摘要：
We propose a theoretical scheme for realizing a two-dimensional (2D) asymmetric diffraction grating in a four-level quantum dot molecules (QDMs) system with double tunneling effects. The QDMs system interacts with a weak probe field, a 2D SW control field and a composite Laguerre-Gaussian (LG) vortex field. By adjusting system parameters such as the orbital angular momentum (OAM) number, the beam waist parameter of the vortex light, the tunneling strength, and the detuning of the standing-wave (SW) field, the energy distribution and the diffraction intensity of the probe field can be controlled effectively. In addition, the detuning of the probe field
can be used to achieve the symmetrical switching control of the 2D diffraction grating between the second and the fourth quadrants.
This investigation may have potential application in beam splitting technology and optical device design.
摘要：
Microorganisms play a key role in fish spoilage and quality deterioration, making the development of a rapid, accurate, and efficient technique for detecting surface microbes essential for enhancing freshness and ensuring the safety of mandarin fish consumption. This study focused on the total viable count (TVC) and Escherichia coli levels in the dorsal and ventral parts of fish, and we constructed a detection model using hyperspectral imaging and data fusion. The results showed that comprehensive and simplified models were successfully developed for quantitative detection across all wavelengths. The models performed best at predicting microbial growth on the dorsal side, with the RAW-CARS-PLSR model proving the most effective at predicting TVC and E. coli counts in that region. The RAW-PLSR model was identified as the optimal predictor of the E. coli concentration on the ventral side. A fusion model in the decision layer constructed using the Dempster-Shafer theory of evidence outperformed models relying solely on spectral or textural information, making it an optimal approach for detecting surface microbes in mandarin fish. The best prediction accuracy for dorsal TVC concentration achieved an Rp value of 0.9337, whereas that for ventral TVC concentration reached 0.8443. For the E. coli concentration, the optimal R(p) values were 0.8180 for the dorsal section and 0.8512 for separate analysis.
期刊：
Surfaces and Interfaces,2025年57:105743 ISSN：2468-0230
通讯作者：
Zhao, X;Wu, SJ
作者机构：
[Chen, Luocheng] Hubei Sino Australian Nano Mat Technol Ltd Co, Guangshui 432700, Peoples R China.;[Zhao, X; Zhao, Xu; Chen, Luocheng] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.;[Wu, Sujuan; Cai, Hengzhuo; Wu, SJ; Luo, Xinyi] South China Normal Univ, Inst Adv Mat, South China Acad Adv Optoelect, Guangzhou 510006, Peoples R China.;[Wu, Sujuan; Cai, Hengzhuo; Wu, SJ; Luo, Xinyi] South China Normal Univ, South China Acad Adv Optoelect, Guangdong Prov Key Lab Quantum Engn & Quantum Mat, Guangzhou 510006, Peoples R China.
通讯机构：
[Zhao, X ] W;[Wu, SJ ] S;Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.;South China Normal Univ, Inst Adv Mat, South China Acad Adv Optoelect, Guangzhou 510006, Peoples R China.;South China Normal Univ, South China Acad Adv Optoelect, Guangdong Prov Key Lab Quantum Engn & Quantum Mat, Guangzhou 510006, Peoples R China.
关键词：
1-butyl-3-methylimidazolium p-;toluenesulfonate;PEDOT:PSS/perovskite interface;photoelectrical properties;Pure Sn-based perovskite solar cells
摘要：
Poly(3,4-ethylenedioxythiophene)-polystyrene sulfonate (PEDOT:PSS) film can absorb moisture from the air, which will become a potential challenge to accelerate the degradation of perovskite solar cells (PSCs). The acidity of PEDOT:PSS can damage the adjacent ITO and perovskite layer, resulting in deteriorating the stability of PSCs. Moreover, the level energy misalignment at the interface will lead to carrier recombination and reducing the efficiency of device. To resolve these problem in PEDOT:PSS layer, the 1‑butyl‑3-methylimidazolium p-toluenesulfonate (BMT) with imidazole and sulfonic acid dual-functional groups is used to modify the PEDOT:PSS film in pure tin-based perovskite solar cells (T-PSCs). The effects of BMT modification on the micrograph and photoelectrical properties of PEDOT:PSS and pure Sn-based perovskite layer, and the photovoltaic performance of T-PSCs have been thoroughly studied. It is found that the BMT modification not only improves the conductivity of the PEDOT:PSS layer but also adjusts its work function, facilitates the hole extraction and transport at the PEDTO:PSS/perovskite interface, leading to significantly increasing the open-circuit voltage. In addition, the perovskite films based on BMT-modified PEDOT:PSS (BMT-PEDOT:PSS) exhibit the improved microstructure and higher Sn²⁺/Sn 4 ⁺ ratio. Thus, the T-PSCs based on the BMT-PEDOT:PSS (BMT-PSCs) at the optimized BMT concentration reach a champion efficiency of 8.74 %, which is higher than the 6.94 % of reference device. Furthermore, the BMT-PSCs demonstrate better long-term stability in N 2 atmosphere. This work provides a simple strategy to regulate the burried PEDOT:PSS/perovkite interface and improve the photovoltaic performance and stability of T-PSCs by a dual-functional material.
Poly(3,4-ethylenedioxythiophene)-polystyrene sulfonate (PEDOT:PSS) film can absorb moisture from the air, which will become a potential challenge to accelerate the degradation of perovskite solar cells (PSCs). The acidity of PEDOT:PSS can damage the adjacent ITO and perovskite layer, resulting in deteriorating the stability of PSCs. Moreover, the level energy misalignment at the interface will lead to carrier recombination and reducing the efficiency of device. To resolve these problem in PEDOT:PSS layer, the 1‑butyl‑3-methylimidazolium p-toluenesulfonate (BMT) with imidazole and sulfonic acid dual-functional groups is used to modify the PEDOT:PSS film in pure tin-based perovskite solar cells (T-PSCs). The effects of BMT modification on the micrograph and photoelectrical properties of PEDOT:PSS and pure Sn-based perovskite layer, and the photovoltaic performance of T-PSCs have been thoroughly studied. It is found that the BMT modification not only improves the conductivity of the PEDOT:PSS layer but also adjusts its work function, facilitates the hole extraction and transport at the PEDTO:PSS/perovskite interface, leading to significantly increasing the open-circuit voltage. In addition, the perovskite films based on BMT-modified PEDOT:PSS (BMT-PEDOT:PSS) exhibit the improved microstructure and higher Sn²⁺/Sn 4 ⁺ ratio. Thus, the T-PSCs based on the BMT-PEDOT:PSS (BMT-PSCs) at the optimized BMT concentration reach a champion efficiency of 8.74 %, which is higher than the 6.94 % of reference device. Furthermore, the BMT-PSCs demonstrate better long-term stability in N 2 atmosphere. This work provides a simple strategy to regulate the burried PEDOT:PSS/perovkite interface and improve the photovoltaic performance and stability of T-PSCs by a dual-functional material.
通讯机构：
[Zhang, D ] W;Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.
关键词：
asymmetric diffraction grating;standing-wave field;laguerre-gaussian vortex field;diffraction property;semiconductor quantum well
摘要：
We present a theoretical scheme to realize two-dimensional (2D) asymmetric diffraction grating in a five-level inverted Y-type asymmetric double semiconductor quantum wells (SQWs) structure with resonant tunneling. The SQW structure interacts with a weak probe laser field, a spatially independent 2D standing-wave (SW) field, and a Laguerre-Gaussian (LG) vortex field, respectively. The results indicate that the diffraction patterns are highly sensitive to amplitude modulation and phase modulation. Because of the existence of vortex light, it is possible to realize asymmetric high-order diffraction in the SQW structure, and then a 2D asymmetric grating is established. By adjusting the detunings of the probe field, vortex field, and SW field, as well as the interaction length, diffraction intensity, and direction of the 2D asymmetric electromagnetically induced grating (EIG) can be controlled effectively. In addition, the number of orbital angular momenta (OAM) and beam waist parameter can be used to modulate the diffraction intensity and energy transfer of the probe light in different regions. High-order diffraction intensity is enhanced and high-efficiency 2D asymmetric diffraction grating with different diffraction patterns is obtained in the scheme. Such 2D asymmetric diffraction grating may be beneficial to the research of optical communication and innovative semiconductor quantum devices.
摘要：
The extended quantum Ising model serves as a paradigmatic model for studying topological quantum phase transitions (TQPTs), which entail fundamental changes in the system's global topological order. In this work, we employ nonlocality spectrum { | λ i | } as the central tool to probe multipartite nonlocal correlations and quantum criticality in this model. Our analysis reveals that the leading one in the spectrum satisfies | λ 1 | > 1 in most parameter regimes, confirming pervasive multipartite nonlocal correlations in the ground states. Furthermore, the spectral gap Δ | λ | universally vanishes at all TQPT points in the model, establishing it as a robust and derivative-free marker for TQPTs. These results highlight the utility of nonlocality spectrum in characterizing both multipartite nonlocal correlations and TQPTs in one-dimensional (1D) quantum systems.
The extended quantum Ising model serves as a paradigmatic model for studying topological quantum phase transitions (TQPTs), which entail fundamental changes in the system's global topological order. In this work, we employ nonlocality spectrum { | λ i | } as the central tool to probe multipartite nonlocal correlations and quantum criticality in this model. Our analysis reveals that the leading one in the spectrum satisfies | λ 1 | > 1 in most parameter regimes, confirming pervasive multipartite nonlocal correlations in the ground states. Furthermore, the spectral gap Δ | λ | universally vanishes at all TQPT points in the model, establishing it as a robust and derivative-free marker for TQPTs. These results highlight the utility of nonlocality spectrum in characterizing both multipartite nonlocal correlations and TQPTs in one-dimensional (1D) quantum systems.
摘要：
This study introduces a sandwich structure model and employs the Monte Carlo (MC) technique to investigate the electromagnetic interference shielding effectiveness (EMI SE) of carbon nanotubes (CNT) nanocomposite foams. Firstly, a two-dimensional Voronoi diagram to simulate the composite foam structure is established. Then, by assuming that the edges of the polygon have a sandwich structure of insulator-conductor-insulator type, we evaluate the optical transmission matrix of the sandwich structure and calculate the transmission and reflection probabilities. Finally, the MC method is used to model the path of numerous light rays entering the composite foams. By statistically analyzing the electromagnetic fields of waves that are transmitted and reflected, we obtained the electromagnetic shielding properties of composite foams in the X-band frequency range. The results indicate that the foams amplify the multiple reflections of electromagnetic waves, thereby increasing its capacity to absorb electromagnetic energy. It is demonstrated that the variation of SE with CNT concentration matches well with the experimental findings. A detailed study is conducted on the effects of foam size, sandwich structure thickness and conductivity, and electromagnetic wave frequency on SE.
作者机构：
[Bu, Lingxin] North Minzu Univ, Coll Mechatron Engn, Yinchuan 750021, Ningxia, Peoples R China.;[Sugirbay, Adilet] West Kazakhstan Agr & Tech Univ Zhangir Khan, Polytech Inst, Uralsk 090009, Kazakhstan.;[Li, Teng] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.
通讯机构：
[Li, T ] W;Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.
关键词：
apple harvesting;dynamic simulation;finite element method;fruit detachment;picking pattern;picking planning
摘要：
Robotic apple harvesting requires the motion planning of a series of movements to perform the efficient picking of fruit without bruises. To optimize the picking motion of apple-harvesting robots and reduce the payload at the end of the robotic arm, this study establishes a finite element model of the branch-stem-apple system. A four-factor, three-level simulation experiment is designed to investigate the horizontal velocity, vertical velocity, bending angular velocity, and torsional angular velocity. The analysis of variance (ANOVA) and response surface methodology (RSM) analysis reveal that the four factors significantly influence the fruit detachment force. By minimizing the fruit detachment force, the simulation results of the optimized parameters suggest that horizontal pulling with bending is the optimized picking motion. The optimized parameters were tested in both simulation and field verification trials, demonstrating a high degree of consistency between the predicted detachment force and experimental measurements without causing fruit bruising during the picking process.
关键词：
Gas sensor materials;Oil-immersed transformer;DFT;Pt-WS2;Cu-WS2
摘要：
In this work, the sensing characteristics of transition metal (Au, Pt, Fe, Rh, Cu) doped WS 2 for faulty decomposition gases (CO, CH 4 , C 2 H 2 , C 2 H 4 ) in oil-immersed transformers were studied using density functional theory (DFT). The analysis showed that pristine WS 2 had limited adsorption capacity for these gases. After comparing two doping sites, the more stable TM-WS 2 structure was selected. Due to weak binding, Au-WS 2 was excluded from further analysis. Adsorption structures were optimized, and interactions between the gas molecules and TM-WS 2 were analyzed through binding energies, charge transfer, band gaps, and density of states . Results showed that doped WS 2 exhibited enhanced gas adsorption compared to pristine WS 2 . Pt-WS 2 showed excellent performance for CH 4 , Rh-WS 2 for C 2 H 4 , and Cu-WS 2 for C 2 H 2 , with short response times and high detection efficiency. This work provides insights into the design of gas-sensing materials based on TM-WS 2 .
In this work, the sensing characteristics of transition metal (Au, Pt, Fe, Rh, Cu) doped WS 2 for faulty decomposition gases (CO, CH 4 , C 2 H 2 , C 2 H 4 ) in oil-immersed transformers were studied using density functional theory (DFT). The analysis showed that pristine WS 2 had limited adsorption capacity for these gases. After comparing two doping sites, the more stable TM-WS 2 structure was selected. Due to weak binding, Au-WS 2 was excluded from further analysis. Adsorption structures were optimized, and interactions between the gas molecules and TM-WS 2 were analyzed through binding energies, charge transfer, band gaps, and density of states . Results showed that doped WS 2 exhibited enhanced gas adsorption compared to pristine WS 2 . Pt-WS 2 showed excellent performance for CH 4 , Rh-WS 2 for C 2 H 4 , and Cu-WS 2 for C 2 H 2 , with short response times and high detection efficiency. This work provides insights into the design of gas-sensing materials based on TM-WS 2 .
摘要：
The rapid changes in the global environment have led to an unprecedented decline in biodiversity, with over 28% of species facing extinction. This includes snakes, which are key to ecological balance. Detecting snakes is challenging due to their camouflage and elusive nature, causing data loss and feature extraction difficulties in ecological monitoring. To address these challenges, we propose an enhanced snake detection model, Snake-DETR, based on RT-DETR, specifically designed for snake detection in complex natural environments. First, we designed the Enhanced Generalized Efficient Layer Aggregation Network Based on Context Anchor Attention, which enhances the feature extraction capability for occluded snakes by aggregating critical layer information and strengthening context-dependent feature extraction. Additionally, we introduced the Enhanced Feature Extraction Backbone Network Based on Context Anchor Attention, which manages input information using multiple Enhanced Generalized Efficient Layer Aggregation Networks to retain essential spatial and semantic information. Subsequently, a lightweight Group-Shuffle Convolution is used to optimize the encoder, which reduces dependency on large-scale training data, thereby making it suitable for deployment on edge devices. Finally, we incorporated the Powerful-IoU loss function to improve regression path accuracy. Experimental results on a custom dataset covering 27 snake species demonstrate that Snake-DETR achieves a good balance between model efficiency and detection performance, meeting the requirements for fine-grained snake object detection. Compared to other state-of-the-art models, Snake-DETR achieved an accuracy of 97.66%, a recall rate of 93.92%, mAP@0.5 of 95.23%, and mAP@0.5:0.95 of 72.15%, all outperforming other algorithms in the comparative tests. Furthermore, the computational load and parameter count of the model are reduced by 47.2 and 52.2%, respectively, compared to the benchmark model. Additionally, the real-time processing capability is 43.5 frames per second, meeting the demand for real-time processing. Snake-DETR demonstrates excellent performance in complex environments and is suitable for wild snake fauna monitoring and edge device deployment, providing key technical support for ecological research.
关键词：
Co doped nanoclusters;Ferromagnetic coupling;Co-doping;First principle calculation
摘要：
To explore stable magnetic semiconductor clusters, Zn12Se12 was selected as the host material, Co doped and III (B, Al, Ga) element co-doped Zn12Se12 clusters were investigated with first principle all-electron calculations. Geometry optimization, frequency calculations and dynamics simulations were performed to determine stable clusters. The analysis revealed that in Co doped Co2Zn10Se12 clusters, two Co atoms preferentially substituted for adjacent Zn atoms in opposite vertices of a rhombus, resulting in the shortest Co-Co distance. The introduction of III (B, Al, Ga) elements generated the most stable Co2IIIZn9Se12 cluster, where two Co atoms replaced adjacent Zn atom sites, and III atoms replaced the Zn atom site nearest to the Se atom between the two Co atoms. Energy differences between ferromagnetic and antiferromagnetic states indicated that the Co2Zn10Se12 clusters exhibited an antiferromagnetic coupling state, whereas the Co2IIIZn9Se12 clusters exhibited ferromagnetic coupling states. A detailed analysis of electron density and electronic configurations for Co element was conducted to uncover the magnetic coupling mechanism. It was found that the introduction of III elements as donor doping decreased the Co-Se hybridization, which reduced the antiferromagnetic superexchange coupling while forming the Se-Co-Se-III bonds with an excess electron, thereby enhancing the Co-Co ferromagnetic double-exchange coupling. The strategy of III element co-doping facilitated ferromagnetic double-exchange coupling between Co atoms, providing valuable insights for the exploration of new dilute magnetic semiconductor materials.
To explore stable magnetic semiconductor clusters, Zn12Se12 was selected as the host material, Co doped and III (B, Al, Ga) element co-doped Zn12Se12 clusters were investigated with first principle all-electron calculations. Geometry optimization, frequency calculations and dynamics simulations were performed to determine stable clusters. The analysis revealed that in Co doped Co2Zn10Se12 clusters, two Co atoms preferentially substituted for adjacent Zn atoms in opposite vertices of a rhombus, resulting in the shortest Co-Co distance. The introduction of III (B, Al, Ga) elements generated the most stable Co2IIIZn9Se12 cluster, where two Co atoms replaced adjacent Zn atom sites, and III atoms replaced the Zn atom site nearest to the Se atom between the two Co atoms. Energy differences between ferromagnetic and antiferromagnetic states indicated that the Co2Zn10Se12 clusters exhibited an antiferromagnetic coupling state, whereas the Co2IIIZn9Se12 clusters exhibited ferromagnetic coupling states. A detailed analysis of electron density and electronic configurations for Co element was conducted to uncover the magnetic coupling mechanism. It was found that the introduction of III elements as donor doping decreased the Co-Se hybridization, which reduced the antiferromagnetic superexchange coupling while forming the Se-Co-Se-III bonds with an excess electron, thereby enhancing the Co-Co ferromagnetic double-exchange coupling. The strategy of III element co-doping facilitated ferromagnetic double-exchange coupling between Co atoms, providing valuable insights for the exploration of new dilute magnetic semiconductor materials.
摘要：
High-voltage gas-insulated switchgear (GIS) experiences insulation aging and related issues during prolonged operation, which significantly reduces the stability and safety of energy power equipment. Therefore, real-time monitoring and assessment of the insulation condition of these devices is essential. This study, based on first-principles calculations, reveals the gas-sensitive properties of decomposition gases of SF 6 and its five insulation defects on the surfaces of AlN and Pt 2 –AlN at the quantum level by calculating the electronic density (total electronic density, differential electronic density, and spin density), density of states (total and partial density of states), and the Integrated Crystal Orbital Hamilton Population (ICOHP). Notably, the modification of the Pt 2 cluster significantly enhances the electronic properties of AlN, improving the overall conductivity of the system. Furthermore, the adsorption properties of the p-type semiconductor Pt 2 -ALN for H 2 S are improved, and calculations of the work function, band gap, and its rate of change indicate that the doped structure possesses the potential to be used as a sensor. Additionally, we explored the feasibility of AlN (targeting SO 2 ) and Pt 2 –AlN (targeting H 2 S) as insulation defect warning materials under different environmental conditions. The results of the sensor application calculations demonstrate that AlN possesses the capability for SO 2 purification and can function as a disposable embedded sensor array, while Pt 2 –AlN shows promise as a sustainable sensor material for H 2 S monitoring at room temperature (300 K), with a desorption time of 0.46 s. Our research aims to provide new insights into semiconductor sensor monitoring of SF 6 gas-insulated equipment and offers guidance for the development of novel materials and sensor devices.
High-voltage gas-insulated switchgear (GIS) experiences insulation aging and related issues during prolonged operation, which significantly reduces the stability and safety of energy power equipment. Therefore, real-time monitoring and assessment of the insulation condition of these devices is essential. This study, based on first-principles calculations, reveals the gas-sensitive properties of decomposition gases of SF 6 and its five insulation defects on the surfaces of AlN and Pt 2 –AlN at the quantum level by calculating the electronic density (total electronic density, differential electronic density, and spin density), density of states (total and partial density of states), and the Integrated Crystal Orbital Hamilton Population (ICOHP). Notably, the modification of the Pt 2 cluster significantly enhances the electronic properties of AlN, improving the overall conductivity of the system. Furthermore, the adsorption properties of the p-type semiconductor Pt 2 -ALN for H 2 S are improved, and calculations of the work function, band gap, and its rate of change indicate that the doped structure possesses the potential to be used as a sensor. Additionally, we explored the feasibility of AlN (targeting SO 2 ) and Pt 2 –AlN (targeting H 2 S) as insulation defect warning materials under different environmental conditions. The results of the sensor application calculations demonstrate that AlN possesses the capability for SO 2 purification and can function as a disposable embedded sensor array, while Pt 2 –AlN shows promise as a sustainable sensor material for H 2 S monitoring at room temperature (300 K), with a desorption time of 0.46 s. Our research aims to provide new insights into semiconductor sensor monitoring of SF 6 gas-insulated equipment and offers guidance for the development of novel materials and sensor devices.
作者机构：
[Jingying Liu; Kexin Dong; Qiuyu Deng; Nan Luo; Pinghao Shao; Ling Xiong] Key Laboratory of Fermentation Engineering (Ministry of Education), National “111” Center for Cellular Regulation and Molecular Pharmaceutics, Hubei Key Laboratoy of Industrial Microbiology, Hubei Research Center of Food Fermentation Engineering and Technology, Hubei University of Technology, Hubei, Wuhan, 430068;Zhengzhou Food Engineering Vocational College, Henan, Zhengzhou 451100;School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Hubei, Wuhan 430048;Hubei Kemai Agricultural Science and Technology Co., Ltd. Hubei, Wuhan 430086;[Yaping Chen] Zhengzhou Food Engineering Vocational College, Henan, Zhengzhou 451100<&wdkj&>Hubei Kemai Agricultural Science and Technology Co., Ltd. Hubei, Wuhan 430086
通讯机构：
[Wei Li] K;Key Laboratory of Fermentation Engineering (Ministry of Education), National “111” Center for Cellular Regulation and Molecular Pharmaceutics, Hubei Key Laboratoy of Industrial Microbiology, Hubei Research Center of Food Fermentation Engineering and Technology, Hubei University of Technology, Hubei, Wuhan, 430068<&wdkj&>Hubei Kemai Agricultural Science and Technology Co., Ltd. Hubei, Wuhan 430086
摘要：
Dehydroepiandrosterone (DHEA) widely exists in the epidermis of sweet potato crops, which is a kind of adrenal hormone precursor secreted by theicular layer of the adrenal cortex in the human body and is used to manufacture intermediate products of steroid hormone drugs, and has the effects of anti-aging and protein anabolism We summarized the green extraction technology and bio-synthesis methods of DHEA in sweet potatoes, and reviewed the application of DHEA antioxidant, anti-fatigue, anti-tumor and anti-inflammatory functions in the human body and the mechanism of playing these effects, and looked forward to the prospects safety of DHEA in the development and application of dietary supplements. It provides references for the research of dehydroepiandrosterone in the future processing and functional foods.
Dehydroepiandrosterone (DHEA) widely exists in the epidermis of sweet potato crops, which is a kind of adrenal hormone precursor secreted by theicular layer of the adrenal cortex in the human body and is used to manufacture intermediate products of steroid hormone drugs, and has the effects of anti-aging and protein anabolism We summarized the green extraction technology and bio-synthesis methods of DHEA in sweet potatoes, and reviewed the application of DHEA antioxidant, anti-fatigue, anti-tumor and anti-inflammatory functions in the human body and the mechanism of playing these effects, and looked forward to the prospects safety of DHEA in the development and application of dietary supplements. It provides references for the research of dehydroepiandrosterone in the future processing and functional foods.
关键词：
The European Physical Journal B;Condensed Matter;Complex Systems;journal;EPJ
摘要：
In this paper, we investigate quantum Fisher information (QFI) density in the ground state of the one-dimensional infinite-size extended quantum Ising model, a system known for its rich phase diagram and topological quantum phase transitions. Notably, the QFI density itself displays clear signatures at many critical points, making it a better indicator compared to previously used two-qubit QFI (which depends upon a two-qubit reduced density matrix). This advantage stems from the QFI density’s reliance on all two-qubit reduced density matrices in the ground state, rather than just one. Beyond critical phenomena, we explore the connection between QFI density and quantum entanglement. We identify wide regions where metrologically useful entanglement is present and consequently quantum-enhanced metrology is expected. Furthermore, the QFI density shows peaks in the vicinity of some critical points, suggesting the possibility of criticality-enhanced metrology. Overall, our results demonstrate that the QFI density serves as a powerful tool for characterizing both quantum criticality and metrologically useful entanglement in the extended quantum Ising model, offering valuable insights for both theoretical understanding and future experimental investigations in quantum metrology and quantum criticality.
摘要：
Segmenting roof planes from airborne LiDAR point cloud data is essential for three-dimensional (3D) building reconstruction. However, the presence of discrete point clouds and complex roof structures present significant challenges to effective roof plane segmentation. To address this, a roof plane segmentation method that leverages multi--scale voxels and graph cuts is proposed. First, an octree voxelizes the original point cloud, generating multi--scale voxels based on geometric features to precisely characterize the data. Next, a bottom--up hierarchical clustering algorithm progressively merges these multi--scale voxels to obtain initial segmentation results. Finally, graph cuts refine the initial segmentation results and address boundary aliasing. The proposed method demonstrates superior performance, achieving roof plane segmentation accuracy of over 92. 6% compared to four other methods. The proposed method accurately enables the generation of accurate roof planes for 3D building reconstruction.
期刊：
QUANTUM INFORMATION PROCESSING,2025年24(11):1-20 ISSN：1570-0755
通讯作者：
Zhao-Yu Sun
作者机构：
[Fan-Qin Xu; Hong-Guang Cheng; Ze-Xing Lu; Zhao-Yu Sun] School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan, China
通讯机构：
[Zhao-Yu Sun] S;School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan, China
摘要：
Multipartite nonlocality, a phenomenon in many-body quantum systems which cannot be explained by any local realistic theory, can be witnessed using Bell-type inequalities and Mermin–Klyshko–Svetlichny (MKS) operators. While numerical optimizations are commonly employed in this context, they leave several important questions unresolved. For instance, an intuitive physical understanding of the optimal MKS operators remains elusive. In this paper, we derive analytical solutions for ground-state multipartite nonlocality in a cluster-Ising model. The analytical solutions help us to improve the transfer matrix theory of nonlocality and provide a deep insight into the nature of MKS operators by connecting them to string-order operators composed of standard Pauli operators (e.g.,
$$\hat{\sigma }^x$$
) and spin ladder operators (e.g.,
$$\hat{S}^{\pm }$$
). The findings pave the way for both theoretical advancements and experimental applications.
关键词：
All data in this work were obtained from the Web of Science database. Keywords searched include “SF6;decomposition;gas sensor;adsorption;DFT;etc.”. After an initial manual screening;a total of 52 research efforts from the past decade (from 2014 to 2024) were selected;focusing on the exploration of gas-sensitive materials for SF6 decomposition products;yielding 250 sets of adsorption data [26];[42] With the help of VOS Viewer software;the collected papers on SF6 decomposition products were clustered and analyzed;and the data were visualized by the keyword co-occurrence mapping module;as shown in Fig. S1 (a);(b) and (c). Fig. S1 (a) presents the changes in the research hotspots related to SF6 decomposition products during the five-year period from 2018 to 2022. Obviously;until 2020;some keywords can be observed;such as ‘decomposition’;‘voltage’;‘characteristic’;‘gas mixture’.
摘要：
The man-made gas sulfur hexafluoride (SF6) is an excellent and stable insulating medium. However, some insulation defects can cause SF6 to decompose, threatening the safe operation of power grids. Based on this, it is of great significance to find and effectively control the decomposition products of SF6 in time. Gas sensors have proven to be an effective way to detect these decomposition gases (SO2, SOF2, SO2F2, H2S, and HF). Nanomaterials with gas-sensitive properties are at the heart of gas sensors. In recent years, data-driven machine learning (ML) has been widely used to predict material properties and discover new materials. However, it has become a major challenge to establish a common model between material properties derived from various types of calculations and intelligent algorithms. In order to make some progress in addressing this challenge. In this work, 250 data sets were extracted from 52 publications exploring the detection of SF6 decomposition products by nanocomposites based on relevant work over the past 10 years, and the adsorption behavior of SF6 decomposition products can be predictively analyzed. By comparing six different algorithmic models, the best model for predicting the adsorption distance (XGBoost: R2 = 91.94 %) and adsorption energy (GBR: R2 = 78.63 %) of SF6 decomposed gas was identified. Subsequently, the importance of each of the selected feature descriptors in predicting the gas adsorption effect was explained. This work combines first-principles computational results and machine-learning algorithms with each other to provide a new research idea for evaluating the gas sensing capability of nanocomposites.
The man-made gas sulfur hexafluoride (SF6) is an excellent and stable insulating medium. However, some insulation defects can cause SF6 to decompose, threatening the safe operation of power grids. Based on this, it is of great significance to find and effectively control the decomposition products of SF6 in time. Gas sensors have proven to be an effective way to detect these decomposition gases (SO2, SOF2, SO2F2, H2S, and HF). Nanomaterials with gas-sensitive properties are at the heart of gas sensors. In recent years, data-driven machine learning (ML) has been widely used to predict material properties and discover new materials. However, it has become a major challenge to establish a common model between material properties derived from various types of calculations and intelligent algorithms. In order to make some progress in addressing this challenge. In this work, 250 data sets were extracted from 52 publications exploring the detection of SF6 decomposition products by nanocomposites based on relevant work over the past 10 years, and the adsorption behavior of SF6 decomposition products can be predictively analyzed. By comparing six different algorithmic models, the best model for predicting the adsorption distance (XGBoost: R2 = 91.94 %) and adsorption energy (GBR: R2 = 78.63 %) of SF6 decomposed gas was identified. Subsequently, the importance of each of the selected feature descriptors in predicting the gas adsorption effect was explained. This work combines first-principles computational results and machine-learning algorithms with each other to provide a new research idea for evaluating the gas sensing capability of nanocomposites.
关键词：
Greenhouse gases;DFT;HfSe (2) monolayers;Adsorption and sensing
摘要：
As greenhouse gas (GHG) emissions continue to rise, it is important to develop effective ways to detect and remove them. This study uses density functional theory (DFT) to look at how four common GHGs (CO 2 , CH 4 , N 2 O, and SF 6 ) are adsorbed and sensed on HfSe 2 monolayers with single-atom vacancies (Hf and Se) and metal oxide doping (Ag 2 O and NiO). Thermal stability was checked using Ab Initio Molecular Dynamics (AIMD) simulations at temperatures between 400 and 600 K. The results show that Se vacancies and NiO doping greatly improve adsorption. Se@HfSe 2 shows big changes in band gap and quick recovery for CO 2 and N 2 O, making it a good reusable sensor. SF 6 strongly attaches to HfSe 2 (-11.187 eV), suggesting it could be a good adsorbent. NiO HfSe 2 works well for CH 4 sensing and strongly adsorbs SF 6 , making it useful for gas detection and leak alarms. These findings give useful insights for better GHG monitoring and control.
As greenhouse gas (GHG) emissions continue to rise, it is important to develop effective ways to detect and remove them. This study uses density functional theory (DFT) to look at how four common GHGs (CO 2 , CH 4 , N 2 O, and SF 6 ) are adsorbed and sensed on HfSe 2 monolayers with single-atom vacancies (Hf and Se) and metal oxide doping (Ag 2 O and NiO). Thermal stability was checked using Ab Initio Molecular Dynamics (AIMD) simulations at temperatures between 400 and 600 K. The results show that Se vacancies and NiO doping greatly improve adsorption. Se@HfSe 2 shows big changes in band gap and quick recovery for CO 2 and N 2 O, making it a good reusable sensor. SF 6 strongly attaches to HfSe 2 (-11.187 eV), suggesting it could be a good adsorbent. NiO HfSe 2 works well for CH 4 sensing and strongly adsorbs SF 6 , making it useful for gas detection and leak alarms. These findings give useful insights for better GHG monitoring and control.
摘要：
We explore bipartite and multipartite nonlocality in the alternating Heisenberg-Ising spin chain model, emphasizing the contrasting and complementary roles of the relative coupling strength lambda\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda $$\end{document} (the ratio of the Ising interaction to the Heisenberg interaction), the external magnetic field h, and the temperature T. Bipartite nonlocality is evaluated using the CHSH inequality, and multipartite nonlocality is assessed through Bell-type inequalities derived from g-grouping model theory. Our results show that lambda\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda $$\end{document}, h, and T significantly affect nonlocality in distinct ways. Increasing lambda\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda $$\end{document} suppresses bipartite nonlocality but enhances multipartite nonlocality, highlighting the interaction-specific roles in the system: The Heisenberg interaction primarily governs bipartite nonlocal correlations, whereas the Ising interaction drives multipartite nonlocal correlations. In contrast, both h and T universally suppress bipartite and multipartite nonlocal correlations, irrespective of the interaction type. We also reveal scaling behaviors of nonlocality near the quantum critical points, denoted as lambda c\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda _{c}$$\end{document}, where both bipartite and multipartite nonlocality exhibit clear signatures in their first derivatives. Critical scaling is described by lambda c(N)=lambda c(infinity)-aN-b\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda _{c}(N) = \lambda _{c}(\infty )-aN<^>{-b}$$\end{document}, allowing precise determination of the critical value lambda c(infinity)=2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda _{c}(\infty ) = 2$$\end{document} in the thermodynamic limit.
摘要：
The rapidly exploring random tree star (RRT*) algorithm is widely used in path planning due to its versatility and ability to adapt to various environments. However, the high degree of randomness in RRT* results in slow initial solution convergence rate and low-quality initial solution. To address these issues, this paper proposes a modified RRT* algorithm named fast forwarding connect RRT*(FFC-RRT*). Firstly, a new constrained sampling method is introduced, allowing the random tree to be sampled within a specific region, thereby improving the algorithm’s effective sampling rate. Secondly, an adaptive hybrid sampling method is employed, enabling the algorithm to better adapt to various environments. Finally, performance comparisons were conducted between the proposed algorithm, RRT*, F-RRT*, and FC-RRT* in various simulation environments. The results show that FFC-RRT* achieves a faster initial path planning speed than the other three algorithms in different environments, especially in complex environments, FFC-RRT* is 84.83%, 72.81%, and 16.68% faster than RRT*, F-RRT*, and FC-RRT*, respectively. Overall, the proposed algorithm demonstrates superior performance, providing faster initial path planning convergence rate while maintaining higher path quality.
摘要：
Noncontact trapping of micro objects has great application potential in fields like material science and biomedical engineering due to its label-freeness and biocompatibility. In this paper, an automated acoustic micro-particle trapping system implemented with phased transducer array (PTA) is prototyped. The system is incorporated with a stereo vision to provide visual feedback benefited from localization of the invisible acoustic field through hydrophone scanning. Binocular vision calibration and stereo matching are realized using image Jacobian matrix. An efficient phase modulation algorithm is proposed for the calculation of desired PTA phase profile in real-time and a spatiotemporal multiplexing control strategy is adopted to dynamically generate multiple trappings. Experimental results well demonstrated that the stable trapping of multiple particles can be robustly realized by the system, leading to the improvements of robotic noncontact manipulation with invisible acoustic end-effector.
