{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/358785"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/358785","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"Ab initio Study of Atomic Dynamics and Thermal Properties of Inorganic Clathrates, Chalcogenides and Perovskite Oxides","abstract":"Inorganic semiconductors are important materials for devices used every day. One property that is crucial to device performance is thermal behaviour. This can be directly related to the efficiency of devices; for example, in thermoelectric power generators, a lower thermal conductivity gives a larger thermometric figure of merit. Or they can indirectly affect the device performance, such as device stability at a certain operating temperature or device lifetime. With the help of computer simulations, one can test theories of material properties and design new functional materials. In this thesis, I present first-principles studies of three types of inorganic materials, namely inorganic clathrates, chalcogenides and perovskite oxides. Inorganic clathrates are promising candidates for thermoelectric applications due to their low thermal conductivity. In order to test approaches that improve the thermoelectric figure of merit of the inorganic clathrate, Ba8Ga16Ge30 (BGG), I generated an amorphous model of BGG and examined its structural, electronic and vibrational properties. Although amorphous BGG could have a lower thermal conductivity, the structure is not stable at the high operating temperatures for inorganic clathrates in thermoelectric power generators. Chalcogenide materials, especially Ge-Sb-Te (GST) alloys, are good candidates for phase- change memory devices. Their thermal properties affect device stability and operational speed. Many computer-simulation methods can be used to calculate the thermal properties of GST, but most are expensive computationally. Here, I compared results from a direct method and the fluctuation-dissipation theorem with packages employing a machine-learning algorithm, to explore computationally cost-effective approaches that give reasonable thermal-property results. The last materials that I studied are perovskite oxides. Perovskite oxides have been widely examined for applications in catalysis, solar-energy harvesting and superconductivity. Obtaining accurate lattice-dynamics results is important in order to understand their thermal properties. Disagreement between experimental and computer-simulation results was found for the phonon-dispersion curves of BaZrO<sub>3</sub> and BaSnO<sub>3</sub>. This results from an inaccurate description of the structure simulated using some exchange-correlation functionals in DFT calculations. This reminds us that, although approximations in quantum-mechanical theories can speed up simulation times, checking whether certain approximations work in some scenarios is necessary. From comparing the vibrational and theraml properties calcualted through MD-Green Kubo, finite displacements-LBTE and a machine learning code HIPHIVE. The following conclusions are reached: for high disordered materials like amorphous BGG and cubic Ge<sub>2</sub>Sb<sub>2</sub>Te<sub>4.9</sub>, molecular dynamics are the most efficient and accurate way among the three; For high symmetrical materials like GeTe, Sb<sub>2</sub>Te<sub>3</sub> and the Kooi structure, the finite displacements are the most appropriate to use and HIPHIVE is useful for calculating vibrational and thermal properties of metastable structures at the finite temperature.","abstract_html":"Inorganic semiconductors are important materials for devices used every day. One property that is crucial to device performance is thermal behaviour. This can be directly related to the efficiency of devices; for example, in thermoelectric power generators, a lower thermal conductivity gives a larger thermometric figure of merit. Or they can indirectly affect the device performance, such as device stability at a certain operating temperature or device lifetime. With the help of computer simulations, one can test theories of material properties and design new functional materials. In this thesis, I present first-principles studies of three types of inorganic materials, namely inorganic clathrates, chalcogenides and perovskite oxides. Inorganic clathrates are promising candidates for thermoelectric applications due to their low thermal conductivity. In order to test approaches that improve the thermoelectric figure of merit of the inorganic clathrate, Ba8Ga16Ge30 (BGG), I generated an amorphous model of BGG and examined its structural, electronic and vibrational properties. Although amorphous BGG could have a lower thermal conductivity, the structure is not stable at the high operating temperatures for inorganic clathrates in thermoelectric power generators. Chalcogenide materials, especially Ge-Sb-Te (GST) alloys, are good candidates for phase- change memory devices. Their thermal properties affect device stability and operational speed. Many computer-simulation methods can be used to calculate the thermal properties of GST, but most are expensive computationally. Here, I compared results from a direct method and the fluctuation-dissipation theorem with packages employing a machine-learning algorithm, to explore computationally cost-effective approaches that give reasonable thermal-property results. The last materials that I studied are perovskite oxides. Perovskite oxides have been widely examined for applications in catalysis, solar-energy harvesting and superconductivity. Obtaining accurate lattice-dynamics results is important in order to understand their thermal properties. Disagreement between experimental and computer-simulation results was found for the phonon-dispersion curves of BaZrO&lt;sub&gt;3&lt;/sub&gt; and BaSnO&lt;sub&gt;3&lt;/sub&gt;. This results from an inaccurate description of the structure simulated using some exchange-correlation functionals in DFT calculations. This reminds us that, although approximations in quantum-mechanical theories can speed up simulation times, checking whether certain approximations work in some scenarios is necessary. From comparing the vibrational and theraml properties calcualted through MD-Green Kubo, finite displacements-LBTE and a machine learning code HIPHIVE. The following conclusions are reached: for high disordered materials like amorphous BGG and cubic Ge&lt;sub&gt;2&lt;/sub&gt;Sb&lt;sub&gt;2&lt;/sub&gt;Te&lt;sub&gt;4.9&lt;/sub&gt;, molecular dynamics are the most efficient and accurate way among the three; For high symmetrical materials like GeTe, Sb&lt;sub&gt;2&lt;/sub&gt;Te&lt;sub&gt;3&lt;/sub&gt; and the Kooi structure, the finite displacements are the most appropriate to use and HIPHIVE is useful for calculating vibrational and thermal properties of metastable structures at the finite temperature.","abstract_has_math":false,"creators":["Hu, Yuchen"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Elliott, Stephen"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-09-30","date_published":"2021-09-30","updated_at":"2026-07-22T22:24:32Z","subjects":["Ab initio","Chalcogenides","First Principles","Inorganic Clathrates","Perovskite Oxides","Thermal Properties"],"languages":["eng"],"rights":[],"rights_urls":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/b126b6fb-47a2-4904-82fc-2c068790078b/download","https://www.rioxx.net/licenses/all-rights-reserved/"],"identifier_entries":[]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.102235","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Elliott, Stephen"]},{"key":"dc:creator","label":"Author","values":["Hu, Yuchen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2021-09-30"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cambridge"]},{"key":"dc:relation.isreferencedby.uri","label":"Dc Relation Isreferencedby URI","values":["https://www.repository.cam.ac.uk/handle/1810/358785"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Ab initio","Chalcogenides","First Principles","Inorganic Clathrates","Perovskite Oxides","Thermal Properties"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/b126b6fb-47a2-4904-82fc-2c068790078b/download","https://www.rioxx.net/licenses/all-rights-reserved/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.17863/CAM.102235"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/d25a3a7c-956f-47b6-be89-7096b55b6d65/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Inorganic semiconductors are important materials for devices used every day. One property that is crucial to device performance is thermal behaviour. This can be directly related to the efficiency of devices; for example, in thermoelectric power generators, a lower thermal conductivity gives a larger thermometric figure of merit. Or they can indirectly affect the device performance, such as device stability at a certain operating temperature or device lifetime. With the help of computer simulations, one can test theories of material properties and design new functional materials. In this thesis, I present first-principles studies of three types of inorganic materials, namely inorganic clathrates, chalcogenides and perovskite oxides. Inorganic clathrates are promising candidates for thermoelectric applications due to their low thermal conductivity. In order to test approaches that improve the thermoelectric figure of merit of the inorganic clathrate, Ba8Ga16Ge30 (BGG), I generated an amorphous model of BGG and examined its structural, electronic and vibrational properties. Although amorphous BGG could have a lower thermal conductivity, the structure is not stable at the high operating temperatures for inorganic clathrates in thermoelectric power generators. Chalcogenide materials, especially Ge-Sb-Te (GST) alloys, are good candidates for phase- change memory devices. Their thermal properties affect device stability and operational speed. Many computer-simulation methods can be used to calculate the thermal properties of GST, but most are expensive computationally. Here, I compared results from a direct method and the fluctuation-dissipation theorem with packages employing a machine-learning algorithm, to explore computationally cost-effective approaches that give reasonable thermal-property results. The last materials that I studied are perovskite oxides. Perovskite oxides have been widely examined for applications in catalysis, solar-energy harvesting and superconductivity. Obtaining accurate lattice-dynamics results is important in order to understand their thermal properties. Disagreement between experimental and computer-simulation results was found for the phonon-dispersion curves of BaZrO<sub>3</sub> and BaSnO<sub>3</sub>. This results from an inaccurate description of the structure simulated using some exchange-correlation functionals in DFT calculations. This reminds us that, although approximations in quantum-mechanical theories can speed up simulation times, checking whether certain approximations work in some scenarios is necessary. From comparing the vibrational and theraml properties calcualted through MD-Green Kubo, finite displacements-LBTE and a machine learning code HIPHIVE. The following conclusions are reached: for high disordered materials like amorphous BGG and cubic Ge<sub>2</sub>Sb<sub>2</sub>Te<sub>4.9</sub>, molecular dynamics are the most efficient and accurate way among the three; For high symmetrical materials like GeTe, Sb<sub>2</sub>Te<sub>3</sub> and the Kooi structure, the finite displacements are the most appropriate to use and HIPHIVE is useful for calculating vibrational and thermal properties of metastable structures at the finite temperature."]},{"key":"dc:format.checksum.md5","label":"Dc Format Checksum Md5","values":["87eda9de84448d1f82354d60eee3eb5f","bc75cdf635f81c2cc4b2d006fddf3500"]},{"key":"dc:title","label":"Title","values":["Ab initio Study of Atomic Dynamics and Thermal Properties of Inorganic Clathrates, Chalcogenides and Perovskite Oxides"]}]}],"canonical_facts":{"dc:contributor.advisor":["Elliott, Stephen"],"dc:creator":["Hu, Yuchen"],"dc:date.issued":["2021-09-30"],"dc:description.abstract":["Inorganic semiconductors are important materials for devices used every day. One property that is crucial to device performance is thermal behaviour. This can be directly related to the efficiency of devices; for example, in thermoelectric power generators, a lower thermal conductivity gives a larger thermometric figure of merit. Or they can indirectly affect the device performance, such as device stability at a certain operating temperature or device lifetime. With the help of computer simulations, one can test theories of material properties and design new functional materials. In this thesis, I present first-principles studies of three types of inorganic materials, namely inorganic clathrates, chalcogenides and perovskite oxides. Inorganic clathrates are promising candidates for thermoelectric applications due to their low thermal conductivity. In order to test approaches that improve the thermoelectric figure of merit of the inorganic clathrate, Ba8Ga16Ge30 (BGG), I generated an amorphous model of BGG and examined its structural, electronic and vibrational properties. Although amorphous BGG could have a lower thermal conductivity, the structure is not stable at the high operating temperatures for inorganic clathrates in thermoelectric power generators. Chalcogenide materials, especially Ge-Sb-Te (GST) alloys, are good candidates for phase- change memory devices. Their thermal properties affect device stability and operational speed. Many computer-simulation methods can be used to calculate the thermal properties of GST, but most are expensive computationally. Here, I compared results from a direct method and the fluctuation-dissipation theorem with packages employing a machine-learning algorithm, to explore computationally cost-effective approaches that give reasonable thermal-property results. The last materials that I studied are perovskite oxides. Perovskite oxides have been widely examined for applications in catalysis, solar-energy harvesting and superconductivity. Obtaining accurate lattice-dynamics results is important in order to understand their thermal properties. Disagreement between experimental and computer-simulation results was found for the phonon-dispersion curves of BaZrO<sub>3</sub> and BaSnO<sub>3</sub>. This results from an inaccurate description of the structure simulated using some exchange-correlation functionals in DFT calculations. This reminds us that, although approximations in quantum-mechanical theories can speed up simulation times, checking whether certain approximations work in some scenarios is necessary. From comparing the vibrational and theraml properties calcualted through MD-Green Kubo, finite displacements-LBTE and a machine learning code HIPHIVE. The following conclusions are reached: for high disordered materials like amorphous BGG and cubic Ge<sub>2</sub>Sb<sub>2</sub>Te<sub>4.9</sub>, molecular dynamics are the most efficient and accurate way among the three; For high symmetrical materials like GeTe, Sb<sub>2</sub>Te<sub>3</sub> and the Kooi structure, the finite displacements are the most appropriate to use and HIPHIVE is useful for calculating vibrational and thermal properties of metastable structures at the finite temperature."],"dc:format.checksum.md5":["87eda9de84448d1f82354d60eee3eb5f","bc75cdf635f81c2cc4b2d006fddf3500"],"dc:identifier.doi":["https://doi.org/10.17863/CAM.102235"],"dc:identifier.uri":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/d25a3a7c-956f-47b6-be89-7096b55b6d65/download"],"dc:language":["eng"],"dc:publisher.institution":["University of Cambridge"],"dc:relation.isreferencedby.uri":["https://www.repository.cam.ac.uk/handle/1810/358785"],"dc:rights":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/b126b6fb-47a2-4904-82fc-2c068790078b/download","https://www.rioxx.net/licenses/all-rights-reserved/"],"dc:subject":["Ab initio","Chalcogenides","First Principles","Inorganic Clathrates","Perovskite Oxides","Thermal Properties"],"dc:title":["Ab initio Study of Atomic Dynamics and Thermal Properties of Inorganic Clathrates, Chalcogenides and Perovskite Oxides"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Doctoral"],"dc:type.qualificationname":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-22T22:24:32Z"}