Analog Programing of Conducting-Polymer ...
Document type :
Article dans une revue scientifique: Article original
Title :
Analog Programing of Conducting-Polymer Dendritic Interconnections and Control of their Morphology
Author(s) :
Janzakova, Kamila [Auteur]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Kumar, Ankush [Auteur]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Ghazal, Mahdi [Auteur]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Susloparova, Anna [Auteur]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Coffinier, Yannick [Auteur]
NanoBioInterfaces - IEMN [NBI - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Alibart, Fabien [Auteur]
Laboratoire Nanotechnologies et Nanosystèmes [Sherbrooke] [LN2]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Pecqueur, Sebastien [Auteur correspondant]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Kumar, Ankush [Auteur]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Ghazal, Mahdi [Auteur]

Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Susloparova, Anna [Auteur]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Coffinier, Yannick [Auteur]

NanoBioInterfaces - IEMN [NBI - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Alibart, Fabien [Auteur]

Laboratoire Nanotechnologies et Nanosystèmes [Sherbrooke] [LN2]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Pecqueur, Sebastien [Auteur correspondant]
Nanostructures, nanoComponents & Molecules - IEMN [NCM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Journal title :
Nature Communications
Publisher :
Nature Publishing Group
Publication date :
2021-12
ISSN :
2041-1723
HAL domain(s) :
Chimie/Matériaux
Physique [physics]/Matière Condensée [cond-mat]/Systèmes désordonnés et réseaux de neurones [cond-mat.dis-nn]
Sciences de l'ingénieur [physics]/Electronique
Physique [physics]/Matière Condensée [cond-mat]/Systèmes désordonnés et réseaux de neurones [cond-mat.dis-nn]
Sciences de l'ingénieur [physics]/Electronique
English abstract : [en]
Although materials and processes are different from biological cells', brain mimicries led to tremendous achievements in massively parallel information processing via neuromorphic engineering. Inexistent in electronics, ...
Show more >Although materials and processes are different from biological cells', brain mimicries led to tremendous achievements in massively parallel information processing via neuromorphic engineering. Inexistent in electronics, we describe how to emulate dendritic morphogenesis by electropolymerization in water, aiming in operando material modification for hardware learning. The systematic study of applied voltage-pulse parameters details on tuning independently morphological aspects of micrometric dendrites': as fractal number, branching degree, asymmetry, density or length. Time-lapse image processing of their growth shows the spatial features to be dynamically-dependent and expand distinctively before and after forming a conductive bridging of two electrochemically grown dendrites. Circuit-element analysis and electrochemical impedance spectroscopy confirms their morphological control to occur in temporal windows where the growth kinetics can be finely perturbed by the input signal frequency and duty cycle. By the emulation of one of the most preponderant mechanisms responsible for brain's long-term memory, its implementation in the vicinity of sensing arrays, neural probes or biochips shall greatly optimize computational costs and recognition performances required to classify high-dimensional patterns from complex aqueous environments.Show less >
Show more >Although materials and processes are different from biological cells', brain mimicries led to tremendous achievements in massively parallel information processing via neuromorphic engineering. Inexistent in electronics, we describe how to emulate dendritic morphogenesis by electropolymerization in water, aiming in operando material modification for hardware learning. The systematic study of applied voltage-pulse parameters details on tuning independently morphological aspects of micrometric dendrites': as fractal number, branching degree, asymmetry, density or length. Time-lapse image processing of their growth shows the spatial features to be dynamically-dependent and expand distinctively before and after forming a conductive bridging of two electrochemically grown dendrites. Circuit-element analysis and electrochemical impedance spectroscopy confirms their morphological control to occur in temporal windows where the growth kinetics can be finely perturbed by the input signal frequency and duty cycle. By the emulation of one of the most preponderant mechanisms responsible for brain's long-term memory, its implementation in the vicinity of sensing arrays, neural probes or biochips shall greatly optimize computational costs and recognition performances required to classify high-dimensional patterns from complex aqueous environments.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Comment :
data available here: 10.6084/m9.figshare.16814710
Source :
Files
- https://hal.archives-ouvertes.fr/hal-03454788/document
- Open access
- Access the document
- https://www.nature.com/articles/s41467-021-27274-9.pdf
- Open access
- Access the document
- https://hal.archives-ouvertes.fr/hal-03454788/document
- Open access
- Access the document
- https://hal.archives-ouvertes.fr/hal-03454788/document
- Open access
- Access the document
- 2021.02.01%20-%20preprint.pdf
- Open access
- Access the document
- s41467-021-27274-9.pdf
- Open access
- Access the document
- document
- Open access
- Access the document
- document
- Open access
- Access the document
- 2021.02.01%20-%20preprint.pdf
- Open access
- Access the document