AI4Green: An Open-Source ELN for Green and Sustainable Chemistry.

An Electronic Laboratory Notebook (ELN) combining features, including data archival, collaboration tools, and green and sustainability metrics for organic chemistry, is presented. AI4Green is a web-based application, available as open-source code and free to use. It offers the core functionality of an ELN, namely, the ability to store reactions securely and share them among different members of a research team. As users plan their reactions and record them in the ELN, green and sustainable chemistry is encouraged by automatically calculating green metrics and color-coding hazards, solvents, and reaction conditions. The interface links a database constructed from data extracted from PubChem, enabling the automatic collation of information for reactions. The application's design facilitates the development of auxiliary sustainability applications, such as our Solvent Guide. As more reaction data are captured, subsequent work will include providing "intelligent" sustainability suggestions to the user.

Dynamic tilting in perovskites.

A new computational analysis of tilt behaviour in perovskites is presented. This includes the development of a computational program - PALAMEDES - to extract tilt angles and the tilt phase from molecular dynamics simulations. The results are used to generate simulated selected-area electron and neutron diffraction patterns which are compared with experimental patterns for CaTiO3. The simulations not only reproduced all symmetrically allowed superlattice reflections associated with tilt but also showed local correlations that give rise to symmetrically forbidden reflections and the kinematic origin of diffuse scattering.

A high throughput computational investigation of the solid solution mechanisms of actinides and lanthanides in zirconolite.

In this work, we perform a theoretical investigation of the actinide and lanthanide solid solution mechanisms of zirconolite-2M, prototypically CaZrTi2O7, as a candidate immobilisation matrix for plutonium. Solid solution energies were calculated using static atomistic simulations by means of the General Utility Lattice Program, for formulations of relevance to ceramic wasteform deployment, with substitution on the Ca2+ and Zr4+ sites by Ce4+, Pu4+, Th4+, and U4+, and appropriate charge balance by substitution of Al3+ or Fe3+ on Ti4+ sites. In simple solid solutions involving substitution on the Zr4+ site, we found that whereas substitution of Ce4+, U4+ and Pu4+ were energetically favoured, substitution of Th4+ was not energetically favoured. For more complex solid solutions involving Ce4+, Pu4+, Th4+, and U4+ substitution on the Ca2+ site, we found the most energetically favoured scheme involved co-substitution of Al3+ or Fe3+ on the five-fold co-ordinate Ti4+ site in the zirconolite-2M structure. Comparison of these computational data with experimental evidence, where available, demonstrated broad agreement. Consequently, this study provides useful insight into formulation design and the efficacy of Ce4+, U4+ and Th4+ as Pu4+ surrogates in zirconolite-2M ceramic wasteforms for plutonium disposition.

Unified approach to multipolar polarisation and charge transfer for ions: microhydrated Na+.

Electrostatic effects play a large part in determining the properties of chemical systems. In addition, a treatment of the polarisation of the electron distribution is important for many systems, including solutions of monatomic ions. Typically employed methods for describing polarisable electrostatics use a number of approximations, including atom-centred point charges and polarisation methods that require iterative calculation on the fly. We present a method that treats charge transfer and polarisation on an equal footing. Atom-centred multipole moments describe the charge distribution of a chemical system. The variation of these multipole moments with the geometry of the surrounding atoms is captured by the machine learning method kriging. The interatomic electrostatic interaction can be computed using the resulting predicted multipole moments. This allows the treatment of both intra- and interatomic polarisation with the same method. The proposed method does not return explicit polarisabilities but instead, predicts the result of the polarisation process. An application of this new method to the sodium cation in a water environment is described. The performance of the method is assessed by comparison of its predictions of atomic multipole moments and atom-atom electrostatic interaction energies to exact results. The kriging models are able to predict the electrostatic interaction energy between the ion and all water atoms within 4 kJ mol(-1) for any of the external test set Na(+)(H2O)6 configurations.

A Multi-Objective Approach to Force Field Optimization: Structures and Spin State Energetics of d(6) Fe(II) Complexes.

The next generation of force fields (FFs), regardless of the accuracy of the potential energy representation, will always have parameters that must be fitted in order to reproduce experimental and/or ab initio data accurately. Single objective methods have been used for many years to automate the obtaining of parameters, but this leads to ambiguity. The solution depends on the chosen weights and is therefore not unique. There have been few advances in solving this problem, which thus remains a major hurdle for the development of empirical FF methods. We propose a solution based on multi-objective evolutionary algorithms (MOEAs). MOEAs allow the FF to be tuned against the desired objectives and offer a powerful, efficient, and automated means to reparameterize FFs, or even discover the parameters for a new potential. Here, we illustrate the application of MOEAs by reparameterizing the ligand field molecular mechanics (LFMM) FF recently reported for modeling spin crossover in iron(II)-amine complexes (Deeth et al. J. Am. Chem. Soc.2010, 132, 6876). We quickly recover the performance of the original parameter set and then significantly improve it to reproduce the geometries and spin state energy differences of an extended series of complexes with RMSD errors in Fe-N and N-N distances reduced from 0.06 Å to 0.03 Å and spin state energy difference RMSDs reduced from 1.5 kcal mol(-1) to 0.2 kcal mol(-1). The new parameter sets highlight, and help resolve, shortcomings both in the non-LFMM FF parameters and in the interpretation of experimental data for several other Fe(II)N6 amine complexes not used in the FF optimization.