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As emerging organic contaminants, siloxanes have severe impacts on the environment and human health. Simple linear siloxanes and derivates, trimethylsilanol (TMS), dimethylsilanediol (DMSD), monomethylsilanetriol (MMST), and dimethylsulfone (DMSO2), are four persistent and common problematic compounds (PCs) from the hydroxylation and sulfuration of polydimethylsiloxanes. Herein, through a two-step computational process, namely Grand Canonical Monte Carlo (GCMC) simulations and machine learning (ML), we systematically screened 50 959 hypothetical pure-silica zeolites and identified 230 preeminent zeolites with excellent adsorption performances with all these four linear siloxanes and derivates. This work vividly demonstrates that the collocation of data-driven science and computational chemistry can greatly accelerate materials discovery and help solve the most challenging separation problems in environmental science. [ABSTRACT FROM AUTHOR]

Correction for 'Machine-learning-assisted screening of pure-silica zeolites for effective removal of linear siloxanes and derivatives' by Shiru Lin et al., J. Mater. Chem. A, 2020, 8, 3228–3237. [ABSTRACT FROM AUTHOR]

We studied the reaction mechanism of di-n-butylmagnesium decomposing into MgH2 in cyclohexane, and found a new route easier than famous β-hydride elimination. Further, we explored the dynamic behavior of graphene nano-flakes and MgH2 in cyclohexane, and gained new insights for efficient hydrogen storage material preparation. [ABSTRACT FROM AUTHOR]

We studied the reaction mechanism of di-n-butylmagnesium decomposing into MgH2 in cyclohexane, and found a new route easier than famous β-hydride elimination. Further, we explored the dynamic behavior of graphene nano-flakes and MgH2 in cyclohexane, and gained new insights for efficient hydrogen storage material preparation.

How structural features observed computationally are connected to excitation-wavelength dependent kinetics observed experimentally remains an unanswered question in the field of ionic liquids. Using molecular dynamics simulation methods and approximated models that simplify the electrostatic interactions in ionic liquids, we discovered that on the timescale shorter than the relaxation time of the photochemical process, the energetic heterogeneity in terms of distribution of excitation energies is the consequence of the structure heterogeneity formed by local arrangement of ions around the solute probe., (This journal is © The Royal Society of Chemistry 2012)