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1. Introducing DDEC6 atomic population analysis: part 4. Efficient parallel computation of net atomic charges, atomic spin moments, bond orders, and more

   https://doi.org/10.1039/c7ra11829e  

   Limas, Nidia Gabaldon ; Manz, Thomas A. ( January 2018 , RSC Advances)

   The DDEC6 method is one of the most accurate and broadly applicable atomic population analysis methods. It works for a broad range of periodic and non-periodic materials with no magnetism, collinear magnetism, and non-collinear magnetism irrespective of the basis set type. First, we show DDEC6 charge partitioning to assign net atomic charges corresponds to solving a series of 14 Lagrangians in order. Then, we provide flow diagrams for overall DDEC6 analysis, spin partitioning, and bond order calculations. We wrote an OpenMP parallelized Fortran code to provide efficient computations. We show that by storing large arrays as shared variables in cachemore »line friendly order, memory requirements are independent of the number of parallel computing cores and false sharing is minimized. We show that both total memory required and the computational time scale linearly with increasing numbers of atoms in the unit cell. Using the presently chosen uniform grids, computational times of ∼9 to 94 seconds per atom were required to perform DDEC6 analysis on a single computing core in an Intel Xeon E5 multi-processor unit. Parallelization efficiencies were usually >50% for computations performed on 2 to 16 cores of a cache coherent node. As examples we study a B-DNA decamer, nickel metal, supercells of hexagonal ice crystals, six X@C 60 endohedral fullerene complexes, a water dimer, a Mn 12 -acetate single molecule magnet exhibiting collinear magnetism, a Fe 4 O 12 N 4 C 40 H 52 single molecule magnet exhibiting non-collinear magnetism, and several spin states of an ozone molecule. Efficient parallel computation was achieved for systems containing as few as one and as many as >8000 atoms in a unit cell. We varied many calculation factors ( e.g. , grid spacing, code design, thread arrangement, etc. ) and report their effects on calculation speed and precision. We make recommendations for excellent performance.« less
2. Multifaceted Sn–Sn bonding in the solid state. Synthesis and structural characterization of four new Ca–Li–Sn compounds

   https://doi.org/10.1039/C9DT02803J  

   Ovchinnikov, Alexander ; Bobev, Svilen ( October 2019 , Dalton Transactions)

   Four novel ternary phases have been prepared in the system Ca–Li–Sn using both the metal flux method and conventional high-temperature synthesis. Each of the obtained compositions represents its own (new) structure type, and the structures feature distinct polyanionic Sn units. Ca 4 LiSn 6 (space group Pbcm , Pearson symbol oP 44) accommodates infinite chains, made up of cyclopentane-like [Sn 5 ]-rings, which are bridged by Sn atoms. The Sn atoms in this structure are two- and three-bonded. The anionic substructure of Ca 9 Li 6+x Sn 13–x ( x ≈ 0.28, space group C 2/ m , Pearson symbolmore »mS 56) displays extensive mixing of Li and Sn and combination of single-bonded and hypervalent interactions between the Sn atoms. Hypervalent bonding is also pronounced in the structure of the third compound, Ca 2 LiSn 3 (space group Pmm 2, Pearson symbol oP 18) with quasi-two-dimensional polyanionic subunits and a variety of coordination environments of the Sn atoms. One-dimensional [Sn 10 ]-chains with an intricate topology of cis - and trans -Sn–Sn bonds exist in the structure of Ca 9–x Li 2 Sn 10 ( x ≈ 0.16, space group C 2/ m , Pearson symbol mS 42), and the Sn–Sn bonding in this case demonstrates the characteristics of an intermediate between single- and double- bond-order. The peculiarities of the bonding are discussed in the context of the Zintl approach, which captures the essence of the main chemical interactions. The electronic structures of all four compounds have also been analyzed in full detail using first-principles calculations.« less
3. Origins and properties of the tetrel bond

   https://doi.org/10.1039/D1CP00242B  

   Scheiner, Steve ( March 2021 , Physical Chemistry Chemical Physics)

   The tetrel bond (TB) recruits an element drawn from the C, Si, Ge, Sn, Pb family as electron acceptor in an interaction with a partner Lewis base. The underlying principles that explain this attractive interaction are described in terms of occupied and vacant orbitals, total electron density, and electrostatic potential. These principles facilitate a delineation of the factors that feed into a strong TB. The geometric deformation that occurs within the tetrel-bearing Lewis acid monomer is a particularly important issue, with both primary and secondary effects. As a first-row atom of low polarizability, C is a reluctant participant in TBs,more »but its preponderance in organic and biochemistry make it extremely important that its potential in this regard be thoroughly understood. The IR and NMR manifestations of tetrel bonding are explored as spectroscopy offers a bridge to experimental examination of this phenomenon. In addition to the most common σ-hole type TBs, discussion is provided of π-hole interactions which are a result of a common alternate covalent bonding pattern of tetrel atoms.« less
4. Predicting Outcomes of Chemical Reactions: A Seq2Seq Approach with Multi-view Attention and Edge Embedding

   Xiao, Xia ; Shang, Chao ; Bi, Jinbo ; Rajasekaran, Sanguthevar ( July 2020 , Proceedings of International Joint Conference on Neural Networks)

   Abstract—Materials Genomics initiative has the goal of rapidly synthesizing materials with a given set of desired properties using data science techniques. An important step in this direction is the ability to predict the outcomes of complex chemical reactions. Some graph-based feature learning algorithms have been proposed recently. However, the comprehensive relationship between atoms or structures is not learned properly and not explainable, and multiple graphs cannot be handled. In this paper, chemical reaction processes are formulated as translation processes. Both atoms and edges are mapped to vectors represent- ing the structural information. We employ the graph convolution layers to learnmore »meaningful information of atom graphs, and further employ its variations, message passing networks (MPNN) and edge attention graph convolution network (EAGCN) to learn edge representations. Particularly, multi-view EAGCN groups and maps edges to a set of representations for the properties of the chemical bond between atoms from multiple views. Each bond is viewed from its atom type, bond type, distance and neighbor environment. The final node and edge representations are mapped to a sequence defined by the SMILES of the molecule and then fed to a decoder model with attention. To make full usage of multi-view information, we propose multi-view attention model to handle self correlation inside each atom or edge, and mutual correlation between edges and atoms, both of which are important in chemical reaction processes. We have evaluated our method on the standard benchmark datasets (that have been used by all the prior works), and the results show that edge embedding with multi-view attention achieves superior accuracy compared to existing techniques.« less
5. An overview of the uses of per- and polyfluoroalkyl substances (PFAS)

   https://doi.org/10.1039/d0em00291g  

   Glüge, Juliane ; Scheringer, Martin ; Cousins, Ian T. ; DeWitt, Jamie C. ; Goldenman, Gretta ; Herzke, Dorte ; Lohmann, Rainer ; Ng, Carla A. ; Trier, Xenia ; Wang, Zhanyun ( December 2020 , Environmental Science: Processes & Impacts)

   Per- and polyfluoroalkyl substances (PFAS) are of concern because of their high persistence (or that of their degradation products) and their impacts on human and environmental health that are known or can be deduced from some well-studied PFAS. Currently, many different PFAS (on the order of several thousands) are used in a wide range of applications, and there is no comprehensive source of information on the many individual substances and their functions in different applications. Here we provide a broad overview of many use categories where PFAS have been employed and for which function; we also specify which PFAS havemore »been used and discuss the magnitude of the uses. Despite being non-exhaustive, our study clearly demonstrates that PFAS are used in almost all industry branches and many consumer products. In total, more than 200 use categories and subcategories are identified for more than 1400 individual PFAS. In addition to well-known categories such as textile impregnation, fire-fighting foam, and electroplating, the identified use categories also include many categories not described in the scientific literature, including PFAS in ammunition, climbing ropes, guitar strings, artificial turf, and soil remediation. We further discuss several use categories that may be prioritised for finding PFAS-free alternatives. Besides the detailed description of use categories, the present study also provides a list of the identified PFAS per use category, including their exact masses for future analytical studies aiming to identify additional PFAS.« less