CrystEngComm, 2017, 19, 5336 – 5340 [ doi:10.1039/C7CE00587C ]
A data-driven approach to predicting co-crystal formation reduces the number of experiments required to successfully produce new co-crystals. A machine learning algorithm trained on an in-house set of co-crystallization experiments results in a 2.6-fold enrichment of successful co-crystal formation in a ranked list of … Read the rest
CrystEngComm, 2017,19, 3737-3745 [ doi:10.1039/C7CE00738H ]
We present here the crystallisation outcomes for 319 publicly available compounds in up to 18 different solvents spread over 5710 individual single solvent evaporation trials. The recorded data is part of a much larger, corresponding in-house database and includes both positive as well as negative crystallisation … Read the rest
Acta. Cryst. (2016) B72 661-683 (Feature Article) [ doi:10.1107/S2052520616012890 ]
Direct determination of the Flack parameter as part of the structure refinement procedure usually gives different, though similar, values to post-refinement methods. The source of this discrepancy has been probed by analysing a range of data sets taken from the recent literature. Most significantly, … Read the rest
Acta. Cryst. (2016) B72(4), 439-459 [ doi:10.1107/S2052520616007447 ] A. M. Reilly, R. I. Cooper, C. S. Adjiman, S. Bhattacharya, A. D. Boese, J. G. Brandenburg, P. J. Bygrave, R. Bylsma, J. E. Campbell, R. Car, D. H. Case, R. Chadha, J. C. Cole, K. Cosburn, H. M. Cuppen, F. Curtis, G. M. Day, … Read the rest
Acta. Cryst. (2016) C72, 261-267 [ doi:10.1107/S2053229616003570 ]
A study of post-refinement absolute structure determination using previously published data was carried out using the CRYSTALS software package. We show that absolute structure determination may be carried out optimally using the analyses available in CRYSTALS, and that it is not necessary to have the … Read the rest
Chemistry Central Journal 2015, 9:30 [ doi:10.1186/s13065-015-0105-4 ]
The size and complexity of molecules being studied by single crystal diffraction is growing year by year, resulting in an increase in the difficulties encountered during structure determination. From the crystallisation itself and sample handling, to structure solution and refinement, specific problems due to larger molecules … Read the rest
Annotated articles are based on research from a range of Royal Society of Chemistry journals that has been re-written into a standard, accessible format.
An annotated article on predicting and controlling the crystallinity of molecular materials by Jerome Wicker and Richard Cooper aims to help readers to understand the research the journal article is based … Read the rest
CrystEngComm (2015) 17, 1927-1934 [ doi:10.1039/C4CE01912A ]
Machine learning algorithms can be used to create models which separate molecular materials which will form good-quality crystals from those that will not, and predict how synthetic modifications will change the crystallinity.