-Organization Motifs Exhibited by Acenes and Acene-Like Structures
7.4.2 Applications of Acenes in Organic Electronic Devices
7.5 Mechanisms of Photocurrent Switching Phenomena
7.5.1 Neat Semiconductor
7.5.2 Composite Semiconductor Materials
7.5.3 Semiconductor–Adsorbate Interactions
7.5.4 Surface-Modified Semiconductor
7.5.5 Optoelectronic Devices Based on Organic Molecules/Semiconductors
7.6 Digital Devices Based on PEPS Effect
7.7 Concluding Remarks
Acknowledgments
References
8. Toward Arithmetic Circuits in Subexcitable Chemical Media
8.1 Awakening Gates in Chemical Media
8.2 Collision-Based Computing
8.3 Localizations in Subexcitable BZ Medium
8.4 BZ Vesicles
8.5 Interaction Between Wave Fragments
8.6 Universality and Polymorphism
8.7 Binary Adder
8.7.1 Sum
8.7.2 Carry Out
8.8 Regular and Irregular BZ Disc Networks
8.8.1 Elementary Logic Gates
8.8.2 Half Adder
8.9 Memory Cells with BZ Discs
8.10 Conclusion
Acknowledgments
References
9. High-Concentration Chemical Computing Techniques for Solving Hard-To-Solve Problems, and their Relation to Numerical Optimization, Neural Computing, Reasoning under Uncertainty, and Freedom of Choice
9.1 What are Hard-To-Solve Problems and Why Solving Even One of Them is Important
9.1.1 What is so Good About Being Able to Solve Hard-To-Solve Problems from Some Exotic Class?
9.1.2 In Many Applications Areas –In Particular in Chemistry –There are Many Well-Defined Complex Problems
9.1.3 In Principle, There Exist Algorithms for Solving These Problems
9.1.4 These Algorithms may Take Too Much Time to be Practical
9.1.5 Feasible and Unfeasible Algorithms: General Idea
9.1.6 Solving Equations of Chemical Kinetics: An Example of a Feasible Algorithm
9.1.7 Straightforward Solution of Schr¨odinger Equation: An Example of an Unfeasible Algorithm
9.1.8 Straightforward Approach to Protein Folding: Another Example of an Unfeasible Algorithm
9.1.9 Feasible and Unfeasible Algorithms: Toward a Formal Description
9.1.10 Maybe the Problem Itself is Hard to Solve?
9.1.11 What Is a Problem in the First Place?
9.1.12 What is a Problem: Mathematics
9.1.13 A Description of a General Problem
9.1.14 What About Other Activity Areas?
9.1.15 What is a Problem: Theoretical Physics
9.1.16 What is a Problem: Engineering
9.1.17 Class NP
9.1.18 Class P and the P ?=NP Problem
9.1.19 Exhaustive Search: Why it is Possible and Why it is Not Feasible
9.1.20 Notion of NP-Complete Problems
9.1.21 Why Solving Even One NP-Complete (Hard-To-Solve) Problem is Very Important
9.1.22 Propositional Satisfiability: Historically the First NP-Complete Problem
9.1.23 What We Do
9.2 How Chemical Computing Can Solve a Hard-To-Solve Problem of Propositional Satisfiability
9.2.1 Chemical Computing: Main Idea
9.2.2 Why Propositional Satisfiability was Historically the First Problem for Which a Chemical Computing Scheme was Proposed
9.2.3 How to Apply Chemical Computing to Propositional Satisfiability: Matiyasevich’s Original Idea
9.2.4 A Precise Description of Matiyasevich’s Chemical Computer: First Example
9.2.5 A Precise Description of Matiyasevich’s Chemical Computer: Second Example
9.2.6 A Precise Description of Matiyasevich’s Chemical Computer: General Formula
9.2.7 A Simplified Version (Corresponding to Catalysis)
9.2.8 Simplified Equations: Example
9.2.9 Chemical Computations Implementing Matiyasevich’s Idea Are Too Slow
9.2.10 Natural Idea: Let us Use High-Concentration Chemical Reactions Instead
9.2.11 Resulting Equations
9.2.12 Discrete-Time Version of These Equations Have Already Been Shown to be Successful in Solving the Propositional Satisfiability Problem
9.2.13 Conclusion
9.2.14 Auxiliary Result: How to Select the Parameter Δt
9.3 The Resulting Method for Solving Hard Problems is Related to Numerical Optimization, Neural Computing, Reasoning under Uncertainty, and Freedom of Choice
9.3.1 Relation to Optimization: Why it is Important
9.3.2 Relation to Optimization: Main Idea
9.3.3 Relation to Numerical Optimization: Conclusion
9.3.4 Relation to Numerical Optimization: What Do We Gain from It?
9.3.5 Relation to Neural Computing
9.3.6 Relation to Reasoning Under Uncertainty
9.3.7 Relation to Freedom of Choice
Acknowledgments
References
10. All Kinds of Behavior are Possible in Chemical Kinetics: A Theorem and its Potential Applications to Chemical Computing
10.1 Introduction
10.1.1 Chemical Computing: A Brief Reminder
10.1.2 Chemical Computing: Remaining Theoretical Challenge
10.1.3 What We Do
10.2 Main Result
10.2.1 Chemical Kinetics Equations: A Brief Reminder
10.2.2 Chemical Kinetics Until Late 1950s
10.2.3 Belousov – Zhabotinsky Reaction and Further Discoveries
10.2.4 A Natural Hypothesis
10.2.5 Dynamical Systems
10.2.6 W.l.o.g., We Start at Time t = 0
10.2.7 Limited Time
10.2.8 Limited Values of xi
10.2.9 Limited Accuracy
10.2.10 Need to Consider Auxiliary Chemical Substances
10.2.11 Discussion
10.2.12 Effect of External Noise
10.3 Proof
Acknowledgments
References
11. Kabbalistic–Leibnizian Automata for Simulating the Universe
11.1 Introduction
11.2 Historical Background of Kabbalistic–Leibnizian Automata
11.3 Proof-Theoretic Cellular Automata
11.4 The Proof-Theoretic Cellular Automaton for Belousov–Zhabotinsky Reaction
11.5 The Proof-Theoretic Cellular Automaton for Dynamics of Plasmodium of Physarum polycephalum
11.6 Unconventional Computing as a Novel Paradigm in Natural Sciences
11.7 Conclusion
Acknowledgments
References
12. Approaches to Control of Noise in Chemical and Biochemical Information and Signal Processing
12.1 Introduction
12.2 From Chemical Information-Processing Gates to Networks
12.3 Noise Handling at the Gate Level and Beyond
12.4 Optimization of AND Gates
12.5 Networking of Gates
12.6 Conclusions and Challenges
Acknowledgments
References
13. Electrochemistry, Emergent Patterns, and Inorganic Intelligent Response
13.1 Introduction
13.2 Patten Formation in Complex Systems
13.3 Intelligent Response and Pattern Formation
13.3.1 Self-Organization in Systems Removed from the Equilibrium State
13.3.2 Patterns in Nature
13.3.3 Functional Self-Organizing Systems
13.3.4 Emergent Patterns and Associative Memory
13.4 Artificial Cognitive Materials
13.5 An Intelligent Electrochemical Platform
13.6 From Chemistry to Brain Dynamics
13.6.1 Understanding the Brain
13.6.2 Brain Dynamics
13.6.3 Electrochemical Dynamics
13.6.4 Experimental Paradigm for Information Processing in Complex Systems
13.7 Final Remarks
References
14. Electrode Interfaces Switchable by Physical and Chemical Signals Operating as a Platform for Information Processing
14.1 Introduction
14.2 Light-Switchable Modified Electrodes Based on Photoisomerizable Materials
14.3 Magnetoswitchable Electrodes Utilizing Functionalized Magnetic Nanoparticles or Nanowires
14.4 Potential-Switchable Modified Electrodes Based on Electrochemical Transformations of Functional Interfaces
14.5 Chemically/Biochemically Switchable Electrodes and Their Coupling with Biomolecular Computing Systems
14.6 Summary and Outlook
Acknowledgments
References
15. Conclusions and Perspectives
References
Index
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