RESUMEN
Tetrahydropyran and tetrahydropyran-fused poly-ethers scaffolds are found in many classes of natural products and medicinally relevant small molecules. Here we describe a catalytic system for 6-endo selective ring-opening of epoxides by Au(I) or Au(III) catalyst that provides rapid access to various tetrahydropyran-derived motifs. It also could efficiently construct the subunits of marine ladder-like poly-ethers through emulating the Nakanishi's hypothesis on the biosynthesis of these toxins. The synthetic utility of this method is also demonstrated in the preparation of the tricyclic core of tetrahydropyran-containing macrolide natural products lituarines A-C.
RESUMEN
Ferroelectric, phase-change, and magnetic materials are considered promising candidates for advanced memory devices. Under the development dilemma of traditional silicon-based memory devices, ferroelectric materials stand out due to their unique polarization properties and diverse manufacturing techniques. On the occasion of the 100th anniversary of the birth of ferroelectricity, scandium-doped aluminum nitride, which is a different wurtzite structure, was reported to be ferroelectric with a larger coercive, remanent polarization, curie temperature, and a more stable ferroelectric phase. The inherent advantages have attracted widespread attention, promising better performance when used as data storage materials and better meeting the needs of the development of the information age. In this paper, we start from the characteristics and development history of ferroelectric materials, mainly focusing on the characteristics, preparation, and applications in memory devices of ferroelectric wurtzite AlScN. It compares and analyzes the unique advantages of AlScN-based memory devices, aiming to lay a theoretical foundation for the development of advanced memory devices in the future.
RESUMEN
Biomolecular materials offer tremendous potential for the development of memristive devices due to their low cost of production, environmental friendliness, and, most notably, biocompatibility. Herein, biocompatible memristive devices based on amyloid-gold nanoparticle hybrids have been investigated. These memristors demonstrate excellent electrical performance, featuring an ultrahigh Roff/Ron ratio (>107), a low switching voltage (<0.8 V), and reliable reproducibility. Additionally, the reversible transition from threshold switching to resistive switching mode was achieved in this work. The arrangement of peptides in amyloid fibrils endows the surface polarity and phenylalanine packing, which provides channels for the migration of Ag ions in the memristors. By modulating voltage pulse signals, the study successfully imitates the synaptic behavior of excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and the transition from short-term plasticity (STP) to long-term plasticity (LTP). More interestingly, Boolean logic standard cells were designed and simulated using the memristive devices. The fundamental and experimental results of this study thus offer insights into the utilization of biomolecular materials for advanced memristive devices.
RESUMEN
Artificial synapses and neurons are two critical, fundamental bricks for constructing hardware neural networks. Owing to its high-density integration, outstanding nonlinearity, and modulated plasticity, memristors have attracted emerging attention on emulating biological synapses and neurons. However, fabricating a low-power and robust memristor-based artificial neuron without extra electrical components is still a challenge for brain-inspired systems. In this work, we demonstrate a single two-dimensional (2D) MXene(V2C)-based threshold switching (TS) memristor to emulate a leaky integrate-and-fire (LIF) neuron without auxiliary circuits, originating from the Ag diffusion-based filamentary mechanism. Moreover, our V2C-based artificial neurons faithfully achieve multiple neural functions including leaky integration, threshold-driven fire, self-relaxation, and linear strength-modulated spike frequency characteristics. This work demonstrates that three-atom-type MXene (e.g., V2C) memristors may provide an efficient method to construct the hardware neuromorphic computing systems.