Reaction analysis and visualization of ReaxFF molecular dynamics simulations

ReaxFF MD (Reactive Force Field Molecular Dynamics) is a promising method for investigating complex chemical reactions in relatively larger scale molecular systems. The existing analysis tools for ReaxFF MD lack the capability of capturing chemical reactions directly by analyzing the simulation trajectory, which is critical in exploring reaction mechanisms. This paper presents the algorithms, implementation strategies, features, and applications of VARxMD, a tool for Visualization and Analysis of Reactive Molecular Dynamics. VARxMD is dedicated to detailed chemical reaction analysis and visualization from the trajectories obtained in ReaxFF MD simulations. The interrelationships among the atoms, bonds, fragments, species and reactions are analyzed directly from the three-dimensional (3D) coordinates and bond orders of the atoms in a trajectory, which are accomplished by determination of atomic connectivity for recognizing connected molecular fragments, perception of bond types in the connected fragments for molecules or radicals, indexing of all these molecules or radicals (chemical species) based on their 3D coordinates and recognition of bond breaking or forming in the chemical species for reactions. Consequently, detailed chemical reactions taking place between two sampled frames can be generated automatically. VARxMD is the first tool specialized for reaction analysis and visualization in ReaxFF MD simulations. Applications of VARxMD in ReaxFF MD simulations of coal and HDPE (high-density polyethylene) pyrolysis show that VARxMD provides the capabilities in exploring the reaction mechanism in large systems with complex chemical reactions involved that are difficult to access manually.     

基于遗传算法的化学反应动力学模型简化法

从化学的详细基元反应出发,通过分析化学反应过程和灵敏度,识别反应过程中的"主干"反应,建立起具有基元反应形式的简化反应动力学模型,再采用遗传算法来优化调整基元反应阿累尼乌斯(Arrehnius)公式中的系数,使简化模型的计算精度尽可能与详细基元反应模型相当,从而建立一种简化化学反应动力学模型的新方法。通过分析典型甲烷点火燃烧算例的初步计算表明,该方法的应用前景较好。     

Efficient calculation of intrinsic low-dimensional manifolds for the simplification of chemical kinetics

During the last years the interest in the numerical simulation of reacting flows has grown considerably and numerical methods are available, which allow to couple chemical kinetics with flow and molecular transport. The use of detailed physical and chemical models, involving several hundred species, is restricted to very simple flow configurations like one-dimensional systems or two-dimensional systems with very simple geometries, and models are required, which simplify chemistry without sacrificing accuracy. One method to simplify the chemical kinetics is based on Intrinsic Low-Dimensional Manifolds (ILDM). They represent attractors for the chemical kinetics, i.e. fast chemical processes relax towards them, and slow chemical processes represent movements within the manifolds. Thus the identification of the ILDMs allows a decoupling of the fast time scales. The concept has been verified by many different reacting flow calculations. However, one remaining problem of the method is the efficient calculation of the low-dimensional manifolds. This problem is addressed in this paper. We present an efficient, robust method, which allows to calculate intrinsic low-dimensional manifolds of chemical reaction systems. It is based on a multi-dimensional continuation process. Examples are shown for a typical combustion system. The method is not restricted to this problem class, but can be applied to other reacting flows or dynamic systems provided that a large number of decaying components can be eliminated from the system. Received: 5 May 1996 / Accepted: 2 September 1997     

Prevention of work‐related musculoskeletal disorders in a chemical plant in Taiwan and a comparison of three assessment tools

Work‐related musculoskeletal disorders (WMSDs) caused by a poor working environment or an improper work design are the most common occupational diseases seriously affecting workers’ health, causing huge economic losses in many countries. Thus, the prevention of WMSDs is considered a priority issue worldwide. In this study, three ergonomics analysis tools and a statistic analysis were used to assess the risk level of exposure to WMSDs and to find improvements for the operations in a chemical plant. The applicability of these tools was also evaluated. Results of the analysis suggest that, to greatly prevent the incidence of WMSDs, a mobile elevating platform should be adopted to adjust the handling height of material bags at 90 cm, allowing the operators to stand in front of them to hold their short or long sides. Among the tools, key indicator methods–manual handling operation methods (KIM‐MHO) have the highest sensitivity.     

一类缩聚反应过程的分子量分布模型

以一个工业化聚酯生产过程为例,将反应度法和生成函作为工具,建立了描述此类缩聚反应过程的反应动力不冢其分子量分布的数学模型,并介绍了求解数学模型的方法。     

Calculation of constrained equilibria by Gibbs energy minimization

The Gibbs energy minimization encompasses active use of the chemical potentials (partial molar Gibbs energies) of the constituents of the system. Usually, these appear at their equilibrium values as a result of the minimization calculation, the mass balance constraints being the necessary subsidiary conditions. Yet, there are several such physico-chemical circumstances where the system is also constrained by other factors, such as surface effects, potential fields or even by chemical reaction kinetics. In this paper a particular method is presented by which constrained chemical potentials can be applied in a multi-phase Gibbs energy minimization. The constrained potentials arise typically from work-related thermodynamic displacements in the system. When Gibbs energy minimization is performed by the Lagrange method, these constraints appear as additional Lagrangian multipliers. Examples of the constrained potential method are presented in terms of the electrochemical Donnan equilibria in aqueous systems containing semi-permeable interfaces, the phase formation in surface-energy controlled systems and in systems with affinities controlled by chemical reaction kinetics. The methods have been applied successfully in calculating distribution coefficients for metal ions together with pH-values in pulp suspensions, in the calculation of surface tension of alloys, and in thermochemical process modeling involving chemical reaction rates.     

Model complexity reduction of chemical reaction networks using mixed-integer quadratic programming

The model complexity reduction problem of large chemical reaction networks under isobaric and isothermal conditions is considered. With a given detailed kinetic mechanism and measured data of the key species over a finite time horizon, the complexity reduction is formulated in the form of a mixed-integer quadratic optimization problem where the objective function is derived from the parametric sensitivity matrix. The proposed method sequentially eliminates reactions from the mechanism and simultaneously tunes the remaining parameters until the pre-specified tolerance limit in the species concentration space is reached. The computational efficiency and numerical stability of the optimization are improved by a pre-reduction step followed by suitable scaling and initial conditioning of the Hessian involved. The proposed complexity reduction method is illustrated using three well-known case studies taken from reaction kinetics literature.     

On the Relevance of Diffusion-Controlled Reactions for Understanding Living Cell Biochemistry

In recent years, a considerable portion of the computer science community has focused its attention on studying the living cell biochemistry. Efforts to understand such complicated reaction environments have stimulated a range of activities, from the ones focusing on the systems biology techniques, through network analysis (motif identification), towards developing languages and simulations for low-level biochemical processes. The approaches that do not use computer simulation techniques, frequently employ mean field equations or, equivalently, classical chemical kinetics. The central quantity of interest is the concentration of reactants, and (mean field) equations describe the time evolution of this quantity. Such equations are used to address various issues among which stability, robustness, or sensitivity analysis. Rarely is the validity of mean field equations questioned. This paper will discuss various situations when mean field equations fail and should not be used. These equations can be derived from the more general theory of diffusion-controlled reactions by assuming that reactants mix well.     

A network dynamics approach to chemical reaction networks

A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a ‘zero’ complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.     

PumpKin: A tool to find principal pathways in plasma chemical models

PumpKin is a software package to find all principal pathways, i.e. the dominant reaction sequences, in chemical reaction systems. Although many tools are available to integrate numerically arbitrarily complex chemical reaction systems, few tools exist in order to analyze the results and interpret them in relatively simple terms. In particular, due to the large disparity in the lifetimes of the interacting components, it is often useful to group reactions into pathways that recycle the fastest species. This allows a researcher to focus on the slow chemical dynamics, eliminating the shortest timescales. Based on the algorithm described by Lehmann (2004), PumpKin automates the process of finding such pathways, allowing the user to analyze complex kinetics and to understand the consumption and production of a certain species of interest. We designed PumpKin with an emphasis on plasma chemical systems but it can also be applied to atmospheric modeling and to industrial applications such as plasma medicine and plasma-assisted combustion.     

Physical modeling of biomolecular computers: Models,limitations, and experimental validation

A principal challenge facing the development and scaling of biomolecular computers is the design of physically well-motivated, experimentally validated simulation tools. In particular, accurate simulations of computational behavior are needed to establish the feasibility of new architectures, and to guide process implementation, by aiding strand design. Key issues accompanying simulator development include model selection, determination of appropriate level of chemical detail, and experimental validation. In this work, each of these issues is discussed in detail, as presented at the workshop on simulation tools for biomolecular computers (SIMBMC), held at the 2003 Congress on Evolutionary Computation. The three major physical models commonly applied to model biomolecular processes, namely molecular mechanics, chemical kinetics, and statistical thermodynamics, are compared and contrasted, with a focus on the potential of each to simulate various aspects of biomolecular computers. The fundamental and practical limitations of each approach are considered, along with a discussion of appropriate chemical detail, at the biopolymer, process, and system levels. The relationship between system analysis and design is addressed, and formalized via the DNA Strand Design problem (DSD). Finally, the need for experimental validation of both underlying parameter sets and overall predictions is discussed, along with illustrative examples.Authors contributed equally to the present work.     

Analysing the novice analyst: cognitive models in software engineering

Cognitive problem-solving by novice systems analysts during a requirements analysis task was investigated by protocol analysis. Protocols were collected from 13 subjects who analysed a scheduling problem. Reasoning, planning, conceptual modelling and information gathering behaviours were recorded and subject's solutions were evaluated for completeness and accuracy. The protocols showed an initial problem scoping phase followed by more detailed reasoning. Performance in analysis was not linked to any one factor although reasoning was correlated with success. Poor performance could be ascribed to failure to scope the problem, poor formation of a conceptual model of the problem domain, or insufficient testing of hypotheses. Good performance concorded with well-formed conceptual models and good reasoning/testing abilities. The implication of these results for structured systems development methods and Computer-Aided Software Engineering (CASE) tools are discussed.     

Computerised approaches for the detection of diabetic retinopathy using retinal fundus images: a survey

Eye-related disease such as diabetic retinopathy (DR) is a medical ailment in which the retina of the human eye is smashed because of damage to the tiny retinal blood vessels in the retina. Ophthalmologists identify DR based on various features such as the blood vessels, textures and pathologies. With the rapid development of methods of analysis of biomedical images and advanced computing techniques, image processing-based software for the detection of eye disease has been widely used as an important tool by ophthalmologists. In particular, computer vision-based methods are growing rapidly in the field of medical images analysis and are appropriate to advance ophthalmology. These tools depend entirely on visual analysis to identify abnormalities in Retinal Fundus images. During the past two decades, exciting improvement in the development of DR detection computerised systems has been observed. This paper reviews the development of analysing retinal images for the detection of DR in three aspects: automatic algorithms (classification or pixel to pixel methods), detection methods of pathologies from retinal fundus images, and extraction of blood vessels of retinal fundus image algorithms for the detection of DR. The paper presents a detailed explanation of each problem with respect to retinal images. The current techniques that are used to analyse retinal images and DR detection issues are also discussed in detail and recommendations are made for some future directions.     

化学工程中的计算流体力学

本文评述了计算流体力学在化学化工研究和开发中的重要地位,介绍了各种模拟方法研究的现状、存在的困难和一些发展中的前沿领域。与传统应用领域相比,化学工程领域主要面对的是复杂多相流体系统及流动、传递和反应相耦合的过程,基于单尺度统计平均的传统连续介质方法已很难满足对产品结构和过程工艺精确设计的要求,而多尺度方法与粒子方法的结合是一条有效的途径。它通过对复杂系统满足的稳定性条件的分析以及对复杂界面和间断性的合理描述实现跨尺度关联的模拟,从而量化介观结构与行为、建立准确的宏观模型。这种结合无论是对湍流、汽液或气固多相流等传统的难题,还是对微流动、生物流、聚合物流动、颗粒流及散料力学等前沿领域,都带来了新的可能性,也将为化学化工领域的研发工作提供更有力的手段。     

用计算奇异值摄动方法简化复杂化学反应动力学模型

介绍了用于简化化学反应动力模型的计算奇异值摄动方法(CSP),给出了其基本思想与具体计算方法,然后用该方法来对一氧化碳／氢气在空气中燃烧的化学反应、激波管中甲烷的点火燃烧反应实例进行了简化。从计算结果看,CSP方法是一种比较有效的化学反应模型简化方法,用该方法简化得出的简化模型不仅减少了微分求解的组分数目,而且保持了较高的计算精度,能有效提高计算效率,具有较强的工程实际价值。     

浆态床合成二甲醚宏观动力学模拟

采用宏观动力学,对以合成气为原料的浆态床液相法合成二甲醚反应进行模拟研究,通过物料恒算建立一组常微分方程组,计算过程采用四阶精度的Runge-Kutta法并结合C++编程求解.通过模拟计算,讨论了压力、温度、空速、催化剂浓度、CO2浓度对反应转化率、收率以及DME的选择性的影响,从而寻找合适的反应器参数,为实际的工业生产提供参考.     

Modeling of chemical kinetics in gases

Some temperature dependences of reaction rate constants have been derived from the laws of quantum mechanics. Chemical reference data have been revealed to be usually dissatisfied with these laws. It is shown how similar reference data should be corrected. The constants for the kinetics of hydrogen combustion in oxygen are corrected as an example. A specialized method for the numerical solution of chemical kinetics problems has been developed. It represents an explicit algorithm, which appreciably surpasses the known methods in simplicity, precision, and robustness.     

Kinetic feedback design for polynomial systems

New computational methods are proposed in this paper to construct polynomial feedback controllers for the stabilization of polynomial systems with linear input structure around a positive equilibrium point. Using the theory of chemical reaction networks (CRNs) and previous results on dynamical equivalence, a complex balanced or weakly reversible zero deficiency closed loop realization is achieved by computing the gain matrix of a polynomial feedback using optimization. It is shown that the feedback resulting in a complex balanced closed loop system having a prescribed equilibrium point can be computed using linear programming (LP). The robust version of the problem, when a convex set of polynomial systems is given over which a stabilizing controller is searched for, is also solvable with an LP solver. The feedback computation for rendering a polynomial system to deficiency zero weakly reversible form can be solved in the mixed integer linear programming (MILP) framework. It is also shown that involving new monomials (complexes) into the feedback does not improve the solvability of the problems. The proposed methods and tools are illustrated on simple examples, including stabilizing an open chemical reaction network.