bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced tunneling electroresistance through interfacial charge-modulated barrier in α-In2Se3-based ferroelectric tunnel junction
Authors: He Shiying , Zou Daifeng 
Published: December 2023

Abstract
The manipulation of tunneling resistance is critical for ferroelectric tunnel junction (FTJ) devices. In this work, we propose a mechanism to manipulate tunneling resistance through interfacial charge-modulated barrier in two-dimensional (2D) n-type semiconductor/ferroelectric FTJs. Driven by ferroelectric reversal, different effective tunneling barriers are realized by the depletion or accumulation of electrons near the n-type semiconductor surface in such devices. Thus, the tunneling resistance in FTJs undergoes significant changes for different polarization orientations, resulting in a giant tunneling electroresistance (TER) effect. To illustrate this idea, we construct 2D FTJs based on n-InSe/α-In2Se3 van der Waals (vdW) heterostructures. Based on the electronic transport calculations, it is found that TER ratio can reach 4.20 × 103% in the designed FTJs. The physical origin of the giant TER effect is verified through analysis of the effective potential energy of the n-InSe/α-In2Se3 vdW heterostructures and the real-space transmission eigenstates of the designed FTJs. This work contributes to the knowledge of carrier tunneling mechanisms at the interface of semiconductor/In2Se3 vdW heterostructures, and providing a significant insight into the TER effect of this FTJ systems, also presenting an alternative approach for the design of FTJ-based devices.
A compound fault diagnosis model for gearboxes using correlation information between single faults
Authors: Zeng Ming , Wang Hao , Cheng Yiwei , Wei Jianyu 
Published: December 2023

Abstract
Gearboxes are key components of rotating machinery. Performing intelligent fault diagnosis of gearboxes with condition-based monitoring information helps to make reliable decisions on equipment operation and maintenance. Besides single faults, compound faults also are common failure forms of gearboxes. Conventional intelligent diagnosis models (known as single-label models) generally treat a compound fault as a new fault type, ignoring the correlations between the compound fault and the corresponding single faults. To overcome this problem, multi-label learning has been introduced and developed into multi-label models. It is also possible that different single faults are not independent but correlated with each other. Existing multi-label models, however, usually ignore this aspect. Therefore, exploiting the correlation information between single faults can further improve multi-label models. To this end, every single fault is treated as a
label node
, resulting in a label graph. The feature vector of each label node is initialized by the word embedding of the corresponding single-fault label. All the word embeddings are mapped using graph convolutional networks (GCN) into the parameter vectors of a set of interdependent binary linear classifiers that can directly perform multi-label classification on health categories. Meanwhile, the adjacency matrix of the label graph is adaptively learned by self-attention (SA) from node feature vectors. In this way, a novel multi-label model based on SA and GCN (referred to as SA-GCN) is proposed for compound fault diagnosis of gearboxes. SA-GCN mainly consists of a ResNet-based fault feature learning module, an SA-based adjacency matrix learning module, and a GCN-based multi-label classifier learning module. The application results on two gearbox cases show that SA-GCN outperforms conventional single-label models as well as state-of-the-art multi-label models in terms of both the diagnostic accuracy of compound faults and the overall diagnostic accuracy. Moreover, the effects of internal modules and hyperparameters on SA-GCN are also investigated.
Study on the influence of internal modulation parameters on the temperature calculation performance of matrix-searching CCD pyrometer
Authors: Li Chao , Xu Chundong , Wang Yongjuan , Gao Liming , Zhang Xiangyong , Zhang Qi , Kong Deren 
Published: December 2023

Abstract
Matrix-searching CCD temperature measurement technology can integrate the complex signal modulation process of CCD because of its forward solution of inverse problem. But in the existing research, there is still a lack of discussion on the temperature calculation ability of this technology in the internal modulation process. Therefore, the research on the influence of temperature calculation performance of matrix-searching CCD pyrometer is carried out. Based on the three-channel temperature equation and the radiation acquisition theory of the detector, the evaluation model of effective measurement range and temperature resolution is defined and constructed. Combined with the calibration experiment, the effects of gain and gamma internal modulation parameters on the effective temperature measurement range and temperature resolution are discussed. Through the analysis of the simulation results, the use and effects of the two internal modulation parameters are obtained, which not only improves the theoretical system of the matrix-seeking temperature measurement method, but also provides theoretical guidance for the parameter selection of the method under different conditions.
Amorphous Co–Mo–P film on nickel foam: a superior bifunctional electrocatalyst for alkaline seawater splitting
Authors: Zhang Xuefeng , Yang Qin , Zhang Longcheng , Li Jun , Sun Shengjun , Yang Yingchun , Sun Yuntong , Sun Xuping 
Published: December 2023

Abstract
Seawater splitting is a compelling avenue to produce abundant hydrogen, which requires high-performance and cost-effective catalysts. Constructing bimetallic transition metal phosphides is a feasible strategy to meet the challenge. Here, an amorphous Co–Mo–P film supported on nickel foam (Co–Mo–P/NF) electrode is developed with bifunctional properties for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline seawater. Corresponding results indicate that the introduction of Mo can improve the active sites and regulate the intrinsic activity. Such a Co–Mo–P/NF behaves with prominent electrocatalytic activity towards both HER and OER, demanding low overpotentials of 193 and 352 mV at 100 mA cm‒2 in alkaline seawater, respectively. Furthermore, the assembled electrolyzer demands a pronounced overall seawater splitting activity with a low cell voltage of 1.76 V to deliver 100 mA cm−2 presenting excellent durability without obvious attenuation after 24 h continuous stability test. This work expands the horizon to develop transition metal-phosphorus electrocatalysts with robust and efficient activity for overall seawater splitting.
SnO2/SnS heterojunction anchoring on CMK-3 mesoporous network improves the reversibility of conversion reaction for lithium/sodium ions storage
Authors: Zhang Dongyang , Liu Limin , Zhang Shishi , Cui Jia , Wang Mingyue , Wang Qingchuan , Dong Haijian , Su Yaqiong , Ding Shujiang 
Published: December 2023

Abstract
Tin oxide-based (SnO2) materials show high theoretical capacity for lithium and sodium storage benefiting from a double-reaction mechanism of conversion and alloying reactions. However, due to the limitation of the reaction thermodynamics and kinetics, the conversion reaction process of SnO2 usually shows irreversibility, resulting in serious capacity decay and hindering the further application of the SnO2 anode. Herein, SnO2/SnS heterojunction was anchored on the surface and inside of CMK-3 by in
situ synthesis method, forming a stable 3D structural material (SnO2/SnS@CMK-3). The electrochemical properties of SnO2/SnS@CMK-3 composite show high capacity and reversible conversion reaction, which was attributed to the synergistic effect of CMK-3 and SnO2/SnS heterojunction. To further investigate the influence of the heterojunction on the reversibility of the conversion reaction, the Gibbs free energy (ΔG) was calculated using density functional theory. The results show that SnO2/SnS heterojunction has a closer to zero ΔG for lithium/sodium ion batteries compared to SnO2, indicating that the heterojunction enhances the reversibility of the conversion reaction in chemical reaction thermodynamics. Our work provides insights into the reversibility of the conversion reaction of SnO2-based materials, which is essential for improving their electrochemical performance.
Optical transparency in 2D ferromagnetic WSe2/1T-VSe2/WSe2 multilayer with strain induced large anomalous Nernst conductivity
Authors: Khan Imran , Marfoua Brahim , Hong Jisang 
Published: December 2023

Abstract
Transparent two-dimensional (2D) magnetic materials may bring intriguing features and are indispensable for transparent electronics. However, it is rare to find both optical transparency and room-temperature ferromagnetism simultaneously in a single 2D material. Herein, we explore the possibility of both these features in 2D WSe2/1T-VSe2 (1ML)/WSe2 and WSe2/1T-VSe2 (2ML)/WSe2 heterostructures by taking one monolayer (1ML) and two monolayers (2ML) of 1T-VSe2 using first-principles calculations. Further, we investigate anomalous Hall conductivity (AHC) and anomalous Nernst conductivity (ANC) using a maximally localized Wannier function. The WSe2/1T-VSe2 (1ML)/WSe2 and WSe2/1T-VSe2 (2ML)/WSe2 systems show Curie temperatures of 328 and 405 K. Under biaxial compressive strain, the magnetic anisotropy of both systems is switched from in-plane to out-of-plane. We find a large AHC of 1.51 e2/h and 3.10 e2/h in the electron-doped region for strained WSe2/1T-VSe2 (1ML)/WSe2 and WSe2/1T-VSe2 (2ML)/WSe2 systems. Furthermore, we obtain a giant ANC of 3.94 AK−1 m−1 in a hole-doped strained WSe2/1T-VSe2 (2ML)/WSe2 system at 100 K. Both WSe2/1T-VSe2 (1ML)/WSe2 and WSe2/1T-VSe2 (2ML)/WSe2 are optically transparent in the visible ranges with large refractive indices of 3.2–3.4. Our results may suggest that the WSe2/1T-VSe2/WSe2 structure possesses multifunctional physical properties and these features can be utilized for spintronics and optoelectronics device applications such as magnetic sensors, memory devices, and transparent magneto-optic devices at room temperature.
Printed graphene and its composite with copper for electromagnetic interference shielding applications
Authors: Gutierrez Daniel , Doshi Pranay , Wong Hiu Yung , Nordlund Dennis , Gandhiraman Ram P 
Published: December 2023

Abstract
Advances in mobile electronics and telecommunication systems along with 5G technologies have been escalating the electromagnetic interference (EMI) problem in recent years. Graphene-based material systems such as pristine graphene, graphene-polymer composites and other graphene-containing candidates have been shown to provide adequate EMI shielding performance. Besides achieving the needed shielding effectiveness (SE), the method of applying the candidate shielding material onto the object in need of protection is of enormous importance due to considerations of ease of application, reduced logistics and infrastructure, rapid prototyping and throughput, versatility to handle both rigid and flexible substrates and cost. Printing readily meets all these criteria and here we demonstrate plasma jet printing of thin films of graphene and its composite with copper to meet the EMI shielding needs. SE over 30 dB is achieved, which represents blocking over 99.9% of the incoming radiation. Graphene and its composite with copper yield higher green index compared to pure copper shields, implying reduced reflection of incoming electromagnetic waves to help reduce secondary pollution.
Enhancement of second-harmonic generation in a 64° stacked WSe2/WS2 heterobilayer with local strain
Authors: Chang Sehwan , Lee Hoo-Cheol , Na Gunwoo , Kim Ryeong Myeong , Moon Yoon-Jong , Kim Ha-Reem , Nam Ki Tae , Park Hong-Gyu 
Published: December 2023

Abstract
Transition metal dichalcogenides (TMDs) are actively studied in various fields of optics and optoelectronics, including nonlinear optics of second-harmonic generation (SHG). By stacking two different TMD materials to form a heterobilyaer, unique optical properties emerge, with stronger SHG at a twist angle of 0° between TMDs and weaker SHG at a twist angle of 60°. In this work, we demonstrate the enhancement of SHG in a heterobilayer consisting of WSe2 and WS2 monolayers stacked at a twist angle of 64.1°, using a nanoparticle to induce local strain. The interatomic spacing of the heterobilayer is deformed by the nanoparticle, breaking the inversion symmetry, resulting in a substantial increase in the SHG of the heterobilayer at room temperature. The SHG increases depending on the polarization of the pump laser: 15-fold for linear polarization, 9-fold for right-circular polarization, and up to 100-fold for left-circular polarization. In addition, the SHG enhanced in the heterobilayer with local strain satisfies the same chiral selection rule as in the unstrained TMD region, demonstrating that the chiral selection rule of SHG is insensitive to local strain. Our findings will increase the applicability of TMD heterobilayers in nonlinear optoelectronics and valleytronics.
Mapping emission heterogeneity in layered halide perovskites using cathodoluminescence
Authors: Griesi Andrea , Faraji Mehrdad , Kusch Gunnar , Khabbazabkenar Sirous , Borreani Martina , Lauciello Simone , Schleusener Alexander , Oliver Rachel A , Krahne Roman , Divitini Giorgio 
Published: December 2023

Abstract
Recent advancements in the fabrication of layered halide perovskites and their subsequent modification for optoelectronic applications have ushered in a need for innovative characterisation techniques. In particular, heterostructures containing multiple phases and consequently featuring spatially defined optoelectronic properties are very challenging to study. Here, we adopt an approach centered on cathodoluminescence, complemented by scanning electron microscopy coupled with energy-dispersive x-ray spectroscopy analysis. Cathodoluminescence enables assessment of local emission variations by injecting charges with a nanometer-scale electron probe, which we use to investigate emission changes in three different systems: PEA2PbBr4, PEA2PbI4 and lateral heterostructures of the two, fabricated via halide substitution. We identify and map different emission bands that can be correlated with local chemical composition and geometry. One emission band is characteristic of bromine-based halide perovskite, while the other originates from iodine-based perovskite. The coexistence of these emissions bands in the halide-substituted sample confirms the formation of lateral heterostructures. To improve the signal quality of the acquired data, we employed multivariate analysis, specifically the non-negative matrix factorization algorithm, on both cathodoluminescence and compositional datasets. The resulting understanding of the halide replacement process and identification of potential synergies in the optical properties will lead to optimised architectures for optoelectronic applications.
CAM-QUS guided self-tuning modular CNNs with multi-loss functions for fully automated breast lesion classification in ultrasound images
Authors: Tasnim Jarin , Hasan Md Kamrul 
Published: December 2023

Abstract

Objective. Breast cancer is the major cause of cancer death among women worldwide. Deep learning-based computer-aided diagnosis (CAD) systems for classifying lesions in breast ultrasound images can help materialise the early detection of breast cancer and enhance survival chances. Approach. This paper presents a completely automated BUS diagnosis system with modular convolutional neural networks tuned with novel loss functions. The proposed network comprises a dynamic channel input enhancement network, an attention-guided InceptionV3-based feature extraction network, a classification network, and a parallel feature transformation network to map deep features into quantitative ultrasound (QUS) feature space. These networks function together to improve classification accuracy by increasing the separation of benign and malignant class-specific features and enriching them simultaneously. Unlike the categorical crossentropy (CCE) loss-based traditional approaches, our method uses two additional novel losses: class activation mapping (CAM)-based and QUS feature-based losses, to capacitate the overall network learn the extraction of clinically valued lesion shape and texture-related properties focusing primarily the lesion area for explainable AI (XAI). Main results. Experiments on four public, one private, and a combined breast ultrasound dataset are used to validate our strategy. The suggested technique obtains an accuracy of 97.28%, sensitivity of 93.87%, F1-score of 95.42% on dataset 1 (BUSI), and an accuracy of 91.50%, sensitivity of 89.38%, and F1-score of 89.31% on the combined dataset, consisting of 1494 images collected from hospitals in five demographic locations using four ultrasound systems of different manufacturers. These results outperform techniques reported in the literature by a considerable margin. Significance. The proposed CAD system provides diagnosis from the auto-focused lesion area of B-mode BUS images, avoiding the explicit requirement of any segmentation or region of interest extraction, and thus can be a handy tool for making accurate and reliable diagnoses even in unspecialized healthcare centers.
Variational principles for sub-additive unstable topological pressures on saturated subsets
Authors: Zhang Wenda , Li Zhiqiang , Ren Xiankun 
Published: December 2023

Abstract
In this paper, under the assumption of unstable almost product property for C
1-smooth partially hyperbolic diffeomorphisms, we establish variational principles for their unstable Bowen topological pressures and unstable packing topological pressures on the typical saturated subsets G

K
, where K is a given non-empty compact connected set of invariant measures. Actually, we show that these two dimension-like topological quantities coincide with the infimum and supremum respectively of the summation of unstable metric entropy and Lyapunov exponent, where the infimum and supremum are taken over all measures inside K. Besides, we also show that G

K
has full unstable topological capacity pressure for reasonable sub-additive potentials.
Health risk analysis of benzene, toluene, ethylbenzene, and xylene (BTEX) in groundwater in Yogyakarta City, Indonesia
Authors: Juliani A , Rahmawati S , Bariroh A , Dalimunthe G A , Ardhayanti L I , Aprilia W P 
Published: December 2023

Abstract
Benzene, Toluene, Ethylbenzene, and Xylene (BTEX) are persistent and bio-accumulative compounds that occur in petroleum-based products. Benzene is categorized as a carcinogenic substance while ethylbenzene is potentially carcinogenic. One of the sources of BTEX contamination in the environment is gas stations. The leakage of underground storage tanks (UST) of gas stations is a potential source of groundwater contamination, while in many areas, it is the main source of daily water consumption. The long-term consumption of this BTEX-contaminated groundwater may generate health risks. This paper will present the health risk analysis of the consumption of BTEX-contaminated groundwater taken from dug wells near a gas station in Yogyakarta City which has a history of major leakage. Analysis of BTEX in groundwater samples has been already presented in the previous study. Data for intake calculation was acquired through questionnaires and interviews on water consumption patterns. Risk analysis was conducted for both the carcinogenic effect of benzene and the non-carcinogenic effect for all BTEX compounds. Health risk analysis on BTEX exposure in groundwater resulted in the Hazard Quotient (HQ) value for all compounds which were still less than one, meanwhile, the Excess Cancer Risk (ECR) for benzene was less than 10-4. The result indicates the low health risk associated with the consumption of BTEX-contaminated groundwater in the study area.
Effect of various housing patterns on social cohesion
Authors: Rahmanita P , Wiranegara H W , Supriatna Y 
Published: December 2023

Abstract
Social cohesion in housing is an attribute of the quality of the community of its inhabitants. Housing planning needs to function to facilitate the social interaction of its inhabitants. This research aims to identify the effect of housing patterns on social cohesion in various housing patterns. Most existing housing patterns built are grid, linear, and T-shape patterns. It is necessary to know the effect of each pattern on social cohesion. The data collection technique used the questionnaire survey method. Two clusters were selected as samples such as the Lavender Lane 1 and Graha Sevilla in Citra Raya, Tangerang Regency. Those samples have linear, grid, and T-shape patterns. The total number of respondents from the three housing patterns is 121. The analysis technique used simple linear regression using Smart-PLS software. The results showed that the effect of housing patterns on social cohesion was evident in the linear and T-shape patterns, while it was not in the grid pattern. The housing pattern indicators affecting social cohesion are the total row of houses, building layout plans, and street patterns that need to be considered in cluster housing planning to build social cohesion.
Comprehensive assets-based approach for neighborhoods that are under-resourced in Jakarta (case study: Keagungan Sub-district in West Jakarta, Indonesia)
Authors: Ischak M , Sejati W , Kridarso E R , Rosnarti D , Purwaningsih L H 
Published: December 2023

Abstract
Neighborhoods that are under-resourced are one of the main problems that almost always accompany the growth of big cities, especially in developing countries, including Jakarta. This research aims to examine the application of the Comprehensive Assets-Based Approach (CABA) as an alternative solution to the problem of neighborhoods that are under-resourced in Jakarta. The research was conducted using a descriptive qualitative method by examining one of the structuring concepts as an alternative solution to settlement problems in Jakarta, which is directed at achieving liveable housing variables. Data on houses and settlements were obtained directly from Keagungan sub-districts, including neighborhoods that are under-resourced in Jakarta. The first step is to analyze settlement data to formulate the main problems in the neighborhoods that are under-resourced. The second step is to analyze the application of the CABA method to the problems that have been obtained before. The results of the research found that one of the primary root problems in the neighborhoods that are under-resourced in Jakarta is the interweaving of economic and social problems, which include lack of income, lack of knowledge and adherence to building regulations, as well as the lack of knowledge on the criteria for liveable housing. We, therefore, conclude that it is very likely to apply the CABA method for solving neighborhoods that are under-resourced in Jakarta based on community empowerment.