Search for: All records

Entropic stabilization has evolved into a strategy to create new oxide materials and realize novel functional properties engineered through the alloy composition. Achieving an atomistic understanding of these properties to enable their design, however, has been challenging due to the local compositional and structural disorder that underlies their fundamental structure-property relationships. Here, we combine high-throughput atomistic calculations and linear regression algorithms to investigate the role of local configurational and structural disorder on the thermodynamics of vacancy formation in (MgCoNiCuZn)O-based entropy-stabilized oxides (ESOs) and their influence on the electrical properties. We find that the cation-vacancy formation energies decrease with increasing local tensile strain caused by the deviation of the bond lengths in ESOs from the equilibrium bond length in the binary oxides. The oxygen-vacancy formation strongly depends on structural distortions associated with the local configuration of chemical species. Vacancies in ESOs exhibit deep thermodynamic transition levels that inhibit electrical conduction. By applying the charge-neutrality condition, we determine that the equilibrium concentrations of both oxygen and cation vacancies increase with increasing Cu mole fraction. Our results demonstrate that tuning the local chemistry and associated structural distortions by varying alloy composition acts an engineering principle that enables controlled defect formation in multi-component alloys.

Memristive devices have demonstrated rich switching behaviors that closely resemble synaptic functions and provide a building block to construct efficient neuromorphic systems. It is demonstrated that resistive switching effects are controlled not only by the external field, but also by the dynamics of various internal state variables that facilitate the ionic processes. The internal temperature, for example, works as a second‐state variable to regulate the ion motion and provides the internal timing mechanism for the native implementation of timing‐ and rate‐based learning rules such as spike timing dependent plasticity (STDP). In this work, it is shown that the 2nd state‐variable in a Ta₂O₅‐based memristor, its internal temperature, can be systematically engineered by adjusting the material properties and device structure, leading to tunable STDP characteristics with different time constants. When combined with an artificial post‐synaptic neuron, the 2nd‐order memristor synapses can spontaneously capture the temporal correlation in the input streaming events.

Memristors have emerged as transformative devices to enable neuromorphic and in‐memory computing, where success requires the identification and development of materials that can overcome challenges in retention and device variability. Here, high‐entropy oxide composed of Zr, Hf, Nb, Ta, Mo, and W oxides is first demonstrated as a switching material for valence change memory. This multielement oxide material provides uniform distribution and higher concentration of oxygen vacancies, limiting the stochastic behavior in resistive switching. (Zr, Hf, Nb, Ta, Mo, W) high‐entropy‐oxide‐based memristors manifest the “cocktail effect,” exhibiting comparable retention with HfO₂‐ or Ta₂O₅‐based memristors while also demonstrating the gradual conductance modulation observed in WO₃‐based memristors. The electrical characterization of these high‐entropy‐oxide‐based memristors demonstrates forming‐free operation, low device and cycle variability, gradual conductance modulation, 6‐bit operation, and long retention which are promising for neuromorphic applications.

Advances in the understanding of nanoscale ionic processes in solid‐state thin films have led to the rapid development of devices based on coupled ionic–electronic effects. For example, ion‐driven resistive‐switching (RS) devices have been extensively studied for future memory applications due to their excellent performance in terms of switching speed, endurance, retention, and scalability. Recent studies further suggest that RS devices are more than just resistors with tunable resistance; instead, they exhibit rich and complex internal ionic dynamics that equip them with native information‐processing capabilities, particularly in the temporal domain. RS effects induced by the migration of different types of ions, often driven by an electric field, are discussed. It is shown that, by taking advantage of the different state variables controlled by the ionic processes, important synaptic functions can be faithfully implemented in solid‐state devices and networks. Recent efforts on improving the controllability of ionic processes to optimize device performance are also discussed, along with new opportunities for material design and engineering enabled by the ability to control ionic processes at the atomic scale.