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      Interfacing Biology and Electronics with Memristive Materials

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          Abstract

          Memristive technologies promise to have a large impact on modern electronics, particularly in the areas of reconfigurable computing and artificial intelligence (AI) hardware. Meanwhile, the evolution of memristive materials alongside the technological progress is opening application perspectives also in the biomedical field, particularly for implantable and lab‐on‐a‐chip devices where advanced sensing technologies generate a large amount of data. Memristive devices are emerging as bioelectronic links merging biosensing with computation, acting as physical processors of analog signals or in the framework of advanced digital computing architectures. Recent developments in the processing of electrical neural signals, as well as on transduction and processing of chemical biomarkers of neural and endocrine functions, are reviewed. It is concluded with a critical perspective on the future applicability of memristive devices as pivotal building blocks in bio‐AI fusion concepts and bionic schemes.

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          Most cited references121

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          The missing memristor found.

          Anyone who ever took an electronics laboratory class will be familiar with the fundamental passive circuit elements: the resistor, the capacitor and the inductor. However, in 1971 Leon Chua reasoned from symmetry arguments that there should be a fourth fundamental element, which he called a memristor (short for memory resistor). Although he showed that such an element has many interesting and valuable circuit properties, until now no one has presented either a useful physical model or an example of a memristor. Here we show, using a simple analytical example, that memristance arises naturally in nanoscale systems in which solid-state electronic and ionic transport are coupled under an external bias voltage. These results serve as the foundation for understanding a wide range of hysteretic current-voltage behaviour observed in many nanoscale electronic devices that involve the motion of charged atomic or molecular species, in particular certain titanium dioxide cross-point switches.
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            Switching the electrical resistance of individual dislocations in single-crystalline SrTiO3.

            The great variability in the electrical properties of multinary oxide materials, ranging from insulating, through semiconducting to metallic behaviour, has given rise to the idea of modulating the electronic properties on a nanometre scale for high-density electronic memory devices. A particularly promising aspect seems to be the ability of perovskites to provide bistable switching of the conductance between non-metallic and metallic behaviour by the application of an appropriate electric field. Here we demonstrate that the switching behaviour is an intrinsic feature of naturally occurring dislocations in single crystals of a prototypical ternary oxide, SrTiO(3). The phenomenon is shown to originate from local modulations of the oxygen content and to be related to the self-doping capability of the early transition metal oxides. Our results show that extended defects, such as dislocations, can act as bistable nanowires and hold technological promise for terabit memory devices.
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              Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing

              Calcium ions play a vital role in enabling synaptic plasticity in biological systems. The dynamic behaviour of these ions has now been emulated in a metal atom diffusion-based memristor.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Advanced Materials
                Advanced Materials
                Wiley
                0935-9648
                1521-4095
                August 2023
                June 29 2023
                August 2023
                : 35
                : 32
                Affiliations
                [1 ] Centre for Microsystems Technology Ghent University–IMEC Ghent 9052 Belgium
                [2 ] Max Planck Institute for Polymer Research 55128 Mainz Germany
                [3 ] NeuroChip Laboratory and Padova Neuroscience Centre University of Padova Padova 35129 Italy
                [4 ] Centre for Electronics Frontiers The University of Edinburgh Edinburgh EH9 3JL UK
                Article
                10.1002/adma.202210035
                ab2fb1da-0f26-49e2-b8ee-20d195f245e9
                © 2023

                http://creativecommons.org/licenses/by/4.0/

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