| --- |
| dataset_info: |
| features: |
| - name: authors |
| dtype: string |
| - name: title |
| dtype: string |
| - name: journal-ref |
| dtype: string |
| - name: doi |
| dtype: string |
| - name: report-no |
| dtype: string |
| - name: categories |
| dtype: string |
| - name: abstract |
| dtype: string |
| - name: versions |
| dtype: string |
| - name: update_date |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1027886 |
| num_examples: 620 |
| download_size: 556996 |
| dataset_size: 1027886 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| # Dataset Card for "Materials-Informatics" |
|
|
| Dataset Name: Materials-Informatics |
|
|
| Dataset Owner: cs-mubashir |
|
|
| Language: English |
|
|
| Size: ~600+ entries |
|
|
| Last Updated: May 2025 |
|
|
| Source: Extracted from arxiv dataset research repository |
|
|
|
|
| # Dataset Summary |
|
|
| The Materials-Informatics dataset is a curated collection of research papers from arxiv repository focusing on the intersection |
| of artificial intelligence (AI) and materials science and engineering (MSE). Each entry provides metadata |
| and descriptive information about a research paper, including its title, authors, abstract, keywords, publication year, |
| material types, AI techniques used, and application domains. |
|
|
| This dataset aims to serve as a valuable resource for researchers and practitioners working at the convergence |
| of machine learning, deep learning, and materials discovery/design. It can be used for tasks like information retrieval, |
| scientific NLP, trend analysis, paper classification, and LLM fine-tuning for domain-specific tasks. |
|
|
