Informatics derived materials databases for multifunctional properties

by Scott Broderick, Krishna Rajan
Published 2015-02-01

Critical Temperature Prediction of Superconductors Based on Atomic Vectors and Deep Learning

by Shaobo Li, Yabo Dan, Xiang Li, Tiantian Hu, Rongzhi Dong, Zhuo Cao, Jianjun Hu
Published 2020-02-01

Materials Informatics Approach to Material Extrusion Additive Manufacturing

by Braconnier, Daniel J
Published 2018

Materials informatics approach to understand aluminum alloys

by Ryo Tamura, Makoto Watanabe, Hiroaki Mamiya, Kota Washio, Masao Yano, Katsunori Danno, Akira Kato, Tetsuya Shoji
Published 2020-01-01

Estimating Regions of Deterioration in Electron Microscope Images of Rubber Materials via a Transfer Learning-Based Anomaly Detection Model

by Ren Togo, Naoki Saito, Takahiro Ogawa, Miki Haseyama
Published 2019-01-01

ChemProps: A RESTful API enabled database for composite polymer name standardization

by Bingyin Hu, Anqi Lin, L. Catherine Brinson
Published 2021-03-01

Understanding and optimization of hard magnetic compounds from first principles

by Takashi Miyake, Yosuke Harashima, Taro Fukazawa, Hisazumi Akai
Published 2021-12-01

Predicting material properties by integrating high-throughput experiments, high-throughput ab-initio calculations, and machine learning

by Yuma Iwasaki, Masahiko Ishida, Masayuki Shirane
Published 2020-01-01

The Representation and Exchange of Material and Other Engineering Properties

by Norman Swindells
Published 2009-09-01

Corrosion rate prediction and influencing factors evaluation of low-alloy steels in marine atmosphere using machine learning approach

by Luchun Yan, Yupeng Diao, Zhaoyang Lang, Kewei Gao
Published 2020-01-01

Machine Learning Based Methods for Obtaining Correlations between Microstructures and Thermal Stresses

by Akshay Bhutada, Sunni Kumar, Dayalan Gunasegaram, Alankar Alankar
Published 2021-07-01

Benchmark datasets incorporating diverse tasks, sample sizes, material systems, and data heterogeneity for materials informatics

by Ashley N. Henderson, Steven K. Kauwe, Taylor D. Sparks
Published 2021-08-01

Explainable machine learning for materials discovery: predicting the potentially formable Nd–Fe–B crystal structures and extracting the structure–stability relationship

by Tien-Lam Pham, Duong-Nguyen Nguyen, Minh-Quyet Ha, Hiori Kino, Takashi Miyake, Hieu-Chi Dam
Published 2020-11-01

Prediction of viscosity behavior in oxide glass materials using cation fingerprints with artificial neural networks

by Jaekyun Hwang, Yuta Tanaka, Seiichiro Ishino, Satoshi Watanabe
Published 2020-01-01

Prediction and optimization of epoxy adhesive strength from a small dataset through active learning

by Sirawit Pruksawan, Guillaume Lambard, Sadaki Samitsu, Keitaro Sodeyama, Masanobu Naito
Published 2019-12-01

Relation extraction with weakly supervised learning based on process-structure-property-performance reciprocity

by Takeshi Onishi, Takuya Kadohira, Ikumu Watanabe
Published 2018-12-01

Construction of interatomic potentials using large sets of DFT calculations and linear regression method

by Takahashi, Akira
Published 2017

An Ontology-Based Approach to Enable Data-Driven Research in the Field of NDT in Civil Engineering

by Benjamí Moreno Torres, Christoph Völker, Sarah Mandy Nagel, Thomas Hanke, Sabine Kruschwitz
Published 2021-06-01

Data-driven analysis of electron relaxation times in PbTe-type thermoelectric materials

by Yukari Katsura, Masaya Kumagai, Takushi Kodani, Mitsunori Kaneshige, Yuki Ando, Sakiko Gunji, Yoji Imai, Hideyasu Ouchi, Kazuki Tobita, Kaoru Kimura, Koji Tsuda
Published 2019-12-01

A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data

by Randy Jalem, Masanobu Nakayama, Yusuke Noda, Tam Le, Ichiro Takeuchi, Yoshitaka Tateyama, Hisatsugu Yamazaki
Published 2018-12-01