Accepted
, , Received Date: 2024-09-30
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, , Received Date: 2024-11-05
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In order to improve the discrepancy between specific on-resistance (Ron,sp) and breakdown voltage (BV) of lateral double-diffused metal oxide semiconductor (LDMOS) and enhance the turn-off characteristic, this paper proposes a novel LDMOS device with dual-drift regions and dual-conduction paths, which achieves an ultra-low Ron,sp. The key feature of the proposed device is the introduction of a dual-drift region structure with alternating P-type and N-type regions, combined with planar and trench gates to control the P-type and N-type drift regions, respectively. This configuration enables the formation of two independent electron conduction paths within the drift region. When a positive voltage is applied to the planar gate, a voltage difference is generated between the surface of the P-type drift region and the body of device’s drift. Therefore, under the influence of the voltage difference, the electrons are pulled to the surface of the P-type drift region to invert and form a high-density electron inversion layer that connects the channel and the N+ drain, significantly increasing the electron density during conduction and reducing the Ron,sp. The introduction of the trench gate provides an additional electron disappearance path, which shortens the device's turn-off time (toff). Furthermore, the introduction of the P-type drift region facilitates the recombination of electrons with holes within the P-type drift region, accelerating the electron disappearance process and further reducing the device's toff. Furthermore, the proposed device exhibits a more uniform electric field distribution and higher voltage capability is due to the P+N-N+P+ structure adopted in the PolySi-top layer. During the off-state, both the P+N- junctions and the N+P+ junctions generate electric field peaks at the interfaces. These peaks modulate the electric field distribution across the surface of the drift region. Simulation results indicate that at a BV of 200V, the proposed LDMOS exhibits an Ron,sp of 3.43 mΩ·cm² and a toff of 9 ns. Compared with traditional LDMOS devices, the proposed LDMOS possesses a 90% reduction in Ron,sp and an 11.6% decrease in toff. The proposed device not only achieves an excellent trade-off between Ron,sp and BV but also shortens the toff, demonstrating that the device achieves superior performance.
, , Received Date: 2024-09-01
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The Max-Cut Problem (MCP) is a classic problem in the field of combinatorial optimization and has important applications in various domains, including statistical physics and image processing. However, except for some special cases, the Max-Cut problem remains an NP-complete problem, and there is currently no known efficient classical algorithm that can solve it in polynomial time. The Quantum Approximate Optimization Algorithm (QAOA), as a pivotal algorithm in the Noisy Intermediate-Scale Quantum (NISQ) computing era, has shown significant potential for solving the Max-Cut problem. However, due to the lack of quantum error correction, the reliability of computations in NISQ systems sharply declines as the circuit depth of the algorithm increases. Therefore, designing an efficient, shallow-depth, and low-complexity QAOA for the Max-Cut problem is a critical challenge in demonstrating the advantages of quantum computing in the NISQ era.In this paper, based on the standard QAOA algorithm, we introduce Pauli Y rotation gates into the target Hamiltonian circuit for the Max-Cut problem. By enhancing the flexibility of quantum trial functions and improving the efficiency of Hilbert space exploration within a single iteration, we significantly improve the performance of QAOA on the Max-Cut problem.We conduct extensive numerical simulations using the MindSpore Quantum platform, comparing the proposed RY-layer-assisted QAOA with standard QAOA and its existing variants, including MA-QAOA and QAOA+. The experiments are performed on various graph types, including complete graphs, 3-regular graphs, 4-regular graphs, and random graphs with edge probabilities between 0.3 and 0.5. Our results demonstrate that the RY-layer-assisted QAOA achieves a higher approximation ratio across all graph types, particularly in regular and random graphs, where traditional QAOA variants struggle. Moreover, the proposed method exhibits strong robustness as the graph size increases, maintaining high performance even for larger graphs. Importantly, the RY-layer-assisted QAOA requires fewer CNOT gates and has a lower circuit depth compared to standard QAOA and its variants, making it more suitable for NISQ devices with limited coherence times and high error rates.In conclusion, the RY-layer-assisted QAOA offers a promising approach to solving Max-Cut problems in the NISQ era. By improving the approximation ratio while reducing circuit complexity, this method demonstrates significant potential for practical quantum computing applications, paving the way for more efficient and reliable quantum optimization algorithms.
, , Received Date: 2025-01-03
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This paper presents a novel convolutional neural network-based single-pixel imaging method that integrates a physics-driven fusion attention mechanism. By incorporating a module combining both channel and spatial attention mechanisms into a randomly initialized convolutional network, the method utilizes the physical model constraints of single-pixel imaging to achieve high-quality image reconstruction. Specifically, the spatial and channel attention mechanisms are combined into a single module and introduced into various layers of a multi-scale U-net convolutional network. In the spatial attention mechanism, we extract the attention weight features of each spatial region of the pooled feature map using convolution. In the channel attention mechanism, we pool the three-dimensional feature map into a single-channel signal and input it into a two-layer fully connected network to obtain the attention weight information for each channel. This approach not only leverages the critical weighting information provided by the attention mechanism in the three-dimensional data cube but also fully integrates the powerful feature extraction capabilities of the U-net network across different spatial frequencies. This innovative method effectively captures image details, suppresses background noise, and improves image reconstruction quality. During the experimental phase, we employed the optical path of single-pixel imaging to acquire bucket signals for two target images, “snowflake” and “basket”. By inputting any noise image into a randomly initialized neural network with an attention mechanism, and leveraging the mean square error between simulated and actual bucket signals, we physically constrained the network's convergence. Ultimately, we achieved a reconstructed image that adhered to the physical model. Experimental results demonstrate that, under low sampling rate conditions, the scheme that integrates the attention mechanism not only intuitively reconstructs image details better but also demonstrates significant advantages in quantitative evaluation metrics such as peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), verifying its effectiveness and potential for application in single-pixel imaging.
, , Received Date: 2025-02-01
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The spatial chirp based single-shot pump-probe technique represents a pivotal technology for studying electron non-equilibrium dynamics in warm dense matter created with intense laser pulses. Notably, its time resolution can reach tens of femtoseconds. In this work, we introduce the single-shot measurement technique of ac conductivity of warm dense matter, as well as a detailed account of the experimental setup. In addition, the main factors limiting the time resolution of the system are discussed in depth. We show the system can achieve a resolution of 13.8 femtoseconds. Nevertheless, during practical application, several aspects, namely the calibration of the zero-delay, the depth of field of the imaging system, and the low-pass filtering effect inherent in the imaging system, will exert a substantial influence on the time-resolution. This research has important reference for enhancing the time accuracy of single-shot measurement of ac conductivity of warm dense matter. Moreover, it serves as a potent tool for the in-depth study of the ultrafast dynamic processes of materials under strong-field conditions.
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Identifying the most influential nodes in the spreading process in complex networks is crucial in many applications, such as accelerating the diffusion of information and suppressing the spread of viruses or rumors. Existing methods for identifying influential spreaders have their limitations: classical network centrality methods rely solely on local or global topology to predict node influence; traditional machine learning and deep learning methods are not suitable for graph-structured data; and existing graph neural network-based methods neglect the dynamic characteristics of the propagation process itself. However, researches have pointed out that a node’s spreading influence does not only depend on its structural location, but is also significantly influenced by the dynamics of the spreading process itself. In this paper, we propose a Propagation Dynamics Graph Neural Network (PDGNN) that integrates the dynamic features of the propagation process and the structural features of nodes to identify influential nodes. Specifically speaking, based on the Susceptible-Infected-Recovered (SIR) propagation model, the dynamic infection features and potential infection capacity of nodes are extracted from the epidemic spreading process. Then a high-dimensional feature vector consisting of the embedding and the degree of the local transmission tree, and the dynamic sensitivity centrality of each node is constructed and used as the input to the graph neural network. To deal with the problem of imbalanced numbers between critical nodes and non-critical nodes in training the model and optimizing the output, an optimized loss function is designed, which combines Focal Loss with Mean Squared Error. Experimental results on two synthetic networks and seven real-world networks show that PDGNN outperforms classical centrality methods, traditional machine learning and deep learning-based methods, and existing graph neural network-based methods in identifying influential nodes in the spreading process in complex networks. The performance of PDGNN is robust when the infection rate and the size of the training set change. Under a wide range of infection rates, the proposed PDGNN can accurately identify influential spreaders. Even when the training set is 30% of the total dataset, the imprecision of PDGNN is small in all nine studied networks.
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Diamond coating has many excellent properties such as extreme hardness, high elastic modulus, high thermal conductivity, low friction coefficient, low thermal expansion coefficient, and good corrosion resistance that are close to natural diamond, making it an ideal new type of wear-resistant tool coating material. However, a large number of experiments have proved that during the deposition of diamond coating, the bonding phase cobalt on the surface of impregnated diamond substrate will generate a layer of graphite at the interface, seriously weakening the adhesive strength between the substrate and the coating. To thoroughly solve this problem, it is necessary to research the theory and microscopic process of graphitization caused by the Co element embedded on the substrate surface. Therefore, this article adopts the first principle theroy to simulate and analyze the interfacial adhesive strength of diamond coating when Co atom is embedded at different depths on the surface of impregnated diamond substrate, in order to explore the influence mechanism of the bonding phase Co element in the substrate on the diamond coating and the
mechanism of Co promoting diamond graphitization. The calculation results show that the interfacial binding energy decreases first and then increases with the increase of Co embedding depth in the substrate. When Co atom is embedded in the third layer, obvious graphite structures are prone to appear at the interface, and Co promotes diamond graphitization most significantly, resulting in the minimum bonding strength between the film and substrate interface. The results of structure and charge indicate that under the influence of surface effect and Co-C bond length, the C atom in the second layer of the substrate move to the first layer and the hybridization mode changes from sp3 to sp2. Meanwhile, this movement leads to an increase in the interaction space and quantity between Co and the surrounding C atoms. In addition, there are many unpaired electrons in the Co valence layer, which can easily mix and rearrange electron orbitals with the surrounding C atoms, ultimately resulting in a graphite structure on the substrate surface. When Co is embedded in the fifth layer, it no longer affects the stable configuration of the substrate surface and the interfacial adhesive strength.
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Microinverters have been widely used in distributed photovoltaic (PV) systems in recent years due to their modularity and flexibility. However, the current development of microinverter topologies faces significant challenges, such as low voltage gain and limited reliability. To address these problems, this paper proposes an Enhanced Switched-Inductor quasi-Z-Source inverter (ESL-qZSI) based on Gallium Nitride High Electron Mobility Transistor (GaN HEMT). The proposed inverter introduces a novel topology that integrates an auxiliary boost unit with a switched-inductor quasi-Z-source network. This topology significantly enhances the voltage gain under low shoot-through duty ratios and reduces the voltage stress across the switching devices. Additionally, the use of GaN HEMT as power switching components increases the switching frequency from the conventional 10 kHz to 100 kHz, in which a specialized negative turn-off gate driver circuit is proposed to adapt the characteristics of the GaN HEMT and to ensure reliable switching operation. This increase in frequency reduces the size of passive components, such as inductors. Experimental results show that the proposed inverter achieves a boost factor of 5.75 at a shoot-through duty ratio of 0.2, which indicates a 15% improvement and a 91% improvement greater than the results of the conventional switched-inductor-capacitor quasi-Z-source inverter (SLC-qZSI) and the conventional switched-inductor Z-source inverter (SL-ZSI), respectively. These results confirm that the proposed inverter enhances the voltage gain of existing topologies. Besides, compared with SLC-qZSI, the proposed inverter could obtain a higher efficiency of 90.5%, which exhibites the advantage of efficiency. In conclusion, the proposed ESL-qZSI with GaN HEMT provides a promising solution for high-efficiency and compact microinverter systems in photovoltaic applications.
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Infrared focal plane array (IRFPA) detector, a key research focus in next-generation infrared detection technology, plays a crucial role in optoelectronic sensing. Here, we report the integration and reliability of a PbSe-based IRFPA employing a row-column scanning readout architecture. The design features a surface passivation layer and through-hole structures to ensure robust electrical connectivity, enhancing both stability and performance. The detector, with dimensions of 3.5 mm×3.5 mm, a pixel size of 200 μm x 100 μm, and a pixel pitch of 200 μm, demonstrates structural integrity validated by electro-thermal simulations. At room temperature, pixel-level and imaging assessments reveal an average detectivity of 9.86×109 Jones and a responsivity of 1.03 A/W, with a 100% effective pixel yield. Remarkably, the device retains high stability, exhibiting only a 3.6% performance decline after 150 days of air exposure, attributed to the protective effects of the passivation layer. Infrared imaging across varied light intensities shows pronounced contrast, confirming the detector’s sensitivity to illumination gradients. These results offer critical technical insights and a theoretical framework for advancing high-performance, stable PbSe-based IRFPA detectors.
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Medium-entropy alloys (MEAs), known for their outstanding strength and ductility, offer great potential for high strain-rate applications. This study focuses on a NiCoV-based MEA system, where a novel alloy design strategy was proposed by introducing 5 at.% high-melting-point tungsten through vacuum arc melting coupled with thermomechanical processing to fabricate the (NiCoV)95 W5 alloy. Split Hopkinson pressure bar (SHPB) experiments were conducted to elucidate the dynamic response mechanisms and deformation behavior under high strain rates (2000-6000 s-1). The results show that the enhanced phonon drag effect at elevated strain rates, caused by severe lattice distortion, leads to a substantial increase of 162% in yield strength from 720 MPa (10-3 s-1) to 1887 MPa (6000 s-1), accompanying with a relatively high strain-rate sensitivity (m = 0.42); Microscopic analysis revealed the multi-scale cooperative deformation mechanism of the alloy system under high strain rate. When the strain rate is 2000 s-1, the alloy exhibits a low dislocation density dominated by dislocation planar slip. As the strain rate rises to 4000 s-1, elevated flow stress and deformation promote substantial dislocation multiplication and entanglement into high-density dislocation cells. Dislocation pile-up stress induces co-deformation of precipitates and releases stress concentration at the phase interface. Upon further increasing the strain rate to 6000 s-1, severe plastic deformation induces nano-twin formation within the matrix, as prevailing strain hardening. This study illustrates the tungsten-doping mediated dynamic response mechanisms in MEAs, providing a guidance for designing novel structural materials with excellent dynamic mechanical responses.
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The transition of Ga+ ions from 4s² ¹S₀ to 4s4p ³P₀ has advantages such as a high quality factor and a small motional frequency shift, making it suitable as a reference for precision measurement experiments like optical clocks. Calculating the dynamic polarizability of 4s21S0-4s4p 3P0 transition for Ga+ ion is of great significance for exploring the potential applications of the Ga+ ion in the field of quantum precision measurement and for testing atomic and molecular structure theories. In this paper, the dynamic polarizability of the Ga+ ion 4s² ¹S₀ - 4s4p ³P₀ transition is theoretically calculated using the relativistic configuration interaction plus many-body perturbation (CI+MBPT) method. The "tune-out" wavelength for the 4s² ¹S₀ state and the 4s4p ³P₀ state, as well as the "magic" wavelength for the 4s² ¹S₀ - 4s4p ³P₀ transition, are also computed. It is observed that the resonant lines situated near a certain “turn-out” and “magic” wavelength can provide dominant contributions to the polarizability, while the remaining resonant lines generally contribute minimally. These " tune-out " and "magic" wavelengths provide theoretical guidance for precise measurements and are important for studying the atomic structure of Ga+ ions. The accurate determination of the difference in static polarizability between the 4s² ¹S₀ and 4s4p ³P₀ states is of significant importance. Additionally, based on the "polarizability scale" method, the paper discusses how the theoretical calculation errors in static polarizability measurements vary with wavelength, offering theoretical guidance for the further high-precision determination of the static polarizability of the 4s² ¹S₀ and 4s4p ³P₀ states. This is crucial for minimizing the uncertainty of the blackbody radiation (BBR) frequency shift in Ga+ optical clock and suppressing the systematic uncertainty.
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Although the molecular strong-field approximation (SFA) theory has achieved significant achievements in characterising the ultrafast dynamics of molecules in strong laser fields, there are fundamental contradictions in the system itself. On the one hand, the basic principle of SFA requires that the initial state be an eigenstate of the system in the absence of the field, and on the other hand, the spatial translation invariance of the physical process requires that the initial state of the system should be a laser-field-dressed state, and these two contradictory requirements correspond to the two forms of molecular SFA theories, namely, the undressed and the dressed states, respectively, and the two theoretical validity and applicability conditions of these are widely disputed. In this paper we investigate the ionization processes of N2 and Ne2 molecules in (elliptically) circularly polarized laser fields, with the expectation of providing an answer to the above controversies. Elliptically polarized laser can efficiently suppress the re-scattering process and the influence of various interference effects, which makes the ionization process cleaner, and thus can effectively screen the applicable conditions for the dressed and undressed states. We have calculated the photoelectron momentum distributions corresponding to different molecular orbitals in the dressed and undressed states by using the strong-field approximation (SFA) and the Coulomb-corrected strong-field approximation (CCSFA) and compared them with the previous experimental results. For molecules with large nuclear spacing such as Ne$_{2}$, we find that the dressed state is necessary to accurately characterise their ionization, whereas for molecules with small nuclear spacing such as N$_{2}$, the dressed state description is not applicable. The conclusions of this paper provide a reference for the accurate description of laser-induced molecular ultrafast processes and the further development of the corresponding theories, and provides a reference for the further development of molecular ultrafast imaging schemes.
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Understanding the oxygen bubble evolution on the electrode surface is important to enhance the efficiency of large-scale water decomposition. In this paper, a numerical model for the growth of oxygen bubbles on the electrode surface based on the dissolved oxygen flux at the bubble boundary is proposed, and the mechanisms of the reaction area and current on the bubble growth are investigated. The results show that the bubble diameters calculated from the oxygen flux at the bubble boundary are in good agreement with the growth of the bubbles in the control phase of the chemical reaction. As the reaction region increases, the transition time from the diffusion-controlled to the chemical reaction-controlled stage becomes longer during the bubble growth. The concentration maximum on the microelectrode surface is significantly higher than that on the large electrode surface, which leads to a steeper concentration gradient between the microelectrode surface and the bubble surface. As the current increases, the bubble growth rate increases and the time coefficient decreases faster. The bubble diameter at a current of 0.06 mA agrees well with the bubble diameter at a current of 0.1 mA in the photoelectrochemical water splitting experiments. This is because the scattering of light by the growing bubbles leads to a decrease in the current density at the bottom of the bubble.
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The monolayer ferroelectric semiconductor Ga2S3 has drawn extensive attention because of its outstanding ductility, extremely high carrier mobility and unique out-of-plane asymmetric polarization characteristics. Utilizing out-of-plane asymmetric polarization characteristics of Ga2S3, we construct the T-NbTe2/Ga2S3ferroelectric heterojunctions. By the first-principles calculations, we systemically study structural stability, preparation possibility and electrical contact properties for various ferroelectric heterojunction T-NbTe2/Ga2S3 with the different polarization directions of Ga2S3. We find that heterojunctions T-NbTe2/Ga2S3exhibit sensitive responses to out-of-plane asymmetric polarization characteristics of Ga2S3. The most energy-stable heterojunctions PD1 ($\vec{P}$ downward) and PU2 ($\vec{P}$ upward) in the intrinsic state form N-type and P-type Schottky contacts, respectively. Changing the polarization characteristics of the ferroelectric semiconductor Ga2S3 can alter the contact type of the Schottky barrier in the ferroelectric heterojunction T-NbTe2/Ga2S3, which provide a practical approach for designing multifunctional Schottky devices. Specifically, the electrical contact depends on the external electric field. For heterojunctions PD1 (PU2), the contact can be transited from Schottky contact to Ohmic contact at electric field strength +0.5 V/Å (+0.6 V/Å). Besides electric field, the contact property of both heterojunctions PD1 and PU2 may also be tuned by external biaxial strain. For heterojunctions PD1, the contact can be transited from Schottky contact to Ohmic contact at the biaxial strain tensile 8%. And for heterojunctions PU2, the contact can be transited from P-type Schottky contact to N-type Schottky contact at the biaxial strain tensile 2%, then from N-type Schottky contact to Ohmic contact at the strain tensile 10%.These results provide a theoretical reference for two-dimensional ferroelectric nanodevices with high-performance electrical contact interfaces.
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Secondary hardening ultra-high-strength steel is widely utilized in aerospace and other advanced engineering applications, with the nanoscale M2C precipitates serving as the primary strengthening factor. Mo plays a crucial role in the formation of the Mo2C secondary hardening phase, which can form composite M2C precipitates with elements such as Cr, V, and W, thereby modifying the composition and properties of Mo2C. To investigate the effects of V and W doping on Mo2C, this study employs first-principles calculations to analyze the formation enthalpy, electronic structure, and mechanical properties of the doped systems. The CASTEP module is utilized in this study, with the Perdew-Burke-Ernzerhof (PBE) functional adopted within the generalized gradient approximation (GGA) framework. The results indicate that V doping reduces the lattice parameters and decreases the formation enthalpy, thereby enhancing structural stability. In contrast, W doping increases the lattice parameters and lowers the formation enthalpy but leads to reduced structural stability. In terms of mechanical properties, V doping decreases toughness while increasing hardness, whereas W doping improves the strength-toughness balance by mitigating the rate of hardness reduction. Covalent bonds are formed within the system, with V and W doping altering their characteristics: compared to the C-Mo bond, the C-V bond exhibits weaker covalency, while the C-W bond displays stronger covalency. Additionally, V doping enhances the stability of Mo-C bonds, whereas W doping reduces their stability. Charge population analysis reveals that metal atoms (Mo, V, and W) act as electron donors, while carbon atoms act as electron acceptors.
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