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R. Douglas Moffat

Historically, public equity markets have provided capital for rapidly expanding firms having established products and seeking growth capital. Periodically, new technology or corporate growth models, combined with unusually heavy money flows into the stock market, fuel speculative demand for shares in new companies. Biotechnology investing has run in such cycles for more than 20 years. The Internet boom of the late 1990s reached unprecedented levels of irrational expectations and speculation. Other examples include the fuel cell boom of 20002001.

The public market’s appetite for initial public offerings (IPOs) in a sector also is heavily influenced by the business model characteristics and the track record of the model for success. Biotech has achieved success in part because of the appetite for these firms by big pharmaceutical firms. Software stocks have proven to be fast growers without heavy capital investment.

Nanotech probably will be a big hit on Wall Street, but the timing will depend on progress achieved in moving products closer to market acceptance. Many of the nanoscience-enabled products being commercialized now are coming out of large companies. Examples include nanotube-based plasma televisions and personal care products. A limited number of smaller firms are introducing nanotech products in the short term. Most companies, however, are still refining the science behind paradigm-shifting technologies having massive potential. Commercialization issues include interfacing nanodevices with the macro environment, scalable manufacturing, and, in the health-care world, long FDA approval cycles.

Wall Street investors typically have preferred focused business models concentrated on growth from a narrowly defined technology or product group. Management focus historically has produced better execution and shareholder returns.

At this stage of nanotechnology development, however, intellectual property platforms based on broad patents (often coming from academia) are the main assets behind many companies. The applicability of this IP could cut across many markets and applications. Some firms have amassed broad IP by taking a portfolio approach to early-stage commercialization, an approach most stock investors do not favor. Such diversification, however, makes sense not only from a scientific point of view but also to lessen risks associated with potential patent litigation. The patent landscape in nanotech might be likened to the gold rush days, with overlapping claims.

Nanotechnology is different from other tech waves. First, the technology is often paradigm shifting, either creating new markets or providing quantum improvement in performance at a low cost. The enabling science probably is applicable to a wide variety of applications. In time, stock market investors may come to appreciate the power of a new nanotech business model, one with core IP at its center and with the prospects to spin off many companies with varied new products. The evolution of acceptable nanotech business models in public markets will depend in part on VC investors’ willingness to extend funding horizons to allow firms to develop products.

There is significant buzz on Wall Street around nanotechnology. Leading Wall Street firms are beginning to commit resources to research and fund nanotechnology. A favorable environment is emerging for a successful nanotech début on the street.

Since the Internet bubble deflation in 2000, public equity markets have taken on a more risk-averse character. IPO investors have preferred to fund companies with established products, revenues, and profits as well as large companies restructured by private equity firms. A limited number of nanotechnology-enabled firms have been able to tap public equity markets. Public equity access likely will improve as nanotechnology firms move closer to the introduction of novel products having a clear path to revenue and profits. Equity issuance by nanotech firms likely will grow slowly over the next five years, gathering potentially explosive momentum thereafter.

Nanotechnology start-up companies should not expect to defy fundamental business principles, as did the Internet companies of the mid- to late 1990s, if only for a brief period. Nanotechnology companies should expect to be measured by standard metrics and to confront the same industry dynamics and fundamental business issues (for example, personnel choices, sales strategy, high-volume manufacturing, efficient allocation of capital, marketing, execution of their business model, time-to-market challenges, and so on) that face the other companies in their relevant industry category.

Certain key characteristics often differentiate nanotechnology start-up companies. They possess a technology platform with a body of intellectual property and a team of scientists, but no formal business plan, product strategy, well-defined market opportunity, or management team. Second, they are founded by (or are associated with) leading researchers at top-tier academic institutions. They employ a financing approach that highly leverages equity financing with the application of grant funding, and they need to have a more scientifically diverse workforce than other start-up companies.

It is common for these companies to employ chemists, physicists, engineers, biologists, computer scientists, and materials scientists because of the interdisciplinary nature of nanotechnology and the unique skills and knowledge that are required for product commercialization. Moreover, nanotech companies tend to sign up development partners (usually larger, more established companies) early in their maturation to provide technology validation and additional resources in the form of development funds, access to technology, sales and distribution channels, and manufacturing expertise.

Nanotechnology start-up companies can best be classified into six primary categories: nanomaterials and nanomaterials processing; nanobiotechnology; nanosoftware; nanophotonics; nanoelectronics, and nanoinstrumentation. Many companies in the nanomaterials category are developing methods and processes to manufacture a range of nanomaterials in large quantities as well as developing techniques to functionalize, solubilize, and integrate these materials into unique formulations. A variety of nanomaterials will ultimately be integrated into a host of end products (several are on the market) that will provide unique properties, such as scratch resistance, increased stiffness and strength, reduced friction and wear, greater electrical and thermal conductivity, and so on.

The three areas that have received the most funding based on dollars invested are nanoelectronics, nanophotonics, and nanoinstrumentation. However, in terms of the absolute number of companies that have been funded, nanomaterials companies are the clear leader.

Nanobiotechnology is the application of nanotechnology to biological systems. Applications exist in all of the traditional areas of biotechnology, such as therapeutics discovery and production, drug-delivery systems technologies, diagnostics, and so on. Incorporating nanotechnology into biotechnology will lead to the enhanced ability to label, detect, and study biological systems (such as genes, proteins, DNA fragments, single molecules, and so on) with great precision as well as to develop unique drug targets and therapies.

Nanoelectronics is based upon individual or ordered assemblies of nanometer-scale device components. These building blocks could lead to devices with significant cost advantages and performance attributes, such as extremely low power operation (~nanoWatt), ultra-high device densities (~1 trillion elements/cm²), and blazing speed (~1 Terahertz switching rates). In addition, the possibility exists of enabling a new class of devices with unique functionality. Examples include, but are not limited to, multi-state logic elements; high-quantum-efficiency, low-power, tunable, multicolor light-emitting diodes (LEDs); low-power, high-density nonvolatile random access memory (RAM); quantum dot-based lasers; universal analyte sensors; low-impedance, high-speed interconnects, and so on.

Nanophotonics companies are developing highly integrated, subwavelength optical communications components using a combination of proprietary nanomaterials and nanotech manufacturing technologies, along with standard complementary metal oxide semiconductor (CMOS) processing. This provides for the low-cost integration of electronic and photonic components on a single chip. Products in this category include low-cost, high-performance devices for high-speed optical communications, such as wavelength converters, tunable filters, polarization combiners, reconfigurable optical add/drop multiplexers (ROADMs), optical transceivers, and so on.

Nanoinstrumentation is based on tools that manipulate, image, chemically profile, and write matter on a nanometer-length scale (far less than 100nm). These tools include the well-known microscopy techniques such as transmission electron microscopy (TEM), scanning electron microscopy (SEM), and atomic force microscopy (AFM), as well as newer techniques such as dip-pen nanolithography (DPN), nanoimprint lithography (NIL), and atom probe microscopes for elucidating three-dimensional atomic composition and structure of solid materials and thin films. These are the basic tools that enable scientists and engineers to perform nanoscale science and to develop nanotechnology products.

Nanosoftware is based on modeling and simulation tools for research in advanced materials (cheminformatics) and the design, development, and testing of drugs in the biotechnology industry (bioinformatics). This category also includes electronic and photonic architecture, structure, and device modeling tools such as specific incarnations of electronic design automation (EDA) software or quantum simulations, and so on. In addition, one might further include proprietary software packages developed to operate nanoinstrumentation-based tools or interpret data collected from such instruments.

Nanotechnology is not a single market but rather a set of enabling (and potentially groundbreaking) technologies that can be applied to solve high-value problems in almost every industry. This includes industries as disparate as telecommunications, biotechnology, microelectronics, textiles, and energy. Many investors refer to nanotechnology investing as if it were its own investment category, because nanotechnology can add unique and specific value to a product that results in greatly enhanced performance attributes or cost advantages (or both). But customers purchasing nanotechnology products are buying these products, not because they are based on nanotechnology, but because they are characterized by specific performance enhancements, reduced costs, or both.

Almost every product application of nanotechnology is based either on a material characterized by nanoscale dimensions or on a process technology conducted at the nanometer scale. Nanomaterials possess unique propertiesincluding optical, electronic, magnetic, physical, and chemical reactivity propertiesthat, when harnessed appropriately, can lead to entirely new, high-performance technologies and products. Changing a material’s size, rather than its chemical composition, enables the control of that material’s fundamental properties.

Daniel V. Leff

Venture capital is money that is typically invested in young, unproven companies with the potential to develop into multibillion-dollar industry leaders, and it has been an increasingly important source of funds for high-technology start-up companies in the last several years. Venture capitalists are the agents that provide these financial resources as well as business guidance in exchange for ownership in a new business venture. VCs typically hope to garner returns in excess of 3050 percent per year on their investments. They expect to do so over a four- to seven-year time horizon, which is the period of time, on average, that it takes a start-up company to reach a liquidity event (a merger, acquisition, or initial public offering).

Very few high-tech start-up companies are attractive candidates for VC investment. This is especially true for nanotechnology start-ups, because the commercialization of nanoscience is still in its nascent stages. Companies that are appropriate for VC investment generally have some combination of the following five characteristics: (1) an innovative (or disruptive) product idea based on defensible intellectual property that gives the company a sustainable competitive advantage; (2) a large and growing market opportunity that is greater than $1 billion and is growing at more than 2030 percent per year; (3) reasonable time to market (one to three years) for the first product to be introduced; (4) a strong management team of seasoned executives; and (5) early customers and relationships with strategic partners, with a strong likelihood of significant revenue.

An early-stage start-up company rarely possesses all of these characteristics and often does not need to in order to attract venture financing. Indeed, early-stage start-ups are often funded without complete management teams, strategic partners, or customers. Absent these characteristics, however, there should be, at a minimum, a passionate, visionary entrepreneur who helped develop the core technology and wants to play an integral role in building the company.

The Commercialization of Nanotechnology

Nanotech is often defined as the manipulation and control of matter at the nanometer scale (critical dimensions of 1 to 100nm). It is a bit unusual to describe a technology by a length scale. We certainly didn’t get very excited by “inch-o technology.” As venture capitalists, we start to get interested when there are unique properties of matter that emerge at the nanoscale and that cannot be exploited at the macroscale world of today’s engineered products. We like to ask the start-ups that we are investing in, “Why now? Why couldn’t you have started this business ten years ago?” The responses of our nanotech start-ups have a common thread: Recent developments in the capacity to understand and engineer nanoscale materials have enabled new products that could not have been developed at larger scale.

Various unique properties of matter are expressed at the nanoscale and are quite foreign to our “bulk statistical” senses (we do not see single photons or quanta of electric charge; we feel bulk phenomena, like friction, at the statistical or emergent macroscale). At the nanoscale, the bulk approximations of Newtonian physics are revealed for their inaccuracy and give way to quantum physics. Nanotechnology is more than a linear improvement with scale; everything changes. Quantum entanglement, tunneling, ballistic transport, frictionless rotation of superfluids, and several other phenomena have been regarded as “spooky” by many of the smartest scientists, even Einstein, upon first exposure.

For a simple example of nanotech’s discontinuous divergence from the “bulk” sciences, consider the simple aluminum soda can. If you take the inert aluminum metal in that can and grind it down into a powder of 2030nm particles, it will spontaneously explode in air. It becomes a rocket fuel catalyst. In other words, the energetic properties of matter change at that scale. The surface-area-to-volume ratios become relevant, and even the distances between the atoms in a metal lattice change from surface effects.

Innovation from the Edge

Disruptive innovation, the driver of growth and renewal, occurs at the edge. In start-ups, innovation occurs out of the mainstream, away from the warmth of the herd. In biological evolution, innovative mutations take hold at the physical edge of the population, at the edge of survival. In complexity theory, structure and complexity emerge at the edge of chaosthe dividing line between predictable regularity and chaotic indeterminacy. And in science, meaningful disruptive innovation occurs at the interdisciplinary interstices between formal academic disciplines.

Herein lies much of the excitement about nanotechnology: in the richness of human communication about science. Nanotech exposes the core areas of overlap in the fundamental sciences, the place where quantum physics and quantum chemistry can cross-pollinate with ideas from the life sciences.

In academic centers and government laboratories, nanotech is fostering new discussions. At Stanford, UCLA, Duke, and many other schools, the new nanotech buildings are physically located at the symbolic hub of the schools of engineering, computer science, and medicine.

Nanotech is the nexus of the sciences, but outside the sciences and research itself, the nanotech umbrella conveys no business synergy whatsoever. The marketing, distribution, and sales of a nanotech solar cell, memory chip, or drug delivery capsule will be completely different from each other and will present few opportunities for common learning or synergy.

Market Timing

As an umbrella term for a myriad of technologies spanning multiple industries, nanotech will eventually disrupt these industries over different time framesbut most are long-term opportunities. Electronics, energy, drug delivery, and materials are areas of active nanotech research today. Medicine and bulk manufacturing are future opportunities. The National Science Foundation predicts that nanotech will have a trillion-dollar impact on various industries within 15 years.

Of course, if one thinks far enough in the future, every industry eventually will be revolutionized by a fundamental capability for molecular manufacturingfrom the inorganic structures to the organic and even the biological. Analog manufacturing will become digital, engendering a profound restructuring of the substrate of the physical world.

Futuristic predictions of potential nanotech products have a near-term benefit. They help attract some of the best and brightest scientists to work on hard problems that are stepping-stones to the future vision. Scientists relish exploring the frontier of the unknown, and nanotech embodies the tangible metaphor of the inner frontier.

Given that much of the abstract potential of nanotech is a question of “when” and not “if,” the challenge for the venture capitalist is one of market timing. When should we be investing, and in which subsectors? It is as if we need to pull the sea of possibilities through an intellectual filter to tease apart the various segments into a time line of probable progression. That is an ongoing process of data collection (for example, the growing pool of business plan submissions), business and technology analysis, and intuition.

Two touchstone events for the scientific enthusiasm for the timing of nanotech were the decoding of the human genome and the dazzling visual images output by the scanning tunneling microscope (such as the arrangement of individual xenon atoms into the IBM logo). These events represent the digitization of biology and mattersymbolic milestones for accelerated learning and simulation-driven innovation.

More recently, nanotech publication has proliferated, as in the early days of the Internet. In addition to the popular press, the number of scientific publications on nanotech has grown by a factor of 10 in the past ten years. According to the U.S. Patent and Trademark Office (USPTO), the number of nanotech patents granted each year has skyrocketed by a factor of 3 in the past seven years. Ripe with symbolism, IBM has more lawyers working on nanotech than engineers.

With the recent codification of the National Nanotech Initiative into law, federal funding will continue to fill the pipeline of nanotech research. With $847 million earmarked for 2004, nanotech was a rarity in the tight budget process; it received more funding than was requested. Now nanotech is second only to the space race for federal funding of science. And the United States is not alone in funding nanotechnology. Unlike many previous technological areas, we aren’t even in the lead; Japan outspends the United States each year on nanotech research. In 2003, the U.S. government spending was one-fourth of the world total.

Federal funding is the seed corn for nanotech entrepreneurship. All of our nanotech portfolio companies are spin-offs (with negotiated intellectual property [IP] transfers) from universities or government labs, and all got their start with federal funding. Often these companies need specialized equipment and expensive laboratories to do the early tinkering that will germinate a new breakthrough. These are typically lacking in the proverbial entrepreneur’s garage.

Corporate investors have discovered a keen interest in nanotechnology, with internal R&D, external investments in start-ups, and acquisitions of promising companies, such as chipmaker AMD’s recent acquisition of Coatue, a molecular electronics company.

Despite all this excitement, there are a fair number of investment dead ends, and so we continue to refine the filters we use in selecting companies to back. All entrepreneurs want to present their businesses as fitting an appropriate time line to commercialization. How can we guide our intuition to determine which of these entrepreneurs are right?

The Question of Vertical Integration

Nanotech involves the reengineering of the lowest-level physical layer of a system, and so a natural business question arises: How far forward do you need to vertically integrate before you can sell a product on the open market? For example, in molecular electronics, if you can ship a DRAM-compatible chip, you have found a horizontal layer of standardization, and further vertical integration is not necessary. If you have an incompatible 3-D memory block, you may have to vertically integrate to the storage subsystem level, or farther, to bring a product to market. That may require that you form industry partnerships, and it will, in general, take more time and money as change is introduced farther up the product stack. Three-dimensional logic with massive interconnectivity may require a new computer design and a new form of software; this would take the longest to commercialize. And most start-ups on this end of the spectrum would seek partnerships to bring their vision to market. The success and timeliness of that endeavor will depend on many factors, including IP protection, the magnitude of improvement, the vertical tier at which that value is recognized, the number of potential partners, and the needed degree of tooling and other industry accommodations.

Product development time lines are impacted by the cycle time of the R&D feedback loop. For example, outdoor lifetime testing for organic light-emitting diodes (LEDs) will take longer than in silicon simulation spins of digital products. If the product requires partners in the R&D loop or multiple nested tiers of testing, it will take longer to commercialize.

The Interface Problem

As we think about the start-up opportunities in nanotechnology, an uncertain financial environment underscores the importance of market timing and revenue opportunities over the next five years. Of the various paths to nanotech, which of them are 20-year quests in search of a government grant, and which are market-driven businesses that will attract venture capital? Are there co-factors of production that require a whole industry to be in place before a company ships products?

As a thought experiment, imagine that I could hand you today any nanotech marvel of your designa molecular machine as advanced as you would like. What would it be? A supercomputer? A bloodstream submarine? A matter compiler capable of producing diamond rods or arbitrary physical objects? Pick something.

Now imagine some of the complexities: Did it blow off my hand as I offered it to you? Can it autonomously move to its intended destination? What is its energy source? How do you communicate with it?

These questions draw the interface problem into sharp focus: Does your design require an entire nanotech industry to support, power, and interface to your molecular machine? As an analogy, imagine that you have one of the latest Intel Pentium processors. How would you make use of the Pentium chip? You then need to wire-bond the chip to a larger lead frame in a package that connects to a larger printed circuit board, fed by a bulky power supply that connects to the electrical power grid. Each of these successive layers relies on its larger-scale precursors (which were developed in reverse chronological order), and the entire hierarchy is needed to access the potential of the microchip.

Where Is the Scaling Hierarchy for Molecular Nanotech?

To cross the interface chasm, today’s business-driven paths to nanotech diverge into two strategies: the biologically inspired bottom-up path, and the top-down approach of the semiconductor industry. The developers of nonbiological micro-electromechanical systems (MEMS) are addressing current markets in the micro world while pursuing an ever-shrinking spiral of miniaturization that builds the relevant infrastructure tiers along the way. Not surprisingly, this path is very similar to the one that has been followed in the semiconductor industry, and many of its adherents see nanotech as inevitable but in the distant future.

On the other hand, biological manipulation presents numerous opportunities to effect great change in the near term. Drug development, tissue engineering, and genetic engineering are all powerfully impacted by the molecular manipulation capabilities available to us today. And genetically modified microbes, whether by artificial evolution or directed gene splicing, give researchers the ability to build structures from the bottom up.

The Top-Down “Chip Path”

This path is consonant with the original vision of physicist Richard Feynman (in a 1959 lecture at Caltech) of the iterative miniaturization of our tools down to the nanoscale. Some companies are pursuing the gradual shrinking of semiconductor manufacturing technology from the MEMS of today into the nanometer domain of nanoelectromechanical systems (NEMS).

MEMS technologies have already revolutionized the automotive industry with air-bag sensors, and the printing sector with ink-jet nozzles, and they are on track to do the same in medical devices and photonic switches for communications and mobile phones. In-StatJMDR forecasts that the $4.7 billion in MEMS revenue in 2003 will grow to $8.3 billion by 2007. But progress is constrained by the pace (and cost) of the semiconductor equipment industry, and by the long turnaround time for fab runs.

Many of the nanotech advances in storage, semiconductors, and molecular electronics can be improved, or in some cases enabled, by tools that allow for the manipulation of matter at the nanoscale. Here are three examples:

• Nanolithography: Molecular Imprints is commercializing a unique imprint lithographic technology developed at the University of Texas at Austin. The technology uses photo-curable liquids and etched quartz plates to dramatically reduce the cost of nanoscale lithography. This lithography approach, recently added to the ITRS Roadmap, has special advantages for applications in the areas of nanodevices, MEMS, microfluidics, and optical components and devices, as well as molecular electronics.

• Optical traps: Arryx has developed a breakthrough in nanomaterial manipulation. Optical traps generate hundreds of independently controllable laser tweezers that can manipulate molecular objects in 3-D (move, rotate, cut, place), all from one laser source passing through an adaptive hologram. The applications span from cell sorting, to carbon nanotube placement, to continuous material handling. They can even manipulate the organelles inside an unruptured living cell (and weigh the DNA in the nucleus).

• Metrology: Imago’s LEAP atom probe microscope is being used by the chip and disk drive industries to produce 3-D pictures that depict both the chemistry and the structure of items on an atom-by-atom basis. Unlike traditional microscopes, which zoom in to see an item on a microscopic level, Imago’s nanoscope analyzes structures, one atom at a time, and “zooms out” as it digitally reconstructs the item of interest at a rate of millions of atoms per minute. This creates an unprecedented level of visibility and information at the atomic level.

Advances in nanoscale tools help us control and analyze matter more precisely, which in turn allows us to produce better tools. To summarize, the top-down path is designed and engineered with the following:

• Semiconductor industry adjacencies (with the benefits of market extensions and revenue along the way and the limitation of planar manufacturing techniques)

• Interfaces of scale inherited from the top

The Biological, Bottom-Up Path

In contrast to the top-down path, the biological bottom-up archetype is

• Grown via replication, evolution, and self-assembly in a 3-D, fluid medium

• Constrained at interfaces to the inorganic world

• Limited by gaps in learning and theory (in systems biology, complexity theory, and the pruning rules of emergence)

• Bootstrapped by a powerful preexisting hierarchy of interpreters of digital molecular code

To elaborate on this last point, a ribosome takes digital instructions in the form of mRNA and manufactures almost everything we care about in our bodies from a sequential concatenation of amino acids into proteins. The ribosome is a wonderful existence proof of the power and robustness of a molecular machine. It is roughly 20nm on a side and consists of only 99,000 atoms. Biological systems are replicating machines that parse molecular code (DNA) and a variety of feedback to grow macroscale beings. These highly evolved systems can be hijacked and reprogrammed to great effect.

So how does this help with the development of molecular electronics or nanotech manufacturing? The biological bootstrap provides a more immediate path to nanotech futures. Biology provides us with a library of prebuilt components and subsystems that can be repurposed and reused, and research in various labs is well under way in reengineering the information systems of biology.

For example, researchers at NASA’s Ames Research Center are taking self-assembling heat shock proteins from thermophiles and genetically modifying them so that they will deposit a regular array of electrodes with a 17nm spacing. This could be useful for making patterned magnetic media in the disk drive industry or electrodes in a polymer solar cell.

At MIT, researchers are using accelerated artificial evolution to rapidly breed an Ml3 bacteriophage to infect bacteria in such a way that they bind and organize semiconducting materials with molecular precision.

At the Institute for Biological Energy Alternatives (IBEA), Craig Venter and Hamilton Smith are leading the Minimal Genome Project. They take Mycoplasma genitalium from the human urogenital tract and strip out 200 unnecessary genes, thereby creating the simplest organism that can self-replicate. Then they plan to layer new functionality onto this artificial genome, such as the ability to generate hydrogen from water using the sun’s energy for photonic hydrolysis.

The limiting factor is our understanding of these complex systems, but our pace of learning has been compounding exponentially. We will learn more about genetics and the origins of disease in the next ten years than we have in all of human history. And for the minimal genome microbes, the possibility of understanding the entire proteome and metabolic pathways seems tantalizingly close to achievable. These simpler organisms have a simple “one gene, one protein” mapping and lack the nested loops of feedback that make the human genetic code so rich.

An Example: Hybrid Molecular Electronics

In the near term, a variety of companies are leveraging the power of organic self-assembly (bottom-up) and the market interface advantages of top-down design. The top-down substrate constrains the domain of self-assembly.

Based in Denver, ZettaCore builds molecular memories from energetically elegant molecules that are similar to chlorophyll. ZettaCore’s synthetic organic porphyrin molecule self-assembles on exposed silicon. These molecules, called multiporphyrin nanostructures, can be oxidized and reduced (their electrons removed or replaced) in a way that is stable, reproducible, and reversible. In this way, the molecules can be used as a reliable storage medium for electronic devices.

Furthermore, the molecules can be engineered to store multiple bits of information and to maintain that information for relatively long periods before needing to be refreshed. Recall the water-drop-to-transistor-count comparison, and add to that the fact that these multiporphyrins have already demonstrated as many as eight stable digital states per molecule.

The technology has future potential to scale to 3-D circuits with minimal power dissipation, but initially it will enhance the weakest element of an otherwise standard 2-D memory chip. To end customers, the ZettaCore memory chip looks like a standard memory chip; nobody needs to know that it has “nano inside.” The input/output pads, sense amps, row decoders, and wiring interconnect are produced via a standard semiconductor process. As a final manufacturing step, the molecules are splashed on the wafer, where they self-assemble in the predefined regions of exposed metal.

From a business perspective, this hybrid product design allows an immediate market entry because the memory chip defines a standard product feature set, and the molecular electronics manufacturing process need not change any of the prior manufacturing steps. Any interdependencies with the standard silicon manufacturing steps are also avoided, thanks to this late coupling; the fab can process wafers as it does now before spin-coating the molecules. In contrast, new materials for gate oxides or metal interconnects can have a number of effects on other processing steps, and these effects need to be tested. That introduces delay (as with copper interconnects).

Generalizing from the ZettaCore experience, the early revenue in molecular electronics will likely come from simple 1-D structures such as chemical sensors and self-assembled 2-D arrays on standard substrates, such as memory chips, sensor arrays, displays, CCDs for cameras, and solar cells.

IP and Business Model

Beyond product development time lines, the path to commercialization is dramatically impacted by the cost and scale of the manufacturing ramp. Partnerships with industry incumbents can be an accelerant or an albatross for market entry.

The strength of the IP protection for nanotech relates to the business models that can be safely pursued. For example, if the composition of matter patents afford the nanotech start-up the same degree of protection as for a biotech start-up, then a “biotech licensing model” may be possible in nanotech. A molecular electronics company could partner with a large semiconductor company for manufacturing, sales, and marketing, just as a biotech company partners with a big pharmaceutical partner for clinical trials, marketing, sales, and distribution. In both cases, the cost to the big partner is on the order of $100 million, and the start-up earns a royalty on future product sales.

Notice how the transaction costs and viability of this business model option pivot on the strength of IP protection. A software business, on the other end of the IP spectrum, would be very cautious about sharing its source code with Microsoft in the hopes of forming a partnership based on royalties.

Manufacturing partnerships are common in the semiconductor industry, with the “fabless” business model. This layering of the value chain separates the formerly integrated functions of product conceptualization, design, manufacturing, testing, and packaging. This has happened in the semiconductor industry because the capital cost of manufacturing is so large. The fabless model is a useful way for a small company with a good idea to bring its own product to market, but the company then must face the issue of gaining access to its market and funding the development of marketing, distribution, and sales.

Having looked at the molecular electronics example in some depth, we can now move up the abstraction ladder to aggregates, complex systems, and the potential to advance the capabilities of Moore’s Law in software.

Molecular Electronics

The primary contender for the post-silicon computation paradigm is molecular electronics, a nanoscale alternative to the CMOS transistor. Eventually, molecular switches will revolutionize computation by scaling into the third dimensionovercoming the planar deposition limitations of CMOS. Initially, these switches will substitute for the transistor bottleneck that results from a standard silicon process using standard external input/output interfaces.

For example, Nantero, a nanotech firm based in Woburn, Massachusetts, employs carbon nanotubes suspended above metal electrodes on silicon to create high-density nonvolatile memory chips (the weak Van der Waals bond can hold a deflected tube in place indefinitely with no power drain). Carbon nanotubes are small (approximately 10 atoms wide), 30 times as strong as steel at one-sixth the weight, and they perform the functions of wires, capacitors, and transistors with better speed, power, density, and cost. Cheap nonvolatile memory enables important advances, such as “instant-on” PCs.

Other companies, such as Hewlett-Packard and ZettaCore, are combining organic chemistry with a silicon substrate to create memory elements that self-assemble using chemical bonds that form along prepatterned regions of exposed silicon.

There are several reasons molecular electronics is the next paradigm for Moore’s Law:

• Size: Molecular electronics has the potential to dramatically extend the miniaturization that has driven the density and speed advantages of the integrated circuit (IC) phase of Moore’s Law. In 2002, using a scanning tunneling microscope (STM) to manipulate individual carbon monoxide molecules, IBM built a three-input sorter by arranging those molecules precisely on a copper surface. It is 260,000 times as small as the equivalent circuit built in the most modern chip plant. For a memorable sense of the difference in scale, consider a single drop of water. There are more molecules in a single drop of water than in all the transistors ever built. Think of the transistors in every memory chip and every processor ever built; there are about 100 times as many molecules in a drop of water. Certainly, water molecules are small, but an important part of the comparison depends on the 3-D volume of a drop. Every IC, in contrast, is a thin veneer of computation on a thick and inert substrate.

• Power: One of the reasons that transistors are not stacked into 3-D volumes today is that the silicon would melt. The inefficiency of the modern transistor is staggering. It is much less efficient at its task than the internal combustion engine. The brain provides an existing proof of what is possible; it is 100 million times as efficient in power and calculation as our best processors. Sure, it is slow (less than 1 kHz), but it is massively interconnected (with 100 trillion synapses between 60 billion neurons), and it is folded into a 3-D volume. Power per calculation will dominate clock speed as the metric of merit for the future of computation.

• Manufacturing cost: Many of the molecular electronics designs use simple spin coating or molecular self-assembly of organic compounds. The process complexity is embodied in the synthesized molecular structures, and so they can literally be splashed on to a prepared silicon wafer. The complexity is not in the deposition nor the manufacturing process nor the systems engineering. Much of the conceptual difference of nanotech products derives from a biological metaphor: Complexity builds from the bottom up and pivots about conformational changes, weak bonds, and surfaces. It is not engineered from the top down with precise manipulation and static placement.

• Low-temperature manufacturing: Biology does not tend to assemble complexity at 1,000 degrees in a high vacuum. It tends to work at room temperature or body temperature. In a manufacturing domain, this opens the possibility of using cheap plastic substrates instead of expensive silicon ingots.

• Elegance: In addition to these advantages, some of the molecular electronics approaches offer elegant solutions to nonvolatile and inherently digital storage. We go through unnatural acts with CMOS silicon to get an inherently analog and leaky medium to approximate a digital and nonvolatile abstraction that we depend on for our design methodology. Many of the molecular electronic approaches are inherently digital, and some are inherently nonvolatile.

Other research projects, from quantum computing to using DNA as a structural material for directed assembly of carbon nanotubes, have one thing in common: They are all nanotechnology.

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