With the demand for low‐power‐operating artificial intelligence systems, bio‐inspired memristor devices exhibit potential in terms of high‐density memory functions and the emulation of the synaptic dynamics of the human brain. The 2D material MXene attracts considerable interest for use in resistive‐switching memory and artificial synapse devices owing to its excellent physicochemical properties in memristor devices. However, few memristive and synaptic MXene devices that display increased switching performances are reported, with no significant results. Herein, the conductivity of MXene (Ti3C2Tx) is engineered via etching and oxidation to enhance the switching performance of the device. The exceptional properties of partially oxidized MXene memristors include large memory windows and low threshold biases, and the complex spike‐timing‐dependent plasticity synaptic rules are also emulated. The low threshold potential distribution, reliable retention time (104 s), and distinct resistance states with a high ON–OFF ratio (>104) are the main memory‐related features of this device. The experimentally determined switching potentials of the optimized device are also uniformly distributed, according to a statistical probability‐based approach. This investigation may promote the essential material properties for use in high‐density non‐volatile memory storage and artificial synapse systems in the field of innovative nanoelectronic devices.

Surface Modification of a Titanium Carbide MXene Memristor to Enhance Memory Window and Low‐Power Operation

https://doi.org/10.1080/14686996.2023.2188878

Emerging memristive neurons for neuromorphic computing and sensing

The development of highly selective and active catalysts to catalyze an industrially important semihydrogenation reaction remains an open challenge. Here, we report the design of a bimetallic Pd/Cu(111) catalyst with Pd rafts confined in a Cu nanosheet, which exhibits desirable catalytic performance for acetylene semihydrogenation to ethylene with the selectivity of >90%. Theory calculations show that Pd atoms replacing neighboring Cu atoms in Cu(111) can improve the catalytic activity by reducing the energy barrier of the semihydrogenation reaction, as compared to unsubstituted Cu(111), and can improve the selectivity by weakening the adsorption of C2H4, as compared to a Pd(111) surface. The presence of Pd rafts confined in Cu nanosheets effectively turns on Cu nanosheets for semihydrogenation of acetylene with high activity and selectivity under mild reaction conditions. This work offers a well-defined nanostructured Pd/Cu(111) model catalyst that bridges the pressure and materials' gap between surface-science catalysis and practical catalysis.

Two-Dimensional Pd Rafts Confined in Copper Nanosheets for Selective Semihydrogenation of Acetylene.

Metal–insulator transition (MIT) coupled with an ultrafast, significant, and reversible resistive change in Mott insulators has attracted tremendous interest for investigation into next‐generation electronic and optoelectronic devices, as well as a fundamental understanding of condensed matter systems. Although the mechanism of MIT in Mott insulators is still controversial, great efforts have been made to understand and modulate MIT behavior for various electronic and optoelectronic applications. In this review, recent progress in the field of nanoelectronics utilizing MIT is highlighted. A brief introduction to the physics of MIT and its underlying mechanisms is begun. After discussing the MIT behaviors of various Mott insulators, recent advances in the design and fabrication of nanoelectronics devices based on MIT, including memories, gas sensors, photodetectors, logic circuits, and artificial neural networks are described. Finally, an outlook on the development and future applications of nanoelectronics utilizing MIT is provided. This review can serve as an overview and a comprehensive understanding of the design of MIT‐based nanoelectronics for future electronic and optoelectronic devices.

Nanoelectronics Using Metal-Insulator Transition.

The burgeoning of artificial intelligence has brought great convenience to people’s lives as large-scale computational models have emerged. Artificial intelligence-related applications, such as autonomous driving, medical diagnosis, and speech recognition, have experienced remarkable progress in recent years; however, such systems require vast amounts of data for accurate inference and reliable performance, presenting challenges in both speed and power consumption. Neuromorphic computing based on photonic integrated circuits (PICs) is currently a subject of interest to achieve high-speed, energy-efficient, and low-latency data processing to alleviate some of these challenges. Herein, we present an overview of the current photonic platforms available, the materials which have the potential to be integrated with PICs to achieve further performance, and recent progress in hybrid devices for neuromorphic computing. 

Hybrid photonic integrated circuits for neuromorphic computing

Future-generation neuromorphic computing seeks to overcome the limitations of von Neumann architectures by co-locating logic and memory functions, thereby emulating the function of neurons and synapses in the human brain. Despite remarkable demonstrations of high-fidelity neuronal emulation, the predictive design of neuromorphic circuits starting from knowledge of material transformations remains challenging. VO2 is an attractive candidate since it manifests a near-room-temperature, discontinuous, and hysteretic metal-insulator transition. The transition provides a nonlinear dynamical response to input signals, as needed to construct neuronal circuit elements. We discuss strategies for tuning the transformation characteristics of VO2 based on modification of material properties, interfacial structure, and field couplings. Dynamical modulation of transformation characteristics through in-situ material processing is discussed as a means of imbuing synaptic function. We emphasize mechanistic understanding of site-selective modification; external, epitaxial, and chemical strain; defect dynamics; and interfacial field coupling in modifying local atomistic structure, the implications therein for electronic structure, and ultimately, the tuning of transformation characteristics. We highlight opportunities for inverse design and for using design principles related to thermodynamics and kinetics of electronic transitions learned from VO2 to inform the design of new Mott materials, as well as to go beyond energy-efficient computation to manifest intelligence. This article is protected by copyright. All rights reserved.

Harnessing the Metal-Insulator Transition of VO2 in Neuromorphic Computing.

The development of electrical insulators that are thermally conducting is critical for thermal management applications in many advanced electronics and electrical devices. Here, we synthesized polymer nanocomposite (PNC) films composed of polymers [polyethylenimine, poly(vinylamine), poly(acrylic acid), and poly(ethylene oxide)] and dielectric fillers (montmorillonite clay and hexagonal boron nitride) by layer-by-layer technique. The cross-plane thermal conductivity [Formula: see text] of the film was measured by the 3ω method. The effect of various factors such as film growth, filler type, filler volume fraction, polymer chemical structures, and temperature on the thermal conductivity is reported. The [Formula: see text] of PNCs with thickness from 37 nm to 1.34  μm was found to be in the range of 0.11 to 0.21 ± 0.02 W m−1 K−1. The [Formula: see text] values were found to be lower than the constituent polymer matrix. The experimental result is compared with existing theoretical models of nanocomposite systems to get insight into heat transfer behavior in such layered films composed of dielectrics and polymers.

Thermal conductivity of multilayer polymer-nanocomposite thin films

Negative differential resistance (NDR) in certain materials has been attributed to spontaneous emergence of symmetry-breaking electrical current density localization from a previously homogeneous distribution, which is postulated to occur due to the nonequilibrium thermodynamic force of minimization of entropy production. However, this phenomenon has not been quantitatively predicted based on intrinsic material properties and an applied electrical stimulus. Herein an instability criterion is derived for localization of current density and temperature from a thermal fluctuation in a parallel conductor model of a thin film that is subject to Newton's law of cooling. The conditions for steady–state electro-thermal localization is predicted, verifying a decrease in entropy production upon localization. Electro-thermal localization accompanied by a decrease of entropy production is confirmed in a multiphysics simulation of current flow in a thin film. The instability criterion predicts conditions for spontaneous current density localization, relating symmetry breaking fundamentally to dynamical instability via Local Activity theory. 

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/aelm.202300265

Spontaneous Symmetry‐Breaking of Nonequilibrium Steady–States Caused by Nonlinear Electrical Transport

A series of PdCu bimetallic catalysts with low Cu and Pd loadings and different Cu: Pd atomic ratios were prepared by conventionally sequential impregnation (CSI) and modified sequential impregnation (MSI) of Cu and Pd for selective hydrogenation of acetylene. Characterization indicates that the supported copper (II) nitrate in the PdCu bimetallic catalysts prepared by MSI can be directly reduced to Cu metal particles due to the hydrogen spillover from Pd to Cu(NO3)2 crystals. In addition, for the catalysts prepared by MSI, Pd atoms can form PdCu alloy on the surface of metal particles, however, for the catalysts prepared by CSI, Pd tends to migrate and exist below the surface layer of Cu. Reaction results indicate that compared with CSI, the MSI method enables samples to possess preferable stability as well as comparable reaction activity. This should be due to the MSI method in favor of the formation of PdCu alloy on the surface of metal particles. Moreover, even Pd loading is super low, < 0.045 wt-% in this study, by through adjusting Cu loading to an appropriate value, attractive reactivity and selectivity still can be achieved.

Preparation and investigation of Pd doped Cu catalysts for selective hydrogenation of acetylene

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Papers

Harnessing the Metal-Insulator Transition of VO2 in Neuromorphic Computing.

Thermal conductivity of multilayer polymer-nanocomposite thin films

Spontaneous Symmetry‐Breaking of Nonequilibrium Steady–States Caused by Nonlinear Electrical Transport

Preparation and investigation of Pd doped Cu catalysts for selective hydrogenation of acetylene