DOI: 10.11583/dtu.27411681.v5
title: Additional data for the polyanion sodium cathode materials dataset

description: As an addition to the Polyanion sodium cathode materials dataset (https://doi.org/10.11583/DTU.27202446), we have used three computational methods used for battery electrodes to generate 88,535 structures.We have performed atomic structural relaxation of four sodium ion polyanionic cathode materials NaTMPO<sub>4</sub>(olivine) ,NaTMPO<sub>4</sub>(maricite), Na<sub>2</sub>TMSiO<sub>4</sub> and Na<sub>2.56</sub>TM<sub>1.72</sub>(SO<sub>4</sub>)<sub>3</sub> with three and four different types of transition metal ions (TM) in each structure. The four possible transition metal ions in the cathode materials are Fe, Mn, Co and Ni and the concentration level of the transition metal ion and Na atoms differs from each structure. The dataset consist of 514 structure optimized.We have also performed ab-initio molecular dynamics simulation (AIMD) of the cathode materials NaTMPO<sub>4</sub>(olivine) and NaTMPO<sub>4</sub>(maricite) with three different pairs of transition metal ions (TM=Fe<sub>1-y</sub>Mn<sub>y</sub>, TM=Fe<sub>1-y</sub>Ni<sub>y </sub>and TM=Mn<sub>1-y</sub>Co<sub>y</sub>) with different concentration of transition metal ion and Na. The dataset consist of 87967 structural trajectory points.We have performed nudged elastic band (NEB) calculation of six cathode materials, FePO<sub>4</sub>(olivine), MnPO<sub>4</sub>(olivine), NiPO<sub>4</sub>(olivine), NaFePO<sub>4</sub>(olivine), NaMnPO<sub>4</sub>(olivine) and NaNiPO<sub>4</sub>(olivine). The NEB calculation estimates the energy barrier a Na atom needs to overcome when moving from one spot to a vacant position. The dataset consist of 36 structural trajectory point along the energy barriers noted by "_NEB" and 12 structure points for the initial and final configuration of the diffusion path.For each sampled structure, we record its crystal composition, total energy, atom-wise force vectors, atom-wise magnetic moments, and atomic charges obtained through Bader analysis.All computational calculation are done using density functional theory (DFT) calculation with the Vienna Ab initio simulation package (VASP) version 6.4 package. The Perdew-Burke-Ernzerhof (PBE) functional with Hubbard-U corrections were appliedwas utilized for all calculations. The U-values are similar to the ones used for materials project (Fe: 5.3eV, Mn: 3.9eV, Co: 3.32eV, Ni: 6.2eV). For all calculations, an energy cutoff of 520eV was applied, with a smearing width of 0.01eV and convergence criteria set to 1e-5eV for energy and 0.03eV/Å for forces. All calculations were performed with spin polarization. The k-points employed for the four materials were fixed, with NaMPO<sub>4</sub>(olivine) and NaMPO<sub>4</sub>(maricite) utilizing [3,4,6] gamma points, Na<sub>2</sub>MSiO<sub>4 </sub>employing [3,4,4] gamma points and Na<sub>2.56</sub>M<sub>1.72</sub>(SO<sub>4</sub>)<sub>3</sub> utilizing [2,3,4] gamma points. When constructing supercells, the gamma point in the direction of cell enlargement was halved. These settings match the ones used for the Polyanion sodium cathode materials dataset (https://doi.org/10.11583/DTU.27202446)All AIMD simulations are conducted using the Langevin thermostat with a friction constant of 0.003. The temperature is maintained at 1000K to facilitate diffusion events, and a time step of 1fs as employed throughout the simulations. All simulations are executed within the canonical (NVT) ensemble and a sample frequency was set to 1fs.All NEB calculations are performed using the ASE version 3.23.0 NEB wrapper with the FIRE optimization algorithm. Five intermediate images were used in the NEB optimization, converging to a maximum atom-wise force of 0.03ev/Å. The initial and final images were manually determined based on the cation's redox position, followed by structural optimization before initiating the NEB calculations. Throughout both structural optimizations and NEB calculations, the cell parameters were kept constant to the theoretical optimized experimental cell parameters.The dataset is presented in XYZ format. The dataset is divided into three folder, one for each computational method.<br>To extract structural compositions and physical properties, the ase.io.read function from ASE version 3.23.0 is used. An example of how to extract data and plot the physical properties is provided in https://github.com/dtu-energy/cPaiNN/blob/main/read_data.py and https://github.com/dtu-energy/cPaiNN/blob/main/attach_bader_charge.ipynb shows how to attached Bader charges to an ASE atom object.<br>To cite the data please use the doi https://doi.org/110.11583/DTU.27411681<br>Along with the data is all the pretrained cPaiNN models and PaiNN models used to test these datasets. To load the pretrained models, please use the descriptions presented here: https://github.com/dtu-energy/cPaiNN<br>Finetuned model and model trained from scratch for CHGNet and Mace-MP-0 large are also included.<br>Versions:<br>Use the data from version 42: All data is uploaded and pretrained model is trained on structures with atomic charge<br>3: The NEB data is updated to consist of theoretical optimized cell parameters instead of experimental parameters. Moreover, are all pretrained model updated to be trained on structures with and without atomic charge, but still predicts atomic charge4: Included more pretrained models as well as the initial and final configuration of the structural optimization. The atomic charge has also changed sign.<br>