Chemistry methods : new approaches to solving problems in chemistry最新文献

The analysis of spectral data, and in particular the quantification of these, highly depends on curve fitting the spectra with suitable methods. The required methodologies have been known for very long. However, even today it is a regular problem that this, i.e. physically correct analyzing spectral data, is not practiced.

An automated flow micropacked bed catalytic reactor platform was developed to conduct pre-planned experiments for rapid screening of kinetic models. The microreactor was fabricated using photolithography and deep reactive ion etching of a silicon wafer, with a reaction channel width and depth of 2 mm and 420 μm respectively. It was packed with ca. 10 mg of 5 wt. % Pd/Al₂O₃ catalyst to perform methane combustion, which was the selected reaction to test the developed platform. The experimental system was monitored and controlled by LabVIEW to which Python scripts for online design of experiments and data analysis were integrated. Within each experimental campaign, the platform automatically adjusted the experimental conditions, and the analysis of the product stream was conducted by online gas chromatography. The experimental platform demonstrated the capability of identifying the most probable kinetic models amidst potential models within two days.

The present article reports the creation and usage of a general natural product database for the structural dereplication of natural products. This database, acd_lotusv7, derives from the LOTUS natural products database as the sole source of chemical structures. Database construction also relies on the commercial “ACD/C+H Predictors and DB” software for the prediction of the carbon-13 nuclear magnetic resonance (NMR) spectral data associated with structures. The linkage of each natural compound with a Wikidata resource identifier already present in LOTUS accelerates the access to the primary literature data such as biologic origin and bibliographic references. The open source nmrshiftdb2 web interface and search engine provide a simple and free way to retrieve compound structures stored in acd_lotusv7 from carbon-13 data and to analyze search results. Dereplication is illustrated by the easy and free retrieval of the structure of three natural compounds of low, medium, and high complexity from published lists of carbon-13 NMR chemical shifts.

Beckmann rearrangement was carried out in the solid state in a ball mill using metal oxides as solid acids. After a comprehensive investigation of different reaction parameters, acids as well as further additives, a combination of aluminosilicate materials, phosphorus pentoxide, and para-toluenesulfonic acid was identified as the optimal system. This allowed the model compounds ϵ-caprolactam and acetanilide to be obtained in yields of 46 % and 94 %, respectively, while the robustness of the method was demonstrated by applying it to additional substrates. Finally, we scaled up our optimized reaction into a continuous process using a twin screw extruder. With this, yields beyond 90 % could be achieved in a residence time as low as seven minutes.

The need for continuous observation of electrocatalytic processes under operating conditions has promoted the popularity of in situ techniques coupled with electrochemical tests. In situ Raman spectrometer coupled with electrochemistry (or Raman spectroelectrochemistry) is a powerful tool to provide real-time structural information related to the dynamic electrolyte/electrode interface. To make it more accessible among the electrocatalysis community, we provide an essential experimental guideline of in situ Raman spectroelectrochemistry to beginners. After the necessary background of the technical principle and primary applications, we focus on the experimental considerations, from electrode preparation, cell design, and laser parameters to the electrochemical sequence and data process. The recent efforts to make this technique more affordable are also highlighted. We hope this review can help beginners to understand and use Raman spectroelectrochemistry.

The novel spinel Cu_0.2Co_0.2Mn_0.2Ni_0.2Zn_0.2Fe₂O₄ comprising six transition metal cations was successfully prepared by a solution-combustion method followed by distinct thermal treatments. The entropic stabilization of this hexa-metallic material is demonstrated using in situ high temperature powder X-ray diffraction (PXRD) and directed removal of some of the constituting elements. Thorough evaluation of the PXRD data yields sizes of coherently scattering domains in the nanometre-range. Transmission electron microscopy based methods support this finding and indicate a homogeneous distribution of the elements in the samples. The combination of ⁵⁷Fe Mössbauer spectroscopy with X-ray absorption near edge spectroscopy allowed determination of the cation occupancy on the tetrahedral and octahedral sites in the cubic spinel structure. Magnetic studies show long-range magnetic exchange interactions which are of ferri- or ferromagnetic nature with an exceptionally high saturation magnetization in the range of 92–108 emu g⁻¹ at low temperature, but also an anomaly in the hysteresis of a sample calcined at 500 °C.

The Front Cover shows a battery cell designed for in operando neutron powder diffraction. The picture seeks to illustrate the experiment process where lithium ions are moving into the crystal structure of the battery cathode during discharge. This leads to changes in the crystal structure that are very important to understand for optimizing the battery materials. These structural changes are probed in operando by neutron powder diffraction, and neutrons are especially suited for probing the location of Li-ion compared with similar techniques such as X-ray diffraction. More information can be found in the Research Article by Daniel R. Sørensen et al..

Invited for this month's cover is the group of Daniel R. Sørensen at the University of Aarhus (Denmark) and at the University of Lund (Sweden). The cover picture shows a battery cell designed for in operando neutron powder diffraction. The picture seeks to illustrate the experiment process where lithium ions are moving into the crystal structure of the battery cathode during discharge. This leads to changes in the crystal structure that are very important to understand for optimizing the battery materials. These structural changes are probed in operando by neutron powder diffraction, and neutrons are especially suited for probing the location of Li-ion compared with similar techniques such as X-ray diffraction. The beauty of using neutrons is also that their penetrating power allows for investigating the battery without the need for windows of any kind. Read the full text of their Research Article at 10.1002/cmtd.202200046.

Digitalisation and industry 4.0 are set to profoundly change the way chemical and materials discovery and development work. The integration of multiple enabling technologies such as flow synthesis, automation, analytics, and real-time reaction control lead to highly efficient, productive, data-driven discovery and synthetic protocols. For instance, the development of flow chemistry enables the fine control and automation of process parameters such as flow rates, temperature, and pressure, which inherently enhances process efficiency. Flow chemistry presents a more sustainable means of manufacturing in terms of waste minimisation, as it enables the integration of synthetic processes with downstream processing. Furthermore, it allows the integration of analytical techniques to provide in situ process monitoring of large amounts of process and product data. The application of Artificial Intelligence (AI) and/or Machine Learning (ML) techniques allows rapid decision making that can optimise existing processes, and it has also been applied in the discovery of novel materials, synthetic pathways and chemicals. All this is contributing to an effective digitalisation of chemical and material synthetic processes from the laboratory to large-scale industrial deployment.

This paper presents recent developments in the effective digitalisation of chemical synthetic processes which integrates continuous flow synthesis, analytics and artificial intelligence technologies. Specifically, this paper illustrates the emerging trend of process digitalisation through the advanced syntheses of materials with catalytic, optical and optoelectronic applications.