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Environmental contextIron-containing combustion particles are likely to contribute to environmental iron deposition, while atmospheric acidic processing of such particles can promote their dissolution. Here we report the surface-mediated dissolution of iron from ashes generated by biomass burning power plants and kilns. Examination of the dissolution process at several environmentally relevant pHs, suggests that pH has little impact on the fraction of bioavailable Fe(II) that dissolves into the aqueous phase, although Fe(III) is heavily pH dependent. RationaleAnthropogenic combustion particles, such as ash produced in power plants or kilns, are byproducts with limited use that accumulate in large deposits and become materials of environmental concern. While stored, these particles can be carried by winds into the atmosphere or into soil or near water bodies. Recent studies suggest that a fraction of metals present in the environment come from combustion particles. MethodologyIn this study, we carry out a comparative study of iron dissolution and speciation from two different combustion particles: bottom ash from a biomass-fired power plant (BA) and lime kiln dust (LKD). Samples were fully characterised and their iron leaching was investigated in aqueous suspensions under environmentally relevant acidic conditions. Iron analysis and speciation was carried out calorimetrically. ResultsFor the combustion particles examined, the fraction of bioavailable Fe2+ is lower than Fe3+. The solubility of Fe3+ is highly dependent on pH, dropping significantly at pHs higher than 3. On the other hand, the solubility of Fe2+ from both BA and LKD was found to be relatively constant over the range of pH investigated. DiscussionIron availability from combustion particles with similar mineralogy is driven by the particle’s surface properties. While iron from LKD dissolves faster than that from BA, the initial rate of dissolution of iron remains statistically constant at pHs relevant for the atmospheric aerosol deliquescent layer, decreasing at pHs above 3. This work provides insight into the ability of combustion particles to provide iron micronutrients under different environmentally relevant acidic conditions. 

Abstract We report hydroboration of carbodiimide and isocyanate substrates catalyzed by a cyclic carbodiphosphorane catalyst. The cyclic carbodiphosphorane outperformed the other Lewis basic carbon species tested, including other zerovalent carbon compounds, phosphorus ylides, anN‐heterocyclic carbene, and anN‐heterocyclic olefin. Hydroborations of seven carbodiimides and nine isocyanates were performed at room temperature to formN‐boryl formamidine andN‐boryl formamide products. Intermolecular competition experiments demonstrated the selective hydroboration of alkyl isocyanates over carbodiimide and ketone substrates. DFT calculations support a proposed mechanism involving activation of pinacolborane by the carbodiphosphorane catalyst, followed by hydride transfer and B−N bond formation. 

Abstract Conjugated polymers have received significant attention as potentially lightweight and highly tailorable alternatives to inorganic semiconductors, but their synthesis is often complex, produces toxic byproducts, and they are not typically designed to be degradable or recyclable. These drawbacks necessitate dedicated efforts to discover materials with design motifs that enable targeted and efficient degradation of conjugated polymers. In this vein, the synthetic simplicity of 1,4‐dihydropyrrolo[3,2‐b]pyrroles (DHPPs) is exploited to access azomethine‐containing copolymers via a benign acid‐catalyzed polycondensation protocol. Polymerizations involve reacting a dialdehyde‐functionalized dihydropyrrolopyrrole withp‐phenylenediamine as the comonomer usingp‐toluenesulfonic acid as a catalyst. The inherent dynamic equilibrium of the azomethine bonds subsequently enabled the degradation of the polymers in solution in the presence of acid. Degradation of the polymers is monitored via NMR, UV‐vis absorbance, and fluorescence spectroscopies, and the polymers are shown to be fully degradable. Notably, while absorbance measurements reveal a continued shift to higher energies with extended exposure to acid, fluorescence measurements show a substantial increase in the fluorescence response upon degradation. Results from this study encourage the continued development of environmentally‐conscious polymerizations to attain polymeric materials with useful properties while simultaneously creating polymers with structural handles for end‐of‐life management or/and recyclability. 

Abstract Aerosol particles are important for our global climate, but the mechanisms and especially the relative importance of various vapors for new particles formation (NPF) remain uncertain. Quantum chemical (QC) studies on organic enhanced nucleation has for the past couple of decades attracted immense attention, but very little remains known about the exact organic compounds that potentially are important for NPF. Here we comprehensively review the QC literature on atmospheric cluster formation involving organic compounds. We outline the potential cluster systems that should be further investigated. Cluster formation involving complex multi‐functional organic accretion products warrant further investigations, but such systems are out of reach with currently applied methodologies. We suggest a “cluster of functional groups” approach to address this issue, which will allow for the identification of the potential structure of organic compounds that are involved in atmospheric NPF. This article is categorized under:Theoretical and Physical Chemistry > Reaction Dynamics and KineticsSoftware > Quantum ChemistryTheoretical and Physical Chemistry > ThermochemistryMolecular and Statistical Mechanics > Molecular Interactions 

Abstract Facing the continuous emergence of new psychoactive substances (NPS) and their threat to public health, more effective methods for NPS prediction and identification are critical. In this study, the pharmacological affinity fingerprints (Ph-fp) of NPS compounds were predicted by Random Forest classification models using bioactivity data from the ChEMBL database. The binaryPh-fpis the vector consisting of a compound’s activity against a list of molecular targets reported to be responsible for the pharmacological effects of NPS. Their performance in similarity searching and unsupervised clustering was assessed and compared to 2D structure fingerprints Morgan and MACCS (1024-bits ECFP4 and 166-bits SMARTS-based MACCS implementation of RDKit). The performance in retrieving compounds according to their pharmacological categorizations is influenced by the predicted active assay counts inPh-fpand the choice of similarity metric. Overall, the comparative unsupervised clustering analysis suggests the use of a classification model with Morgan fingerprints as input for the construction ofPh-fp. This combination gives satisfactory clustering performance based on external and internal clustering validation indices. 

Abstract The 3D reference interaction site model (3D‐RISM) of molecular solvation is a powerful tool for computing the equilibrium thermodynamics and density distributions of solvents, such as water and co‐ions, around solute molecules. However, 3D‐RISM solutions can be expensive to calculate, especially for proteins and other large molecules where calculating the potential energy between solute and solvent requires more than half the computation time. To address this problem, we have developed and implemented treecode summation for long‐range interactions and analytically corrected cut‐offs for short‐range interactions to accelerate the potential energy and long‐range asymptotics calculations in non‐periodic 3D‐RISM in the AmberTools molecular modeling suite. For the largest single protein considered in this work, tubulin, the total computation time was reduced by a factor of 4. In addition, parallel calculations with these new methods scale almost linearly and the iterative solver remains the largest impediment to parallel scaling. To demonstrate the utility of our approach for large systems, we used 3D‐RISM to calculate the solvation thermodynamics and density distribution of 7‐ring microtubule, consisting of 910 tubulin dimers, over 1.2 million atoms. 

Abstract Charged residues on the surface of proteins are critical for both protein stability and interactions. However, many proteins contain binding regions with a high net charge that may destabilize the protein but are useful for binding to oppositely charged targets. We hypothesized that these domains would be marginally stable, as electrostatic repulsion would compete with favorable hydrophobic collapse during folding. Furthermore, by increasing the salt concentration, we predict that these protein folds would be stabilized by mimicking some of the favorable electrostatic interactions that take place during target binding. We varied the salt and urea concentrations to probe the contributions of electrostatic and hydrophobic interactions for the folding of the yeast SH3 domain found in Abp1p. The SH3 domain was significantly stabilized with increased salt concentrations due to Debye–Huckel screening and a nonspecific territorial ion‐binding effect. Molecular dynamics and NMR show that sodium ions interact with all 15 acidic residues but do little to change backbone dynamics or overall structure. Folding kinetics experiments show that the addition of urea or salt primarily affects the folding rate, indicating that almost all the hydrophobic collapse and electrostatic repulsion occur in the transition state. After the transition state formation, modest yet favorable short‐range salt bridges are formed along with hydrogen bonds, as the native state fully folds. Thus, hydrophobic collapse offsets electrostatic repulsion to ensure this highly charged binding domain can still fold and be ready to bind to its charged peptide targets, a property that is likely evolutionarily conserved over 1 billion years. 

The title compound, [Al 4 (CH 3 ) 8 (C 2 H 7 N) 2 H 2 ], crystallizes as eight-membered rings with –(CH 3 ) 2 Al–(CH 3 ) 2 N–(CH 3 ) 2 Al– moieties connected by single hydride bridges. In the X-ray structure, the ring has a chair conformation, with the hydride H atoms being close to the plane through the four Al atoms. An optimized structure was also calculated by all-electron density functional theory (DFT) methods, which agrees with the X-ray structure but gives a somewhat different geometry for the hydride bridge. Charges on the individual atoms were determined by valence shell occupancy refinements using MoPro and also by DFT calculations analyzed by several different methods. All methods agree in assigning a positive charge to the Al atoms, negative charges to the C, N, and hydride H atoms, and small positive charges to the methyl H atoms. 

Abstract The nature of halogen bonding under different dielectric conditions remains underexplored, especially for inorganic systems. The structural and energetic properties of model halogen bonded complexes (R₃M−I—NH₃for R=H and F, and M=C, Si, and Ge) are examined computationally for relative permittivities between 1 and 109 using an implicit solvent model. We confirm and assess the exceptionally high maximum potentials at the sigma hole on I (V_s,max) in F₃Ge−I relative to cases where M=C or Si. In particular, Ge far outperforms Si in mediating inductive effects. Linear relationships, typically with R²>0.97, are identified betweenV_s,max, the full point charge on I in R₃M−I, and the interaction energy, and optimized I—N distance in the complexes. An anomalous trend is identified in which, for each M, F₃M−I—NH₃becomeslessstable as the optimized I—N distance getsshorterin different dielectric environments; it is explained using the F−I—NH₃complex as a reference. 

Abstract AutoMeKin2021 is an updated version of tsscds2018, a program for the automated discovery of reaction mechanisms (J. Comput. Chem.2018,39, 1922). This release features a number of new capabilities: rare‐event molecular dynamics simulations to enhance reaction discovery, extension of the original search algorithm to study van der Waals complexes, use of chemical knowledge, a new search algorithm based on bond‐order time series analysis, statistics of the chemical reaction networks, a web application to submit jobs, and other features. The source code, manual, installation instructions and the website link are available at:https://rxnkin.usc.es/index.php/AutoMeKin