ACS Applied Electronic Materials最新文献

Electrochemical metallization-based memristors have attracted considerable attention as artificial synaptic devices owing to their ion-mediated conductance modulation. Although halide-based resistive switching (RS) layers are promising for neuromorphic applications, the use of active metals such as Ag or Cu as the top electrode (TE) can induce unstable switching behavior through unwanted interfacial reactions and metal migration into the halide layer. In this study, a poly(methyl methacrylate) (PMMA) buffer layer was inserted between the Ag TE and the CuI RS layer to improve the electrical and structural stability of CuI-based memristors. The PMMA buffer layer suppressed Ag diffusion into the CuI layer, thereby preserving the Ag TE for up to six months. This suppression of electrode degradation consequently enabled stable resistive switching and long-term electrical stability without significant degradation. X-ray diffraction and time-dependent scanning electron microscopy – energy dispersive X-ray spectroscopy analyses were performed to investigate the presence of Ag and its diffusion behavior over time. In addition, ABAQUS-based finite element analysis was conducted to simulate the time-dependent Ag concentration distribution, revealing that the maximum Ag concentration in the PMMA/CuI device was reduced by approximately 88% compared with that in the device without PMMA. The synaptic characteristics of the devices were further evaluated through long-term potentiation and depression measurements and implemented in artificial neural network simulation. As a result, the recognition accuracy increased from 66.0% for the CuI device to 79.4% for the PMMA/CuI device, corresponding to an approximately 20% improvement. Furthermore, spike-dependent conductance modulation was demonstrated by varying the spike amplitude, number, and duration, confirming the capability of the PMMA/CuI device to emulate synaptic weight modulation. These results demonstrate that PMMA acts as an effective diffusion-modulating buffer layer for improving the reliability of CuI-based artificial synaptic devices.

Hysteresis is the defining electrical signature of memristive dynamics and underpins the history-dependent conductance required for artificial synapses and neuromorphic computing. However, unlike conventional passive electronic components, memristive devices lack a universally accepted framework for quantitatively characterizing and reporting their diverse hysteretic responses, making cross-device comparison and systematic engineering difficult. For lateral 2D-material memristors, this challenge is amplified by the strong dependence of hysteresis on coupled material, transport, and interface parameters, yet a unified quantitative map connecting these parameters to hysteresis emergence, loop classes, figures of merit (FoMs), and controllable transformations between hysteresis types remains unavailable. In this work, we develop a physics-informed, data-driven hysteresis engineering framework for 2D lateral memristors using a coupled transport model that solves the drift–diffusion equations for the quasi-Fermi potentials of charge carriers, the electrostatic potential from Poisson’s equation, and Schottky barrier modulation at a specified temperature. From ∼10,000 simulations across seven input parameters, we identified that ∼13.3% of configurations exhibit hysteresis, clustering into six loop types. We define 11 FoMs (loop area, memory ratios, nonlinearity, collapse/stationary indicators) and map their type-specific statistical distributions. Sensitivity and correlation analyses identify dominant knobs and enable loop transformations by tuning electrode spacing, vacancy mobility, barrier height, and scan rate, in agreement with experimental reports. We establish more than 500 relationships between input material/device properties and output hysteresis FoMs. Machine-learning models achieve 96.5% accuracy in hysteresis prediction and 76.38% accuracy in hysteresis loop-type classification. This work provides a framework for hysteresis engineering in memristive devices, enabling rapid screening and inverse design for next-generation computing applications.

Defects play an essential role in determining the resistive switching behavior, variability, and scalability of hBN-based memristors. In this work, we employ Ar⁺ implantation to create atomic defects within an array of Au/hBN/Au sandwich structures. As the Ar⁺ implantation dose increases from 0 to 4 × 10¹¹ cm⁻², the yield of Au/hBN/Au memristors linearly increases from 1.4% to 77%. Lateral force microscopy indicates that atomic-scale defects are created in the pristine hBN flakes by Ar⁺ ion implantation. High-resolution transmission electron microscopy shows that atomic-scale defect channels exist in the hBN flake with a memristive switching behavior. It is evident that conduction via these atomic-scale defect channels enables memristive behavior in Au/hBN/Au sandwich structures.

The rapid progression in smart wearable healthcare technologies has intensified the demand for sustainable, maintenance-free, and intelligent sensing systems for continuous human motion monitoring. Among the various sensing systems, triboelectric nanogenerators (TENGs) emerge as a promising solution for self-powered gait monitoring due to their ability to efficiently harvest biomechanical energy from human body motion. This review provides a comprehensive overview of intelligent self-powered gait monitoring systems based on TENGs, spanning from device design to data-driven health prediction. We discuss various device designs for the analysis of gait monitoring and motion sensing and fabrication strategies that enhance sensitivity, flexibility, and durability for wearable applications. Subsequently, we examine the integration of TENG-based sensors into smart footwear and wearable platforms for real-time gait analysis, highlighting key performance metrics and signal characteristics. The review further explores the convergence of TENG sensing with artificial intelligence (AI) techniques, including machine learning and deep learning algorithms, for accurate gait pattern recognition, anomaly detection, and early diagnosis of osteoarthritis, flat foot, and Parkinson’s disorders. Finally, current challenges such as signal variability, system integration, data reliability, and scalability are critically analyzed, along with future perspectives toward personalized, AI-driven healthcare systems. This work aims to provide a unified framework for the development of next-generation intelligent, self-powered gait monitoring technologies and paves the way toward artificial intelligence of things (AIoT).

Metal–insulator–metal (MIM) tunnel junctions have various applications in microelectronics. As a core building block within this space, these simple structures are fabricated using conventional patterning, deposition, and etching techniques. As such, MIM devices are subject to the inherent limitations and undesirable byproducts of these techniques. Herein, an alternative approach to MIM tunnel junction fabrication is presented, in which classical patterning is used in conjunction with bottom-up, self-assembly to form these structures. Area-selective deposition is utilized to grow encroaching electrodes that terminate at their meeting point to make junctions. The resulting resistances of these junctions are found to be independent of their initial spacing, an indication of self-limited growth. Temperature dependence of these resistances and the behavior of these devices upon annealing indicate electronic tunneling as the dominant transport mechanism. Analysis of these properties is used to estimate barrier thicknesses and conclude that steric effects are the likely reason for self-limitation.

Highly sensitive and self-powered photodetection is a key requirement for applications in space communication, flame sensing, bioimaging, and environmental monitoring. The integration of topological insulator (TI) materials with wide-bandgap (WBG) semiconductors offers an effective platform for high-performance self-powered ultraviolet (UV) and near-infrared (NIR) photodetection due to the efficient carrier transport and strong light–matter interactions. Despite the remarkable topological and optical properties of TIs, comprehensive and systematic studies of their magnetotransport and photodetection behavior in heterojunctions with WBG GaN are relatively underexplored. Here, we have deposited Bi₂Te₃ thin films on p-GaN/sapphire (0001) substrates by DC magnetron sputtering and investigated their magnetotransport and dual-band UV and NIR photodetector (PD) properties. Raman spectroscopy and high-resolution X-ray diffraction analyses revealed the formation of the rhombohedral crystalline Bi₂Te₃ thin films, while X-ray photoelectron spectroscopy confirmed their chemical states. Atomic force microscopy characterization showed that the truncated triangular and hexagonal quintuple-layered-like formations are strongly connected to one another, forming a continuous network exhibiting distinct crystalline growth. The magneto-transport analysis reveals weak antilocalization in Bi₂Te₃/p-GaN, with the Hikami–Larkin–Nagaoka coefficient “α”; value of –2 at 2 K. The “α” value indicates more than two decoupled transport channels arising from the topological surface states (TSS) at the top and bottom surfaces of Bi₂Te₃. The fabricated metal-semiconductor-metal-based Bi₂Te₃/p-GaN PD exhibited self-powered operation with a responsivity of ∼1.51 × 10³ mA/W and ∼0.67 mA/W under UV and NIR illumination, respectively. It achieves UV photoresponsivity of ∼4.91 × 10² A/W at 5 V bias, which represents an ∼5.64 × 10²-fold enhancement over the bare p-GaN-based PD. This remarkable enhancement in PD performances is attributed to the synergistic effects, i.e., strong built-in electric field at the heterojunction and TSS of TIs on p-GaN for the development of next-generation self-powered and high-responsivity dual-band photodetection applications.

Low hole mobility, strong hole trapping, and self-compensation effects limit the achievement of stable p-type conductivity in the β-Ga₂O₃ semiconductor, thereby inhibiting its application in advanced electronic devices. From a theoretical standpoint, the relatively flat nature of the valence band maximum (VBM) with dominant oxygen vacancy-related donor states constitutes a major bottleneck that intrinsically drives the material toward n-type conductivity. In this study, we successfully achieved p-type conductivity in gallium oxide thin films using copper doping. The introduction of controlled Cu as an acceptor dopant using RF magnetron sputtering into the Ga₂O₃ film facilitates bipolar transport by creating an acceptor impurity level near the valence band maximum (VBM), resulting in conductivity modulation. X-ray photoelectron spectroscopy (XPS) and capacitance–voltage (C–V) measurements provide evidence of p-type conduction with a high hole concentration on the order of 10¹⁹cm^–3. The positive Seebeck coefficient (S) further confirms hole-dominated electrical transport. Moreover, theoretical analysis reveals that the Cu-induced localized states near the VBM predominantly originate from Cu-d states hybridized with O-p states, indicating strong local Cu–O interactions at the octahedral sites and providing microscopic insight into the experimentally observed modulation of electrical conductivity. Finally, a solar-blind photodetector was fabricated using optimized copper-doped p-type gallium oxide thin films. The fabricated device demonstrates remarkably high performance with a photo-to-dark current ratio (PDCR) of 157.33 ± 0.88, responsivity of 806.88 ± 20.55 A/W, external quantum efficiency of (4.01 ± 0.10) × 10⁵%, noise-equivalent power of (1.88 ± 0.01) × 10^–13 W Hz^–1/2, and a specific detectivity of (2.58 ± 0.05) × 10¹² Jones at 250 nm with a moderate bias of 5 V at a 1 Hz frequency, demonstrating consistent performance across five nominally identical devices. These findings show that the interfacial electrostatics and charge-transport mechanisms in Ga₂O₃ Schottky devices are efficiently tuned by regulated Cu inclusion, offering insights for enhancing ultra-wide-bandgap oxide-related devices.

With the rapid advancement of the Internet of Things (IoT), artificial intelligence (AI), and wearable technologies, barium titanate (BTO) thin films play a vital role as core functional layer materials. This also imposes higher demands on the crystallization quality of thin films, interface states, and compositional uniformity. Pulsed laser deposition (PLD) technology has become a key method for fabricating high-quality BTO thin films due to its advantages of precise composition control and ease of achieving in-situ epitaxial growth. This paper provides a systematic review of research progress in fabricating BTO thin films using PLD technology, focusing on the effects of key process parameters such as deposition temperature, oxygen pressure, laser energy, and repetition rate on the crystalline quality, surface morphology, and performance characteristics of the thin films. The results demonstrate that BTO thin films with high dielectric constant, low leakage current, and pronounced ferroelectric properties can be obtained by optimizing the PLD process conditions. Furthermore, this paper summarizes the application potential of BTO thin films in electro-optic modulators (EOMs), ferroelectric memristors, and sensors, while identifying current technical challenges and future development directions. This review aims to provide theoretical references and process guidance for the controllable preparation and integration of high-performance devices in BTO thin films, advancing their development in the field of functional oxide thin films.

Colloidal quantum dot (CQD) infrared (IR) photodetectors exhibit great application potential in the fields of optical communication, environmental monitoring, imaging, and wearable sensing. Specifically, AgBiS₂ CQD IR photodetectors have garnered extensive attention because of their excellent photoelectric properties, solution-processability, as well as non-toxicity and environmental friendliness. However, the high trap density and relatively low carrier mobility of AgBiS₂ CQDs have limited their development in high-performance IR photodetectors. Herein, a representative 2D transition carbide, Ti₃C₂T_x, is introduced into the AgBiS₂ CQD films to develop enhanced IR photodetectors based on MXene/AgBiS₂ hybrid films. By finely controlling of the MXene additive concentration, this combination possibly helps reduce trap state density in AgBiS₂ films to suppress carrier nonradiative recombination and simultaneously constructs an efficient conductive pathway in AgBiS₂ films to enhance the extraction of photo-generated carriers. Consequently, compared to the pristine AgBiS₂ CQD devices, the MXene/AgBiS₂ CQD-based infrared photodetector exhibits significant promotion in the responsivity, EQE, and estimated normalized detectivity under a broad band from 500 to 900 nm, demonstrating an alternative method for tailoring the performance of AgBiS₂ CQD optoelectronic devices.

Achieving high electrical quality gate dielectrics for thin-film transistors atop flexible substrates is a challenge due to thermal constraints imposed by the soft and sensitive substrates. This study examines a multitude of deposition pathways using rigid metal–insulator–metal (MIM) capacitors to discern effective solutions. This study provides a comprehensive evaluation of both material characterization and electrical performance of HfO₂-based MIM capacitors fabricated using three ALD processes: (1) standard as-deposited thermal atomic layer deposition (TALD), (2) plasma-enhanced ALD (PEALD) at 200 and 250 W (PEALD200, PEALD250), and (3) in situ atomic layer annealing (ALA)-ALD at similar plasma power (ALA200 and ALA250). Material characterization highlights the impact of deposition conditions on film quality. X-ray reflectivity (XRR) revealed improved film density and reduced surface roughness for PEALD250 and ALA processes compared to TALD, while X-ray photoelectron spectroscopy (XPS) verified stoichiometric HfO₂ with minimal hydroxyl incorporation under optimized plasma and ALA conditions. Electrical characterization demonstrated clear process-dependent differences in capacitance, dielectric constant, interfacial trap density (D_it), and leakage current. Capacitance–voltage measurements exhibited slight bias dependence and frequency dispersion, indicative of interfacial polarization and dipolar relaxation. TALD films delivered the highest capacitance (∼1.3 μF/cm^–2) due to reduced thickness using the same precursor pulse steps but suffered from a lower dielectric constant (ε_r ≈ 23) and elevated leakage (∼2 × 10^–7 A cm^–2). In contrast, ALA processed devices achieved the best overall performance, combining a high dielectric constant (ε_r ≈ 26), ultralow leakage (∼1 × 10^–7 and 9 × 10^–8 A cm^–2), and reduced trap density (6.4 × 10¹² and 1.4 × 10¹³ cm^–2eV⁻¹), attributed to enhanced film densification and suppressed oxygen vacancies. These results position ALA-based processes as promising candidates for high-κ dielectrics in advanced MIM capacitors and gate dielectric applications, offering improved reliability and scalability for next-generation electronics.