bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Physicochemical Property Data in the ECHA Database
Authors: Glüge Juliane , Scheringer Martin
Published: October 2023

The database of the European Chemicals Agency (ECHA) is one of the most important databases that contains physicochemical properties, also because these data are used for the regulation of chemicals in the European Economic Area. The present study investigates the availability and quality of the data in the ECHA database for the logarithmic octanol–water partition coefficient (log10 KOW), solubility in water (SW), vapor pressure (pV), air–water partition coefficient, boiling point (Tb), second-order rate constant for the degradation with OH radicals, and the soil adsorption coefficient. For the evaluation of the data, calculations were run with COSMOtherm for the majority of the mono-constituent, neutral organic substances that are fully registered under the EU Regulation on the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH). The COSMOtherm data were evaluated against data from the PHYSPROP database, a manually curated database of experimental property data, to ensure that the COSMOtherm data were free of systematic errors. The comparison between COSMOtherm and the experimental data in the ECHA database showed that the data agree (within some variability) for many of the endpoints. However, there are also certain ranges with substantial discrepancies. These include log10 KOW > 8, SW < 10−3 mg/l, pV < 10−6 Pa, and Tb > 400 °C. The deviations between the non-experimental data and the COSMOtherm values are for all endpoints on average higher than the deviations between the experimental data and the COSMOtherm values. With this study, we provide COSMOtherm data for more than 4400 substances that can be used in the future for the hazard and risk assessment of these chemicals.
Empirical model for bandgaps of armchair graphene nanoribbons
Authors: Jamal G. R. Ahmed , Mominuzzaman S. M.
Published: October 2023

Based on an empirical approach, we present a relation for the bandgaps of armchair graphene nanoribbons (aGNRs) as a function of their widths and number of armchair chains. Experimental bandgaps of a number of atomically well-defined aGNRs are studied here. It is found that experimentally reported bandgaps are underestimated or overestimated by existing theoretical models. Experimental data reveal that the bandgaps of N = 3p and N = 3p + 1 families of aGNR are directly related to the width and number of armchair chains. An empirical model for calculating the bandgaps of aGNRs is devised based on theoretical and experimental observations. Calculated bandgaps offer significant corrections for armchair aGNRs compared with previous tight-binding and density functional theory studies, and the amount of correction is represented by a semi-empirical correction term. The proposed relation indicates that not only the ribbon width but also the number of armchair chains plays a crucial role in determining the values and scaling rule for the bandgaps. Compared with previous models, our estimated bandgaps from the proposed empirical model can track qualitative and quantitative patterns of the experimental bandgaps very precisely, thus helping predict the bandgap of an aGNR for potential electronic and optoelectronic applications. The proposed empirical relation also gives insight into the correlation between the physical structure and electronic properties of a GNR. Furthermore, this model can be taken as a guide for devising a similar empirical model for calculating the bandgaps of other types of GNRs.
Explainable forecasting of global horizontal irradiance over multiple time steps using temporal fusion transformer
Authors: Ait Mouloud Louiza , Kheldoun Aissa , Deboucha Abdelhakim , Mekhilef Saad
Published: October 2023

Accurate prediction of solar irradiance is essential for the successful integration of solar power plants into electrical systems. Despite recent advancements in deep learning technology yielding impressive results in solar forecasting, their lack of interpretability has hindered their widespread adoption. In this paper, we propose a novel approach that integrates a Temporal Fusion Transformer (TFT) with a McClear model to achieve accurate and interpretable forecasting performance. The TFT is a deep learning model that provides transparency in its predictions through the use of interpretable self-attention layers for long-term dependencies, recurrent layers for local processing, specialized components for feature selection, and gating layers to suppress extraneous components. The model is capable of learning temporal associations between continuous time-series variables, namely, historical global horizontal irradiance (GHI) and clear sky GHI, accounting for cloud cover variability and clear sky conditions that are often ignored by most machine learning solar forecasters. Additionally, it minimizes a quantile loss during training to produce accurate probabilistic forecasts. In this study, we evaluate the performance of hourly GHI forecasts on eight diverse datasets with varying climates: temperate, cold, arid, and equatorial, for multiple temporal horizons of 2, 3, 6, 12, and 24 h. The model is benchmarked against both climatological persistence for deterministic forecasting and Complete History Persistence Ensemble for probabilistic forecasting. To prove that our model is not location locked, it has been blind tested on four completely different datasets. The results demonstrate that the proposed model outperforms its counterparts across all forecast horizons.
Spiral room-temperature thin-filmed photo-thermoelectric THz detector based on Bi88Sb12 solid solutions
Authors: Demchenko P. S. , Tukmakova A. S. , Tkhorzhevskiy I. L. , Kablukova N. S. , Khodzitsky M. K.
Published: October 2023

A terahertz (THz) room-temperature photo-thermoelectric (PTE) detector based on elements of spiral shape has been proposed. The units have been fabricated on a 20 μm mica substrate from 150 nm thin films of Bi88Sb12 and copper by a thermal deposition technique. Thermoelectric Bi88Sb12 leg acted as a sensitive element due to its high absorption and spiral shape that enable heating. It also acts as a radiator to maintain a temperature difference and a thermo-electromotive force formation. A prototype of a PTE detector has been designed, fabricated, and tested at the 0.14 THz radiation frequency. Measurements showed a voltage signal of 275 μV from 1 unit, the responsivity of 50.7 mV/W. It showed a noise equivalent power of 158 nW Hz−1/2, which is 1–2 orders of magnitude higher than for bolometers and Golay cells, but is comparable with pyroelectric detectors. The response time was 2.21 s and 1.75 s according to the experiment and the simulation, respectively, which is a bit better than for pyroelectric detectors. Based on numerical simulation an improved detector design has been proposed allowing the voltage up to 800 μV from 1 unit. The proposed PTE detector possesses several significant advantages resulting from the usage of Bi88Sb12 and comprehensive design. The fabrication process is fast, low-cost, and CMOS-compatible. The design is compact and simple and requires only two materials that simultaneously act as an absorber, thermocouple, electrical contacts, and radiator. The detector operates at room temperature and can be applied in 6 G communication systems, imaging and medical diagnostics.
Efficient single-cell oxygen consumption rate characterization based on frequency domain fluorescence lifetime imaging microscopy measurement and microfluidic platform
Authors: Kannan Santhosh , Ko Ping-Liang , Wu Hsiao-Mei , Tung Yi-Chung
Published: October 2023

Cell metabolism is critical in regulating normal cell functions to maintain energy homeostasis. In order to monitor cell metabolism, the oxygen consumption rate (OCR) of cells has been characterized as an important factor. In conventional cell analysis, the cells are characterized in bulk due to technical limitations. However, the heterogeneity between the cells cannot be identified. Therefore, single-cell analysis has been proposed to reveal cellular functions and their heterogeneity. In this research, an approach integrating a microfluidic device and widefield frequency domain fluorescence imaging lifetime microscopy (FD-FLIM) for single-cell OCR characterization in an efficient manner is developed. The microfluidic device provides an efficient platform to trap and isolate single cells in microwells with the buffer saline containing an oxygen-sensitive phosphorescent dye. The oxygen tension variation within the microwells can be efficiently estimated by measuring the fluorescence lifetime change using the FD-FLIM, and the OCR values of the single cells can then be calculated. In the experiments, breast cancer (MCF-7) cells are exploited for the OCR measurement. The results demonstrate the functionality of the developed approach and show the heterogeneity among the cells. The developed approach possesses great potential to advance cellular metabolism studies with single-cell resolution.
A geometry-enhanced graph neural network for learning the smoothness of glassy dynamics from static structure
Authors: Jiang Xiao , Tian Zean , Li Kenli , Hu Wangyu
Published: October 2023

Modeling the dynamics of glassy systems has been challenging in physics for several decades. Recent studies have shown the efficacy of Graph Neural Networks (GNNs) in capturing particle dynamics from the graph structure of glassy systems. However, current GNN methods do not take the dynamic patterns established by neighboring particles explicitly into account. In contrast to these approaches, this paper introduces a novel dynamical parameter termed “smoothness” based on the theory of graph signal processing, which explores the dynamic patterns from a graph perspective. Present graph-based approaches encode structural features without considering smoothness constraints, leading to a weakened correlation between structure and dynamics, particularly on short timescales. To address this limitation, we propose a Geometry-enhanced Graph Neural Network (Geo-GNN) to learn the smoothness of dynamics. Results demonstrate that our method outperforms state-of-the-art baselines in predicting glassy dynamics. Ablation studies validate the effectiveness of each proposed component in capturing smoothness within dynamics. These findings contribute to a deeper understanding of the interplay between glassy dynamics and static structure.
Time-dependent probability density functions, information geometry and entropy production in a stochastic prey–predator model of fusion plasmas
Authors: Fuller Patrick , Kim Eun-jin , Hollerbach Rainer , Hnat Bogdan
Published: October 2023

A stochastic, prey–predator model of the L–H transition in fusion plasma is investigated. The model concerns the regulation of turbulence by zonal and mean flow shear. Independent delta-correlated Gaussian stochastic noises are used to construct Langevin equations for the amplitudes of turbulence and zonal flow shear. We then find numerical solutions of the equivalent Fokker–Planck equation for the time-dependent joint probability distribution of these quantities. We extend the earlier studies [Kim and Hollerbach, Phys. Rev. Res. 2, 023077 (2020) and Hollerbach et al., Phys. Plasmas 27, 102301 (2020)] by applying different functional forms of the time-dependent external heating (input power), which is increased and then decreased in a symmetric fashion to study hysteresis. The hysteresis is examined through the probability distribution and statistical measures, which include information geometry and entropy. We find strongly non-Gaussian probability distributions with bi-modality being a persistent feature across the input powers; the information length to be a better indicator of distance to equilibrium than the total entropy. Both dithering transitions and direct L-–H transitions are (also) seen when the input power is stepped in time. By increasing the number of steps, we see less hysteresis (in the statistical measures) and a reduced probability of H-mode access; intermittent zonal flow shear is seen to have a role in the initial suppression of turbulence by zonal flow shear and stronger excitation of intermittent zonal flow shear for a faster changing input power.
Exploring the free-energy landscape of a rotating superfluid
Authors: Cleary Andrew , Page Jacob
Published: October 2023

The equilibrium state of a superfluid in a rotating cylindrical vessel is a vortex crystal—an array of vortex lines, which is stationary in the rotating frame. Experimental realizations of this behavior typically show a sequence of transient states before the free-energy-minimizing configuration is reached. Motivated by these observations, we construct a new method for a systematic exploration of the free-energy landscape via gradient-based optimization of a scalar loss function. Our approach is inspired by the pioneering numerical work of Campbell and Ziff [Phys. Rev. B. 20, 1886 (1979)] and makes use of automatic differentiation, which crucially allows us to include entire solution trajectories in the loss. We first use the method to converge thousands of low free-energy relative equilibria in the unbounded domain for vortex numbers in the range 10≤N≤30, which reveals an extremely dense set of mostly saddle-like solutions. As part of this search, we discover new continuous families of relative equilibria, which are often global minimizers of free energy. These continuous families all consist of crystals arranged in a double-ring configuration, and we assess which state from the family is most likely to be observed experimentally by computing energy-minimizing pathways from nearby local minima—identifying a common entry point into the family. The continuous families become discrete sets of equal-energy solutions when the wall is introduced in the problem. Finally, we develop an approach to compute homoclinic orbits and use it to examine the dynamics in the vicinity of the minimizing state by converging connections for low-energy saddles.
Investigation of ferroelectric Ba1−xCaxZryTi1−yO3 single crystal by in situ temperature-dependent x-ray diffraction and first-principles calculations
Authors: Gadelmawla Ahmed , Spreafico Samuele , Heinemann Frank W. , Urushihara Daisuke , Liu Donglin , Li Qiang , Yan Qingfeng , Ceresoli Davide , Kimura Koji , Hayashi Kouichi , Meyer Bernd , Webber Kyle G.
Published: October 2023

In situ temperature-dependent crystal structure of lead-free ferroelectric perovskite Ba0.798Ca0.202Zr0.006Ti0.994O3 single crystal was characterized using x-ray diffraction from 170 to 380 K. Three phases were identified at different temperatures of 170, 220, and 298 K, revealing rhombohedral (R3m), orthorhombic (Pmm2), and tetragonal (P4mm) crystal structures, respectively. The change in the bond length and its distortion are reported for both AO12 and BO6 polyhedrons, allowing for the estimation of the spontaneous polarization. The Debye–Waller factor is reported as a function of temperature for A and B-sites. Density-functional theory calculations on the tetragonal phase were performed to obtain information on the distribution of the Ca ions, the local atomic displacements, and the ideal value of the spontaneous polarization of a defect-free crystal at 0 K. We find that Ca prefers to arrange in columnar 2D plates oriented along the tetragonal axis. The Ca ions avoid being next neighbors of Zr; however, the specific arrangement of Ca has only a minor impact on the spontaneous polarization.
Study on heat transfer and pressure drop characteristics for nanofluids in microchannel heat exchangers
Authors: Lalagi Gururaj , Nagaraj P. B. , Talugeri Vinayak , Bidari Mallikarjuna Veerabhadrappa
Published: October 2023

The microchannel heat exchanger (MCHE) is considered the next-generation heat exchanger owing to its high-performance thermal management systems and fabrication processes. The MCHE is used in many cooling applications, such as x ray medical devices, high-power microelectronics, and high-heat flux devices. Comprehensive exploration of different nanofluids, their concentrations, and impacts on pressure drop and heat transfer within the context of MCHEs was the main focus of the current study. The experiments were conducted at Reynolds numbers ranging from 100 to 500 for laminar flow. Additionally, nanoparticles (np) such as Al2O3, CuO, and carbon nanotubes (CNT) were added to de-ionized water at weight percentages of 0.01, 0.03, and 0.05. The results indicated that heat transfer significantly increased at a particle concentration 0.05 by wt. % for all nanofluids (nf). Furthermore, at a particle of 0.05 by wt. %, the heat transfer of the CNT-based nf increased by 37%, whereas those of the Al2O3- and CuO-based nf increased by 24.01% and 6.23%, respectively. The nanofluid pressure drop (PD) increases with an increase in the Reynolds number owing to the increase in the viscosity of the liquid compared to de-ionized water (base fluid) and requires more pumping power.
Spin current in the early stage of radical reactions and its mechanisms
Authors: Hanasaki Kota , Takatsuka Kazuo
Published: October 2023

We study the electronic spin flux (atomic-scale flow of the spin density in molecules) by a perturbation analysis and ab initio nonadiabatic calculations. We derive a general perturbative expression of the charge and spin fluxes and identify the driving perturbation of the fluxes to be the time derivative of the electron-nucleus interaction term in the Hamiltonian. We then expand the expression in molecular orbitals so as to identify relevant components of the fluxes. Our perturbation theory describes the electronic fluxes in the early stage of reactions in an intuitively clear manner. The perturbation theory is then applied to an analysis of the spin flux obtained in ab initio calculations of the radical reaction of O2 and CH3· starting from three distinct spin configurations; (a) CH3· and triplet O2 with total spin of the system set Stot=1/2 (b) CH3· and singlet O2, Stot=1/2, and (c) CH3· and triplet O2, Stot=3/2. Further analysis of the time-dependent behaviors of the spin flux in these numerical simulations reveals (i) the spin flux induces rearrangement of the local spin structure, such as reduction of the spin polarization arising from the triplet O2 and (ii) the spin flux flows from O2 to CH3· in the reaction starting from spin configuration (a) and from CH3· to O2 in that starting from configuration (b), whereas no major intermolecular spin flux was observed in that starting from configuration (c). Our study thus establishes the mechanism of the spin flux that rearranges the local spin structures associated with chemical bonds.
Polyatomic radiative association by quasiclassical trajectory calculations: Formation of HCN and HNC molecules in H + CN collisions
Authors: Szabó Péter , Gustafsson Magnus
Published: October 2023

We have developed the polyatomic extension of the established [M. Gustafsson, J. Chem. Phys. 138, 074308 (2013)] classical theory of radiative association in the absence of electronic transitions. The cross section and the emission spectrum of the process is calculated by a quasiclassical trajectory method combined with the classical Larmor formula which can provide the radiated power in collisions. We have also proposed a Monte Carlo scheme for efficient computation of ro-vibrationally quantum state resolved cross sections for radiative association. Besides the method development, the global potential energy and dipole surfaces for H + CN collisions have been calculated and fitted to test our polyatomic semiclassical method.
Sensitivity analysis of various factors on the micropolar hybrid nanofluid flow with optimized heat transfer rate using response surface methodology: A statistical approach
Authors: Baithalu Rupa , Mishra S. R. , Ali Shah Nehad
Published: October 2023

The current investigation is based on the impact of the nanoparticle shape on the micropolar hybrid nanofluid flow in a vertical plate. Furthermore, the aim of this investigation is to optimize the skin friction as well as the Nusselt number using a statistical approach known as “Response Surface Methodology” (RSM). The micropolar hybrid nanofluid is considered due to its enhanced thermal properties likely the Hamilton–Crosser thermal conductivity, Gharesim model viscosity, etc. A suitable similarity rule is adopted for the transformation of the designed model into ordinary and then solved numerically utilizing the shooting-based Runge–Kutta fourth-order technique. The simulated results of diversified parameters are presented through graphs. Furthermore, RSM is employed to design and develop a mathematical model to get an optimized hear transfer rate along with the rate of shear stress. The required components are carefully selected, and the corresponding responses are recorded. The collected data is subsequently employed in constructing a response surface through regression analysis. This process allows for the determination of optimal conditions to enhance heat transfer, which is then confirmed through analysis of variance testing. However, the major outcomes of the study are; for the case of suction with increasing particle concentrations, the shear rate, hear transfer rate, and couple stress coefficients are enhanced significantly. Furthermore, the non-Newtonian parameter and the magnetic parameter also favor in enhancing the rate coefficients.
2-thiouridine is a broad-spectrum antiviral nucleoside analogue against positive-strand RNA viruses
Authors: Uemura Kentaro , Nobori Haruaki , Sato Akihiko , Toba Shinsuke , Kusakabe Shinji , Sasaki Michihito , Tabata Koshiro , Matsuno Keita , Maeda Naoyoshi , Ito Shiori , Tanaka Mayu , Anraku Yuki , Kita Shunsuke , Ishii Mayumi , Kanamitsu Kayoko , Orba Yasuko , Matsuura Yoshiharu , Hall William W. , Sawa Hirofumi , Kida Hiroshi , Matsuda Akira , Maenaka Katsumi
Published: October 2023

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are causing significant morbidity and mortality worldwide. Furthermore, over 1 million cases of newly emerging or re-emerging viral infections, specifically dengue virus (DENV), are known to occur annually. Because no virus-specific and fully effective treatments against these or many other viruses have been approved, there is an urgent need for novel, effective therapeutic agents. Here, we identified 2-thiouridine (s2U) as a broad-spectrum antiviral ribonucleoside analogue that exhibited antiviral activity against several positive-sense single-stranded RNA (ssRNA+) viruses, such as DENV, SARS-CoV-2, and its variants of concern, including the currently circulating Omicron subvariants. s2U inhibits RNA synthesis catalyzed by viral RNA-dependent RNA polymerase, thereby reducing viral RNA replication, which improved the survival rate of mice infected with DENV2 or SARS-CoV-2 in our animal models. Our findings demonstrate that s2U is a potential broad-spectrum antiviral agent not only against DENV and SARS-CoV-2 but other ssRNA+ viruses.
Human RNase P exhibits and controls distinct ribonucleolytic activities required for ordered maturation of tRNA
Authors: Orlovetskie Natalie , Mani Dhivakar , Rouvinski Alexander , Jarrous Nayef
Published: October 2023

Precursor tRNAs are transcribed with flanking and intervening sequences known to be processed by specific ribonucleases. Here, we show that transcription complexes of RNA polymerase III assembled on tRNA genes comprise RNase P that cleaves precursor tRNA and subsequently degrades the excised 5′ leader. Degradation is based on a 3′–5′ exoribonucleolytic activity carried out by the protein subunit Rpp14, as determined by biochemical and reverse genetic analyses. Neither reconstituted nor purified RNase P displays this magnesium ion-dependent, processive exoribonucleolytic activity. Markedly, knockdown of Rpp14 by RNA interference leads to a wide-ranging inhibition of cleavage of flanking and intervening sequences of various precursor tRNAs in extracts and cells. This study reveals that RNase P controls tRNA splicing complex and RNase Z for ordered maturation of nascent precursor tRNAs by transcription complexes.
Cellular migration into a subretinal honeycomb-shaped prosthesis for high-resolution prosthetic vision
Authors: Bhuckory Mohajeet B. , Wang Bing-Yi , Chen Zhijie Charles , Shin Andrew , Huang Tiffany , Galambos Ludwig , Vounotrypidis Efstathios , Mathieson Keith , Kamins Theodore , Palanker Daniel
Published: October 2023

In patients blinded by geographic atrophy, a subretinal photovoltaic implant with 100 µm pixels provided visual acuity closely matching the pixel pitch. However, such flat bipolar pixels cannot be scaled below 75 µm, limiting the attainable visual acuity. This limitation can be overcome by shaping the electric field with 3-dimensional (3-D) electrodes. In particular, elevating the return electrode on top of the honeycomb-shaped vertical walls surrounding each pixel extends the electric field vertically and decouples its penetration into tissue from the pixel width. This approach relies on migration of the retinal cells into the honeycomb wells. Here, we demonstrate that majority of the inner retinal neurons migrate into the 25 µm deep wells, leaving the third-order neurons, such as amacrine and ganglion cells, outside. This enables selective stimulation of the second-order neurons inside the wells, thus preserving the intraretinal signal processing in prosthetic vision. Comparable glial response to that with flat implants suggests that migration and separation of the retinal cells by the walls does not cause additional stress. Furthermore, retinal migration into the honeycombs does not negatively affect its electrical excitability, while grating acuity matches the pixel pitch down to 40 μm and reaches the 27 μm limit of natural resolution in rats with 20 μm pixels. These findings pave the way for 3-D subretinal prostheses with pixel sizes of cellular dimensions.
Elucidating the clandestine behavior of enantiomeric DHPs in calcium channels
Authors: Smith Nathaniel , Sun Han
Published: October 2023

Computational study suggests that π-bulges play an integral role in the gating mechanisms of Cav channels, governing the binding of enantiomeric DHP.
Negative Poisson’s Ratios of Layered Materials by First-Principles High-Throughput Calculations
Authors: Zhao 赵 Hanzhang 汉章 , Cai 蔡 Yuxin 雨欣 , Liang 梁 Xinghao 兴昊 , Zhou 周 Kun 琨 , Zou 邹 Hongshuai 洪帅 , Zhang 张 Lijun 立军
Published: October 2023

Auxetic two-dimensional (2D) materials, known from their negative Poisson’s ratios (NPRs), exhibit the unique property of expanding (contracting) longitudinally while being laterally stretched (compressed), contrary to typical materials. These materials offer improved mechanical characteristics and hold great potential for applications in nanoscale devices such as sensors, electronic skins, and tissue engineering. Despite their promising attributes, the availability of 2D materials with NPRs is limited, as most 2D layered materials possess positive Poisson’s ratios. In this study, we employ first-principles high-throughput calculations to systematically explore Poisson’s ratios of 40 commonly used 2D monolayer materials, along with various bilayer structures. Our investigation reveals that BP, GeS and GeSe exhibit out-of-plane NPRs due to their hinge-like puckered structures. For 1T-type transition metal dichalcogenides such as MX
2 (M = Mo, W; X = S, Se, Te) and transition metal selenides/halides the auxetic behavior stems from a combination of geometric and electronic structural factors. Notably, our findings unveil V2O5 as a novel material with out-of-plane NPR. This behavior arises primarily from the outward movement of the outermost oxygen atoms triggered by the relaxation of strain energy under uniaxial tensile strain along one of the in-plane directions. Furthermore, our computations demonstrate that Poisson’s ratio can be tuned by varying the bilayer structure with distinct stacking modes attributed to interlayer coupling disparities. These results not only furnish valuable insights into designing 2D materials with a controllable NPR but also introduce V2O5 as an exciting addition to the realm of auxetic 2D materials, holding promise for diverse nanoscale applications.
Radioactivity in a bucket
Authors: Peralta Luis
Published: October 2023

In radiation physics classes, point sources are typically used, for which it is relatively easy to describe the signal obtained by a radiation detector, such as the NaI(Tl) scintillation detector. The use of large extended radiation sources is generally avoided due to the mathematical complexity that their description may involve. However, the use of Monte Carlo simulation methods allows this limitation to be overcome. Potassium chloride, containing the 40K isotope, is an ideal candidate for carrying out this type of experiment. The source activity is obtained through the detection of the 1460.8 keV gamma-photon emitted in the 40K decay. In the first experiment, a cylindrical container is used, placing the NaI(Tl) detector in its center and filling the remaining space with potassium chloride. In a second, more complex case, a large radioactive source consisting of a container filled with a mixture of sand and potassium chloride, with the NaI(Tl) detector placed in the center of the mixture, is used. In this case, the mass of potassium chloride is approximately 1/5 of the sand mass. In both experiments, the detection efficiency is obtained by Monte Carlo simulation. A careful analysis of the experimental data allows to obtain a good agreement between the measured and calculated value of the activity.
The noncollinear interlayer coupling in NiFe/NiO/NiFe trilayers
Authors: Zhan Xiaozhi , Li Jialiang , Deng Xiao , Xiao Songwen , Sun Yuan , Cheng Sheng , Bai He , Zhu Tao
Published: October 2023

The interlayer coupling and magnetization reversal behaviors in NiFe/NiO/NiFe trilayers were investigated using polarized neutron reflectivity and Monte Carlo (MC) simulations. Our results reveal that the shape of NiFe loops transitions from square to tilted as the NiO thicknesses decrease, indicating changes in the direction of NiFe layer’s easy axis. This phenomenon can be attributed to variations occurring at NiO/NiFe interfaces for different NiO layer thicknesses. With thin NiO layer, interdiffusion at the NiO/NiFe interfaces leads to frustrated coupling, resulting in a noncollinear interlayer coupling. This observation is supported by MC simulations. Conversely, hardly any coupling frustration is observed for the sample with a thick NiO layer. Our findings propose a novel way to tailor the interlayer coupling through interface engineering.
Irreversible metamagnetic transitions in Yb3+ distorted tetragonal Pr0.45Sr0.55MnO3
Authors: Dokala R K , Das S , Jangam G , Mishra P K , Thota S
Published: October 2023

Field-induced metamagnetic behavior and orbital-ordering (OO) in Yb-substituted (PrSr)MnO3 perovskites have been reported. The occurrence of distortions in the tetragonal crystal lattice leads to a reduction in the

Mn

−

O

2

−

Mn

bond angle, which in turn governs the temperature and field-dependent long-range magnetic orderings. Extensive magnetization measurements reveal the high Curie temperature

T

C

∼ 302 K ferromagnetic (FM) phase and suggest the possibility of the existence of the OO in Pr0.45–x
Yb
x
Sr0.55MnO3 accompanied by antiferromagnetic (AFM) Néel temperature,

T

N

, as low as 158 K. Irreversible metamagnetic transitions from the AFM phase to the FM phase occur for a specific composition x = 0.05 (Yb5) until

T

⩽ 220 K. The admixture of AFM and FM metastable states is quite robust in the investigated system, whereas the AFM state is mediated by Yb3+ ions, while the FM state arises as a result of field-driven thermo-magnetic kinetics. These results provide a constructive approach for designing novel spin-valve devices.
Comparative study of neural network and model averaging methods in nuclear β-decay half-life predictions
Authors: Li 李 W F 伟峰 , Zhang 张 X Y 晓燕 , Niu 牛 Y F 一斐 , Niu 牛 Z M 中明
Published: October 2023

Nuclear β-decay half-lives are investigated using the two-hidden-layer neural network and compared with the model averaging method. By carefully designing the input and hidden layers of the neural network, the neural network achieves better accuracy of nuclear β-decay half-life predictions and well eliminates the too strong odd–even staggering predicted by the previous neural networks. For nuclei with half-lives less than 1 s, the neural network can describe experimental half-lives within 1.6 times. The half-life predictions of the neural network are further tested with the newly measured half-lives, demonstrating its reliable extrapolation ability not far from the training region. Compared to the model averaging method, the neural network has higher accuracy and smaller uncertainties of half-life predictions in the known region. When extrapolated to the unknown region, the half-life uncertainties of the neural network are still smaller than those of the model averaging method within about 5–10 steps for nuclei with 35 ≲ Z ≲ 90, while the model averaging method has smaller half-life uncertainties for nuclei near the drip line.
A nonuniform demagnetizing field model for both static and dynamic responses of anisotropic magnetoresistive thin film sensors
Authors: Huang Yiya , Shan Xin , Ren Hongyu , Zhu Ronggui , Zhu Guanlun , Teng Jiao , Zhang Hui , Feng Chun , Yu Guanghua
Published: October 2023

In this paper, an anisotropic magnetoresistive (AMR) thin film sensor which can be used for magnetic scale has been prepared, and its output voltage is about 4.7–4.9 mV V−1. On the basis of the Stoner–Wohlfarth model and with considering the non-uniformity of the demagnetizing field along the width direction of the strips, both the static and dynamic responses of the AMR sensors have been calculated. The results have shown that the calculated results are in agreement with the experimental data. The magnetization rotation in the magnetic sensor strongly depends on the nonuniform demagnetizing field along the width direction. The magnetization at the center is easily rotated into the field direction, and the magnetization at the edge is difficult to be rotated. The smaller the width of the magnetoresistive strip is, the larger both the demagnetizing field at the edge and the saturation field of the magnetic sensor are. The results are helpful for understanding the magnetization rotation of magnetic sensors and developing the magnetic sensors with high performance.
Investigation of the SERS application of gold films deposited on uncured polydimethylsiloxane with tunable LSPR
Authors: Ye Ziran , Huang Haixia , Lu Ping , Chen Yiben , Shen Jiawei , Ye Gaoxiang , Yan Bo
Published: October 2023

We present an approach to investigate the localized surface plasmon resonance and surface-enhanced Raman scattering of gold films deposited on uncured polydimethylsiloxane via thermal evaporation. Differing from solid substrates, the liquid surface of uncured polydimethylsiloxane can serve as an isotropic substrate on which gold atoms nucleate and disperse to form characteristic microstructures in a controlled manner. By adjusting experimental parameters during film deposition, the absorption of resonant plasmon modes can be tuned in the visible spectral range due to the control of particle size and distribution in Au films. Furthermore, Raman measurements are conducted to investigate the enhancement of Raman signals in these films, and the experimental results are verified by simulation analysis. This work exhibits tunability of surface plasmon resonance frequency and enhanced Raman detection capability by depositing metal films on liquid surfaces, thus providing potential applications of these films in flexible biosensors and chemical detection.
Characterizing inertial particle clustering with 1D signals
Authors: Odens Mora Daniel , Aliseda Alberto , Cartellier Alain , Obligado Martin
Published: October 2023

Preferential concentration in turbulent flows laden with inertial particles still presents many open fundamental physics questions. These gaps hinder the reconciliation of different experimental and numerical studies into a coherent quantitative view, which is needed to enable accurate high resolution modeling. We examine the influence of the dimensionality of the measurement technique (1D line, 2D planes or 3D volumes) on the characterization of cluster properties/preferential concentration, and proposes an approach to disentangle the cluster-characterizing results from random contributions that could contaminate the cluster statistical analysis. We studied this effect by projecting 2D and 3D data snapshots containing inertial particle clusters onto a 1D axis. The objective was to simulate 1D sensors (widely used experimentally: hot wire, fiber optics probes, LDV/PDA, etc) with different sensing lengths. These projected records were analysed by means of one-dimensional Voronoï tessellations. For the experimental parameters explored in this study, our results retrieved average clustering properties, when the measuring window is equal or larger than the Kolmogorov length scale (η), and smaller than

10
%

of the integral length scale of the turbulence

L

. These observations are consistent with previous research using 2D and 3D datasets taken under similar experimental conditions. The raw probability density function (PDF) of the Voronoï length in 1D does not provide error-free information on the clusters size or local concentration. This measurement bias is corrected based on the histograms of the number of particles within each cluster. Importantly, the analysis of these histograms explains the well-known clusters size PDFs power law reported in previous numerical and experimental research using 2D and 3D datasets. This power-law behavior, however, spanning less than a decade, is not robust in 1D. To address this, we use conditioned statistics (on the number of particles inside each cluster) to discern between turbulence-driven clustering and random particle concentration fluctuations. This secondary analysis complements standard cluster identification algorithms that rely on Voronoï tessellations.
Physical model simulations of Hf oxide resistive random access memory device with a spike electrode structure
Authors: Yang Fei , Liu Bingkun , He Zijian , Lou Shilong , Wang Wentao , Hu Bo , Li Duogui , Jiang Shuo
Published: October 2023

Resistive memory has become an attractive new memory type due to its outstanding performance. Oxide-based resistive random access memory is one type of widely used memory whose resistance can be transformed by applying current or voltage. Memristors are widely used in various kinds of memories and neural morphological calculations. Therefore, it is of vital importance to understand the physical change mechanism of an internal memristor under stimulation to improve electrical properties of the memristor. In our studies, a device model based on Hf oxide was proposed, then completely processes of the forming, reset and set were simulated. Meantime, the generation and recombination of oxygen vacancies were considered in all the processes, making the simulation more practical. In addition, a spike electrode structure was applied, a gathering electric field can be generated in the oxide layer so that the improved device has a faster forming voltage, lower forming current and lower instantaneous power consumption in the ON state. Finally, the effects of spike electrode length on the forming process were studied, the research results reveal that a longer probe electrode can engage a lower forming voltage and accelerate the formation of conductive filaments.
Stratonovich–Khasminskii averaging principle for multiscale random Korteweg–de Vries-Burgers equation
Authors: Gao Peng
Published: October 2023

In this paper, we consider the multiscale random Korteweg–de Vries-Burgers (KdVB) equation, namely, the KdVB equation perturbated by a fast time oscillating external force and a random oscillating noise, the random oscillating noise is made up of a family of strong mixing stationary processes with singular small parameters. A Stratonovich–Khasminskii type averaging principle for multiscale random KdVB equation is established, in physics, this averaging principle can describe the asymptotic behavior for the propagation of small-amplitude long waves in nonlinear dispersive and dissipative media with singular structure and the soliton propagation in the random weakly viscous media or in the random field.
Automated marker-free longitudinal infrared breast image registration by GA-PSO
Authors: Lin Fan-Ya , Lee Chi-En , Chen Chung-Ming , Chang Yeun-Chung , Huang Chiun-Sheng
Published: October 2023

The automated marker-free longitudinal Infrared (IR) breast image registration overcomes several challenges like no anatomic fiducial markers on the body surface, blurry boundaries, heat pattern variation by environmental and physiological factors, nonrigid deformation, etc, has the ability of quantitative pixel-wise analysis with the heat energy and patterns change in a time course study. To achieve the goal, scale-invariant feature transform, Harris corner, and Hessian matrix were employed to generate the feature points as anatomic fiducial markers, and hybrid genetic algorithm and particle swarm optimization minimizing the matching errors was used to find the appropriate corresponding pairs between the 1st IR image and the nth IR image. Moreover, the mechanism of the IR spectrogram hardware system has a high level of reproducibility. The performance of the proposed longitudinal image registration system was evaluated by the simulated experiments and the clinical trial. In the simulated experiments, the mean difference of our system is 1.64 mm, which increases 57.58% accuracy than manual determination and makes a 17.4% improvement than the previous study. In the clinical trial, 80 patients were captured several times of IR breast images during chemotherapy. Most of them were well aligned in the spatiotemporal domain. In the few cases with evident heat pattern dissipation and spatial deviation, it still provided a reliable comparison of vascular variation. Therefore, the proposed system is accurate and robust, which could be considered as a reliable tool for longitudinal approaches to breast cancer diagnosis.
Superconducting joints for the 1.3 GHz persistent NMR magnet under JST-Mirai Program
Authors: Shimoyama J
Published: October 2023

Superconducting joint technologies connecting high-T
c superconducting (HTS) tapes, such as REBCO-coated conductors and Bi2223 silver-sheathed tapes, have been developed for the fabrication of superconducting magnets generating 30.5 T with persistent current operation at 4.2 K under the JST-Mirai Program since 2017. These are indirect joints using a superconducting intermediate layer to join highly crystallized HTS layers of tapes. Thus far, high I
c values of above 100 A at 77 K in the self-field have been achieved by both joints. These performances are sufficient for installation to the 30.5 T magnet, while efforts to further improve the reproducibility of high I
c for joints connecting long-length HTS tapes have been continuously made. The current status of HTS joint technologies is summarized in this paper partly from the view point of material science.
Dynamical model and numerical study of cavitation bubble in ultrasonic assisted electrochemical polishing solution of selective laser melting NiTi alloy
Authors: Che Jianwei , Shi Guangfeng , Zhou Tianwen
Published: October 2023

In the process of ultrasound assisted electrochemical polishing of selective laser melting (SLM) NiTi alloy, a large number of cavitation bubbles will be generated in the anode and cathode, and these cavitation bubbles will expand and compress rapidly until finally collapse. At the moment of collapse, high temperature and high pressure will occur, and at the same time, pressure shock wave and micro-jet will be produced, which will have a certain impact on material removal during polishing. In order to explore the mechanism of ultrasonic assisted electrochemical polishing, in this paper, the dynamics of cavitation bubbles with free interface and rigid interface are analyzed by ultrasonic assisted electrochemical polishing. The dynamics models of single cavitation bubble and two cavitation bubbles are established. The fourth order Runge–Kutta method was used to solve the model numerically, and the influence of electric field intensity, initial bubble radius, sound pressure amplitude and ultrasonic frequency on the dynamics of cavitation bubble was analyzed. The results show that in the range of f = 1–10 KHz, the initial radius of bubble is 0.01–0.05 micron, the sound pressure amplitude is 103 Pa, and the electric field intensity is 104 V m−1, the cavitation movement gradually becomes regular, and it goes through a complete process of expansion, contraction and then collapse, which is beneficial to the cavitation effect. This provides a theoretical basis for further research on the mechanism of ultrasonic assisted electrochemical polishing of SLM-NiTi alloy, which is of great significance for broadening the processing of additive manufacturing parts with low cost, high efficiency, and consistent quality.
Propagation of hollow higher-order cosh-Gaussian beam in human upper dermis
Authors: Bayraktar Mert , Elmabruk Kholoud , Duncan Juan Carlos Merlano , Chatzinotas Symeon
Published: October 2023

Optical detection, measurement, and treatment methods are widely used in the medical industry nowadays. The evolution of radiated beams, received power and beam size play vital roles while developing devices. The propagation properties of hollow higher-order cosh-Gaussian beam (HHOCGB) while propagating in human upper dermis tissue are derived analytically and analyzed numerically. The impact of the hollowness parameter, beam order, operating wavelength, and Gaussian beam waists on the beam’s intensity profile is examined. Received power and beam size variations are analyzed considering operating wavelength and Gaussian waist width. According to the results, as the beam propagates, its profile rapidly evolves into a shape with a circular Gaussian peak in the center and petals at the corner. Dark hollow regions are observed among the petals. Furthermore, the received power by HHOCGBs with a higher Gaussian waist width is more than those received by beams with a lower Gaussian waist width. However, at far field, operating at a lower wavelength prevents the increase of the beam spread. Thus, the obtained results will be significant in the bio-optical disease detection and treatment technology development.
Starting inflation from inhomogeneous initial conditions with momentum
Authors: Corman Maxence , East William E.
Published: October 2023

We investigate the circumstances under which cosmic inflation can arise from very inhomogeneous initial conditions using numerical relativity simulations.
Previous studies have not considered cases with non-zero momentum density
due to technical challenges with solving the coupled Einstein constraint
equations. Here we address these, introducing and comparing several
different ways of constructing cosmological initial conditions with
inhomogeneous scalar field and time derivative profiles. We evolve such
initial conditions with large inhomogeneities in both single- and two-field
inflationary models. We study cases where the initial gradient and
kinetic energy are much larger than the inflationary energy scale, and black
holes can form, as well as cases where the initial scalar potential energy
is comparable, as in scenarios where inflation occurs at nearly Planckian
densities, finding large-field inflation to be generally robust. We
consider examples of initial conditions where a large scalar field velocity
towards non-inflationary values would prevent inflation from occurring in
the homogeneous case, finding that the addition of large gradients in the
scalar field can actually dilute this effect, with the increased expansion
and non-vanishing restoring force leading to inflation.