Solid-state electrolytes hold great promise for advancing electrochemical energy storage devices. Advanced batteries based on solid electrolytes, particularly all-solid-state lithium-metal batteries, hold the potential to simultaneously address both high energy density and safety concerns associated with traditional lithium-ion batteries. Ideally, solid electrolytes should exhibit a high ionic conductivity at room temperature. In practical applications, other properties, such as electrochemical stability and compatibility with electrodes, are equally important. However, the pursuit of a single solid electrolyte possessing all of these properties remains challenging. Simulation techniques play an important role in the design of solid electrolyte materials, bypassing the difficulty of chemical synthesis and structural characterization. In these simulations, ionic conduction within bulk electrolytes and the ion deposition and stripping processes at the charged electrode–electrolyte interface can be investigated. By providing the flexibility to construct electrolyte models and explore structural evolution at multiple scales, simulation techniques facilitate the rational design of advanced solid electrolytes that maximizes their advantages and mitigates limitations. This account is initiated by introducing fundamental theories and simulation techniques to investigate the ionic conductivity of an inorganic solid electrolyte. Subsequently, we present our recent progress in designing high ionic conductivity electrolytes by increasing the concentration of Li vacancies, by tuning the type of defects, by constructing diffusion pathways, and by avoiding ion crowding. At last, the electrochemical stability of inorganic solid electrolytes and their compatibility with lithium-metal electrodes are addressed.

In bulk electrolytes, increasing the defect concentration can often enhance the ionic conductivity. For instance, to surpass the upper limit of Li vacancy concentration without compromising structural stability, we adopt an antispinel crystal structure, enhancing Li mobility within the Li₃OBr electrolyte. The type of defects also matters. Instead of O doping, we propose to introduce Li interstitials effectively through S doping, significantly reducing lattice distortion and eliminating the anchoring effect of Li around the O dopant. Compared to the electrolyte with vacancy defects, introducing Li interstitials boosts the ionic conductivity of Li₃OCl by 3 orders of magnitude. In addition to defect engineering, designing a three-dimensional diffusion pathway for Li ions enhances bulk ionic conductivity. While LaCl₃-based electrolytes exhibit good compatibility with Li-metal electrodes, their intrinsic low ionic conductivity poses limitations. We propose constructing a three-dimensional diffusion pathway by connecting neighboring one-dimensional channels through the introduction of La vacancies, significantly enhancing the ionic conductivity of LaCl₃-based electrolytes at room temperature. Furthermore, we investigate ion diffusion in the space charge layer (SCL) near charged solid interfaces. We observe that the mobility of Li interstitials in the SCL is close to that of Li vacancies in bulk electrolytes. However, a defect-deficient region within the SCL may induce high ionic resistance. These studies demonstrate that material design based on simulation techniques offers promise for the development of solid electrolytes and the advancement of electrochemical energy storage devices.

Electronic medicines represent a class of biomedical technology that exploits electrical impulses to achieve diagnostic and therapeutic purposes. They allow patients to identify their physiological conditions themselves through effortless diagnosis methods, no longer confining treatment solely to medical examinations by physicians. Their clinical practices also operate as an alternative therapeutic approach to pharmacological interventions, wherein the electrical impulses are directly administered to biological tissues with minimal adverse effects. However, unlike wearable electronic medicines that offer the convenient replacement of their energy storages, medical implants require surgical removal for recharging energy storages, thereby imposing substantial physical and psychological burdens on patients. To address these challenges, many efforts are widely conducted to develop self-powered medical implants by utilizing energy harvesting technologies to extend the lifetime of energy storages.

Compared to their applications in wearable devices, energy harvesting technologies for powering implantable electronics encounter technical constraints, because the human body exhibits the limited depth penetration of light sources and hemostasis reactions on body temperature. Triboelectric energy harvesting technologies have been highlighted as a promising energy solution of medical implants, exploiting diverse mechanical energy sources to generate electrical energy in vivo. Benefitting from the simple device structure favorable for device miniaturization, triboelectric nanogenerators (TENGs) are extensively explored. Herein, we introduce self-powered medical implants driven by the triboelectric mechanism, providing an exposition on their recent research trends. First, we describe the varying device structures and energy generation performances of TENGs, upon their mechanical energy sources with various frequency ranges. Most devices powered by high-frequency energy sources exhibit superior electrical output performances compared to those powered by low-frequency energy sources. However, the current status indicates that these energy solutions still fall short of meeting the energy consumption demands for their instantaneous application in commercialized electronic medicines. As potential solutions to meet the energy consumption demand, we describe material design strategies to aim for high output performance of triboelectric nanogenerators. Beyond their conventional role as mere power supplies for commercialized medical implants, battery-less electronic medicines based on TENGs hold the great potential for diverse clinical applications. This Account also presents our previous studies of self-powered electronic medicines to carry out clinical practices such as wound healing, tissue engineering, neurostimulation, neuroregeneration, and antibacterial activity. Lastly, we illustrate advanced technologies in materials and devices design with their applicability based on the implantation sites and clinical timeline of self-powered electronic medicines. We anticipate that this Account, by sharing our insights, will contribute to the future generation of outstanding achievements for potential readers engaged in the fields of bioelectronics, self-powered systems, and biomedical engineering.

In the realm of high-frequency sensing technology, the revolutionary integration and modification of novel materials such as metal–organic frameworks (MOFs), graphene, MXene, carbon nanotubes, and other advanced nanostructured materials have significantly propelled the field forward. These materials have not only broadened the scope of applications but have also markedly enhanced the capabilities of high-frequency sensors. Despite these advancements, a notable gap remains in fully understanding the relationship between the intricate structural properties of these materials and their impact on sensor performance, particularly in high-frequency contexts. Our comprehensive account seeks to bridge this gap by thoroughly analyzing the underpinning mechanisms of materials-based high-frequency sensor technology. We focus on the unique structural, electromagnetic, and surface properties of these innovative materials, emphasizing the customizable porosity and high surface area of MOFs and their influence on sensing capabilities. This Account highlights the importance of polarization theory and the strategic tailoring of materials such as MOFs, which have demonstrated potential in enhancing sensor specificity and sensitivity. Through detailed case studies and analytical explorations, we establish comprehensive guidelines for material selection in the design of high-frequency sensors. This process involves a careful consideration of target substances and specific application scenarios to ensure optimal material compatibility and performance. Additionally, we explore the significant impact of nano- and microlevel modifications in materials like MOFs on sensor characteristics, particularly in enhancing sensitivity, selectivity, and response time. The objective of our account is to elucidate the critical role that advanced materials play in the development of high-frequency sensing technology. We delve into the promising future of materials customization in high-frequency sensing, with a focus on materials that exhibit high electromagnetic properties and specialized surface characteristics. The adaptation of materials from 0D to 3D offers unique opportunities for microstructural modifications tailored to the molecular diameter of target materials, paving the way for optimal sensing system performance. This Account provides a clear and comprehensive perspective on the latest advancements and future research directions in this field. We aim to guide researchers and industry practitioners in selecting and engineering materials for superior performance in high-frequency sensing applications. By highlighting innovative research strategies and contributing to the continuous evolution of high-frequency sensing technology, our work opens new avenues for applications such as wireless transmission systems and precision biomedical monitoring. This endeavor not only pushes the boundaries of current sensing capabilities but also sets the stage for groundbreaking developments in the field of high-frequency sensing.

Rechargeable lithium-ion batteries (LIBs) are currently the most popular energy storage devices. However, the essential elements for commercial LIBs, i.e., lithium, cobalt, and nickel, are scarce, leading to an increase in cost, which together with the environmental concerns results in concern for future energy storage and calls for large-scale post-LIBs, including Na-, K-, Ca-, Mg-, Zn-, Al-, and dual-ion batteries. However, these post-LIBs are facing challenges in storage of either large-sized (Na-, K-, Ca-ions, anions) or high-charge-density multivalent (Ca-, Mg-, Zn-, Al-) metal ions. The large ionic sizes will inevitably result in the sluggish ionic diffusion, difficulty in storage, enormous volume variation, pulverization, low capacity, and poor cyclability. While the high charge/radius ratio of multivalent ions leads to strong electrostatic interactions with solvent molecules and electrode lattice, strong solvation, high desolvation energy, possible storage of complex ions, sluggish ionic diffusion and reaction kinetics, low actual capacity, and poor rate capability and cyclability.

From this point of view, redox-active organic electrode materials (OEMs) are promising for these post-LIBs. OEMs can be easily synthesized from natural resources, which could meet the low-cost requirements for large-scale applications. Another advantage of OEMs is that the electrochemical performance could be facilely tuned through molecular design. High specific capacity could be expected, surpassing inorganic materials with intercalation chemistry. More importantly, organic materials have the merits of flexibility, which makes it intriguing for storage of large-sized ions with fast kinetics, and relatively small volume variation compared with inorganic electrode materials. In addition, organic/polymeric materials are composed by molecules via weak intermolecular interactions and hence should be suitable for storage of multivalent metal ions with reduced electrostatic interactions. In the past two decades, various OEMs have been reported with decent electrochemical performance for both LIBs and post-LIBs. However, they are still facing a lot of challenges, and effective strategies to enhance the performance of organic batteries are scarce.

In the past few years, it has also been found that the storage of ions may lead to chelation with the OEMs when the OEMs have multiple active sites for improving the theoretical capacity or substituents for enhancing the intermolecular interactions. Later, we found that the intentional design of adjacent functional groups for chelation could enhance the storage of ions. In this Account, we first give an overview of challenges faced by post-LIBs and then propose a strategy to boost the storage of large-sized or multivalent metal ions by promoting chelation with stored ions, based on the recent works from our group and others. The findings on chelation with both Li ions and other monovalent and multivalent metal ions are summarized. We hope this Account could stimulate further research on molecular design through chelation to enhance the performance of organic batteries.

Polymeric material research is encountering a new paradigm driven by machine learning (ML) and big data. The ML-assisted design has proven to be a successful approach for designing novel high-performance polymeric materials. This goal is mainly achieved through the following procedure: structure representation and database construction, establishment of a ML-based property prediction model, virtual design and high-throughput screening. The key to this approach lies in training ML models that delineate structure–property relationships based on available polymer data (e.g., structure, component, and property data), enabling the screening of promising polymers that satisfy the targeted property requirements. However, the relative scarcity of high-quality polymer data and the complex polymeric multiscale structure–property relationships pose challenges for this ML-assisted design method, such as data and modeling challenges.

In this Account, we summarize the state-of-the-art advancements concerning the ML-assisted design of polymeric materials. Regarding structure representation and database construction, the digital representations of polymers are the predominant methods in cheminformatics along with some newly developed methods that integrate the polymeric multiscale structure characteristics. When establishing a ML-based property prediction model, the key is choosing and optimizing ML models to attain high-precision predictions across a vast chemical structure space. Advanced ML algorithms, such as transfer learning and multitask learning, have been utilized to address the data and modeling challenges. During the ML-assisted screening process, by defining and combining polymer genes, virtual polymer candidates are generated, and subsequently, their properties are predicted and high-throughput screened using ML property prediction models. Finally, the promising polymers identified through this approach are verified by computer simulations and experiments.

We provide an overview of our recent efforts toward developing ML-assisted design approaches for discovering advanced polymeric materials and emphasize the intricate nature of polymer structural design. To well describe the multiscale structures of polymers, new structure representation methods, such as polymer fingerprint and cross-linking descriptors, were developed. Moreover, a multifidelity learning method was proposed to leverage the multisource isomerous polymer data from experiments and simulations. Additionally, graph neural networks and Bayesian optimization methods have been developed and applied for predicting polymer properties as well as designing polymer structures and compositions.

Finally, we identify the current challenges and point out the development directions in this emerging field. It is highly desirable to establish new structure representation and advanced ML modeling methods for polymeric materials, particularly when constructing polymer large models based on chemical language. Through this Account, we seek to stimulate further interest and foster active collaborations for developing ML-assisted design approaches and realizing the innovation of advanced polymeric materials.

Heterogeneous Fenton-like reaction is a promising process for refractory wastewater treatment. Among the various heterogeneous Fenton-like catalysts, Prussian blue (PB) and Prussian blue analogues (PBAs) show great potential for hydrogen peroxide and persulfate activation owing to their low toxicity, simple preparation, and high activity. To further improve the catalytic activity of PBAs and their derivatives (PBDs), many efforts have been made to overcome the instability of the crystal structure and develop feasible methodologies to prepare PBAs/PBDs with diverse morphologies and compositions. In this Account, our recent achievements on novel synthetic strategies to obtain PBAs/PBDs with controlled morphologies, geometric sites, and electronic structures were systematically summarized. The physicochemical properties of the PBAs/PBDs and their contribution to the catalytic reaction in the advanced oxidation processes (AOPs) were also discussed.

First, we focus on developing a novel synthesis technology (such as “copolymer-co-morphology” conception) of PBAs with controllable morphology. By regulating the chelating agents, surfactants, metal ions, and preparation conditions and constructing a heterojunction, the stability of PBAs/PBDs was significantly improved to overcome their instability during redox reaction. Notably, to inherit the characteristics of PBAs, a topological transformation strategy was applied to fabricate metal oxides with morphologies similar to those of PBAs through thermal calcination under an aerobic atmosphere. Subsequently, this strategy has been extensively applied to prepare single-atom catalysts, metal nitrides, and zerovalent metals via thermal treatment under inert/reducing atmospheres. These novel strategies provide guidance for devising controllable PBAs/PBDs materials with superior activity and stability during cycling tests not only in Fenton-like reactions but also in other catalytic systems. In addition to the physicochemical property optimization, the relationship between the deliberately designed electronic structure and the catalytic activity of PBAs/PBDs was first explored in depth using ⁵⁷Fe Mössbauer spectroscopy. Moreover, benefiting from these efficient techniques and conscientious explorations, our research not only elucidated the important descriptors for the intrinsic oxidation pathways but also revealed the significant effect of external energy (ultraviolet and visible light) on the catalytic pathways in PBAs/PBDs-dominant Fenton-like systems. These findings provide a novel inspiration for further application of additional energy. Finally, the recent challenges and development prospects of PBAs/PBDs in AOPs are comprehensively discussed. Overall, this Account provides comprehensive insights into PBAs/PBDs fabrication strategies, physicochemical properties, local electronic structures, and the intrinsic correlation between these characteristics and catalytic mechanisms using advanced analysis techniques and paves the way for the future development of PBAs/PBDs in various catalysis fields.

Optical biomedical imaging offers unparalleled advantages in biological research, enabling precise visualization of physiological and pathological processes with exceptional sensitivity and specificity. Its noninvasive nature, high signal-to-noise ratio (SNR), and the ability to target specific molecules make it an indispensable tool for studying dynamic events within living organisms. This technology advances our understanding of life processes, provides crucial insights into disease mechanisms, and fosters breakthroughs in both medicine and biological sciences. Recently, the newly developed fluorescence imaging in the second near-infrared (NIR-II, 1000–1700 nm) window represents a significant advancement in biomedical imaging, which offers distinct advantages, such as deeper tissue penetration and higher spatiotemporal resolution over conventional imaging techniques in the well-established visible and traditional near-infrared (400–900 nm) region, resulting in clearer and more detailed images of biological structures and processes. Moreover, NIR-II fluorescence imaging exhibits minimal background interference, enhancing sensitivity and specificity in detecting molecular targets. These characteristics make NIR-II fluorescence imaging a promising tool for various biomedical applications, including tumor detection, drug delivery monitoring, and in vivo imaging of biological processes. Its potential to provide high-resolution, real-time imaging with improved sensitivity holds great promise for advancing both basic research and clinical diagnostics in the field of biomedicine. Up to now, functional NIR-II materials including small molecular dyes, polymers, single-walled carbon nanotubes, quantum dots, lanthanide nanoparticles, and coordination complex have gradually enriched the toolbox for high performance in vivo visualization of physiological structures and abnormal diseases. Although the diverse NIR-II materials differ in component, size, and surface, their optical properties confer them with multifunctional capability from imaging, sensing to phototheranostics.

In this Account, we highlight the recent contributions of our research group in utilizing NIR-II materials for enhanced biomedical performance. First, we summarize our efforts on the repurposing of commercially available NIR dyes for NIR-II imaging using their emission tail. Protein and fragments further shield the dyes for improved imaging performance and adjustable pharmacokinetics. Then, we discuss the application of the contrast agent in image-guided tumor precision surgery. After that, we present a series of responsive NIR-II materials for real-time visualization of in vivo tumor microenvironment before and after therapy. We also conclude the NIR-II materials with photon energy conversion capability for phototheranostics. Finally, we propose an outlook on the possible issues and future development of this field for improved biomedical applications. We hope this Account can update the understanding of recently developed multifunctional NIR-II materials, providing some references, and promoting more adoption to accelerate the development of material science and biomedical applications.

Graphite and diamond, two naturally occurring carbon allotropes, have been extensively exploited for millennia. However, it was not until the mid-20th century that scientists successfully synthesized diamonds using the phase transformation of graphite under high pressure and high temperature. Understanding the mechanism of direct phase transformation from graphite to diamond is of great scientific and practical significance and has stimulated extensive interest and efforts. Although the concerted transformation mechanism and nucleation-and-growth mechanism proposed theoretically are helpful for the understanding of phase transformations, they fail to account for the diffraction peak of so-called “compressed graphite” observed at ∼3.1 Å in partially transformed samples. Recently, we proposed a new mechanism called motif propagation mechanism by combining electron microscopy observation and theoretical simulation. It solves the long-standing puzzle of how graphite transforms into diamond. Within the motif propagation mechanism, the formation of diamond motifs initially begins with the connection of two carbon six-membered rings belonging to adjacent graphite layers; then, the motifs gradually advance toward the graphite region along the graphite–diamond coherent interface, thereby achieving the transformation from graphite to diamond. Our results demonstrate that graphite is not completely transformed into diamond at once but first transforms into an intermediate structure, namely a graphite–diamond hybrid (called Gradia). Then, Gradia gradually transforms into diamond. Gradia, a metastable carbon form, can be quenched to ambient conditions and exists stably. The diffraction peaks of Gradia include those of both diamond and so-called compressed graphite, which match well with the diffraction peaks of intermediate products determined in experiments. In this Account, we provide a comprehensive overview of the concerted transformation mechanism, the nucleation-and-growth mechanism, and the motif propagation mechanism as well as the discovery of Gradia. Gradia represents a new form of carbon with excellent mechanical properties, such as superhigh hardness and toughness, and adjustable electrical properties. In Gradia, the proportion of graphite and diamond domains as well as interface types can be tailored, which opens up promising opportunities for nanostructure engineering to achieve the desired properties that are inaccessible to diamond and graphite alone. The discovery of Gradia also holds significant implications for previously unresolved scientific mysteries, such as the formation mechanism of “cold-compressed graphite”, diamond graphitization, and the phase transformation of boron nitride (BN), known as the twin brother of carbon. Gradia-BN is expected to be synthesized, which may possess excellent thermal stability and chemical inertness, superior hardness and toughness, and unique electronic properties.

The petrochemical industry plays a pivotal role in the manufacturing process of petrochemical products by transforming crude oil into monomers of synthetic polymers used to produce a wide range of commercial products. However, the generation of elemental sulfur, a significant byproduct of the petroleum refining process, has raised substantial environmental concerns as the volume of petroleum refining is increasing to meet rapidly growing energy consumption and demand for petrochemical products. Due to hydrodesulfurization, 7 million tons of elemental sulfur is produced as an annual surplus, which exceeds the amount used for rubber vulcanization, fertilizer production, and sulfuric acid manufacturing. If, however, we can upcycle this abundant resource for high-value applications, the mass production of high-purity elemental sulfur might provide huge economic benefits. In 2013, the first successful research study in synthesizing sulfur-rich polymers (SRPs) with a high sulfur content of up to 90 wt % was reported, employing inverse vulcanization. Unlike carbon-based polymers, SRPs demonstrate remarkable infrared (IR) transparency, which allows us to usher in a new era of polymer-based IR optics. Furthermore, SRPs also show high potential as sustainable and high-performance triboelectric materials due to the highest electron affinity of elemental sulfur excluding halogen atoms. Hence, SRPs have garnered significant interest in practical applications, such as IR thermal imaging and triboelectric energy harvesting.

In this Account, we highlight our recent progress in upcycling SRPs into the aforementioned practical applications, such as IR polarizers and triboelectric nanogenerators (TENG) toward value-addition of elemental sulfur. First, we will discuss strategies to enhance thermo-mechanical properties of SRPs such as the glass transition temperature (T_g), cross-linking density, and elastic modulus without significant deterioration of IR transparency. Despite these unique advantages, SRPs often suffer from low thermo-mechanical properties, limiting durability and robustness for practical applications. Although numerous research efforts have been devoted to identifying optimal comonomers during the inverse vulcanization process, addressing these issues remains a focus for ongoing investigation. Then, we will explain the strategy to achieve a high-performance IR polarizer in terms of nanoscaled manufacturing. Most studies related to SRPs in the context of IR optics focus on preparing IR windows which are typically utilized as a protective layer of thermal imaging systems. Hence, for value-addition of SRPs, it can be an effective strategy to directly prepare nanostructured SRPs for the IR polarizer. In the last section, we look beyond IR-related applications to introduce new advances for SRPs in sustainable and high-performance triboelectric energy harvesting. We focus on achieving a highly charged surface of SRP film by considering rational design based on electron affinity and hypervalency of sulfur and structural design via microphase separation in the polymer blend system. Finally, we outline the current state, limitations, and future direction to realize true sustainability in the process toward value addition of SRPs.

Negative gas adsorption (NGA) is a particularly eye-catching phenomenon, involving the spontaneous desorption of gas upon pressure increase during adsorption in a flexible nanoporous material. The material undergoes a structural transition from an “open-pore” phase to a contracted “closed-pore” phase upon gas adsorption, leading to macroscopic gas desorption visible to the naked eye. It was initially evidenced experimentally in 2016 for the adsorption of methane and n-butane in the DUT-49 metal–organic framework (DUT = Dresden University of Technology) and later demonstrated to be a general phenomenon, occurring for different gases and in a variety of materials with the same topology. NGA materials belong to the category of metamaterials, displaying behavior that is not found (or rarely observed) in “natural” or simple materials. The negative adsorption transition takes place outside of thermodynamic equilibrium, and its characterization requires the use of many complementary experimental techniques (adsorption measurements, in situ X-ray diffraction, EXAFS, NMR, etc.), as well as molecular simulation techniques. In order to obtain a full and consistent picture of the NGA phenomenon, it is indeed necessary to combine computational modeling with a variety of methods, at different scales, in order to understand the microscopic behavior of the host framework and guest molecules to the macroscopic experimental results. At the smallest scale, density functional theory calculations have been used to understand the energetics and structure of the NGA materials, as well as the micromechanical properties of their organic linkers: the buckling of these linkers explains the large metastability of the open-pore phase and gives rise to the NGA transition. At a larger scale, classical grand canonical Monte Carlo simulations in the “rigid host” structures can predict the adsorption capacity of different phases, elucidating the driving force behind the structural transition. To explicitly couple the flexibility of the framework and the adsorption of guest molecules, molecular dynamics simulations (relying on a classical force field for the flexible metal–organic framework) can be coupled with free energy methods to investigate the thermodynamics of NGA, obtaining free energy profiles that determine the relative stability of different phases with varying amounts of adsorbed gas. Finally, mesoscopic-scale modeling methods are required in order to understand the phenomenon at a scale larger than one unit cell and explain experimental findings about the influence of crystal size effects on the NGA transition. This Account summarizes the computational approaches that have been used so far to better understand negative gas adsorption and highlights open questions and perspectives in this field of research.

The manipulation of functional oxide materials’ properties through energy-efficient means is of great importance in materials science. Electric field-driven ionic control of functional oxides presents a versatile and effective approach for tailoring material properties, including insulator–metal transitions, superconductivity, magnetism, and optical characteristics, through spin, orbit, charge, and lattice degrees of freedom. This approach introduces a dynamic means of tuning these properties, allowing for real-time adjustments through external stimuli such as electric fields. The ability to modify material characteristics through ionic means is promising for both scientific exploration and practical applications, owing to its energy efficiency and compatibility with room temperature operation. Traditionally, this was primarily explored for energy storage applications, but it has now found broad utility in optoelectronics, nanoelectronic memory, and computing.

Controlling charge carriers is a pivotal aspect of advancing the electronic functionalities of oxide materials. The substantial accumulation of charge carriers via electric field-induced electric double layers at oxide–electrolyte interfaces prompts extremely large electric fields, leading to different phenomena such as chemical reactions, phase transitions, and magnetic ordering. The mechanisms involved in electric field-controlled ionic motion using ionic liquids and gels range from primarily electrostatic to completely electrochemical. The electrostatic effect involves the induction of electrons or holes, and ionic motion is specific to the electrolyte side of the interface. In contrast, the electrochemical effect involves ionic motion occurring on both sides of the interface and across it. Through the application of electric fields, the insertion or extraction of ions in functional oxide materials enables the control of various phases and properties. In the electrostatic mechanism, carrier density modulation is primarily driven by band bending, whereas the electrochemical mechanism can completely reshape electronic band structures due to exceptionally high carrier densities. The electrolyte nature and target material properties significantly influence both the electrostatic and electrochemical effects. Recent advancements in characterization techniques and theoretical simulations have improved our understanding of the gating mechanisms in various material systems.

In this Account, we provide a concise summary of recent advancements in manipulating the properties of various transition metal oxide material systems using electrolyte-based ionic motion through an electric field. We begin by exploring the detailed mechanisms that underlie how electric field gating can bring about substantial changes in the material properties. These changes encompass alterations in crystal and electronic structures as well as modifications in electrical, optical, and magnetic properties. Additionally, we assess the potential applications of functional oxide devices made possible through these ionic control mechanisms, particularly their relevance to neuromorphic computing. Finally, we address the primary challenges in this field and suggest future research directions to further its progress.