Optimized geometry and electronic structure of graphyne-like silicyne nanoribbons

Silicyne, a silicon allotrope, which is closely related to silicene and has graphyne-like structure, is theoretically in- vestigated in this work. Its optimized geometry and electronic band structure are calculated by means of the first-principles frozen-core projector-augmented wave method implemented in the Vienna ab initio simulation package （VASP）. We find that the lattice parameter is 9.5A, the silicon chain between hexagons is composed of disilynic linkages （-Si≡Si-） rather than cumulative linkages （=Si=Si=）, and the binding energy is -3.41 eV per atom. The band structure is calculated by adopting the generalized gradient approximation and hybrid functionals. The band gap produced by the HSE06 functional is 0.73 eV, which is nearly triple that by the generalized gradient approximation of Perdew-Burke-Emzerhof functional.

Molecular simulation study on K^＋-Cl^- ion pair in geological fluids

This paper reports a classical molecular dynamics study of the potential of mean forces(PMFs),association constants,microstructures K^+-Cl^- ion pair in supercritical fluids.The constrained MD method is used to derive the PMFs of K^+-Cl^- ion pair from 673 to 1273 K in low-density water(0.10-0.60 g/cm).The PMF results show that the contact ion-pair(CIP) state is the one most energetically favored for a K^+-Cl^- ion pair.The association constants of the K^+-Cl^- ion pair are calculated from the PMFs,indicating that the K^+-Cl^- ion pair is thermodynamically stable.It gets more stable as T increases or water density decreases.The microstructures of the K^+-Cl^- ion pair in the CIP and solvent-shared ion-pair states are characterized in detail.Moreover,we explore the structures and stabilities of the KCl-Au(I)/Cu(I) complexes by using quantum mechanical calculations.The results reveal that these complexes can remain stable for T up to1273 K,which indicates that KCl may act as a ligand complexing ore-forming metals in hydrothermal fluids.

Optimization of Geometry at Hartree-Fock level Using the Generalized Simulated Annealing

This work presents a procedure to optimize the molecular geometry at the Hartree-Fock level, based on a global opti-mization method—the Generalized Simulated Annealing. The main characteristic of this methodology is that, at least in principle, it enables the mapping of the energy hypersurface as to guarantee the achievement of the absolute minimum. This method does not use expansions of the energy, nor of its derivates, in terms of the conformation variables. Distinctly, it performs a direct optimization of the total Hartree-Fock energy through a stochastic strategy. The algorithm was tested by determining the Hartree-Fock ground state and optimum geometries of the H2, LiH, BH, Li2, CH+, OH?, FH, CO, CH, NH, OH and O2 systems. The convergence of our algorithm is totally independent of the initial point and do not require any previous specification of the orbital occupancies.

Optimized geometry and electronic structure of three-dimensional β-graphyne

β-graphyne, a carbon allotrope, is a gapless semiconductor with hexagonal lattice symmetry, just like graphene. We calculated the optimized structure and electronic structures of some possible three-dimensional β- graphyne stacking arrangements by means of the first-principles frozen-core projector augmented-wave method implemented in the Vienna ab initio simulation package. The optimized lattice constant a of the three-dimensional β-graphyne turns out to be 9.46 A, which is slightly smaller than its two-dimensional counterpart. The binding energy is about 90% of that of graphite, which suggests that three-dimensional β-graphyne will be stable when it is synthesized. The band structure is calculated via the hybrid functional. We found that the most stable threedimensional stacking arrangement is an indirect band gap semiconductor with an energy gap of 0.1 eV.

Effects of Working Fluid,Tubeside Enhancement and Bundle Depth on the Optimized Fin Geometry of a Horizontal Condenser Tube

A theoretical study has been made to optimize the fin geometry of a horizontal finned tube which is to be used for condensers that handle the vapor load of a liquid phase change cooling module.Systematic numerical calcu- lations of the vapor to coolant heat transfer have been performed for parametric values of fin height,fin spacing, vertical bundle depth and tubeside heat transfer coefficient.Three dielectric fluids (R-113,FC-72,and FC-87) at atmospheric pressure were selected as the working fluids.For a single tube with optimized fin geometry,the average heat flux increased in the order of FC-87,R-113 and FC-72.Both the optimum fin height and optimum fin spacing increased with increasing vertical bundle depth.

Geometry and size optimization of stiffener layout for three-dimensional box structures with maximization of natural frequencies

Based on the growth mechanism of natural biological branching systems and inspiration from the morphology of plant root tips,a bionic design method called Improved Adaptive Growth Method(IAGM)has been proposed in the authors’previous research and successfully applied to the reinforcement optimization of three-dimensional box structures with respect to natural frequencies.However,as a kind of ground structure methods,the final layout patterns of stiffeners obtained by using the IAGM are highly subjected to their ground structures,which restricts the optimization effect and freedom to further improve the dynamic performance of structures.To solve this problem,a novel post-processing geometry and size optimization approach is proposed in this article.This method takes the former layout optimization result as start,and iteratively finds the optimal layout angles,locations,and lengths of stiffeners with a few design variables by optimizing the positions of some specific node lines called active node lines.At the same time,thick-nesses of stiffeners are also optimized to further improve natural frequencies of three-dimensional box structures.Using this method,stiffeners can be successfully separated from their ground structures and further effectively improve natural frequencies of three-dimensional box structures with less material consumption.Typical numerical examples are illustrated to validate the effectiveness and advantages of the suggested method.

Evaluation of Multi-Scale Full Waveform Inversion with Marine Vertical Cable Data

Seismic illumination plays an important role in subsurface imaging. A better image can be expected either through optimizing acquisition geometry or introducing more advanced seismic mi- gration and/or tomographic inversion methods involving illumination compensation. Vertical cable survey is a potential replacement of traditional marine seismic survey for its flexibility and data quality. Conventional vertical cable data processing requires separation of primaries and multiples before migration. We proposed to use multi-scale full waveform inversion （FWI） to improve illumination coverage of vertical cable survey. A deep water velocity model is built to test the capability of multi-scale FWI in detecting low velocity anomalies below seabed. Synthetic results show that multi-scale FWI is an effective model building tool in deep-water exploration. Geometry optimization through target ori- ented illumination analysis and multi-scale FWI may help to mitigate the risks of vertical cable survey. The combination of multi-scale FWI, low-frequency data and multi-vertical-cable acquisition system may provide both high resolution and high fidelity subsurface models.

Multi-objective Optimization of Welding Parameters in Submerged Arc Welding of API X65 Steel Plates

Submerged arc welding（SAW）is one of the main welding processes with high deposition rate and high welding quality.This welding method is extensively used in welding large-diameter gas transmission pipelines and high-pressure vessels.In welding of such structures,the selection process parameters has great influence on the weld bead geometry and consequently affects the weld quality.Based on Fuzzy logic and NSGA-II（Non-dominated Sorting Genetic Algorithm-II）algorithm,a new approach was proposed for weld bead geometry prediction and for process parameters optimization.First,different welding parameters including welding voltage,current and speed were set to perform SAW under different conditions on API X65 steel plates.Next,the designed Fuzzy model was used for predicting the weld bead geometry and modeling of the process.The obtained mean percentage error of penetration depth,weld bead width and height from the proposed Fuzzy model was 6.06%,6.40% and 5.82%,respectively.The process parameters were then optimized to achieve the desired values of convexity and penetration indexes simultaneously using NSGA-II algorithm.As a result,a set of optimum vectors（each vector contains current,voltage and speed within their selected experimental domains）was presented for desirable values of convexity and penetration indexes in the ranges of（0.106,0.168）and（0.354,0.561）respectively,which was more applicable in real conditions.

Geometry optimization of a barrel silicon pixelated tracker

We have studied optimization of the design of a barrel-shaped pixelated tracker for given spatial boundaries. The optimization includes choice of number of layers and layer spacing. Focusing on tracking performance only,momentum resolution is chosen as the figure of merit. The layer spacing is studied based on Gluckstern＇s method and a numerical geometry scan of all possible tracker layouts. A formula to give the optimal geometry for curvature measurement is derived in the case of negligible multiple scattering to deal with trajectories of very high momentum particles. The result is validated by a numerical scan method, which could also be implemented with any track fitting algorithm involving material effects, to search for the optimal layer spacing and to determine the total number of layers for the momentum range of interest under the same magnetic field. The geometry optimization of an inner silicon pixel tracker proposed for BESIII is also studied by using a numerical scan and these results are compared with Geant4-based simulations.

Kinetics of Reduction of Thionine with Ribose and the Structural Properties of the Dye at Different pH Using DFT Method

The reaction between the thionine （Th） and the ribose was observed spectrophotometrically and changes in absorbance of Th were recorded at variable concentration of dye, reductant and pH. A pseudo first order rate of reaction was found to establish the reduction kinetics of the dye, studied at a pH range of 0.34 to 12.8. Absorption spectrum of Th at different pH, with ribose showed a pH （12.8） dependent introversion. The reduction most probably took place with enediol intermediate of the sugar at high pH. A full geometry optimization of predominant species of Th namely, mono-deprotonated, di-deprotonated Th, and LTh （leuco thionine） respectively, at low and high pH, was performed at B3LYP level of theory. The data obtained from the energy minimization were in excellent agreement with other experimental and theoretical observations. The calculated enthalpies of formation for both reduction reactions （mono-deprotonated Th＋H＋→leucothionine and di-deprotonated Th＋2H＋→leucothionine） provided evidences for maximum reduction of the dye at high pH.

An iterative refinement method combining detector geometry optimization and diffraction model refinement in serial femtosecond crystallography

Background Recent advances in serial femtosecond crystallography(SFX)using X-ray free electron lasers(XFELs)have facilitated accurate structure determination for biological macromolecules.However,given the many fluctuations inherent in SFX,the acquisition of SFX data of sufficiently high quality still remains challenging.Method Aimed at enhancing the accuracy of SFX data,this study proposes an iterative refinement method to optimally match pairs of the observed and predicted reflections on the detector plane.This method features a combination of detector geometry optimization and diffraction model refinement in an alternate manner,concomitant with a cycle-by-cycle peak selection procedure.Result To demonstrate whether this iterative method is convergent and feasible,both numerical simulations and experimental tests have been performed.The results reveal that this method can gradually improve overall quality of the integrated SFX data and therefore accelerate the convergence of Monte Carlo integration,while simultaneously suppressing correlations inherent in certain parameters and precluding outliers to some extent during the refinement.Conclusion We have demonstrated that our iterative refinement method is applicable to both simulated and experimental SFX data.It is expected that this method could provide meaningful insights into the refinement of SFX data and take the step forward toward more accurate Monte Carlo integration.

Geometry optimizations of benzene clusters using a modified genetic algorithm

A modified genetic algorithm with real-number coding, non-uniform mutation and arithmetical crossover operators was described in this paper. A local minimization was used to improve the final solution obtained by the genetic algorithm. Using the exp-6–1 interatomic energy function, the modified genetic algorithm with local minimization (MGALM) was applied to the geometry optimization problem of small benzene clusters (C6H6)N(N = 2–7) to obtain the global minimum energy structures. MGALM is simple but the structures optimized are comparable to the published results obtained by parallel genetic algorithms.

Geometry optimization and electronic structures of molecules H_3AXAH_3

The geometries of molecules H_3AXAH_3(X=O,S,Se and A=C,Si)have been optimized using STO-3G ab initio calculations and gradient method and the results are in good agreement with reported experimental values.From the STO-3G optimized geometries,we have also calculated the electronic structures of these molecules using 4-31G and 6-31G basis sets to obtain the MO energies. atomic net charges and dipole moments.The ionization potentials calculated by 6-31G basis set are in good agreement with experimental values.

Systematic assessment of various universal machine-learning interatomic potentials

Machine-learning interatomic potentials have revolutionized materials modeling at the atomic scale.Thanks to these,it is now indeed possible to perform simulations of ab initio quality over very large time and length scales.More recently,various universal machine-learning models have been proposed as an out-of-box approach avoiding the need to train and validate specific potentials for each particular material of interest.In this paper,we review and evaluate four different universal machine-learning interatomic potentials(uMLIPs),all based on graph neural network architectures which have demonstrated transferability from one chemical system to another.The evaluation procedure relies on data both from a recent verification study of density-functional-theory implementations and from the Materials Project.Through this comprehensive evaluation,we aim to provide guidance to materials scientists in selecting suitable models for their specific research problems,offer recommendations for model selection and optimization,and stimulate discussion on potential areas for improvement in current machinelearning methodologies in materials science.