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193 9 Molecular-scale Electronics “Computers in the future may weigh no more than 1.5 tons.” – Popular Mechanics, 1949 9.1 Miniaturization At least since the Club of Rome published The Limits of Growth’ in 1973 [1], we have been aware that many products of our civilization grow exponentially. It is less well known that some decrease exponentially. An example of the latter is electronic devices. In Figure 9-1 the minimum feature size of electronic components is plotted versus the year of use. A straight line results, provided the size is plotted on logarithmic scale. Such diagrams are known as Moore plots [2]. Originally they were used to demonstrate the continuous decrease of the price per bit in integrated memories. Figure 9-1 Development of the structural size of electronic devices in the course of time and extrapolation to sizes as small as typical interatomic distances in solids by the year 2020. One-Dimensional Metals, Second Edition. Siegmar Roth, David Carroll Copyright © 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 3-527-30749-4 194 9 Molecular-scale Electronics Because the price of a silicon chip remains more-or-less constant (some p Dollars’), and because the number of bits per chip increases continuously (from 124 kbits in the seventies to 16 Mbits in the mid 19902), a bit becomes cheaper and cheaper. Extrapolating the Moore plot in the reverse direction, vacuum tubes and probably also the Chinese abacus might be included. If extended to the future the plot would lead to a feature size of 10 in the year 2020. This increasing density of electronics through miniaturization has become a relatively large part of the economies of western nations. For example, increasing computational power creates machines for applications that were previously not approached with computers. The molecular dimensions of such ultrasmall circuitry certainly justify the name molecular electronics’. From a contemporary point of view, however, the term molecular electronics is not very well defined. It is used in connection with both electronics on a molecular level, which we discuss in this chapter, and molecular materials for electronics, which we discuss in Chapter 10 [3]. In the context of the first meaning, molecular electronics first found expression when, in the 1970s, chemists Mark Ratner and Ari Aviram speculated about using single molecules as rectifiers, allowing electrical currents to pass only in one direction (discussed in more detail below). Throughout the 1970s and 1980s, the fundamental concepts of this field Figure 9-2 Three-terminal devices make gain possible. 9.1 Miniaturization were laid down in a variety of topical conferences. Some of the proceedings of these workshops on molecular electronics are listed in the Refs. [4–10]. It was not until the 1990s, however, when a key development came, and Tour and coworkers measured the current flowing between two gold electrodes connected by a single molecule [11]. The basic premise of these early approaches is quite easy to visualize. As shown in Figure 9-2, the conceptualization is of a single molecule between interconnecting leads that performs a signal-processing electrical function, such as rectification, resistance, etc. One can already see that many of the issues of dimensionality discussed previously should apply to such situations. In this conformation, the electrodes are linked to the atoms of the molecule through a chemical bond. In the example cited above, a benzene molecule was linked to Au electrodes via sulfur atoms at each end. The sulfur atoms, which happen to form strong bonds with gold, held the molecule in place between the two gold wires separated by a distance of several nanometers. By using such configurations and doping the molecule in the leads, effects such as molecular conduction, coulomb blockade, and negative-differential resistance’ (when the current decreases as the voltage increases) have been observed. Although these phenomena have provided interesting tests of molecular orbital theory, they fall short of the essential element necessary for information processing electronics: gain. The basis of computer circuits is the transistor. The transistor is essentially nothing more than a variable-state switch. Very simply, it works like this: two contacts are placed on a thin, doped, semiconducting film (like Si), so that charge injection can be accomplished easily. A back electrode is placed on the back of the semiconductor layer. When a voltage is applied to the gate, a space charge or depletion’ region builds up in the active layer. This impedes charge flow through the source and drain electrodes. When the bias reaches some specified large value, the current flow between source and drain is turned off altogether. This is actually a field-effect transistor, of which several types exist. However, they all have a singular property: if the configuration is balanced just right, it is clear that small fluctuations in the gate can result in rather large changes in the source–drain current. Importantly, we could take the point of view of supplying an input current at the gate (Ig) and measuring its output at the drain (Id). If we did this, it would appear as though small inputs of Ig lead to large outputs of Id. In fact, the gain of such a system is generally defined in terms of this concept: b = Id/Ig. It is not a real gain of course; the currents must all sum throughout the circuit. However, the nonlinearity in the circuit response is quite powerful and can be useful in signal amplification, information processing, and memory applications. Essentially, it relies on a three-terminal flow-control’ system. In contrast, early experiments on molecules used two-terminal devices without the capability of exhibiting gain. Trying to achieve gain within a single-molecule device is a significant stumbling block to the overall usefulness of such concepts. In 2000, however, Di Ventra and colleagues showed, through rather complex calculations, that this hurdle is surmountable under some conditions. The predicted the behavior of a three-terminal device, based on the 1997 benzene device, can exhibit gain by resonant tunneling [12]. Quite different from the macroscopic charge-flow device described above, the resonant-tunneling device must express ele- 195 196 9 Molecular-scale Electronics ments of quantum mechanical confinement (i.e., be zero- or one-dimensional) to work. Alternatively, we have already seen several much more simple materials in which quantum phenomena are expressed; specifically, quantum dots and quantum wires. Such inorganic systems could also generate gain by similar principles to those described above. We mentioned in Section 1.2 that, in these systems with a small electron concentration (silicon, gallium arsenide), effects of low dimensionality (socalled quantum-size effects) are seen at much larger sizes than in systems with high electron concentration (carbonic systems). In fact, the preparation of inorganic quantum wires and quantum dots is state-of-the-art today, and these systems are subjects of intensive research and development [13]. Quantum dots can be made so small that they contain only a few or even single’ electrons. The possibility of single-electron electronics has been pointed out [14,15], and single-electron transistors [16,17] and single-electron memories [18–20] have been demonstrated. Thus, this can be seen as a second approach to molecular-scale electronics and, incidentally, an approach more easily accomplished by using the lithography tools of topdown assembly. In both approaches, the operational parameters must be taken into account. For single-electron devices, the level spacing of electrons-in-a-box (Section 1.2, Eq. (1)), and also the coulombic energy of the occupants of that box, or coulombic blockade, determine the energy to place another electron into the system. For large’ particles the coulombic blockade can be calculated from the charging energy of a capacitor: Echarging = e2 2C (1) For a platelet of several micrometers in diameter, the capacitance is on the order of 10–15 F and the charging energy is several tenths of a millielectronvolt. Only at temperatures below 1 K can single-electron effects be observed; otherwise, the thermal energy kT exceeds the charging energy. The capacitance is proportional to the cross section of a particle and, in macromolecules several nanometers in diameter, the charging energy is comparable to the thermal energy at room temperature [21]. For individual atomic sites in a crystal lattice, the charging energy will finally correspond to the Hubbard model discussed in Section 8.2 (Figure 8-1). These considerations immediately link electronic device miniaturization and single-electron effects to molecular electronics, and indeed, articles on multiple tunnel junctions’ in GaAs do not fail to point out that their ideas are also applicable to macromolecules [21]. 9.2 Information in Molecular Electronics As described above, the information within a molecular circuit is carried and acted upon by the existence and magnitude of charge. The flow of charge is literally the flow of information within the system. We note here, that within this paradigm there should be some inherent advantages of organic materials. Specifically, in low- 9.3 Early and Radical Concepts dimensional organic materials, electronic excitations are usually strongly coupled to the underlying crystal structure. The complicated structure of a macromolecule offers additional degrees of freedom, e.g., conformational degrees of freedom, which localize the excitations. Figure 4-2 shows an example of a molecule twisting and puckering when its excitation state is changed. Better localization should allow for closer packing of information than is possible in inorganic semiconductors. A particular case of localization in one-dimensional systems is solitons/polarons in conjugated polymeric chains (Section 5.4). They move as compact form-preserving pulses and not as dispersing wave packages (Figure 5-14). Information transfer in these systems is simply the group velocity of the wave function of the localized charge. The periodic structure of Si or GaAs, however, implies a certain degree of delocalization of electrons (Bloch waves). Under the conditions of low defect density, the charge is well represented by plane waves across the entire molecular structure. In this situation, not only is the modulus of the wave function preserved from one contact to the next, the phase of the wave function also is. In a phase-preserving system, it is conceivable that gain can also be achieved in a three-terminal configuration. However, we may ask if information transfer within this system now occurs at the phase velocity. The answer to this is not so straightforward. Generally, information is transferred when the phase between two states is compared. When these compared states are entangled, then information transfer may not be restricted to the group velocity of the states. These concepts lead naturally to the concepts of quantum bits [22]. Of course, we do not mean to imply that organics cannot be used in such applications. As Teich and colleagues have shown, it is quite possible to build an addressable entangled state with heteropolymers [23]. However, the delocalizedcarrier concept seems to have a natural extension to such applications. 9.3 Early and Radical Concepts Clearly, from the above discussion, the computational paradigm will ultimately decide the best approach to molecular-scale electronics. Most early work revolved around conjugated organic (synthetic metal) systems used as devices, as discussed above. In fact, this is still the mainstay effort in molecular-scale electronics. Thus, it is helpful to examine detailed proposals for molecular circuit elements in terms of their excitations and their dimensionality. 9.3.1 Soliton Switching Soon after solitons were discussed for polyacetylene [24–26], F. L. Carter introduced the concept of soliton switching’ [27]. In Chapter 5 a soliton in polyacetylene was described as a domain wall separating chain segments with different arrangements of bond alternation. These arrangements can be interpreted as logical states, and a 197 198 9 Molecular-scale Electronics Figure 9-3 Polyacetylene chain with two differently-conjugated segments separated by a domain wall (soliton). The domains can be interpreted as different states, to which different logical values can be assigned. passing soliton switches’ the chain from one state to the other (Figure 9-3). To read’ the state of a chain segment, two adjacent carbon atoms have to be marked and the bond between them has to be inspected. Carter proposed to incorporate a push–pull olefin (Figure 9-4) into the chain. In the ground state there is a double bond between the two central carbon atoms. The molecule can be excited by absorption of light. The excited molecule has a single bond in the central position and carries a dipole moment. The substituted polyacetylene chain is depicted in Figure 9-5. The push–pull olefin is used either as a soliton valve’ – in the ground state the conjugation along the chain is unaffected and the soliton can pass; in the excited state the conjugation is interrupted and the soliton movement is blocked – or as a soliton detector’ – if the unit is imbedded in a state-B segment, light can be absorbed (double bond between central carbon atoms = ground state), but if in a state-A segment, it already has a central single bond and cannot absorb light. There are also soliton bifurcations’ (Figure 9-6) and soliton reversals’ (Figure 9-7). Carter’s proposals have often been ridiculed as too naive and unfeasible. But their value is not to give instructions on how to synthesize a computer but rather to initiate the development of simple concepts for theoretical investigations. Figure 9-4 A push–pull olefin, which changes the nature of the bond between the central carbon atoms. It can be incorporated into a polyacetylene chain to serve as a soliton valve’ or as a soliton detector’. 9.3 Early and Radical Concepts Figure 9-5 A push–pull olefin imbedded in trans-polyacetylene can be switched off by the propagation of a soliton or can be used as a soliton detector. Figure 9-6 Soliton bifurcations. If the link is more complicated, the switch could be set from the outside, and bifurcations could be used to fan’ information from the macroscopic world into the molecular-electronic device. 199 200 9 Molecular-scale Electronics Figure 9-7 Molecular soliton reversals’. 9.3.2 Molecular Rectifiers Almost ten years before Carter, Aviram and Ratner designed a molecular rectifier’ [28]. An organic donor, for example TTF, is linked via an inert spacer to an organic acceptor, e.g., TCNQ (Figure 9-8) [29]. The spacer is called the r bridge, because it contains only saturated bonds (in Section 9.3.4 we will also meet p bridges). Figure 9-9 depicts the level scheme of a D–r–A molecule. Evidently, it is very asymmetric with respect to electron transfer from donor to acceptor or vice versa. The Aviram–Ratner device is shown in Figure 9-10. The rectifying molecules have to be organized in an ordered way between metal electrodes, so that all donor sites point in the same direction. To extend these ideas from a single molecule, as discussed in the introduction, to a computer in a beaker’, an ordered deposition of organic molecules is necessary. Many researchers have suggested that molecules like the one described may lend themselves well to Langmuir–Blodgett techniques [30,31]. Figure 9-8 Molecular rectifier as proposed by Aviram and Ratner [28], a so-called D–r–A molecule. 9.3 Early and Radical Concepts Figure 9-9 Level scheme of a D–r–A molecule. Because of the energy difference between D––r–A+ and D+–r–A– it is easier for electrons to move in one direction, and so the molecule acts as a rectifier [29]. Molecular rectifier using D–r–A molecules as proposed by Aviram and Ratner [28]. M1 and M2 are neutral electrodes. Schematic view according to Metzger [29]. Figure 9-10 9.3.3 Molecular Shift Register In 1989 Hopfield and coworkers [32] proposed a molecular shift register. A shift register is an array of cells (Figure 9-11). At each clock purse, the information of one cell is shifted to the next cell. Hopfield’s proposal is to make a microelectronic memory based on silicon. The information would be stored in capacitors of about 1 lm2 in cross section, and to extend the storage capacity, the third dimension would be used. That is, a molecular shift register would be set on top of each capacitor. The 201 202 9 Molecular-scale Electronics Figure 9-11 Schematic view of a molecular shift register. The cells are polymerized and a polymer chain is suspended between two electrodes, which are part of a microelectronic capacitor [32]. shift register would then be loaded by injecting electrons from the metallic capacitor plate into the first cell of the register, and it would be read by depositing the electrons into the channel of a field-effect transistor at the opposite side of the register. A cell of the shift register would have to consist of a donor and an acceptor part, as indicated in Figure 9-12. Electron transfer from cell to cell is shown in the schematic energy diagram in Figure 9-13. An organic molecule that could act as a cell in a molecular shift register is depicted in Figure 9-14. It has not only a donor and an acceptor group, but also a Schematic representation of the cells in a shift register memory. The cells contain at least one donor and one acceptor functional group [32]. Figure 9-12 Figure 9-13 The donor and acceptor levels in a typical shift register polymer [32]. Organic molecule that could act as a cell in a molecular shift register: upon proper illumination an electron is transferred from the left side to the right side [32]. Figure 9-14 9.3 Early and Radical Concepts sensitizer in the bridge. The sensitizer acts as a valve. Absorption of light opens the valve, and an electron is transferred from the donor to the acceptor. The process is very fast, e.g., it occurs within 1 ps. When the light source is shut off, the valve closes and the electron cannot go back. However, it can – and will – tunnel to the next cell, e.g., within 1 ns. So if there is a clock pulse every 10 ns, each clock pulse shifts the electrons by one step to the right, because the shift involves fast intramolecular and slow intermolecular charge transfer. The filled and empty cells carry information as 1’ and 0’ (chemically speaking, the molecules are neutral or ionized). The molecule shown in Figure 9-14 is polymerized to a chain length of about 600 repeat units and many identical chains would be placed between the electrodes. The device would be immersed in a solution to shield the coulombic repulsion (see the discussion on single-electron devices in Section 9.1). If the transfer efficiency is 99.9%, at each step about half of the electrons arrive at the receiving electrode after 600 hops, and 5000 chains would provide a signal large enough for detection with the sensitivity of present-day microcircuits. The realization of Hopfield’s proposal does not seem to be impossible, although probably not with 600 repeat-unit polymers. 9.3.4 Molecular Cellular Automata Figure 9-15 shows a donor and an acceptor linked by a p bridge (in contrast to the r bridge used in Section 9.3.2). Excitation of a D–p–A molecule can be interpreted as soliton switching: in the excited state, single and double bonds are inverted relative to the ground state. In addition, the excited state carries an electronic dipole moment. At the risk of oversimplifying, we could say that in a D–p–A molecule the donor and acceptor communicate by the exchange of solitons. A third functional group in the chain, called the modulable barrier (Figure 9-16), leads to a three-terminal device and allows logical operations. A linear array of D–p–A molecules (Figure 9-17) has been proposed as a molecular cellular automaton [33]. The scheme of a cellular automaton is presented in Figure 9-18. Here, only a one-dimensional array of cells is shown, but there could be two- or three-dimensional arrays, or arrays with even higher connectivities. The cells Polyene chain with donor and acceptor groups attached at the ends. Upon optical excitation, single and double bonds in this D–p–A molecule are inverted and the excited molecule carries a dipole moment. Figure 9-15 203 204 9 Molecular-scale Electronics Donor–acceptor-substituted polyene with a third functional group incorporated, the barrier’. This three-dimensional device allows for logical operations. Figure 9-16 Figure 9-17 Donor–acceptor-substituted polyenes as cells of a linear cellular automaton [33]. Figure 9-18 Scheme of a cellular automaton. must exhibit at least two states to be capable of storing information. When the array is exposed to clock pulses, e.g., to pulses from a laser, the cells switch (change their state), and the probability of switching a particular cell has to depend on the states of the neighboring cells (conditional switching). A cellular automaton is the extreme of a parallel computer. It can be shown that a cellular automaton can carry out all computations of a conventional (sequential) computer, however, often much faster. It is easy to see that the array of D–p–A molecules is a cellular automaton: by the absorption of light the cells switch from state A to state B. The switching probability depends on the state of the neighboring cells, according to the dipolar moment associated with the state of the cells. The field of the dipoles detunes the resonance frequency for absorption. The relevant question is, of course, How good a cellular automaton is a D–p–A chain? Like all the proposals in this section, the D–p–A cellular automaton also is not intended to work as a practical device; it is a model to allow the asking and study of particular questions. 9.4 Carbon Nanotubes With the advent of novel molecules like the carbon nanotube, another approach to organic molecular-scale circuitry has appeared. Nanotubes are possible to manipulate spatially and, as demonstrated earlier, contacts can be added by several lithographic routes. Because of the unique one-dimensional band structure of the carbon nanotube and the fact that it represents a single crystal (generally visualized without defect), one might expect that charge would be transported ballistically’, that is, 9.4 Carbon Nanotubes Schematically, the total number of available conduction channels in a mesoscopic wire that lie between the Fermi levels of the contacts all contribute to the current. Figure 9-19 without scattering from one end to the other [34]. Of course, there are still the leads that touch the tube. There is a simple way to imagine what will happen in such a material and to understand why it would be useful as a device. Imagine a nanowire arranged between two electrodes as in Figure 9-19. Electrodes 1 and 2 have chemical potentials l1 and l2. The wire has length L. We take the electrodes as an unlimited reservoir of charge. If we assume no scattering at the interfaces between electrode and nanowire, and l1 > l2, then only electrons with energies l1 > E > l2 and having a wave vector going from left to right contribute to current in the wire. The pseudo Fermi level (defined by the highest occupied energy level for k > 0 and k < 0, treated as though these are independent because there is no scattering between them) for k > 0 is l1 and for k < 0 is l2. As we saw earlier, the dimensionality of the wire causes the allowed states to spread apart into sub-bands, as shown by the dashed lines. We can denote these energy states as Ei(k), for the ith state or band. So, whatever the current in the system is, we must add up the currents in the individual states between the pseudo Fermi levels to get it. Typically, the sub-bands with k states that have energies l1 > E > l2 are referred to as channels.’ The number of channels is a function of E, generally denoted M(E). Classically, an electron with a velocity given by v = h–1 (¶E/¶k) goes toward contact 2 in the above example, and one with an energy l1 > E > l2 contributes to the net current as I = ev/L. L/v is simply the transit time for the carrier. We can then add up a total current as: I = 2e/p P Ð i k>0 (h–1 (¶E/¶k) [ f(Ei – l1) – f(Ei – l2)] dk = 2 {e2/h} M (l1 – l2)/e Spin degeneracy has of course been added to the sum. The inverse of the level spacing (demonstrated in previous chapters) has been used as the current density per sub-band, and the f’s are the Fermi levels. Now notice that if the width of the wire is small, as in a carbon nanotube, » 1.4 nm, the number of states between l1 and l2, M, is about 2 (spin-up and spin-down), even for large differences in the chemical potentials (i.e., > 1 eV). However, for large wires, say > 1 lm, the number of channels is huge (l1 – l2 = 1 eV, M » 106) [35]. 205 206 9 Molecular-scale Electronics Schematic view of a nanotube field-effect transistor (taken from the homepage of the Molecular Biophysics Group at Delft University of Technology, C. Dekker www.mb.tn.tudelft.nl). Figure 9-20 The voltage between the two leads is obviously V = (l2 – l1)/e and the resistance is given by Rc = V/I = h/2e2 (1/M), a very famous result. This is generally referred to as the contact resistance’, and h/2e2 is the quantum of resistance, » 12.9 kX. Thus, a wire with no scattering has a resistance proportional to M–1 or a conductance proportional to M. Because we have M = 2 for a metallic nanotube, as stated above, we should measure 2 · 12.9 kX for its resistance. If the scattering mechanism is time-independent, Landauer has shown that the conductance formula above is modified by adding a probabilistic term (the transfer matrix). This is essentially the probability of scattering between channels as the charge travels between the leads. It looks like this: R = h/2e2 (1/M T) where T is the probability for transmission and is given as P ij ‰tij‰2 where the sum is over all M, and tij is the probability of scattering from the ith state to the jth state. Thus, for a nanotube, we expect the resistance to be R = 2 · 12.9 kX (1–T)/T Note that the reflected wave function causes a drop in the wire’s potential and that resistance is proportional to (1 – T). Of course, the actual predicted value then depends on a specific model for the scattering phenomena. It is also important to note that the phase relation of the carrier’s wave function can be lost in the scattering events. However, when it is preserved, scattering can lead to interference effects 9.4 Carbon Nanotubes that result in localization of charge on the nanowire. The most important expression of these phase-preserving interactions is universal conductance fluctuations in which the noise observed in a transport IV curve is not noise at all, but rather interference patterns formed by the impurities and defects within the quantum wire [36]. This formulation holds only when a high degree of delocalization exists in the wire. This is certainly true for nanotubes, and a number of experiments have demonstrated this [34]. Shown in Figure 9-20 is a nanotube placed on two electrodes. Notice too, that the tube has been placed in a field-effect transistor configuration as described above. The behavior of this system as a transistor is shown in Figure 9-21. The conductance is given in the inset, and the numbers are different from our expectations above. Clearly, the contacts here are not quite ideal. Nevertheless, many people have now repeated these experiments and suggest that such performance is more than adequate in transistor design. In fact, carrying the concepts of molecular circuits one step further, several groups, including researchers at Delft and IBM [38] have constructed more complex signal-processing circuits from these basic transistors. Figures 9-22 and 9-23 show circuits developed by the Delft group. The circuits demonstrate the use of molecular electronics in inverters, logic gates, memory systems, and oscillators; all the basic building blocks of computational systems. To date, the question remains: How will this be done on the scale of modern semiconductor chips? However, it is clear the conceptually, there are a number of routes to achieving molecular-scale electronics. IV characteristics as a function of gate voltage shows that nanotubes would make rather good transistors at room temperature [38]. Figure 9-21 207 208 9 Molecular-scale Electronics Figure 9-22 Height image of a single-nanotube transistor, acquired with an atomic force microscope. Whereas in Figure 9-20 the nanotube is placed on a SiO2 layer over doped silicon, here the nanotube is placed on Al2O3 over Al. The gate contact is Al, which allows better coupling and higher gain. Demonstration of one-, two-, and three-transistor logic circuits with carbon nanotube FETs. (A) Output voltage as a function of the input voltage of a nanotube inverter. (inset) Schematic of the electronic circuit. The resistance is 100 MX. (B) Output voltage of a nanotubes NOR for the four possible input states (1,1), (1,0), (0,1), and (0,0). A voltage of 0 V represents a logical 0 and a voltage of –1.5 V represents a logical 1. The resistance is 50 MX. (C) Output voltage of a flip-flop memory cell (SRAM) composed of two nanotube FETs. The output logical stays at 0 or 1 after the switch to the input has been opened. The two resistances are 100 MX and 2 GX. (D) Output voltage as a function of time for a nanotube ring oscillator. The three resistances are 100 MX, 100 MX, and 2 GX [39]. Figure 9-23 References and Notes References and Notes 1 D.H. Meadows, D.L. Meadows, and J. Randers. The Limits of Growth, Report to the Club of Rome, 1972. 2 H. Queisser. Kristallene Krisen: Mikroelektronik; Wege der Forschung, Kampf und Mrkte. Piper, Mnchen, 1985. 3 D. Bloor, M. Hanack, A. Le Mhaut, R. Lazzaroni, J.P. Rabe, S. Roth, and H. Sassabe. Conjugated polymeric materials, opportunities in electronics, optoelectronics, and molecular electronics. NATO ASI Series E: Applied Science 182, 587. J.L. Bredas and R.R. Chance (Eds.), Kluwer, Dordrecht, 1990. 4 F.L. Carter. Molecular Electronic Devices. Marcel Dekker, New York, 1982. 5 F.L. Carter. Molecular Electronic Devices II. Marcel Dekker, New York, 1987. 6 F.L. Carter, R.E. Siatkowski, and H. Wohltjen. Molecular Electronic Devices. North Holland, Amsterdam, 1988. 7 A. Aviram. Molecular Electronics – Science and Technology. United Engineering Trustees, New York, 1989. 8 F.T. Hong. 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Kluwer, Amsterdam, 2003. P. Harrison (Ed.), Quantum Wells, Wires and Dots: Theoretical and Computational Physics. John Wiley & Sons, New York, 2000. 14 K.K. Likharev. Possibility of creating analog and digital integrated circuits using the discrete, one-electron tunneling effect. Soviet Microelektronics 16, 109 (1987). K.K. Likharev. Correlated discrete transfer of single electrons in ultrasmall tunnel junctions. IBM Journal of Research and Development 32, 144 (1988). 15 D.V. Averin and K.K. Likharev. Mesoscopic Phenomena in Solids. p. 173. B.L. Altshuler, P.A. Lee, R.A. Webb (Eds.), Elsevier, Amsterdam, 1991. D.V. Averin and K.K. Likharev. Single Charge Tunneling. p. 311. H. Grabert and H.M. Devoret (Eds.), Plenum Press, New York, 1992. 16 T.A. Fulton and G.J. Dolan. Observation of single-electron charging effects in small tunnel junctions. Physical Review Letters, 59, 109 (1987). 17 L.S. Kuz’min and K.K. Likharev. 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