MatNexus: A Comprehensive Text Mining and Analysis Suite for Materials Discover

Lei Zhang, Markus Stricker
11/7/2023
cond-mat.mtrl-scics.CLphysics.chem-ph

No confident code implementation found for this paper.

Abstract

MatNexus is a specialized software for the automated collection, processing, and analysis of text from scientific articles. Through an integrated suite of modules, the MatNexus facilitates the retrieval of scientific articles, processes textual data for insights, generates vector representations suitable for machine learning, and offers visualization capabilities for word embeddings. With the vast volume of scientific publications, MatNexus stands out as an end-to-end tool for researchers aiming to gain insights from scientific literature in material science, making the exploration of materials, such as the electrocatalyst examples we show here, efficient and insightful.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Reconstructing Materials Tetrahedron: Challenges in Materials Information Extraction

85% match1 repo12023

DARWIN Series: Domain Specific Large Language Models for Natural Science

84% match2 repos2492023

MatKB: Semantic Search for Polycrystalline Materials Synthesis Procedures

83% match1 repo32023

Image and Data Mining in Reticular Chemistry Using GPT-4V

83% match2023

Agent-based Learning of Materials Datasets from Scientific Literature

82% match1 repo772023

ChatGPT Chemistry Assistant for Text Mining and Prediction of MOF Synthesis

82% match1 repo892023

Cite this paper

@article{zhang2023matnexus,
  title  = {MatNexus: A Comprehensive Text Mining and Analysis Suite for Materials Discover},
  author = {Lei Zhang and Markus Stricker},
  year   = {2023},
  eprint = {2311.06303},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2311.06303v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2311.06303.svg)](https://codeofpaper.com/paper/2311.06303)

Discussion