Nanotechnology最新文献

The self-powered solar-blind photodetector offers irreplaceable advantages for applications such as wearable electronics and ultra-low power systems, but their performance is often limited due to the absence of an external bias. In this work, we demonstrate a highperformance self-powered photodetectors based on a well-designed NiO/Ga₂O₃ p-i-n heterostructure that requires no complex pre-treatment methods. The photodetector exhibits a high photo-to-dark current ratio of 378, a high responsivity of 137 mA/W, and fast response times of 27 ms/650 ms. Furthermore, we address the common lack of discussion on the physical origin of self-powered behaviour in other studies. The analysis of the p⁺-n⁻ one-sided abrupt junction, based on repeatable capacitance-voltage characterization, confirmed the presence of a strong built-in electric field with a calculated maximum field strength of 136 kV/cm. It is the fundamental driving force for the photodetector's excellent self-powered performance.

Black phosphorus (BP) is a novel two-dimensional (2D) material with tunable electronic and optical properties. Thickness is a pivotal parameter in defining the electronic, optical, and thermal properties of 2D crystals. Determining the thickness of a material is crucial to studying its properties. However, conventional characterization methods for the directly determination of thick layers of BP are complex and inefficient. In this paper, we propose a machine learning (ML)-based method that can efficiently and accurately determine the layer number of BP. The features of the three characteristic peaks (Ag1,B2g, andAg2) were extracted from the Raman spectra, including peak position, intensity, full width at half maximum, and integrated intensity. Subsequently, we found that the intensity ratio of the substrate (Si) peak to the Raman mode is crucial to predicting the number of layers by feature importance analysis. This study makes a key contribution by presenting, for the first time, a comparative analysis of multiple ML algorithms for identifying the layer number of BP. Furthermore, it identifies a specific set of discriminative features tailored for BP's Raman spectra. Finally, by synergistically augmenting the dataset and refining the model architecture, we effectively mitigated the performance limitations imposed by the small dataset. The performance of the model is evaluated based onR2, mean square error, and mean absolute error, where theR2of all algorithms is not less than 0.9. ML models can accurately predict the number of layers of BP material. ML algorithms can automatically learn from the data and optimize the algorithm to improve the efficiency and accuracy of the model. This not only reduces the analysis burden on researchers but also promotes the in-depth application of artificial intelligence in 2D material characterization.

Tellurium (Te), a typical p-type elemental semiconductor, exhibits exceptional properties including environmental stability, high carrier mobility, and superior optical responsiveness, demonstrating significant application potential in next-generation optoelectronic devices. This review provides a systematic overview of the crystal structures and optoelectronic properties of Te, along with the research progress in the field of Te-based photodetectors. Firstly, the crystal structures and band characteristics of Te are elucidated, with its optical and electrical properties analyzed in depth to lay a theoretical foundation for subsequent research. On this basis, the photoelectric performance and operating mechanisms of photodetectors based on individual Te nanomaterials are explored, encompassing one-dimensional (1D) Te nanowires, nanoribbons, nanocoils, and two-dimensional (2D) Te nanosheets and nanofilms. Furthermore, the structural designs and application potential of Te nanomaterial heterostructure photodetectors based on different band alignment types are elaborated in detail. Finally, the current bottlenecks encountered by Te-based materials in the field of photoelectric detection are synthesized, and perspectives on future researchdirections within this field are delineated. We believe that that frontier explorations of Te-based materials will yield significant breakthroughs, and such research will offer highly valuable industrial references for the commercialization of nanodevices.

A nano-inscribing technique was tested as a method of cost-effective replication of blazed diffraction gratings for x-rays. A saw-tooth mold for the nano-inscribing was fabricated by a double-replication process from a master blazed grating. The nano-inscribing was performed using a UV-curable resist of low viscosity to provide a small thickness of the resist replicas, required for a following transfer process. The nano-inscribing process was optimized to minimize surface relaxation and preserve the saw-tooth shape of the grooves, required for high diffraction efficiency. The quality of the replica gratings was evaluated via diffraction efficiency simulations. The simulations demonstrated that near theoretical efficiency can be achieved for the x-ray gratings made by the nano-inscribing approach.

Phosphorene exhibits promising tribological application due to its layered structure that imparts intrinsic lubricating properties. Understanding the mechanisms by which oxygen and other ambient species modify phosphorene remains a key challenge, with the impact of the layer thickness and point defects still unknown. Despite its promise as a solid-state lubricant, detailed nanoscale understanding of layer-dependent defect formation, surface reactivity, and potential degradation is still limited. In particular, the possible multilayer-dependent degradation behaviour of phosphorene in the presence of common environmental species such as hydrogen (H), oxygen (O), and hydroxyl (OH) has received little attention. In this work, we perform a systematic density functional theory investigation to explore how these chemical species interact with monolayer to four-layer phosphorene, including systems with and without phosphorus vacancies. Our findings show that H, OH adsorption is energetically not favourable in any layer configurations, while O shows strong exothermic interactions across all thicknesses, regardless of the presence of defects, with the bilayer showing the most favourable interaction with these species. Structural responses, including changes in bond lengths and interlayer spacing, were quantified and found to depend on both the type of adsorbate and the number of layers. The presence of vacancies induces localized distortions but does not compromise the overall structural integrity. Bader charge calculations show charge transfer between phosphorene layers and adsorbates. Overall, our results set a foundation for further work on phosphorene by providing a detailed, layer-by-layer understanding of phosphorene's chemical reactivity in ambient environments and highlight the need to consider layer number, intrinsic defects and environmental species in models of phosphorene.

In power electronics, silicon carbide (SiC) MOSFETs can experience ultra-high gate voltage pulses during electrostatic events, yet their reliability under such extreme conditions remains insufficiently explored. In this work, we fabricate SiC MOSFETs and present systematic reliability evaluation under ultra-high gate pulse stress. Our results reveal that hole-related charge trapping dominates the degradation for both positive and negative gate stress. Under high positive pulses, the threshold voltage (V_th) exhibits a non-monotonic shift driven by hole injection, whereas under high negative pulses,V_thdecreases rapidly due to hole capture and the formation of additional donor-like traps. Moreover, the time and field dependence ofV_thdegradation demonstrates that oxide breakdown is primarily caused by electric field stress. Overall, this study provides new insight into the degradation pathways of SiC MOSFETs under extreme electrical stress and offers practical guidance for improving device robustness in power applications.

This paper proposes substrate nitridation as an effective method to reduce radio-frequency (RF) loss in Si-based GaN epitaxial wafers. By optimizing the process, an amorphous SiNₓ layer was formed, which effectively blocks the downward diffusion of Al atoms and suppresses the formation of a parasitic conductive channel, thereby leading to a significant reduction in RF loss. Four distinct pre-flow conditions were specifically designed to decouple and modulate the properties of the AlN/Si interface. A detailed analysis of the initial dislocation evolution behavior was conducted, comparing the nitridated substrate with conventional pre-deposited Al processes. Although the nitridation process leads to a moderate increase in threading dislocation density by promoting their parallel propagation, the proposed dislocation coalescence mechanism, supported by our experimental design and analysis, indicates that the spatial extent of individual dislocations and defects is effectively constrained. This results in a substantial improvement in the overall RF electrical characteristics. Based on this proposed process, a coplanar waveguide (CPW) transmission line was fabricated, demonstrating a low RF loss of only -0.6 dB at 40 GHz. These results underscore that the nitridation process is a highly promising pathway for enhancing the RF performance of Si-based GaN materials; more importantly, this study reveals that the advantage of an initially optimized interface must be synergistically integrated and stabilized with subsequent epitaxial processes to achieve low-loss performance in final HEMT devices, which holds significant implications for the development of high-performance RF devices.

Lithium-ion batteries face challenges in achieving high energy density and long cycle life, due to limitations of conventional anode materials. MXenes, a class of two-dimensional materials, show great potential as anodes but suffer from low intrinsic capacity and severe nanosheet self-stacking.To overcome these issues, this study developed a double transition metal MXene, Ti 2 NbC 2 T x , which offers enlarged interlayer spacing and high electrical conductivity. To further address the selfstacking issue, a Ti 2 NbC 2 T x @CNFs (carbon nanofibers) composite was fabricated via electrospinning and subsequent carbonization. This structure uniformly embedded the MXene within a continuous conductive carbon matrix, effectively inhibiting self-stacking and facilitating electron/ion transport. As a lithium-ion battery anode, the composite demonstrated excellent electrochemical performance. A reversible capacity of 246.5 mAh g -1 was retained after 7000 cycles at a high current density of 5 A g -1 , demonstrating outstanding specific capacity and cycling stability.This work provides a viable strategy for developing high-performance MXene-based anodes for next-generation energy storage.

The static and dynamic properties of meron-like magnetic textures stabilised by anisotropic Dzyaloshinskii-Moriya interaction (A-DMI) are examined in nanodots across hosting geometries. By considering a circular magnetic nanoring, we use micromagnetic simulations to identify geometric conditions that minimise the total energy and favour the stabilisation of vortex or antivortex textures as a function of the ring hole. For each texture, we find an optimal geometry that maximises stability. We further map the spin-wave spectra under in-plane and out-of-plane field pulses. For antivortices, out-of-plane excitation yields a single well-defined mode, whereas vortices exhibit a richer modal structure arising from the competition between A-DMI and geometry. Under in-plane excitation, vortices and antivortices support the same number of low-frequency modes with similar spatial profiles. These results highlight the interplay between meron cores and chiral interactions, with implications for spintronic and magnonic devices that rely on stabilising magnetic textures or tailoring spin-wave modes.

Deviatoric stress-induced coalescence of nanocrystal superlattices is a promising route for massively fabricating nanowires. We perform atomistic molecular dynamics simulations to characterize the deviatoric stress-induced fusion behavior of alkylthiol-capped gold superlattices and examine the influence of ligand length on the nanowire formation. The results show that a threshold deviatoric stress along the compression direction is essential for forming the ordered nanowire arrays, and it significantly increases with the ligand length. The ligand length dependence can be attributed to the fusion energy barrier between constituent gold nanocrystals as well as its alternation induced by the change in ligand length. We show that the ligands on neighboring gold nanocrystals abundantly interdigitate at the potential minimum but become highly splayed or bent at the repulsive maximum. Increasing the ligand length promotes ligand interdigitation at the potential minimum but causes a larger contact area between ligands on opposite nanocrystals at the repulsive maximum. This jointly results in a marked increase in fusion energy barrier with the increasing ligand length, thereby requiring a higher critical deviatoric stress to drive the gold nanocrystals into nanowires for longer ligands. This study reveals that reducing the ligand length can effectively decreases the operational stress required for the formation of nanowires, which can provide theoretical guidance for optimizing the stress-induced nanofabrication approaches.