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1.  Transition from exo- to endo- Cu absorption in CuSin clusters: A Genetic Algorithms Density Functional Theory (DFT) Study 
Molecular simulation  2011;37(8):678-688.
The characterization and prediction of the structures of metal silicon clusters is important for nanotechnology research because these clusters can be used as building blocks for nano devices, integrated circuits and solar cells. Several authors have postulated that there is a transition between exo to endo absorption of Cu in Sin clusters and showed that for n larger than 9 it is possible to find endohedral clusters. Unfortunately, no global searchers have confirmed this observation, which is based on local optimizations of plausible structures. Here we use parallel Genetic Algorithms (GA), as implemented in our MGAC software, directly coupled with DFT energy calculations to show that the global search of CuSin cluster structures does not find endohedral clusters for n < 8 but finds them for n ≥ 10.
doi:10.1080/08927020903583830
PMCID: PMC3139224  PMID: 21785526
copper-silicon clusters; genetic algorithms; global optimization
2.  Towards crystal structure prediction of complex organic compounds – a report on the fifth blind test 
Following on from the success of the previous crystal structure prediction blind tests (CSP1999, CSP2001, CSP2004 and CSP2007), a fifth such collaborative project (CSP2010) was organized at the Cambridge Crystallographic Data Centre. A range of methodologies was used by the participating groups in order to evaluate the ability of the current computational methods to predict the crystal structures of the six organic molecules chosen as targets for this blind test. The first four targets, two rigid molecules, one semi-flexible molecule and a 1:1 salt, matched the criteria for the targets from CSP2007, while the last two targets belonged to two new challenging categories – a larger, much more flexible molecule and a hydrate with more than one polymorph. Each group submitted three predictions for each target it attempted. There was at least one successful prediction for each target, and two groups were able to successfully predict the structure of the large flexible molecule as their first place submission. The results show that while not as many groups successfully predicted the structures of the three smallest molecules as in CSP2007, there is now evidence that methodologies such as dispersion-corrected density functional theory (DFT-D) are able to reliably do so. The results also highlight the many challenges posed by more complex systems and show that there are still issues to be overcome.
doi:10.1107/S0108768111042868
PMCID: PMC3222142  PMID: 22101543
3.  Towards crystal structure prediction of complex organic compounds – a report on the fifth blind test 
The results of the fifth blind test of crystal structure prediction, which show important success with more challenging large and flexible molecules, are presented and discussed.
Following on from the success of the previous crystal structure prediction blind tests (CSP1999, CSP2001, CSP2004 and CSP2007), a fifth such collaborative project (CSP2010) was organized at the Cambridge Crystallographic Data Centre. A range of methodologies was used by the participating groups in order to evaluate the ability of the current computational methods to predict the crystal structures of the six organic molecules chosen as targets for this blind test. The first four targets, two rigid molecules, one semi-flexible molecule and a 1:1 salt, matched the criteria for the targets from CSP2007, while the last two targets belonged to two new challenging categories – a larger, much more flexible molecule and a hydrate with more than one polymorph. Each group submitted three predictions for each target it attempted. There was at least one successful prediction for each target, and two groups were able to successfully predict the structure of the large flexible molecule as their first place submission. The results show that while not as many groups successfully predicted the structures of the three smallest molecules as in CSP2007, there is now evidence that methodologies such as dispersion-corrected density functional theory (DFT-D) are able to reliably do so. The results also highlight the many challenges posed by more complex systems and show that there are still issues to be overcome.
doi:10.1107/S0108768111042868
PMCID: PMC3222142  PMID: 22101543
prediction; blind test; polymorph; crystal structure prediction
4.  Crystal Structure Prediction (CSP) of Flexible Molecules using Parallel Genetic Algorithms with a Standard Force Field 
Journal of computational chemistry  2009;30(13):1973-1985.
This paper describes the application of our distributed computing framework for crystal structure prediction (CSP), Modified Genetic Algorithms for Crystal and Cluster Prediction (MGAC) to predict the crystal structure of flexible molecules using the General Amber Force Field (GAFF) and the CHARMM program. The MGAC distributed computing framework which includes a series of tightly integrated computer programs for generating the molecule’s force field, sampling crystal structures using a distributed parallel genetic algorithm, local energy minimization of the structures followed by the classifying, sorting and archiving of the most relevant structures. Our results indicate that the method can consistently find the experimentally known crystal structures of flexible molecules, but the number of missing structures and poor ranking observed in some crystals show the need for further improvement of the potential.
doi:10.1002/jcc.21189
PMCID: PMC2720422  PMID: 19130496

Results 1-4 (4)