02373nas a2200301 4500008004100000022001400041245011000055210006900165260000800234490000700242520133400249653001901583653002201602653003701624653001601661653002901677653001201706653002601718653001501744653006101759100001901820700001901839700001901858700002401877700002101901700001901922856013001941 2017 eng d a1477-922600aUnprecedented solvent induced inter-conversion between monomeric and dimeric silylene-zinc iodide adducts0 aUnprecedented solvent induced interconversion between monomeric  cSEP0 v463 a

Usually, when a silylene reacts with a transition metal Lewis acid, it forms an adduct which could be either monomeric or dimeric. However, we present here that a silylene, [PhC(NtBu)(2)SiN(SiMe3)(2)] can form both monomeric [PhC(NtBu)(2)Si{N(SiMe3)(2)} -> ZnI2]center dot THF (1) and dimeric [{PhC(NtBu)(2)}(N(SiMe3)(2))SiZnI,(mu-I)](2) (2) adducts upon reaction with ZnI2. The formation of 1 and 2 relies upon the solvent used for the reaction or crystallization. When the crystallization is carried out in THF complex 1 is formed, however, when the reaction and crystallization are performed in acetonitrile complex 2 is obtained. Both 1 and 2 were structurally authenticated and the nature of the Si-Zn bond in these complexes was determined by quantum chemical calculations. In addition, a spontaneous inter-conversion between 1 and 2 just by changing the solvents has been also observed; a feature presently not known for silylene-transition metal Lewis adducts.

 

10aBis(Silylene )10aCarbene Complexes10aCrystal -structure Determination10aDative bond10aLewis acid base reaction10aLigands10aMain- group compounds10aReactivity10aSilicon(II) Bis(Trimethylsilyl)Amide; Carbonyl-Complexes1 aYadav, Sandeep1 aSangtani, Ekta1 aDhawan, Diksha1 aGonnade, Rajesh, G.1 aGhosh, Debashree1 aSen, Sakya, S. uhttps://library.ncl.res.in/content/unprecedented-solvent-induced-inter-conversion-between-monomeric-and-dimeric-silylene-zinc01825nas a2200181 4500008004100000245008000041210006900121260000800190300001600198490000700214520121800221100001601439700001901455700001801474700002101492700002101513856010901534 2018 eng d00aMachine learning prediction of interaction energies in rigid water clusters0 aMachine learning prediction of interaction energies in rigid wat cSEP a22987-229960 v203 aClassical force fields form a computationally efficient avenue for calculating the energetics of large systems. However, due to the constraints of the underlying analytical form, it is sometimes not accurate enough. Quantum mechanical (QM) methods, although accurate, are computationally prohibitive for large systems. In order to circumvent the bottle-neck of interaction energy estimation of large systems, data driven approaches based on machine learning (ML) have been employed in recent years. In most of these studies, the method of choice is artificial neural networks (ANN). In this work, we have shown an alternative ML method, support vector regression (SVR), that provides comparable accuracy with better computational efficiency. We have further used many body expansion (MBE) along with SVR to predict interaction energies in water clusters (decamers). In the case of dimer and trimer interaction energies, the root mean square errors (RMSEs) of the SVR based scheme are 0.12 kcal mol(-1) and 0.34 kcal mol(-1), respectively. We show that the SVR and MBE based scheme has a RMSE of 2.78% in the estimation of decamer interaction energy against the parent QM method in a computationally efficient way.1 aBose, Samik1 aDhawan, Diksha1 aNandi, Sutanu1 aSarkar, Ram, Rup1 aGhosh, Debashree uhttps://library.ncl.res.in/content/machine-learning-prediction-interaction-energies-rigid-water-clusters