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Molecular field-coupled nanocomputing (molFCN) encodes information in the molecule charge distribution and elaborates it through electrostatic coupling. Despite the advantageous sub-nanometric size and low-power dissipation, only a few attempts have been made to validate the technology experimentally. One of the obstacles is the difficulty in measuring molecule charges to validate information encoding or integrate molFCN with complementary-metal-oxide-semiconductor (CMOS). In this work, we propose a paradigm preserving the advantages of molFCN, which exploits the position of waiving molecules to augment the information encoding. We validate the paradigm, named bend-boosted molFCN, with density functional theory using 6-(ferrocenyl)hexanethiol cations. We demonstrate that the encoded information can be electrically read by constituting a molecular junction. The paradigm is compatible with the charge-based molFCN, thus acting as a readout system. The obtained results favor the experimental assessment of the molFCN principle through scanning probe microscopy techniques and the design of molFCN-CMOS heterogeneous circuits.
Lent, C. S.; Tougaw, P. D.; Porod, W.; Bernstein, G. H. Quantum cellular automata. Nanotechnology 1993, 4, 49–57.
Lent, C. S. Bypassing the transistor paradigm. Science 2000, 288, 1597–1599.
Lent, C. S.; Isaksen, B.; Lieberman, M. Molecular quantum-dot cellular automata. J. Am. Chem. Soc. 2003, 125, 1056–1063.
Lent, C. S.; Isaksen, B. Clocked molecular quantum-dot cellular automata. IEEE Trans. Electron Devices 2003, 50, 1890–1896.
Arima, V.; Iurlo, M.; Zoli, L.; Kumar, S.; Piacenza, M.; Della Sala, F.; Matino, F.; Maruccio, G.; Rinaldi, R.; Paolucci, F. et al. Toward quantum-dot cellular automata units: Thiolated-carbazole linked bisferrocenes. Nanoscale 2012, 4, 813–823.
Lu, Y. H.; Lent, C. S. A metric for characterizing the bistability of molecular quantum-dot cellular automata. Nanotechnology 2008, 19, 155703.
Ardesi, Y.; Garlando, U.; Riente, F.; Beretta, G.; Piccinini, G.; Graziano, M. Taming molecular field-coupling for nanocomputing design. J. Emerg. Technol. Comput. Syst. 2023, 19, 1.
Blair, E. P.; Yost, E.; Lent, C. S. Power dissipation in clocking wires for clocked molecular quantum-dot cellular automata. J. Comput. Electron. 2010, 9, 49–55.
Ardesi, Y.; Graziano, M.; Piccinini, G. A model for the evaluation of monostable molecule signal energy in molecular field-coupled nanocomputing. J. Low Power Electron. Appl. 2022, 12, 13.
Blair, E. P.; Corcelli, S. A.; Lent, C. S. Electric-field-driven electron-transfer in mixed-valence molecules. J. Chem. Phys. 2016, 145, 014307.
Wang, Y.; Lieberman, M. Thermodynamic behavior of molecular-scale quantum-dot cellular automata (QCA) wires and logic devices. IEEE Trans. Nanotechnol. 2004, 3, 368–376.
Ardesi, Y.; Gaeta, A.; Beretta, G.; Piccinini, G.; Graziano, M. Ab initio molecular dynamics simulations of field-coupled nanocomputing molecules. J. Integr. Circuits Syst. 2021, 16, 1–8.
Verstraete, L.; Szabelski, P.; Bragança, A. M.; Hirsch, B. E.; De Feyter, S. Adaptive self-assembly in 2D nanoconfined spaces: Dealing with geometric frustration. Chem. Mater. 2019, 31, 6779–6786.
Christie, J. A.; Forrest, R. P.; Corcelli, S. A.; Wasio, N. A.; Quardokus, R. C.; Brown, R.; Kandel, S. A.; Lu, Y. H.; Lent, C. S.; Henderson, K. W. Synthesis of a neutral mixed-valence diferrocenyl carborane for molecular quantum-dot cellular automata applications. Angew. Chem., Int. Ed. 2015, 54, 15448–15451.
Ardesi, Y.; Beretta, G.; Fabiano, C.; Graziano, M.; Piccinini, G. A reconfigurable field-coupled nanocomputing paradigm on uniform molecular monolayers. In 2021 International Conference on Rebooting Computing (ICRC), Los Alamitos, CA, USA, 2021, pp 124–128.
Mallada, B.; Ondráček, M.; Lamanec, M.; Gallardo, A.; Jiménez-Martín, A.; de la Torre, B.; Hobza, P.; Jelínek, P. Visualization of π-hole in molecules by means of kelvin probe force microscopy. Nat. Commun. 2023, 14, 4954.
Gross, L.; Mohn, F.; Liljeroth, P.; Repp, J.; Giessibl, F. J.; Meyer, G. Measuring the charge state of an adatom with noncontact atomic force microscopy. Science 2009, 324, 1428–1431.
Liza, N.; Murphey, D.; Cong, P. Z.; Beggs, D. W.; Lu, Y.; Blair, E. P. Asymmetric, mixed-valence molecules for spectroscopic readout of quantum-dot cellular automata. Nanotechnology 2022, 33, 115201.
Ardesi, Y.; Mo, F.; Spano, C. E.; Ardia, G.; Piccinini, G.; Graziano, M. Conformation-based molecular memories for nanoscale memcomputing. In IEEE 23rd International Conference on Nanotechnology (NANO), Jeju Island, Korea, 2023, pp 694–697.
Peng, J. B.; Sokolov, S.; Hernangómez-Pérez, D.; Evers, F.; Gross, L.; Lupton, J. M.; Repp, J. Atomically resolved single-molecule triplet quenching. Science 2021, 373, 452–456.
Mishra, S.; Fatayer, S.; Fernández, S.; Kaiser, K.; Peña, D.; Gross, L. Nonbenzenoid high-spin polycyclic hydrocarbons generated by atom manipulation. ACS Nano 2022, 16, 3264–3271.
Hieulle, J.; Castro, S.; Friedrich, N.; Vegliante, A.; Lara, F. R.; Sanz, S.; Rey, D.; Corso, M.; Frederiksen, T.; Pascual, J. I. et al. On-surface synthesis and collective spin excitations of a triangulene-based nanostar. Angew. Chem., Int. Ed. 2021, 60, 25224–25229.
Mo, F.; Ardesi, Y.; Roch, M. R.; Graziano, M.; Piccinini, G. Investigation of amperometric sensing mechanism in gold-C60-gold molecular dot. IEEE Sensors J. 2022, 22, 19152–19161.
Mo, F.; Spano, C. E.; Ardesi, Y.; Roch, M. R.; Piccinini, G.; Graziano, M. Design of pyrrole-based gate-controlled molecular junctions optimized for single-molecule aflatoxin B1 detection. Sensors 2023, 23, 1687.
Ardesi, Y.; Pulimeno, A.; Graziano, M.; Riente, F.; Piccinini, G. Effectiveness of molecules for quantum cellular automata as computing devices. J. Low Power Electron. Appl. 2018, 8, 24.
Karadag, M.; Geyik, C.; Demirkol, D. O.; Ertas, F. N.; Timur, S. Modified gold surfaces by 6-(ferrocenyl)hexanethiol/dendrimer/gold nanoparticles as a platform for the mediated biosensing applications. Mater. Sci. Eng.: C 2013, 33, 634–640.
Göver, T.; Yazıcıgil, Z. Electrochemical study of 6-(ferrocenyl)hexanethiol on gold electrode surface in non-aqueous media. Surf. Interfaces 2018, 13, 163–167.
Csaba, G.; Imre, A.; Bernstein, G. H.; Porod, W.; Metlushko, V. Nanocomputing by field-coupled nanomagnets. IEEE Trans. Nanotechnol. 2002, 1, 209–213.
Solomon, G. C.; Herrmann, C.; Hansen, T.; Mujica, V.; Ratner, M. A. Exploring local currents in molecular junctions. Nat. Chem. 2010, 2, 223–228.
Ardesi, Y.; Turvani, G.; Graziano, M.; Piccinini, G. SCERPA simulation of clocked molecular field-coupling nanocomputing. IEEE Trans. Very Large Scale Integr. VLSI Syst. 2021, 29, 558–567.
Neese, F. The ORCA program system. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2012, 2, 73–78.
Neese, F. Software update: The ORCA program system, version 4.0. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2018, 8, e1327.
Weigend, F.; Ahlrichs, R. Balanced basis sets of split valence, triple zeta valence and quadruple zeta valence quality for H to Rn: Design and assessment of accuracy. Phys. Chem. Chem. Phys. 2005, 7, 3297.
Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H–Pu. J. Chem. Phys. 2010, 132, 154104.
Grimme, S.; Ehrlich, S.; Goerigk, L. Effect of the damping function in dispersion corrected density functional theory. J. Comput. Chem. 2011, 32, 1456–1465.
Breneman, C. M.; Wiberg, K. B. Determining atom-centered monopoles from molecular electrostatic potentials The need for high sampling density in formamide conformational analysis. J. Comput. Chem. 1990, 11, 361–373.
Weigend, F. Accurate Coulomb-fitting basis sets for H to Rn. Phys. Chem. Chem. Phys. 2006, 8, 1057–1065.
Thompson, A. P.; Aktulga, H. M.; Berger, R.; Bolintineanu, D. S.; Brown, W. M.; Crozier, P. S.; in ’t Veld, P. J.; Kohlmeyer, A.; Moore, S. G.; Nguyen, T. D. et al. LAMMPS—A flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comput. Phys. Commun. 2022, 271, 108171.
Aktulga, H. M.; Fogarty, J. C.; Pandit, S. A.; Grama, A. Y. Parallel reactive molecular dynamics: Numerical methods and algorithmic techniques. Parallel Comput. 2012, 38, 245–259.
Rodriguez, J. A.; Dvorak, J.; Jirsak, T.; Liu, G.; Hrbek, J.; Aray, Y.; González, C. Coverage effects and the nature of the metal–sulfur bond in S/Au(111): High-resolution photoemission and density-functional studies. J. Am. Chem. Soc. 2003, 125, 276–285.
Smidstrup, S.; Markussen, T.; Vancraeyveld, P.; Wellendorff, J.; Schneider, J.; Gunst, T.; Verstichel, B.; Stradi, D.; Khomyakov, P. A.; Vej-Hansen, U. G. et al. Quantumatk: An integrated platform of electronic and atomic-scale modelling tools. J. Phys.: Condens. Matter 2020, 32, 015901.
Smidstrup, S.; Stradi, D.; Wellendorff, J.; Khomyakov, P. A.; Vej-Hansen, U. G.; Lee, M. E.; Ghosh, T.; Jónsson, E.; Jónsson, H.; Stokbro, K. First-principles Green’s-function method for surface calculations: A pseudopotential localized basis set approach. Phys. Rev. B 2017, 96, 195309.
Brandbyge, M.; Mozos, J. L.; Ordejón, P.; Taylor, J.; Stokbro, K. Density-functional method for nonequilibrium electron transport. Phys. Rev. B 2002, 65, 165401.
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