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0 min at neutral pH. The knowledge gained herein on the effective role of Ru(III) to activate PAA to oxidize micropollutants may aid in developing Ru(III)-containing catalysts for PAA-based AOPs.Protein pores recently enabled a breakthrough in bioanalytics by making it possible to sequence individual DNA and RNA strands during their translocation through the lumen of the pore. Despite this success and the overall promise of nanopore-based single-molecule analytics, protein pores have not yet reached their full potential for the analysis and characterization of globular biomolecules such as natively folded proteins. One reason is that the diameters of available protein pores are too small for accommodating the translocation of most folded globular proteins through their lumen. The work presented here provides a step toward overcoming this limitation by programmed self-assembly of α-helical pore-forming peptides with covalently attached single-stranded DNA (ssDNA). Specifically, hybridization of the peptide ceratotoxin A (CtxA) with N-terminally attached ssDNA to a complementary DNA template strand with 4, 8, or 12 hybridization sites made it possible to trigger the assembly of pores with various diameters ranging from approximately 0.5 to 4 nm. Hybridization of additional DNA strands to these assemblies achieved extended functionality in a modular fashion without the need for modifying the amino acid sequence of the peptides. For instance, functionalization of these semisynthetic biological nanopores with DNA-cholesterol anchors increased their affinity to lipid membranes compared to pores formed by native CtxA, while charged transmembrane segments prolonged their open-state lifetime. Assembly of these hybrid DNA-peptides by a template increased their cytotoxic activity and made it possible to kill cancer cells at 20-fold lower total peptide concentrations than nontemplated CtxA.Energy consumption is a growing phenomenon in our society causing many negative effects such as global warming. There is a need for the development of new sustainable materials for energy storage. Carbons are materials derivable from biowaste that can rather easily store energy due to their high conductivity and surface area. However, their large-scale processing is challenging as derived materials can be rather heterogeneous and homogenization requires ball milling, a process that can damage carbons in the process of oxidation. Herein, we have prepared caffeine-derived noble nitrogen-doped carbon that withstands the ball milling process without significant oxidation. Additionally, it performs extraordinarily as a cathode material for lithium-ion capacitors, making it an attractive biowaste-derived alternative to commercial heavy metal cathodes.Distributions of chlorine isotopologues are potentially a fingerprint feature of organochlorines. However, the exact distributions remain little known. This study measured compound-specific chlorine isotopologue distributions of six polychlorinated organic compounds (POCs) for source identification. Complete chlorine isotopologues of POCs were detected by gas chromatography coupled to high-resolution mass spectrometry. The measured relative abundances (Ameas), theoretical relative abundances (Atheo), and relative variations between Ameas and Atheo (ΔA) of chlorine isotopologues were determined. These ΔA values were applied to characterize differences in isotopologue distribution patterns, and the ΔA patterns directly illustrated the distribution characteristics. Perchloroethylene (PCE) and trichloroethylene (TCE) from two manufacturers were chosen as model analytes to develop and validate the analytical method, including precision, concentration dependency, and temporal drift. The ΔA values of isotopologues of the PCE and TCE chemicals were from -82.5 to 19.9‰ with standard deviations (SDs) of 0.3-16.9‰. In addition, the ΔA values of the first three isotopologues (with 0-2 37Cl atoms) were from -15.5 to 19.9‰ with SDs of 0.3-1.6‰, showing sufficient precisions. No concentration dependency and temporal drift of ΔA were observed. The method has been successfully applied to source identification for PCE and TCE in commercial chemicals and plastic materials, and four polychlorinated biphenyls in chemicals and sediments, demonstrating that the ΔA values and ΔA patterns were discernable for POCs from different sources. IPI-549 price This study demonstrates that compound-specific chlorine isotopologue distributions of POCs are differentiable and measurable, proposing a novel approach to perform fingerprinting analysis for the distributions, which is anticipated to facilitate source identification for organochlorine pollutants.Superhydrophobic surfaces have been largely achieved through various surface topographies. Both empirical and numerical simulations have been reported to help understand and design superhydrophobic surfaces. Many such successful surfaces have also been achieved using bioinspired and biomimetic designs. Despite this, identifying the right surface texture to meet the requirements of specific applications is not a straightforward task. Here, we report a hybrid approach that includes experimental methods, numerical simulations, and machine learning (ML) algorithms to create design maps for superhydrophobic polymer topographies. Two design objectives to investigate superhydrophobic properties were the maximum water contact angle (WCA) and Laplace pressure. The design parameters were the geometries of an isotropic pillar structure in micrometer and sub-micrometer length scales. The finite element method (FEM) was validated by the experimental data and employed to generate a labeled dataset for ML training. Artificial neural network (ANN) models were then trained on the labeled database for the topographic parameters (width W, height H, and pitch P) with the corresponding WCA and Laplace pressure. The ANN models yielded a series of nonlinear relationships between the topographic design parameters and the WCA and Laplace pressure and substantial differences between the micrometer and sub-micrometer length scales. Design maps that span the topography design parameters provide optimal design or tradeoff parameters. This research demonstrates the potential of ANN as a rapid design tool for surface topography exploration.