Near-frictionless ion transport within triazine framework membranes.

The enhancement of separation processes and electrochemical technologies such as water electrolysers1,2, fuel cells3,4, redox flow batteries5,6 and ion-capture electrodialysis7 depends on the development of low-resistance and high-selectivity ion-transport membranes. The transport of ions through these membranes depends on the overall energy barriers imposed by the collective interplay of pore architecture and pore-analyte interaction8,9. However, it remains challenging to design efficient, scaleable and low-cost selective ion-transport membranes that provide ion channels for low-energy-barrier transport. Here we pursue a strategy that allows the diffusion limit of ions in water to be approached for large-area, free-standing, synthetic membranes using covalently bonded polymer frameworks with rigidity-confined ion channels. The near-frictionless ion flow is synergistically fulfilled by robust micropore confinement and multi-interaction between ion and membrane, which afford, for instance, a Na+ diffusion coefficient of 1.18 × 10-9 m2 s-1, close to the value in pure water at infinite dilution, and an area-specific membrane resistance as low as 0.17 Ω cm2. We demonstrate highly efficient membranes in rapidly charging aqueous organic redox flow batteries that deliver both high energy efficiency and high-capacity utilization at extremely high current densities (up to 500 mA cm-2), and also that avoid crossover-induced capacity decay. This membrane design concept may be broadly applicable to membranes for a wide range of electrochemical devices and for precise molecular separation.

Development of a multi-step screening procedure for redox active molecules in organic radical polymer anodes and as redox flow anolytes.

Benzo[d]-X-zolyl-pyridinyl (XO, S, NH) radicals represent a promising class of redox-active molecules for organic batteries. We present a multistep screening procedure to identify the most promising radical candidates. Experimental investigations and highly correlated wave function-based calculations are performed to determine benchmark redox potentials. Based on these, the accuracies of different methods (semi-empirical, density functional theory, wave function-based), solvent models, dispersion corrections, and basis sets are evaluated. The developed screening procedure consists of three steps: First, a conformer search is performed with CREST. The molecules are selected based on the redox potentials calculated using GFN2-xTB. Second, HOMO energies calculated with reparametrized B3LYP-D3(BJ) and the def2-SVP basis set are used as selection criteria. The final molecules are selected based on the redox potentials calculated from Gibbs energies using BP86-D3(BJ)/def2-TZVP. With this multistep screening approach, promising molecules can be suggested for synthesis, and structure-property relationships can be derived.

Optimization of Mixed Micelles Based on Oppositely Charged Block Copolymers by Machine Learning for Application in Gene Delivery.

The COVID-19 mRNA vaccines represent a milestone in developing non-viral gene carriers, and their success highlights the crucial need for continued research in this field to address further challenges. Polymer-based delivery systems are particularly promising due to their versatile chemical structure and convenient adaptability, but struggle with the toxicity-efficiency dilemma. Introducing anionic, hydrophilic, or "stealth" functionalities represents a promising approach to overcome this dilemma in gene delivery. Here, two sets of diblock terpolymers are created comprising hydrophobic poly(n-butyl acrylate) (PnBA), a copolymer segment made of hydrophilic 4-acryloylmorpholine (NAM), and either the cationic 3-guanidinopropyl acrylamide (GPAm) or the 2-carboxyethyl acrylamide (CEAm), which is negatively charged at neutral conditions. These oppositely charged sets of diblocks are co-assembled in different ratios to form mixed micelles. Since this experimental design enables countless mixing possibilities, a machine learning approach is applied to identify an optimal GPAm/CEAm ratio for achieving high transfection efficiency and cell viability with little resource expenses. After two runs, an optimal ratio to overcome the toxicity-efficiency dilemma is identified. The results highlight the remarkable potential of integrating machine learning into polymer chemistry to effectively tackle the enormous number of conceivable combinations for identifying novel and powerful gene transporters.

Structural Chemistry of Titanium (IV) Oxo Clusters, Part 2: Clusters without Carboxylate or Phosphonate Ligands.

Homometallic titanium oxo clusters (TOC) are one of the most important groups of metal oxo clusters. In a previous article, TOC structures with carboxylato and phosphonato ligands were reviewed and categorized. This work is now extended to clusters with other ligands. Comparison of the different cluster types shows how the interplay between condensation of the titanium polyhedra by means of bridging oxygen atoms and the coordination characteristics of the ligands influences the cluster structures and allows working out basic construction principles of the cluster core.

Advancements and Challenges in the Synthesis of Oxymethylene Ethers (OMEs) as Sustainable Transportation Fuels.

The urgent need for sustainable alternatives to fossil fuels in the transportation sector is driving research into novel energy carriers that can meet the high energy density requirements of heavy-duty vehicles without exacerbating the climate change. This concept article examines the synthesis, mechanisms, and challenges associated with oxymethylene ethers (OMEs), a promising class of synthetic fuels potentially derived from carbon dioxide and hydrogen. We highlight the importance of OMEs in the transition towards non-fossil energy sources due to their compatibility with the existing Diesel infrastructure and their cleaner combustion profile. The synthesis mechanisms, including the Schulz-Flory distribution and its implications for OME chain length specificity, and the role of various catalysts and starting materials are discussed in depth. Despite advancements in the field, significant challenges remain, such as overcoming the Schulz-Flory distribution, efficiently managing water as an undesirable byproduct, and improving the overall energy efficiency of the OME synthesis. Addressing these challenges is crucial for OMEs to become a viable alternative fuel, contributing to the reduction of greenhouse gas emissions and the transition to a sustainable energy future in the transportation sector.

Development of Novel Redox-Active Organic Materials Based on Benzimidazole, Benzoxazole, and Benzothiazole: A Combined Theoretical and Experimental Screening Approach.

Sustainability is one of the hot topics of today's research, in particular when it comes to energy-storage systems such as batteries. Redox-active molecules implemented in organic batteries represent a promising alternative to lithium-ion batteries, which partially rely on non-sustainable heavy metal salts. As an alternative, we propose benzothiazole, -oxazole and -imidazole derivatives as redox-active moieties for polymers in organic (radical) batteries. The target molecules were identified by a combination of theoretical and experimental approaches for the investigation of new organic active materials. Herein, we present the synthesis, electrochemical characterization and theoretical investigation of the proposed molecules, which can later be introduced into a polymer backbone and used in organic polymer batteries.

Exploiting Orthogonal C-C Cross-Coupling Reactions for Chemistry-on-the-Complex: Modular Assembly of 2,6-Di(quinolin-8-yl)pyridine Ruthenium(II) Photosensitizer Triads.

In this work, we present a concise modular assembly strategy using one universal heteroleptic 2,6-di(quinolin-8-yl)pyridine-based ruthenium(II) complex as a starting building block. Extending the concept from established ligand modifications and subsequent complexation (classical route), the later appearing chemistry-on-the-complex methodology was used for late-stage syntheses, i.e., assembling discrete building blocks to molecular architectures (here: dyad and triads). We focused on Suzuki-Miyaura and Sonogashira cross-couplings as two of the best-known C-C bond forming reactions. Both were performed on one building block complex bearing a bromine and TIPS-protected alkyne for functional group interconversion (bromine to TMS-protected alkyne, a benzyl azide, or a boronic acid pinacol ester moiety with ≥95% isolated yield and simple purification) as well as building block assemblies using both a triarylamine-based donor and a naphthalene diimide-based acceptor in up to 86% isolated yield. Additionally, the developed purification via automated flash chromatography is simple compared to tedious manual chromatography for ruthenium(II)-based substrates in the classical route. Based on the preliminary characterization by steady-state spectroscopy, the observed emission quenching in the triad (55%) serves as an entry to rationally optimize the modular units via chemistry-on-the-complex to elucidate energy and electron transfer.

Knowledge-Based Design of Multifunctional Polymeric Nanoparticles.

Conventional drug delivery systems (DDS) today still face several drawbacks and obstacles. High total doses of active pharmaceutical ingredients (API) are often difficult or impossible to deliver due to poor solubility of the API or undesired clearance from the body caused by strong interactions with plasma proteins. In addition, high doses lead to a high overall body burden, in particular if they cannot be delivered specifically to the target site. Therefore, modern DDS must not only be able to deliver a dose into the body, but should also overcome the hurdles mentioned above as examples. One of these promising devices are polymeric nanoparticles, which can encapsulate a wide range of APIs despite having different physicochemical properties. Most importantly, polymeric nanoparticles are tunable to obtain tailored systems for each application. This can already be achieved via the starting material, the polymer, by incorporating, e.g., functional groups. This enables the particle properties to be influenced not only specifically in terms of their interactions with APIs, but also in terms of their general properties such as size, degradability, and surface properties. In particular, the combination of size, shape, and surface modification allows polymeric nanoparticles to be used not only as a simple drug delivery device, but also to achieve targeting. This chapter discusses to what extent polymers can be designed to form defined nanoparticles and how their properties affect their performance.

Nanoparticle Formulation Composition Analysis by Liquid Chromatography on Reversed-Phase Monolithic Silica.

Multifunctional nanoparticle (NP) formulations for medical purposes have already found their way toward envisaged translation. A persistent challenge of those systems is, next to NP size analysis, the compositional analysis of the NPs with the polymer as the matrix component and the encapsulated drug, particularly in a quantitative manner. Herein, we report the formulation of poly(lactic-co-glycolic acid) (PLGA) NPs by nanoprecipitation and the analysis of their integrity and size by dynamic light scattering (DLS) and scanning electron microscopy (SEM). Those NPs feature a variety of encapsulated drugs including the well-known ibuprofen (Ibu) as well as dexamethasone (Dex) and dexamethasone acetate (DexAce), with the latter being of potential interest for clinical treatment of SARS-CoV-2 patients. All those dissolved formulation compositions have been subjected to liquid chromatography on reversed-phase silica monolithic columns, allowing to quantitatively assess amounts of small molecule drug and NP constituting PLGA polymer in a single run. The chromatographically resolved hydrophobicity differences of the drugs correlated with their formulation loading and were clearly separated from the PLGA matrix polymer with high resolution. Our study identifies the viability of reversed-phase monolithic silica in the chromatography of both small drug molecules and particularly pharmapolymers in a repeatable and simultaneous fashion, and can provide a valuable strategy for analysis of diverse precursor polymer systems and drug components in multifunctional drug formulations.

Oxymethylene Ether (OME) Fuel Catalyst Screening Using In Situ NMR Spectroscopy.

Online NMR measurements are introduced in the current study as a new analytical setup for investigation of the oxymethylene dimethyl ether (OME) synthesis. For the validation of the setup, the newly established method is compared with state-of-the-art gas chromatographic analysis. Afterwards, the influence of different parameters, such as temperature, catalyst concentration and catalyst type on the OME fuel formation based on trioxane and dimethoxymethane is investigated. As catalysts, AmberlystTM 15 (A15) and trifluoromethanesulfonic acid (TfOH) are utilized. A kinetic model is applied to describe the reaction in more detail. Based on these results, the activation energy (A15: 48.0 kJ mol-1 and TfOH: 72.3 kJ mol-1 ) and the order in catalyst (A15: 1.1 and TfOH: 1.3) are calculated and discussed.