气体-表面相互作用中动量和能量分量间转化机制的分子动力学研究

气体分子与壁面之间的相互作用是影响稀薄气体流动状态的主要因素,但是由于其物理上的复杂性和微观性,这一过程的机理并没有得到充分揭示.本文利用分子束法对Ar分子在金属Pt表面的碰撞过程进行了分子动力学模拟,并探究了入射速度、角度和壁面粗糙度对动量、能量转化机制的影响.结果表明,当气体分子以5o的极角入射时,分子的法向速度分量占主导因素,在与壁面发生碰撞之后,分子的切向和法向动量都会损失,法向动能会向切向转移,并且当分子速度不低于2.0时,切向和法向动能的比值会稳定在一个很小的区间,而粗糙度对动量和能量转化的影响不明显.与小角度入射时不同,当气体分子以75o的极角与金属表面碰撞时,粗糙度的影响就不能再被忽略了.大极角入射的气体分子在光滑壁面散射之后,其运动规律基本符合Maxwell所假设的镜面反射,动量和能量分量的变化都不明显.而粗糙度的引入则会促进气体分子切向动量和能量向法向转移,并且会使分子总能量的损失更加显著.     

Why Do Big Data and Machine Learning Entail the Fractional Dynamics?

Fractional-order calculus is about the differentiation and integration of non-integer orders. Fractional calculus (FC) is based on fractional-order thinking (FOT) and has been shown to help us to understand complex systems better, improve the processing of complex signals, enhance the control of complex systems, increase the performance of optimization, and even extend the enabling of the potential for creativity. In this article, the authors discuss the fractional dynamics, FOT and rich fractional stochastic models. First, the use of fractional dynamics in big data analytics for quantifying big data variability stemming from the generation of complex systems is justified. Second, we show why fractional dynamics is needed in machine learning and optimal randomness when asking: “is there a more optimal way to optimize?”. Third, an optimal randomness case study for a stochastic configuration network (SCN) machine-learning method with heavy-tailed distributions is discussed. Finally, views on big data and (physics-informed) machine learning with fractional dynamics for future research are presented with concluding remarks.     

Matrix Product State Simulations of Non-Equilibrium Steady States and Transient Heat Flows in the Two-Bath Spin-Boson Model at Finite Temperatures

Simulating the non-perturbative and non-Markovian dynamics of open quantum systems is a very challenging many body problem, due to the need to evolve both the system and its environments on an equal footing. Tensor network and matrix product states (MPS) have emerged as powerful tools for open system models, but the numerical resources required to treat finite-temperature environments grow extremely rapidly and limit their applications. In this study we use time-dependent variational evolution of MPS to explore the striking theory of Tamascelli et al. (Phys. Rev. Lett. 2019, 123, 090402.) that shows how finite-temperature open dynamics can be obtained from zero temperature, i.e., pure wave function, simulations. Using this approach, we produce a benchmark dataset for the dynamics of the Ohmic spin-boson model across a wide range of coupling strengths and temperatures, and also present a detailed analysis of the numerical costs of simulating non-equilibrium steady states, such as those emerging from the non-perturbative coupling of a qubit to baths at different temperatures. Despite ever-growing resource requirements, we find that converged non-perturbative results can be obtained, and we discuss a number of recent ideas and numerical techniques that should allow wide application of MPS to complex open quantum systems.     

Transient Dynamics in the Random Growth and Reset Model

A mean-field type model with random growth and reset terms is considered. The stationary distributions resulting from the corresponding master equation are relatively easy to obtain; however, for practical applications one also needs to know the convergence to stationarity. The present work contributes to this direction, studying the transient dynamics in the discrete version of the model by two different approaches. The first method is based on mathematical induction by the recursive integration of the coupled differential equations for the discrete states. The second method transforms the coupled ordinary differential equation system into a partial differential equation for the generating function. We derive analytical results for some important, practically interesting cases and discuss the obtained results for the transient dynamics.     

Spectral Properties of Effective Dynamics from Conditional Expectations

The reduction of high-dimensional systems to effective models on a smaller set of variables is an essential task in many areas of science. For stochastic dynamics governed by diffusion processes, a general procedure to find effective equations is the conditioning approach. In this paper, we are interested in the spectrum of the generator of the resulting effective dynamics, and how it compares to the spectrum of the full generator. We prove a new relative error bound in terms of the eigenfunction approximation error for reversible systems. We also present numerical examples indicating that, if Kramers–Moyal (KM) type approximations are used to compute the spectrum of the reduced generator, it seems largely insensitive to the time window used for the KM estimators. We analyze the implications of these observations for systems driven by underdamped Langevin dynamics, and show how meaningful effective dynamics can be defined in this setting.     

Experimental study of bubble dynamics in the neighbourhood of a vertical incomplete boundary

The bubbles have been widely used in biomedical field, military and chemical industry. The liquid jet generated by the bubble collapse through an orifice is utilized in needle-free injections and inkjet printing. In this paper we devised synchronized triggering equipment, experimentally investigated the mechanism in the interaction of an electric-spark generated a single bubble and a vertical wall with an air-back opening. Detailed observations were recorded and described for bubble oscillation, migration, jetting, as well as the high-speed water spike penetrating through the opening. The results revealed that there was a critical value of the bubble-wall distance, below which the bubble was directed away from the incomplete boundary, while the bubble may tear from the middle for larger distance. As the distance varied, we studied the volume of the water that rushed through the opening, the velocity at the tip of the water spike, and the center of the bubble as well as the migration of the bubble boundary. This work reveals that the high-speed water spike caused by the bubble may be a potential threat to the structures, specifically for cases with a small opening size and short bubble-boundary distance.     

Simulation and experiment of the cooling effect of trapped ion by pulsed laser

We investigate the process of pulsed laser cooling using a self-constructed molecular dynamics simulation(MDSimulation) program. We simulate the Doppler cooling process and pulsed laser Doppler cooling process of a single ~(40)Ca~+ ion, and the comparison with the experimental results shows that this self-constructed MD-Simulation program works well in the weak laser intensity situation. Furthermore, we analyze the pulsed laser Doppler cooling process of a single ~(27)Al~+ ion. This program can be used to analyze the molecular dynamic process of various situations of Doppler cooling in an ion trap, which could give predictions and experimental guidance.     

林火中的阴燃现象:研究前沿与展望

森林中的植物腐殖质和有机泥炭土的阴燃是地球上尺度最大的燃烧与火灾现象,造成了巨大的经济损失及跨国界的雾霾,并严重破坏了生态系统。本文综述了阴燃林火的基础燃烧理论和化学反应机理,总结了其点火、火蔓延和熄火的行为特性。同时,归纳了近年来泥炭阴燃火的研究动态,包括如何通过小尺度的阴燃实验理解大尺度的阴燃林火,如何构建阴燃的数值模型等关键科学问题。最后,探讨了阴燃林火问题在燃烧学、火灾科学、林学、生态环境学、地球物理等多学科的交叉研究热点和方向,以期对未来多学科的交叉研究提供必要的参考和科学指导。     

Notch fatigue of Cu_(50)Zr_(50) metallic glasses under cyclic loading: molecular dynamics simulations

Molecular dynamics simulation is performed to simulate the tension–compression fatigue of notched metallic glasses(MGs), and the notch effect of MGs is explored. The notches will accelerate the accumulation of shear transition zones, leading to faster shear banding around the notches' root causing it to undergo severe plastic deformation. Furthermore, a qualitative investigation of the notched MGs demonstrates that fatigue life gradually becomes shorter with the increase in sharpness until it reaches a critical scale. The fatigue performance of blunt notches is stronger than that of sharp notches. Making the notches blunter can improve the fatigue life of MGs.     

Insight into the chemomechanical coupling mechanism of kinesin molecular motors

Kinesin is a two-headed biological molecular motor that can walk processively on microtubule via consumption of ATP molecules. The central issue for the molecular motor is how the chemical energy released from ATP hydrolysis is converted to the kinetic energy of the mechanical motion, namely the mechanism of chemomechanical coupling. To address the issue, diverse experimental methods have been employed and a lot of models have been proposed. This review focuses on the proposed models as well as the qualitative and quantitative comparisons between the results derived from the models and those from the structural, biochemical and single-molecule experimental studies.