{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/303691"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/303691","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"Fitting Interatomic Potentials to Reproduce Phase Transitions","abstract":"Due to the high computational demand of quantum mechanical simulations, researchers still rely on models for atomic interactions to simulate a large number of atoms. These so called “interatomic potentials” take a variety of forms ranging from the simple Lennard-Jones potential to machine learning potentials. They are usually fitted for specific structures as well as pressure and temperature realms and do not necessarily reproduce the full experimentally known solid and liquid phase diagram. There have been limited trials of fitting the parameters of interatomic potentials to phase transitions. In this work, I present improvements upon two already existing potentials from the literature – a CuAu potential and a Ti potential. These potentials are modified so that they reproduce experimental phase transitions better than before. For the CuAu potential, I fit the eutectic melting curve using my own implementation of the Nelder-Mead algorithm. The Ti potential is modified to predict a triple point which is in qualitative agreement with experimental predictions. To calculate phase transitions, I use the nested sampling algorithm which was already established in the literature. The Ti nested sampling results are verified with thermodynamic integration. My Nelder-Mead implementation allows for semi-automatic submission and analysis of the nested sampling runs. Both potentials are improved considerably. The new CuAu potential now accurately reproduces the melting curve for the alloy compositions used in the fitting procedure. The new Ti potential now – as opposed to before the modifications – predicts a triple point which is in qualitative accordance with experimental predictions. My work demonstrates how the transferability of potentials can be improved by just slight modifications to the original parameters using experimental data of the phase diagram. The Nelder-Mead implementation used for the CuAu potential could be used to improve other potentials. To fit more complex systems, the way the objective function is calculated could be upgraded in future.","abstract_html":"Due to the high computational demand of quantum mechanical simulations, researchers still rely on models for atomic interactions to simulate a large number of atoms. These so called “interatomic potentials” take a variety of forms ranging from the simple Lennard-Jones potential to machine learning potentials. They are usually fitted for specific structures as well as pressure and temperature realms and do not necessarily reproduce the full experimentally known solid and liquid phase diagram. There have been limited trials of fitting the parameters of interatomic potentials to phase transitions. In this work, I present improvements upon two already existing potentials from the literature – a CuAu potential and a Ti potential. These potentials are modified so that they reproduce experimental phase transitions better than before. For the CuAu potential, I fit the eutectic melting curve using my own implementation of the Nelder-Mead algorithm. The Ti potential is modified to predict a triple point which is in qualitative agreement with experimental predictions. To calculate phase transitions, I use the nested sampling algorithm which was already established in the literature. The Ti nested sampling results are verified with thermodynamic integration. My Nelder-Mead implementation allows for semi-automatic submission and analysis of the nested sampling runs. Both potentials are improved considerably. The new CuAu potential now accurately reproduces the melting curve for the alloy compositions used in the fitting procedure. The new Ti potential now – as opposed to before the modifications – predicts a triple point which is in qualitative accordance with experimental predictions. My work demonstrates how the transferability of potentials can be improved by just slight modifications to the original parameters using experimental data of the phase diagram. The Nelder-Mead implementation used for the CuAu potential could be used to improve other potentials. To fit more complex systems, the way the objective function is calculated could be upgraded in future.","abstract_has_math":false,"creators":["Schlegel, Martin"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Csányi, Gábor"],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-04-25","date_published":"2020-04-25","updated_at":"2026-07-22T22:23:54Z","subjects":["interatomic potentials","phase diagrams","phase transitions","copper","gold","titanium","nested sampling","Nelder-Mead method","fitting interatomic potentials","CuAu","Ti","melting curve","eutectic"],"languages":["en"],"rights":[],"rights_urls":["https://www.repository.cam.ac.uk/bitstreams/b7b5540c-c596-462d-9c18-54bdf0104046/download","https://creativecommons.org/licenses/by/4.0/"],"identifier_entries":[{"key":"dc:creator.authoridentifier","label":"Author Identifier","values":["0000000198017377","0000000281802034"],"render_values":[{"text":"0000-0001-9801-7377","href":"https://orcid.org/0000-0001-9801-7377","code":true},{"text":"0000-0002-8180-2034","href":"https://orcid.org/0000-0002-8180-2034","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.50769","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Csányi, Gábor"]},{"key":"dc:contributor.sponsor","label":"Sponsor","values":["EPSRC Centre for Doctoral Training in Computational Methods for Materials Science under grant number EP/L015552/1. 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