Numerical methods for the computation of mutli-component decompositions with spectroscopic applications

光谱应用多分量分解计算的数值方法

• 批准号: 214012032
• 负责人: Professor Dr. Klaus Neymeyr
• 金额: --
• 依托单位: Lehrstuhl für Numerische Mathematik und Approximationstheorie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/214012032?language=en
• 关键词: Numerical; methods; computation; mutli; component

The spectroscopic observation of chemical reactions with high frequency resolution and a large number of spectra results in a high volume of data. These spectral data contain the superposed contributions from the pure components. Factor analytic methods of chemometrics allow to extract from these data the number of underlying pure components, their spectra and the associated concentration profiles. New mathematical techniques and new numerical solution methods for the factor analysis of multicomponent systems are under development in the current funding period of the project. Whereas the so-called self-modeling factor analytic methods in chemometrics generally suggest only a single feasible pure component decomposition, our new systematic approach allows to compute the full set of all feasible solutions. Further methods have been developed in order to identify the correct pure component factorization for instance by coupling with a kinetic model of the reaction or by the new complementarity theory. The fast and stable numerical solvers have been published in the FAC-PACK software. Our work primarily aims at the development of chemometric methods but is also accompanied by a close cooperation with the Leibniz-Institute for Catalysis e.V. in Rostock. Spectroscopic data for various chemical reaction systems with the focus on transition metal catalyzed carbonylation reactions have been used for the validation of the numerical methods. Significant progress has been made for in-situ FT-IR studies on reaction systems of homogeneous catalysis.

化学反应的光谱观测具有高频率分辨率和大量光谱，数据量大。这些光谱数据包含纯组分的叠加贡献。化学计量学的因子分析方法允许从这些数据中提取潜在的纯组分的数量，它们的光谱和相关的浓度分布。在本项目供资期间，正在为多组分体系的因素分析开发新的数学技术和新的数值求解方法。 而所谓的自建模因子分析方法在化学计量学一般只建议一个单一的可行的纯组分分解，我们的新的系统方法允许计算所有可行的解决方案的完整集合。为了确定正确的纯组分因子分解，已经开发了进一步的方法，例如通过与反应的动力学模型耦合或通过新的互补理论。该快速稳定的数值求解器已在FAC-PACK软件中发布。我们的工作主要旨在开发化学计量学方法，但也与罗斯托克的莱布尼茨催化研究所密切合作。各种化学反应体系的光谱数据，重点是过渡金属催化的羰基化反应已被用于验证的数值方法。均相催化反应体系的原位红外光谱研究已取得重要进展。

项目成果

Simultaneous construction of dual Borgen plots. II: Algorithmic enhancement for applications to noisy spectral data

同时构建双 Borgen 图 II：噪声光谱数据应用的算法增强

• DOI: 10.1002/cem.3012
• 发表时间: 2018
• 期刊: Journal of Chemometrics
• 影响因子: 2.4
• 作者: M. Sawall;A. Moog;C. Kubis;H. Schröder;D. Selent;R. Franke;A. Brächer;A. Börner;K. Neymeyr
• 通讯作者: K. Neymeyr

A ray casting method for the computation of the area of feasible solutions for multicomponent systems: Theory, applications and FACPACK-implementation.

用于计算多组分系统可行解面积的射线投射方法：理论、应用和 FACPACK 实现

• DOI: 10.1016/j.aca.2016.11.069
• 发表时间: 2017
• 期刊: Analytica chimica acta
• 影响因子: 6.2
• 作者: M. Sawall;K. Neymeyr
• 通讯作者: K. Neymeyr

Simultaneous construction of dual Borgen plots. I: The case of noise‐free data

同时构建双 Borgen 图 I：无噪声数据的情况

• DOI: 10.1002/cem.2954
• 发表时间: 2017
• 期刊: Journal of Chemometrics
• 影响因子: 2.4
• 作者: M. Sawall;A. Jürß;H. Schröder;K. Neymeyr
• 通讯作者: K. Neymeyr

Analysis of the ambiguity in the determination of quantum yields from spectral data on a photoinduced isomerization

光致异构化光谱数据测定量子产率的模糊性分析

• DOI: 10.1016/j.chemolab.2019.03.013
• 发表时间: 2019
• 期刊: Chemometrics and Intelligent Laboratory Systems
• 影响因子: 3.9
• 作者: H. Schröder;C. Ruckebusch;O. Devos;R. Metivier;M. Sawall;D. Meinhardt;K. Neymeyr
• 通讯作者: K. Neymeyr