Nanocell Logic Gates for Molecular Computing

1. Nanocell Logic Gates for Molecular Computing J. M. Tour, W. L. Van Zandt, C. P. Husband, S. M. Husband, L. S. Wilson, P. D. Franzon and D. P. Nackashi IEEE TRANSACTIONS ON NANOTECHNOLOGY, VOL. 1, NO. 2, pp. 100-109, JUNE 2002 Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

2. Nanocell Logic Gates for Molecular Computing Molecular electronics Molecular electronics seeks to build electrical devices to implement computation using individual or small collections of moleculesthat are approximately one million times smaller in area than their present solid state counterparts. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

3. Nanocell Logic Gates for Molecular Computing Molecular electronics • Goals: reducing device size and fabrication costs • Requirements: molecular switches and scaled interconnections • Challenges: placement and interconnection (bottom-up vs. top-down approach) Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

4. Nanocell Logic Gates for Molecular Computing Molecular electronics Potential advantages of molecular electronic systems could be: • reducing the complexity and cost of current integrated circuit fabrication technologies; • reducing heat generation by using only a few electrons per bit of information; • providing a route to meet the ever-continuing demand for miniaturization. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

5. Nanocell Logic Gates for Molecular Computing Molecular electronics A scaled interconnect technology is necessary for: • building logic blocks and discrete device components, analogously to VLSI architectures; • selective connection to mesoscopically defined input-output. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

6. Nanocell Logic Gates for Molecular Computing Molecular electronics: NANOCELL The nanocell approach described here, differently from other solutions, is not dependent on placing molecules in precise orientations or locations, but it needs a programming activity in the postfabrication to achieve the desired design. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

7. Nanocell Logic Gates for Molecular Computing Molecular electronics: NANOCELL A nanocell is a two-dimensional (2-D) network of self-assembled metallic particles connected by molecules that show reprogrammable (can be turned ON or OFF) negative differential resistance (NDR). Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

8. Nanocell Logic Gates for Molecular Computing Molecular electronics: NANOCELL Unlike typical chip fabrication butsimilar in some respects to an FPGA, the nanocell is not constructed as a specific logic gate and the internal topology is, for the most part, disordered. Logic is created in the nanocell by training its postfabrication. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

9. Nanocell Logic Gates for Molecular Computing Molecular electronics: NANOCELL Even if this approach is only a few percent efficient in the use of the nanocell, very high logic densities will be possible. Moreover, the nanocell has the potential to be reprogrammed throughout a computational process via changes in the ON and OFF states of the molecules (molecular switches), thereby creating a real-time dynamic reconfigurable hard-wired logic. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

10. Nanocell Logic Gates for Molecular Computing Molecular electronics: from NANOCELL to computer The central processing unit of the computer would be comprised of arrays of nanocells wherein each nanocell would have the functionality of many transistors working in concert. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

11. Nanocell Logic Gates for Molecular Computing Molecular electronics: from NANOCELL to computer Pure hierarchical structure in a regular array of nanocells or underlying CMOS programming? • a few nanocells, once programmed, should be capable of programming their neighboring nanocells; or • arrays could be programmed one nanocell at a time via an underlying CMOS platform. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

12. Nanocell Logic Gates for Molecular Computing Molecular electronics: from NANOCELL to computer Objects: • search of a nanocell programming algorithm to create functionality from disorder • defect, fault-tolerance and performance analysis by SPICE simulations Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

13. Nanocell Logic Gates for Molecular Computing NANOCELL Example of a self-assembled nanocell with I/O leads (gray cell area  1m²) Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

14. Nanocell Logic Gates for Molecular Computing NANOCELL This cell has been obtained depositing a 2-D array of metal nanoparticles on an oxide surface; a molecular self-assembled monolayer coating each nanoparticle would control the spacing between nanoparticles. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

15. Nanocell Logic Gates for Molecular Computing NANOCELL: molecular switches Molecular switches are added to create barriers around each nanoparticle into the inert monolayer and to inter-link in a controllable way adjacent nanoparticles. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

16. Nanocell Logic Gates for Molecular Computing NANOCELL: molecular switches • There could be multiple switches between pairs of nanoparticles. • Each molecular switch could be set into an ON state or an OFF state. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

17. Nanocell Logic Gates for Molecular Computing NANOCELL: nanoparticles • Nanoparticle diameter  60 nm • Nanoparticle spacing  3 nm • Regular grid placement  • 200 - 250 nanoparticles in a single nanocell Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

18. Nanocell Logic Gates for Molecular Computing NANOCELL: nanoparticles and molecular switches • Nanoparticle placement according to a regular grid is not necessary, but it lets us to: • determine the possible connections within the nanocell; • estimate the number of switches with the proper orientation between adjacent nanoparticles. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

19. Nanocell Logic Gates for Molecular Computing NANOCELL Once the physical topology of the self-assembly is formed in the nanocell, it remains static; the only changeable behavior is in the molecular switch states. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

20. Nanocell Logic Gates for Molecular Computing NANOCELL I/O leads are interchangeable: only in the programming phase designer reveals their own identity, relatively to the requested function for the nanocell. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

21. Nanocell Logic Gates for Molecular Computing NANOCELL Enormous space savings could be attained since a nanocell could possess the functionality of numerous transistors working in concert to produce a specified logic function  Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

22. Nanocell Logic Gates for Molecular Computing NANOCELL • We can accept the use of a CMOS gain transistor at the output of a nanocell, without wasting the area reduction compared to a CMOS realization. • We can suppose to build internal gain elements based upon nanoparticles and molecular switches. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

23. Nanocell Logic Gates for Molecular Computing MOLECULAR SWITCH A molecular switch is a molecule terminated on both its end with molecular alligator clips, such as thiols, and inserted between adjacent nanoparticles via self-assembly with molecule-metal chemical bonding to establish electrical contacts. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

24. Nanocell Logic Gates for Molecular Computing MOLECULAR SWITCH Each molecular switch can be reversibly turned ON or OFF in the postfabrication, using voltage pulses at nearby lithographically defined contact pads in the periphery of the cell. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

25. Nanocell Logic Gates for Molecular Computing MOLECULAR SWITCH The functionality of the entire nanocell depends largely on the I(V) characteristics of molecular switches; in particular it is interesting the use of a molecular switch with a Negative Differential Resistance in order to build logic devices that exhibit negating functionality such as nand or xor. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

26. Nanocell Logic Gates for Molecular Computing MOLECULAR SWITCH Examples of I(V) responses with NDR Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

27. Nanocell Logic Gates for Molecular Computing MOLECULAR SWITCH A number of devices with the previous I(V) response have been tested for over one year with no signs of degradation over nearly 109 switching events. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

28. Nanocell Logic Gates for Molecular Computing NANOCELL programming The object in programming or training a nanocell is to take a random nanocell with a fixed topology and turn its switches ON and OFF until it functions as a target logic device. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

29. Nanocell Logic Gates for Molecular Computing NANOCELL programming: OMNISCIENCE Location and state of each switch and connections within the nanocell are known. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

30. Nanocell Logic Gates for Molecular Computing NANOCELL programming: OMNIPOTENCE The search algorithmknows the location of each molecular switch and has preciseand selective access to reversibly set its ON or OFF state (omnipotence implies omniscience). Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

31. Nanocell Logic Gates for Molecular Computing NANOCELL programming: MORTAL SWITCHING The algorithm does not know theconnections within the nanocell or locations of the switches and switching is limited to voltage pulses applied to the I/Opins. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

32. Nanocell Logic Gates for Molecular Computing NANOCELL programming: MORTAL SWITCHING Nanocell is considered as a black box.  Programming has to find: • switch states such that the given nanocell functions as the target logic device; • a series of voltage pulses (applied to the I/O pins) that give rise to these desired switch states. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

33. Nanocell Logic Gates for Molecular Computing NANOCELL programming: MORTAL SWITCHING • Given a certain density of nanoparticles and molecular switches, can any random nanocell be trained as some target logic device? • Which are the switch states where a nanocells works as a target logic device? • How have we got to build the training for a nanocell using voltage pulses at the I/O pins? Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

34. Nanocell Logic Gates for Molecular Computing NANOCELL programming: nanocell modeling • A nanocell is generated as a hexagonal grid of metallic particles with distributed molecular switch. • To train the nanocell, we have to evaluate the output current resulting from the voltage traces applied to input. • In the following simulations individual molecules have been modeled asnonlinear resistors. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

35. Nanocell Logic Gates for Molecular Computing NANOCELL programming: nanocell search space • Programming a nanocell, we have to solve a combinatorial optimization problem whose search space is the set of all possible switch states in the cell; in particular we have to find the minimization of a function evaluating nanocell behaviour. • Here a Genetic Algorithm is used to search the solution space for a given nanocell. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

36. Nanocell Logic Gates for Molecular Computing NANOCELL programming: nanocell search space For an actual nanocell of 1m² with 250-1000 nanoparticles and 750-10000 molecular switches, the search space is minimally 2750 (the number of elemental particles inthe universe is estimated at2300). Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

37. Nanocell Logic Gates for Molecular Computing Genetic algorithms Genetic algorithms work by taking a population of individuals, represented as strings of “1s” and “0s” (chromosomes) quantifying their fitness, then recombining them to generate a new population of children. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

38. Nanocell Logic Gates for Molecular Computing Genetic algorithms Usually the first generation is randomly created and then three operatorsare used to produce each subsequent generation: • selection • crossover • mutation Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

39. Nanocell Logic Gates for Molecular Computing Genetic algorithms • Among the individuals of each generation the two most fit are chosen to reproduce the next. • Crossover and mutation of bits representing the chromosome preserve the main feature of good individuals without leaving unexplored far regions in the solution space. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

40. Nanocell Logic Gates for Molecular Computing Training nanocells with a genetic algorithm • In order to find configurations that perform the desired logic function, some pins of the nanocell are set to input or output. • The nanocell is treated as a voltage-in current-out device, so VIH, VIL, IOH and IOL have to be defined. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

41. Nanocell Logic Gates for Molecular Computing Training nanocells with a genetic algorithm • Using VIH, VIL, IOH and IOL values we can build a function f evaluating the fitness of the nanocell. • In the following simulations the condition f=0 assures that nanocell works properly to achieve the desired logic function. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

42. Nanocell Logic Gates for Molecular Computing Training nanocells with a genetic algorithm • It is quite important to choose a good function evaluating the performance of the nanocell. • Fitness expression f is not independent of the desired function for the nanocell; every contribution to f must be weighed to assure convergence for solutions. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

43. Nanocell Logic Gates for Molecular Computing GA training results : inverter Example of nanocell performing INVERTER Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

44. Nanocell Logic Gates for Molecular Computing GA training results: inverter • Twelve nanocells were randomly generated and all were successfully trained as inverters. • It took an average of four generation to train each inverter (with 25 individuals for each generation). • Final result: pin A is set to input and pin 1 is set to output. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

45. Nanocell Logic Gates for Molecular Computing GA training results: nand gate Example of nanocell performing NAND gate Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

46. Nanocell Logic Gates for Molecular Computing GA training results:nand gate • Twelve nanocells were randomly generated and all were successfully trained and tested as robust nands. • On average it took about nine generations for each nand to converge. • A configuration with adjacent I/O pins was hunted. • Final result: pins A and B are set to input and pin 1 is set to output. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

47. Nanocell Logic Gates for Molecular Computing GA training results: full-adder Example of nanocell performing 1-bit adder Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

48. Nanocell Logic Gates for Molecular Computing GA training results: full-adder • Full-adder has been trained on a nanocell with 70 nanoparticles and 1000 molecular switches. • Final results: • pins A, B and C are set to input and pins 1 and 2 are set to output; • a nanocell can be trained as a complex logic device with multiple outputs. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

49. Nanocell Logic Gates for Molecular Computing GA training results • The simulation time depends primarily on the number of molecular switches in the nanocell. • Because of the vast solution space, in lucky events we can find functioning devices in the initial random population. • A test of robustness is opportune to value nanocell properties and performance. Nanotecnologie 1 Saverio Minutoli and Paolo Spiga

50. Nanocell Logic Gates for Molecular Computing Adjunctive GA training results for nands • Nands are particularly attractive since they constitute a functionally complete logic set: any logic function could be created from nand sets. • Simulation has been run to exhaustively evaluate every possible combination of switch states for 50 small nanocells (516 switches  25216 switch state combinations.  Nanotecnologie 1 Saverio Minutoli and Paolo Spiga