Main Handbook of Nanoscience, Engineering, and Technology (Electrical Engineering Handbook)
Handbook of Nanoscience, Engineering, and Technology (Electrical Engineering Handbook)
William A. Goddard III, Donald Brenner, Sergey Edward Lyshevski, Gerald J Iafrate
Categories: Technique
Publisher: CRC Press
Series: Electrical Engineering Handbook
molecular1639
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electron665
quantum552
molecules471
nanotubes378
molecule364
electrons350
handbook of nanoscience335
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dna301
photonic294
silicon288
atoms278
diode257
circuits228
synthesis227
dendrimers227
nanoscale226
particle221
molecular electronic218
architectures212
appl208
atomic200
covalent199
tunneling187
simulations187
carbon nanotubes181
junctions181
optical177
bonding177
conductance175
bonds170
electrostatic168
nanostructures167
wires159
deformation146
Numerical Solution of Elliptic Problems
Society for Industrial Mathematics
Garrett Birkhoff, Robert E. Lynch
JavaFX: Developing Rich Internet Applications
Jim Clarke, Jim Connors, Eric J. Bruno
Handbook of
NANOSCIENCE,
and TECHNOLOGY
William A. Goddard, III
The Beckman Institute
Donald W. Brenner
Sergey Edward Lyshevski
Gerald J. Iafrate
CRC PR E S S
Boca Raton London New York Washington, D.C.
The front cover depicts a model of a gramicidin ionic channel showing the atoms forming the protein, and the conduction
pore defined by a representative potential isosurface. The back cover (left) shows a 3D simulation of a nano-arch termination/
zipping of a graphite crystal edge whose structure may serve as an element for a future nanodevice, and as a template for
nanotube growth. The back cover (right) shows five figures explained within the text.
Cover design by Benjamin Grosser, Imaging Technology Group, Beckman Institute for Advanced Science and Technology,
University of Illinois at Urbana-Champaign. Ionic channel image (front) by Grosser and Janet Sinn-Hanlon; data by Munoj
Gupta and Karl Hess. Graphite nano-arch simulation image (back left) by Grosser and Slava V. Rotkin; data by Rotkin.
Small figure images by (from top to bottom): 1) T. van der Straaten; 2) Rotkin and Grosser; 3) Rotkin and Grosser; 4) B.
Tuttle, Rotkin and Grosser; 5) Rotkin and M. Dequesnes. Background image by Glenn Fried.
Library of Congress Cataloging-in-Publication Data
Handbook of nanoscience, engineering, and technology / edited by William A. Goddard,
III … [et al.].
p. cm. — (Electrical engineering handbook series)
ISBN 0-8493-1200-0 (alk. paper)
1. Molecular electronics. 2. Nanotechnology. I. Goddard, William A., 1937– II. Series.
TK7874.8 .H35 2002
620′.5—dc21
This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with
permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish
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International Standard Book Number 0-8493-1200-0
Library of Congress Card Number 2002073329
Printed in the United States of America 1 2 3 4 5 6 7 8 9 0
Printed on acid-free paper
For my wife Karen, for her dedication and love, and for Sophie and Maxwell.
For my dearest wife Marina, and for my children Lydia and Alexander.
Sergey E. Lyshevski
To my wife, Kathy, and my family for their loving support and patience.
In the now-famous talk given in 1959, "There's Plenty of Room at the Bottom," Nobel Prize laureate
Richard Feynman outlined the promise of nanotechnology. It took over two decades, but the development
of the scanning tunneling microscope by IBM researchers in the early 1980s gave scientists and engineers
the ability not only to image atoms but also to manipulate atoms and clusters with a precision equal to
that of a chemical bond. Also in the 1980s, Eric Drexler wrote several books that went beyond Feynman's
vision to outline a fantastic technology that includes pumps, gears, and molecular assemblers consisting
of only hundreds to thousands of atoms that, if built, promised to revolutionize almost every aspect of
human endeavor. While Drexler's vision continues to stir controversy and skepticism in the science
community, it has served to inspire a curious young generation to pursue what is perceived as the next
frontier of technological innovation. Fueled by breakthroughs such as in the production and characterization of fullerene nanotubes, self-assembled monolayers, and quantum dots — together with advances
in theory and modeling and concerted funding from the National Nanotechnology Initiative in the U.S.
and similar programs in other countries — the promise of nanotechnology is beginning to come true.
Will nanotechnology revolutionize the human condition? Only time will tell. Clearly, though, this is an
exciting era in which to be involved in science and engineering at the nanometer scale.
Research at the nanometer scale and the new technologies being developed from this research are
evolving much too rapidly for a book like this to provide a complete picture of the field. Many journals
such as Nature, Science, and Physical Review Letters report critical breakthroughs in nanometer-scale
science and technology almost weekly. Instead, the intent of this handbook is to provide a wide-angle
snapshot of the state of the field today, including basic concepts, current challenges, and advanced research
results, as well as a glimpse of the many breakthroughs that will assuredly come in the next decade and
beyond. Specifically, visionary research and developments in nanoscale and molecular electronics, biotechnology, carbon nanotubes, and nanocomputers are reported. This handbook is intended for a wide
audience, with chapters that can be understood by laymen and educate and challenge seasoned researchers. A major goal of this handbook is to further develop and promote nanotechnology by expanding its
horizon to new and exciting areas and fields in engineering, science, medicine, and technology.
Dr. Brenner would like to thank his current and former colleagues for their intellectual stimulation and
personal support. Especially thanked are Dr. Brett Dunlap, Professor Barbara Garrison, Professor Judith
Harrison, Professor John Mintmire, Professor Rod Ruoff, Dr. Peter Schmidt, Professor Olga Shenderova,
Professor Susan Sinnott, Dr. Deepak Srivastava, and Dr. Carter White. Professor Brenner also wishes to
thank the Office of Naval Research, the National Science Foundation, the NASA Ames and NASA Langley
Research Centers, the Army Research Office, and the Department of Energy for supporting his research
group over the last 8 years.
This handbook is the product of the collaborative efforts of all contributors. Correspondingly, I would
like to acknowledge the authors' willingness, commitment, and support of this timely project. The support
and assistance I have received from the outstanding CRC team, lead by Nora Konopka, Helena Redshaw,
and Gail Renard, are truly appreciated and deeply treasured. In advance, I would like also to thank the
readers who will provide feedback on this handbook.
I would like to acknowledge the career support and encouragement from my colleagues, the Department
of Defense, the University of Notre Dame, and North Carolina State University.
William A. Goddard, III, obtained his Ph.D. in Engineering Science
(minor in Physics) from the California Institute of Technology,
Pasadena, in October 1964, after which he joined the faculty of the
Chemistry Department at Caltech and became a professor of theoretical chemistry in 1975.
In November 1984, Goddard was honored as the first holder of the
Charles and Mary Ferkel Chair in Chemistry and Applied Physics.
He received the Badger Teaching Prize from the Chemistry and
Chemical Engineering Division for Fall 1995.
Goddard is a member of the National Academy of Sciences (U.S.)
and the International Academy of Quantum Molecular Science. He
was a National Science Foundation (NSF) Predoctoral Fellow
(1960–1964) and an Alfred P. Sloan Foundation Fellow (1967–69).
In 1978 he received the Buck–Whitney Medal (for major contributions to theoretical chemistry in North America). In 1988 he received
the American Chemical Society Award for Computers in Chemistry.
In 1999 he received the Feynman Prize for Nanotechnology Theory (shared with Tahir Cagin and Yue
Qi). In 2000 he received a NASA Space Sciences Award (shared with N. Vaidehi, A. Jain, and G. Rodriquez).
He is a fellow of the American Physical Society and of the American Association for the Advancement
of Science. He is also a member of the American Chemical Society, the California Society, the California
Catalysis Society (president for 1997–1998), the Materials Research Society, and the American Vacuum
Society. He is a member of Tau Beta Pi and Sigma Xi.
His activities include serving as a member of the board of trustees of the Gordon Research Conferences (1988–1994), the Computer Science and Telecommunications Board of the National Research
Council (1990–1993), and the Board on Chemical Science and Technology (1980s), and a member
and chairman of the board of advisors for the Chemistry Division of the NSF (1980s). In addition,
Goddard serves or has served on the editorial boards of several journals ( Journal of the American
Chemical Society, Journal of Physical Chemistry, Chemical Physics, Catalysis Letters, Langmuir, and
Computational Materials Science).
Goddard is director of the Materials and Process Simulation Center (MSC) of the Beckman Institute
at Caltech. He was the principal investigator of an NSF Grand Challenge Application Group
(1992–1997) for developing advanced methods for quantum mechanics and molecular dynamics
simulations optimized for massively parallel computers. He was also the principal investigator for the
NSF Materials Research Group at Caltech (1985–1991).
Goddard is a co-founder (1984) of Molecular Simulations Inc., which develops and markets stateof-the-art computer software for molecular dynamics simulations and interactive graphics for
applications to chemistry, biological, and materials sciences. He is also a co-founder (1991) of
Schrödinger, Inc., which develops and markets state-of-the-art computer software using quantum
mechanical methods for applications to chemical, biological, and materials sciences. In 1998 he cofounded Materials Research Source LLC, dedicated to development of new processing techniques
for materials with an emphasis on nanoscale processing of semiconductors. In 2000 he co-founded
BionomiX Inc., dedicated to predicting the structures and functions of all molecules for all known
gene sequences.
Goddard's research activities focus on the use of quantum mechanics and of molecular dynamics
to study reaction mechanisms in catalysis (homogeneous and heterogeneous); the chemical and electronic properties of surfaces (semiconductors, metals, ceramics, and polymers); biochemical processes;
the structural, mechanical, and thermodynamic properties of materials (semiconductors, metals,
ceramics, and polymers); mesoscale dynamics; and materials processing. He has published over 440
scientific articles.
Donald W. Brenner is currently an associate professor in the
Department of Materials Science and Engineering at North Carolina State University. He earned his B.S. from the State University
of New York College at Fredonia in 1982 and his Ph.D. from
Pennsylvania State University in 1987, both in chemistry. He
joined the Theoretical Chemistry Section at the U.S. Naval
Research Laboratory as a staff scientist in 1987 and the North
Carolina State University faculty in 1994. His research interests
focus on using atomic and mesoscale simulation and theory to
understand technologically important processes and materials.
Recent research areas include first-principles predictions of the
mechanical properties of polycrystalline ceramics; crack dynamics;
dynamics of nanotribology, tribochemistry, and nanoindentation;
simulation of the vapor deposition and surface reactivity of covalent materials; fullerene-based materials and devices; self-assembled monolayers; simulations of shock and detonation chemistry; and potential function
development. He is also involved in the development of new cost-effective virtual reality technologies
for engineering education.
Brenner's awards include the Alcoa Foundation Engineering Research Achievement Award (2000),
the Veridian Medal Paper (co-author, 1999), an Outstanding Teacher Award from the North Carolina
State College of Engineering (1999), an NSF Faculty Early Career Development Award (1995), the
Naval Research Laboratory Chemistry Division Young Investigator Award (1991), the Naval Research
Laboratory Chemistry Division Berman Award for Technical Publication (1990), and the Xerox Award
from Penn State for the best materials-related Ph.D. thesis (1987). He was the scientific co-chair for
the Eighth (2000) and Ninth (2001) Foresight Conferences on Molecular Nanotechnology; and he is
a member of the editorial board for the journal Molecular Simulation, the Scientific Advisory Boards
of Nanotechnology Partners and of L.P. and Apex Nanotechnologies, and the North Carolina State
University Academy of Outstanding Teachers.
Sergey Edward Lyshevski earned his M.S. (1980) and Ph.D. (1987)
degrees from Kiev Polytechnic Institute, both in electrical engineering. From 1980 to 1993 Dr. Lyshevski held faculty positions at the
Department of Electrical Engineering at Kiev Polytechnic Institute
and the Academy of Sciences of Ukraine. From 1989 to 1993 he was
head of the Microelectronic and Electromechanical Systems Division
at the Academy of Sciences of Ukraine. From 1993 to 2002, he was
with Purdue University/Indianapolis. In 2002, Dr. Lyshevski joined
Rochester Institute of Technology, where he is a professor of electrical
engineering.
Lyshevski serves as the senior faculty fellow at the U.S. Surface and
Undersea Naval Warfare Centers. He is the author of eight books including Nano- and Micro-Electromechanical Systems: Fundamentals of Micro- and Nano- Engineering (for which he also acts as CRC series
editor; CRC Press, 2000); MEMS and NEMS: Systems, Devices, and Structures (CRC Press, 2002); and
author or co-author of more than 250 journal articles, handbook chapters, and regular conference papers.
His current teaching and research activities are in the areas of MEMS and NEMS (CAD, design, highfidelity modeling, data-intensive analysis, heterogeneous simulation, fabrication), intelligent large-scale
microsystems, learning configurations, novel architectures, self-organization, micro- and nanoscale
devices (actuators, sensors, logics, switches, memories, etc.), nanocomputers and their components,
reconfigurable (adaptive) defect-tolerant computer architectures, and systems informatics. Dr. Lyshevski
has been active in the design, application, verification, and implementation of advanced aerospace,
automotive, electromechanical, and naval systems.
Lyshevski has made 29 invited presentations (nationally and internationally) and has taught undergraduate and graduate courses in NEMS, MEMS, microsystems, computer architecture, motion devices,
integrated circuits, and signals and systems.
Gerald J. Iafrate joined the faculty of North Carolina State University
in August 2001. Previously, he was a professor at the University of
Notre Dame; he also served as Associate Dean for Research in the
College of Engineering, and as director of the newly established
University Center of Excellence in Nanoscience and Technology. He
has extensive experience in managing large interdisciplinary research
programs. From 1989 to 1997, Dr. Iafrate served as the Director of
the U.S. Army Research Office (ARO). As director, he was the Army's
key executive for the conduct of extramural research in the physical
and engineering sciences in response to DoD-wide objectives. Prior
to becoming Director of ARO, Dr. Iafrate was the Director of Electronic Devices Research at the U.S. Army Electronics Technology and
Devices Laboratory (ETDL). Working with the National Science
Foundation, he played a key leadership role in establishing the firstof-its-kind Army–NSF–University consortium.
He is currently a professor of electrical and computer engineering at North Carolina State University,
Raleigh, where his research interests include quantum transport in nanostructures such as resonant
tunneling diodes and quantum dots. He is also conducting studies in the area of quantum dissipation,
with emphasis on ratchet-like transport phenomena and nonequilibrium processes in nanosystems. Dr.
Iafrate is a fellow of the IEEE, APS, and AAAS.
S. Adiga
Kwong–Kit Choi
J.A. Harrison
and Engineering
U.S. Army Research Laboratory
Adelphi, MD
Damian G. Allis
Narayan R. Aluru
Beckman Institute for Advanced
D.A. Areshkin
Rashid Bashir
School of Electrical and
Department of Biomedical
Almadena Y.
Chtchelkanova
Scott A. Henderson
Strategic Analysis, Inc.
Starpharma Limited
Supriyo Datta
James C. Ellenbogen
G. Holan
The MITRE Corporation
Nanosystems Group
Michael Pycraft Hughes
R. Esfand
Dendritic Nanotechnologies Ltd.
Mt. Pleasant, MI
Guildford, Surrey, England
Dustin K. James
Michael Falvo
Department of Physics and
Jean-Pierre Leburton
Wing Kam Liu
Airat A. Nazarov
Umberto Ravaioli
Department of Mechanical
Russian Academy of Science
Institute for Metals
Superplasticity Problems
Ufa, Russia
J. Christopher Love
Gregory N. Parsons
Slava V. Rotkin
Sergey Edward
Lyshevski
Rochester Institute of
Department of Electrical
Magnus Paulsson
Rodney S. Ruoff
Karen Mardel
Meyya Meyyappan
Moffett Field, CA
Vladimiro Mujica
Wolfgang Porod
Dennis W. Prather
Department of Electrical and
Dong Qian
J.D. Schall
Ahmed S. Sharkawy
O.A. Shenderova
Shouyuan Shi
Radik R. Mulyukov
Mark A. Ratner
James T. Spencer
Donald A. Tomalia
Sean Washburn
Deepak Srivastava
James M. Tour
Center for Nanoscale Science
Martin Staedele
Corporate Research ND
Richard Superfine
Russell M. Taylor, II
Department of Computer
Science, Physics, and
DARPA/DSO, NRL
Boris I. Yakobson
Daryl Treger
S.J. Stuart
Stuart A. Wolf
Blair R. Tuttle
Behrend College
Min–Feng Yu
Department of Mechanical and
Trudy van der Straaten
Gregory J. Wagner
Ferdows Zahid
Section 1 The Promise of Nanotechnology and Nanoscience
There's Plenty of Room at the Bottom: An Invitation to Enter a New
Field of Physics Richard P. Feynman
Room at the Bottom, Plenty of Tyranny at the Top
Rising to the Feynman Challenge
Tyranny at the Top
New Forms of Switching and Storage
New Architectures
How Does Nature Do It?
Section 2 Molecular and Nano-Electronics: Concepts,
Challenges, and Designs
Engineering Challenges in Molecular Electronics
Molecular Electronic Computing Architectures
3.2 Silicon-Based Electrical Devices and Logic Circuits
3.3 CMOS Device Parameters and Scaling
3.4 Memory Devices
3.5 Opportunities and Challenges for Molecular Circuits
3.6 Summary and Conclusions
and Dustin K. James
Present Microelectronic Technology
Fundamental Physical Limitations of Present Technology
Molecular Electronics
4.4 Computer Architectures Based on Molecular Electronics
4.5 Characterization of Switches and Complex Molecular Devices
Nanoelectronic Circuit Architectures
Nanocomputer Architectronics and Nanotechnology
Architectures for Molecular Electronic Computers
5.2 Quantum-Dot Cellular Automata (QCA)
5.3 Single-Electron Circuits
5.4 Molecular Circuits
6.2 Brief History of Computers: Retrospects and Prospects
6.3 Nanocomputer Architecture and Nanocomputer Architectronics
6.4 Nanocomputer Architectronics and Neuroscience
6.5 Nanocomputer Architecture
6.6 Hierarchical Finite-State Machines and Their Use in Hardware and Software Design
6.7 Adaptive (Reconfigurable) Defect-Tolerant Nanocomputer Architectures,
Redundancy, and Robust Synthesis
6.8 Information Theory, Entropy Analysis, and Optimization
6.9 Some Problems in Nanocomputer Hardware–Software Modeling
and J. Christopher Love
7.3 Approach and Objectives
7.4 Polyphenylene-Based Molecular Rectifying Diode Switches: Design and
Theoretical Characterization
7.5 Novel Designs for Diode-Based Molecular Electronic Digital Circuits
Appendix 7.A
Appendix 7.B
Appendix 7.C
Spintronics — Spin-Based Electronics
QWIP: A Quantum Device Success
Stuart A. Wolf, Almadena Y. Chtchelkanova,
and Daryl Treger
8.1 Spin Transport Electronics in Metallic Systems
8.2 Issues in Spin Electronics
8.3 Potential Spintronics Devices
8.4 Quantum Computation and Spintronics
Kwong-Kit Choi
9.2 QWIP Focal Plane Array Technology
9.3 Optical Properties of Semiconductor Nanostructures
9.4 Transport Properties of Semiconductor Nanostructures
9.5 Noise in Semiconductor Nanostructures
9.6 Voltage-Tunable QWIPs
9.7 Quantum Grid Infrared Photodetectors
Section 3 Molecular Electronics: Fundamental Processes
Molecular Conductance Junctions: A Theory and Modeling
Progress Report Vladimiro Mujica and Mark A. Ratner
10.2 Experimental Techniques for Molecular Junction Transport
10.3 Coherent Transport: The Generalized Landauer Formula
10.4 Gating and Control of Junctions: Diodes and Triodes
10.5 The Onset of Inelasticity
10.6 Molecular Junction Conductance and Nonadiabatic Electron Transfer
10.7 Onset of Incoherence and Hopping Transport
10.8 Advanced Theoretical Challenges
10.9 Remarks
Modeling Electronics at the Nanoscale
Resistance of a Molecule
Narayan R. Aluru, Jean-Pierre Leburton,
William McMahon, Umberto Ravaioli, Slava V. Rotkin, Martin Staedele, Trudy van der
Straaten, Blair R. Tuttle, and Karl Hess
11.2 Nanostructure Studies of the Si-SiO2 Interface
11.3 Modeling of Quantum Dots and Artificial Atoms
11.4 Carbon Nanotubes and Nanotechnology
11.5 Simulation of Ionic Channels
Magnus Paulsson, Ferdows Zahid, and Supriyo Datta
12.2 Qualitative Discussion
12.3 Coulomb Blockade?
12.4 Nonequilibrium Green's Function (NEGF) Formalism
12.5 An Example: Quantum Point Contact (QPC)
12.6 Concluding Remarks
12.A MATLAB® Codes
Section 4 Manipulation and Assembly
Nanomanipulation: Buckling, Transport, and Rolling at the Nanoscale
Richard Superfine, Michael Falvo, Russell M. Taylor, II, and Sean Washburn
13.2 Instrumentation Systems: The Nanomanipulator and Combined Microscopy Tools
13.3 Nanomanipulation for Mechanical Properties
Nanoparticle Manipulation by Electrostatic Forces
Biologically Mediated Assembly of Artificial Nanostructures
and Microstructures Rashid Bashir
14.2 Theoretical Aspects of AC Electrokinetics
14.3 Applications of Dielectrophoresis on the Nanoscale
14.4 Limitations of Nanoscale Dielectrophoresis
15.2 Bio-Inspired Self-Assembly
15.3 The Forces and Interactions of Self-Assembly
15.4 Biological Linkers
15.5 State of the Art in Bio-Inspired Self-Assembly
15.6 Future Directions
Nanostructural Architectures from Molecular Building Blocks
Damian G. Allis and James T. Spencer
16.2 Bonding and Connectivity
16.3 Molecular Building Block Approaches
Section 5 Functional Structures and Mechanics
17.2 Linear Elastic Properties
17.3 Nonlinear Elasticity and Shell Model
17.4 Atomic Relaxation and Failure Mechanisms
17.5 Kinetic Theory of Strength
17.6 Coalescence of Nanotubes as a Reversed Failure
17.7 Persistence Length, Coils, and Random FuzzBalls of CNTS
Mechanics of Carbon Nanotubes
Dendrimers — An Enabling Synthetic Science to Controlled Organic
Nanostructures Donald A. Tomalia, Karen Mardel, Scott A. Henderson, G. Holan, and
Meyya Meyyappan and Deepak Srivastava
18.2 Structure and Properties of Carbon Nanotubes
18.3 Computational Modeling and Simulation
18.4 Nanotube Growth
18.5 Material Development
18.6 Application Development
Dong Qian, Gregory J. Wagner, Wing Kam Liu,
Min-Feng Yu, and Rodney S. Ruoff
19.2 Mechanical Properties of Nanotubes
19.3 Experimental Techniques
19.4 Simulation Methods
19.5 Mechanical Applications of Nanotubes
The Dendritic State
Unique Dendrimer Properties
Dendrimers as Nanopharmaceuticals and Nanomedical Devices
Dendrimers as Reactive Modules for the Synthesis of More Complex Nanoscale
Design and Applications of Photonic Crystals
Dennis W. Prather,
Ahmed S. Sharkawy, and Shouyuan Shi
21.2 Photonic Crystals — How They Work
21.3 Analogy between Photonic and Semiconductor Crystals
21.4 Analyzing Photonic Bandgap Structures
21.5 Electromagnetic Localization in Photonic Crystals
21.6 Doping of Photonic Crystals
21.7 Microcavities in Photonic Crystals
21.8 Photonic Crystal Applications
Nano- and Micromachines in NEMS and MEMS
Contributions of Molecular Modeling to Nanometer-Scale Science and
Technology Donald W. Brenner, O.A. Shenderova, J.D. Schall, D.A. Areshkin, S. Adiga,
Airat A. Nazarov and Radik R. Mulyukov
22.2 Preparation of Nanostructured Materials
22.3 Structure
22.4 Properties
23.1 Introduction to Nano- and Micromachines
23.2 Biomimetics and Its Application to Nano- and Micromachines: Directions
toward Nanoarchitectronics
23.3 Controlled Nano- and Micromachines
23.4 Synthesis of Nano- and Micromachines: Synthesis and Classification Solver
23.5 Fabrication Aspects
23.6 Introduction to Modeling and Computer-Aided Design: Preliminaries
23.7 High-Fidelity Mathematical Modeling of Nano- and Micromachines:
Energy-Based Quantum and Classical Mechanics and Electromagnetics
23.8 Density Functional Theory
23.9 Electromagnetics and Quantization
23.10 Conclusions
J.A. Harrison, and S.J. Stuart
24.1 Molecular Simulations
24.2 First-Principles Approaches: Forces on the Fly
24.3 Applications
There's Plenty of Room
at the Bottom: An
Invitation to Enter a
New Field of Physics
How Do We Write Small? • Information on a Small Scale •
Better Electron Microscopes • The Marvelous Biological
System • Miniaturizing the Computer • Miniaturization by
Evaporation • Problems of Lubrication • A Hundred Tiny
Hands • Rearranging the Atoms • Atoms in a Small World •
This transcript of the classic talk that Richard Feynman gave on December 29, 1959, at the annual meeting
of the American Physical Society at the California Institute of Technology (Caltech) was first published
in the February 1960 issue (Volume XXIII, No. 5, pp. 22–36) of Caltech's Engineering and Science, which
owns the copyright. It has been made available on the web at http://www.zyvex.com/nanotech/feynman.html with their kind permission.
For an account of the talk and how people reacted to it, see Chapter 4 of Nano! by Ed Regis. An
excellent technical introduction to nanotechnology is Nanosystems: Molecular Machinery, Manufacturing,
and Computation by K. Eric Drexler.
1.1 Transcript
I imagine experimental physicists must often look with envy at men like Kamerlingh Onnes, who
discovered a field like low temperature, which seems to be bottomless and in which one can go down
and down. Such a man is then a leader and has some temporary monopoly in a scientific adventure.
Percy Bridgman, in designing a way to obtain higher pressures, opened up another new field and was
able to move into it and to lead us all along. The development of ever-higher vacuum was a continuing
development of the same kind.
I would like to describe a field in which little has been done but in which an enormous amount can
be done in principle. This field is not quite the same as the others in that it will not tell us much of
fundamental physics (in the sense of "what are the strange particles?"); but it is more like solid-state
physics in the sense that it might tell us much of great interest about the strange phenomena that occur
in complex situations. Furthermore, a point that is most important is that it would have an enormous
number of technical applications.
Handbook of Nanoscience, Engineering, and Technology
What I want to talk about is the problem of manipulating and controlling things on a small scale.
As soon as I mention this, people tell me about miniaturization, and how far it has progressed today.
They tell me about electric motors that are the size of the nail on your small finger. And there is a device
on the market, they tell me, by which you can write the Lord's Prayer on the head of a pin. But that's
nothing; that's the most primitive, halting step in the direction I intend to discuss. It is a staggeringly
small world that is below. In the year 2000, when they look back at this age, they will wonder why it was
not until the year 1960 that anybody began seriously to move in this direction.
Why cannot we write the entire 24 volumes of the Encyclopaedia Britannica on the head of a pin?
Let's see what would be involved. The head of a pin is a sixteenth of an inch across. If you magnify it by
25,000 diameters, the area of the head of the pin is then equal to the area of all the pages of the Encyclopaedia
Britannica. Therefore, all it is necessary to do is to reduce in size all the writing in the encyclopedia by
25,000 times. Is that possible? The resolving power of the eye is about 1/120 of an inch — that is roughly
the diameter of one of the little dots on the fine half-tone reproductions in the encyclopedia. This, when
you demagnify it by 25,000 times, is still 80 angstroms in diameter — 32 atoms across, in an ordinary metal.
In other words, one of those dots still would contain in its area 1000 atoms. So, each dot can easily be
adjusted in size as required by the photoengraving, and there is no question that there is enough room on
the head of a pin to put all of the Encyclopaedia Britannica. Furthermore, it can be read if it is so written.
Let's imagine that it is written in raised letters of metal; that is, where the black is in the encyclopedia, we
have raised letters of metal that are actually 1/25,000 of their ordinary size. How would we read it?
If we had something written in such a way, we could read it using techniques in common use today.
(They will undoubtedly find a better way when we do actually have it written, but to make my point
conservatively I shall just take techniques we know today.) We would press the metal into a plastic
material and make a mold of it, then peel the plastic off very carefully, evaporate silica into the plastic
to get a very thin film, then shadow it by evaporating gold at an angle against the silica so that all the
little letters will appear clearly, dissolve the plastic away from the silica film, and then look through it
with an electron microscope!
There is no question that if the thing were reduced by 25,000 times in the form of raised letters on
the pin, it would be easy for us to read it today. Furthermore, there is no question that we would find it
easy to make copies of the master; we would just need to press the same metal plate again into plastic
and we would have another copy.
How Do We Write Small?
The next question is, how do we write it? We have no standard technique to do this now. But let me
argue that it is not as difficult as it first appears to be. We can reverse the lenses of the electron microscope
in order to demagnify as well as magnify. A source of ions, sent through the microscope lenses in reverse,
could be focused to a very small spot. We could write with that spot like we write in a TV cathode ray
oscilloscope, by going across in lines and having an adjustment that determines the amount of material
which is going to be deposited as we scan in lines.
This method might be very slow because of space charge limitations. There will be more rapid methods.
We could first make, perhaps by some photo process, a screen that has holes in it in the form of the
letters. Then we would strike an arc behind the holes and draw metallic ions through the holes; then we
could again use our system of lenses and make a small image in the form of ions, which would deposit
the metal on the pin.
A simpler way might be this (though I am not sure it would work): we take light and, through an
optical microscope running backwards, we focus it onto a very small photoelectric screen. Then electrons
come away from the screen where the light is shining. These electrons are focused down in size by the
electron microscope lenses to impinge directly upon the surface of the metal. Will such a beam etch away
the metal if it is run long enough? I don't know. If it doesn't work for a metal surface, it must be possible
to find some surface with which to coat the original pin so that, where the electrons bombard, a change
is made which we could recognize later.
There's Plenty of Room at the Bottom: An Invitation to Enter a New Field of Physics
There is no intensity problem in these devices — not what you are used to in magnification, where
you have to take a few electrons and spread them over a bigger and bigger screen; it is just the opposite.
The light which we get from a page is concentrated onto a very small area so it is very intense. The few
electrons which come from the photoelectric screen are demagnified down to a very tiny area so that,
again, they are very intense. I don't know why this hasn't been done yet!
That's the Encyclopedia Britannica on the head of a pin, but let's consider all the books in the world.
The Library of Congress has approximately 9 million volumes; the British Museum Library has 5 million
volumes; there are also 5 million volumes in the National Library in France. Undoubtedly there are
duplications, so let us say that there are some 24 million volumes of interest in the world.
What would happen if I print all this down at the scale we have been discussing? How much space
would it take? It would take, of course, the area of about a million pinheads because, instead of there
being just the 24 volumes of the encyclopedia, there are 24 million volumes. The million pinheads can
be put in a square of a thousand pins on a side, or an area of about 3 square yards. That is to say, the
silica replica with the paper-thin backing of plastic, with which we have made the copies, with all this
information, is on an area approximately the size of 35 pages of the encyclopedia. That is about half
as many pages as there are in this magazine. All of the information which all of mankind has ever
recorded in books can be carried around in a pamphlet in your hand — and not written in code, but
a simple reproduction of the original pictures, engravings, and everything else on a small scale without
loss of resolution.
What would our librarian at Caltech say, as she runs all over from one building to another, if I tell
her that, 10 years from now, all of the information that she is struggling to keep track of — 120,000
volumes, stacked from the floor to the ceiling, drawers full of cards, storage rooms full of the older books
— can be kept on just one library card! When the University of Brazil, for example, finds that their
library is burned, we can send them a copy of every book in our library by striking off a copy from the
master plate in a few hours and mailing it in an envelope no bigger or heavier than any other ordinary
airmail letter. Now, the name of this talk is "There Is Plenty of Room at the Bottom" — not just "There
Is Room at the Bottom." What I have demonstrated is that there is room — that you can decrease the
size of things in a practical way. I now want to show that there is plenty of room. I will not now discuss
how we are going to do it, but only what is possible in principle — in other words, what is possible
according to the laws of physics. I am not inventing antigravity, which is possible someday only if the
laws are not what we think. I am telling you what could be done if the laws are what we think; we are
not doing it simply because we haven't yet gotten around to it.
Information on a Small Scale
Suppose that, instead of trying to reproduce the pictures and all the information directly in its present
form, we write only the information content in a code of dots and dashes, or something like that, to
represent the various letters. Each letter represents six or seven "bits" of information; that is, you need
only about six or seven dots or dashes for each letter. Now, instead of writing everything, as I did before,
on the surface of the head of a pin, I am going to use the interior of the material as well.
Let us represent a dot by a small spot of one metal, the next dash by an adjacent spot of another metal,
and so on. Suppose, to be conservative, that a bit of information is going to require a little cube of atoms
5 × 5 × 5 — that is 125 atoms. Perhaps we need a hundred and some odd atoms to make sure that the
information is not lost through diffusion or through some other process.
I have estimated how many letters there are in the encyclopedia, and I have assumed that each of my
24 million books is as big as an encyclopedia volume, and have calculated, then, how many bits of
information there are (1015). For each bit I allow 100 atoms. And it turns out that all of the information
that man has carefully accumulated in all the books in the world can be written in this form in a cube
of material 1/200 of an inch wide — which is the barest piece of dust that can be made out by the human
eye. So there is plenty of room at the bottom! Don't tell me about microfilm! This fact — that enormous
amounts of information can be carried in an exceedingly small space — is, of course, well known to the
biologists and resolves the mystery that existed before we understood all this clearly — of how it could
be that, in the tiniest cell, all of the information for the organization of a complex creature such as
ourselves can be stored. All this information — whether we have brown eyes, or whether we think at all,
or that in the embryo the jawbone should first develop with a little hole in the side so that later a nerve
can grow through it — all this information is contained in a very tiny fraction of the cell in the form of
long-chain DNA molecules in which approximately 50 atoms are used for one bit of information about
the cell.
Better Electron Microscopes
If I have written in a code with 5 × 5 × 5 atoms to a bit, the question is, how could I read it today? The
electron microscope is not quite good enough — with the greatest care and effort, it can only resolve
about 10 angstroms. I would like to try and impress upon you, while I am talking about all of these
things on a small scale, the importance of improving the electron microscope by a hundred times. It is
not impossible; it is not against the laws of diffraction of the electron. The wavelength of the electron in
such a microscope is only 1/20 of an angstrom. So it should be possible to see the individual atoms. What
good would it be to see individual atoms distinctly? We have friends in other fields — in biology, for
instance. We physicists often look at them and say, "You know the reason you fellows are making so little
progress?" (Actually I don't know any field where they are making more rapid progress than they are in
biology today.) "You should use more mathematics, like we do." They could answer us — but they're
polite, so I'll answer for them: "What you should do in order for us to make more rapid progress is to
make the electron microscope 100 times better."
What are the most central and fundamental problems of biology today? They are questions like, what
is the sequence of bases in the DNA? What happens when you have a mutation? How is the base order
in the DNA connected to the order of amino acids in the protein? What is the structure of the RNA; is
it single-chain or double-chain, and how is it related in its order of bases to the DNA? What is the
organization of the microsomes? How are proteins synthesized? Where does the RNA go? How does it
sit? Where do the proteins sit? Where do the amino acids go in? In photosynthesis, where is the chlorophyll;
how is it arranged; where are the carotenoids involved in this thing? What is the system of the conversion
of light into chemical energy?
It is very easy to answer many of these fundamental biological questions; you just look at the thing!
You will see the order of bases in the chain; you will see the structure of the microsome. Unfortunately,
the present microscope sees at a scale which is just a bit too crude. Make the microscope one hundred
times more powerful, and many problems of biology would be made very much easier. I exaggerate, of
course, but the biologists would surely be very thankful to you — and they would prefer that to the
criticism that they should use more mathematics.
The theory of chemical processes today is based on theoretical physics. In this sense, physics supplies
the foundation of chemistry. But chemistry also has analysis. If you have a strange substance and you
want to know what it is, you go through a long and complicated process of chemical analysis. You can
analyze almost anything today, so I am a little late with my idea. But if the physicists wanted to, they
could also dig under the chemists in the problem of chemical analysis. It would be very easy to make an
analysis of any complicated chemical substance; all one would have to do would be to look at it and see
where the atoms are. The only trouble is that the electron microscope is 100 times too poor. (Later, I
would like to ask the question: can the physicists do something about the third problem of chemistry —
namely, synthesis? Is there a physical way to synthesize any chemical substance?)
The reason the electron microscope is so poor is that the f-value of the lenses is only 1 part to 1000;
you don't have a big enough numerical aperture. And I know that there are theorems which prove that
it is impossible, with axially symmetrical stationary field lenses, to produce an f-value any bigger than
so and so; and therefore the resolving power at the present time is at its theoretical maximum. But in
every theorem there are assumptions. Why must the field be symmetrical? I put this out as a challenge:
is there no way to make the electron microscope more powerful?
The Marvelous Biological System
The biological example of writing information on a small scale has inspired me to think of something
that should be possible. Biology is not simply writing information; it is doing something about it. A
biological system can be exceedingly small. Many of the cells are very tiny, but they are very active;
they manufacture various substances; they walk around; they wiggle; and they do all kinds of marvelous
things — all on a very small scale. Also, they store information. Consider the possibility that we too
can make a thing very small which does what we want — that we can manufacture an object that
maneuvers at that level!
There may even be an economic point to this business of making things very small. Let me remind
you of some of the problems of computing machines. In computers we have to store an enormous
amount of information. The kind of writing that I was mentioning before, in which I had everything
down as a distribution of metal, is permanent. Much more interesting to a computer is a way of
writing, erasing, and writing something else. (This is usually because we don't want to waste the
material on which we have just written. Yet if we could write it in a very small space, it wouldn't
make any difference; it could just be thrown away after it was read. It doesn't cost very much for
the material).
Miniaturizing the Computer
I don't know how to do this on a small scale in a practical way, but I do know that computing machines
are very large; they fill rooms. Why can't we make them very small, make them of little wires, little
elements — and by little, I mean little. For instance, the wires should be 10 or 100 atoms in diameter,
and the circuits should be a few thousand angstroms across. Everybody who has analyzed the logical
theory of computers has come to the conclusion that the possibilities of computers are very interesting
— if they could be made to be more complicated by several orders of magnitude. If they had millions
of times as many elements, they could make judgments. They would have time to calculate what is the
best way to make the calculation that they are about to make. They could select the method of analysis
which, from their experience, is better than the one that we would give to them. And in many other
ways, they would have new qualitative features.
If I look at your face I immediately recognize that I have seen it before. (Actually, my friends will say
I have chosen an unfortunate example here for the subject of this illustration. At least I recognize that it
is a man and not an apple.) Yet there is no machine which, with that speed, can take a picture of a face
and say even that it is a man; and much less that it is the same man that you showed it before — unless
it is exactly the same picture. If the face is changed; if I am closer to the face; if I am further from the
face; if the light changes — I recognize it anyway. Now, this little computer I carry in my head is easily
able to do that. The computers that we build are not able to do that. The number of elements in this
bone box of mine are enormously greater than the number of elements in our "wonderful" computers.
But our mechanical computers are too big; the elements in this box are microscopic. I want to make
some that are submicroscopic.
If we wanted to make a computer that had all these marvelous extra qualitative abilities, we would
have to make it, perhaps, the size of the Pentagon. This has several disadvantages. First, it requires too
much material; there may not be enough germanium in the world for all the transistors which would
have to be put into this enormous thing. There is also the problem of heat generation and power
consumption; TVA would be needed to run the computer. But an even more practical difficulty is that
the computer would be limited to a certain speed. Because of its large size, there is finite time required
to get the information from one place to another. The information cannot go any faster than the speed
of light — so, ultimately, when our computers get faster and faster and more and more elaborate, we
will have to make them smaller and smaller. But there is plenty of room to make them smaller. There is
nothing that I can see in the physical laws that says the computer elements cannot be made enormously
smaller than they are now. In fact, there may be certain advantages.
Miniaturization by Evaporation
How can we make such a device? What kind of manufacturing processes would we use? One possibility
we might consider, since we have talked about writing by putting atoms down in a certain arrangement,
would be to evaporate the material, then evaporate the insulator next to it. Then, for the next layer,
evaporate another position of a wire, another insulator, and so on. So, you simply evaporate until you
have a block of stuff which has the elements — coils and condensers, transistors and so on — of
exceedingly fine dimensions.
But I would like to discuss, just for amusement, that there are other possibilities. Why can't we
manufacture these small computers somewhat like we manufacture the big ones? Why can't we drill
holes, cut things, solder things, stamp things out, mold different shapes all at an infinitesimal level? What
are the limitations as to how small a thing has to be before you can no longer mold it? How many times
when you are working on something frustratingly tiny, like your wife's wristwatch, have you said to
yourself, "If I could only train an ant to do this!" What I would like to suggest is the possibility of training
an ant to train a mite to do this. What are the possibilities of small but movable machines? They may
or may not be useful, but they surely would be fun to make.
Consider any machine — for example, an automobile — and ask about the problems of making an
infinitesimal machine like it. Suppose, in the particular design of the automobile, we need a certain
precision of the parts; we need an accuracy, let's suppose, of 4/10,000 of an inch. If things are more
inaccurate than that in the shape of the cylinder and so on, it isn't going to work very well. If I make the
thing too small, I have to worry about the size of the atoms; I can't make a circle of "balls" so to speak,
if the circle is too small. So if I make the error — corresponding to 4/10,000 of an inch — correspond
to an error of 10 atoms, it turns out that I can reduce the dimensions of an automobile 4000 times,
approximately, so that it is 1 mm across. Obviously, if you redesign the car so that it would work with
a much larger tolerance, which is not at all impossible, then you could make a much smaller device.
It is interesting to consider what the problems are in such small machines. Firstly, with parts stressed
to the same degree, the forces go as the area you are reducing, so that things like weight and inertia are
of relatively no importance. The strength of material, in other words, is very much greater in proportion.
The stresses and expansion of the flywheel from centrifugal force, for example, would be the same
proportion only if the rotational speed is increased in the same proportion as we decrease the size. On
the other hand, the metals that we use have a grain structure, and this would be very annoying at small
scale because the material is not homogeneous. Plastics and glass and things of this amorphous nature
are very much more homogeneous, and so we would have to make our machines out of such materials.
There are problems associated with the electrical part of the system — with the copper wires and the
magnetic parts. The magnetic properties on a very small scale are not the same as on a large scale; there
is the "domain" problem involved. A big magnet made of millions of domains can only be made on a
small scale with one domain. The electrical equipment won't simply be scaled down; it has to be
redesigned. But I can see no reason why it can't be redesigned to work again.
Problems of Lubrication
Lubrication involves some interesting points. The effective viscosity of oil would be higher and higher
in proportion as we went down (and if we increase the speed as much as we can). If we don't increase
the speed so much, and change from oil to kerosene or some other fluid, the problem is not so bad. But
actually we may not have to lubricate at all! We have a lot of extra force. Let the bearings run dry; they
won't run hot because the heat escapes away from such a small device very, very rapidly.
This rapid heat loss would prevent the gasoline from exploding, so an internal combustion engine is
impossible. Other chemical reactions, liberating energy when cold, can be used. Probably an external
supply of electrical power would be most convenient for such small machines.
What would be the utility of such machines? Who knows? Of course, a small automobile would only
be useful for the mites to drive around in, and I suppose our Christian interests don't go that far. However,
we did note the possibility of the manufacture of small elements for computers in completely automatic
factories, containing lathes and other machine tools at the very small level. The small lathe would not
have to be exactly like our big lathe. I leave to your imagination the improvement of the design to take
full advantage of the properties of things on a small scale, and in such a way that the fully automatic
aspect would be easiest to manage.
A friend of mine (Albert R. Hibbs) suggests a very interesting possibility for relatively small machines.
He says that although it is a very wild idea, it would be interesting in surgery if you could swallow the
surgeon. You put the mechanical surgeon inside the blood vessel and it goes into the heart and "looks"
around. (Of course the information has to be fed out.) It finds out which valve is the faulty one and
takes a little knife and slices it out. Other small machines might be permanently incorporated in the
body to assist some inadequately functioning organ.
Now comes the interesting question: how do we make such a tiny mechanism? I leave that to you.
However, let me suggest one weird possibility. You know, in the atomic energy plants they have materials
and machines that they can't handle directly because they have become radioactive. To unscrew nuts
and put on bolts and so on, they have a set of master and slave hands, so that by operating a set of
levers here, you control the "hands" there, and can turn them this way and that so you can handle
things quite nicely.
Most of these devices are actually made rather simply, in that there is a particular cable, like a marionette
string, that goes directly from the controls to the "hands." But, of course, things also have been made
using servo motors, so that the connection between the one thing and the other is electrical rather than
mechanical. When you turn the levers, they turn a servo motor, and it changes the electrical currents in
the wires, which repositions a motor at the other end.
Now, I want to build much the same device — a master–slave system which operates electrically. But
I want the slaves to be made especially carefully by modern large-scale machinists so that they are 1/4
the scale of the "hands" that you ordinarily maneuver. So you have a scheme by which you can do things
at 1/4 scale anyway — the little servo motors with little hands play with little nuts and bolts; they drill
little holes; they are four times smaller. Aha! So I manufacture a 1/4-size lathe; I manufacture 1/4-size
tools; and I make, at the 1/4 scale, still another set of hands again relatively 1/4 size! This is 1/16 size,
from my point of view. And after I finish doing this I wire directly from my large-scale system, through
transformers perhaps, to the 1/16-size servo motors. Thus I can now manipulate the 1/16 size hands.
Well, you get the principle from there on. It is rather a difficult program, but it is a possibility. You
might say that one can go much farther in one step than from one to four. Of course, this all has to be
designed very carefully, and it is not necessary simply to make it like hands. If you thought of it very
carefully, you could probably arrive at a much better system for doing such things.
If you work through a pantograph, even today, you can get much more than a factor of four in even
one step. But you can't work directly through a pantograph which makes a smaller pantograph which
then makes a smaller pantograph — because of the looseness of the holes and the irregularities of
construction. The end of the pantograph wiggles with a relatively greater irregularity than the irregularity
with which you move your hands. In going down this scale, I would find the end of the pantograph on
the end of the pantograph on the end of the pantograph shaking so badly that it wasn't doing anything
sensible at all.
At each stage, it is necessary to improve the precision of the apparatus. If, for instance, having made
a small lathe with a pantograph, we find its lead screw irregular — more irregular than the large-scale
one —we could lap the lead screw against breakable nuts that you can reverse in the usual way back and
forth until this lead screw is, at its scale, as accurate as our original lead screws, at our scale.
We can make flats by rubbing unflat surfaces in triplicates together — in three pairs — and the flats
then become flatter than the thing you started with. Thus, it is not impossible to improve precision on
a small scale by the correct operations. So, when we build this stuff, it is necessary at each step to improve
the accuracy of the equipment by working for a while down there, making accurate lead screws, Johansen
blocks, and all the other materials which we use in accurate machine work at the higher level. We have
to stop at each level and manufacture all the stuff to go to the next level — a very long and very difficult
program. Perhaps you can figure a better way than that to get down to small scale more rapidly.
Yet, after all this, you have just got one little baby lathe 4000 times smaller than usual. But we were
thinking of making an enormous computer, which we were going to build by drilling holes on this lathe
to make little washers for the computer. How many washers can you manufacture on this one lathe?
A Hundred Tiny Hands
When I make my first set of slave "hands" at 1/4 scale, I am going to make ten sets. I make ten sets of
"hands," and I wire them to my original levers so they each do exactly the same thing at the same time
in parallel. Now, when I am making my new devices 1/4 again as small, I let each one manufacture ten
copies, so that I would have a hundred "hands" at the 1/16 size.
Where am I going to put the million lathes that I am going to have? Why, there is nothing to it; the
volume is much less than that of even one full-scale lathe. For instance, if I made a billion little lathes,
each 1/4000 of the scale of a regular lathe, there are plenty of materials and space available because in
the billion little ones there is less than 2% of the materials in one big lathe.
It doesn't cost anything for materials, you see. So I want to build a billion tiny factories, models of
each other, which are manufacturing simultaneously, drilling holes, stamping parts, and so on.
As we go down in size, there are a number of interesting problems that arise. All things do not
simply scale down in proportion. There is the problem that materials stick together by the molecular
(Van der Waals) attractions. It would be like this: after you have made a part and you unscrew the nut
from a bolt, it isn't going to fall down because the gravity isn't appreciable; it would even be hard to
get it off the bolt. It would be like those old movies of a man with his hands full of molasses, trying
to get rid of a glass of water. There will be several problems of this nature that we will have to be ready
to design for.
Rearranging the Atoms
But I am not afraid to consider the final question as to whether, ultimately — in the great future — we
can arrange the atoms the way we want; the very atoms, all the way down! What would happen if we
could arrange the atoms one by one the way we want them (within reason, of course; you can't put them
so that they are chemically unstable, for example).
Up to now, we have been content to dig in the ground to find minerals. We heat them and we do
things on a large scale with them, and we hope to get a pure substance with just so much impurity, and
so on. But we must always accept some atomic arrangement that nature gives us. We haven't got anything,
say, with a "checkerboard" arrangement, with the impurity atoms exactly arranged 1000 angstroms apart,
or in some other particular pattern. What could we do with layered structures with just the right layers?
What would the properties of materials be if we could really arrange the atoms the way we want them?
They would be very interesting to investigate theoretically. I can't see exactly what would happen, but I
can hardly doubt that when we have some control of the arrangement of things on a small scale we will
get an enormously greater range of possible properties that substances can have, and of different things
that we can do.
Consider, for example, a piece of material in which we make little coils and condensers (or their
solid state analogs) 1,000 or 10,000 angstroms in a circuit, one right next to the other, over a large
area, with little antennas sticking out at the other end — a whole series of circuits. Is it possible, for
example, to emit light from a whole set of antennas, like we emit radio waves from an organized set
of antennas to beam the radio programs to Europe? The same thing would be to beam the light out
in a definite direction with very high intensity. (Perhaps such a beam is not very useful technically
or economically.)
I have thought about some of the problems of building electric circuits on a small scale, and the
problem of resistance is serious. If you build a corresponding circuit on a small scale, its natural frequency
goes up, since the wavelength goes down as the scale; but the skin depth only decreases with the square
root of the scale ratio, and so resistive problems are of increasing difficulty. Possibly we can beat resistance
through the use of superconductivity if the frequency is not too high, or by other tricks.
Atoms in a Small World
When we get to the very, very small world — say circuits of seven atoms — we have a lot of new things
that would happen that represent completely new opportunities for design. Atoms on a small scale behave
like nothing on a large scale, for they satisfy the laws of quantum mechanics. So, as we go down and
fiddle around with the atoms down there, we are working with different laws, and we can expect to do
different things. We can manufacture in different ways. We can use not just circuits but some system
involving the quantized energy levels, or the interactions of quantized spins, etc.
Another thing we will notice is that, if we go down far enough, all of our devices can be mass produced
so that they are absolutely perfect copies of one another. We cannot build two large machines so that the
dimensions are exactly the same. But if your machine is only 100 atoms high, you only have to get it
correct to 1/2% to make sure the other machine is exactly the same size — namely, 100 atoms high!
At the atomic level, we have new kinds of forces and new kinds of possibilities, new kinds of effects.
The problems of manufacture and reproduction of materials will be quite different. I am, as I said,
inspired by the biological phenomena in which chemical forces are used in repetitious fashion to produce
all kinds of weird effects (one of which is the author).
The principles of physics, as far as I can see, do not speak against the possibility of maneuvering things
atom by atom. It is not an attempt to violate any laws; it is something, in principle, that can be done;
but in practice, it has not been done because we are too big.
Ultimately, we can do chemical synthesis. A chemist comes to us and says, "Look, I want a molecule
that has the atoms arranged thus and so; make me that molecule." The chemist does a mysterious thing
when he wants to make a molecule. He sees that it has that ring, so he mixes this and that, and he shakes
it, and he fiddles around. And, at the end of a difficult process, he usually does succeed in synthesizing
what he wants. By the time I get my devices working, so that we can do it by physics, he will have figured
out how to synthesize absolutely anything, so that this will really be useless. But it is interesting that it
would be, in principle, possible (I think) for a physicist to synthesize any chemical substance that the
chemist writes down. Give the orders and the physicist synthesizes it. How? Put the atoms down where
the chemist says, and so you make the substance. The problems of chemistry and biology can be greatly
helped if our ability to see what we are doing, and to do things on an atomic level, is ultimately developed
— a development which I think cannot be avoided.
Now, you might say, "Who should do this and why should they do it?" Well, I pointed out a few of
the economic applications, but I know that the reason that you would do it might be just for fun. But
have some fun! Let's have a competition between laboratories. Let one laboratory make a tiny motor
which it sends to another lab which sends it back with a thing that fits inside the shaft of the first motor.
Just for the fun of it, and in order to get kids interested in this field, I would propose that someone who
has some contact with the high schools think of making some kind of high school competition. After
all, we haven't even started in this field, and even the kids can write smaller than has ever been written
before. They could have competition in high schools. The Los Angeles high school could send a pin to
the Venice high school on which it says, "How's this?" They get the pin back, and in the dot of the "i" it
says, "Not so hot."
Perhaps this doesn't excite you to do it, and only economics will do so. Then I want to do something,
but I can't do it at the present moment because I haven't prepared the ground. It is my intention to offer
a prize of $1000 to the first guy who can take the information on the page of a book and put it on an
area 1/25,000 smaller in linear scale in such manner that it can be read by an electron microscope.
And I want to offer another prize — if I can figure out how to phrase it so that I don't get into a mess
of arguments about definitions — of another $1000 to the first guy who makes an operating electric
motor — a rotating electric motor which can be controlled from the outside and, not counting the leadin wires, is only a 1/64-inch cube.
I do not expect that such prizes will have to wait very long for claimants.
Room at the Bottom,
Plenty of Tyranny
How Does Nature Do It? .
2.1 Rising to the Feynman Challenge
Richard Feynman is generally regarded as one of the fathers of nanotechnology. In giving his landmark
presentation to the American Physical Society on December 29, 1959, at Caltech, his title line was, "There's
Plenty of Room at the Bottom." At that time, Feynman extended an invitation for "manipulating and
controlling things on a small scale, thereby entering a new field of physics which was bottomless, like
low-temperature physics." He started with the question, can we "write the Lord's prayer on the head of
a pin," and immediately extended the goal to the entire 24 volumes of the Encyclopaedia Britannica. By
following the Gedanken Experiment, Feynman showed that there is no physical law against the realization
of such goals: if you magnify the head of a pin by 25,000 diameters, its surface area is then equal to that
of all the pages in the Encyclopaedia Britannica.
Feynman's dreams of writing small have all been fulfilled and even exceeded in the past decades. Since
the advent of scanning tunneling microscopy, as introduced by Binnig and Rohrer, it has been repeatedly
demonstrated that single atoms can not only be conveniently represented for the human eye but manipulated as well. Thus, it is conceivable to store all the books in the world (which Feynman estimates to
contain 1015 bits of information) on the area of a credit card! The encyclopedia, having around 109 bits
of information, can be written on about 1/100 the surface area of the head of a pin.
One need not look to atomic writing to achieve astonishing results: current microchips contain close
to 100 million transistors. A small number of such chips could not only store large amounts of information
(such as the Encyclopaedia Britannica); they can process it with GHz speed as well. To find a particular
word takes just a few nanoseconds. Typical disk hard drives can store much more than the semiconductor
chips, with a trade-off for retrieval speeds. Feynman's vision for storing and retrieving information on
a small scale was very close to these numbers. He did not ask himself what the practical difficulties were
in achieving these goals, but rather asked only what the principal limitations were. Even he could not
possibly foresee the ultimate consequences of writing small and reading fast: the creation of the Internet.
Sifting through large databases is, of course, what is done during Internet browsing. It is not only the
microrepresentation of information that has led to the revolution we are witnessing but also the ability
to browse through this information at very high speeds.
Can one improve current chip technology beyond the achievements listed above? Certainly! Further
improvements are still expected just by scaling down known silicon technology. Beyond this, if it were
possible to change the technology completely and create transistors the size of molecules, then one could
fit hundreds of billions of transistors on a chip. Changing technology so dramatically is not easy and less
likely to happen. A molecular transistor that is as robust and efficient as the existing ones is beyond
current implementation capabilities; we do not know how to achieve such densities without running
into problems of excessive heat generation and other problems related to highly integrated systems.
However, Feynman would not be satisfied that we have exhausted our options. He still points to the
room that opens if the third dimension is used. Current silicon technology is in its essence (with respect
to the transistors) a planar technology. Why not use volumes, says Feynman, and put all books of the
world in the space of a small dust particle? He may be right, but before assessing the chances of this
happening, I would like to take you on a tour to review some of the possibilities and limitations of current
planar silicon technology.
2.2 Tyranny at the Top
Yes, we do have plenty of room at the bottom. However, just a few years after Feynman's vision was
published, J. Morton from Bell Laboratories noticed what he called the tyranny of large systems. This
tyranny arises from the fact that scaling is, in general, not part of the laws of nature. For example, we
know that one cannot hold larger and larger weights with a rope by making the rope thicker and thicker.
At some point the weight of the rope itself comes into play, and things may get out of hand. As a corollary,
why should one, without such difficulty, be able to make transistors smaller and smaller and, at the same
time, integrate more of them on a chip? This is a crucial point that deserves some elaboration.
It is often said that all we need is to invent a new type of transistor that scales to atomic size. The
question then arises: did the transistor, as invented in 1947, scale to the current microsize? The answer
is no! The point-contact transistor, as it was invented by Bardeen and Brattain, was much smaller than
a vacuum tube. However, its design was not suitable for aggressive scaling. The field-effect transistor,
based on planar silicon technology and the hetero-junction interface of silicon and silicon dioxide with
a metal on top (MOS technology), did much better in this respect. Nevertheless, it took the introduction
of many new concepts (beginning with that of an inversion layer) to scale transistors to the current size.
This scalability alone would still not have been sufficient to build large integrated systems on a chip.
Each transistor develops heat when operated, and a large number of them may be better used as a
soldering iron than for computing. The saving idea was to use both electron and hole-inversion layers
to form the CMOS technology. The transistors of this technology create heat essentially only during
switching operation, and heat generation during steady state is very small. A large system also requires
interconnection of all transistors using metallic "wires." This becomes increasingly problematic when
large numbers of transistors are involved, and many predictions have been made that it could not be
done beyond a certain critical density of transistors. It turned out that there never was such a critical
density for interconnection, and we will discuss the very interesting reason for this below. Remember
that Feynman never talked about the tyranny at the top. He only was interested in fundamental limitations. The exponential growth of silicon technology with respect to the numbers of transistors on a chip
seems to prove Feynman right, at least up to now. How can this be if the original transistors were not
scalable? How could one always find a modification that permitted further scaling?
One of the reasons for continued miniaturization of silicon technology is that its basic idea is very
flexible: use solids instead of vacuum tubes. The high density of solids permits us to create very small
structures without hitting the atomic limit. Gas molecules or electrons in tubes have a much lower density
than electrons or atoms in solids typically have. One has about 1018 atoms in a cm3 of gas but 1023 in a
cm3 of a solid. Can one therefore go to sizes that would contain only a few hundred atoms with current
silicon technology? I believe not. The reason is that current technology is based on the doping of silicon
with donors and acceptors to create electron- and hole-inversion layers. The doping densities are much
lower than the densities of atoms in a solid, usually below 1020 per cm3. Therefore, to go to the ultimate
limits of atomic size, a new type of transistor, without doping, is needed. We will discuss such possibilities
below. But even if we have such transistors, can they be interconnected? Interestingly enough, interconnection problems have always been overcome in the past. The reason was that use of the third dimension
has been made for interconnects. Chip designers have used the third dimension — not to overcome the
limitations that two dimensions place on the number of transistors, but to overcome the limitations that
two dimensions present for interconnecting the transistors. There is an increasing number of stacks of
metal interconnect layers on chips — 2, 5, 8. How many can we have? (One can also still improve the
conductivity of the metals in use by using, for example, copper technology.)
Pattern generation is, of course, key for producing the chips of silicon technology and represents
another example of the tyranny of large systems. Chips are produced by using lithographic techniques.
Masks that contain the desired pattern are placed above the chip material, which is coated with photosensitive layers that are exposed to light to engrave the pattern. As the feature sizes become smaller and
smaller, the wavelength of the light needs to be reduced. The current work is performed in the extreme
ultraviolet, and future scaling must overcome considerable obstacles. Why can one not use the atomic
resolution of scanning tunneling microscopes? The reason is, of course, that the scanning process takes
time; and this would make efficient chip production extremely difficult. One does need a process that
works "in parallel" like photography. In principle there are many possibilities to achieve this, ranging
from the use of X-rays to electron and ion beams and even self-organization of patterns in materials as
known in chemistry and biology. One cannot see principal limitations here that would impede further
scaling. However, efficiency and expense of production do represent considerable tyranny and make it
difficult to predict what course the future will take. If use is made of the third dimension, however, optical
lithography will go a long way.
Feynman suggested that there will be plenty of room at the bottom only when the third dimension is
used. Can we also use it to improve the packing density of transistors? This is not going to be so easy.
The current technology is based on a silicon surface that contains patterns of doping atoms and is topped
by silicon dioxide. To use the third dimension, a generalization of the technology is needed. One would
need another layer of silicon on top of the silicon dioxide, and so forth. Actually, such technology does
already exist: silicon-on-insulator (SOI) technology. Interestingly enough, some devices that are currently
heralded by major chip producers as devices of the future are SOI transistors. These may be scalable
further than current devices and may open the horizon to the use of the third dimension. Will they open
the way to unlimited growth of chip capacity? Well, there is still heat generation and other tyrannies that
may prevent the basically unlimited possibilities that Feynman predicted. However, billions of dollars of
business income have overcome most practical limitations (the tyranny) and may still do so for a long
time to come. Asked how he accumulated his wealth, Arnold Beckman responded: "We built a pH-meter
and sold it for three hundred dollars. Using this income, we built two and sold them for $600 … and
then 4, 8, … ." This is, of course, the well-known story of the fast growth of a geometric series as known
since ages for the rice corns on the chess board. Moore's law for the growth of silicon technology is
probably just another such example and therefore a law of business rather than of science and engineering.
No doubt, it is the business income that will determine the limitations of scaling to a large extent. But
then, there are also new ideas.
2.3 New Forms of Switching and Storage
Many new types of transistors or switching devices have been investigated and even mass fabricated in
the past decades. Discussions have focused on GaAs and III-V compound materials because of their
special properties with respect to electron speed and the possibility of creating lattice-matched interfaces
and layered patterns of atomic thickness. Silicon and silicon-dioxide have very different lattice constants
(spacing between their atoms). It is therefore difficult to imagine that the interface between them can be
electronically perfect. GaAs and AlAs on the other side have almost equal lattice spacing, and two crystals
can be perfectly placed on top of each other. The formation of superlattices of such layers of semiconductors has, in fact, been one of the bigger achievements of recent semiconductor technology and was
made possible by new techniques of crystal growth (molecular beam epitaxy, metal organic chemical
vapor deposition, and the like). Quantum wells, wires, and dots have been the subject of extremely
interesting research and have enriched quantum physics for example, by the discovery of the Quantum
Hall Effect and the Fractional Quantum Hall effect. Use of such layers has also brought significant progress
to semiconductor electronics. The concept of modulation doping (selective doping of layers, particularly
involving pseudomorphic InGaAs) has led to modulation-doped transistors that hold the current speed
records and are used for microwave applications. The removal of the doping to neighboring layers has
permitted the creation of the highest possible electron mobilities and velocities. The effect of resonant
tunneling has also been shown to lead to ultrafast devices and applications that reach to infrared
frequencies, encompassing in this way both optics and electronics applications. When it comes to largescale integration, however, the tyranny from the top has favored silicon technology. Silicon dioxide, as
an insulator, is superior to all possible III-V compound materials; and its interface with silicon can be
made electronically perfect enough, at least when treated with hydrogen or deuterium.
When it comes to optical applications, however, silicon is inefficient because it is an indirect semiconductor and therefore cannot emit light efficiently. Light generation may be possible by using silicon.
However, this is limited by the laws of physics and materials science. It is my guess that silicon will have
only limited applications for optics, much as III-V compounds have for large-scale integrated electronics.
III-V compounds and quantum well layers have been successfully used to create efficient light-emitting
devices including light-emitting and semiconductor laser diodes. These are ubiquitous in every household, e.g., in CD players and in the back-lights of cars. New forms of laser diodes, such as the so-called
vertical cavity surface emitting laser diodes (VCSELs), are even suitable to relatively large integration.
One can put thousands and even millions of them on a chip. Optical pattern generation has made great
advances by use of selective superlattice intermixing (compositionally disordered III-V compounds and
superlattices have a different index of refraction) and by other methods. This is an area in great flux and
with many possibilities for miniaturization. Layered semiconductors and quantum well structures have
also led to new forms of lasers such as the quantum cascade laser. Feynman mentioned in his paper the
use of layered materials. What would he predict for the limits of optical integration and the use of
quantum effects due to size quantization in optoelectronics?
A number of ideas are in discussion for new forms of ultrasmall electronic switching and storage
devices. Using the simple fact that it takes a finite energy to bring a single electron from one capacitor
plate to the other (and using tunneling for doing so), single-electron transistors have been proposed and
built. The energy for this single-electron switching process is inversely proportional to the area of the
capacitor. To achieve energies that are larger than the thermal energy at room temperature (necessary
for robust operation), extremely small capacitors are needed. The required feature sizes are of the order
of one nanometer. There are also staggering requirements for material purity and perfection since singly
charged defects will perturb operation. Nevertheless, Feynman may have liked this device because the
limitations for its use are not due to physical principles. It also has been shown that memory cells storing
only a few electrons do have some very attractive features. For example, if many electrons are stored in
a larger volume, a single material defect can lead to unwanted discharge of the whole volume. If, on the
other hand, all these electrons are stored in a larger number of quantum dots (each carrying few electrons),
a single defect can discharge only a single dot, and the remainder of the stored charge stays intact.
Two electrons stored on a square-shaped "quantum dot" have been proposed as a switching element
by researchers at Notre Dame. The electrons start residing in a pair of opposite corners of the square
and are switched to the other opposite corner. This switching can be effected by the electrons residing
in a neighboring rectangular dot. Domino-type effects can thus be achieved. It has been shown that
architectures of cellular neural networks (CNNs) can be created that way as discussed briefly below.
A new field referred to as spintronics is developing around the spin properties of particles. Spin
properties have not been explored in conventional electronics and enter only indirectly, through the Pauli
principle, into the equations for transistors. Of particular interest in this new area are particle pairs that
exhibit quantum entanglement. Consider a pair of particles in a singlet spin-state sent out to detectors
or spin analyzers in opposite directions. Such a pair has the following remarkable properties: measurements of the spin on each side separately give random values of the spin (up/down). However, the spin
of one side is always correlated to the spin on the other side. If one is up, the other is down. If the spin
analyzers are rotated relative to each other, then the result for the spin pair correlation shows rotational
symmetry. A theorem of Bell proclaims such results incompatible with Einstein's relativity and suggests
the necessity of instantaneous influences at a distance. Such influences do not exist in classical information
theory and are therefore considered a quantum addition to classical information. This quantum addition
provides part of the novelty that is claimed for possible future quantum computers. Spintronics and
entanglement are therefore thought to open new horizons for computing.
Still other new device types use the wave-like nature of electrons and the possibility to guide these
waves by externally controllable potential profiles. All of these devices are sensitive to temperature and
defects, and it is not clear whether they will be practical. However, new forms of architectures may open
new possibilities that circumvent the difficulties.
2.4 New Architectures
Transistors of the current technology have been developed and adjusted to accommodate the tyranny
from the top, in particular the demands set forth by the von Neuman architecture of conventional
computers. It is therefore not surprising that new devices are always looked at with suspicion by design
engineers and are always found wanting with respect to some tyrannical requirement. Many regard it
extremely unlikely that a completely new device will be used for silicon chip technology. Therefore,
architectures that deviate from von Neuman's principles have received increasing attention. These architectures invariably involve some form of parallelism. Switching and storage is not localized to a single
transistor or small circuit. The devices are connected to each other, and their collective interactions are
the basis for computation. It has been shown that such collective interactions can perform some tasks
in ways much superior to von Neuman's sequential processing.
One example for such new principles is the cellular neural network (CNN) type of architectures. Each
cell is connected by a certain coupling constant to its nearest neighbors, and after interaction with each
other, a large number of cells settle on a solution that hopefully is the desired solution of a problem that
cannot easily be done with conventional sequential computation. This is, of course, very similar to the
advantages of parallel computation (computation by use of more than one processor) with the difference
that it is not processors that interact and compute in parallel but the constituent devices themselves.
CNNs have advantageously been used for image processing and other specialized applications and can
be implemented in silicon technology. It appears that CNNs formed by using new devices, such as the
coupled square quantum dots discussed above, could (at least in principle) be embedded into a conventional chip environment to perform a certain desired task; and new devices could be used that way in
connection with conventional technology. There are at least three big obstacles that need to be overcome
if this goal should be achieved. The biggest problem is posed by the desire to operate at room temperature.
As discussed above, this frequently is equivalent to the requirement that the single elements of the CNN
need to be extremely small, on the order of one nanometer. This presents the second problem — to
create such feature sizes by a lithographic process. Third, each element of the CNN needs to be virtually
perfect and free of defects that would impede its operation. Can one create such a CNN by the organizing
and self-organizing principles of chemistry on semiconductor surfaces? As Dirac once said (in connection
with difficult problems), "one must try." Of course, it will be tried only if an important problem exists
that defies conventional solution. An example would be the cryptographically important problem of
factorizing large numbers. It has been shown that this problem may find a solution through quantum
computation.
The idea of quantum computation has, up to now, mainly received the attention of theoreticians who
have shown the superior power of certain algorithms that are based on a few quantum principles. One
such principle is the unitarity of certain operators in quantum mechanics that forms a solid basis for the
possibility of quantum computing. Beyond this, it is claimed that the number of elements of the set of
parameters that constitutes quantum information is much larger than the comparable set used in all of
classical information. This means there are additional quantum bits (qubits) of information that are not
covered by the known classical bits. In simpler words, there are instantaneous action at a distance and
connected phenomena, such as quantum teleportation, that have not been used classically but can be
used in future quantum information processing and computation. These claims are invariably based on
the theorem of Bell and are therefore subject to some criticism. It is well known that the Bell theorem
has certain loopholes that can be closed only if certain time dependencies of the involved parameters are
excluded. This means that even if the Bell theorem were general otherwise, it does not cover the full
classical parameter space. How can one then draw conclusions about the number of elements in parameter
sets for classical and quantum information? In addition, recent work has shown that the Bell theorem
excludes practically all time-related parameters — not only those discussed in the well-known loopholes.
What I want to say here is that the very advanced topic of quantum information complexity will need
further discussion even about its foundations. Beyond this, obstacles exist for implementation of qubits
due to the tyranny from the top. It is necessary to have a reasonably large number of qubits in order to
implement the quantum computing algorithms and make them applicable to large problems. All of these
qubits need to be connected in a quantum mechanical coherent way. Up to now, this coherence has
always necessitated the use of extremely low temperatures, at least when electronics (as opposed to optics)
is the basis for implementation. With all these difficulties, however, it is clear that there are great
opportunities for solving problems of new magnitude by harnessing the quantum world.
2.5 How Does Nature Do It?
Feynman noticed that nature has already made use of nanostructures in biological systems with greatest
success. Why do we not copy nature? Take, for example, biological ion channels. These are tiny pores
formed by protein structures. Their opening can be as small as a few one-tenths of a nanometer. Ion
currents are controlled by these pores that have opening and closing gates much as transistors have. The
on/off current ratio of ion channels is practically infinite, which is a very desirable property for large
systems. Remember that we do not want energy dissipation when the system is off. Transistors do not
come close to an infinite on/off ratio, which represents a big design problem. How do the ion channels
do it? The various gating mechanisms are not exactly understood, but they probably involve changes in
the aperture of the pore by electrochemical mechanisms. Ion channels do not only switch currents
perfectly. They also can choose the type of ions they let through and the type they do not. Channels
perform in this way a multitude of functions. They regulate our heart rate, kill bacteria and cancer cells,
and discharge and recharge biological neural networks, thus forming elements of logic and computation.
The multitude of functions may be a great cure for some of the tyranny from the top as Jack Morton
has pointed out in his essay "From Physics to Function." No doubt, we can learn in this respect by copying
nature. Of course, proteins are not entirely ideal materials when it comes to building a computer within
the limits of a preconceived technology. However, nature does have an inexpensive way of pattern
formation and replication — a self-organizing way. This again may be something to copy. If we cannot
produce chip patterns down to nanometer size by inexpensive photographic means, why not produce
them by methods of self-organization? Can one make ion channels out of materials other than proteins
that compare more closely to the solid-state materials of chip technology? Perhaps carbon nanotubes can
be used. Material science has certainly shown great inventiveness in the past decades.
Nature also has no problems in using all three dimensions of space for applying its nanostructures.
Self-organization is not limited to a plane as photography is. Feynman's ultimate frontier of using three
dimensions for information storage is automatically included in some biological systems such as, for
example, neural networks. The large capacity and intricate capability of the human brain derives, of
course, from this fact.
The multitude of nanostructure functionalities in nature is made possible because nature is not limited
by disciplinary boundaries. It uses everything, whether physics or chemistry, mechanics or electronics
— and yes, nature also uses optics, e.g., to harvest energy from the sun. I have not covered nanometersize mechanical functionality because I have no research record in this area. However, great advances are
currently made in the area of nanoelectromechanical systems (NEMS). It is no problem any more to
pick up and drop atoms, or even to rotate molecules. Feynman's challenge has been far surpassed in the
mechanical area, and even his wildest dreams have long since become reality. Medical applications, such
as the insertion of small machinery to repair arteries, are commonplace. As we understand nature better,
we will not only be able to find new medical applications but may even improve nature by use of special
smart materials for our bodies. Optics, electronics, and mechanics, physics, chemistry, and biology need
to merge to form generations of nanostructure technologies for a multitude of applications.
However, an area exists in which man-made chips excel and are superior to natural systems (if manmade is not counted as natural). This area relates to processing speed. The mere speed of a numbercrunching machine is unthinkable for the workings of a biological neural network. To be sure, nature
has developed fast processing; visual evaluations of dangerous situations and recognition of vital patterns
are performed with lightening speed by some parallel processing of biological neural networks. However,
when it comes to the raw speed of converting numbers, which can also be used for alphabetical ordering
and for a multitude of algorithms, man-made chips are unequaled. Algorithmic speed and variability is
a very desirable property, as we know from browsing the Internet, and represents a great achievement
in chip technology.
Can we have both —the algorithmic speed and variability of semiconductor-based processors and, at
the same time, three-dimensional implementations and the multitude of functionality as nature features
it in her nanostructure designs? I would not dare to guess an answer to this question. The difficulties are
staggering! Processing speed seems invariably connected to heat generation. Cooling becomes increasingly
difficult when three-dimensional systems are involved and the heat generation intensifies.
But then, there are always new ideas, new materials, new devices, new architectures, and altogether
new horizo