Bayesian uncertainty quantification in inverse modeling of electrochemical systems

This present study proposes a novel approach to quantifying uncertainties of constitutive relations inferred from noisy experimental data using inverse modeling. We focus on electrochemical systems in which charged species (e.g., Lithium ions) are transported in electrolyte solutions under an applied current. Such systems are typically described by the Planck-Nernst equation in which the unknown material properties are the diffusion coefficient and the transference number assumed constant or concentration-dependent. These material properties can be optimally reconstructed from time- and space-resolved concentration profiles measured during experiments using the magnetic resonance imaging (MRI) technique. However, as the measurement data is usually noisy, it is important to quantify how the presence of noise affects the uncertainty of the reconstructed material properties. We address this problem by developing a state-of-the-art Bayesian approach to uncertainty quantification in which the reconstructed material properties are recast in terms of probability distributions, allowing us to rigorously determine suitable confidence intervals. The proposed approach is first thoroughly validated using “manufactured” data exhibiting the expected behavior as the magnitude of noise is varied. Then, this approach is applied to quantify the uncertainty of the diffusion coefficient and the transference number reconstructed from experimental data revealing interesting insights. © 2018 Wiley Periodicals, Inc.     

Acuchem: A computer program for modeling complex chemical reaction systems

Acuchem is a program for solving the system of differential equations describing the temporal behavior of spatially homogeneous, isothermal, multicomponent chemical reaction systems. It is designed to provide modelers, data evaluators, and laboratory scientists with an easy to use program for modeling complex chemical reactions, and for presenting the results in tabular or graphical form. The program is described and some examples of its application given. Acuchem is designed to operate on the IBM Personal Computer family and other compatible microcomputers, and is available in a compiled version on a floppy disk.     

Measurement uncertainty and chemical analysis

The author considers issues covered by A.B. Blank in his letter “Uncertainty in Measurements and Chemical Analysis” published in Zhurnal Analiticheskoi Khimii in 2005 (vol. 60, no. 12, p. 1316). It is noted that the negative attitude towards the introduction of the measurement uncertainty concept is to a great extent due to the incorrect translation of the term “uncertainty” as “pogreshnost’” (error) in the guides published in Russian earlier. It is shown that the estimation of uncertainty, which combines both random and so-called “systematic” error components, is consistent with the structure of the error of measurements (determinations) made by following specified procedures. Reporting of the results together with their uncertainties is necessary for the proper interpretation of the experimental data; this reflects current trends in the analytical quality assurance based on metrological principles.     

Introduction to measurement uncertainty in chemical analysis

 This paper reviews the experience of the use of the Eurachem Guide and gives a brief overview of the principles of evaluating uncertainty. This is followed by discussion of the comments received on the Guide and highlights some of the issues that need to be considered in the next version. Accepted: 21 October 1997     

Quantifying chemical composition from two-dimensional data arrays

Many analytical instruments (e.g., videofluorimeter and liquid chromatographs with spectrometric detectors) can produce two-dimensional data arrays. Rank-annihilation factor analysis enables chemical composition to be quantified from such an array. Solution by this method requires a search for a minimum value of an eigenvector which cannot be calculated even iteratively. The problem is presented here as a generalized eigenvalue problem and a direct solution is found by using singular value decomposition.     

Quantifying the measurement uncertainty of results from environmental analytical methods

The Eurachem-CITAC Guide Quantifying Uncertainty in Analytical Measurement was put into practice in a public laboratory devoted to environmental analytical measurements. In doing so due regard was given to the provisions of ISO 17025 and an attempt was made to base the entire estimation of measurement uncertainty on available data from the literature or from previously performed validation studies. Most environmental analytical procedures laid down in national or international standards are the result of cooperative efforts and put into effect as part of a compromise between all parties involved, public and private, that also encompasses environmental standards and statutory limits. Central to many procedures is the focus on the measurement of environmental effects rather than on individual chemical species. In this situation it is particularly important to understand the measurement process well enough to produce a realistic uncertainty statement. Environmental analytical methods will be examined as far as necessary, but reference will also be made to analytical methods in general and to physical measurement methods where appropriate. This paper describes ways and means of quantifying uncertainty for frequently practised methods of environmental analysis. It will be shown that operationally defined measurands are no obstacle to the estimation process as described in the Eurachem/CITAC Guide if it is accepted that the dominating component of uncertainty comes from the actual practice of the method as a reproducibility standard deviation.     

Quantifying the measurement uncertainty of results from environmental analytical methods

The Eurachem–CITAC Guide Quantifying Uncertainty in Analytical Measurement was put into practice in a public laboratory devoted to environmental analytical measurements. In doing so due regard was given to the provisions of ISO 17025 and an attempt was made to base the entire estimation of measurement uncertainty on available data from the literature or from previously performed validation studies. Most environmental analytical procedures laid down in national or international standards are the result of cooperative efforts and put into effect as part of a compromise between all parties involved, public and private, that also encompasses environmental standards and statutory limits. Central to many procedures is the focus on the measurement of environmental effects rather than on individual chemical species. In this situation it is particularly important to understand the measurement process well enough to produce a realistic uncertainty statement. Environmental analytical methods will be examined as far as necessary, but reference will also be made to analytical methods in general and to physical measurement methods where appropriate. This paper describes ways and means of quantifying uncertainty for frequently practised methods of environmental analysis. It will be shown that operationally defined measurands are no obstacle to the estimation process as described in the Eurachem/CITAC Guide if it is accepted that the dominating component of uncertainty comes from the actual practice of the method as a reproducibility standard deviation.     

Quantifying uncertainty in determination of polysaccharides in glycoconjugate vaccines based on in-house validation data

The measurement uncertainty in quantifying polysaccharides in glycoconjugate vaccines was estimated in order to ascertain compliance of these products in the batch release procedure of an Official Medicines Control Laboratory. A single-laboratory validation approach of an internal analytical procedure to quantify the total saccharide by the way of the sialic acid (N-Acetylneuraminic acid) concentration in a meningococcal glycoconjugate vaccine by High Performance Anion Exchange Chromatography coupled with Pulsed Amperometric Detection is reported. Uncertainty components from precision, bias and other sources were evaluated. It turned out that uncertainty is dominated by the precision contribution, while bias was mainly due to the non-recovery from hydrolysis. As a consequence, a correction factor was considered. At a confidence level of approximately 95%, the expanded uncertainty of the total polysaccharide concentration in a vaccine, when measured using the internal method, was found to be 11.5%.     

量子化学模型方法在机械力化学中的应用

机械力化学作为一种无需溶剂的绿色化学技术得到广泛关注。然而,机械力化学反应机制需要从原子和分子尺度上深入理解力诱导的化学反应。在过去的20年中,量子化学模型方法在机械力化学机理研究中得到广泛应用,高精度量化计算可得到外力下变形分子的几何结构、能量、过渡态等诸多性质。本文介绍了目前机械力化学领域的主流量子化学模型的基本原理,同时也关注了这些模型方法在软件上的具体实现,并借助典型的案例阐述了量子化学模型在解释机械力化学机理中的作用与价值。     

Nonoscillation in closed reversible chemical systems

For a closed reversible chemical system obeying mass action kinetics, we prove that structurally stable closed orbits do not exist if there are no more reaction steps than reactants. We derive this using an appropriate Lyapunov function for a special case in which the number of reaction steps equals the number of reactants and a stationary point is shown to be unique and asymptotically stable.     

Tracking chemical kinetics in high-throughput systems

Combinatorial chemistry and high‐throughput experimentation (HTE) have revolutionized the pharmaceutical industry—but can chemists truly repeat this success in the fields of catalysis and materials science? We propose to bridge the traditional “discovery” and “optimization” stages in HTE by enabling parallel kinetic analysis of an array of chemical reactions. We present here the theoretical basis to extract concentration profiles from reaction arrays and derive the optimal criteria to follow (pseudo)first‐order reactions in time in parallel systems. We use the information vector f and introduce in this context the information gain ratio, χ_r, to quantify the amount of useful information that can be obtained by measuring the extent of a specified reaction r in the array at any given time. Our method is general and independent of the analysis technique, but it is more effective if the analysis is performed on‐line. The feasibility of this new approach is demonstrated in the fast kinetic analysis of the carbon–sulfur coupling between 3‐chlorophenylhydrazonopropane dinitrile and β‐mercaptoethanol. The theory agrees well with the results obtained from 31 repeated C? S coupling experiments.