Tholander Nitrides

A challenging data set for quantum machine learning containing a diverse set of 12.8k polymorphs in the Zn-Ti-N, Zn-Zr-N and Zn-Hf-N chemical systems. The phase diagrams of the Ti-Zn-N, Zr-Zn-N, and Hf-Zn-N systems are determined using large-scale high-throughput density functional calculations (DFT-GGA) (PBE). In total 12,815 relaxed structures are shared alongside their energy calculated using the VASP DFT code. The High-Throughput Toolkit was used to manage the calculations. Data adapted and deduplicated from the original data on Zenodo at https://zenodo.org/record/5530535#.YjJ3ZhDMJLQ. Deduplicated according to identical structures matching ht_ids. Prepared in collaboration with Rhys Goodall.

本数据集为量子机器学习（quantum machine learning）领域的挑战性基准数据集，涵盖Zn-Ti-N、Zn-Zr-N与Zn-Hf-N三类化学体系中的12800余种多晶型体。本研究通过大规模高通量密度泛函计算（density functional calculations, DFT-GGA）结合PBE泛函，构建了Ti-Zn-N、Zr-Zn-N及Hf-Zn-N体系的相图。本次共公开12815个经结构弛豫的晶体结构，及其通过VASP密度泛函程序计算得到的能量值。本次计算通过高通量工具包（High-Throughput Toolkit）进行管理。本数据集改编自Zenodo平台的原始数据（链接：https://zenodo.org/record/5530535#.YjJ3ZhDMJLQ），并按照匹配ht_id的相同结构规则完成去重。本数据集由里斯·古德尔（Rhys Goodall）合作完成。