bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phase behavior of metastable water from large-scale simulations of a quantitatively accurate model near ambient conditions: The liquid–liquid critical point
Authors: Coronas Luis Enrique , Franzese Giancarlo 
Published: October 2024

The molecular mechanisms of water’s unique anomalies are still debated upon. Experimental challenges have led to simulations suggesting a liquid–liquid (LL) phase transition, culminating in the supercooled region’s LL critical point (LLCP). Computational expense, small system sizes, and the reliability of water models often limit these simulations. We adopt the CVF model, which is reliable, transferable, scalable, and efficient across a wide range of temperatures and pressures around ambient conditions. By leveraging the timescale separation between fast hydrogen bonds and slow molecular coordinates, the model allows a thorough exploration of the metastable phase diagram of liquid water. Using advanced numerical techniques to bypass dynamical slowing down, we perform finite-size scaling on larger systems than those used in previous analyses. Our study extrapolates thermodynamic behavior in the infinite-system limit, demonstrating the existence of the LLCP in the 3D Ising universality class in the low-temperature, low-pressure side of the line of temperatures of maximum density, specifically at TC = 186 ± 4 K and PC = 174 ± 14 MPa, at the end of a liquid–liquid phase separation stretching up to ∼200 MPa. These predictions align with recent experimental data and sophisticated models, highlighting that hydrogen bond cooperativity governs the LLCP and the origin of water anomalies. We also observe substantial cooperative fluctuations in the hydrogen bond network at scales larger than 10 nm, even at temperatures relevant to biopreservation. These findings have significant implications for nanotechnology and biophysics, providing new insights into water’s behavior under varied conditions.
An ion soft-landing apparatus for ion transport study with surface potential measurement
Authors: Chen Qiwei , He Liluo , Liu Xianzheng , Zhu Zhen , Bai Yuchen , Zhu Yifan , Liu Jing , Zhou Xiong , Wu Kai 
Published: October 2024

An apparatus for explorations of ion transport in a medium and across an interface has been constructed. The ion soft-landing technique is used to deposit low-energy ions onto a pre-adsorbed medium layer on a metal substrate. The designed low-energy ion source can produce a mass-filtered ion beam with tens of nanoampere from solid sources such as bulk metals and salts. The kinetic energy of the ion beam can be lower than 1.0 eV, enabling the ions to be soft-landed onto the medium at the surface. A Kelvin probe with a resolution of less than 32 mV is incorporated to measure the surface potential (SP) variation of the ion-landed sample to monitor the ion transport process in the medium. Temperature-programmed SP measurements on an Ag+-adsorbed ice film prepared on Pt(111) reveal that the temperature threshold for the Ag+-induced SP change of the ice film is about 110 K. The apparatus performance demonstrates its potential in studies of ion transport and related phenomena at both macroscopic and microscopic levels.
Proton transfer driven by the fluctuation of water molecules in chitin film
Authors: Matsui Hiroshi , Takebe Yusuke , Takahashi Masae , Ikemoto Yuka , Matsuo Yasumitsu 
Published: October 2024

Proton-transfer mechanisms and hydration states were investigated in chitin films possessing the functionality of fuel-cell electrolytes. The absolute hydration number per chitin molecule (N) as a function of relative humidity (RH) was determined from the OH stretching bands of H2O molecules, and the proton conductivity was found to enhance above N = 2 (80%RH). The FIR spectrum at 500–900 cm−1 for 20%RH (N &lt; 1) together with first-principles calculations clearly shows that the w1 site has the same hydration strength as the w2 site. The molecular dynamics simulations for N = 2 demonstrate that H2O molecules with tiny fluctuations are localized on w1 and w2, and the hydrogen-bond (HB) network is formed via the CH2OH group of chitin molecules. Shrinkage of the O–O distance (dOO), which synchronizes with the barrier height, is required for proton transfer from H3O+ to adjacent CH2OH groups or H2O molecules. Nevertheless, dOO is hardly modulated for N = 2 because H2O molecules are strongly constrained on w1 and w2, and therefore, the transfer probability becomes small. For N = 3, novel HBs emerged between the additional H2O molecules broadly distributed on the w3 site and H2O molecules on w1 and w2. The transfer probability is enhanced because large fluctuations and diffusions in the whole H2O molecule yield large modulations of dOO. Consequently, long-range proton hopping is driven by the Zundel-type protonated hydrates in the water network.
Competing excitation quenching and charge exchange in ultracold Li-Ba+ collisions
Authors: Xing Xiaodong , Weckesser Pascal , Thielemann Fabian , Jónás Tibor , Vexiau Romain , Bouloufa-Maafa Nadia , Luc-Koenig Eliane , Madison Kirk W , Orbán Andrea , Xie Ting , Schaetz Tobias , Dulieu Olivier 
Published: October 2024

Abstract
Hybrid atom-ion systems are a rich and powerful platform for studying chemical reactions, as they feature both excellent control over the electronic state preparation and readout as well as a versatile tunability over the scattering energy, ranging from the few-partial wave regime to the quantum regime. In this work, we make use of these excellent control knobs, and present a joint experimental and theoretical study of the collisions of a single 138Ba+ ion prepared in the

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metastable states with a ground state 6Li gas near quantum degeneracy. We show that in contrast to previously reported atom-ion mixtures, several non-radiative processes, including charge exchange, excitation exchange and quenching, compete with each other due to the inherent complexity of the ion-atom molecular structure. We present a full quantum model based on high-level electronic structure calculations involving spin-orbit couplings. Results are in excellent agreement with observations, highlighting the strong coupling between the internal angular momenta and the mechanical rotation of the colliding pair, which is relevant in any other hybrid system composed of an alkali-metal atom and an alkaline-earth ion.
Magneto-optical Goos–Hänchen shift in uniaxial anisotropic epsilon-near-zero metamaterials
Authors: Sun Yi , Zhang Zan , Zhang Jing , Yang Chenfei , Zhuang Chuhong , Deng Dongmei 
Published: October 2024

Abstract
We theoretically investigate the enhancement of the magneto-optical Goos–Hänchen (MOGH) shift in multilayer structure combining uniaxially anisotropic epsilon-near-zero (ENZ) metamaterials with magneto-optical (MO) materials. The structure enables the excitation of MO surface plasmon resonance (MOSPR) without the need for a prism or grating coupler, thereby achieving a significant enhancement of the MOGH shift. The effect of the thickness of the ENZ layer and the type of magnetic metal in this structure on the MOGH shift is also discussed. Based on the above structure, we design a high-sensitivity miniature biosensor that is used for the detection of hemoglobin concentration in human blood. The maximum sensitivity achievable with this sensor is 1.4 × 106 λ/RIU. The results of this investigation contribute to the development of biosensors towards miniaturization and integration.
Point cloud segmentation method based on an image mask and its application verification
Authors: Cao Jiayong , Liu Chenshu , Liu Hu , Wu Shihao 
Published: October 2024

Abstract
Accurately perceiving three-dimensional (3D) environments or objects is crucial for the advancement of artificial intelligence interaction technologies. Currently, various types of sensors are employed to obtain point cloud data for 3D object detection or segmentation tasks. While this multi-sensor approach provides more precise 3D data than monocular or stereo cameras, it is also more expensive. The advent of RGB-D cameras, which provide both RGB images and depth information, addresses this issue. In this study, we propose a point cloud segmentation method based on image masks. By using an RGB-D camera to capture color and depth images, we generate image masks through object recognition and segmentation. Given the mapping relationship between RGB image pixels and point clouds, these image masks can be further used to extract the point cloud data of the target objects. The experimental results revealed that the average accuracy of target segmentation was 84.78%, which was close to that of PointNet++. Compared with three traditional segmentation algorithms, the accuracy was improved by nearly 23.97%. The running time of our algorithm is reduced by 95.76% compared to the PointNet++ algorithm, which has the longest running time; and by 15.65% compared to the LCCP algorithm, which has the shortest running time among traditional methods. Compared with PointNet++, the segmentation accuracy was improved. This method addressed the issues of low robustness and excessive reliance on manual feature extraction in traditional point cloud segmentation methods, providing valuable support and reference for the accurate segmentation of 3D point clouds.
A novel method: YOLO-CE and 3D point cloud-based feature extraction for welding seams of tower bases
Authors: Pan Haihong , Wang Longyou , Fu Yu , Jia Bingqi , Chen Lin 
Published: October 2024

Abstract
Robotic automated welding of non-standard steel structures presents significant challenges, particularly for electric power tower bases. This study introduces a novel approach that integrates the You Only Look Once—Compact Invert Block and Efficient Local Attention (YOLO-CE) model, an enhanced version of YOLOV8 for 2D image segmentation, with 3D point cloud technology. The YOLO-CE model is used to accurately extract point cloud data from the target area, which is then processed using the MSAC algorithm for efficient plane segmentation. Weld lines are identified through plane equations, allowing for initial weld point cloud extraction. To further refine accuracy, an optimized evaluation equation is developed that accounts for both the distance between the weld point cloud and the fitted plane, and the angle between their normal vectors. This enables precise classification of the weld point cloud. From this classification, key weld feature points are identified, and their exact positions are determined by calculating the distances between these points and their intersections with three planes. The reliability of the proposed method was validated using a robot for precise measurements, with a total error margin of less than 1.5084 mm, demonstrating high accuracy and stability. Post-operation inspections confirmed that the welds were filled and free from defects, meeting all process requirements. The YOLO-CE model achieved a mIoU of 96.38% and a precision of 99.8%, highlighting its effectiveness. This method provides an efficient and precise solution for the automated welding of non-standard steel structural components and has promising application potential.
Compact and simple antenna inspection testing range for 5G smartphones
Authors: Lee Jisu , Kim Jinjoo , Lee Soonyoong , Kim Namkyoung , Jung Kyung-Young 
Published: October 2024

Abstract
Over-the-air antenna performance evaluation in the millimeter-wave band often relies on compact antenna test range systems, which require large reflectors and a substantial measurement range volume. Such setups are impractical for rapid testing in space-constrained environments such as antenna fault diagnosis in smartphone manufacturing facilities. This paper presents a novel design methodology for highly compact antenna inspection testing range utilizing offset parabolic reflectors specifically designed for 5G smartphones. The proposed design system employs three small offset parabolic reflectors configured to account for beam tilting caused by smartphone back covers, eliminating the need to physically reposition the smartphone during testing. By directing electromagnetic fields toward a fixed receiver antenna from multiple angles corresponding to different antenna module positions, the system streamlines the test procedure, significantly reducing measurement time and measurement range volume. The proposed antenna inspection testing range provides a cost-effective and efficient solution for 5G antenna fault diagnosis in manufacturing facilities, ensuring rapid and reliable inspection while minimizing space requirements on the production line.
Size and shape dependence of hydrogen-induced phase transformation and sorption hysteresis in palladium nanoparticles
Authors: Sun Xingsheng , Jin Rong 
Published: October 2024

Abstract
Phase transitions of metals in hydrogen (H) environments are critically important for applications in energy storage, catalysis, and sensing. Nanostructured metallic particles can lead to faster charging and discharging kinetics, increased lifespan, and enhanced catalytic activities. However, establishing a direct causal link between nanoparticle structure and function remains challenging. In this work, we establish a computational framework to explore the atomic configuration of a metal-hydrogen system when in equilibrium with a H environment. This approach combines Diffusive Molecular Dynamics with an iteration strategy, aiming to minimize the system’s free energy and ensure uniform chemical potential across the system that matches that of the H environment. Applying this framework, we investigate H chemical potential-composition isotherms during the hydrogenation and dehydrogenation of palladium nanoparticles, ranging in size from 3.9 nm to 15.6 nm and featuring various shapes including cube, rhombic dodecahedron, octahedron, and sphere. Our findings reveal an abrupt phase transformation in all examined particles during both H loading and unloading processes, accompanied by a distinct hysteresis gap between absorption and desorption chemical potentials. Notably, as particle size increases, absorption chemical potential rises while desorption chemical potential declines, consequently widening the hysteresis gap across all shapes. Regarding shape effects, we observe that, at a given size, cubic particles exhibit the lowest absorption chemical potentials during H loading, whereas octahedral particles demonstrate the highest. Moreover, octahedral particles also exhibit the highest desorption chemical potentials during H unloading. These size and shape effects are elucidated by statistics of atomic volumetric strains resulting from specific facet orientations and inhomogeneous H distributions. Prior to phase transformation in absorption, a H-rich surface shell induces lattice expansion in the H-poor core, while before phase transformation in desorption, surface stress promotes lattice compression in the H-rich core. The magnitude of the volumetric strains correlates well with the size and shape dependence, underlining their pivotal role in the observed phenomena.
Method for measuring the energy transfer upconversion rate of laser crystal for solid-state lasers
Authors: Huang Lei , Pan Wu , Xu Xuesen , Zhang Nana , Liu Ziqi , Chen Shanshan , Yang Huan , Li Renpu , Guo Yongrui 
Published: October 2024

Abstract
A new method for measuring the energy transfer upconversion (ETU) rate of laser crystal for solid-state lasers is provided in this paper. When the ETU effect is considered, the laser’s output power can be expressed in terms of the input power, the ETU rate and the nonradiative lifetime. Multiple sets of binary equations about the ETU rate and the nonradiative lifetime can be obtained by substituting the measured laser input–output powers into the equation of laser output power. By solving the binary equations, the ETU rate and the nonradiative lifetime of the laser crystal can be obtained simultaneously. Employing this method, the measured average values of ETU rate and nonradiative lifetime of the Nd:YLF (Nd3+, 1.0 at.%) crystal are 3.930 × 10−23 m3 s−1 and 6.274 × 10−3 s, respectively. The measured results are further analysed and discussed, showing the feasibility of the method. We believe that the proposed method can offer a good reference for measuring the ETU rate of new laser crystals.
Synthesis of poly (N-isopropylacrylamide)-poly(ε-caprolactone) for temperature-controlled wettability of poly(L-lactic acid)
Authors: Lu Jian , Xia Wenlong , Ye Xiangyang , Song Xiaofeng 
Published: October 2024

Abstract
The biomaterials that can respond to environmental stimuli have attracted increasing attention because their applications will greatly expand the boundaries of modern medicine. In the work, poly(N-isopropylacrylamide)-poly(ε-caprolactone) (PNIPAm-PCL) with the low critical solution temperature (LCST) was synthesized by a combination of chain transfer and ring-opening method to endow poly (lactic acid) (PLLA) with the temperature-controlled wettability. The effects of PNIPAm-PCL on the thermal properties, mechanical properties, and temperature-controlled wettability were studied. At 20 wt% of PNIPAm-PCL/PLLA, the tensile strength of the material reduces slightly, but its elongation at break is enhanced significantly, which reaches 135.1%. PNIPAm-PCL/PLLA exhibits good temperature-controlled wettability. With the temperature rising from 0 to 45 °C, the water contact angle increases from 29.8° to 80.1°; conversely, it goes down, and there is a hysteresis. The material still has good stability and degradability. This work provides an example for the development of intelligent tissue engineering materials.
Shift of plasmon resonance in silver nanoparticles: effect of magnetic field pre-treatment
Authors: Redko Roman , Shvalagin Vitaliy , Milenin Grigorii , Redko Svitlana , Sarikov Andrey 
Published: October 2024

Abstract
A novel magnetic field induced phenomenon in ZnO/Ag nanoparticles is detected and investigated with reference to the surface plasmon resonance (SPR) effect. A shift of the maximum of plasmon absorption of the ZnO/Ag nanoparticles formed in different days in magnetic field treated ZnO/ethanol solutions was observed. The observed phenomena were explained in terms of the ferromagnetic-like properties of the ZnO nanoparticles due to the surface broken bonds, which result in the appearance of non-zero magnetic moments. Magnetic field pre-treatment may be used as an effective tool for manipulating the plasmon properties of silver-based nanoparticles, which is perspective for creating new-generation sensor systems.
Classification of EEG evoked in 2D and 3D virtual reality: traditional machine learning versus deep learning
Authors: Zuo MingLiang , Yu BingBing , Sui Li 
Published: October 2024

Abstract

Backgrounds. Virtual reality (VR) simulates real-life events and scenarios and is widely utilized in education, entertainment, and medicine. VR can be presented in two dimensions (2D) or three dimensions (3D), with 3D VR offering a more realistic and immersive experience. Previous research has shown that electroencephalogram (EEG) profiles induced by 3D VR differ from those of 2D VR in various aspects, including brain rhythm power, activation, and functional connectivity. However, studies focused on classifying EEG in 2D and 3D VR contexts remain limited. Methods. A 56-channel EEG was recorded while visual stimuli were presented in 2D and 3D VR. The recorded EEG signals were classified using two machine learning approaches: traditional machine learning and deep learning. In the traditional approach, features such as power spectral density (PSD) and common spatial patterns (CSP) were extracted, and three classifiers—support vector machines (SVM), K-nearest neighbors (KNN), and random forests (RF)—were used. For the deep learning approach, a specialized convolutional neural network, EEGNet, was employed. The classification performance of these methods was then compared. Results. In terms of accuracy, precision, recall, and F1-score, the deep learning method outperformed traditional machine learning approaches. Specifically, the classification accuracy using the EEGNet deep learning model reached up to 97.86%. Conclusions. EEGNet-based deep learning significantly outperforms conventional machine learning methods in classifying EEG signals induced by 2D and 3D VR. Given EEGNet’s design for EEG-based brain-computer interfaces (BCI), this superior classification performance suggests that it can enhance the application of 3D VR in BCI systems.
Additive manufacturing of multiscale NiFeMn multi-principal element alloys with tailored composition
Authors: Mooraj Shahryar , Fu Jintao , Feng Shuai , K Ng Alexander , Duoss Eric B , Baker Sarah E , Zhu Cheng , Detsi Eric , Chen Wen 
Published: October 2024

Abstract
Nanostructured multi-principal element alloys (MPEAs) have been explored as next-generation engineering materials due to unique mechanical and functional properties which have significant advantages over traditional dilute alloys. However, the practical applications of nanostructured MPEAs are still limited due to the lack of scalable processing approaches to prepare a large quantity of nanostructured MPEAs, as well as lack of an efficient pathway for high-throughput discovery of better functional nanostructured MPEAs within their vast compositional space. Here we tackle these challenges by presenting an integrated approach by combining direct-ink-writing-based additive manufacturing, solid-state sintering, and chemical dealloying to manufacture hierarchically porous MPEAs. The hierarchical structure is comprised of macro- and micro-scale pores introduced via extrusion printing and polymer decomposition during sintering, as well as nanoscale pores formed via chemical dealloying. The macro- and micro-scale pores allow efficient dealloying of a large mass of material as the diffusion length that the corroding medium must penetrate remains at the scale of the ligaments formed after sintering (∼10 μm), despite the large volume of the 3D-printed samples. In addition, this integrated approach enables versatile control of the alloy composition via precisely tuning the ratio of elemental powders in the starting ink, thus offering a pathway for high-throughput discovery of novel functional MPEAs. As a case study, multiscale macro/micro/nanoporous NiFeMn MPEAs with three different compositions were investigated as catalysts to reduce the overpotential of oxygen evolution reaction (OER), where NiFeMn-based electrocatalysts display composition-dependent performance such that the overpotential measured at a current of 0.5 A g−1 for OER increases in the order of Ni58Fe29Mn13 ⩽ Ni64Fe26Mn10 < Ni76Fe18Mn6. This introduced manufacturing process offers new opportunities for scalable fabrication and rapid screening of nanostructured multi-component complex alloys.