Electronic Materials Letters最新文献

Two-dimensional material, tellurium, composed of tellurium, has emerged as a promising material for NO₂ gas sensing due to its superior intrinsic electrical conductivity and strong affinity to NO₂. However, the majority of literature on tellurene-based gas sensors has primarily focused on NO₂ detection performances under dry condition, despite the importance of considering humidity-dependent detection properties for practical gas sensing applications. Here, we explore NO₂ detection properties of tellurene-based chemiresistive gas sensor devices under humidity environments at room temperature. The resultant tellurene synthesized via a hydrothermal route presents 2D flake-like morphologies with highly crystalline hexagonal structures. The obtained tellurene chemiresistive sensor devices exhibit a good NO₂ gas response of 35% with a fast response time of 14 s, under dry conditions. Interestingly, our tellurene-based sensor devices also present the humidity-independent NO₂ gas detection performances while achieving a fast response time. These outstanding detection performances are likely due to intrinsically superior electrical conductivity and structural stability of tellurene in air.

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The assessment of the State of Health (SOH) of lithium-ion batteries is paramount to ensuring the safety and reliability of battery management systems. Numerous researchers have employed Equivalent Circuit Models (ECM) and data-driven methodologies to estimate SOH. Each methodology has its merits and drawbacks, yet their integration poses substantial challenges. This paper proposes a novel approach for SOH estimation that synthesizes ECM with data-driven techniques. Initially, parameters for a second-order ECM are identified utilizing the voltage rebound characteristics of lithium-ion batteries. Subsequently, a predictive model is established employing a Long Short-Term Memory (LSTM) neural network. Finally, features extracted from the ECM and the dataset are utilized as inputs for the LSTM neural network to predict SOH. The efficacy of the proposed technique is corroborated by datasets from NASA and CALCE. Results indicate that the novel method’s maximum Root Mean Square Error (RMSE) is confined to 0.79%, and the Mean Absolute Error (MAE) is limited to 0.47%. Compared to other methods, this approach exhibits faster convergence, higher precision, and enhanced generalizability.

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This study investigates methods to enhance the permeability of metal magnetic composites, crucial for the performance of thin film power inductors in high-frequency applications, such as those in contemporary smartphones operating in the MHz range. Traditional reliance on ferrite magnetic materials is eschewed in favor of metal magnetic materials combined with epoxy to create novel composites aimed at optimizing packing density and significantly increasing magnetic permeability. The impact on permeability is explored using four different metal powders: pure iron (FE), Fe-Si (FS), Fe-Si-B-C-Cr (AM), and Fe-Si-B-Nb-Cu (NC). The FE sample is produced using carbonyl iron powder, resulting in a particle size (D50) of 2.1 μm. The FS sample, produced through gas atomization, has a particle size of 17.5 μm, while the AM and NC samples, produced via water atomization, yield particle sizes (D50) of 19.4 μm and 23 μm, respectively. Analyses using X-ray diffraction (XRD) and Mösbauer spectroscopy reveal that FE and FS samples have crystalline structures, whereas AM and NC are amorphous. Scanning electron microscopy confirms the spherical shape of particles in all samples. Theoretical calculations, based on Ollendorff’s theory of permeability and Suzuki and Oshima’s models on packing fraction, suggest that a composite with a ratio of 8:1.2:0.8 and particle sizes of approximately 25 μm, 1.5 μm, and 0.1 μm, respectively, could achieve a permeability value of up to 138.1. This demonstrates the potential for achieving high permeability at MHz frequencies through strategic packing of voids with submicron and nanopowders, marking a significant advancement in the field of thin film power inductors.

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Flexible strain sensors that combine high sensitivity and wide range are important for developing wearable electronics. In this paper, AgNWs/MXene/SEBS flexible strain sensor with high sensitivity and wide strain range was prepared using a thermoplastic elastomer (styrene-ethylene-butene-styrene) SEBS as the polymer matrix and AgNWs and MXene as the composite conductive fillers. The sensitivity of the AgNWs/MXene/SEBS sensor is significantly higher than that of the AgNWs/SEBS and MXene/SEBS sensors based on a single conductive filler. At 100% strain, the AgNWs/MXene/SEBS sensor has a sensitivity of 176.25. The sensor detects small strains of 0.5-5% as well as large strains of 5–50% with high linearity. The sensors remained stable after 200 cycles. The AgNWs/MXene/SEBS tensile sensors were subjected to array testing and finger bending recognition, and the sensors have promising applications in human motion monitoring.

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With the advent of artificial intelligence (AI), automated machines could replace human labor in the near future. Nevertheless, AI implementation is currently confined to environments with huge power supplies and computing resources. Artificial neural networks are only implemented at the software level, which necessitates the continual retrieval of synaptic weights among devices. Physically constructing neural networks using emerging nonvolatile memories allows synaptic weights to be directly mapped, thereby enhancing the computational efficiency of AI. While resistive switching memory (RRAM) represents superior performances for in-memory computing, unresolved challenges persist regarding its nonideal properties. A significant challenge to the optimal performance of neural networks using RRAMs is the nonlinear conductance update. Ionic hopping of oxygen vacancy species should be thoroughly investigated and controlled for the successful implementation of RRAM-based AI acceleration. This study dopes tantalum oxide-based RRAM with aluminum, thus improving the nonlinear conductance modulation during the resistive switching process. As a result, the simulated classification accuracy of the trained network was significant improved.

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In this paper, nitrogen-doped carbon (NC) coated tens nanometer hydrangea macrophylla-like CeO₂(CeO₂-NC) was synthesized by simple hydrothermal and polymeric calcination approach. Samples are characterised by SEM, Raman spectroscopy, XPS, etc. CeO₂-NC shows an initial potential of 0.90V (vs. Ag/AgCl) in 9.5 M H₃PO₄. In addition, the CeO₂-NC composite also exhibits a high limiting current (6.25 mA mg⁻¹). CeO₂-NC effectively combines the high initial potential of CeO₂ with the high limiting current of NC. Moreover, a hybrid proton battery assembled with CeO₂-NC composite as the cathode catalyst and MoO₃ (1 mg) as anode catalyst can produce a high capacity of 261.7 mAh at 1 A g⁻¹. The hybrid battery also exhibits excellent catalytic stability. After 1000 cycles at a high current density of 15 A g⁻¹, the capacity of the battery still remains 125.0 mAh, with a retention rate of approximately 90.9%. The improvement in battery performance is due to the use of NC to coat CeO₂, which improves the limiting current and durability of the electrode. The presented hybrid proton batteries have further enriched the application of electrochemical energy storage devices, and the preliminary exploration of cathode catalysts significantly improved the catalytic performance of ORR under acidic conditions.

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In this article, we have investigated the electronic structure and magnetic properties of Sm₂MgMnO₆ prepared through auto-combustion method. The first principles of the density-functional theory have been applied to study of the electronic structure. The oxidation states of Mn and Mg are Mn³⁺/Mn⁴⁺ and Mg²⁺, respectively. The existence of Mn³⁺ is higher than Mn⁴⁺. The magnetic study reveals the sample shows ferromagnetic to paramagnetic transition at around 13.5 K which is followed by an antiferromagnetic ordering at 8.3 K. Antiferromagnetic and ferromagnetic ordering have been identified at 8.3 K and higher temperature, respectively. Sm₂MgMnO₆ shows a maximum magnetic entropy change of 1.25 J kg^-1K^-1 and relative cooling power of 86.9 J/kg for a field variation of 70 kOe near 25 K. The values are comparable to many double perovskites reported previously. This study highlights that Sm₂MgMnO₆ is a potential material for magnetocaloric refrigerant at low temperature.

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The asymmetrical gate-drain bias stress (GDBS) stability of a mesa-shaped vertical-channel thin-film transistors (VTFTs) was investigated using an In-Ga-Zn–O (IGZO) active layer prepared by atomic-layer deposition. The GDBS measurements were conducted with variations in electrode configurations and overlapped areas between the active and bottom electrode regions. The GDBS stability of the IGZO VTFTs was found to be significantly degraded, when a plasma-damaged electrode was used as the drain electrode, due to the formation of defective channel regions that are more susceptible to the hot carrier effect. To address the effect of plasma-damaged electrode, an ultrathin passivation layer was introduced, resulting in the achievement of VTFTs with excellent and uniform GDBS stability.

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Two-dimensional (2D) transition metal dichalcogenides (TMDs) are excellent candidates for electronic applications because of their high carrier mobility, tunable bandgap energy depending on the number of layers, monolayer thickness, and the absence of dangling bonds on their surfaces. Despite these advantages, the crystalline structures of TMDs contain intrinsic defects such as vacancies, adatoms, grain boundaries, and substitutional impurities, which can cause large contact resistance at the source/drain interface. Customized engineering of interfaces and defects, which provides a method to modulate the properties of TMDs, is crucial as it can significantly enhance device performance. Herein, we explored a novel electrode to enhance the interface between electrode and semiconductor materials. we report the synthesis of high-quality atomically thin MoO₂ using atmospheric pressure chemical vapor deposition (APCVD) and its application to field-effect transistors. To improve crystallinity of MoO₂, we investigated the influence of hydrogen concentration, a key parameter in the reduction process, on the synthesis of high-crystallinity MoO₂. By adding NaCl to MoO₃ powder, we optimized the synthesis of high-crystallinity MoO₂. Utilizing the optimized MoO₂, we fabricated transistors that exhibited a mobility of 29.1 cm²/V∙s and an on/off ratio of 1.78 × 10⁴, demonstrating excellent performance. Our findings confirm that single-crystal MoO₂ can be effectively applied as a contact electrode in high-performance two-dimensional semiconductor devices.

The incorporation of semi-crystalline polymers as additives with small-molecule organic semiconductors has emerged as a pioneering method for the alteration of crystallization processes, thin film morphologies, and charge carrier mobility within organic semiconductor matrices. In this paper, we utilize the intrinsic attributes of polyethylene oxide (PEO), acting as a semi-crystalline polymer additive, to modulate the crystallization, phase segregation and charge transport of 6,13-bis (triisopropylsilyl) pentacene (TIPS pentacene). To understand the synergistic effects between varying molecular weights (8, 100, 300 and 900 K) of PEO and the crystallization behavior of TIPS pentacene, we conducted a quantitative analysis of the films' relative crystallinity and crystallographic morphology employing X-ray diffraction (XRD) and optical microscopy. Our findings indicate that higher molecular weight PEOs (300K and 900K) exhibit reduced molecular chain activity, resulting in lower crystallinity at increased doping ratios. Furthermore, attributes such as a high dielectric constant and a substantial melting point, combined with favorable thermoplastic properties, predispose these films to a more susceptible phase separation within the crystalline matrix. Conversely, films with lower molecular weight PEOs (8 and 100 K) showed lesser impact from molecular chain dynamics, leading to enhanced crystal morphology, higher crystallinity, and improved charge carrier mobility by up to 11 times. This substantial enhancement underscores the potential of employing low molecular weight semi-crystalline polymers as additive agents in the development of advanced organic semiconductor devices.

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