DSpace at KOASAS
Browsing DSpace

Browse "Dept. of Chemistry(화학과)" by Subject machine learning

A to Z

All 0-9

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

or enter first few letters:

Showing results 1 to 5 of 5

1
2023 Roadmap on molecular modelling of electrochemical energy materials

Zhang, Chao; Cheng, Jun; Chen, Yiming; Chan, Maria K. Y.; Cai, Qiong; Carvalho, Rodrigo P.; Marchiori, Cleber F. N.; et al, JOURNAL OF PHYSICS-ENERGY, v.5, no.4, 2023-10

2
Bimetallic Gold-Silver Nanostructures Drive Low Overpotentials for Electrochemical Carbon Dioxide Reduction

Park, Joon Woo; Choi, Woong; Noh, Juhwan; Park, Woonghyeon; Gu, Geun Ho; Park, Jonghyeok; Jung, Yousung; et al, ACS APPLIED MATERIALS & INTERFACES, v.14, no.5, pp.6604 - 6614, 2022-02

3
Enhanced Deep-Learning Prediction of Molecular Properties via Augmentation of Bond Topology

Cho, Hyeoncheol; Choi, Insung S., CHEMMEDCHEM, v.14, no.17, pp.1604 - 1609, 2019-09

4
Feasibility of Activation Energy Prediction of Gas-Phase Reactions by Machine Learning

Choi, Sunghwan; Kim, Yeonjoon; Kim, Jin Woo; Kim, Zeehyo; Kim, Woo Youn, CHEMISTRY-A EUROPEAN JOURNAL, v.24, no.47, pp.12354 - 12358, 2018-08

5
Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration

Hong, Seungbum; Liow, Chi Hao; Yuk, Jong Min; Byon, Hye Ryung; Yang, Yongsoo; Cho, EunAe; Yeom, Jiwon; et al, ACS NANO, v.15, no.3, pp.3971 - 3995, 2021-02

Discover

Type

Open Access

Date issued

. next

rss_1.0 rss_2.0 atom_1.0