# First-principles lattice thermal conductivity calculation for Th2SN2 / P-3m1 (164) / materials id 7769 https://mdr.nims.go.jp/datasets/ac7fb734-c43a-4b1d-b783-05d62be3d919 ## Files - [FORCES_FC3.xz](https://mdr.nims.go.jp/filesets/8776664b-3039-4a83-a61c-3bfa8ccf4036/download) ([Detail](https://mdr.nims.go.jp/filesets/8776664b-3039-4a83-a61c-3bfa8ccf4036.md)) - [LTC-calc.log](https://mdr.nims.go.jp/filesets/bfce33f7-7066-42b8-899b-3ea0d68c98fb/download) ([Detail](https://mdr.nims.go.jp/filesets/bfce33f7-7066-42b8-899b-3ea0d68c98fb.md)) - [phono3py_mlp_eval_fc3_disp.yaml.xz](https://mdr.nims.go.jp/filesets/e165226b-d429-4d8b-9ae1-80ef94ef862e/download) ([Detail](https://mdr.nims.go.jp/filesets/e165226b-d429-4d8b-9ae1-80ef94ef862e.md)) - [phonopy_mlp_eval_fc2_dataset.yaml.xz](https://mdr.nims.go.jp/filesets/2dc55c9e-b176-4d64-82c0-c7f6cdf15cfb/download) ([Detail](https://mdr.nims.go.jp/filesets/2dc55c9e-b176-4d64-82c0-c7f6cdf15cfb.md)) - [phonopy_training_dataset.yaml.xz](https://mdr.nims.go.jp/filesets/16b5b542-aedd-4e9f-9b3e-ebea57d2eb05/download) ([Detail](https://mdr.nims.go.jp/filesets/16b5b542-aedd-4e9f-9b3e-ebea57d2eb05.md)) - [polymlp.yaml.xz](https://mdr.nims.go.jp/filesets/4108b9e4-4344-4fd7-adfb-3a9c6518a18a/download) ([Detail](https://mdr.nims.go.jp/filesets/4108b9e4-4344-4fd7-adfb-3a9c6518a18a.md)) - [vasp-settings.tar.xz](https://mdr.nims.go.jp/filesets/05974582-8f31-4d61-8d96-28b64e1c4e87/download) ([Detail](https://mdr.nims.go.jp/filesets/05974582-8f31-4d61-8d96-28b64e1c4e87.md)) - [band_pdos.png](https://mdr.nims.go.jp/filesets/7f8018f3-9303-4982-a5e0-d2854a094579/download) ([Detail](https://mdr.nims.go.jp/filesets/7f8018f3-9303-4982-a5e0-d2854a094579.md)) ## Id ac7fb734-c43a-4b1d-b783-05d62be3d919 ## Local identifier identifier: MDR-LTC-2026Jan9/mp-7769 ## Visibility open_to_public ## State published ## Created at 2026-01-15T06:00:57.859098Z ## Updated at 2026-01-24T04:28:24.935632Z ## Published at 2026-01-24T01:51:17.675879Z ## Doi ## First published url ## Date published ## Recorded date published ## Resource type dataset ## Manuscript type na ## Collection - id: 0113dccc-ec45-42ed-86db-f455f9b63fb1 identifier: https://mdr.nims.go.jp/pid/0113dccc-ec45-42ed-86db-f455f9b63fb1 title: MDR lattice thermal conductivity calculation database ## Title - title: First-principles lattice thermal conductivity calculation for Th2SN2 / P-3m1 (164) / materials id 7769 title_type: original lang: en ## Description - description: | Input data used to calculate the lattice thermal conductivities of Th2SN2. description_type: abstract lang: en - description: | Initial geometry optimization of the conventional unit cell, standardized by the spglib code, was performed using the VASP code with the PBEsol exchange-correlation functional. Supercell forces and energies were calculated using the VASP code, and these data were used to develop polynomial machine learning potentials (MLPs) with the pypolymlp code. The generated MLPs are stored in polymlp.yaml.xz. Parameters required for the non-analytical term correction (Born effective charges and dielectric constants) were calculated using the VASP code with the primitive cell. These VASP results are provided in phonopy_training_dataset.yaml.xz, and the VASP input configurations can be found in vasp-settings.tar.xz. The primitive cell, unit cell, and supercell structures used for the VASP calculations are also provided in phonopy_training_dataset.yaml.xz. The internal atomic positions of the supercell were then optimized using the pypolymlp code under symmetry constraints; the relaxed structure can be found in phonopy_mlp_eval_fc2_dataset.yaml.xz (or phono3py_mlp_eval_fc3_disp.yaml.xz). Second-order force constants (fc2) can be calculated using the phonopy and symfc codes with the displacement–force dataset evaluated by the pypolymlp code, which is stored in phonopy_mlp_eval_fc2_dataset.yaml.xz. Third-order force constants (fc3) can be calculated using the built-in finite difference approach in the phono3py code with the displacement–force dataset stored in phono3py_mlp_eval_fc3_disp.yaml.xz (displacements) and FORCES_FC3.xz (forces). As an example, lattice thermal conductivities (LTCs) were calculated using the phono3py code with fc2 and fc3, and the calculation log is provided in LTC-calc.log. The harmonic phonon band structure and density of states are plotted in band_pdos.png. The band path was generated using the SeeK-path code. description_type: abstract lang: en ## Creator - name: Atsushi Togo role: author orcid: https://orcid.org/0000-0001-8393-9766 organization: National Institute for Materials Science department: Center for Basic Research on Materials ror: https://ror.org/026v1ze26 ## Contact agent - name: Atsushi Togo email: togo.atsushi@nims.go.jp organization: National Institute for Materials Science ror: https://ror.org/026v1ze26 ## Publisher organization: NIMS ror: https://ror.org/026v1ze26 ## Managing organization organization: National Institute for Materials Science department: CBRM ror: https://ror.org/026v1ze26 ## Keyword - subject: Lattice thermal conductivity schema: not_defined - subject: Th2SN2 schema: not_defined ## Rights - description: Creative Commons Attribution 4.0 International identifier: https://creativecommons.org/licenses/by/4.0/ ## Other identifier(s) ## Data origin - data_origin_type: simulation ## Embargo ## Journal ## Conference ## Related item ## Funding ## Instrument ## Instrument operator ## Instrument managing organization ## Measurement method ## Specimen - name: Th2SN2 description: Th2SN2 ## Chemical composition - identifier: Th2SN2 description: Th2SN2 ## Structure for specimen - description: Th2SN2 category_description: Th2SN2 ## Structural feature for specimen ## Specific property for specimen ## Process for specimen treatment ## Computational method ## Energy level/transition state ## Software - name: phono3py identifier: https://github.com/phonopy/phono3py - name: phonopy identifier: https://github.com/phonopy/phonopy - name: spglib identifier: https://github.com/spglib/spglib - name: symfc identifier: https://github.com/symfc/symfc - name: pypolymlp identifier: https://github.com/sekocha/pypolymlp - name: VASP identifier: https://www.vasp.at/ - name: Seek-path identifier: https://github.com/giovannipizzi/seekpath ## Custom property ## Fileset - id: 8776664b-3039-4a83-a61c-3bfa8ccf4036 filename: FORCES_FC3.xz content_type: application/x-xz size: 2342120 md5: 41991b8cf3c8faf3859ed75cc6e2c11d - id: bfce33f7-7066-42b8-899b-3ea0d68c98fb filename: LTC-calc.log content_type: text/x-log size: 201042 md5: 0b1fc9a4ef43649cbadddad2608040ee - id: e165226b-d429-4d8b-9ae1-80ef94ef862e filename: phono3py_mlp_eval_fc3_disp.yaml.xz content_type: application/x-xz size: 7584 md5: 937db5568df3a04af7c56375ece76860 - id: 2dc55c9e-b176-4d64-82c0-c7f6cdf15cfb filename: phonopy_mlp_eval_fc2_dataset.yaml.xz content_type: application/x-xz size: 250348 md5: 90ab65ea97386f96780e6976bba704b5 - id: 16b5b542-aedd-4e9f-9b3e-ebea57d2eb05 filename: phonopy_training_dataset.yaml.xz content_type: application/x-xz size: 642156 md5: 95d356fe8aa49cdc297c82e4fa08cd59 - id: 4108b9e4-4344-4fd7-adfb-3a9c6518a18a filename: polymlp.yaml.xz content_type: application/x-xz size: 294196 md5: 442735ec247597f034dfd0b8681f9ce8 - id: '05974582-8f31-4d61-8d96-28b64e1c4e87' filename: vasp-settings.tar.xz content_type: application/x-xz size: 584 md5: c0e3288a85857e46849b23901553a20c - id: 7f8018f3-9303-4982-a5e0-d2854a094579 filename: band_pdos.png content_type: image/png size: 62488 md5: 45a31d3da87514c413f0617ba4d3987c ## Thumbnail fileset_id: 7f8018f3-9303-4982-a5e0-d2854a094579 filename: band_pdos.png