Conventional artificial intelligence (AI) systems are facing bottlenecks due to the fundamental mismatches between AI models, which rely on parallel, in-memory, and dynamic computation, and traditional transistors, which have been designed and optimized for sequential logic operations. This calls for the development of novel computing units beyond transistors. Inspired by the high efficiency and adaptability of biological neural networks, computing systems mimicking the capabilities of biological structures are gaining more attention. Ion-based memristive devices (IMDs), owing to the intrinsic functional similarities to their biological counterparts, hold significant promise for implementing emerging neuromorphic learning and computing algorithms. In this article, we review the fundamental mechanisms of IMDs based on ion drift and diffusion to elucidate the origins of their diverse dynamics. We then examine how these mechanisms operate within different materials to enable IMDs with various types of switching behaviors, leading to a wide range of applications, from emulating biological components to realizing specialized computing requirements. Furthermore, we explore the potential for IMDs to be modified and tuned to achieve customized dynamics, which positions them as one of the most promising hardware candidates for executing bioinspired algorithms with unique specifications. Finally, we identify the challenges currently facing IMDs that hinder their widespread usage and highlight emerging research directions that could significantly benefit from incorporating IMDs.

Hierarchically organized three-dimensional (3D) carbon nanotubes/graphene (CNTs/graphene) hybrid nanostructures hold great promises in composite and battery applications. Understanding the junction strength between CNTs and graphene is crucial for utilizing such special nanostructures. Here, in situ pulling an individual CNT bundle out of graphene is carried out for the first time using a nanomechanical tester developed in-house, and the measured junction strength of CNTs/graphene is 2.23 ± 0.56 GPa. The post transmission electron microscopy (TEM) analysis of remained graphene after peeling off CNT forest confirms that the failure during pull-out test occurs at the CNT–graphene junction. Such a carefully designed study makes it possible to better understand the interfacial interactions between CNTs and graphene in the 3D CNTs/graphene nanostructures. The coupled experimental and computational effort suggests that the junction between the CNTs and the graphene layer is likely to be chemically bonded, or at least consisting of a mixture of chemical bonding and van der Waals interactions.

The resistive switching behavior in Ta₂O₅ based memristors is largely controlled by the formation and annihilation of conductive filaments (CFs) that are generated by the migration of oxygen vacancies (OVs). To gain a fundamental insight on the switching characteristics, we have systematically investigated the electrical transport properties of two different Ta₂O₅ polymorphs ( $$\epsilon$$ϵ -Ta₂O₅ and λ-Ta₂O₅), using density functional theory calculations, and associated vacancy induced electrical conductivity using Boltzmann transport theory. The projected band structure and DOS in a few types of OVs, (two-fold (O_2fV), three-fold (O_3fV), interlayer (O_ILV), and distorted octahedral coordinated vacancies (O_εV)) reveal that the presence of O_ILV would cause Ta₂O₅ to transition from a semiconductor to a metal, leading to improved electrical conductivity, whereas the other OV types only create localized mid-gap defect states within the bandgap. On studying the combined effect of OVs and Si-doping, a reduction of the formation energy and creation of defect states near the conduction band edge, is observed in Si-doped Ta₂O₅, and lower energy is found for the OVs near Si atoms, which would be advantageous to the uniformity of CFs produced by OVs. These findings can serve as guidance for further experimental work aimed at enhancing the uniformity and switching properties of resistance switching for Ta₂O₅-based memristors.

Electromechanical, adhesion, and viscoelastic properties of polymers and polymer nanocomposites (PNCs) are of interest for additive manufacturing (AM) and flexible electronics. Development/optimization of inks for AM is complex, expensive, and substrate/interface dependent. This study investigates properties of free standing films of a thermoplastic polyurethane (TPU) polymer and an Ag–carbon black (Ag-CB) TPU PNC in a lightly loaded low strain compression contact as a rough measure of their suitability for AM. The TPU exhibited high hysteresis and a large viscoelastic response, and sufficient dwell time was needed for polymer chain relaxation and measurable adhesion. A new discovery is that large enough contact area is needed to allow longer time constant polymer ordering in the contact that led to higher adhesion and better performance/reliability. This has previously unknown implications for interface size relative to polymer chain length in AM design. The standard linear model was found to be a good fit for the viscoelastic behavior of the TPU. The PNC exhibited no adhesion (new result), low electrical resistance, and relatively small viscoelastic response. This implies potential for AM electrical trace as well as switch applications.

Heterostructures of atomically thin 2D materials could have improved physical, mechanical and chemical properties as compared to its individual components. Here we report, the effect of heterostructure coatings of h BN and MoS ₂ on the corrosion behavior as compared to coatings employing the individual 2D layer compositions. The poor corrosion resistance of MoS ₂ (widely used as wear resistant coating) can be improved by incorporating h BN sheets. Depending on the atomic stacking of the 2D sheets, we can further engineer the corrosion resistance properties of these coatings. A detailed spectroscopy and microscopy analysis has been used to characterize the different combinations of layered coatings. Detailed DFT based calculation reveals that the effect on the electrical properties due to atomic stacking is one of the major reasons for the improvement seen in corrosion resistance.