Results 41 to 50 of about 10,388,998 (324)

Data-Driven Computing in Dynamics [PDF]

, 2017
We formulate extensions to Data Driven Computing for both distance minimizing and entropy maximizing schemes to incorporate time integration. Previous works focused on formulating both types of solvers in the presence of static equilibrium constraints ...
Kirchdoerfer, Trenton, Ortiz, Michael
core   +3 more sources

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

Science and Technology of Advanced Materials, 2020
We propose a novel descriptor of materials, named ‘cation fingerprints’, based on the chemical formula or concentrations of raw materials and their respective properties.
Jaekyun Hwang, Yuta Tanaka, Seiichiro Ishino, Satoshi Watanabe   +3 more
doaj   +1 more source

Automated computation of materials properties

, 2018
Materials informatics offers a promising pathway towards rational materials design, replacing the current trial-and-error approach and accelerating the development of new functional materials.
Agapito L.A., Ashcroft N.W., Carrete J., Daams J.L.C., Frisch M.J., Hahn T., Hart G.L.W., Leibfried G., Maradudin A.A., Nye J.F., Scheffler M., Schroers J., Villars P.   +12 more
core   +1 more source

Informatics derived materials databases for multifunctional properties

Science and Technology of Advanced Materials, 2015
In this review, we provide an overview of the development of quantitative structure–property relationships incorporating the impact of data uncertainty from small, limited knowledge data sets from which we rapidly develop new and larger databases. Unlike
Scott Broderick, Krishna Rajan
doaj   +1 more source

Hybrid algorithm of Bayesian optimization and evolutionary algorithm in crystal structure prediction

Science and Technology of Advanced Materials: Methods, 2022
We propose a highly efficient searching algorithm in crystal structure prediction. The searching algorithm is a hybrid of the evolutionary algorithm and Bayesian optimization. The evolutionary algorithm is widely used in crystal structure prediction, and
Tomoki Yamashita, Hiori Kino, Koji Tsuda, Takashi Miyake, Tamio Oguchi   +4 more
doaj   +1 more source

Accelerated materials property predictions and design using motif-based fingerprints

, 2015
Data-driven approaches are particularly useful for computational materials discovery and design as they can be used for rapidly screening over a very large number of materials, thus suggesting lead candidates for further in-depth investigations.
Huan, Tran Doan, Mannodi-Kanakkithodi, Arun, Ramprasad, Rampi   +2 more
core   +1 more source

Data integration for multiple alkali metals in predicting coordination energies based on Bayesian inference

Science and Technology of Advanced Materials: Methods, 2022
Building machine learning models using a dataset calculated by first principles calculations is an important approach to explore the next-generation batteries.
Koki Obinata, Tomofumi Nakayama, Atsushi Ishikawa, Keitaro Sodeyama, Kenji Nagata, Yasuhiko Igarashi, Masato Okada   +6 more
doaj   +1 more source

A Map of the Inorganic Ternary Metal Nitrides

, 2018
Exploratory synthesis in novel chemical spaces is the essence of solid-state chemistry. However, uncharted chemical spaces can be difficult to navigate, especially when materials synthesis is challenging.
Arca, Elisabetta, Bartel, Christopher, Bauers, Sage, Ceder, Gerbrand, Chen, Bor-Rong, Holder, Aaron, Lany, Stephan, Matthews, Bethany, Orvañanos, Bernardo, Schelhas, Laura T., Sun, Wenhao, Tate, Janet, Toney, Michael F., Tumas, William, Zakutayev, Andriy   +14 more
core   +3 more sources

Thinking Informatically [PDF]

, 2013
On being promoted to a personal chair in 1993 I chose the title of Professor of Informatics, specifically acknowledging Donna Haraway’s definition of the term as the “technologies of information [and communication] as well as the biological, social ...
Bryant, A
core   +2 more sources

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

Science and Technology of Advanced Materials: Methods, 2021
A growing number of papers are published in the area of superconducting materials science. However, novel text and data mining (TDM) processes are still needed to efficiently access and exploit this accumulated knowledge, paving the way towards data ...
Luca Foppiano, Sae Dieb, Akira Suzuki, Pedro Baptista de Castro, Suguru Iwasaki, Azusa Uzuki, Miren Garbine Esparza Echevarria, Yan Meng, Kensei Terashima, Laurent Romary, Yoshihiko Takano, Masashi Ishii   +11 more
doaj   +1 more source