(Nature Comm. 11, 1861 (2020))
Memristive devices are promising candidates to emulate biological computing. However, the typical switching voltages (0.2-2 V) in previously described devices are much higher than the amplitude in biological counterparts. We developed a type of diffusive memristor, fabricated from the protein nanowires harvested from the bacterium Geobacter sulfurreducens, that functions at the biological voltages of 40-100 mV. Memristive function at biological voltages is possible because the protein nanowires catalyze metallization. Artificial neurons built from these memristors not only function at biological action potentials (e.g., 100 mV, 1 ms) but also exhibit temporal integration close to that in biological neurons.
(Nature Comm. 12, 3351 (2021))
Incorporating neuromorphic electronics in bioelectronic interfaces can provide intelligent responsiveness to environments. However, the signal mismatch between the environmental stimuli and driving amplitude in neuromorphic devices has limited the functional versatility and energy sustainability. we demonstrate multifunctional, self-sustained neuromorphic interfaces by achieving signal matching at the biological level. The advances rely on the unique properties of microbially produced protein nanowires, which enable both bio-amplitude (e.g., <100 mV) signal processing and energy harvesting from ambient humidity. Integrating protein nanowire-based sensors, energy devices and memristors of bio-amplitude functions yields flexible, self-powered neuromorphic interfaces that can intelligently interpret biologically relevant stimuli for smart responses.
(Adv. Mater. 202207133 (2022))
Efficient strategy for addressing individual devices is required to unveil the full potential of memristors for high-density memory and computing applications. Existing strategies using two-terminal selectors that are preferable for compact integration have trade-offs in reduced generality or functional window. We propose a strategy that applies to broad memristors and maintains their full-range functional window. The strategy uses a type of unipolar switch featuring a transient relaxation or retention as the selector. The unidirectional current flow in the switch suppresses the sneak-path current, whereas the transient-relaxation window is exploited for bidirectional programming. A unipolar volatile memristor of ultralow switching voltage (e.g., <100 mV), constructed from protein nanowire dielectric harvested from Geobacter sulfurreducens, is specifically employed as the exemplary switch to highlight the advantage and scalability in the strategy for array integration.
(Device, 2, 100329 (2024))
The transistor is broadly used to address memristor networks, but its three-terminal structure can impose limitations on fully exploiting the potential of efficient integration that a two-terminal memristor can offer. While a two-terminal selector is desirable for unlocking this potential, no existing device has attained a similar level of functional maturity. The diode, despite its technological maturity, is still limited by its unipolarity in addressing mainstream bipolar memristors. Here, we demonstrate that a diode can be implemented as a bidirectional selector for constructing two-terminal memristor architecture by exploiting its reverse recovery dynamics. This is demonstrated by the construction of one-diode-one-memristor (1D1R) programmable arrays, which are implemented for in situ neural training and classification. Furthermore, a crossbar array made from stacking 1D1R cells is fabricated to demonstrate scalable integration. This dynamic paradigm combines the advantages of functional maturity and structural simplicity of diode selectors to improve the development of memristor integration.