Catalytic Hydrogen Doping of NdNiO3 Thin Films under Electric Fields

Quantifying Hydrogen Chemical Diffusivity in NdNiO3 Thin Films through Operando Multimodal Measurements

Nickelate oxides show unique properties that make them highly applicable in electrocatalysis, neuromorphic computing, and superconductors. Proton insertion, which effectively tunes their properties, is critical in advancing these applications. Its dynamics is governed by protonation kinetics, mainly controlled by hydrogen chemical diffusivity in nickelates. However, its precise quantification remains a significant knowledge gap, with reported values showing substantial discrepancies and a lack of comprehensive, rigorous methods. In this study, we propose a new quantitative approach that combines operando multimodal measurements. We provide the precise quantification of hydrogen chemical diffusivity in NdNiO3 (NNO), a prototypical nickelate, using rigorous kinetic modeling and cross-validation across multiple data dimensions. Our results reveal that proton mobility in NNO is inherently limited, challenging the assumption of its rapid transport in nickelates. This finding is critical for optimizing proton-based devices and paves the way for further understandings ion dynamics in correlated oxides.

Kelvin Probe Force Microscopy Imaging of Plasticity in Hydrogenated Perovskite Nickelate Multilevel Neuromorphic Devices

Ion drift in nanoscale electronically inhomogeneous semiconductors is among the most important mechanisms being studied for designing neuromorphic computing hardware. However, nondestructive imaging of the ion drift in operando devices directly responsible for multiresistance states and synaptic memory represents a formidable challenge. Here, we present Kelvin probe force microscopy imaging of hydrogen-doped perovskite nickelate device channels subject to high-speed electric field pulses to directly visualize proton distribution by monitoring surface potential changes spatially, which is also supported with finite element-based electric field distribution studies. First-principles calculations provide mechanistic insights into the origin of surface potential changes as a function of hydrogen donor doping that serves as the contrast mechanism. We demonstrate 128 (7-bit) nonvolatile conductance levels in such devices relevant to in-memory computing applications. The synaptic plasticity measurements are implemented in spiking neural networks and show promising results for classification (SciKit Learn's Iris and Wine data sets) and control (OpenAI's CartPole-v1 and BipedalWalker-v3) simulation tasks.

On the Topotactic Phase Transition Achieving Superconducting Infinite-Layer Nickelates

Topotactic reduction is critical to a wealth of phase transitions of current interest, including synthesis of the superconducting nickelate Nd0.8Sr0.2NiO2, reduced from the initial Nd0.8Sr0.2NiO3/SrTiO3 heterostructure. Due to the highly sensitive and often damaging nature of the topotactic reduction, however, only a handful of research groups have been able to reproduce the superconductivity results. A series of in situ synchrotron-based investigations reveal that this is due to the necessary formation of an initial, ultrathin layer at the Nd0.8Sr0.2NiO3 surface that helps to mediate the introduction of hydrogen into the film such that apical oxygens are first removed from the Nd0.8Sr0.2NiO3 / SrTiO3 (001) interface and delivered into the reducing environment. This allows the square-planar / perovskite interface to stabilize and propagate from the bottom to the top of the film without the formation of interphase defects. Importantly, neither geometric rotations in the square planar structure nor significant incorporation of hydrogen within the films is detected, obviating its need for superconductivity. These findings unveil the structural basis underlying the transformation pathway and provide important guidance on achieving the superconducting phase in reduced nickelate systems.

Proton Conducting Neuromorphic Materials and Devices

Neuromorphic computing and artificial intelligence hardware generally aims to emulate features found in biological neural circuit components and to enable the development of energy-efficient machines. In the biological brain, ionic currents and temporal concentration gradients control information flow and storage. It is therefore of interest to examine materials and devices for neuromorphic computing wherein ionic and electronic currents can propagate. Protons being mobile under an external electric field offers a compelling avenue for facilitating biological functionalities in artificial synapses and neurons. In this review, we first highlight the interesting biological analog of protons as neurotransmitters in various animals. We then discuss the experimental approaches and mechanisms of proton doping in various classes of inorganic and organic proton-conducting materials for the advancement of neuromorphic architectures. Since hydrogen is among the lightest of elements, characterization in a solid matrix requires advanced techniques. We review powerful synchrotron-based spectroscopic techniques for characterizing hydrogen doping in various materials as well as complementary scattering techniques to detect hydrogen. First-principles calculations are then discussed as they help provide an understanding of proton migration and electronic structure modification. Outstanding scientific challenges to further our understanding of proton doping and its use in emerging neuromorphic electronics are pointed out.

Hydrogen-induced tunable remanent polarization in a perovskite nickelate

Materials with field-tunable polarization are of broad interest to condensed matter sciences and solid-state device technologies. Here, using hydrogen (H) donor doping, we modify the room temperature metallic phase of a perovskite nickelate NdNiO3 into an insulating phase with both metastable dipolar polarization and space-charge polarization. We then demonstrate transient negative differential capacitance in thin film capacitors. The space-charge polarization caused by long-range movement and trapping of protons dominates when the electric field exceeds the threshold value. First-principles calculations suggest the polarization originates from the polar structure created by H doping. We find that polarization decays within ~1 second which is an interesting temporal regime for neuromorphic computing hardware design, and we implement the transient characteristics in a neural network to demonstrate unsupervised learning. These discoveries open new avenues for designing ferroelectric materials and electrets using light-ion doping.

Infrared Nanoimaging of Hydrogenated Perovskite Nickelate Memristive Devices

Solid-state devices made from correlated oxides, such as perovskite nickelates, are promising for neuromorphic computing by mimicking biological synaptic function. However, comprehending dopant action at the nanoscale poses a formidable challenge to understanding the elementary mechanisms involved. Here, we perform operando infrared nanoimaging of hydrogen-doped correlated perovskite, neodymium nickel oxide (H-NdNiO3, H-NNO), devices and reveal how an applied field perturbs dopant distribution at the nanoscale. This perturbation leads to stripe phases of varying conductivity perpendicular to the applied field, which define the macroscale electrical characteristics of the devices. Hyperspectral nano-FTIR imaging in conjunction with density functional theory calculations unveils a real-space map of multiple vibrational states of H-NNO associated with OH stretching modes and their dependence on the dopant concentration. Moreover, the localization of excess charges induces an out-of-plane lattice expansion in NNO which was confirmed by in situ X-ray diffraction and creates a strain that acts as a barrier against further diffusion. Our results and the techniques presented here hold great potential for the rapidly growing field of memristors and neuromorphic devices wherein nanoscale ion motion is fundamentally responsible for function.

Spatial Interactions in Hydrogenated Perovskite Nickelate Synaptic Networks

A key aspect of how the brain learns and enables decision-making processes is through synaptic interactions. Electrical transmission and communication in a network of synapses are modulated by extracellular fields generated by ionic chemical gradients. Emulating such spatial interactions in synthetic networks can be of potential use for neuromorphic learning and the hardware implementation of artificial intelligence. Here, we demonstrate that in a network of hydrogen-doped perovskite nickelate devices, electric bias across a single junction can tune the coupling strength between the neighboring cells. Electrical transport measurements and spatially resolved diffraction and nanoprobe X-ray and scanning microwave impedance spectroscopic studies suggest that graded proton distribution in the inhomogeneous medium of hydrogen-doped nickelate film enables this behavior. We further demonstrate signal integration through the coupling of various junctions.

Realizing Metastable Cobaltite Perovskite via Proton-Induced Filling of Oxygen Vacancy Channels

The interaction between transition-metal oxides (TMOs) and protons has become a key issue in magneto-ionics and proton-conducting fuel cells. Until now, most investigations on oxide-proton reactions rely on electrochemical tools, while the direct interplay between protons and oxides remains basically at simple dissolution of metal oxides by an acidic solution. In this work, we find classical TMO brownmillerite SrCoO_2.5 (B-SCO) films with ordered oxygen vacancy channels experiencing an interesting transition to a metastable perovskite phase (M-SCO) in a weak acidic solution. M-SCO exhibits a strong ferromagnetism (1.01 μ_B/Co, T_c > 200 K) and a greatly elevated electrical conductivity (∼10⁴ of pristine SrCoO_2.5), which is similar to the prototypical perovskite SrCoO₃. Besides, such M-SCO tends to transform back to B-SCO in a vacuum environment or heating at a relatively low temperature. Two possible mechanisms (H₂O addition/active oxygen filling) have been proposed to explain the phenomenon, and the control experiments demonstrate that the latter mechanism is the dominant process. Our work finds a new way to realize cobaltite perovskite with enhanced magnetoelectric properties and may deepen the understanding of oxide-proton interaction in an aqueous solution.

Template Engineering of Metal-to-Insulator Transitions in Epitaxial Bilayer Nickelate Thin Films

Understanding metal-to-insulator phase transitions in solids has been a keystone not only for discovering novel physical phenomena in condensed matter physics but also for achieving scientific breakthroughs in materials science. In this work, we demonstrate that the transport properties (i.e., resistivity and transition temperature) in the metal-to-insulator transitions of perovskite nickelates are tunable via the epitaxial heterojunctions of LaNiO₃ and NdNiO₃ thin films. A mismatch in the oxygen coordination environment and interfacial octahedral coupling at the oxide heterointerface allows us to realize an exotic phase that is unattainable in the parent compound. With oxygen vacancy formation for strain accommodation, the topmost LaNiO₃ layer in LaNiO₃/NdNiO₃ bilayer thin films is structurally engineered and it electrically undergoes a metal-to-insulator transition that does not appear in metallic LaNiO₃. Modification of the NdNiO₃ template layer thickness provides an additional knob for tailoring the tilting angles of corner-connected NiO₆ octahedra and the linked transport characteristics further. Our approaches can be harnessed to tune physical properties in complex oxides and to realize exotic physical phenomena through oxide thin-film heterostructuring.

Transverse barrier formation by electrical triggering of a metal-to-insulator transition

Application of an electric stimulus to a material with a metal-insulator transition can trigger a large resistance change. Resistive switching from an insulating into a metallic phase, which typically occurs by the formation of a conducting filament parallel to the current flow, is a highly active research topic. Using the magneto-optical Kerr imaging, we found that the opposite type of resistive switching, from a metal into an insulator, occurs in a reciprocal characteristic spatial pattern: the formation of an insulating barrier perpendicular to the driving current. This barrier formation leads to an unusual N-type negative differential resistance in the current-voltage characteristics. We further demonstrate that electrically inducing a transverse barrier enables a unique approach to voltage-controlled magnetism. By triggering the metal-to-insulator resistive switching in a magnetic material, local on/off control of ferromagnetism is achieved using a global voltage bias applied to the whole device.