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Biosensing under Surface Plasmon Resonance Conditions
Published in Klaus D. Sattler, st Century Nanoscience – A Handbook, 2020
In classical cases, the above examined adsorption processes that are uniform in the surface plane with their uniformity quite often observed in experiment are no less frequently disrupted. The differences from classical behavior, often observed in practice, lead to a series of kinetic relationships, which is not surprising from this standpoint (Martinez et al. 2009, Minton 2001, Snopok 2014). The simplest case is concentration depletion processes occurring in a closed system with no access to reagents. More complex models take into account the nonuniformity of the analyte flow toward the surface, the differences in the bonding constants for the surface sites, the multivalent bonding, the effects of the geometric surface blockage, the change in the structure of the analyte after bonding, etc. Numerical models can be illustrated by various versions of random or cooperative sequential adsorption (random sequential adsorption, RSA) (Evans 1993), etc. All these models illustrate some specific aspects of the nonuniform adsorption process, when the driving forces of particle motion are modeled by a single dedicated mechanism. An increasing number of processes in a more and more advanced phenomenological model leads to the fact that an initially simple and clear situation turns into an evolving reaction space with a huge number of parameters. The microscopic dynamics of the analyte under these conditions is so complex that it is not possible to describe the features of a single particle trajectory or the kinetic behavior of their ensemble as a whole in terms of some deterministic mathematical formalism.
Motion characteristics and residence time of particles in the new cross structure under constant-pulse condition
Published in Numerical Heat Transfer, Part A: Applications, 2023
Shuyu Su, Yuan Xi, Yan Dai, Hongjing Liu, Hanli Wang
While there have been many reports of experimental and numerical studies on improving agglomeration efficiency through turbulent agglomeration, there has been surprisingly little investigation into the relationship between the structure of the reactor and the residence time, and data on optimal operating conditions is also lacking. A CFD-DEM model was employed to study the single particle motion behavior under the condition of three kinds SIS, asymmetric impinging streams (AIS), and CP. We propose constant and pulse-coupled dynamic inlet flow and a novel cross-type structure. Therefore, the purpose of this article is to investigate the effects of particle motion and residence time in a novel cross-type structure under constant-pulse conditions, focusing on the influences of inflow conditions, reactor geometric model, and particle residence times on local flow behaviors and single particle trajectory.
Thermophysical properties of low-density polystyrene under extreme conditions using ReaxFF molecular dynamics
Published in Molecular Physics, 2021
Yu Cao, Yanyun Chu, Zhen Wang, Jianmin Qi, Lin Zhou, Zhenghong Li
The mean-square displacement (MSD) is widely used to characterise the dynamical properties in experiments, theories, and simulations [48–50]. In particular, it is suited to analyse the particles diffusion transport properties. The MSD can be observed by following the single-particle trajectory in a simulated system. When the system achieves the thermal equilibrium, the average squared displacement can be obtained by equation (5): Where τ denotes the total simulation time, and r(t) means the position of a particle at the moment of t. The mean-square displacement (MSD) curves as a function of simulation time are shown in Figure 8(a). MSD value shows the linear increase trend and is influenced by the temperature. The slope of the MSD curve closely related to the diffusion coefficient of molecules and increases as the temperature rises. The slope of MSD curve defines the (self) diffusion coefficient D according to the Einstein equation:
Sequential linear programming and particle swarm optimization for the optimization of energy districts
Published in Engineering Optimization, 2019
Elisa Riccietti, Stefania Bellavia, Stefano Sello
These methods are heuristic and standard convergence results. Similarly to those proved for exact optimization methods, they are not usually provided. However, a different kind on analysis of the algorithm can be performed. Using results from dynamic system theory, it is possible to provide an understanding about how the swarm searches the problem space through the analysis of a single particle trajectory or of the swarm seen as a stochastic system (Trelea 2003; Clerc and Kennedy 2002). The analysis provides useful guidelines for the choice of the free parameters to control the system's convergence tendencies.