ACS Applied Electronic Materials最新文献

Cubic InGaN alloys are a promising candidate material for next-generation optoelectronic applications as they lack internal fields and promise to cover large parts of the electromagnetic spectrum from the deep UV toward the mid-infrared. This demands high-quality epitaxial growth of cubic InGaN/GaN quantum wells, especially for the red energy range. However, the growth of indium-bearing nitride quantum wells in the metastable cubic phase still poses many challenges. InGaN and GaN are typically grown at different temperatures and with different metal fluxes in molecular beam epitaxy, leading to either long waiting periods for temperature adjustment or growth under suboptimal conditions. Both degrade the crystal quality and optical properties. In this study, we apply a metal-modulated growth approach in molecular beam epitaxy that enables us to grow either self-assembled, phase pure, cubic InGaN/GaN multi quantum wells (MQWs) or homogeneous c-InGaN layers, only by adjusting the shutter duration times for Ga and In. We achieve smooth surfaces and sharp interfaces with a quantum well thickness tunable from 6 to 16 nm and a barrier thickness ranging from 4 to 10 nm. X-ray diffraction confirms >99% phase purity of our cubic layers, while time-of-flight secondary ion mass spectrometry, scanning transmission electron microscopy, and energy-dispersive X-ray spectroscopy provide detailed information on the quantum well composition and strain. Photoluminescence measurements at room temperature demonstrate the emission properties of the samples, with the emission wavelength ranging from 540 to 670 nm. Changing the barrier and QW thickness results in a shift of emission energy of up to 400 meV, which is explained by quantum confinement and strain. The high interface quality and excellent optical properties of the quantum wells without the need for multiple metal sources or long waiting times represent a significant advance in the development of next-generation optoelectronic devices.

In this study, an enhanced precursor atomic layer seeding (EPALS) assisted atomic layer deposition (ALD) is proposed to prepare high-quality hafnium oxide (HfO₂) high-K gate dielectrics on highly oriented pyrolytic graphite (HOPG) surfaces. The EPALS technique addresses the challenge of depositing high-quality oxides directly on two-dimensional (2D) materials, which typically lack dangling bonds on their surfaces. By enhancing the precursor reactivity through remote plasma, the EPALS process facilitates the adsorption of precursors, thereby enabling the effective deposition of HfO₂ on the HOPG surface without compromising its intrinsic sp² structure. The HfO₂ thin films prepared by the EPALS-assisted ALD method upon HOPG present desirable dielectric properties, characterized by a high dielectric constant of 19.65 and a low equivalent oxide thickness of 1.46 nm, as evidenced by the electrical characterization of a metal–insulator–metal structure. Furthermore, Raman and X-ray photoelectron spectroscopy analyses confirm the minimal impact of the EPALS process on the integrity of the HOPG surface. This study provides valuable insights into oxide deposition on 2D materials, paving the way for the advancement of high-performance electronic and optical devices based on graphene and other 2D materials.

Refractory materials with good optical properties are required for the development of novel high-temperature photonic and plasmonic photothermal applications. Whereas conventional plasmonic materials have excellent optical properties but low melting points, most refractory metals exhibit low plasmonic responses and oxidize easily in the atmosphere. Hence, in this study, cerium hexaboride (CeB₆) thin films are grown via electron-beam deposition on Si(100) and sapphire substrates. Epitaxial growth of this material is achieved under specific conditions, thus yielding high crystallinity and strong plasmonic polarizability within the infrared spectral region. The optical properties of CeB₆ improved significantly depending on the template substrate and growth conditions, achieving a six times higher plasmonic figure-of-merit on R-sapphire compared with on Si substrates. The high performance of CeB₆ films, as reflected by their superior plasmonic figures-of-merit particularly in the near-infrared region (1.0–2.0 μm) compared with conventional refractory materials, renders them highly promising candidates for photothermal and optoelectronic applications.

Antiferroelectric (AFE) fluorite, e.g., ZrO₂ thin films, is emerging as a promising architecture for energy storage and low-power memory applications due to its mature compatibility with complementary metal-oxide-semiconductor technology. However, despite the considerable potential of AFE materials for memory applications, the manipulation of the double hysteresis of AFE materials remains insufficient. Therefore, we deterministically controlled the split-up behavior of the polarization switching current of 10 nm thick AFE ZrO₂ thin films. Polycrystalline ZrO₂ thin films were deposited on TiN/Si substrates by atomic layer deposition. Then, using conventional current–electric field measurements, we demonstrated that the splitting of the AFE switching current can be controlled by adjusting the applied bias voltage during subloop cycling. First-order reversal curves showed that this split phenomenon represents the separation of the internal bias field. Additionally, we report that the sequential unipolar subloop cycling of different electric fields induced multiple and asymmetric split-up behavior. These findings suggest the possibility of symmetry engineering of the switching current peak in AFE ZrO₂ through conventional electric bias stimulus.

Self-rectifying organic memristors with integrated biosynaptic functionalities show significant potential for enabling high-density neuromorphic networks by inherently suppressing stealth current effects. In this study, we present a fully solution-processed PEDOT:PSS-based memristor that combines resistive switching and self-rectifying properties. The device features spin-coated PEDOT:PSS as both the top and the bottom electrodes. To enhance the conductivity of the PEDOT:PSS film, ethylene glycol was added to the spin-coating solution, followed by sequential methanol cleaning. The functionalities are achieved through enhancing the redox activity of PEDOT and the transformation of the ionic PSS within the hybrid film. The inclusion of ZnO nanoparticles (ZnO NPs) significantly enhances device performance, resulting in a higher on/off current ratio and sophisticated synaptic behaviors, including transitions from short- to long-term plasticity and improved linear potentiation and depression. This work underscores the potential of solution-processed PEDOT-metal oxide hybrid systems as a foundation for advancing neuromorphic computing architectures.

Amorphous In–Al–Sn–O (IATO) is a very promising channel material for thin film transistors (TFTs). In this study, we first investigated the properties of IATO films and TFTs under various oxygen partial pressures (P(O₂)) of RF magnetron sputtering. The IATO films were amorphous with smooth surfaces, high average absolute visible transmittances exceeding 92.0%, large optical band gaps of 4.11–4.36 eV, and a wide Hall mobility range of 8.23–84.3 cm² V^–1s^–1. As P(O₂) increased from 0 to 4%, the performance of the IATO TFTs gradually degraded. Under P(O₂) of 0%, the IATO TFTs exhibited high field-effect and saturation mobilities exceeding 10 cm² V^–1 s^–1, high on/off current ratios of 3.42 ± 0.13 × 10⁹, and the best positive and negative bias stress stability. Upon replacing the SiO₂ gate insulator with atomic layer deposited Al₂O₃, further enhanced overall performance of IATO TFTs was achieved, including high saturation mobilities of 13.1 ± 0.13 cm² V^–1 s^–1, low threshold voltages of 1.17 ± 0.10 V, low subthreshold swings of 106 ± 6.2 mV dec^–1, and low hysteresis values of 0.09 ± 0.01 V. They also demonstrated excellent bias stability, with the maximum threshold voltage shifts under 3000 s of negative bias (−1 V) and positive bias (5 V) stresses being only −0.32 and +0.61 V, respectively.

An electronic tongue is a sensor-based system designed to mimic human taste by detecting and analyzing the chemical properties of liquids through electrochemical methods. Here, we introduce the HITS concept, an electronic tongue system that enables rapid and sequential classification of various beverages. This system utilizes a single, cost-effective platform with interdigital electrodes made of carbon printed on recyclable poly(ethylene terephthalate) (PET), significantly reducing the need for multiple electrodes. With the use of interchangeable hydrogel tapes, the system requires a single deep (150 μL) pore per analysis, allowing for efficient sequential testing. The hydrogel seamlessly accommodates the electrode interface and operates with a semisolid electrolyte, achieving ultrafast analysis times of just 5 min. Employing AI and machine learning algorithms, HITS accurately differentiated between coffee, juice, water, white wine, and red wine with a 100% success rate. This sustainable approach combines high precision, speed, and low environmental impact, offering a versatile solution for various technological applications, including food science, quality control, and health monitoring. This e-solution not only enhances precision and speed but also aligns with growing environmental concerns, offering a low-impact and scalable platform for advanced liquid analysis.

Organic synaptic memristors have recently attracted considerable interest due to the ease of fabrication enabled by solution processing and their potential roles in neuromorphic electronics. In this research, an organic polymer memristor based on poly(3-octylthiophene-2,5-diyl) (P3OT) was designed, and a systematic characterization of its electrical properties was experimentally demonstrated. The device successfully emulated multiple synaptic behaviors, including paired-pulse facilitation (PPF), paired-pulse depression (PPD), post-tetanic potentiation (PTP), spike-timing-dependent plasticity (STDP), and short-term plasticity (STP) to long-term plasticity (LTP) transition, as well as experience learning. Detailed analysis of the I–V characteristics indicated that resistance switching resulted from a combination of tunneling, space charge-limited conduction (SCLC), and Schottky emission mechanisms. The electrical performance of the device remained stable even after being stored in an air environment for more than 90 days. Furthermore, an artificial neural network (ANN) implemented using this device achieved a recognition accuracy of 91% on the MNIST data set. This study offers valuable theoretical insights and experimental references for advancing the use of organic polymer memristors in simulating synaptic functions and implementing artificial neural networks.

With the continuous advances in technology and the persistent necessity of a recycling economy, biosourced materials have drawn much attention. Here, one kind of eutectogel with high mechanical strength, antidrying performance, and good conductivity was fabricated through a facile solvent replacement strategy. Based on double reversible physical cross-linking networks of the gel and the sol–gel transformation ability of gelatin, the eutectogel is capable of self-healing ability. By altering the weight ratio of gelatin/natural rubber (G/N) and immersion time in DES, the mechanical strength and toughness could be effectively regulated. Combining the antifatigue performance, lower freezing point, and stable gauge factor, the eutectogel may not only broaden the application fields of gels but also be used in flexible sensors and wearable electronic devices to satisfy the demands in extreme environments.

An electronic tongue is a sensor-based system designed to mimic human taste by detecting and analyzing the chemical properties of liquids through electrochemical methods. Here, we introduce the HITS concept, an electronic tongue system that enables rapid and sequential classification of various beverages. This system utilizes a single, cost-effective platform with interdigital electrodes made of carbon printed on recyclable poly(ethylene terephthalate) (PET), significantly reducing the need for multiple electrodes. With the use of interchangeable hydrogel tapes, the system requires a single deep (150 μL) pore per analysis, allowing for efficient sequential testing. The hydrogel seamlessly accommodates the electrode interface and operates with a semisolid electrolyte, achieving ultrafast analysis times of just 5 min. Employing AI and machine learning algorithms, HITS accurately differentiated between coffee, juice, water, white wine, and red wine with a 100% success rate. This sustainable approach combines high precision, speed, and low environmental impact, offering a versatile solution for various technological applications, including food science, quality control, and health monitoring. This e-solution not only enhances precision and speed but also aligns with growing environmental concerns, offering a low-impact and scalable platform for advanced liquid analysis.