From the very beginning, the emulation of biological principles has been the primary avenue for the development of energy-efficient artificial intelligence systems. Reservoir computing, which has a solid biological basis, is particularly appealing due to its simplicity and efficiency. So-called memristors, resistive switching elements with complex dynamics, have proved beneficial for replicating both principal parts of a reservoir computing system.
View Article and Find Full Text PDFMemristive devices, known for their nonvolatile resistive switching, are promising components for next-generation neuromorphic computing systems, which mimic the brain's neural architecture. Specifically, these devices are well-suited for functioning as artificial synapses due to their analogue tunability and low energy consumption. However, the improvement of their performance and reliability remains a pressing challenge.
View Article and Find Full Text PDFOrganic-inorganic hybrid materials often face a stability challenge. β-ZnTe(en) , which uniquely has over 15-year real-time degradation data, is taken as a prototype structure to demonstrate an accelerated thermal aging method for assessing the intrinsic and ambient-condition long-term stability of hybrid materials. Micro-Raman spectroscopy is used to investigate the thermal degradation of β-ZnTe(en) in a protected condition and in air by monitoring the temperature dependences of the intrinsic and degradation-product Raman modes.
View Article and Find Full Text PDFAnhydrobiosis, an adaptive ability to withstand complete desiccation, in the nonbiting midge , is associated with the emergence of new multimember gene families, including a group of 27 genes of late embryogenesis abundant (LEA) proteins (). To obtain new insights into the possible functional specialization of these genes, we investigated the expression and localization of genes in a -derived cell line (Pv11), capable of anhydrobiosis. We confirmed that all but two genes identified in the genome of are expressed in Pv11 cells.
View Article and Find Full Text PDFCurrently, there is growing interest in wearable and biocompatible smart computing and information processing systems that are safe for the human body. Memristive devices are promising for solving such problems due to a number of their attractive properties, such as low power consumption, scalability, and the multilevel nature of resistive switching (plasticity). The multilevel plasticity allows memristors to emulate synapses in hardware neuromorphic computing systems (NCSs).
View Article and Find Full Text PDF