bluuebunny/crossref_metadata_2025_split huggingface dataset:
An improved similarity-based RUL prediction method considering degradation degree of multiple condition monitoring parameters for aero-engines
Authors: Peng Chong , Sun Youchao , Su Siyu , Guo Chaochao 
Published: September 2024

Abstract
The aero-engine is the heart of an airplane. Predicting the remaining useful lifetime (RUL) of an aero-engine bears great significance, not only for improving the reliability and safety of the aero-engine but also for ensuring aircraft safety and performance. However, both issues, namely the selection of uncorrelated parameters for RUL estimation and the lack of a standard theoretical methodology for Health Index (HI) construction, inevitably impact the prediction accuracy. Here, we proposed an improved similarity-based RUL prediction method considering the degradation degree of multiple condition monitoring parameters for aero-engines. This method includes the improved minimum-redundancy maximum-relevancy approach for the quantitative selection of key parameters, and the similarity matching approach which takes into account the degradation degree of multiple parameters instead of constructing HI. The effectiveness of the proposed method was evaluated on turbine engine datasets. Experimental results show that (1) compared with other feature selection methods, the root mean square error (RMSE) of the proposed method is reduced by 12.3%; (2) compared with other RUL prediction methods, the RMSE of the proposed method is smaller than most methods but without a complicated training process. The results demonstrate that the proposed method achieves highly competitive prediction performance. By employing the proposed method, it is possible to significantly reduce the risk of engine failures, thereby improving safety and economic efficiency.
NIM–TTL and TTL–NIM converters for single particle pulse counting experiments
Authors: Murray Andrew James , Harvey Matthew 
Published: September 2024

Abstract
Low-cost interface circuits are detailed that convert negative-going NIM signals to TTL and TTL to NIM, using high-speed digital and analogue components to convert between formats. By converting NIM pulses derived from single particle detectors to TTL logic, the large suite of TTL compatible devices available to manipulate, control and measure TTL signals can be exploited. Conversion of TTL pulses to NIM allows them to be used to trigger timing events, e.g. in time of flight measurements and coincidence studies. Examples using these techniques are presented.
STAKgram: a method for optimal demodulation band selection in bearing fault diagnosis under complex interference
Authors: Jia Min , Wang Jinrui , Zhang Zongzhen , Han Baokun , Bao Huaiqian , Wang Yangchao 
Published: September 2024

Abstract
Within rotating machinery, bearings constitute critical and vulnerable components. When they operate in a compromised state, they generate periodic shock pulses. While spectral kurtosis (SK) has been demonstrated as an effective tool for pulse detection, in complex operating environments, the vibration signals of damaged bearings acquired through sensors often contain a variety of interfering pulses, such as ambient background noise, episodic single pulses, which cause SK to produce poor computational results. In this paper, an innovative bearing fault diagnostic method named subband trimmed average kurtogram (STAKgram) is proposed, aiming to minimize the effect of interfering signals on signal processing results, thus ensuring reliable diagnostic results even in complex interference environments. Firstly, the signal is segmented into

N

sub-signals by employing a sliding window method. Following, the subband kurtosis is calculated for every sub-signal. Ultimately, the trimmed average kurtosis of the respective sub-band is computed to construct the STAKgram, indicating the optimal demodulation frequency band. It is used for squared envelope demodulation analysis. By simulation analysis and the application of test signals obtained under conditions closely resembling authentic bearing operating conditions, the STAKgram method is proven to provide more accurate results for diagnosing bearing faults in complex interference.
Sensitivity matrix update method for electrical resistance tomography based on error-constrained cross fusion residual attention network
Authors: Wang Chao , Zhu Shiyi , Zhao Linshuo , Pang Ran , Ye Jiamin , Yan Jingyi 
Published: September 2024

Abstract
Electrical resistance tomography (ERT) is an imaging technique of conductivity distribution. The image reconstruction algorithm based on the empty field sensitivity matrix is widely used because it provides an approximate solution to the complex ERT inverse problems. However, due to the soft field effect, the sensitivity matrix changes with the media distribution, leading to significant errors in image reconstruction. To address this issue, an error-constrained deep learning scheme for bubble flow, namely cross fusion residual attention network (CFRA-Net) is designed to update the sensitivity matrix during gas–liquid–solid fluidized bed operation. CFRA-Net employs a multi-head self-attention mechanism to enhance bubble features in boundary measurements, a multilevel cross fusion (CF) module to fuse empty field strength and boundary measurement information, and a novel serial-channel residual spatial attention block to boost the feature extraction capability of the model. A weighted loss function is designed to give more weight to the gas phase distribution region. Additionally, this paper establishes a dataset for gas–liquid–solid three-phase flow, considering background field conductivity variations. Validation and reliability of the proposed method are assessed through ablation, comparison, and noise experiments. The experimental results demonstrate that CFRA-Net achieves rapid updates of the sensitivity matrix, high imaging accuracy, and robust noise immunity.
A ship detection model with progressive feature fusion and cross-spatial learning attention mechanism for optical remote sensing images
Authors: Miao Ru , Wang Jiaqian , Zhou Ke , Meng Geng , Li Yi , Chang Ranran 
Published: September 2024

Abstract
Using remote sensing images to detect ships is vital for port management, maritime transportation, and security. Challenges such as false detection and omission arise in ship target detection in optical remote sensing images due to the complexity of the background and the diversity of target scales. To address these issues, this paper proposes a novel model called MBE-YOLO. Firstly, the multiscale input spatial pyramid pooling-fast structure is designed to effectively extract more feature information by efficiently integrating the features from different stages of the backbone network. Secondly, the backbone to neck structure is designed with a progressive architecture to mitigate semantic differences between non-adjacent layers in the feature delivery process, thereby significantly reducing the risk of information loss. Finally, we introduce the efficient multi-scale attention attention mechanism, which establishes short and long dependencies through multi-scale parallel subnetworks. This enhances the ability to detect targets in complex environments at various scales. MBE-YOLO is applied to the HRSC2016 and HiresShipDetection datasets. Comparison experiments with current mainstream and state-of-the-art models demonstrate its effectiveness in addressing errors and omissions due to scene complexity and scale variations in remote sensing ship detection, with a parameter size of only 3.24 M.
Facile synthesis of Bi2ZnB2O7-MoS2 nanocomposite for photodetector and photocatalytic Rhodamine B dye degradation application
Authors: Porwal Chirag , Thakur Deepa , Gaur Akshay , Chauhan Vishal Singh , Balakrishnan Viswanath , Vaish Rahul 
Published: September 2024

Abstract
In this research, the visible light active performance of Bi2ZnB2O7 (BBZO) was significantly enhanced through the formation of a composite with few layer MoS2. The resultant MoS2@BBZO catalyst was employed in both photocatalysis and photodetector applications. Comprehensive structural and morphological analyses of the MoS2@BBZO catalyst were conducted using x-ray diffraction, Raman spectroscopy, field-emission scanning electron microscopy (FE-SEM), and transmission electron microscopy. The estimated band gaps of BBZO and the composite were found to be 2.8 eV and 1.74 eV, respectively. Rhodamine B degradation studies demonstrated that the catalyst achieved 75% degradation within 30 min. Additionally, the photodetector application was investigated, revealing rapid photo-switching capabilities and an increased photocurrent.
Enhancement of photovoltaic parameters of thermally stable graphene/LaVO3 semitransparent solar cell by employing interfacial graphene quantum dots
Authors: Kim Hyo-Han , Kim Do Hoon , Choi Bo Gyu , Kim Da Hee , Oh Si Duck , Shin Dong Hee , Lee Hosun 
Published: September 2024

Abstract
Semitransparent solar cells are attracting attention not only for their visual effects but also for their ability to effectively utilize solar energy. Here, we demonstrate a translucent solar cell composed of bis(trifluoromethane sulfonyl)-amide (TFSA)-doped graphene (Gr), graphene quantum dots (GQDs), and LaVO3. By introducing a GQDs intermediate layer at the TFSA-Gr/LaVO3 interface, we can improve efficiency by preventing carrier recombination and promoting charge collection/separation in the device. As a result, the efficiency of the GQDs-based solar cell was 4.35%, which was higher than the 3.52% of the device without GQDs. Furthermore, the average visible transmittance of the device is 28%, making it suitable for translucent solar cells. The Al reflective mirror-based system improved the power conversion efficiency by approximately 7% compared to a device without a mirror. Additionally, the thermal stability of the device remains at 90% even after 2000 h under an environment with a temperature of 60 °C and 40% relative humidity. These results suggest that TFSA-Gr/GQDs/LaVO3-based cells have a high potential for practical use as a next-generation translucent solar energy power source.
Visible-light-driven selective cleavage of lignin C-C bonds on the TiO2@g-C3N4 heterostructured photocatalyst
Authors: Xiao Gang , Wang Zishuai , Jin Yu , Wang Fengping 
Published: September 2024

Abstract
The selective cleavage of lignin C–C bonds is a highly sought-after process with the goal of obtaining low-molecular-weight aromatic chemicals from renewable resources. However, it remains a challenging task to achieve under mild conditions. Photocatalysis is a potentially promising approach to address this issue, but the development of efficient photocatalysts is still in progress. In this study, we introduce the heterostructured TiO2@g-C3N4 photocatalyst for the development of a visible light photocatalytic procedure for the selective cleavage of lignin C–C bonds under mild conditions. The photocatalyst displays favourable visible light absorption, efficient charge separation efficiency, and promising reusability. A typical β–O–4 dimer model, 2-phenoxy-1-phenylethanol, was effectively (96.0% conversion) and selectively (95.0 selectivity) cleaved under visible light at ambient conditions. This photocatalytic procedure was also effective when subjected to solar irradiation or other lignin dimer models with β–O–4 or β-1 linkages. This reaction occurred through a C
β
-centred radical intermediate and a six-membered transition state with photogenerated holes as the primary active species. The C
α
–OH oxidative dehydrogenation of the substrate could also take place but was a relatively minor route. This study provides a new photocatalytic procedure for visible-light-driven lignin valorisation and sheds light on the design of high-performance nanocomposite photocatalysts for C–C bond cleavage.
Fabrication of a graphene@Ni foam-supported silver nanoplates-PANI 3D architecture electrode for enzyme-free glucose sensing
Authors: Wahid Ahtisham Abdul , Usman Muhammad , Haleem Yasir A , Ahmed Arsalan , Raza Kabeer , Munir Muhammad Usman , Pan Lujan , Khan Aslam 
Published: September 2024

Abstract
Reliable and cost-effective glucose sensors are in rising demand among diabetes patients. The combination of metals and conducting polymers creates a robust electrocatalyst for glucose oxidation, offering enzyme-free, high stability, and sensitivity with outstanding electrochemical results. Herein, graphene is grown on nickel foam by chemical vapor deposition to make a graphene@nickel foam scaffold (G@NF), on which silver nanoplates-polyaniline (Ag–PANI) 3D architecture is developed by sonication-assisted co-electrodeposition. The resulting binder-free 3D Ag–PANI/G@NF electrode was highly porous, as characterized by x-ray photoelectron spectroscopy, Field emission scanning electron microscope, x-ray diffractometer, FTIR, and Raman spectroscopy. The binder-free 3D Ag–PANI/G@NF electrode exhibits remarkable electrochemical efficiency with a superior electrochemical active surface area. The amperometric analysis provides excellent anti-interference performance, a low limit of deduction (0.1 nM), robust sensitivity (1.7 × 1013
µA mM−1cm−2), and a good response time. Moreover, the Ag–PANI/G@NF enzyme-free sensor is utilized to observe glucose levels in human blood serums and exhibits excellent potential to become a reliable clinical glucose sensor.
Elucidating the time-dependent charge neutrality point modulation of polymer-coated graphene field-effect transistors in an ambient environment
Authors: Norhakim Nadia , Gunasilan Thaachayinie , Kesuma Zayyan Rafi , Hawari Huzein Fahmi , Burhanudin Zainal Arif 
Published: September 2024

Abstract
The charge neutrality point (CNP) is one of the essential parameters in the development of graphene field-effect transistors (GFETs). For GFET with an intrinsic graphene channel layer, the CNP is typically near-zero-volt gate voltage, implying that a well-balanced density of electrons and holes exists in the graphene channel layer. Fabricated GFET, however, typically exhibits CNP that is either positively or negatively shifted from the near-zero-volt gate voltage, implying that the graphene channel layer is unintentionally doped, leading to a unipolar GFET transfer characteristic. Furthermore, the CNP is also modulated in time, indicating that charges are dynamically induced in the graphene channel layer. In this work, understanding and mitigating the CNP shift were attempted by introducing passivation layers made of polyvinyl alcohol and polydimethylsiloxane onto the graphene channel layer. The CNP was found to be negatively shifted, recovered back to near-zero-volt gate voltage, and then positively shifted in time. By analyzing the charge density, carrier mobility, and correlation between the CNP and the charge density, it can be concluded that positive CNP shifts can be attributed to the charge trapping at the graphene/SiO2 interface. The negative CNP shift, on the other hand, is caused by dipole coupling between dipoles in the polymer layer and carriers on the surface of the graphene layer. By gaining a deeper understanding of the intricate mechanisms governing the CNP shifts, an ambiently stable GFET suitable for next-generation electronics could be realized.
Examining transport and integrated modeling predictive capabilities for negative-triangularity scenarios
Authors: McClenaghan J , Marinoni A , Nelson A O , Neiser T , Lao L L , Staebler G M , Smith S P , Meneghini O M , Lyons B C , Snyder P B , Austin M 
Published: September 2024

Abstract
This paper investigates the predictive capabilities of TGYRO and TGLF models in assessing the performance of negative triangularity (NT) plasmas compared to positive triangularity (PT) plasmas in fusion devices. TGYRO predicts kinetic profiles, while TGLF analyzes turbulent transport. The study reveals that TGYRO reasonably predicts NT profiles similar to PT, although it overpredicts the high-power scenarios where there is increased experimental MHD activity. TGLF analysis finds reduced linear growth rates in NT and altered flux spectra relative to PT. Additionally, the TGLF SAT0 saturation model is observed to predict high-k transport and a reduction of particle transport with the electron temperature gradient. These findings are further corroborated by core-pedestal modeling using the Stability Transport Equilibrium Pedestal workflow, showing stronger confinement improvements in NT, particularly at higher power densities for the SAT0 saturation model. The study underscores the importance of accurately capturing turbulence saturation mechanisms for NT in order to project its performance accurately in fusion reactors.
Determinant- and derivative-free quantum Monte Carlo within the stochastic representation of wavefunctions
Authors: Bernheimer Liam , Atanasova Hristiana , Cohen Guy 
Published: September 2024

Abstract
Describing the ground states of continuous, real-space quantum many-body systems, like atoms and molecules, is a significant computational challenge with applications throughout the physical sciences. Recent progress was made by variational methods based on machine learning (ML) ansatzes. However, since these approaches are based on energy minimization, ansatzes must be twice differentiable. This (a) precludes the use of many powerful classes of ML models; and (b) makes the enforcement of bosonic, fermionic, and other symmetries costly. Furthermore, (c) the optimization procedure is often unstable unless it is done by imaginary time propagation, which is often impractically expensive in modern ML models with many parameters. The stochastic representation of wavefunctions (SRW), introduced in (Atanasova et al 2023 Nat. Commun.
14 3601), is a recent approach to overcoming (c). SRW enables imaginary time propagation at scale, and makes some headway towards the solution of problem (b), but remains limited by problem (a). Here, we argue that combining SRW with path integral techniques leads to a new formulation that overcomes all three problems simultaneously. As a demonstration, we apply the approach to generalized ‘Hooke’s atoms’: interacting particles in harmonic wells. We benchmark our results against state-of-the-art data where possible, and use it to investigate the crossover between the Fermi liquid and the Wigner molecule within closed-shell systems. Our results shed new light on the competition between interaction-driven symmetry breaking and kinetic-energy-driven delocalization.
Simulation of the functionality of ZnO, TiO2 and Ta2O5, and MoO2 carrier selective contacts of GaAs0.99Bi0.01 nanowire-based solar cells
Authors: Roy Debamita , Samajdar Dip Prakash , Biswas Abhijit 
Published: September 2024

Abstract
The photovoltaic performance of perpendicularly aligned GaAs0.99Bi0.01/CSC/ITO core–shell nanowire solar cells is thoroughly investigated in this simulation-based theoretical study for both electron-selective contact (ESC) and hole selective contact (HSC) as carrier selective contact (CSC) shell around GaAs0.99Bi0.01 core nanowire. The overall performance is compared with radial p-i-n-doped GaAs0.99Bi0.01 nanowire solar cell (NWSC) to mark the improvement caused by carrier selectivity. ZnO, TiO2 and Ta2O5 are chosen as ESC material and MoO2 is chosen as HSC material in order to carry out this comparative study. We have thoroughly performed geometric optimization tests over a wide range of periods in order to select the optimized ITO (indium tin oxide) thickness for obtaining maximum photocurrent generation. A maximum short-circuit photocurrent density (J
sc) of 38.76 mA cm−2 is obtained with a ZnO coated NWSC for a pitch (P) of 400 nm and ITO shell thickness of 90 nm. For this optimized geometry, TiO2, Ta2O5 and MoO2 coated structures offer J
sc of 35.82, 35.69 and 35.27 mA cm−2, respectively, and an uncoated NW exhibits J
sc of 31.15 mA cm−2. The planar structure without coating gives a J
sc of 24.86 mA cm−2, which is significantly lower than the nanostructured solar cells. Finally, a Lumerical 3D charge transport simulator is used to perform electrical stimulation of ZnO-coated structure, which offers maximum ideal J
sc. A detailed electrical performance analysis of GaAs0.99Bi0.01/CSC/ITO unit NW solar cell for ZnO, TiO2 and Ta2O5 as ESCs and MoO2 as HSC is also covered in this article. ZnO as an ESC offers the best photo-conversion efficiency (PCE) of ∼25% and open-circuit voltage (V
oc) of 0.95 V for a very small minority carrier lifetime (Ʈn) of 0.1 ns for GaAs0.99Bi0.01 and Ʈn of 1 ps for ZnO, with high surface recombination velocity of 105cm s−1 at the interfaces.
Structure, morphology and magnetic performance of (Fe65Co35)
x
@(Ni0.5Zn0.5Fe2O4)100–x
nanocomposite thin films
Authors: Wang Jun Bao , Xiao Wei Wei , Ma Dian Guo , Wang Lu , Liu Yun Yun , Tian Xiao Zhong , Liang Lan Ju , Gao Ju 
Published: September 2024

Abstract
A bi-magnetic phase (Fe65Co35)x@(Ni0.5Zn0.5Fe2O4)100–x nanocomposite thin film was created by combining Fe65Co35 alloy nanoclusters produced through plasma gas condensation with Ni0.5Zn0.5Fe2O4 thin film prepared via RF magnetron sputtering. The study revealed that the Fe65Co35 alloy nanoclusters, with an average particle size of approximately 6 nm, are surrounded by the amorphous ferrite phase, forming a granular ‘core–shell’ structure. As the proportion of Fe65Co35 alloy nanoclusters increased from 5.9 wt% to 35.4 wt%, the grain size of the nanocomposite thin films decreased from 24 nm to 10.4 nm. Magnetic analysis demonstrated that the nanocomposite thin films displayed soft magnetic properties at room temperature. With an increase in Fe65Co35 content, the saturated magnetization of the nanocomposite thin films escalated from 68 emu cm−3 to 214 emu/cm3, significantly surpassing that of the corresponding NiZn ferrite films (∼17 emu/cm3). The fluctuation of coercivity is intricately linked to the grain size of the nanocomposite thin films, and at 24.5 wt% of Fe65Co35 alloy nanoclusters, the coercivity is minimized to 14 Oe. The ferromagnetic resonance spectra of the nanocomposite films exhibited some asymmetric broadening and shift. As the Fe65Co35 content increased, the resonance field initially decreased and then rose, while the resonance linewidth gradually decreased.