bluuebunny/crossref_metadata_2025 huggingface dataset:
Static magnetic fields in regenerative medicine
Authors: Xie Wenjing , Song Chao , Guo Ruowen , Zhang Xin
Published: March 2024

All organisms on Earth live in the weak but ubiquitous geomagnetic field. Human beings are also exposed to magnetic fields generated by multiple sources, ranging from permanent magnets to magnetic resonance imaging (MRI) in hospitals. It has been shown that different magnetic fields can generate various effects on different tissues and cells. Among them, stem cells appear to be one of the most sensitive cell types to magnetic fields, which are the fundamental units of regenerative therapies. In this review, we focus on the bioeffects of static magnetic fields (SMFs), which are related to regenerative medicine. Most reports in the literature focus on the influence of SMF on bone regeneration, wound healing, and stem cell production. Multiple aspects of the cellular events, including gene expression, cell signaling pathways, reactive oxygen species, inflammation, and cytoskeleton, have been shown to be affected by SMFs. Although no consensus yet, current evidence indicates that moderate and high SMFs could serve as a promising physical tool to promote bone regeneration, wound healing, neural differentiation, and dental regeneration. All in vivo studies of SMFs on bone regeneration and wound healing have shown beneficial effects, which unravel the great potential of SMFs in these aspects. More mechanistic studies, magnetic field parameter optimization, and clinical investigations on human bodies will be imperative for the successful clinical applications of SMFs in regenerative medicine.
Physical simulation study on production characteristics and mechanism of connate water in gas reservoirs
Authors: Zhou Mengfei , Li Xizhe , Hu Yong , Xu Xuan , He Chang , Zhan Hongming , Huang Yize
Published: March 2024

The late-stage development of gas reservoirs often encounters the paradox of significant remaining formation pressure coupled with low wellhead pressure, which indicates small drainage volume, low gas production rate, and low recovery efficiency, reducing gas supply and economic benefit. Owing to the lack of experimental research, the reasons behind this contradiction between gas production and producing pressure differential are unclear. The key factors affecting the development outcomes are reservoir permeability and initial water saturation, while the evaluation parameters include gas and water production rates, reservoir pressure, and recovery efficiency. Based on the characteristic properties of typical gas fields, physical simulation experiments of constant-rate gas production are conducted on spliced long cores with average permeabilities of 2.300, 0.486, and 0.046 millidarcy (mD). Furthermore, leveraging the multi-point embedded pressure measurement technique, the pressure drawdown propagations and the macroscopic and microscopic characteristics of connate water production at the initial water saturations of 0%, 20%, 40%, and 55% are investigated. By connate water, we mean water that occurs naturally within the pores of rock. Pre- and post-experiment core weighing and nuclear magnetic resonance testing are performed. In addition to the mercury injection tests, the results indicate that during gas reservoir depletion, connate water primarily stems from macropores and mesopores, with micropores and nanopores capturing water through capillary imbibition. Moreover, lower permeability and higher initial water saturation lead to greater pressure gradients, increased connate water production, and reduced recovery efficiency. Reservoirs with permeabilities below 0.1 mD are significantly affected by connate water, exhibiting steep pressure profiles. Owing to connate water, the near-wellbore pressure quickly decreases, while distant reservoir pressure barely decreases, implying a limited drainage area. To enhance the recovery efficiency, measures like infill drilling and reservoir stimulation are recommended for low-permeability gas reservoirs.
Free convection in a differentially heated square cavity filled with low-Prandtl-number materials: Numerical studies using transition shear stress transport model
Authors: Das Karmakar Satyajit , Dutta Prasun , Chattopadhyay Himadri
Published: March 2024

Computing the flow field under free convection in a cavity becomes particularly challenging for low-Prandtl-number (Pr) fluids typically encountered for liquid metals. The objective of the present study is to investigate the natural convection process in a differentially heated square cavity employing the transition shear stress transport (SST) model for the Prandtl number Pr∈[0.001,0.1] and the Rayleigh number Ra∈[104,1010]. The mean flow field is visualized through streamlines, isotherms, non-dimensional velocity, and temperature profiles, turbulence intensity, contours of intermittency (γ) times, the production of turbulent kinetic energy (Pκ), and distribution of skin friction coefficient and the Nusselt number (Nu). The transition SST model can capture the mean flow field and thermal transport over the entire parametric regime successfully. An average Nusselt number (Nu¯) on the hot wall is found to scale with a certain power (n) of the Boussinesq number (Bo), the product of Ra and Pr. The value of n is 0.18 for Ra up to 106 and 0.25 for higher Ra.
Study on water entry into shallow-water current using smoothed particle hydrodynamics method
Authors: Zhao Ke , Yang Sheng-Fa , Ming Fu-Ren , Yuan Pei-Yin
Published: March 2024

Water entry is a typical problem in shipbuilding and ocean engineering. When the ship entering shallow-water current, the combined effects of current and water bottom will complicate the fluid field and further affect the hydrodynamic responses of the ship. In this paper, a two-dimensional bow section entering shallow-water current is studied by smoothed particle hydrodynamics method and the accuracy of the method is first validated. Then, the flows around the hull in shallow and deep water are compared. It is found that the shallow water will produce a more significant effect of flow around the hull, resulting in an increasing in the diffusion velocity of the vortex structure and the related flow-induced forces. The asymmetry of free surface is more obvious in shallow water. Furthermore, the water entries into current and into still water under different water depths are simulated, respectively. When entering shallow-water current, several asymmetrical stagnation-point regions will be induced, which intensify the variation and asymmetric distribution of velocity in the fluid around the hull. Due to the bottom effect in shallow water, the pressure on the hull's lower part increases and two obvious pressure peaks will be caused. The influence of water depth on the pressure gradually disappears as the gauging point gets higher. Accordingly, the vertical force under shallow water also has two peaks and is higher than that under deep water. Moreover, when entering shallow-water current, there will be a greater decrease in vertical velocity than entering still water.
Effect of turbulent coflows on the dynamics of turbulent twin jets
Authors: Homayounfar Farzin , Khorsandi Babak , Gaskin Susan
Published: March 2024

The impact of turbulent coflows on the dynamics of turbulent twin round jets is investigated experimentally. Parallel twin jets, at three jet spacing values and two Reynolds number/jet-to-coflow velocity ratios, were released into turbulent coflows with two distinct levels of turbulence intensity. Velocity measurements were made using acoustic Doppler velocimetry. An increase in the coflow turbulence intensity leads to an earlier merging and combining of the jets and also accelerates the rate of decay with downstream distance of the mean centerline excess velocity of the jets. The mean velocity on the symmetry line, for different values of jet spacing, ratios of jet exit velocity to coflow mean velocity, and coflow turbulence intensity, is self-similar when scaled by the maximum mean velocity on the symmetry line and the corresponding streamwise distance. Moreover, as the turbulence level of the coflow intensifies, the turbulence intensity along the symmetry line of the jets increases. The longitudinal integral length scale on the symmetry line of the twin jets decreases as the coflow turbulence intensity increases. The energy spectra of the coflowing twin jets show that the turbulence in the coflow transfers the energy contained by the larger scales to the smaller scales at a greater rate than that which occurs for jets in a quiescent background. However, as the jet spacing increases, less energy is transferred to the smaller scales.
Pillararene-based donor–acceptor complex for ferroelectric self-assembled supramolecular materials
Authors: Cao Shuai , Song Leqian , Zheng Yangyang , Nguyen Kim Truc , Zhang Huacheng , Han Jie
Published: March 2024

The investigation of ferroelectric materials is an important aspect of condensed matter physics. Compared to the traditional inorganic ferroelectric ones, organic ferroelectric materials possess unique advantages, including light weight, scalability, flexibility, and solvent treatability. However, the study of organic ferroelectric materials is still in its infancy, especially from the view of supramolecular chemistry; various mechanisms of forming self-assembly and thus diverse building blocks employed are not yet to be further developed. Herein, a pillararene-based charge transfer (CT) self-assembly was produced by utilizing pillar[5]quinone (P5Q) as the electron acceptor and phenothiazine (PTZ) as the electron donor. Compared to the intrinsic P5Q, our fabricated donor–acceptor complex displays particular intriguing features, such as the enhanced second-harmonic generation and ferroelectric responses, benefiting from the CT interaction between P5Q and PTZ. The current work provides a unique strategy for the successful construction of supramolecular ferroelectrics.
High-throughput measurement of elastic moduli of microfibers by rope coiling
Authors: Liu Yuan , Lo Jack H. Y. , Nunes Janine K. , Stone Howard A. , Shum Ho Cheung
Published: March 2024

There are many fields where it is of interest to measure the elastic moduli of tiny fragile fibers, such as filamentous bacteria, actin filaments, DNA, carbon nanotubes, and functional microfibers. The elastic modulus is typically deduced from a sophisticated tensile test under a microscope, but the throughput is low and limited by the time-consuming and skill-intensive sample loading/unloading. Here, we demonstrate a simple microfluidic method enabling the high-throughput measurement of the elastic moduli of microfibers by rope coiling using a localized compression, where sample loading/unloading are not needed between consecutive measurements. The rope coiling phenomenon occurs spontaneously when a microfiber flows from a small channel into a wide channel. The elastic modulus is determined by measuring either the buckling length or the coiling radius. The throughput of this method, currently 3,300 fibers per hour, is a thousand times higher than that of a tensile tester. We demonstrate the feasibility of the method by testing a nonuniform fiber with axially varying elastic modulus. We also demonstrate its capability for in situ inline measurement in a microfluidic production line. We envisage that high-throughput measurements may facilitate potential applications such as screening or sorting by mechanical properties and real-time control during production of microfibers.
Predictive phage therapy for
Escherichia coli
urinary tract infections: Cocktail selection for therapy based on machine learning models
Authors: Keith Marianne , Park de la Torriente Alba , Chalka Antonia , Vallejo-Trujillo Adriana , McAteer Sean P. , Paterson Gavin K. , Low Alison S. , Gally David L.
Published: March 2024

This study supports the development of predictive bacteriophage (phage) therapy: the concept of phage cocktail selection to treat a bacterial infection based on machine learning (ML) models. For this purpose, ML models were trained on thousands of measured interactions between a panel of phage and sequenced bacterial isolates. The concept was applied to
Escherichia coli
associated with urinary tract infections. This is an important common infection in humans and companion animals from which multidrug-resistant (MDR) bloodstream infections can originate. The global threat of MDR infection has reinvigorated international efforts into alternatives to antibiotics including phage therapy.
E. coli
exhibit extensive genome-level variation due to horizontal gene transfer via phage and plasmids. Associated with this, phage selection for
E. coli
is difficult as individual isolates can exhibit considerable variation in phage susceptibility due to differences in factors important to phage infection including phage receptor profiles and resistance mechanisms. The activity of 31 phage was measured on 314 isolates with growth curves in artificial urine. Random Forest models were built for each phage from bacterial genome features, and the more generalist phage, acting on over 20% of the bacterial population, exhibited F1 scores of >0.6 and could be used to predict phage cocktails effective against previously untested strains. The study demonstrates the potential of predictive ML models which integrate bacterial genomics with phage activity datasets allowing their use on data derived from direct sequencing of clinical samples to inform rapid and effective phage therapy.
Resonance frequency band structure in heterojunction of one-dimension string-ball chain system
Authors: Li Boxi , Liu Chunling
Published: March 2024

Using the concept of heterostructures in semiconductor physics and the similarity between the Schrödinger equation and the vibration equation of the one-dimension string-ball chain system, we create a heterojunction in our string-ball chain system by assembling a string-ball chain with two kinds of mass in a lattice-matched and an unmatched system and study the two systems through first-principle calculation, theoretical analysis, and experiment perspectives. A discontinuity in the frequency dependence is observed in the matched system, while a phase transition is discovered in the unmatched system. A proper theoretical analysis based on the wave function is also given to explain these phenomena.
How often does unguided peer interaction lead to correct response consensus? An example from conceptual survey of electricity and magnetism
Authors: Ghimire Apekshya , Singh Chandralekha
Published: March 2024

In this research, we investigated the impact of peer collaboration and changes from individual to group performance of graduate students on the conceptual survey of electricity and magnetism (CSEM) without any guidance from the instructor. We define construction of knowledge as a case in which the group answered the question correctly but in the individual administration of the survey before the group work, one member gave the correct answer and the other gave incorrect answer. We find that there was a significant improvement in the performance of students after peer interaction, which was mostly attributed to construction of knowledge. However, students had very few opportunities to co-construct knowledge as there were hardly any situations in which neither student in a group provided a correct answer. We analyzed the effect size for improvement from individual to group scores for each CSEM item to understand the characteristics of these questions that led to productive group interaction. We also compared the group performance of the graduate students to the introductory physics students in a prior study using the CSEM to get insight into the concepts that showed differences for the two groups and those that were challenging for both groups of students before and after collaboration with peers. Our findings can motivate physics instructors to incorporate group interactions both inside and outside of the classroom even without instructor’s involvement so that students at all levels can learn from each other and develop a functional understanding of the underlying concepts.
Speckle interference for naked-eye detection of vibrations
Authors: Córdova Zahid G , Limón Dana S , Torres Jesús A
Published: March 2024

An affordable optical project for students is explained in this work. The experiment only requires a handheld laser illuminating a structure with stationary vibrations induced, but the interpretation of this phenomenon demands a strong understanding of optical interference and modal behavior of a bar. The operating principle employs the speckle phenomenon, which is a type of interference between coherent light incident on a rough surface and its reflection. This interference occurs in a luminous plane outside of the vibrating object and shows a granular structure due to the brightness fluctuations. Speckle is static but if the surface illuminated oscillates, the plane of interference moves from one side to the other, causing a streak pattern. Mode shapes of the object under examination can be naked eye detected from streak patterns. What is more, this phenomenon can be photographed using a manual focus digital camera. Therefore all the components of the procedure can be available (or acquired) by almost any physics laboratory, at any level, which would be unthinkable for optical experiments just a few years ago.
Customizing superior surface insulation properties of polymeric dielectric via in-plane molecular chain orientation
Authors: Zeng Jiakai , Li Zhiyuan , Zhou Yihan , Yang Liuqing , Liu Wenfeng , Chi Xiaohong , Cheng Lu , Li Shengtao
Published: March 2024

Surface flashover is a common breakdown phenomenon on material surfaces for which surface charge migration property, determined by surface composition and molecular chain structure, is crucial. Precise modulation of charge migration property by simple and efficient methods to improve surface flashover voltage is the goal in industry. Here, in-plane molecular chain orientation (MCO) modulation by uniaxial stretching was proposed to achieve this goal and investigate the intrinsic mechanism of charge migration on flashover. Flashover voltage and accompanying leakage current, performed with electrodes oriented at varying angles to the MCO direction, show a consistent trend, which skillfully reveals that the facilitated charge migration is favorable for improving flashover voltage. When the stretching ratio is 3.5, the flashover voltage along the stretching direction (SD) increases by up to 48.7%, while the in-plane minimum flashover voltage remains essentially unchanged with the change in stretching ratio. Molecular chain segment motion properties along different directions further elucidate that the surprising improvement of flashover voltage along SD is primarily due to the MCO that promotes intra-chain charge migration. This work provides a new perspective on anti-flashover modification of polymeric dielectric and will promote the development of surface flashover mechanisms.
Gaussian process regression based inspection robot for predicting and locating pipeline anticorrosion coating defects
Authors: Tian Shunxin , Wu Zhenning , Zhang Dexin
Published: March 2024

The direct current voltage gradient (DCVG) technology is adept at identifying defects and corrosion issues within the anti-corrosion layer of buried pipelines by measuring changes in voltage gradient above the ground. Its widespread adoption in the field of anti-corrosion layer defect detection for its high precision and accuracy. However, the current DCVG inspection process relies on experienced operators holding electrodes to walk along the pipeline, resulting in a huge workload. To address these challenges, this paper proposes an innovative method that combines Gaussian process regression (GPR) with an intelligent inspection robot for autonomous pipeline anti-corrosion coating defect detection. This method uses environmental data to directly predict the location of defects within a pipeline’s anti-corrosion coating. Through incremental learning, the GPR model is trained to be continuously updated based on new samples such as position coordinates and voltage measurements during autonomous inspections. In addition, the intelligent inspection robot operates collaboratively with crawler wheels and UR robotic arms, enhancing motion stability and flexibility in expanding training data sets. Experimental results confirm that the intelligent inspection robot driven by Gaussian process prediction can achieve accurate defect positioning within 25 iteration cycles, with a positioning accuracy within 0.12 m. This method enhances defect detection accuracy, alleviating operator burden and offering an efficient solution for buried pipeline maintenance.
Stability theory for two-lobe states on the tadpole graph for the NLS equation
Authors: Pava Jaime Angulo
Published: March 2024

The aim of this work is to present new spectral tools for studying the orbital stability of standing waves solutions for the nonlinear Schrödinger equation (NLS) with power nonlinearity on a tadpole graph, namely, a graph consisting of a circle with a half-line attached at a single vertex. By considering δ-type boundary conditions at the junction and bound states with a positive two-lobe profile, the main novelty of this paper is at least twofold. Via a splitting eigenvalue method developed by the author, we identify the Morse index and the nullity index of a specific linearized operator around of an a priori positive two-lobe state profile for every positive power; and we also obtain new results about the existence and the orbital stability of positive two-lobe states at least in the cubic NLS case. To our knowledge, the results contained in this paper are the first in studying positive bound states for the NLS on a tadpole graph by non-variational techniques. In particular, our approach has prospect of being extended to study stability properties of other bound states for the NLS on a tadpole graph or on other non-compact metric graph such as a looping edge graph, as well as, for other nonlinear evolution models on a tadpole graph.
Development of a novel fibre optic beam profile and dose monitor for very high energy electron radiotherapy at ultrahigh dose rates
Authors: Bateman Joseph J , Buchanan Emma , Corsini Roberto , Farabolini Wilfrid , Korysko Pierre , Garbrecht Larsen Robert , Malyzhenkov Alexander , Ortega Ruiz Iñaki , Rieker Vilde , Gerbershagen Alexander , Dosanjh Manjit
Published: March 2024

Objective. Very high energy electrons (VHEE) in the range of 50–250 MeV are of interest for treating deep-seated tumours with FLASH radiotherapy (RT). This approach offers favourable dose distributions and the ability to deliver ultra-high dose rates (UHDR) efficiently. To make VHEE-based FLASH treatment clinically viable, a novel beam monitoring technology is explored as an alternative to transmission ionisation monitor chambers, which have non-linear responses at UHDR. This study introduces the fibre optic flash monitor (FOFM), which consists of an array of silica optical fibre-based Cherenkov sensors with a photodetector for signal readout. Approach. Experiments were conducted at the CLEAR facility at CERN using 200 MeV and 160 MeV electrons to assess the FOFM’s response linearity to UHDR (characterised with radiochromic films) required for FLASH radiotherapy. Beam profile measurements made on the FOFM were compared to those using radiochromic film and scintillating yttrium aluminium garnet (YAG) screens. Main results. A range of photodetectors were evaluated, with a complementary-metal-oxide-semiconductor (CMOS) camera being the most suitable choice for this monitor. The FOFM demonstrated excellent response linearity from 0.9 Gy/pulse to 57.4 Gy/pulse (R
2 = 0.999). Furthermore, it did not exhibit any significant dependence on the energy between 160 MeV and 200 MeV nor the instantaneous dose rate. Gaussian fits applied to vertical beam profile measurements indicated that the FOFM could accurately provide pulse-by-pulse beam size measurements, agreeing within the error range of radiochromic film and YAG screen measurements, respectively. Significance. The FOFM proves to be a promising solution for real-time beam profile and dose monitoring for UHDR VHEE beams, with a linear response in the UHDR regime. Additionally it can perform pulse-by-pulse beam size measurements, a feature currently lacking in transmission ionisation monitor chambers, which may become crucial for implementing FLASH radiotherapy and its associated quality assurance requirements.
Verification of neuronavigated TMS accuracy using structured-light 3D scans
Authors: Matilainen Noora , Kataja Juhani , Laakso Ilkka
Published: March 2024

Objective. To investigate the reliability and accuracy of the manual three-point co-registration in neuronavigated transcranial magnetic stimulation (TMS). The effect of the error in landmark pointing on the coil placement and on the induced electric and magnetic fields was examined. Approach. The position of the TMS coil on the head was recorded by the neuronavigation system and by 3D scanning for ten healthy participants. The differences in the coil locations and orientations and the theoretical error values for electric and magnetic fields between the neuronavigated and 3D scanned coil positions were calculated. In addition, the sensitivity of the coil location on landmark accuracy was calculated. Main results. The measured distances between the neuronavigated and 3D scanned coil locations were on average 10.2 mm, ranging from 3.1 to 18.7 mm. The error in angles were on average from two to three degrees. The coil misplacement caused on average a 29% relative error in the electric field with a range from 9% to 51%. In the magnetic field, the same error was on average 33%, ranging from 10% to 58%. The misplacement of landmark points could cause a 1.8-fold error for the coil location. Significance. TMS neuronavigation with three landmark points can cause a significant error in the coil position, hampering research using highly accurate electric field calculations. Including 3D scanning to the process provides an efficient method to achieve a more accurate coil position.
Simultaneously unveiling the EBL and intrinsic spectral parameters of gamma-ray sources with Hamiltonian Monte Carlo
Authors: Genaro M. , Stuani Pereira L.A. , de Matos Pimentel D.R. , Moura Santos E.
Published: March 2024

The Extragalactic Background Light (EBL) is the main radiation field responsible for
attenuating extragalactic gamma-ray emission at very high energies, but its precise spectral
intensity is not fully determined. Therefore, disentangling propagation effects from the intrinsic
spectral properties of gamma-ray sources (such as active galactic nuclei, AGN) is the primary
challenge to interpret observations of these objects. We present a Bayesian and Markov Chain Monte
Carlo approach to simultaneously infer parameters characterizing the EBL and the intrinsic spectra
in a combined fit of a set of sources, which has the advantage of easily incorporating the
uncertainties of both sets of parameters into one another through marginalization of the posterior
distribution. Taking a sample of synthetic blazars observed by the ideal CTA configuration, we
study the effects on the EBL constraints of combining multiple observations and varying their
exposure. We also apply the methodology to a set of 65 gamma-ray spectra of 36 different AGNs
measured by current Imaging Atmospheric Cherenkov Telescopes, using Hamiltonian Monte Carlo as a
solution to the difficult task of sampling in spaces with a high number of parameters. We find
robust constraints in the mid-IR region while simultaneously obtaining intrinsic spectral
parameters for all of these objects. In particular, we identify Markarian 501 (Mkn 501) flare data
(HEGRA/1997) as essential for constraining the EBL above 30 μm.
A Robust and Simple Method for Filling in Masked Data in Astronomical Images
Authors: van Dokkum Pieter , Pasha Imad
Published: March 2024

Astronomical images often have regions with missing or unwanted information, such as bad pixels, bad columns, cosmic rays, masked objects, or residuals from imperfect model subtractions. In certain situations it can be essential, or preferable, to fill in these regions. Most existing methods use low order interpolations for this task. In this paper a method is described that uses the full information that is contained in the pixels just outside masked regions. These edge pixels are extrapolated inwards, using iterative median filtering. This leads to a smoothly varying spatial resolution within the filled-in regions, and ensures seamless transitions between masked pixels and good pixels. Gaps in continuous, narrow features can be reconstructed with high fidelity, even if they are large. The method is implemented in maskfill, an open-source MIT licensed Python package (https://github.com/dokkum/maskfill). Its performance is illustrated with several examples, and compared to several alternative interpolation schemes.
Finite element models for radiation effects in nuclear fusion applications
Authors: Reali Luca , Dudarev Sergei L.
Published: March 2024

Deuterium-tritium fusion reactions produce energy in the form of 14.1 MeV neutrons, and hence fusion reactor components will be exposed to high energy neutron irradiation while also being subjected to thermal, mechanical and magnetic loads. Exposure to neutron irradiation has numerous consequences, including swelling and dimensional changes, comparable in magnitude to the peak transient thermal deformations occurring in plasma-facing components. Irradiation also dynamically alters the various thermo-mechanical properties, relating temperature, stress and swelling in a strongly non-linear way. Experimental data on the effect of neutron exposure spanning the design parameter space are very sparse and this highlights the relevance of computer simulations. In this study we explore the equivalence between the body force/surface traction approach and the eigenstrain formalism for treating anisotropic irradiation-induced swelling. We find that both commercial and massively parallelised open source software for finite element method (FEM) simulations are suitable for assessing the effect of neutron exposure on the mechanically loaded reactor components. We demonstrate how two primary effects of irradiation, radiation swelling and the degradation of thermal conductivity, affect the distributions of stress and temperature in the divertor of the ITER tokamak. Significant uncertainties characterising the magnitude of swelling and models for treating it suggest that on the basis of the presently available data, only an order of magnitude estimate can be given to the stress developing in reactor components most exposed to irradiation during service.
Research Progress of MXene Composites In Electromagetic Wave Absorption
Authors: Cao Lanlan , Zhang Yong , Qiu Zhenxing , Wang Xuan
Published: March 2024

The issue of electromagnetic wave pollution is increasingly severe due to the rapid advancement of communication technology. Advanced electromagnetic wave absorbing materials have become an important research field. The excellent microwave absorption capabilities of the MXene composite can be attributed to its unique two-dimensional structure, abundant adjustable surfaces with functional groups, significant specific surface area, and high electrical conductivity. In this paper, the electromagnetic properties, electromagnetic wave absorption advantages and electromagnetic wave absorption principles of MXene compared with other materials are reviewed, and the wave absorption properties of MXene/graphene, MXene/carbon nanotubes, MXene/polymer, MXene/metal particles and MXene/oxide composites are summarized and analyzed. It is being investigated what the future holds for MXene and its mixed absorbent materials.
Preparation and Application of Self-adaptive Porous Polyethylene for Mulch Film
Authors: Han Haojie , Ghosh Pintu , Li Qiang
Published: March 2024

Porous polyethylene has emerged as a consequential constituent within the realm of infrared thermal management, owing to its commendable transmittance in the thermal infrared domain and noteworthy high scattering capabilities within the visible spectrum. In this study, we have fabricated porous polyethylene and conducted a comprehensive investigation into its adaptable emissivity alterations within the infrared range, while concurrently upholding a pronounced scattering proficiency in the visible band. Furthermore, we have proffered the prospective application of the prepared adaptive porous polyethylene in the context of mulch film. Empirical has unequivocally demonstrated that the utilization of adaptive porous polyethylene can effectively engender adaptive cooling and insulation modulation in the realm of subterranean plant growth, by harnessing its efficient performance across both the visible and thermal infrared spectra. Simultaneously, the material continually scatters visible light, thereby providing supplemental illumination to plant leaves and fruits in a retrograde manner. This breakthrough affords an efficacious and cost-effective energy-conserving apparatus in the domain of agricultural production.
Application of Neural Network Prediction in the Optimization of Forming Process of Magnetic Ceramic/Rare Earth Alloy Composite Magnets
Authors: Zhao Haofeng , Xia Jun , Wang Ru , He Yiheng
Published: March 2024

In order to ensure that magnet materials have higher mechanical properties and magnetic properties at the same time, magnetic ceramics and rare earth alloys are combined to form composite magnets by bonding and pressing. The nonlinear relationship from input (pressing pressure and holding time) to output (coercivity, density and compressive strength) was established by neural network platform, and the optimization of pressing process was studied. The results show that the density, compressive strength and coercivity of the material increase with increasing pressure. When the pressing pressure exceeds a certain value, the density and compressive strength of the material increase slowly, but the coercivity of the material will decrease. The reason for the decrease of coercivity is related to the crushing of the fast quenched rare earth alloy powders in the form of scales due to excessive pressure and long holding time. The experimental results show that the optimum process parameters with high compressive strength and high coercivity can be found by the prediction of neural network.
Research on the Water Injection Pressure Reducing and Increasing Injection System for Low Permeability Reservoirs in Fushan Oilfield
Authors: Deng Xiaoguo , Dou Tongwei , Fu Jie , Li Heng , He Pixiang , Zhao Junfeng , Cao Xiaomei , Dong Jun , Han Xiangyong , Fan Songlin , Ren Lihua
Published: March 2024

In response to the problems of increased injection pressure, decreased injection volume, and stopped injection caused by scaling and impurity blockage during the water injection process in the low permeability reservoir of HuaX block in Fushan Oilfield, water quality analysis and scaling experiments were conducted on the injected water in the block to determine the cause of scaling. Secondly, core displacement damage experiments were conducted using natural rock cores and on-site injected water to determine the degree of permeability damage during the water injection process, with a permeability damage rate greater than 70%, Finally, based on the causes of scaling and core displacement experiments, scale inhibitors, anti expansion agents, and surfactants were selected. Through orthogonal experiments, the optimal system formula was determined. The scale inhibition rate was greater than 90%, the anti expansion agent was greater than 90%, and the interfacial tension was less than 0.01mN/m. Core displacement experiments showed that the permeability damage rate of the system to the core was less than 15%, which can achieve the effect of reducing pressure and increasing injection in water injection wells.
Research on Classification Method of Highway Concrete Water Reducing Agent Manufacturers Based on K-means++ Clustering
Authors: Ye Haolong , Fang Shaohong , Zhang Qun
Published: March 2024

Concrete water reducing agent is an important admixture in the preparation of concrete. Machine learning has a wide range of applications in the field of material science. In this paper, machine learning is creatively applied to the classification of water reducing agent manufacturers. This is because the act of categorizing water reducing agent supply manufacturers in practical engineering relies heavily on the experience of experts, which makes it more difficult to find similar alternative manufacturers when the water reducing agent is out of stock. In order to solve this kind of problem, this paper first performs data cleaning on the original data, a total of 72-dimensional eigenvalues are selected, and missing value processing and standardization are performed to normalize the dataset. Afterwards, the K-means++ algorithm is used to analyze the clustering of manufacturers, and the optimal K value is selected by introducing three evaluation indexes, such as Silhouette Coefficient, and the optimal clustering effect is obtained when K is 3. At this time, when the manufacturers of a certain class are out of stock, similar manufacturers can be found for the replacement of the goods.
Low Frequency Noise Behavior in Resistive Memory Devices with Hf/HfO2 Stack
Authors: Li Kexin
Published: March 2024

Resistive-random-access-memory (RRAM) devices are considered to be one of the most potential candidates of next generation emerging memory technologies due to their excellent device properties, such as high density, low power, low voltage, and high speed. RRAM features simple metal–insulator–metal (MIM) structures and is fully compatible with traditional CMOS fabrication processes. Low-frequency noise (LFN) measurement is a technique to characterize electrically the trap-assisted conduction processes in dielectrics. In this work, we report the LFN characteristics of Hf/HfO2-based bipolar RRAM and investigate the current conduction mechanism and internal physics.
Optimization of Prestressed Anchor Cable Layout for Left Pier of Jinchuan Hydropower Station
Authors: Si Jianhui , Zhou Yuan , Ding Xinchao
Published: March 2024

With the increase of the flood discharge capacity of the flood discharge structure, the size of the flood discharge orifice is widened, which leads to the increasing thrust of the radial gate. A large tensile stress zone will be formed at the connection between the anchor block and the pier, which may lead to concrete cracking. The optimization design of the prestressed anchor cable of the pier has always been a concern of the engineering community. In this paper, the left pier of Jinchuan Hydropower Station is taken as the research object, and the finite element simulation model is established. The layout position of prestressed anchor cable is optimized, and different layout schemes of prestressed anchor cable on the left pier are designed and calculated. The results show that when the amount of main anchor cable is the same, it should be arranged outside the pier as far as possible; under the condition that the number of main anchor cables on the inner side of the pier is constant, when the direction of the main anchor cable force is consistent with the direction of the radial gate thrust, the main anchor cable prestress plays the greatest role; the arrangement of balance cable has no obvious effect on the tension of concrete at pier neck. It can provide reference for structural design.
Performance Analysis of a Vibration Absorber with the Inerter Element and Amplifying Mechanism
Authors: Gao Ting , Li Jing , Zhu Shaotao , Wang Boyang
Published: March 2024

Based on the good performance of the new control elements, we introduce the viscoelastic model, the amplification mechanism and the inerter element into the dynamic vibration absorber (DVA). Then, we take it as the research object to obtain the DVA parameters when the system achieves the optimal vibration reduction effect based on the fixed-point theory. Finally, it is eventually demonstrated that the DVA discussed in this paper possesses significant benefits in mitigating vibrations, which provides theoretical basis and data support for the parameters design of DVAs in engineering application.
Synthesis and Preliminary Biological Activity of Selenium Polysaccharides from Tussilago farfara L.
Authors: Liu Simei , Ye Shili , Zhao Peng , Zhang Lihua
Published: March 2024

Tussilago farfara L. selenium polysaccharides (STFPs, similarly hereinafter) were prepared by Selenous acid salt method from Tussilago farfara L. polysaccharide (TFP, similarly hereinafter). Taking the selenium content of STFPs as an indicator, the synthesis process of STFPs was optimized using response surface methodology based on single factor experiments. The optimal synthesis process conditions obtained are: 90 °C, 12 hours, selenide reagent ratio of 1.2: 1, HNO3 volume fraction of 0.7%, and the average selenium content of STFPs measured under these conditions is 2.338 mg/g. Characterization was carried out by measuring the selenium content, molecular weight, infrared spectroscopy. The results of antioxidant experiments showed that the maximum clearance rate of DPPH· by the selenium polysaccharide from Tussilago farfara L. was 73.16%, which were higher than from Tussilago farfara L. polysaccharides.
Accurate Determination of Trace Sulfur in Superalloys and Its Application
Authors: Wei Jianhuan , Wu Yujie , Gao Jinfeng , Ye Jingjing
Published: March 2024

The accurate determination technology of trace sulfur in superalloys adopts the latest infrared carbon/sulfur analyzer CS844ES, and carries out technological innovation in five aspects: the three calibrations technology at both ends, the ultrapure composite flux, the reference material traceability technology, the blank influence value determination technology, and the criteria for the accurate determination of trace sulfur. The lower limit of sulfur measurement is extended to 0.5ppm. After appraisal, it has reached the international advanced level. Two reference materials of wrought superalloy GH4169 with trace Sulfur concentration were developed by this technology. Finally, the accurate determination technology of trace Sulfur in superalloys, independent intellectual property rights and trace sulfur reference materials constitute a “Trinity” technical system. This technical system was used to measure GH4169 superalloy in the United States and China at the same time, and the results showed that there are differences in sulfur content among them. This technology is mainly applied independently and has been applied in relevant units and won many technical awards.
Multi-objective Optimization Design of Low-carbon Modular Building
Authors: Li Jing , Zhang Sumei , Qi He
Published: March 2024

In recently architectural research, there is a well-documented emphasis on energy-saving design optimization. However, there is a conspicuous deficiency in studies that address multi-objective optimization related to the long-term carbon emissions associated with building lifecycles. In this study, modular buildings in construction sites are taken as the research object, and box-type rooms are taken as the prototypical model. A set of multi-objective optimization methods for architectural design is established by series modeling tools, building performance simulation tools and NSGA-II non-dominated sorting genetic algorithm tools, combined with Python programming tools. This method is to optimize the reduction of carbon emissions, energy consumption and costs throughout the life cycle. The purpose of this investigation is to establish a methodology for assessing and optimizing architectural designs with a primary focus on carbon emissions during the design phase. The goal is to provide architects with practical insights to enhance their designs while simultaneously achieving intelligent, eco-friendly buildings.
Research on a New Flow Measurement for Intelligent Injection Tools
Authors: Wang Min , Deng Gang , Liu Junli , Yue Qingfeng , Sun Yufei
Published: March 2024

Intelligent separate injection technology can achieve continuous monitoring data of layered water Injection wells. So it can find out the inefficient water circulating formation timely. Then the water injection schemes can be adjusted in real-time to ensure the high water injection pass rate. It can also increase the working efficiency of the workers’ because of its automatic mode.

But its prime cost is high, which limits its large-scale industrialization application in fine layered water injection wells. The key part is the intelligent water distributor in the intelligent separate injection technology. The cost of electromagnetic flow meter accounts for 38% in the intelligent water distributor. The paper intends to research on flow measurement without flow meter to reduce the high-cost. The pressure difference equation was established for flow rate and the opening ratio of the nozzle using the dimensionless analysis method. The empirical parameters of the equation were obtained through laboratory experiments. The pressure sensors are used to monitor the pressure of water injection wells while achieving the measurement of layered flow rate.

The laboratory experiments results indicate that the calculated flow rate obtained by this method coincides well with the standard flow rate. The relative error is less than 12%. Then,it provides a new flow measurement method for intelligent injection tools. The most significant feature is that the flow meter is no longer mandatory for intelligent water distributors. Due to the cheaper cost that it provides a technical support for the large-scale industrialization application of intelligent separate injection technology in fine layered water injection wells.