-
Lacroix Saleh posted an update 6 months ago
The state-of-the-art research into both catalysis and products, as well as future challenges and directions, are presented.The porphyrinic metal-organic framework, PCN-222, exhibits anisotropic growth behavior to form nanorods and microrods with aspect ratios 3 less then x less then 94. Control of microrod aspect ratios has been demonstrated through the identification of several factors that dictate crystal growth, particularly the concentrations of a ligand, a modulator, and an exogenous base. An increase in the local concentration of a deprotonated ligand, which is proportional to the nucleation rate, is associated with smaller crystals, while increased modulator concentration leads to longer microrods. Addition of a deprotonating agent not only contributes to higher aspect ratios but also results in an improvement to particle dispersity. Here, we report acid-base co-modulation methods with difluoroacetic acid and triethylamine to effectively tune PCN-222 aspect ratios. A series of mechanisms is identified for the growth of PCN-222 (1) ligand deprotonation, (2) nucleation, (3) oriented attachment, (4) Ostwald ripening, and (5) dissolution-recrystallization. Time trials of co-modulated samples revealed three separate ripening growth events, with each resulting in larger and more monodisperse crystals. With an understanding of these crystal growth factors and mechanisms, the highest aspect ratio, non-templated metal-organic frameworks were synthesized (94 ± 9).Fourier transform infrared spectroscopy (FTIR) is a ubiquitous spectroscopic technique. Spectral interpretation is a time-consuming process, but it yields important information about functional groups present in compounds and in complex substances. We develop a generalizable model via a machine learning (ML) algorithm using convolutional neural networks (CNNs) to identify the presence of functional groups in gas-phase FTIR spectra. The ML models reduce the amount of time required to analyze functional groups and facilitate interpretation of FTIR spectra. Through web scraping, we acquire intensity-frequency data from 8728 gas-phase organic molecules within the NIST spectral database and transform the data into spectral images. We successfully train models for 15 of the most common organic functional groups, which we then determine via identification from previously untrained spectra. These models serve to expand the application of FTIR measurements for facile analysis of organic samples. Our approach was done such that we have broad functional group models that infer in tandem to provide full interpretation of a spectrum. SAR405 We present the first implementation of ML using image-based CNNs for predicting functional groups from a spectroscopic method.The practical uses of lithium-sulfur batteries are greatly restricted by the sluggish reaction kinetics of lithium polysulfides (LiPSs), leading to low sulfur utilization and poor cyclic stability. Using the heterostructure catalysts is an effective way to solve the above problems, but how to further enhance the conversion efficiency and avoid the surface passivation by the insulative Li2S has not been well investigated. Herein, a heterostructure catalyst with rich heterointerfaces was prepared by modifying Mo2N microbelt with SnO2 nanodots. The formed rich interfaces with high accessibility act as the profitable nucleation sites guiding the Li2S 3D growth, which avoids the catalyst surface passivation and facilitates the LiPS conversion. The introduction of SnO2 nanodots also enhances the LiPS adsorption. Thus, the assembled battery with the above catalyst as the cathode additive shows a high capacity of 738.3 mAh g-1 after 550 cycles at 0.5 C with an ultralow capacity decay of 0.025% per cycle. Even with high sulfur loading of 9.0 mg cm-2, good cyclic stability is also achieved at 0.5 C with a low E/S ratio of 5 μL mgs-1. This work shows an effective way to enhance the LiPS conversion kinetics and guide Li2S deposition in Li-S batteries.The coordination chemistry of Cm(III) with aqueous phosphates was investigated by means of laser-induced luminescence spectroscopy and ab initio simulations. For the first time, in addition to the presence of Cm(H2PO4)2+, the formation of Cm(H2PO4)2+ was unambiguously established from the luminescence spectroscopic data collected at various H+ concentrations (-log10 = 2.52, 3.44, and 3.65), ionic strengths (0.5-3.0 mol·L-1 NaClO4), and temperatures (25-90 °C). Complexation constants for both species were derived and extrapolated to standard conditions using the specific ion interaction theory. The molal enthalpy ΔRHm0 and molal entropy ΔRSm0 of both complexation reactions were derived using the integrated van’t Hoff equation and indicated an endothermic and entropy-driven complexation. For the Cm(H2PO4)2+ complex, a more satisfactory description could be obtained when including the molal heat capacity term. While monodentate binding of the H2PO4- ligand(s) to the central curium ion was found to be the most stable configuration for both complexes in our ab initio simulations and luminescence lifetime analyses, a different temperature-dependent coordination to hydration water molecules could be deduced from the electronic structure of the Cm(III)-phosphate complexes. More precisely, where the Cm(H2PO4)2+ complex could be shown to retain an overall coordination number of 9 over the entire investigated temperature range, a coordination change from 9 to 8 was established for the Cm(H2PO4)2+ species with increasing temperature.Microcapsules made of synthetic polymers are used for the release of cargo in agriculture, food, and cosmetics but are often difficult to be degraded in the environment. To diminish the environmental impact of microcapsules, we use the biofilm-forming ability of bacteria to grow cellulose-based biodegradable microcapsules. The present work focuses on the design and optimization of self-grown bacterial cellulose capsules. In contrast to their conventionally attributed pathogenic role, bacteria and their self-secreted biofilms represent a multifunctional class of biomaterials. The bacterial strain used in this work, Gluconacetobacter xylinus, is able to survive and proliferate in various environmental conditions by forming biofilms as part of its lifecycle. Cellulose is one of the main components present in these self-secreted protective layers and is known for its outstanding mechanical properties. Provided enough nutrients and oxygen, these bacteria and the produced cellulose are able to self-assemble at the interface of any given three-dimensional template and could be used as a novel stabilization concept for water-in-oil emulsions.
Please follow & like us :)
All content contained on CatsWannaBeCats.Com, unless otherwise acknowledged,is the property of CatsWannaBeCats.Com and subject to copyright.