bluuebunny/crossref_metadata_2025_split huggingface dataset:
Molecular dynamics study of a nano-scale β-type Stirling engine
Authors: Kitaya K , Isobe M 
Published: March 2022

Abstract
A Stirling engine is based on a thermodynamic cycle; a temperature difference causes flywheel rotation. Because the arbitrary (stochastic) heat resources contact some of the systems that generate the work (i.e., the energy), Stirling engines remain important in the present era of Sustainable Development Goals because of their broad applicability. This study focuses on a nano-scale “β-type” Stirling engine, specifically concerning a model for numerical simulation. We perform molecular dynamics simulation of the two-dimensional model (using hundreds of particles) and calculate the thermal efficiency. We figured out the minimal necessary conditions for stable rotation, as well as the lower limits of particle numbers and temperature differences for autonomous thermodynamic cycles.
Nonequilibrium dynamics of a fluid vesicle: Turing patterns and traveling waves
Authors: Noguchi Hiroshi , Tamemoto Naoki 
Published: March 2022

Abstract
In living cells, the shapes of biomembranes are dynamically regulated by proteins. We briefly review our recent studies on the membrane dynamics coupled with reaction-diffusion dynamics of curvature-inducing proteins. We simulated a vesicle in a fluid phase using a dynamically triangulated membrane model combined with a modified Brusselator model. The mechanochemical feedback of curvature-inducing proteins changes the condition of Turing patterns relative to those that occur on a non-deformable curved surface. Budding and multi-spindle shapes are also stabilized by Turing patterns. The speed of traveling waves increases or decreases with increasing local membrane curvature depending on the condition. Moreover, the reaction-diffusion waves can induce the self-oscillation of vesicle shapes.
Theoretical Study of Dissociation Process of Plastocyanins by PaCS-MD Simulation
Authors: Fitrasari D , Arwansyah M S , Kawaguchi K , Purqon A , Suprijadi  , Nagao H 
Published: March 2022

Abstract
We present a procedure of calculation of free energy landscape of two proteins by using parallel cascade molecular dynamics (PaCS-MD) and multiple independent umbrella sampling (MIUS). The free energy landscape of two plastocyanins for association/dissociation process is investigate by using the present method. We find that binding free energy is around 1 kcal/mol and that the barrier energy at around the middle range between the equilibrium point and the dissociation state becomes about 1 kcal/mol from the association process. The present results suggest that the energy barrier may arise from hydrogen bonds between two plastocyanins. We also find that the effective interaction between two plastocyanins already vanishes at the distance of 2 Å from equilibrium state. The equilibrium point of the complex around 27.9 Å is a good agreement with the experimental result 27.8 Å
Enhancing efficient computation of long-wavelength relaxation dynamics in a 2D liquid involving millions of particles
Authors: Shiba Hayato 
Published: March 2022

Abstract
Recently, a two-dimensional liquid cooled toward the glass transition was found to exhibit a t
−1 long-time tail in the velocity autocorrelation function (VACF) owing to the presence of long-wavelength fluctuations. To directly observe this power-law behaviour, it is necessary to simulate a large system with millions of particles, which is a challenging task from the computational viewpoint. In this study, to address this difficulty, I first show that this power-law tail can be reproduced by differentiating the finite-time diffusivity with respect to time. In addition, the feasibility of another direction, a direct on-the-fly computation of the VACFs utilizing GPGPUs, wherein VACFs are evaluated as the simulation runs, is also demonstrated. A performance benchmark was executed on Wisteria/BDEC-01 (Aquarius subsystem) supercomputer using a simulation code developed by the author, which enabled the direct computation of the VACF of 4 million particlesx for as long as the 108 simulation steps within 10 days.
Higher Order Auxiliary Field Quantum Monte Carlo Methods
Authors: Goth Florian 
Published: March 2022

Abstract
The auxiliary field quantum Monte Carlo (AFQMC) method has been a workhorse in the field of strongly correlated electrons for a long time and has found its most recent implementation in the ALF package (alf.physik.uni-wuerzburg.de). The utilization of the Trotter decomposition to decouple the interaction from the non-interacting Hamiltonian makes this method inherently second order in terms of the imaginary time slice. We show that due to the use of the Hubbard-Stratonovich transformation (HST) a semigroup structure on the time evolution is imposed that necessitates the introduction of a new family of complex-hermitian splitting methods for the purpose of reaching higher order. We will give examples of these new methods and study their efficiency, as well as perform comparisons with other established second and higher order methods in the realm of the AFQMC method.
QMC study of the chiral Heisenberg Gross-Neveu universality class
Authors: Otsuka Yuichi , Seki Kazuhiro , Sorella Sandro , Yunoki Seiji 
Published: March 2022

Abstract
We investigate a quantum criticality of an antiferromagnetic phase transition in the Hubbard model on a square lattice with a d-wave pairing field by large-scale auxiliary-field quantum Monte Carlo simulations. Since the d-wave pairing filed induces Dirac cones in the non-interacting single-particle spectrum, the quantum criticality should correspond to the chiral Heisenberg universality class in terms of the Gross-Neveu theory, which is the same as those expected in the Hubbard model on the honeycomb lattice, despite the unit cells being different (e.g., they contain one and two sites, respectively). We show that both the two phase transitions, expected to occur on the square and on the honeycomb lattices, indeed have the same quantum criticality. We also argue that details of the models, i.e., the way of counting the total number N of fermion components and the anisotropy of the Dirac cones, do not change the critical exponents.
Density-matrix renormalization-group study for a two-dimensional lattice-gas on the Ih-ice prism surface
Authors: Akutsu Noriko 
Published: March 2022

Abstract
The phase transition temperature of a two-dimensional (2D) lattice-gas model for the Ih-ice prism surface ((1010) surface on a wurtzite crystal structure) is calculated using the density-matrix renormalization-group (DMRG) method. Since the unit cell on the prism surface contains four atoms without inversion symmetry, the asymmetric version of the DMRG is required to obtain a precise value of the phase transition temperature. The effective bond energy on the surface is obtained by comparing the phase transition temperature with the faceting transition temperature observed for a real ice crystal. Using the effective bond energy, the temperature dependence of the coverage on sub-lattice sites is calculated. The surface tensions on the (0001) surface (the basal plane) and the prism plane are also calculated. The surface tension of the basal plane for the ice/water interface agrees well with the recent calculated values obtained by large scale molecular dynamics.
Unified Time Evolution Approach for the Electronic Structure Calculation
Authors: Wang Q , Zempo Y 
Published: March 2022

Abstract
In imaginary-time evolution, the same technique, Crank–Nicolson’s method, as for the analysis of real-time evolution is employed. For the verification using the model oscillators such as quantum well, Morse, and harmonic potentials, practical density functional theory (DFT) calculations are performed for hydrogen atoms and molecules. The convergence is confirmed to be faster under appropriate initial and boundary conditions. The results are consistent with the analytical solutions and those of other DFT calculations. Imaginary-time evolution is quite convenient to subsequent real-time real-space time-dependent DFT calculation. Although the operators are different, similar evolution is adopted. This technique is expected to unify into practical electronic state calculations for the self-consistent electronic structure and system’s response due to perturbation because calculations are in the same framework as the time-dependent equation.
Optical Properties of OLED Materials by TDDFT
Authors: Akino N , Zempo Y 
Published: March 2022

Abstract
For the material design of organic light emitting diodes, it is highly desired to simulate the spectral profile, that is, not only the peak wavelength but also its spectrum shape. Time dependent density functional theory in real-space and real-time formalism is applied to simulate the spectrum profile of typical organic materials, poly(9,9’-dioctyl-fluorene) and Ir(ppy)3. Although the some red-shift in the peak wavelength has been observed due to the use of the local density approximation, the overall simulated profiles agree well with the experiments. Although the study is in preliminary stage, the results show that this approach may be able to simulate the spectrum profile reasonably well within a reasonable computation time.
Phenomenological Simulations of Intermediate States in a Type I Superconducting Wire
Authors: Mizuhara Yohitaka , Kato Masaru 
Published: March 2022

Abstract
We have investigated superconducting state of a type I superconducting wire solving the Ginzburg Landau equation with finite element method. When a critical current is applied to a type I superconducting wire, superconductivity becomes inhomogeneous. We find superconductivity shows oscillatory structures which are similar to London proposed intermediate state. In the simulations, we impose two types of boundary conditions, phase-fixed and vector potential-fixed. Under both boundary conditions, we have obtained similar periodic structures.
The Unstable Analysis of Soliton Compression in Silicon Photonic Crystal
Authors: Phibanchon Sarun 
Published: March 2022

Abstract
Soliton solutions to the perturbed nonlinear Schrodinger equation, for describing the wave in the photonic crystal, can be found by the sine-Gordon expansion method. This method provides both bright and dark soliton solutions. The instability of the perturbed bright soliton in the perpendicular direction to the wave motion cab be expressed in terms of the growth rate. The time evolution of the unstable soliton can be visualized from the transformation to the higher dimensional solitons by the spectral method.
Plasma propagation via radiation transfer in millimeter-wave discharge under subcritical condition
Authors: Suzuki S , Kato C , Takahashi M , Ohnishi N 
Published: March 2022

Abstract
An improved model was proposed to reduce a computational cost for subcritical millimeter-wave discharge. The proposed model was able to reproduce the plasma-front propagation via radiation transport as similar to the conventional model, and the plasma-front propagation speed was in agreement with the previous simulation. An electron transport effect by neutral fluid advection, which has been introduced into the conventional model, does not affect the propagation speed. By using the presented model, a computational time was reduced by 35%, which was suitable for a multi-dimensional simulation in the future.
Quantum field theories, Markov random fields and machine learning
Authors: Bachtis Dimitrios , Aarts Gert , Lucini Biagio 
Published: March 2022

Abstract
The transition to Euclidean space and the discretization of quantum field theories on spatial or space-time lattices opens up the opportunity to investigate probabilistic machine learning within quantum field theory. Here, we will discuss how discretized Euclidean field theories, such as the ϕ
4 lattice field theory on a square lattice, are mathematically equivalent to Markov fields, a notable class of probabilistic graphical models with applications in a variety of research areas, including machine learning. The results are established based on the Hammersley-Clifford theorem. We will then derive neural networks from quantum field theories and discuss applications pertinent to the minimization of the Kullback-Leibler divergence for the probability distribution of the ϕ
4 machine learning algorithms and other probability distributions.
Machine Learning the Square-Lattice Ising Model
Authors: Çivitcioğlu Burak , Römer Rudolf A. , Honecker Andreas 
Published: March 2022

Abstract
Recently, machine-learning methods have been shown to be successful in identifying and classifying different phases of the square-lattice Ising model. We study the performance and limits of classification and regression models. In particular, we investigate how accurately the correlation length, energy and magnetisation can be recovered from a given configuration. We find that a supervised learning study of a regression model yields good predictions for magnetisation and energy, and acceptable predictions for the correlation length.
Effect of mask-film properties on the initial GaAs nanowire growth stages
Authors: Zhikharev P V , Shwartz N L 
Published: March 2022

Abstract
The initial self-catalyze GaAs nanowire (NW) growth stages were studied using Monte Carlo simulation. We analyzed the effect of the mask-film etching rate with liquid gallium for different thicknesses on the initial nanowire formation stages. At a high etching rate NWs do not form on thick mask-films. A high etching rate of a thin film-mask can lead to lateral Ga drop motion over the crystalline substrate surface, which delays the nanowire formation onset. It is shown that, for the NW formation, it is necessary to maintain the correct ratio between the film thickness, etching rate, Ga and As2 flux intensities.
Linear and nonlinear optical properties of vertically coupled cylindrical double quantum dots with modified Pöschl-Teller potential
Authors: Sargsian T A , Vinnichenko M Ya , Hayrapetyan D B 
Published: March 2022

Abstract
Linear and third-order nonlinear absorption coefficients have been theoretically investigated in a system of vertically coupled cylindrical double quantum dots with the modified Pöschl-Teller potential in the axial direction and parabolic potential in the radial direction. Also, changes in the refractive index in these conditions were obtained. For intraband optical transitions of charge carriers in such system the selection rules have been obtained. The behaviour of the linear, nonlinear and total absorption spectra and changes in the refractive index have been theoretically observed for different lattice temperatures and illustrated by the corresponding graphs for two temperatures.
Photoluminescence temperature quenching of H2TPP and ZnTPP tetraphenylporphyrins thin films
Authors: Alimova E S , Zakharova I B , Elistratova M A 
Published: March 2022

Abstract
Photoluminescence temperature quenching of tetraphenylporphyrins thin films on silicon substrates have been investigated. Free-based tetraphenylporphyrin (H2TPP) and Zinc-tetraphenylporphyrin (ZnTPP) films were obtained by thermal evaporation in vacuum. The photoluminescence properties of these samples are observed in the wide temperature range from 77 to 300 K. The temperature-depended photoluminescence intensity of ZnTPP exhibits abnormal behaviour. An increase in the photoluminescence intensity is observed in the temperature range of 77-180 K. We suppose that charge carriers are trapped by non-radiative centres when the temperature decreases down to 77 K. The release of carriers occurs with a further temperature increase. In addition, there are sharp increases in the luminescence intensity of thin H2TPP and ZnTPP films at a temperature of 270 K, which are associated with a second-order phase transition.
Climate change impacts and adaptation strategies for crops in West Africa: a systematic review
Authors: Carr Tony W , Mkuhlani Siyabusa , Segnon Alcade C , Ali Zakari , Zougmoré Robert , Dangour Alan D , Green Rosemary , Scheelbeek Pauline 
Published: March 2022

Abstract
Agriculture in West Africa faces the challenge of meeting the rising demand for food as national incomes and populations increase while production becomes more uncertain due to climate change. Crop production models can provide helpful information on agricultural yields under a range of climate change scenarios and on the impact of adaptation strategies. Here, we report a systematic review of the impact of climate change on the yield of major staple crops in West Africa. Unlike earlier reviews we pay particular attention to the potential of common agricultural adaptation strategies (such as optimised planting dates, use of fertilisers and climate-resilient crop varieties) to mitigate the effects of climate change on crop yields. We systematically searched two databases for literature published between 2005 and 2020 and identified 35 relevant studies. We analysed yield changes of major staple crops (maize, sorghum, rice, millet, yam, cassava and groundnuts) caused by different climate change and field management scenarios. Yields declined by a median of 6% (−8% to +2% depending on the crop) due to climate change in all scenarios analysed. We show that the common adaptation strategies could increase crop yields affected by climate change by 13% (−4% to +19% depending on the strategy) as compared to business-as-usual field management practices, and that optimised planting dates and cultivars with longer crop cycle duration could in fact offset the negative effects of climate change on crop yields. Increased fertiliser use has not mitigated the impact of climate change on crops but could substantially increase yields now and in the future. Our results suggest that a combination of increased fertiliser use and adopting cropping practices that take advantage of favourable climate conditions have great potential to protect and enhance future crop production in West Africa.
CFD analysis of Effect of journal bearing lubricated with non-Newtonian fluid
Authors: Prakash sharma Jai , Tyagi M R , Thakre G D 
Published: March 2022

Abstract
The present paper deals with the CFD analysis of hydrodynamic bearing lubricated with a non-Newtonian fluid and the non-Newtonian behaviour of lubricant is represented by a power-law. Bearing parameters such as fluid film pressure and load-carrying capacity are determined by varying the power-law index (n) in terms of its viscosity from 0.8 to 1.2 under steady-state conditions through the CFX 17.2 software module and the flow model opted as Laminar based on Reynolds number calculation as per the geometry developed for the simulation. The relationship between the pressure and load-carrying capacity are also obtained for different relative clearance, revolution per minute and L/D ratio. Fluid film pressure profile was drawn by varying input parameters at different power-law index for understanding the performance of HDB under different regimes i.e. dilatant, Newtonian and pseudoplastic fluids. Plots were also created between Pressure, load carrying capacity and power law index to study the performance of HDB. This has been observed that the bearings lubricated with dilatant fluid (n >1) have higher pressure and load carrying capacity as compared to those lubricated with pseudoplastic fluid (n < 1). Occurrences of cavitation were also seen at lower angle with increases in power law index for 0.0006 relative clearance but increases at 0.0008.
Face Recognition Method Based on Residual Convolution Neural Network
Authors: Husain Arshi , Vishvakarma Virendra P. 
Published: March 2022

Abstract
With the advancement of information technology and societal growth, social security has become more important than ever. Face recognition, as compared to other traditional recognition methods like fingerprint recognition, palm recognition, etc, has the benefit that it is contact less, and now it is becoming one among the most prominent technologies in development. Although there are numerous recognition systems that use DNNs in the field of facial expression recognition, their accuracy and practicality are still insufficient for real-world applications. A facial recognition approach based on Resnet 152 v2 has been proposed in this work. In this paper, a residual learning approach is presented to make the training of networks that are far deeper than previously employed networks easier. The proposed method, employs the AT&T face dataset, and supposing that normalization and segmentation are complete, we concentrate on the subtask of person verification and recognition, demonstrating performance using a testing database comprising illumination, pose, expression and occlusion variations. SoftMax is the activation function that has been used, which adjusts the output sum up to one allowing it to be understood as probabilities. Then, the model would generate a judgment depending on which option has a strong likelihood. This system employs Adam as an optimizer to control the learning rate through training and categorical cross entropy as its loss function. The proposed approach has a 97 percent face recognition accuracy on AT&T dataset, showing its efficacy after a significant number of analyses and experimental verification.
Water absorption study and characterization of polymer composites developed from discarded nylon carpet
Authors: Verma Rajesh Kumar , Jaiswal Balram , Vishwakarma Rahul , Kumar Kuldeep , Kumar Kaushlendra 
Published: March 2022

Abstract
The scientific objective of this work is to reuse the polymer materials generated from carpet waste. The nylon obtained from the discarded carpet was used as reinforcement material into the epoxy matrix phase. A modified approach of Vacuum-assisted resin transfer molding (VARTM) was used to infuse the mixture of epoxy and hardener into the nylon carpet polymer composites. This investigates the water absorption behavior of carpet waste composite. It will justify the application of proposed composites for lightweight structural applications in a moisture environment. The nylon fiber-based-epoxy composite was dipped in water as per ASTM standard for a different duration, namely, 24, 48, 72, 144 hours. The findings demonstrate that it can effectively withstand in moisture environment, and a maximum 4.5% weight of samples increased among all the samples for a different duration. Also, the developed composite showed a lower water diffusion co-efficient than the nail head structure and linden wood. Also, the carpet waste composite samples were investigated for thermal degradation and chemical behavior using X-Ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy, respectively. The finding shows that the proposed composite could be used for lightweight components such as dashboard panels, sound absorbers, panel sheets, wall tiles, etc.
A study on engine piston optimization by generative design approach
Authors: Arunkumar A , Sooriyamoorthy A , Mishael C , Giri A 
Published: March 2022

Abstract
Significant enterprises today favor the cooperation of generative plans in the manufacturing and assembling departments. Therefore our aim is to dwell on the more straightforward degrees of generative design to demonstrate the modification of boundary conditions and properties to exhibit modern applications. Generative Design has demonstrated to be a significant upgrade in the machine-producing side of the business because of the simplicity in changes, higher resilience, and reduced number of faults that arise. Nevertheless owing to the added complex shape of structures, the model generation and design are posed with challenges. This paper involves the examination and generative design of a 4-Stroke engine piston. The proposed method is validated through a study which closely resembles a real life prototype. The examination aims to dissect and detail a newly formed design grid for the current cylinder of the F20C 4 - stroke 4 - cylinder engine at the core of the Honda S2000. Our aim to study on piston design, which makes it lighter and more efficient while keeping the similar volume yield in the cylinder. The paper depicts the process of optimizing the component through mass reduction where the mass was reduced by close to twenty three percent.