bluuebunny/crossref_metadata_2025 huggingface dataset:
Phonon engineering in thermal materials with nano-carbon dopants
Authors: Stamper Caleb , Cortie David , Nazrul-Islam Sheik Md Kazi , Rahman Md Rezoanur , Yu Dehong , Yang Guangsai , Al-Mamun Abdullah , Wang Xiaolin , Yue Zengji
Published: June 2024

The unique geometric and thermal properties of carbon nanoparticles (NPs)—including nanotubes, graphene, and nanodiamonds—have led to their use as additives in many composite material systems. In this review, we investigate the mechanisms behind the altered thermal conductivity (κ) of thermoelectric (TE) and other thermal materials that have been composited with carbon NPs. We provide a comprehensive overview and analysis of the relevant theoretical and applied literature, including a detailed review of the available thermal conductivity data across five common classes of TE materials (Bi2Te3 variants, skutterudites, metal–oxide, SnSe, Cu2Se) in combination with carbon additives, including graphene, nanotubes, carbon black, carbon fiber, and C60. We argue that the effectiveness of carbon NPs in reducing κ in TE composites generally arises due to a combination of the presence of the carbon NP interfaces and significant changes in the microstructure of the host material due to compositing, such as suppressed grain growth and the introduction of pores, dislocations, and strain. Carbon NPs themselves are effective phonon scatterers in TE composites due to a significant mismatch between their high-frequency phonon distribution and the lower-frequency phonon distribution of the host material. While carbon NP doping has proven itself as an effective way to increase the performance of TE materials, there is still a significant amount of work to do to precisely understand the fundamental thermal transport mechanisms at play. Rigorous material characterization of nanocomposites and spectroscopic studies of the precise lattice dynamics will greatly aid the development of a fully quantitative, self-consistent model for the thermal conductivity of carbon nanocomposites.
Striations in a radio frequency hydrogen discharge tube: Optical emission plasma diagnostics and Raman analysis of in situ graphite probes
Authors: Lee Szetsen , Peng Jr-Wei
Published: June 2024

Standing striations with a unique pattern have been observed in a radio-frequency-generated hydrogen plasma. The striation pattern consists of a sequence of closely spaced bright ring doublets and two types of dark gaps of different widths. The bright and dark regions in striations were spectroscopically resolved with the Balmer series and the Fulcher band emission lines of hydrogen. Temperatures in these fine structures were determined. In general, the wider dark gap has a higher excitation temperature than the nearby narrower ones in the striation pattern sequence. Bright regions are rotationally hotter than the adjacent dark ones. However, for vibrational temperatures, the trends are not so obvious. No clear pressure dependence of temperatures was observed in striations within the pressure range of maintaining stable standing striations in this work. In addition to optical emission spectroscopy, we used graphite granules as in situ probes for plasma conditions in different striation regions. The striated hydrogen plasma-treated graphite granules were analyzed with Raman spectroscopy. The observed hydrogen-graphite interaction was correlated with the measured temperatures and the fine structures of striations in a discharge tube.
Energy exchange between electrons and ions in ion temperature gradient turbulence
Authors: Kato T. , Sugama H. , Watanabe T.-H. , Nunami M.
Published: June 2024

Microturbulence in magnetic confined plasmas contributes to energy exchange between particles of different species as well as the particle and heat fluxes. Although the effect of turbulent energy exchange has not been considered significant in previous studies, it is anticipated to have a greater impact than collisional energy exchange in low collisional plasmas such as those in future fusion reactors. In this study, gyrokinetic simulations are performed to evaluate the energy exchange due to ion temperature gradient (ITG) turbulence in a tokamak configuration. The energy exchange due to the ITG turbulence mainly consists of the cooling of ions in the ∇B-curvature drift motion and the heating of electrons streaming along a field line. It is found that the ITG turbulence transfers energy from ions to electrons regardless of whether the ions or electrons are hotter, which is in marked contrast to the energy transfer by Coulomb collisions. This implies that the ITG turbulence should be suppressed from the viewpoint of sustaining the high ion temperature required for fusion reactions since it prevents energy transfer from alpha-heated electrons to ions as well as enhancing ion heat transport toward the outside of the reactor. Furthermore, linear and nonlinear simulation analyses confirm the feasibility of quasilinear modeling for predicting the turbulent energy exchange in addition to the particle and heat fluxes.
Achieving reading–writing electromagnetic signal memory based on high-order topological state
Authors: Gong Ping , Fang Yun-Tuan
Published: June 2024

In order to achieve an optical signal memory device with read–write functions, a topological Su–Schrieffer–Heeger lattice is proposed. It is found that a transformation between a topological corner state and an edge state occurs under the magneto-optical effect. Without an external magnetic field, the electromagnetic (EM) signal is confined and stored at the corner, which realizes the writing process of a signal. When an external magnetic field is applied, the EM signal is released from the corner to the edge, which realizes the reading process of the signal. The result is expected to provide guidance for the design of high-performance reading–writing EM memories.
A high-level ab initio study of the photodissociation of acetaldehyde
Authors: Jaddi A. , Marakchi K. , Zanchet A. , García-Vela A.
Published: June 2024

Acetaldehyde is a very relevant atmospheric species whose photodissociation has been extensively studied in the first absorption band both experimentally and theoretically. Very few works have been reported on acetaldehyde photodissociation at higher excitation energies. In this work, the photodissociation dynamics of acetaldehyde is investigated by means of high-level multireference configuration interaction ab initio calculations. Five different fragmentation pathways of acetaldehyde are explored by calculating the potential-energy curves of the ground and several excited electronic states along the corresponding dissociating bond distances. The excitation energy range covered in the study is up to 10 eV, nearly the ionization energy of acetaldehyde. We intend to rationalize the available experimental results and, in particular, to elucidate why some of the studied fragmentation pathways are experimentally observed in the different excitation energy regions and some others are not. Based on the shape of the calculated potential curves, we are able to explain the main findings of the available experiments, also suggesting possible dynamical dissociation mechanisms in the different energy regions. Thus, the reported potential curves are envisioned as a useful tool to interpret the currently available experiments as well as future ones on acetaldehyde photodissociation at excitation wavelengths in the range studied here.
Thermodynamic properties of quasi-one-dimensional fluids
Authors: Franosch Thomas , Schilling Rolf
Published: June 2024

We calculate thermodynamic and structural quantities of a fluid of hard spheres of diameter σ in a quasi-one-dimensional pore with accessible pore width W smaller than σ by applying a perturbative method worked out earlier for a confined fluid in a slit pore [Franosch et al. Phys. Rev. Lett. 109, 240601 (2012)]. In a first step, we prove that the thermodynamic and a certain class of structural quantities of the hard-sphere fluid in the pore can be obtained from a purely one-dimensional fluid of rods of length σ with a central hard core of size σW=σ2−W2 and a soft part at both ends of length (σ − σW)/2. These rods interact via effective k-body potentials veff(k) (k ≥ 2). The two- and the three-body potential will be calculated explicitly. In a second step, the free energy of this effective one-dimensional fluid is calculated up to leading order in (W/σ)2. Explicit results for, e.g., the perpendicular pressure, surface tension, and the density profile as a function of density, temperature, and pore width are presented and partly compared with results from Monte-Carlo simulations and standard virial expansions. Despite the perturbative character of our approach, it encompasses the singularity of the thermodynamic quantities at the jamming transition point.
The capability of a deep learning based ODE solution for low temperature plasma chemistry
Authors: Yin Bo , Zhu Yifei , Chen Xiancong , Wu Yun
Published: June 2024

A deep learning-based solution is proposed to resolve the highly non-linear ordinary differential equation (ODE) system of the plasma chemistry model. A feed-forward neural network (FNN) is built and trained based on the data generated by the existing global plasma kinetics code. Good agreement is achieved between the results obtained from the deep learning-based method and the traditional plasma kinetics solver for both argon and air discharge conditions. The results demonstrate that the temporal evolution of O-atom density predicted by both the FNN and the 0D model aligns closely with the measurements obtained from the fast ionization wave discharge. Furthermore, the differences in O-atom density between the predictions and measurements are the same order of magnitude. The computational costs of the ODE solver and the FNN model are compared and discussed in this work. The feasibility of using deep learning methods to resolve low temperature plasma chemistry systems is demonstrated through the tests shown in this study.
Two-dimensional space charge limited current in regime between accelerating diode and drift space for sheet and circular beam
Authors: Liu Yao-Li , Ang L. K.
Published: June 2024

We develop a general electrostatic steady-state model to calculate the two-dimensional (2D) space-charge-limited current (SCLC) with an initial velocity v0 (i.e., kinetic energy eKV=mv02/2) injected from a cathode into a vacuum diode with a spacing D and a potential difference of Vg. We consider two types of beam cross section: (a) a sheet beam with a width W and (b) a circular beam with a radius R, where both W and R are larger than D in the calculation. By introducing a parameter ε≡KV/Vg≥0, we can tune the operating regime to be in between the accelerating diode (ε≪1) and drift space (ε≫1). Hence, we verify the 2D SCLC model by converging to some prior analytical findings such as the 2D Child–Langmuir law at ε = 0, 2D SCLC at drift space at ε≫1, and their 1D limits at W/D≫1 or R/D≫1. Our 2D SCLC model indicates that there is a maximal value at ε∼1/60, which is independent of W/D or R/D. Furthermore, the hysteresis behavior is also studied when the injected current density is beyond the SCLC threshold and its dynamics are mainly influenced by ε instead of geometrical effect. This model is useful in high current electron beam emission with a finite emission area and with a non-negligible arbitrary injection kinetic energy.
Hybrid-attention-based Swin-Transformer super-resolution reconstruction for tomographic particle image velocimetry
Authors: Li Xin , Yang Zhen , Yang Hua
Published: June 2024

Research on three-dimensional (3D) flow velocity fields holds significant importance in aerodynamic performance design, energy power, and biomedicine. Nevertheless, current techniques for measuring three-dimensional flow velocity fields, such as tomographic particle image velocimetry (Tomo-PIV), have challenges in achieving accurate and high-resolution measurements of tiny structures in flow fields. Consequently, a 3D flow field super-resolution (SR) reconstruction method based on Swin-Transformer framework (SWINFlow-3D) has been proposed in this paper. SWINFlow-3D comprises stacked residual channel attention Swin-transformer blocks, each containing multiple Swin-Transformer standard layers, incorporating a hybrid attention mechanism that allows for integrating relevant information from several channels and gives greater importance to critical information. Second, a loss function for SR reconstruction of the flow field has been introduced, taking into account the physical constraints such as divergence and curl. Furthermore, the characteristics obtained by interpolation downsampling methods are different from those of real experiments. To address this limitation, we construct a dataset based on cross correlation downsampling. Simulation experiments are carried out on Johns Hopkins Turbulence Database isotropic turbulence data and cylindrical wake data. The results are subsequently compared with those of the interpolation approach and 3D flow field SR reconstruction method, and our model yields the best results for all the metrics. Ultimately, to ascertain the accuracy and practical applicability of the model in practical tests, we conduct experiments on jet data and cylindrical wake recorded by Tomo-PIV. The experimental results demonstrate that SWINFlow-3D with the loss function presented in this study can be used to effectively reconstruct the 3D flow field and flow features, exhibiting strong generalizability.
Numerical investigation on characteristics of the muzzle flow field at different ambient temperatures
Authors: Tu Xin-xin , Du Ping , Nan Feng-qiang , Han Pei-chen , Chen Fei-yun
Published: June 2024

To adapt to the complex and changing environment, the artillery often needs to be launched at different ambient temperatures, and different temperatures can have complex effects on the muzzle flow characteristics. It is crucial to fully understand the effect of ambient temperature on the muzzle flow field characteristics, which will help optimize the design of the propellant charge and improve the stability and consistency of the ballistic trajectory. Therefore, the internal and intermediate ballistic trajectories of the artillery are simulated to investigate the effect of ambient temperature on muzzle flow development and the phenomenon of secondary combustion. A set of internal ballistic equations is used to provide precise velocity and pressure as the projectile moves to the muzzle. By coupling the van der Waals gas state equation and a detailed chemical reaction kinetic model, the multispecies Navier–Stokes equations with complex chemical reactions were solved. The established numerical model is validated by comparing it with experimental results. The results demonstrate that the shock wave propagation speed gradually increases and the shock wave intensity gradually decreases with the increase in ambient temperature. The initial formation time of Mach disk lags, and the diameter of the Mach disk decreases with increasing temperature, while the displacement of the Mach disk increases with increasing temperature. The structure of muzzle flash is synchronized with the Mach disk structure; the lower the temperature, the “shorter and fatter” the flash is.
Vibrational energy relaxation in shock-heated CO/N2/Ar mixtures
Authors: He Dong , Hong Qizhen , Pirani Fernando , Li Renjie , Li Fei , Sun Quanhua , Si Ting , Luo Xisheng
Published: June 2024

Experimental and numerical studies were performed on the vibrational energy relaxation in shock-heated CO/N2/Ar mixtures. A laser absorption technique was applied to the time-dependent rovibrational temperature time-history measurements. The vibrational relaxation data of reflected-shock-heated CO were summarized at 1720–3230 K. In shock-tube experiments, the rotational temperature of CO quickly reached equilibrium, whereas a relaxation process was found in the time-dependent vibrational temperature. For the mixture with 1.0% CO and 10.0% N2, the vibrational excitation caused a decrease in the macroscopic thermodynamic temperature of the test gas. In the simulations, the state-to-state (StS) approach was employed, where the vibrational energy levels of CO and N2 are treated as pseudo-species. The vibrational state-specific inelastic rate coefficients of N2–Ar collisions were calculated using the mixed quantum–classical method based on a newly developed three-dimensional potential energy surface. The StS predictions agreed well with the measurements, whereas deviations were found between the Schwartz–Slawsky–Herzfeld formula predictions and the measurements. The Millikan–White vibrational relaxation data of the N2–Ar system were found to have the most significant impact on the model predictions via sensitivity analysis. The vibrational relaxation data of the N2–Ar system were then modified according to the experimental data and StS results, providing an indirect way to optimize the vibrational relaxation data of a specific system. Moreover, the vibrational distribution functions of CO and N2 and the effects of the vibration–vibration–translation energy transfer path on the thermal nonequilibrium behaviors were highlighted.
Slip effects on electroosmotic flow in a microchannel with squeezing wall motion
Authors: Aboelkassem Yasser
Published: June 2024

This study investigates the effects of slip boundary conditions on the electroosmotic flow of an electrolyte solution in a microchannel with a squeezing upper wall and a charged lower wall. The mathematical model is derived by utilizing a tight coupling between the nonlinear Poisson–Boltzmann equation and the flow Navier–Stokes equations. An analytical solution to the problem is acquired through the application of lubrication theory, enabling the resolution of the Poisson–Boltzmann equation without resorting to any approximation techniques. The study thoroughly investigates the impact of various electrokinetic parameters, including the Helmholtz–Smoluchowski velocity, wall zeta potential, Debye length, and electric field, on fluid shear stress, pressure distributions, velocity field, and net flow rate. The results demonstrate that the time-averaged net flow rate is significantly influenced by the collective impact of wall slip velocity, Helmholtz–Smoluchowski velocity, zeta potential, and electric double layer. The data clearly show that altering the Helmholtz–Smoluchowski velocity direction can also impact the direction of the net flow rate, regardless of the slip effects. These results further confirm that applying slip boundary conditions to both walls can improve pumping efficiency.
Numerical simulation study on the effect of porosity on the flapping characteristics of perforated flags in different flow environments
Authors: Zhao Zhuoqun , Hu Jun , Yu Yong
Published: June 2024

The flapping characteristics of perforated flags with various porosities in different flow environments are studied using XFlow-Abaqus co-simulation. It is proved that flapping characteristics significantly correlate with flag porosity in different flow environments. Specifically, as the flag porosity increases, the flapping speed and vortex strength decrease monotonically. Further study of the influence of perforated flags on the flow structures surrounding a square cylinder revealed that different flag porosities lead to different levels of flow control. As the flag porosity increases, the flag's modulation weakens, the average drag on the square cylinder rises, and the influence of the Kármán vortex street becomes more significant. The flag-induced vortices can generate a high-pressure zone on the rear side of the square cylinder's top surface, leading to a decrease in the average lift on the square cylinder. It is notable that flags with different porosities generate vortices at different flapping states, which results in phase differences between the lift on the square cylinder and the flag. Finally, the study discusses the peaks of the Reynolds stress in the x- and y-directions, which delineate the boundary of the recirculation zone and reflect force fluctuations on the flag and the square cylinder, respectively.
Dynamic evolution of oxygen vacancies during cycling in antiferroelectric HfxZr1−xO2
Authors: Qian Haoji , Shen Rongzong , Zhang Hongrui , Xu Jiacheng , Lin Gaobo , Ding Yian , Gu Jiani , Yu Xiao , Liu Yan , Jin Chengji , Chen Jiajia , Han Genquan
Published: June 2024

Antiferroelectric (AFE) ZrO2-based devices are anticipated to exhibit superior endurance properties in comparison to their ferroelectric (FE) counterparts. Nevertheless, the underlying mechanisms of AFE devices remain elusive. In this study, guided by the dynamic evolution of oxygen vacancies (Vo), we reveal three kinds of fatigue in AFE HfxZr1−xO2 (HZO) during uni-directional cycling. The first mechanism is related to the interfacial Vo charge trapping, which accelerates the switching from the P↓↑ state to the P↓↓ state, leading to extrinsic fatigue, and is demonstrated by electrical stress measurements. The other two mechanisms are Vo-related AFE to FE phase transition (PT) and Vo localization inside the HZO films, which are supported by the first-principles calculations. The highest polarization switching barrier occurs when Vo is localized at the tetra-coordinated oxygen sites inside HZO films. This means that tetra-coordinated Vo accumulation leads to less polarization switching, resulting in AFE to FE PT and Vo localization induced fatigue, i.e., intrinsic fatigue. This work reveals the dynamic evolution of Vo during cycling and its impact on AFE properties, paving the way for developing more durable AFE ZrO2-based devices and contributing to the emergence of diverse recovery methods in the future.
N6-methyladenosine modification of a parvovirus-encoded small noncoding RNA facilitates viral DNA replication through recruiting Y-family DNA polymerases
Authors: Ning Kang , Zhao Junxing , Feng Zehua , Park Soo Yeun , McFarlin Shane , Cheng Fang , Yan Ziying , Wang Jingxin , Qiu Jianming
Published: June 2024

Human bocavirus 1 (HBoV1) is a human parvovirus that causes lower respiratory tract infections in young children. It contains a single-stranded (ss) DNA genome of ~5.5 kb that encodes a small noncoding RNA of 140 nucleotides known as bocavirus-encoded small RNA (BocaSR), in addition to viral proteins. Here, we determined the secondary structure of BocaSR in vivo by using DMS-MaPseq. Our findings reveal that BocaSR undergoes N6-methyladenosine (m6A) modification at multiple sites, which is critical for viral DNA replication in both dividing HEK293 cells and nondividing cells of the human airway epithelium. Mechanistically, we found that m6A-modified BocaSR serves as a mediator for recruiting Y-family DNA repair DNA polymerase (Pol) η and Pol κ likely through a direct interaction between BocaSR and the viral DNA replication origin at the right terminus of the viral genome. Thus, this report represents direct involvement of a viral small noncoding RNA in viral DNA replication through m6A modification.
The development of speech and gesture in Sesotho narratives
Authors: Brookes Heather , Agyepong Dorothy , White Michelle , Yalala Sefela
Published: June 2024

Studies show that speech and gesture develop together with age, and the nature of gestures changes with increasing
cognitive and discursive abilities. While there are common developmental trends, cultural differences may also impact development.
We examined gesture development in narratives of Sesotho speaking children aged 5 to 6 years (n = 12), 9 to 10
years (n = 12) and adults (n = 12), who watched a wordless cartoon and narrated the story back
to an interlocutor. Our results show that narrative ability develops with age. Speech and gesture become more complex.
Representational and pragmatic gestures increase, but the proportion of these gesture types changes. Gestures become semiotically
more complex and integrated with spoken discourse. Narrative development in Sesotho speakers shows similar developmental trends to
those found in other studies. However, cultural factors influence some aspects with Sesotho speakers exhibiting similar narrative
patterns in spoken and gestural behaviour to speakers of isiZulu, a closely related language and cultural group.
Structural, magnetic, magnetocaloric behavior and magneto-transport, electrical polarization study in 3d based bulk and nano-crystalline multiferroic double perovskite Dy2MnCoO6
Authors: Chatterjee Soma , Das I
Published: June 2024

In this paper, we report a detailed investigation of the crystal structure, magnetic, magnetocaloric, magneto-transport and electrical polarization properties of a new multiferroic material in the polycrystalline and nanocrystalline form of the Dy2MnCoO6 double perovskite. Both compounds crystallized in the monoclinic structure with P21/n space group. The magnetic properties of both systems are mainly dominant ferromagnetic (FM) and weak antiferromagnetic (AFM). The FM/AFM coupling is related by the competing and combining functions of the radius and the magnetic moments of rare earth ions (i.e. 3d–4f exchange interactions). The reduction of the saturation magnetization in the isothermal magnetization curves can be explained by the existence of anti-phase boundaries and local anti-site defects in the system. Moreover, these materials hold reasonable values of magnetocaloric parameters and the absence of hysteresis makes the system a potential candidate for magnetic refrigeration. These compounds revealed two magnetic phase transitions, according to the appearance of two peaks in the temperature dependence of magnetic entropy change curves. The temperature dependent resistivity data for both the systems display semiconductor nature near room temperature and insulating like behavior at low temperature regime. The variable-range hopping conduction mechanism is used to best understand their transport mechanism. In addition, the electrical polarization loop at low temperature confirms the presence of ferroelectricity for both the studied systems. The decreases polarization under an external magnetic field evidence the weak magnetoelectric coupling. The coexistence of FM ordering with insulating behavior and ferroelectricity at low temperature promises new opportunities and improvements in next generation applications for information storage, spintronic, and sensors.
Periodic group-sparse method via generalized minimax-concave penalty for machinery fault diagnosis
Authors: He Wangpeng , Wen Zhihui , Liu Xuan , Guo Xiaoya , Zhu Juanjuan , Chen Weisheng
Published: June 2024

Diagnosing faults in large mechanical equipment poses challenges due to strong background noise interference, wherein extracting weak fault features with periodic group-sparse property is the most critical step for machinery intelligent maintenance. To address this problem, a periodic group-sparse method based on a generalized minimax-concave penalty function is proposed in this paper. This method uses periodic group sparse techniques to capture the periodic clustering trends of fault impact signals. To further enhance the sparsity of the results and preserve the high amplitude of the impact signals, non-convex optimization techniques are integrated. The overall convexity of the optimization problem is maintained through the introduction of a non-convex controllable parameter, and an appropriate optimization algorithm is derived. The effectiveness of this method has been demonstrated through experiments with simulated signals and mechanical fault signals.
A new dual-channel convolutional neural network and its application in rolling bearing fault diagnosis
Authors: Hu Baoquan , Liu Jun , Zhao Rongzhen , Xu Yue , Huo Tianlong
Published: June 2024

Recently, deep learning has received widespread attention in the field of bearing fault diagnosis due to its powerful feature learning capability. However, when the actual working conditions are complex and variable, the fault information in a single domain is limited, making it difficult to achieve high accuracy. To overcome these challenges, this paper proposes a bearing fault diagnosis method based on the Markov transition field, continuous wavelet transform (CWT), and dual-channel convolutional neural network (CNN). The method combines the descriptive ability of the Markov model for state transfer, the time-frequency analysis ability of CWT for signal, and the excellent performance of CNN with attention mechanism in feature extraction and classification. Specifically, we first propose a multi-channel Markov transition field method, which is combined with CWT to obtain two different representations of two-dimensional (2D) images. To comprehensively mine fault information, we further propose a dual-channel CNN with an attention mechanism. The design of this network structure aims to extract multi-level features from two types of 2D images. At the same time, we designed and embedded an attention mechanism to enable the network to focus more on extracting effective features, thereby improving the performance and accuracy of the network. To verify the effectiveness of the proposed method, three datasets were used for empirical research. The results show that this method exhibits superior performance in bearing fault diagnosis and has higher accuracy compared to traditional methods.
A machine learning framework for the prediction of grain boundary segregation in chemically complex environments
Authors: Aksoy Doruk , Luo Jian , Cao Penghui , Rupert Timothy J
Published: June 2024

The discovery of complex concentrated alloys (CCA) has unveiled materials with diverse atomic environments, prompting the exploration of solute segregation beyond dilute alloys. However, the vast number of possible elemental interactions means a computationally prohibitive number of simulations are needed for comprehensive segregation energy spectrum analysis. Data-driven methods offer promising solutions for overcoming such limitations for modeling segregation in such chemically complex environments (CCEs), and are employed in this study to understand segregation behavior of a refractory CCA, NbMoTaW. A flexible methodology is developed that uses composable computational modules, with different arrangements of these modules employed to obtain site availabilities at absolute zero and the corresponding density of states beyond the dilute limit, resulting in an extremely large dataset containing 10 million data points. The artificial neural network developed here can rely solely on descriptions of local atomic environments to predict behavior at the dilute limit with very small errors, while the addition of negative segregation instance classification allows any solute concentration from zero up to the equiatomic concentration for ternary or quaternary alloys to be modeled at room temperature. The machine learning model thus achieves a significant speed advantage over traditional atomistic simulations, being four orders of magnitude faster, while only experiencing a minimal reduction in accuracy. This efficiency presents a powerful tool for rapid microstructural and interfacial design in unseen domains. Scientifically, our approach reveals a transition in the segregation behavior of Mo from unfavorable in simple systems to favorable in complex environments. Additionally, increasing solute concentration was observed to cause anti-segregation sites to begin to fill, challenging conventional understanding and highlighting the complexity of segregation dynamics in CCEs.
Comparative experiment using free fall and projectile motions in determining the acceleration due to gravitational force
Authors: Marte Sherwin J , Bug-os Mary Allein Antoenette C , Pili Unofre B
Published: June 2024

Classroom experiments using modern experimental tools like smartphones are in growing popularity. Hence, this study conducted a comparative experiment to determine the acceleration values due to gravitational force in free fall and projectile motions using simple materials and the sound sensor. In this experiment, the relationship between the height and the time squared of the fall in both free fall and projectile motions is represented in regression model. Notably, experimental values for g for free fall and projectile motions are close to the accepted acceleration value due to gravitational force.
Discharging a capacitor
Authors: Ziese M
Published: June 2024

Discharging a capacitor is a standard experiment in physics education. Here it is described in a form that challenges students’ preconceptions, since the voltage across the capacitor is observed to oscillate after switching off the power supply. The aim is to demonstrate the importance and relevance of experiments and measurements, even if these are in contradiction with expectations and textbooks. Students have the opportunity to develop a quantitative model for the observations and explore the transition from oscillatory to overdamped behaviour—with the latter being the standard in textbook presentations—in further measurements. The experiment can also be used in schools, since the concept of tuning the damping by resistance variation is rather intuitive and insightful even without a formal mathematical background.
Piezoelectric energy harvester for wind turbine blades based on bistable response of a composite beam in post-buckling
Authors: Plagianakos Theofanis S , Leventakis Nikolaos , Chrysochoidis Nikolaos A , Kardarakos Grigorios-Christos , Margelis Nikolaos , Bolanakis Georgios , Papadopoulos Evangelos G , Saravanos Dimitris A
Published: June 2024

A bistable piezoelectric energy harvester (PEH) is presented for harvesting power from vibrations occurring at low frequencies, as is the case of wind turbine blades. The axial compressive prestress of a piezoelectric composite beam at post-buckling serves as the bistability source, leading to high mechanical to electric power conversion. An in-house harvesting circuit connected to the piezoelectric terminals is used for demonstration of its harvesting power capabilities. A finite element (FE) model is used to analyze and optimize the coupled nonlinear electromechanical response of the PEH, including structure and circuit. A physical prototype has been manufactured and tested for validation of the electromechanical design and the FE modeling approach. Predictions and measurements indicate an increase of harvested power with applied prestress up to a transition point, where a sudden drop in power occurs. Good comparison between numerical and experimental results verified the modeling approach, whereas deviations related to physical boundary conditions at large compressive forces affected the prediction of the transition point in harvested power. The harvester produced 1.32 mW of electrical power under tonal base excitation of 1 g at 8 Hz. Hence, the nonlinear PEH has demonstrated its capability to harvest energy at frequencies much lower than its first linear modal frequency and could thus serve as a promising solution for powering IoT devices and sensors in large vibrating structures.
Enhancement of structural, optical, electrical, optoelectronic and thermoelectric properties of ZnO thin film via Ni doping and Ni-B co-doping
Authors: Üzar N , Abdulaziz U , Erbas O G , Aydin M , Dolgun M F
Published: June 2024

In this study, the effects of nickel (Ni) and boron (B) elements on the structural, optical, electrical, optoelectronic, and thermoelectric properties of zinc oxide (ZnO) material were investigated. Therefore, undoped ZnO, 3% Ni-doped ZnO (Zn0.97Ni0.03O), and 3% Ni-1% B co-doped ZnO (Zn0.96Ni0.03B0.01O) solutions were prepared by the sol gel method. The produced solutions were coated on glass and p-type Si substrates via dip coating and spraying methods in the form of thin films. We produce pure and n-type semiconductors in the form of nanodots which have wurtzite ZnO polycrystalline structure for all samples. Ni and B co-doped sample is morphologically, electrically and optically enhanced the ZnO material with 3.08 eV band gap, homogenous surface and the highest electrical conductivity. In addition, the best material among the three samples that can be used as a visible light-sensitive sensor is Zn0.96Ni0.03B0.01O under feedback voltage. Technologically, this material can be turned into a photodiode device in the form of Au/Zn0.96Ni0.03B0.01O/p-Si. While the obtained ideality factor of ZnO from the forward bias region decreases from 5.7 to 3.4, its barrier height increases from 0.636 eV to 0.667 eV and serial resistance of contact decreases from 121.6 × 103 Ω to 5.6 × 103 Ω with Ni and B co-doping. Ni doping thin film improves the photovoltaic, and thermoelectric properties of ZnO. Ni-doped ZnO sample can be studied in form of the thin films as a thermoelectric material due to its ZT value is nearly 1.73 × 10–4 at 650 K. Its thermoelectric performance is 13 times better than the that of pure ZnO for the same temperature values. The efficiency of Ni-doped ZnO sample as solar cell increases 10 times compared to pure ZnO. In addition to the production of materials with improved energy efficiency, economical products suitable for use in large areas have been obtained in this study.
Optical limiting performance of Ga0.85In0.15Se and Ga0.90In0.10Se crystals in near infrared region
Authors: Pepe Yasemin
Published: June 2024

Optical limiter materials are essential for protecting people’s health due to its higher penetrating capabilities. In this study, Ga0.85In0.15Se and Ga0.90In0.10Se crystals were synthesized using Bridgemann-Stochbarger method to investigate their optical limiting performance in near infrared region. Linear optical results revealed that although the crystals had approximately the same band gap energy, the Ga0.90In0.10Se crystal had more defects due to its higher thickness. Open aperture Z-scan measurements were conducted with femtosecond pulsed laser at 1200 nm excitation wavelength. The examined crystals’ nonlinear absorption (NA) behavior was shown, with the Ga0.90In0.10Se crystal exhibiting the strongest NA behavior. Considering to their band gap energy and Urbach energies, the main NA mechanism was the two-photon absorption (2PA) and its contribution to NA increased with increase of the input intensity. Among the studied ternary crystals Ga0.90In0.10Se crystal showed high limiting performance with 1.11 mJ/cm2 optical limiting threshold. They are attractive candidates for efficient optical limiting applications at 1200 nm due to their strong NA behavior.
Dynamical analysis of the low-temperature phase diagram of a cuprate superconductor
Authors: Suzuki Sokichi
Published: June 2024

For a cuprate superconductor, specifically the yttrium barium copper oxide system, we analyze the low-temperature phase diagram consisting of the superconducting, pseudogap, and normal phases by using a phonon-mediated attraction and Coulomb repulsion mechanism. Through this analysis, we show this mechanism in the cuprate is quite important for its key dynamics. For the pairing mechanism, a variational method is developed and applied, and a generalized mean field theory is used to calculate the condensate energy and the energy gap of the quasiparticle. We obtain a self-consistent system of equations for these quantities. The superconducting and pseudogap phases, which involve pair-condensates, are assumed to be equilibrium systems of the condensate and normal subphases. The condition for the phase transition point is given by the equal total electronic energy gains. Assuming that the difference in the pairing range of the pair condensate is small between just above and below the transition temperature, computations are performed to solve the self-consistent system of equations. We find solutions compatible with experimental data. Plausible values of the energy gap in the superconducting phase and in the pseudogap phase are obtained. The present analysis shows that the phonon-mediated attraction and Coulomb repulsion mechanism itself is compatible with the experimental data. The importance of the screening effect through one-phonon exchange in the pairing mechanism and of the structure of the valence band is discussed.
High-efficiency implementation of Toeplitz Strong Extractor for PRNG and QRNG output on CPU/GPU hardware systems
Authors: K S V Anurag , Raghavan G , P Kanaka Raju
Published: June 2024

Random Number Generators (RNGs) are devices whose utility spans from cryptography to gambling. Depending on the source of the random seed, RNGs are classified as Pseudo-Random Number Generators (PRNGs), which are based on mathematical algorithms, True Random Number Generators (TRNGs) sourced through seemingly random physical processes, and finally, Quantum Random Number Generators (QRNGs) which harness the intrinsic randomness of measured outcomes of quantum states. To ensure that the output of a QRNG is private and nearly uniform, the raw data undergoes a strong extraction process such as Toeplitz or Trevisan Hashing. The extraction process needs to be extremely efficient to achieve high-speed random number generation. The present work demonstrates state-of-the-art methods for performing information-theoretically provable randomness extraction using variations of the Toeplitz Hashing algorithm. These algorithms are implemented on various hardware for comprehensive analysis. Subsequently, these methods are applied to two raw data sets from a PRNG source and a quantum source. A new benchmark of 19.5 Gbps for Randomness Extraction using the Fast Fourier Transform-based Toeplitz Strong Extractor is demonstrated in this work. The implementation of the algorithm on a GPU-based system demonstrates notably enhanced speed, marking a significant leap beyond the existing state-of-the-art implementations.
First-principales study of the structural, magnetic and optoelectronic properties of double perovskite Ba2FeReO6
Authors: Kerrai Hamza , Zaim Ahmed , Kerouad Mohamed
Published: June 2024

In this study, we investigate the electronic, magnetic, and optical properties of the Ba2FeReO6 double perovskite using density functional theory within the framework of the full-potential linearized augmented plane Wave method. We employ various approximations including GGA-PBE, GGA + U (Hubbard Coulomb correction), and GGA plus Spin-Orbit coupling (GGA + SOC). The densities of states and spin-polarized band structure reveal a half-metallic behavior with a magnetic moment of 3 μ

B
for all approximations, with iron and rhenium atoms contributing the most to the overall magnetic moment. Regarding optical properties, it can be stated that the Ba2FeReO6 material exhibits strong absorption and holds potential for application across a wide energy range spanning from visible to ultraviolet light spectra in future spintronics and optoelectronic technologies.
Structural, electronic, mechanical, thermodynamic and optical properties of oxide perovskite BeZrO3: a DFT study
Authors: Munshi Md Rajib , Al Masud Md , Khatun Afroza
Published: June 2024

The geometrical, electronic, mechanical, thermodynamic, and optical aspects of BeZrO3 crystal have been investigated employing Generalized Gradient Approximation (GGA) with Perdew–Burke–Ernzerhof (PBE), Revised Perdew–Burke–Ernzerhof (RPBE), Local density approximation (LDA) with Ceperley Alder and Perdew Zunger (CA-PZ) techniques under density functional theory. The band gap values of BeZrO3 have been reported to be 0.603 eV, 0.623 eV, 0.614 eV and 2.20 eV respectively in PBE, RPBE, LDA and Becke, 3-parameter, Lee–Yang–Parr (B3LYP) methods. Total and partial density analysis was used to determine atomic orbital nature of the Be, Zr, and O atoms in BeZrO3. By estimating the Mulliken population charge, the bonding characteristics of BeZrO3 have been elucidated. Using the Born mechanical stability criterion, it was determined that BeZrO3 crystal is mechanically stable. The evaluation of ductile strength was expressed by using Poisson and Pugh’s critical ratios, revealing the inherent elastic anisotropy features. The optical characteristics have been conducted using various methodologies, concluded that BeZrO3 exhibits remarkable efficacy in absorbing ultraviolet and visible light.
Screening effect on the phonon drag induced seebeck coefficient in bilayer graphene/quasi-two-dimensional electron gas structures
Authors: Van Tuan T , Khanh N Q , Van Tai V , Van Nguyen Khoe , Dang Linh Khanh
Published: June 2024

In this work, we investigate the impacts of the temperature-dependent screening effect on the Seebeck coefficient originating from the phonon drag, namely phonon—drag thermopower S

g
, of a double layer system consisting of bilayer graphene (BLG) separated from a quasi-two-dimensional electron gas (q2DEG) by an air medium (hereafter referred to as BLG-q2DEG). For such a system, we can assume that the two-dimensional (2D) electrons in BLG only interact internally with acoustic phonons. We consider the effects of screening induced by the 2D electrons in q2DEG on the electron–phonon interactions in BLG by comparing with the results obtained when only using the monolayer screening function in BLG. The monolayer screening functions in BLG (q2DEG) do not depend on the distance d between the two layers, and the screening function of the double layer system approaches the respective monolayer screening functions for large d. When taking into account of the screening effect caused by charged carriers in both layers, S

g
of a BLG-q2DEG decreases compared to the case of only considering the monolayer screening effect, especially in the low-T regime. With different carrier densities in the two layers

N

s

BLG

≠

N

s

GaAs

,

it has shown that S

g
strongly depends on BLG. Besides, when changing the width L of the q2DEG such as GaAs quantum well, the double layer screening function makes S

g
increase for small L and negligibly affects S

g
for large L. On the contrary, the monolayer screening functions make S

g
decrease for large L. The monolayer screening functions cause S

g
to increase for

N

s

BLG

<

N

s

GaAs

.
Radio Galaxy Zoo: Leveraging latent space representations from variational autoencoder
Authors: Andrianomena Sambatra , Tang Hongming
Published: June 2024

We propose to learn latent space representations of radio galaxies, and train a very deep
variational autoencoder (VDVAE) on RGZ DR1, an unlabeled dataset, to this end. We show
that the encoded features can be leveraged for downstream tasks such as classifying galaxies in
labeled datasets, and similarity search. Results show that the model is able to reconstruct its
given inputs, capturing the salient features of the latter. We use the latent codes of galaxy
images, from MiraBest Confident and FR-DEEP NVSS datasets, to train various non-neural network
classifiers. It is found that the latter can differentiate FRI from FRII galaxies achieving
 accuracy ≥ 76%, roc-auc ≥ 0.86, specificity ≥ 0.73 and
 recall ≥ 0.78 on MiraBest Confident dataset, comparable to results obtained in
previous studies. The performance of simple classifiers trained on FR-DEEP NVSS data
representations is on par with that of a deep learning classifier (CNN based) trained on images in
previous work, highlighting how powerful the compressed information is. We successfully exploit
the learned representations to search for galaxies in a dataset that are semantically similar to a
query image belonging to a different dataset. Although generating new galaxy images (e.g. for data
augmentation) is not our primary objective, we find that the VDVAE model is a relatively
good emulator. Finally, as a step toward detecting anomaly/novelty, a density estimator — Masked
Autoregressive Flow (MAF) — is trained on the latent codes, such that the log-likelihood
of data can be estimated. The downstream tasks conducted in this work demonstrate the
meaningfulness of the latent codes.