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Solid-state ion shuttles are of broad interest in electrochemical devices, nonvolatile memory, neuromorphic computing, and biomimicry utilizing synthetic membranes. Traditional design approaches are primarily based on substitutional doping of dissimilar valent cations in a solid lattice, which has inherent limits on dopant concentration and thereby ionic conductivity. Here, we demonstrate perovskite nickelates as Li-ion shuttles with simultaneous suppression of electronic transport via Mott transition. Electrochemically lithiated SmNiO 3 (Li-SNO) contains a large amount of mobile Li + located in interstitial sites of the perovskite approaching one dopant ion per unit cell. A significant lattice expansion associated with interstitial doping allows for fast Li + conduction with reduced activation energy. We further present a generalization of this approach with results on other rare-earth perovskite nickelates as well as dopants such as Na + . The results highlight the potential of quantum materials and emergent physics in design of ion conductors.

Point defects, such as oxygen vacancies, control the physical properties of complex oxides, relevant in active areas of research from superconductivity to resistive memory to catalysis. In most oxide semiconductors, electrons that are associated with oxygen vacancies occupy the conduction band, leading to an increase in the electrical conductivity. Here we demonstrate, in contrast, that in the correlated-electron perovskite rare-earth nickelates, RNiO(3) (R is a rare-earth element such as Sm or Nd), electrons associated with oxygen vacancies strongly localize, leading to a dramatic decrease in the electrical conductivity by several orders of magnitude. This unusual behavior is found to stem from the combination of crystal field splitting and filling-controlled Mott–Hubbard electron–electron correlations in the Ni 3d orbitals. Furthermore, we show the distribution of oxygen vacancies in NdNiO(3) can be controlled via an electric field, leading to analog resistance switching behavior. This study demonstrates the potential of nickelates as testbeds to better understand emergent physics in oxide heterostructures as well as candidate systems in the emerging fields of artificial intelligence.

Significance Heterojunctions between dissimilar materials provide an opportunity to generate emergent properties not present in their individual components. These properties are often linked to interfacial charge transfer, an important mechanism allowing one to access and control novel quantum states. Here, we have grown unit-cell scale superlattices composed of 5 d S r I r O 3 and 3 d L a N i O 3 . We have discovered a massive interfacial charge transfer from Ir to Ni, triggering dramatic electronic and magnetic reconstructions at the interface that suppress strong spin–orbit coupling effects normally present in the iridates. These findings call for careful evaluation and reinterpretation of experiments on spin–orbit-driven physics in thin films and heterostructures based on prototypical 5 d transition metal oxides.

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmental breathing studies. We implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: A key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment., United States. Army Research Office (Grant W911NF-16-1-0289), United States. Air Force Office of Scientific Research (Grant FA9550-16-1-0159), United States. Army Research Office (Grant W911NF-16-1-0042)

Designing materials to function in harsh environments, such as conductive aqueous media, is a problem of broad interest to a range of technologies, including energy, ocean monitoring and biological applications. The main challenge is to retain the stability and morphology of the material as it interacts dynamically with the surrounding environment. Materials that respond to mild stimuli through collective phase transitions and amplify signals could open up new avenues for sensing. Here we present the discovery of an electric-field-driven, water-mediated reversible phase change in a perovskite-structured nickelate, SmNiO3. This prototypical strongly correlated quantum material is stable in salt water, does not corrode, and allows exchange of protons with the surrounding water at ambient temperature, with the concurrent modification in electrical resistance and optical properties being capable of multi-modal readout. Besides operating both as thermistors and pH sensors, devices made of this material can detect sub-volt electric potentials in salt water. We postulate that such devices could be used in oceanic environments for monitoring electrical signals from various maritime vessels and sea creatures.