bluuebunny/crossref_metadata_2025_split huggingface dataset:
Low-temperature diffusion in thin-film Pt-(Au-)-Co heterostructures: a structural and magnetic characterization
Authors: Pedan Roman , Makushko Pavlo , Yavorskyi Yurii , Dubikovskyi Oleksandr , Bodnaruk Andrii , Burmak Andrii , Golub Vladimir , Voloshko Svitlana , Hübner René , Makarov Denys , Vladymyrskyi Igor 
Published: January 2024

Abstract
Formation of functional thin films for nanoelectronics and magnetic data storage via thermally induced diffusion-driven structural phase transformations in multilayer stacks is a promising technology-relevant approach. Ferromagnetic thin films based on Co Pt alloys are considered as a material science platform for the development of various applications such as spin valves, spin orbit torque devices, and high-density data storage media. Here, we study diffusion processes in Pt–Co-based stacks with the focus on the effect of layers inversion (Pt/Co/substrate versus Co/Pt/substrate) and insertion of an intermediate Au layer on the structural transitions and magnetic properties. We demonstrate that the layer stacking has a pronounced effect on the diffusion rate at temperatures, where the diffusion is dominated by grain boundaries. We quantify effective diffusion coefficients, which characterize the diffusion rate of Co and Pt through the interface and grain boundaries, providing the possibility to control the homogenization rate of the Pt–Co-based heterostructures. The obtained values are in the range of 10−16–10−13 cm2 s−1 for temperatures of 150 °C–350 °C. Heat treatment of the thin-film samples results in the coercivity enhancement, which is attributed to short-range chemical ordering effects. We show that introducing an additional Au intermediate layer leads to an increase of the coercive field of the annealed samples due to a modification of exchange coupling between the magnetic grains at the grain boundaries.
Phosphorus-doped TiO2 mesoporous nanocrystals for anodes in high-current-rate lithium ion batteries
Authors: Ko Wen-Yin , Wu Tung-Ching , He Sin-Yu , Lin Kuan-Jiuh 
Published: January 2024

Abstract
Limited by the intrinsic low electronic conductivity and inferior electrode kinetics, the use of TiO2 as an anode material for lithium ion batteries (LIBs) is hampered. Nanoscale surface-engineering strategies of morphology control and particle size reduction have been devoted to increase the lithium storage performances. It is found that the ultrafine nanocrystal with mesoporous framework plays a crucial role in achieving the excellent electrochemical performances due to the surface area effect. Herein, a promising anode material for LIBs consisting of phosphorus-doped TiO2 mesoporous nanocrystals (P-TMC) with ultrafine size of 2–8 nm and high specific surface area (234.164 m2 g–1) has been synthesized. It is formed through a hydrothermal process and NaBH4 assisted heat treatment for anatase defective TiO2 (TiO2–x) formation followed by a simple gas phosphorylation process in a low-cost reactor for P-doping. Due to the merits of the large specific surface area for providing more reaction sites for Li+ ions to increase the storage capacity and the presence of oxygen vacancies and P-doping for enhancing material’s electronic conductivity and diffusion coefficient of ions, the as-designed P-TMC can display improved electrochemical properties. As a LIB anode, it can deliver a high reversible discharge capacity of 187 mAh g–1 at 0.2 C and a good long cycling performance with ∼82.6% capacity retention (101 mAh g–1) after 2500 cycles at 10 C with an average capacity loss of only 0.007% per cycle. Impressively, even the current rate increases to 100 times of the original rate, a satisfactory capacity of 104 mAh g−1 can be delivered, displaying good rate capacity. These results suggest the P-TMC a viable choice for application as an anode material in LIB applications. Also, the strategy in this work can be easily extended to the design of other high-performance electrode materials with P-doping for energy storage.
Direct chemical-vapor-deposition growth of alloyed perovskite microcrystals for tunable emissions
Authors: Shen Xia , Wu Yu , Dang Chanjuan , Li Pu , Guo Pengfei 
Published: January 2024

Abstract
Tunable composition of perovskite micro/nanostructures are perfect candidate for the designing of multifunctional optoelectronic circuits. Especially, integrated polychromatic luminescence based on the perovskite materials along a single substrate or chip is essential to the integrated photonic devices and multicolor displays. Here, we reported a synthesis of composition tunable CsPbI3(1–x)Br3x
(X = 0.65–0.9) perovskite microstructures on a single substrate via a magnetic-pulling CVD method. The PL emissions can be changed gradually from green (558 nm, 2.23 eV) to red (610 nm, 2.03 eV) under a focused 375 nm laser illumination. Furthermore, these composition-graded alloyed perovskite microcrystals show stable emissions after six months in air, which may find applications in multicolor display and broad band light sources in the future.
Structural phase transition and resistive switching properties of Cu
x
O films during post-thermal annealing
Authors: Seo Juwon , Kim Taeyoung , Kim Yoonsok , Jeong Mun Seok , Kim Eun Kyu 
Published: January 2024

Abstract
We studied the phase change and resistive switching characteristics of copper oxide (Cu
x
O) films through post-thermal annealing. This investigation aimed to assess the material’s potential for a variety of electrical devices, exploring its versatility in electronic applications. The Cu
x
O films deposited by RF magnetron sputtering were annealed at 300, 500, and 700 °C in ambient air for 4 min by rapid thermal annealing (RTA) method, and then it was confirmed that the structural phase change from Cu2O to CuO occurred with increasing annealing temperature. Resistive random-access memory (ReRAM) devices with Au/Cu
x
O/p+-Si structures were fabricated, and the ReRAM properties appeared in CuO-based devices, while Cu2O ReRAM devices did not exhibit resistive switching behavior. The CuO ReRAM device annealed at 500 °C showed the best properties, with a on/off ratio of 8 × 102, good switching endurance of ∼100 cycles, data retention for 104 s, and stable uniformity in the cumulative probability distribution. This characteristic change could be explained by the difference in the grain size and density of defects between the Cu2O and CuO films. These results demonstrate that superior and stable resistive switching properties of RF-sputtered Cu
x
O films can be obtained by low-temperature RTA.
Stacking-induced phonon transport engineering of siligene
Authors: Cao Haibin , Luo Yufeng , Jiao Wenyan , Lei Wen , Han Shihao , Liu Huijun 
Published: January 2024

Abstract
Tunable phonon transport properties of two-dimensional materials are desirable for effective heat management in various application scenarios. Here, we demonstrate by first-principles calculations and Boltzmann transport theory that the lattice thermal conductivity of siligene could be efficiently engineered by forming various stacking configurations. Unlike few-layer graphene, the stacked siligenes are found to be covalently bonded along the out-of-plane direction, which leads to unique dependence of the thermal conductivity on both the stacking order and layer number. Due to the restricted flexural phonon scattering induced by the horizontal reflection symmetry, the AA stacking configuration of bilayer siligene exhibits obviously higher thermal conductivity compared with the AB stacking. In addition, we observe increasing thermal conductivity with the layer number, as evidenced by the reduced phonon scattering phase space and Grüneisen parameter. Interestingly, the Fuchs-Sondheimer model works well for the thickness-dependent thermal conductivity of stacked siligenes.
A model-based direct inversion network (MDIN) for dual spectral computed tomography
Authors: Zhou Haichuan , Zhang Huitao , Zhao Xing , Zhang Peng , Zhu Yining 
Published: January 2024

Abstract

Objective. Dual spectral computed tomography (DSCT) is a very challenging problem in the field of imaging. Due to the nonlinearity of its mathematical model, the images reconstructed by the conventional CT usually suffer from the beam hardening artifacts. Additionally, several existing DSCT methods rely heavily on the information of the spectra, which is often not readily available in applications. To address this problem, in this study, we aim to develop a novel approach to improve the DSCT reconstruction performance. Approach. A model-based direct inversion network (MDIN) is proposed for DSCT, which can directly predict the basis material images from the collected polychromatic projections. The all operations are performed in the network, requiring neither the conventional algorithms nor the information of the spectra. It can be viewed as an approximation to the inverse procedure of DSCT imaging model. The MDIN is composed of projection pre-decomposition module (PD-module), domain transformation layer (DT-layer), and image post-decomposition module (ID-module). The PD-module first performs the pre-decomposition on the polychromatic projections that consists of a series of stacked one-dimensional convolution layers. The DT-layer is designed to obtain the preliminary decomposed results, which has the characteristics of sparsely connected and learnable parameters. And the ID-module uses a deep neural network to further decompose the reconstructed results of the DT-layer so as to achieve higher-quality basis material images. Main results. Numerical experiments demonstrate that the proposed MDIN has significant advantages in substance decomposition, artifact reduction and noise suppression compared to other methods in the DSCT reconstruction. Significance. The proposed method has a flexible applicability, which can be extended to other CT problems, such as multi-spectral CT and low dose CT.
UC-stack: a deep learning computer automatic detection system for diabetic retinopathy classification
Authors: Fu Yong , Wei Yuekun , Chen Siying , Chen Caihong , Zhou Rong , Li Hongjun , Qiu Mochan , Xie Jin , Huang Daizheng 
Published: January 2024

Abstract

Object. The existing diagnostic paradigm for diabetic retinopathy (DR) greatly relies on subjective assessments by medical practitioners utilizing optical imaging, introducing susceptibility to individual interpretation. This work presents a novel system for the early detection and grading of DR, providing an automated alternative to the manual examination. Approach. First, we use advanced image preprocessing techniques, specifically contrast-limited adaptive histogram equalization and Gaussian filtering, with the goal of enhancing image quality and module learning capabilities. Second, a deep learning-based automatic detection system is developed. The system consists of a feature segmentation module, a deep learning feature extraction module, and an ensemble classification module. The feature segmentation module accomplishes vascular segmentation, the deep learning feature extraction module realizes the global feature and local feature extraction of retinopathy images, and the ensemble module performs the diagnosis and classification of DR for the extracted features. Lastly, nine performance evaluation metrics are applied to assess the quality of the model’s performance. Main results. Extensive experiments are conducted on four retinal image databases (APTOS 2019, Messidor, DDR, and EyePACS). The proposed method demonstrates promising performance in the binary and multi-classification tasks for DR, evaluated through nine indicators, including AUC and quadratic weighted Kappa score. The system shows the best performance in the comparison of three segmentation methods, two convolutional neural network architecture models, four Swin Transformer structures, and the latest literature methods. Significance. In contrast to existing methods, our system demonstrates superior performance across multiple indicators, enabling accurate screening of DR and providing valuable support to clinicians in the diagnostic process. Our automated approach minimizes the reliance on subjective assessments, contributing to more consistent and reliable DR evaluations.
Detection of negative ions in streamer discharge in air by transient cavity ringdown spectroscopy
Authors: Fushimi Kimika , Shirai Naoki , Sasaki Koichi 
Published: January 2024

Abstract
Atmospheric-pressure discharges generated in air are expected to be electronegative, but experiments that examine negative ion densities are limited to date. In this work, we measured the temporal variation of the negative ion density in a streamer discharge generated in air. We adopted cavity ringdown spectroscopy, where negative ions were detected via weak optical absorption caused by laser photodetachment. The temporal variation of the absolute negative ion density was deduced by the transient analysis of the ringdown curve. Negative ions were detected after the disappearance of the discharge voltage and current. The negative ion density started the increase at 0.4 µs after the initiation of the discharge. The increase means the enhancement of the electron attachment frequency in the late phase of the secondary streamer with electron cooling. The survival of electrons until 0.4 µs is understood by the steep decrease in the cross section of dissociative recombination with the electron energy. The maximum negative ion density was observed at 1 µs, and it was around the noise level at 1.5 µs. The rapid decay is consistent with the destruction of negative ions by mutual neutralization with positive ions.
Color image encryption algorithm based on quantum random walk and multiple reset scrambling*
Authors: Mou Dingkang , Dong Yumin 
Published: January 2024

Abstract
In order to address the issues of privacy breaches, data tampering, and security threats in the realm of image encryption and information security, it is essential to ensure the confidentiality, integrity, and reliability of image data. In this paper, we propose a novel hybrid color image encryption scheme that increases the complexity of the key space and provides better data integrity protection by combining the quantum random walk and SHA-256 algorithm. At the same time, three chaotic systems were combined, and multiple XOR operations were introduced to effectively scramble the spatial and pixel levels of the color image. Through numerous simulation experiments and security analyses, the results demonstrate that the solution exhibits efficient encryption performance, excellent resistance to attacks, and outstanding privacy protection capabilities.
Synergistic effects of graphene additives and piston ring surface treatment on friction properties of engine oil
Authors: Zhou Long , Wang Hongshuo , Sun Guanghua 
Published: January 2024

Abstract
The use of nano-additives improves the performance of lubricants by minimizing energy loss due to friction and wear. In this study, tribological properties of cylinder liner-piston ring were improved by modifying monolayer graphene with surfactants. Additionally, surface chemical chromium coating and chemical heat treatment were conducted on the friction surfaces of specially made piston ring samples to further enhance the friction of piston ring. From the comparison of experimental results, the best lubrication performance was exhibited by the use of 0.05 wt% modified graphene nano-lubricant, which reduced the friction coefficient by approximately 31.1% and improved the anti-wear performance by approximately 59.6% compared to the base oil. In addition, the effect of the graphene nano-lubricant on the friction performance of chromium-coated samples was more substantial than that of the chemically heat-treated samples. Under high-temperature and heavy-load conditions, the corresponding friction coefficient was reduced by 15.5% and 34%, respectively, when compared to the base oils. This can be attributed to the porous surface of the chromium-coated sample, which promotes the storage of the graphene nano-lubricant. The results highlight the synergistic effect of graphene additives and piston ring surface treatment on the tribological performance.
Port-based entanglement teleportation via noisy resource states
Authors: Kim Ha Eum , Jeong Kabgyun 
Published: January 2024

Abstract
Port-based teleportation (PBT) represents a variation of the standard quantum teleportation and is currently being employed and explored within the field of quantum information processing owing to its various applications. In this study, we focus on PBT protocol when the resource state is disrupted by local Pauli noises. Here, we fully characterise the channel of the noisy PBT protocol using Krauss representation. Especially, by exploiting the application of PBT for entanglement distribution necessary in realizing quantum networks, we investigate entanglement transmission through this protocol for each qubit considering noisy resource states, denoted as port-based entanglement teleportation (PBET). Finally, we derive upper and lower bounds for the teleported entanglement as a function of the initial entanglement and the noises. Our study demonstrates that quantum entanglement can be efficiently distributed by protocols utilizing large-sized resource states in the presence of noise and is expected to serve as a reliable guide for developing optimized PBET protocols. To obtain these results, we address that the order of entanglement of two qubit states is preserved through the local Pauli channel, and identify the boundaries of entanglement loss through this teleportation channel.
Studies of reflection asymmetry in heavy nuclei
Authors: Butler P A 
Published: January 2024

Abstract
For certain combinations of protons and neutrons it is expected that the shape of atomic nuclei can undergo octupole deformation, which would give rise to reflection asymmetry or a ‘pear shape’. Here it is described how recent experiments carried out at CERN using the HIE-ISOLDE facility to accelerate radioactive beams and detect the subsequent γ-emission using the Miniball spectrometer have provided evidence that several radium and radon isotopes have either stable pear shapes or are octupole vibrational in nature. Their behaviour is compared with that of nuclei with A ≈ 150 exhibiting strong octupole correlations. It will be shown that the data on transition moments present some challenges for theory. The relevance of these measurements for atomic EDM searches will also be discussed.
Confronting dark matter freeze-in during reheating with constraints from inflation
Authors: Becker Mathias , Copello Emanuele , Harz Julia , Lang Jonas , Xu Yong 
Published: January 2024

Abstract
We investigate the production of particle Dark Matter (DM) in a minimal freeze-in model considering a non-instantaneous reheating phase after inflation.
We demonstrate that for low reheating temperatures, bosonic or fermionic reheating from monomial potentials can lead to a different evolution in the DM production and hence to distinct predictions for the parent particle lifetime and mass, constrained by long-lived particle (LLP) searches.
We highlight that such scenario predicts
parent particle decay lengths larger compared to using the instantaneous reheating approximation. Moreover, we demonstrate the importance of an accurate definition of the reheating temperature and emphasize its relevance for the correct interpretation of experimental constraints.
We explore different models of inflation, which can lead to the considered reheating potential. We find that the extent to which the standard DM freeze-in production can be modified crucially depends on the underlying inflationary model. Based on the latest CMB constraints, we derive lower limits on the decay length of the parent particle and confront these results with the corresponding reach of LLP searches.
Our findings underscore the impact of the specific dynamics of inflation on DM freeze-in production and highlight their importance for the interpretation of collider signatures.
At the same time, our results indicate the potential for LLP searches to shed light on the underlying dynamics of reheating.
Non-perturbative ⟨ϕ⟩, ⟨ϕ2 ⟩ and the dynamically generated scalar mass with Yukawa interaction in the inflationary de Sitter spacetime
Authors: Bhattacharya Sourav , Choudhury Moutushi Dutta 
Published: January 2024

Abstract
We consider a massless minimally coupled self interacting quantum scalar field coupled to fermion via the Yukawa interaction, in the inflationary de Sitter background. The fermion is also taken to be massless and the scalar potential is taken to be a hybrid, V(ϕ) = λϕ
4/4!+ βϕ
3/3! (λ>0). The chief physical motivation behind this choice of V(ϕ) corresponds to, apart from its boundedness from below property, the fact that shape wise V(ϕ) has qualitative similarity with standard inflationary classical slow roll potentials. Also, its vacuum expectation value can be negative, suggesting some screening of the inflationary cosmological constant. We choose that ⟨ϕ⟩∼ 0 at early times with respect to the Bunch-Davies vacuum, so that perturbation theory is valid initially. We consider the equations satisfied by ⟨ϕ (t) ⟩ and ⟨ϕ
2(t) ⟩, constructed from the coarse grained equation of motion for the slowly rolling ϕ. We then compute the vacuum diagrammes of various relevant operators using the in-in formalism up to three loop, in terms of the leading powers of the secular logarithms. For a closed fermion loop, we have restricted ourselves here to only the local contribution. These large temporal logarithms are then resummed by constructing suitable non-perturbative equations to compute ⟨ϕ⟩ and ⟨ϕ
2 ⟩. ⟨ϕ⟩ turns out to be at least approximately an order of magnitude less compared to the minimum of the classical potential, -3β/λ, owing to the strong quantum fluctuations. For ⟨ϕ
2 ⟩, we have computed the dynamically generated scalar mass at late times, by taking the appropriate purely local contributions. Variations of these quantities with respect to different couplings have also been presented.
Polarization state transition mechanism of light through turbid media by Monte Carlo simulation
Authors: Ren Yuhu , Jian Jimo , Tan Wenjiang , Wang Jing , Chen Tao , Zhang Haikun , Xia Wei 
Published: January 2024

Abstract
We study the propagation of polarized light through turbid media with high scattering coefficient (μ
s = 50 cm−1) and disclose the physical processes involved in the evolution of Stokes vector. The results show that the components of the Stokes vector can be expressed as the superimposition of the generalized divergence and the generalized curl of the two orthogonal electric field vectors. The components I, Q, and U can be represented as the superimposition of the generalized divergence. The components V can be conveyed as the superimposition of the generalized curl omitting the direction. Further, the depolarization of the linearly polarized light corresponds to the alteration of the generalized divergence, while the depolarization of the circularly polarized light coincides with the variability of the generalized curl omitting the direction. The evolutions of the scattering electric fields arise from the scattering of the particles, followed by the polarization state transition of the incident light and the change of the scattering phase function. Further, the circularly polarized light can preserve the polarization state better than that of the linearly polarized light with an increase of the thickness of the scattering volume.