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

For years now, High-Throughput Experimentation (HTE) have been applied to organic chemistry for reaction optimization and reaction discovery as a powerful tool for time and cost reduction. If this technology has been first developed by and for industry, and used as a routine method today, some academic researchers, including in Europe, are still challenging the accessibility of HTE as a general and daily used technology. One of the reasons is probably the expensive cost of such facilities development, which generally involves automation with robots, dedicated research teams, and expensive analytical instrumentation. This paper aims at bringing to light the accessibility of batch HTE with a minimum of instrumentation and cost, in order to help organic chemists to accelerate the discovery and optimization of new synthetic methodology, leading them to reduce their costs and empower their innovative research.

With this work, we wish to facilitate further developments in photocatalysis by proposing reliable methods for the computational pre-screening of potential photocatalysts. To this end, we have developed a new benchmark strategy, and we have applied it to evaluate the predictions given by two wavefunction and several density functional theory (DFT) methods for the UV-vis absorption spectra of recently developed organic photocatalyst molecules. The novelty in our benchmark framework is that it focuses on evaluating the real-world applicability of computational methods and does not penalize errors that do not contribute to spectral shapes. We employ a spectral fitting process where the calculated excitations are convoluted with Gaussians using two parameters for broadening and wavelength scaling. This way, most methods can sufficiently reproduce the experimental spectra, but they differ in how much adjustment they require from the parameters. Overall, the double hybrids (with the notable exception of DSD-BLYP) are the best functionals that offer the highest predictive power as they require practically no scaling. They are exceptionally good in estimating the excitation energies with almost 90 % of the fitted spectra falling into the ±10 % scaling window. This is the same level of accuracy as provided by the STEOM-DLPNO-CCSD correlated wavefunction method. In terms of cost efficiency, M06 emerges as the best functional. It compensates a slightly less consistent performance with lower computational demand and availability in nearly all computational codes. Therefore, we recommend the use of double-hybrid and M06 functionals for UV-vis spectrum prediction of novel organic photocatalysts, and we also highlight that M06 can be used as a black-box method even by those who are non-experts in computational chemistry. The developed protocol and a user-friendly notebook to assist the analysis are available on GitHub.

The quest for atomic structures of microsecond reaction intermediates is at the frontline of modern biochemistry. Currently, there is a clear lack of experimental methods for preparing necessary time-resolved samples. Here, we report the development of a single-turnover technique for nanosecond initiation and suspension of biomolecular reactions with kinetic resolution in the microsecond time domain. Reactions can be started by large temperature-jump or direct mixing and arrested by hyperquenching in liquid cryogen at a target temperature of 77 K. Diverse morphology of nanoscale glassy bodies feature among others thin field-of-view plane sheets that can be used for structure analyses of freeze-trapped macromolecules by transmission electron cryomicroscopy. We also report the ultra-high vacuum sublimation at 77 K – a novel method for concentrating reaction intermediates for structural studies by low-temperature techniques.

The Front Cover shows how X-rays can be used to obtain spatially resolved chemical imaging insight from within an industrial catalytic reactor. Understanding how the microstructure of the active Cu⁰ component in the commercially applicable Cu/ZnO/Al₂O₃(−Cs₂O) low-temperature water-gas shift catalyst evolves under various H₂ partial pressures in the presence/absence of a Cs promoter during thermal activation has been the subject of the present investigation. More information can be found in the Research Article by Daniela M. Farmer et al..

Invited for this month's cover is the group of Andrew M. Beale at the University College London and at the Research Complex at Harwell (UK). The cover picture demonstrates how X-rays can be used to obtain spatially resolved chemical imaging insight from within an industrial catalytic reactor. Understanding how the microstructure of the active Cu⁰ component in the commercially applicable Cu/ZnO/Al₂O₃(−Cs₂O) low-temperature water-gas shift catalyst evolves under various H₂ partial pressures in the presence/absence of a Cs promoter during thermal activation has been the subject of the present investigation. Read the full text of their Research Article at 10.1002/cmtd.202200015.

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.