Index Catalog // MDR

Free Analysis and Visualization Programs for Electrochemical Impedance Spectroscopy Coded in Python

Description/Abstract:: New programs for fitting using an equivalent circuit model and data visualization of electrochemical impedance spectroscopy were develope...
Keyword:: data visualization, electrochemical impedance, free software, and model fitting
Resource Type:: Article, Video, and Software or Program Code
Author:: KOBAYASHI, Kiyoshi and SUZUKI, Tohru S.
Journal:: Electrochemistry
Date Uploaded:: 08/02/2021
Date Modified:: 10/02/2021

SuperMat: Construction of a linked annotated dataset from superconductors-related publications

Description/Abstract:: A growing number of papers are published in the area of superconducting materials science. However, novel text and data mining (TDM) pro...
Keyword:: annotation, annotation guidelines, dataset, superconductors, and tdm
Resource Type:: Article
Author:: FOPPIANO, Luca, DIEB, Sae, SUZUKI, Akira, BAPTISTA DE CASTRO, Pedro, IWASAKI, Suguru, UZUKI, Azusa, ESPARZA ECHEVARRIA, Miren Garbine, MENG, Yan, TERASHIMA, Kensei, TAKANO, Yoshihiko, and ISHII, Masashi
Date Uploaded:: 07/01/2021
Date Modified:: 01/07/2021

Microbubble flows in superwettable fluidic channels

Description/Abstract:: The control of bubble adhesion underwater is important for various applications, yet the dynamics under flow conditions are still to be u...
Keyword:: microbubble and superwettability
Resource Type:: Article
Author:: Naito, Masanobu, Tenjimbayashi, Mizuki, and Doi, Kotaro
Journal:: RSC Advances
Date Uploaded:: 02/01/2021
Date Modified:: 18/10/2022

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

Description/Abstract:: Machine learning is emerging as a powerful tool for the discovery of novel high-performance functional materials. However, experimental d...
Keyword:: Machine learning, active learning, and adhesive
Resource Type:: Article
Author:: Pruksawan, Sirawit, Lambard, Guillaume, Samitsu, Sadaki, Sodeyama, Keitaro, and Naito, Masanobu
Journal:: Science and Technology of Advanced Materials
Date Uploaded:: 02/01/2021
Date Modified:: 18/10/2022

Automatic Experimental Data Collection System Using a Wireless LAN Capable SD Card as an IoT Device

Description/Abstract:: 実験・計算・データ科学を融合させた材料の研究開発を推進するマテリアルズインフォマティクス(MI)が推進されているが、実験データの収集については既存データベースのインポートや出版済み論文のデータマイニングに限られる場合が多い。効果的な MI のためには各種装置から自動的に実験...
Keyword:: FlashAir, IoT, Wi-Fi, and data transfer
Resource Type:: Presentation
Author:: MATSUDA, Asahiko, YOSHIKAWA, Hideki, and CHIKYOW, Toyohiro
Date Uploaded:: 23/10/2020
Date Modified:: 01/07/2021

Materials metadata: as a custom schema, as directories, or in a data package

Description/Abstract:: Metadata for a research dataset can be about the dataset's bibliographic properties as well as their scientific properties. The scientifi...
Keyword:: data platform, materials informatics, and metadata
Resource Type:: Poster
Author:: MATSUDA, Asahiko, TANABE, Kosuke, KADOHIRA, Takuya, and TANIFUJI, Mikiko
Date Uploaded:: 23/10/2020
Date Modified:: 01/07/2021

Examples of SQS (special quasirandom structure) models for arbitrary binary bcc (body centered cubic) and hcp (hexagonal close packed) structures

Description/Abstract:: These atomic coordinates are examples of SQS (special quasirandom structure) models for arbitrary binary bcc (body centered cubic) and hc...
Keyword:: Debye model, First-principles calculation, Sommerfeld model, quasi-harmonic vibrational contribution, and titanium alloys
Resource Type:: Dataset
Data origin:: simulations
Author:: SAHARA, Ryoji
Date Uploaded:: 09/10/2020
Date Modified:: 20/10/2020

Monte Carlo tree search for materials design and discovery

Description/Abstract:: Materials design and discovery can be represented as selecting the optimal structure from a space of candidates that optimizes a target p...
Keyword:: Materials design and discovery
Resource Type:: Article
Author:: Shiomi, Junichiro, Ju, Shenghong, Tsuda, Koji, and Dieb, Thaer M.
Journal:: MRS Communications
Date Uploaded:: 02/10/2020
Date Modified:: 16/10/2020

Structure prediction of boron-doped graphene by machine learning

Description/Abstract:: Heteroatom doping has endowed graphene with manifold aspects of material properties and boosted its applications. The atomic structure de...
Keyword:: Materials design and Monte Carlo tree search
Resource Type:: Article
Author:: Hou, Zhufeng, Tsuda, Koji, and Dieb, Thaer M.
Journal:: The Journal of Chemical Physics
Date Uploaded:: 02/10/2020
Date Modified:: 16/10/2020

MDTS: automatic complex materials design using Monte Carlo tree search

Description/Abstract:: Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python...
Keyword:: Monte Carlo tree search and materials design
Resource Type:: Article
Author:: Yoshizoe, Kazuki, Ju, Shenghong, Dieb, Thaer M., Shiomi, Junichiro, Hou, Zhufeng, and Tsuda, Koji
Journal:: Science and Technology of Advanced Materials
Date Uploaded:: 02/10/2020
Date Modified:: 16/10/2020

Free Analysis and Visualization Programs for Electrochemical Impedance Spectroscopy Coded in Python

SuperMat: Construction of a linked annotated dataset from superconductors-related publications

Microbubble flows in superwettable fluidic channels

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

Automatic Experimental Data Collection System Using a Wireless LAN Capable SD Card as an IoT Device

Materials metadata: as a custom schema, as directories, or in a data package

Examples of SQS (special quasirandom structure) models for arbitrary binary bcc (body centered cubic) and hcp (hexagonal close packed) structures

Monte Carlo tree search for materials design and discovery

Structure prediction of boron-doped graphene by machine learning

MDTS: automatic complex materials design using Monte Carlo tree search

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