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---
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.
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