Our societies are profoundly affected by the development of Artificial Intelligence (AI). In fact, AI is applied in many fields: in science, medicine, security, economy, and well-being [1]. There are two strategies to develop AI. One is by writing human-like intelligent programs running in computers or special-purpose hardware. The other is through neuromorphic engineering [2]. In neuromorphic engineering, surrogates of neurons are implemented through non-biological systems. Surrogates of neurons can be implemented through specific solid materials, in hardware that can be rigid if made of solid inorganic compounds [3] or flexible if based on organic films [4]. Alternatively, surrogates of neurons can be implemented through solutions of specific non-linear chemical systems, in wetware [5]. In our group, we are pursuing this second approach: we propose the use of peculiar chemical systems that, in the liquid phase and out-of-equilibrium conditions, can mimic the dynamics of real neurons [6-11]. We usually exploit UV-visible radiation as signals, and we study their optical communication, giving rise to feedback actions and emergent phenomena of temporal synchronization, analogous to those shown by real neural networks. In this contribution, we show how photochromic and luminescent compounds can be used to mimic phasic excitable and pacemaker neurons, and to implement neuromodulation [12]. References [1] S. J. Russell, P. Norvig, Artificial Intelligence. A Modern Approach. (2009) Prentice-Hall, New Jersey. [2] C. Mead, Proc IEEE 78 (1990) 1629-1636. [3] R. A. Nawrocki, R. M. Voyles, IEEE T Electron Dev 63 (2016) 3819-3829. [4] Y. Lee, T.-W. Lee, Acc Chem Res 52 (2019) 964-974. [5] P. L. Gentili, RSC Adv 3 (2013) 25523-25549. [6] P. L. Gentili, V. Horvath, V. K. Vanag, I. R. Epstein, Int J Unconv Comput 8 (2012) 177-192. [7] V. Horvath, P. L. Gentili, V. K. Vanag, I. R. Epstein, Angew. Chem. Int. Ed. 51 (2012) 6878-6881. [8] P. L. Gentili, A. L. Rightler, B. M. Heron, C. D. Gabbutt, Chem Commun. 52 (2016)1474-1477. [9] P. L. Gentili, A. L. Rightler, B. M. Heron, C. D. Gabbutt, Dyes Pigments 135 (2016) 169-176. [10] P. L. Gentili, M. S. Giubila, R. Germani, A. Romani, A. Nicoziani, A. Spalletti, B. M. Heron, Angew Chem Int Ed 56 (2017) 7535-7540. [11] P. L. Gentili, M. S. Giubila, R. Germani, B. M. Heron, Dyes Pigments 156 (2018) 149-159. [12] B. Bartolomei, B. M. Heron, P. L. Gentili, Rend. Fis. Acc. Lincei (2020) DOI :10.1007/s12210-020-00869-y.

Photochromic and Luminescent Compounds at the service of Artificial Intelligence

Pier Luigi Gentili
Project Administration
;
Beatrice Bartolomei
Membro del Collaboration Group
;
Raimondo Germani
Membro del Collaboration Group
;
2020

Abstract

Our societies are profoundly affected by the development of Artificial Intelligence (AI). In fact, AI is applied in many fields: in science, medicine, security, economy, and well-being [1]. There are two strategies to develop AI. One is by writing human-like intelligent programs running in computers or special-purpose hardware. The other is through neuromorphic engineering [2]. In neuromorphic engineering, surrogates of neurons are implemented through non-biological systems. Surrogates of neurons can be implemented through specific solid materials, in hardware that can be rigid if made of solid inorganic compounds [3] or flexible if based on organic films [4]. Alternatively, surrogates of neurons can be implemented through solutions of specific non-linear chemical systems, in wetware [5]. In our group, we are pursuing this second approach: we propose the use of peculiar chemical systems that, in the liquid phase and out-of-equilibrium conditions, can mimic the dynamics of real neurons [6-11]. We usually exploit UV-visible radiation as signals, and we study their optical communication, giving rise to feedback actions and emergent phenomena of temporal synchronization, analogous to those shown by real neural networks. In this contribution, we show how photochromic and luminescent compounds can be used to mimic phasic excitable and pacemaker neurons, and to implement neuromodulation [12]. References [1] S. J. Russell, P. Norvig, Artificial Intelligence. A Modern Approach. (2009) Prentice-Hall, New Jersey. [2] C. Mead, Proc IEEE 78 (1990) 1629-1636. [3] R. A. Nawrocki, R. M. Voyles, IEEE T Electron Dev 63 (2016) 3819-3829. [4] Y. Lee, T.-W. Lee, Acc Chem Res 52 (2019) 964-974. [5] P. L. Gentili, RSC Adv 3 (2013) 25523-25549. [6] P. L. Gentili, V. Horvath, V. K. Vanag, I. R. Epstein, Int J Unconv Comput 8 (2012) 177-192. [7] V. Horvath, P. L. Gentili, V. K. Vanag, I. R. Epstein, Angew. Chem. Int. Ed. 51 (2012) 6878-6881. [8] P. L. Gentili, A. L. Rightler, B. M. Heron, C. D. Gabbutt, Chem Commun. 52 (2016)1474-1477. [9] P. L. Gentili, A. L. Rightler, B. M. Heron, C. D. Gabbutt, Dyes Pigments 135 (2016) 169-176. [10] P. L. Gentili, M. S. Giubila, R. Germani, A. Romani, A. Nicoziani, A. Spalletti, B. M. Heron, Angew Chem Int Ed 56 (2017) 7535-7540. [11] P. L. Gentili, M. S. Giubila, R. Germani, B. M. Heron, Dyes Pigments 156 (2018) 149-159. [12] B. Bartolomei, B. M. Heron, P. L. Gentili, Rend. Fis. Acc. Lincei (2020) DOI :10.1007/s12210-020-00869-y.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1479838
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