---
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.