Use of Bayesian inference for parameter recovery in DC and AC voltammetry

We describe the use of Bayesian inference for quantitative comparison of voltammetric methods for investigating electrode kinetics. We illustrate the utility of the approach by comparing the information content in both DC and AC voltammetry at a planar electrode for the case of a quasi-reversible one electron reaction mechanism. Using synthetic data (i. e. simulated data based on Butler-Volmer electrode kinetics for which the true parameter values are known and to which realistic levels of simulated experimental noise have been added), we are able to show that AC voltammetry is less affected by experimental noise (so that in effect it has a greater information content then the corresponding DC measurement) and hence yields more accurate estimates of the experimental parameters for a given level of noise. Significantly, the AC approach is shown to be able to distinguish higher values of the rate constant. The results of using synthetic data are then confirmed for an illustrative case of experimental data for the [Fe(CN)6]3−/4−process

Vacuum compatible flow-cell for high-quality in situ and operando soft X-ray photon-in–photon-out spectroelectrochemical studies of energy materials

Abstract: Soft X‐ray spectroscopy is a powerful method to investigate materials on an element selective level with respect to their atomic and electronic structure. However, its application is technically challenging for in situ or operando investigations of materials for electrochemical applications. Herein, we present a spectroelectrochemical flow‐cell designed to enable state‐of‐the‐art electrochemical characterization while being installed in a vacuum chamber for the direct accessibility of the electroactive sample to soft X‐rays. An overview of the application of soft X‐ray photon‐in–photon‐out spectroscopic studies to electromaterials is provided, along with discussions of experimental and technical considerations specific to this highly sensitive mode of analysis. Application of the cell for the in situ spectroelectrochemical characterization of an electrodeposited nickel oxide water electrooxidation catalyst is demonstrated

A Strategic Thinking of the Issues in Cost Management of FB Real Estate Company

摘要 论文结合FB房地产公司开发项目遇到的主要问题：如何选择项目开发的成本管理战略以获取成本竞争优势？成本管理效果不佳的问题：如成本核算数据不准确不能及时反映项目产品的成本状况、项目开发预算与实际支出差异大、产品的成本与利润不清楚、项目间成本不可比、成本管理不能及时对市场变化进行调整和企业利润被侵蚀的成本失控问题如何解决？怎么对异地项目开发进行成本控制及风险管理？怎样创新管理针对房地产成本管理的疑难问题展开战略分析研究，通过对解决问题的相关因素分析得出解决方案，在某项目开发中进行应用取得成功以验证其可行性。 论文以某项目开发针对成本管理中存在的疑难问题，以企业成本战略管理方法的“五力分析法...Abstract This article is mainly focused on the following topics of FB Real Estate Company: how to obtain the competitive advantage of project management by carrying on effective cost management strategies? How to change the situation of ineffective cost management, such as the data can't reflect the cost of the project accurately and there is a huge gap between the project's budget and actual...学位：工商管理硕士院系专业：管理学院高级经理教育中心（EMBA项目）_高级管理人员工商管理硕士(EMBA)学号：X200715612

Mermaid 3D code in ATLAS applications

The paper describes the new periodic boundary condition model of ATLAS detector and changes in the Mermaid 3D code algorithms necessary to calculate it. The parallel processing modification of the Mermaid code to perform the complete Atlas model calculation is presented in comparison with this 1:10 model of the fine TileCal structure

Separating the effects of experimental noise from inherent system variability in voltammetry: The [Fe(CN)6]3–/4– Process

Recently, we introduced the use of techniques drawn from Bayesian statistics to recover kinetic and thermodynamic parameters from voltammetric data and were able to show that the technique of large amplitude ac voltammetry yielded significantly more accurate parameter values than the equivalent dc approach. In this paper, we build on this work to show that this approach allows us, for the first time, to separate the effects of random experimental noise and inherent system variability in voltammetric experiments. We analyze ten repeated experimental data sets for the [Fe(CN)6] 3−/4− process, again using large-amplitude ac cyclic voltammetry. In each of the ten cases, we obtain an extremely good fit to the experimental data and obtain very narrow distributions of the recovered parameters governing both the faradaic (the reversible formal potential, E0, the standard heterogeneous charge transfer rate constant, k0, and the charge transfer coefficient, α) and nonfaradaic terms (uncompensated resistance, Ru, and double layer capacitance, Cdl). We then employ hierarchical Bayesian methods to recover the underlying “hyperdistribution” of the faradaic and nonfaradaic parameters, showing that in general the variation between the experimental data sets is significantly greater than suggested by individual experiments, except for α where the interexperiment variation was relatively minor. Correlations between pairs of parameters are provided, and for example, reveal a weak link between k0 and Cdl (surface activity of a glassy carbon electrode surface). Finally, we discuss the implications of our findings for voltammetric experiments more generally

Use of Bayesian Inference for Parameter Recovery in DC and AC Voltammetry

We describe the use of Bayesian inference for quantitative comparison of voltammetric methods for investigating electrode kinetics. We illustrate the utility of the approach by comparing the information content in both DC and AC voltammetry at a planar electrode for the case of a quasi-reversible one electron reaction mechanism. Using synthetic data (i. e. simulated data based on Butler-Volmer electrode kinetics for which the true parameter values are known and to which realistic levels of simulated experimental noise have been added), we are able to show that AC voltammetry is less affected by experimental noise (so that in effect it has a greater information content then the corresponding DC measurement) and hence yields more accurate estimates of the experimental parameters for a given level of noise. Significantly, the AC approach is shown to be able to distinguish higher values of the rate constant. The results of using synthetic data are then confirmed for an illustrative case of experimental data for the [Fe(CN)6]3−/4− process

Probing Electron Transfer in the Manganese-Oxide-Forming MnxEFG Protein Complex using Fourier Transformed AC Voltammetry: Understanding the Oxidative Priming Effect

MnxG, a multicopper oxidase, is an enzyme from the marine Bacillus species, which produces manganese oxide minerals through the aerobic oxidation of dissolved Mn − a key process in global manganese geochemical cycling. When isolated in an active form as a part of the MnxEFG protein complex, the enzymatic activity of MnxG is substantially enhanced by mild oxidative priming. Herein, the mechanism for this effect is probed by using direct current (dc) and Fourier transformed alternating current (ac) voltammetric analysis of the MnxEFG complex and the catalytically inactive MnxEF subunit immobilised on a carbon electrode. Analysis of these ac voltammetric data reveals a significant enhancement in the rate of electron transfer in the Type 2 Cu sites upon oxidative priming of the enzyme, which is attributed to the improved catalytic activity of MnxG in the MnxEFG protein complex. 2

Use of Bayesian inference for parameter recovery in DC and AC voltammetry

We describe the use of Bayesian inference for quantitative comparison of voltammetric methods for investigating electrode kinetics. We illustrate the utility of the approach by comparing the information content in both DC and AC voltammetry at a planar electrode for the case of a quasi-reversible one electron reaction mechanism. Using synthetic data (i. e. simulated data based on Butler-Volmer electrode kinetics for which the true parameter values are known and to which realistic levels of simulated experimental noise have been added), we are able to show that AC voltammetry is less affected by experimental noise (so that in effect it has a greater information content then the corresponding DC measurement) and hence yields more accurate estimates of the experimental parameters for a given level of noise. Significantly, the AC approach is shown to be able to distinguish higher values of the rate constant. The results of using synthetic data are then confirmed for an illustrative case of experimental data for the [Fe(CN)6]3−/4−process

Use of Bayesian inference for parameter recovery in DC and AC voltammetry

We describe the use of Bayesian inference for quantitative comparison of voltammetric methods for investigating electrode kinetics. We illustrate the utility of the approach by comparing the information content in both DC and AC voltammetry at a planar electrode for the case of a quasi-reversible one electron reaction mechanism. Using synthetic data (i. e. simulated data based on Butler-Volmer electrode kinetics for which the true parameter values are known and to which realistic levels of simulated experimental noise have been added), we are able to show that AC voltammetry is less affected by experimental noise (so that in effect it has a greater information content then the corresponding DC measurement) and hence yields more accurate estimates of the experimental parameters for a given level of noise. Significantly, the AC approach is shown to be able to distinguish higher values of the rate constant. The results of using synthetic data are then confirmed for an illustrative case of experimental data for the [Fe(CN)6]3−/4−process