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

The design and commissioning of a cell suitable for operando studies using high-energy-resolution fluorescence-detected X-ray absorption near-edge structure (HERFD-XANES) spectroscopy in the tender X-ray regime is reported. The cell is optimized for measurements within the energy range of 1.5 keV to 4.5 keV. It has a plug-flow geometry and can be used for sieved powder samples, analogous to reactors employed for laboratory tests. The functionality of the spectroscopic cell is demonstrated in the area of emission control using CO oxidation as target reaction over 1 wt.% Rh/γ-Al₂O₃ as catalyst. We show how HERFD-XANES at the Rh L₃-edge captures variations in the noble metal structure resulting from the interaction with the support material and reactant molecules. Moreover, distinct structural changes were identified along the catalyst bed as a function of temperature and local gas mixture.

Polymer membrane electrolyzers benefit from high-pressure operation conditions and low gas cross-over and can either conduct protons (H⁺) or hydroxide ions (OH⁻). Both types of electrolyzers have a similar design, but differ in power density and the choice of catalysts. Despite the significant endeavor of their optimization, to date, there is no well-established impedance model for detailed analysis for either type of these devices. This complicates the in-situ characterization of electrolyzers, hindering the investigation of degradation mechanisms and electrocatalytic processes as a function of applied current density or time. Nevertheless, a detailed understanding of such individual processes and distinguishing the performance-limiting factors are the keystones for sophisticated device optimization. In this work, an impedance model based on electrode processes has been developed for an anion exchange membrane electrolyzer utilizing iridium oxide anode and platinum cathode electrocatalysts. This model allows to deconvolute the measured impedances into constituents related to the individual electrode processes and to estimate actual physico-chemical quantities such as the reaction kinetic parameters and double-layer capacitances. We discuss the meaning of the fitting parameters and show that this model enables, for the first time, the estimation of the electrochemically active surface area of the anode electrocatalysts under reaction conditions.

pH adjustment is crucial for many industrial products, yet this step is typically performed by manual trial-and-error. A particularly industrially relevant yet challenging titration is that of adjusting viscous liquid formulations using weak, polyprotic titrants (usually citric acid). Handling of viscous, non-Newtonian formulations, with such polyprotic acids preferred for their chelation and buffering effects make a robotic solution challenging. We present a self-driving pH robot integrated with physics-informed learning; this hybrid physical-ML model enables automated titration with weak-strong acid/base pairs. To deal with the high viscosities of these formulations, we developed specific automated mixing and cleaning protocols. We hit the target pH within two to five iterations over 250 distinct formulations in lab-scale small-batch (~10 mL and 12 samples) titrations. In the interest of scaling up to match industrial processes, we also demonstrate that our hybrid algorithm works at ~25× scale-up. The method is general, and we open-source our algorithm and designs.

Liquid Cell Transmission Electron Microscopy (LCTEM) is a great progression in nanostructure imaging, allowing the observation of chemical reactions in real time. It is widely reported, that this technique can be successfully used for analyzing nanoparticles synthesis, diffusion, aggregation and degradation. This gives a completely new insight into nanotechnological research. Normally, samples in TEM must be observed in vacuum, showing only the results of a performed experiment, whereas in situ observations in liquid environment provide information about the dynamics of the processes. LCTEM can show, how orientation of the particles/aggregates, surface roughness or solution flow rate influence the examined reaction. Those data are highly valuable for creating kinetic models of the reactions. There are however still some obstacles in LCTEM. Imaging of nanostructures in liquid environment is problematic since the electron beam reportedly may affect the observed sample. The beam modifies the temperature and pH of the liquid sample, changing the process dynamics. Therefore, its influence needs to be considered during in situ TEM observations. Nevertheless, LCTEM remains one of the highest achievements in the field of nanostructures imaging. In this review, recent achievements and developments of the LCTEM technique are presented.

Lithiated transition metal oxides are the most important cathode materials for lithium-ion batteries. Many efforts have been devoted in recent years to improving their energy density, stability, and safety, as demonstrated by thousands of publications. However, the commercialization of several promising materials is limited due to obstacles like stability limitations. To overcome the limitations of energetically high-voltage or high-capacity cathode materials, unconventional solutions for their surface engineering were suggested; among them, metal–organic frameworks (MOFs) and zeolites have been employed. MOFs possess favorable characteristics for stabilization goals, including manageable structures, topological control, high porosity, large surface area, and low density. This review article explores promising strategies for improving the electrochemical behavior of favorable cathode materials through surface modifications by using MOFs and zeolites. Investigating the potential of this frameworks-based surface engineering for high energy density batteries’ electrodes is essential for optimal control of their surface chemistry. It may be highly effective to upgrade the performance of high-energy cathode materials, thus extending the practical use of very high energy density rechargeable batteries.

Protein functionalisation for the development of imaging agents and antibody drug conjugates still often relies on statistical amidation of the protein through accessible lysine and cysteine residues, requiring protein to protein conjugation optimisation and can potentially impact the overall function. To combat this, focus has turned to developing proteins that have noncanonical amino acids incorporated into their structure, allowing for site-specific labelling and functionalisation. Herein we showcase the incorporation of non-canonical amino acids bearing a tetrazine or azide orthogonal coupling modality into biologics targeted to the prostate-specific membrane antigen and epidermal growth factor receptor respectively. The placement of these bioorthogonal residues into nanobody or single chain variable fragments (scFvs) is introduced by site-directed mutagenesis of the protein-coding DNA that allows for controlled insertion when these proteins are expressed. We show that bioorthogonal coupling of model compounds such as fluorophore or polymeric materials onto the protein does not significantly change the binding affinity, making these protein conjugation methods a powerful tool for development of simple customisable personalised targeted antibody-drug conjugates where affinity is retained.