Publications 3
2022
Barnard, T; Tseng, S; Darby, JP; Bartók, AP; Broo, A; Sosso, GC
Leveraging genetic algorithms to maximise the predictive capabilities of the SOAP descriptor Journal Article
In: Molecular Systems Design & Engineering, 2022.
Links | BibTeX | Tags: Machine Learning
@article{Barnard2022GAPredictive,
title = {Leveraging genetic algorithms to maximise the predictive capabilities of the SOAP descriptor},
author = {T Barnard and S Tseng and JP Darby and AP Bartók and A Broo and GC Sosso},
url = {https://sossogroup.uk/wp-content/uploads/2022/11/Barnard2022GAPredictive.pdf},
doi = {10.1039/d2me00149g},
year = {2022},
date = {2022-11-03},
urldate = {2022-11-23},
journal = {Molecular Systems Design & Engineering},
keywords = {Machine Learning},
pubstate = {published},
tppubtype = {article}
}
2020
Barnard, T; Hagan, H; Tseng, S; Sosso, GC
Less may be more: an informed reflection on molecular descriptors for drug design and discovery Journal Article
In: Molecular Systems Design and Engineering, vol. 5, pp. 317-329, 2020.
Links | BibTeX | Tags: Machine Learning
@article{DrugDesign2020Barnard,
title = {Less may be more: an informed reflection on molecular descriptors for drug design and discovery},
author = {T Barnard and H Hagan and S Tseng and GC Sosso},
url = {https://sossogroup.uk/wp-content/uploads/2019/11/MolecularDescriptorsDrugDesignDiscovery.pdf},
doi = {10.1039/C9ME00109C},
year = {2020},
date = {2020-01-12},
journal = {Molecular Systems Design and Engineering},
volume = {5},
pages = {317-329},
keywords = {Machine Learning},
pubstate = {published},
tppubtype = {article}
}
Bosoni, E; Campi, D; Donadio, D; Sosso, G C; Behler, J; Bernasconi, M
Atomistic simulations of thermal conductivity in GeTe nanowires Journal Article
In: Journal of Physics D: Applied Physics, vol. 53, pp. 054001, 2020.
Links | BibTeX | Tags: Machine Learning, PCM
@article{Bosoni2020GeTeNanowires,
title = {Atomistic simulations of thermal conductivity in GeTe nanowires},
author = {E Bosoni and D Campi and D Donadio and G C Sosso and J Behler and M Bernasconi },
url = {https://sossogroup.uk/wp-content/uploads/2019/11/Bosoni_2020_J._Phys._D3A_Appl._Phys._53_054001.pdf},
doi = {10.1088/1361-6463/ab5478},
year = {2020},
date = {2020-01-01},
journal = {Journal of Physics D: Applied Physics},
volume = {53},
pages = {054001},
keywords = {Machine Learning, PCM},
pubstate = {published},
tppubtype = {article}
}
2019
Sosso, GC; Bernasconi, M
Harnessing machine learning potentials to understand the functional properties of phase-change materials Journal Article
In: MRS Bulletin, vol. 44, no. 9, pp. 705-709, 2019.
Links | BibTeX | Tags: Machine Learning, PCM
@article{HarnessingMLSosso2019,
title = {Harnessing machine learning potentials to understand the functional properties of phase-change materials},
author = {GC Sosso and M Bernasconi},
url = { https://doi.org/10.1557/mrs.2019.202
https://soss-2fcc96.ingress-alpha.easywp.com/wp-content/uploads/2019/11/harnessing_machine_learning_potentials_to_understand_the_functional_properties_of_phasechange_materials.pdf},
doi = {10.1557/mrs.2019.202},
year = {2019},
date = {2019-09-05},
journal = {MRS Bulletin},
volume = {44},
number = {9},
pages = {705-709},
keywords = {Machine Learning, PCM},
pubstate = {published},
tppubtype = {article}
}
2022
Barnard, T; Tseng, S; Darby, JP; Bartók, AP; Broo, A; Sosso, GC
Leveraging genetic algorithms to maximise the predictive capabilities of the SOAP descriptor Journal Article
In: Molecular Systems Design & Engineering, 2022.
@article{Barnard2022GAPredictive,
title = {Leveraging genetic algorithms to maximise the predictive capabilities of the SOAP descriptor},
author = {T Barnard and S Tseng and JP Darby and AP Bartók and A Broo and GC Sosso},
url = {https://sossogroup.uk/wp-content/uploads/2022/11/Barnard2022GAPredictive.pdf},
doi = {10.1039/d2me00149g},
year = {2022},
date = {2022-11-03},
urldate = {2022-11-23},
journal = {Molecular Systems Design & Engineering},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2020
Barnard, T; Hagan, H; Tseng, S; Sosso, GC
Less may be more: an informed reflection on molecular descriptors for drug design and discovery Journal Article
In: Molecular Systems Design and Engineering, vol. 5, pp. 317-329, 2020.
@article{DrugDesign2020Barnard,
title = {Less may be more: an informed reflection on molecular descriptors for drug design and discovery},
author = {T Barnard and H Hagan and S Tseng and GC Sosso},
url = {https://sossogroup.uk/wp-content/uploads/2019/11/MolecularDescriptorsDrugDesignDiscovery.pdf},
doi = {10.1039/C9ME00109C},
year = {2020},
date = {2020-01-12},
journal = {Molecular Systems Design and Engineering},
volume = {5},
pages = {317-329},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Bosoni, E; Campi, D; Donadio, D; Sosso, G C; Behler, J; Bernasconi, M
Atomistic simulations of thermal conductivity in GeTe nanowires Journal Article
In: Journal of Physics D: Applied Physics, vol. 53, pp. 054001, 2020.
@article{Bosoni2020GeTeNanowires,
title = {Atomistic simulations of thermal conductivity in GeTe nanowires},
author = {E Bosoni and D Campi and D Donadio and G C Sosso and J Behler and M Bernasconi },
url = {https://sossogroup.uk/wp-content/uploads/2019/11/Bosoni_2020_J._Phys._D3A_Appl._Phys._53_054001.pdf},
doi = {10.1088/1361-6463/ab5478},
year = {2020},
date = {2020-01-01},
journal = {Journal of Physics D: Applied Physics},
volume = {53},
pages = {054001},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2019
Sosso, GC; Bernasconi, M
Harnessing machine learning potentials to understand the functional properties of phase-change materials Journal Article
In: MRS Bulletin, vol. 44, no. 9, pp. 705-709, 2019.
@article{HarnessingMLSosso2019,
title = {Harnessing machine learning potentials to understand the functional properties of phase-change materials},
author = {GC Sosso and M Bernasconi},
url = { https://doi.org/10.1557/mrs.2019.202
https://soss-2fcc96.ingress-alpha.easywp.com/wp-content/uploads/2019/11/harnessing_machine_learning_potentials_to_understand_the_functional_properties_of_phasechange_materials.pdf},
doi = {10.1557/mrs.2019.202},
year = {2019},
date = {2019-09-05},
journal = {MRS Bulletin},
volume = {44},
number = {9},
pages = {705-709},
keywords = {},
pubstate = {published},
tppubtype = {article}
}