Evolution of a designless nanoparticle network into reconfigurable Boolean logic

Abstract

Natural computers exploit the emergent properties and massive parallelism of interconnected networks of locally active components1,2,3. Evolution has resulted in systems that compute quickly and that use energy efficiently, utilizing whatever physical properties are exploitable4. Man-made computers, on the other hand, are based on circuits of functional units that follow given design rules5,6. Hence, potentially exploitable physical processes, such as capacitive crosstalk, to solve a problem are left out7,8. Until now, designless nanoscale networks of inanimate matter that exhibit robust computational functionality had not been realized. Here we artificially evolve the electrical properties of a disordered nanomaterials system (by optimizing the values of control voltages using a genetic algorithm) to perform computational tasks reconfigurably. We exploit the rich behaviour that emerges from interconnected metal nanoparticles, which act as strongly nonlinear single-electron transistors9,10, and find that this nanoscale architecture can be configured in situ into any Boolean logic gate. This universal, reconfigurable gate would require about ten transistors in a conventional circuit. Our system meets the criteria for the physical realization of (cellular) neural networks11: universality (arbitrary Boolean functions), compactness, robustness and evolvability, which implies scalability to perform more advanced tasks12,13. Our evolutionary approach works around device-to-device variations and the accompanying uncertainties in performance. Moreover, it bears a great potential for more energy-efficient computation, and for solving problems that are very hard to tackle in conventional architectures14,15,16.

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Figure 1: Schematic of the device layout and working principle.
Figure 2: Reconfigurable Boolean logic gates.
Figure 3: Stability and robustness of logic gates.
Figure 4: Addition functionality using a two-input-two-output gate.

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Acknowledgements

We thank A.-J. Annema, M. Danish, J. Huskens, S. Intan, M. de Jong, J. Mikhal, B. Nauta, D. Reinhoudt, I. Rianasari, E. Strambini, F. Zwanenburg and all the collaborators of the NASCENCE project for fruitful discussions. We acknowledge financial support from MESA+, CTIT, the European Community's Seventh Framework Programme (FP7/2007–2013) under grant agreement No. 317662 and the European Research Council, ERC Starting Grant No. 240433.

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Contributions

S.K.B. and C.P.L. fabricated the samples, carried out the experiments and performed the data analysis. C.P.L. designed and programmed the genetic search algorithm. R.M.J.v.D. contributed with theoretical inputs. W.G.v.d.W. conceived the experiments, and planned and supervised the project. H.J.B. conceived the project together with W.G.v.d.W. and cosupervised. Z.L. and K.S.M. contributed to the sample fabrication. All the authors discussed the results, provided important insights and helped write the manuscript.

Corresponding author

Correspondence to W. G. van der Wiel.

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The authors declare no competing financial interests.

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Bose, S., Lawrence, C., Liu, Z. et al. Evolution of a designless nanoparticle network into reconfigurable Boolean logic. Nature Nanotech 10, 1048–1052 (2015). https://doi.org/10.1038/nnano.2015.207

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