AI-Empowered Database Management Platform for New Materials Discovery for Consumer Electronics

被引：0

作者：

Kim, Taeyeop ^{[1
]}

Lee, JaeSeong ^{[1
]}

Song, Jaeho ^{[1
]}

Lee, Dongwoo ^{[1
]}

Na, Jun-Chae ^{[2
]}

Yang, Sung-Il ^{[2
]}

Park, Kyong-Jin ^{[2
]}

Yoo, Young-Jin ^{[2
,3
]}

Lee, Juhye ^{[2
]}

Shin, Won-Yong ^{[3
,4
]}

机构：

[1] Sungkyunkwan Univ, Sch Mech Engn, Suwon 16419, South Korea

[2] KAILOS LAB Co Ltd, Seoul 03722, South Korea

[3] Yonsei Univ, Sch Math & Comp CSE, Seoul 03722, South Korea

[4] Pohang Univ Sci & Technol Artificial Intelligence, Pohang 37673, South Korea

来源：

2023 IEEE 20TH CONSUMER COMMUNICATIONS & NETWORKING CONFERENCE, CCNC | 2023年

基金：

新加坡国家研究基金会;

关键词：

D O I：

10.1109/CCNC51644.2023.10060412

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Considerable attention has been paid to discover new materials with a desired set of properties for consumer electronics. However, the databases of the properties of a wide range of materials are not readily available, making data-driven discovery of novel materials challenging. In this study, we present an AI-empowered one-stop alloy database platform as an example and showcase its performance.

引用

页数：2

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