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Physical adsorption at cryogenic temperature (cryoadsorption) is a reversible mechanism that can reduce the pressure of conventional compressed gas storage systems. Metal–organic framework (MOF) materials are remarkable candidates due to the combination of high specific surface area and density which, in some cases, provide a high volumetric storage capacity. However, such extensive use of MOFs for this application requires the selection of affordable structures, easy to produce and made from feasible metallic and organic components. Herein, we introduce a MOF database detailing the crystallographic and porous properties of 3600 existing MOFs made from industrially relevant metals and their organic composition. The comparison of the available minimum costs of linkers allowed the creation of a database to select affordable structures with high potential for volumetric hydrogen storage by cryoadsorption, considering their composition based on individual or mixed building blocks. A user interface, available online, facilitates the selection of MOFs based on the properties or names of structures and linkers.
Mechanical flexibility in single crystals of covalently bound materials is a fascinating and poorly understood phenomenon. We present here the first example of a plastically flexible one-dimensional (1D) coordination polymer. The compound [Zn(m-Cl)2(3,5-dichloropyridine)2]n is flexible over two crystallographic faces. Remarkably, the single crystal remains intact when bent to 1808. A combination of microscopy, diffraction, and spectroscopic studies have been used to probe the structural response of the crystal lattice to mechanical bending. Deformation of the covalent polymer chains does not appear to be responsible for the observed macroscopic bending. Instead, our results suggest that mechanical bending occurs by displacement of the coordination polymer chains. Based on experimental and theoretical evidence, we propose a new model for mechanical flexibility in 1D coordination polymers. Moreover, our calculations propose a cause of the different mechanical properties of this compound and a structurally similar elastic material
Engineered nanomaterials (NM) with their large surface-to-volume ratios and their for some materials observed size-dependent functional properties are of increasing relevance for current and future developments in various fields such as medical and pharmaceutical industry, computing and electronics or food and consumer products. The performance and safety of NM are determined by the sum of their intrinsic physicochemical properties. Especially, the particle surface chemistry, which is largely controlled by the chemical nature and density of functional groups (FG) and ligands, is an important key driver for NM performance, stability, and processibility as well as the interaction of NM with the environment. Thus, methods for FG quantification can foster the sustainable development of functional and safe(r) NM.
Aiming at the development of simple, versatile, and multimodal tools for the quantification of many bioanalytically relevant FG and ligands, we investigated and compared various analytical methods commonly used for FG quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance and thermal analysis methods.
The potential of our multimodal approach for FG quantification was demonstrated for commercial and custom-made polymeric and silica particles of varying FG, used as optical pH sensors. In the future, our strategy can contribute to establish multi-method characterization strategies to provide a more detailed picture of the structure-properties relationship.
Nowadays amorphous silica nanoparticles (SiO2-NP) are one of the most abundant engineered nanomaterials, that are highly stable and can be easily produced on a large scale at low cost. Surface functionalized SiO2-NP are of great interest in the life and material sciences, as they can be used e.g. as
drug carriers, fluorescent sensors, and multimodal labels in bioanalytical assays and imaging applications. Their performance in such applications depends not only on particle size, size distribution, and morphology, but also on surface chemistry, i.e. the total number of surface functional groups (FG)
and the number of FG accessible for subsequent functionalization with ligands or biomolecules, which in turn determines surface charge, colloidal stability, biocompatibility, and toxicity. Aiming at the development of simple, versatile, and multimodal tools for the quantification of many bioanalytically relevant FG and ligands, we investigated and compared various analytical methods commonly used for FG quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance and thermal analysis methods.
The potential of our multimodal approach for FG quantification was demonstrated for commercial and custom-made silica particles of varying FG, showing not only an influence of the synthesis methods on the number of FG but also on the performance. In the future, our strategy can contribute to establish multi-method characterization strategies to provide a more detailed picture of the structure-properties relationship.
The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples.
In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge.
Organic/inorganic mixtures were prepared from ordinary Portland cement (OPC), water (w/c 0.22), a fluorescent dye in aqueous solution (stable at alkaline pH; BAM-I), and two different comb shape polycarboxylates (PCEs), i.e., high charge (PCE-HC) and low charge (PCE-LC), respectively. Rheological and calorimetric measurements were performed prior to optical studies in order to select PCE concentrations. Absorption and fluorescence spectroscopy of the system OPC + BAM-I (CBAM-I) revealed maxima of dye BAM-I located at 645 nm and 663 nm, respectively. In presence of PCE-HC and PCE-LC, these mixtures displayed a small red shift in reflectance and a faster decrease in intensity compared to studies with CBAM-I; however, only slight differences were observed between the different PCEs. With time, all systems exhibited a decrease in intensity of BAM-I in absorption/reflectance and emission. This could be caused by dye adsorption and possibly decomposition when in contact with cement particles or hydration products.
Structural modularity of polymer frameworks is a key advantage of covalent organic polymers, however, only C, N, O, Si and S have found their way into their building blocks so far. Here, we expand the toolbox available to polymer and materials chemists by one additional nonmetal, phosphorus. Starting with a building block that contains a λ⁵‐phosphinine (C₅P) moiety, we evaluate a number of polymerisation protocols, finally obtaining a π‐conjugated, covalent phosphinine‐based framework (CPF‐1) via Suzuki‐Miyaura coupling. CPF‐1 is a weakly porous polymer glass (72.4 m2 g‐1 N2 BET at 77 K) with green fluorescence (λmax 546 nm) and extremely high thermal stability. The polymer catalyzes hydrogen evolution from water under UV and visible light irradiation without the need for additional co‐catalyst at a rate of 33.3 μmol h‐¹ g‐¹. Our results demonstrate for the first time the incorporation of the phosphinine motif into a complex polymer framework. Phosphinine‐based frameworks show promising electronic and optical properties that might spark future interest in their applications in light‐emitting devices and heterogeneous catalysis.
The fluorescence lifetime is a key property of fluorophores that can be utilized for microenvironment probing, analyte sensing, and multiplexing as well as barcoding applications. For the rational design of lifetime probes and barcodes, theoretical methods have been developed to enable the ab initio prediction of this parameter, which depends strongly on interactions with solvent molecules and other chemical species in the emitters' immediate environment. In this work, we investigate how a conductor-like screening model (COSMO) can account for variations in fluorescence lifetimes that are caused by such fluorophore−solvent interactions. Therefore, we calculate vibrationally broadened fluorescence spectra using the nuclear ensemble method to obtain distorted molecular geometries to sample the electronic transitions with time-dependent density functional theory (TDDFT). The influence of the solvent on fluorescence lifetimes is accounted for with COSMO. For example, for 4-hydroxythiazole fluorophore containing different heteroatoms and acidic and basic moieties in aprotic and protic solvents of varying polarity, this approach was compared to experimentally determined lifetimes in the same solvents. Our results demonstrate a good correlation between theoretically predicted and experimentally measured fluorescence lifetimes except for the polar solvents Ethanol and acetonitrile that can specifically interact with the heteroatoms and the carboxylic acid of the thiazole derivative.
Absolute upconversion quantum yields of blue-emitting LiYF4:Yb3+,Tm3+ upconverting nanoparticles
(2018)
The upconversion quantum yield (QY) is an essential parameter for the characterization of the optical performance of lanthanoid-doped upconverting nanoparticles (UCNPs). Despite its nonlinear dependence on excitation power density, it is typically reported only as a single number. Here, we present the first measurement of absolute upconversion quantum yields of the individual emission bands of blue light-emitting LiYF4:Yb3+,Tm3+ UCNPs in toluene. Reporting the quantum yields for the individual emission bands is required for assessing the usability of UCNPs in various applications that require upconverted light of different wavelengths, such as bioimaging, photocatalysis and phototherapy.
Here, the reliability of the QY measurements is demonstrated by studying the same batch of UCNPs in three different research groups. The results show that whereas the total upconversion quantum yield of these UCNPs is quite high - typically 0.02 at a power density of 5 W/cm2 — most of the upconverted photon flux is emitted in the 794 nm upconversion band, while the blue emission band at 480 nm is very weak, with a much lower quantum yield of 6 times 10^5 at 5 W/cm2. Overall, although the total upconversion quantum yield of LiYF4:Yb3+,Tm3+ UCNPs seems satisfying, notably for NIR bioimaging, blue-light demanding phototherapy applications will require better-performing UCNPs with higher blue light
upconversion quantum yields.