# First-principles lattice thermal conductivity calculation for Zn3(PS4)2 / P-4n2 (118) / materials id 30311

https://mdr.nims.go.jp/datasets/67b2925f-555e-4f72-b6ef-daf3c5e04901

## File

- [FORCES_FC3.xz](https://mdr.nims.go.jp/filesets/a93329cd-f61d-4e83-a082-1a9b5d46150f/download) ([Detail](https://mdr.nims.go.jp/filesets/a93329cd-f61d-4e83-a082-1a9b5d46150f.md))
- [LTC-calc.log](https://mdr.nims.go.jp/filesets/e52d4fee-5f12-4c90-a343-9777de983a6a/download) ([Detail](https://mdr.nims.go.jp/filesets/e52d4fee-5f12-4c90-a343-9777de983a6a.md))
- [phono3py_mlp_eval_fc3_disp.yaml.xz](https://mdr.nims.go.jp/filesets/21a7d141-9045-4b69-a0d0-c3d5061fe11a/download) ([Detail](https://mdr.nims.go.jp/filesets/21a7d141-9045-4b69-a0d0-c3d5061fe11a.md))
- [phonopy_mlp_eval_fc2_dataset.yaml.xz](https://mdr.nims.go.jp/filesets/1a2fdef2-60a7-4e5a-9096-ee8287f73c1b/download) ([Detail](https://mdr.nims.go.jp/filesets/1a2fdef2-60a7-4e5a-9096-ee8287f73c1b.md))
- [phonopy_training_dataset.yaml.xz](https://mdr.nims.go.jp/filesets/a5206290-a077-4019-9f89-51313bcd7eaf/download) ([Detail](https://mdr.nims.go.jp/filesets/a5206290-a077-4019-9f89-51313bcd7eaf.md))
- [polymlp.yaml.xz](https://mdr.nims.go.jp/filesets/dcf6f31e-6d2b-4bd0-8b96-e749af7fd806/download) ([Detail](https://mdr.nims.go.jp/filesets/dcf6f31e-6d2b-4bd0-8b96-e749af7fd806.md))
- [vasp-settings.tar.xz](https://mdr.nims.go.jp/filesets/1afb8ffa-cdd6-4954-bd2d-dd5d91a7fd1f/download) ([Detail](https://mdr.nims.go.jp/filesets/1afb8ffa-cdd6-4954-bd2d-dd5d91a7fd1f.md))
- [band_pdos.png](https://mdr.nims.go.jp/filesets/6bb0e12c-5d87-4927-a204-8d016a2de877/download) ([Detail](https://mdr.nims.go.jp/filesets/6bb0e12c-5d87-4927-a204-8d016a2de877.md))

## Id

67b2925f-555e-4f72-b6ef-daf3c5e04901

## Local identifier

identifier: MDR-LTC-2026Jan9/mp-30311

## Visibility

open_to_public

## State

published

## Created at

2026-01-15T06:09:10.475322Z

## Updated at

2026-01-24T05:10:34.048543Z

## Published at

2026-01-24T01:52:42.650342Z

## 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 Zn3(PS4)2 /
    P-4n2 (118) / materials id 30311
  title_type: original
  lang: en

## Description

- description: |
    Input data used to calculate the lattice thermal conductivities of
    Zn3(PS4)2.
  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
- description: |
    Input data used to calculate the lattice thermal conductivities of
    Zn3(PS4)2.
  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: Zn3(PS4)2
  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: Zn3(PS4)2
  description: Zn3(PS4)2

## Chemical composition

- identifier: Zn3(PS4)2
  description: Zn3(PS4)2

## Structure for specimen

- description: Zn3(PS4)2
  category_description: Zn3(PS4)2

## 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: a93329cd-f61d-4e83-a082-1a9b5d46150f
  filename: FORCES_FC3.xz
  content_type: application/x-xz
  size: 15143200
  md5: 669efb1fbb4e6bd43551885140d92e80
- id: e52d4fee-5f12-4c90-a343-9777de983a6a
  filename: LTC-calc.log
  content_type: text/x-log
  size: 240018
  md5: 8a52a113f639c84ffbfd59d9e46bc48d
- id: 21a7d141-9045-4b69-a0d0-c3d5061fe11a
  filename: phono3py_mlp_eval_fc3_disp.yaml.xz
  content_type: application/x-xz
  size: 26396
  md5: fb519130f045b5d0fae4046c837e1f50
- id: 1a2fdef2-60a7-4e5a-9096-ee8287f73c1b
  filename: phonopy_mlp_eval_fc2_dataset.yaml.xz
  content_type: application/x-xz
  size: 1434960
  md5: 655b4b25b2446b67c27a2fe15bd0ca7e
- id: a5206290-a077-4019-9f89-51313bcd7eaf
  filename: phonopy_training_dataset.yaml.xz
  content_type: application/x-xz
  size: 740684
  md5: d425657fad8e560db40cc5a9272dd3f6
- id: dcf6f31e-6d2b-4bd0-8b96-e749af7fd806
  filename: polymlp.yaml.xz
  content_type: application/x-xz
  size: 290904
  md5: 1e11fa8e897d7f3e0b7378e13a2a16ff
- id: 1afb8ffa-cdd6-4954-bd2d-dd5d91a7fd1f
  filename: vasp-settings.tar.xz
  content_type: application/x-xz
  size: 576
  md5: e94f775d9f9c930ae98a12e94c0744c2
- id: 6bb0e12c-5d87-4927-a204-8d016a2de877
  filename: band_pdos.png
  content_type: image/png
  size: 81327
  md5: 742bb6a8635091a4d8c1ee3a4e975f12

## Thumbnail

fileset_id: 6bb0e12c-5d87-4927-a204-8d016a2de877
filename: band_pdos.png