Open Access
Machine Learning with Enormous “Synthetic” Data Sets: Predicting Glass Transition Temperature of Polyimides Using Graph Convolutional Neural Networks
Igor V Volgin
1
,
Pavel A Batyr
2
,
Andrey V Matseevich
3
,
Alexey Yu Dobrovskiy
1
,
Maria V. Andreeva
1
,
V M Nazarychev
1
,
S V Larin
1
,
Mikhail Ya Goikhman
1
,
Yury V. Vizilter
2
,
Andrey A Askadskii
3, 4
,
Publication type: Journal Article
Publication date: 2022-11-17
scimago Q1
wos Q2
SJR: 0.773
CiteScore: 7.1
Impact factor: 4.3
ISSN: 24701343
PubMed ID:
36506114
General Chemistry
General Chemical Engineering
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Metrics
52
Total citations:
52
Citations from 2024:
37
(71.15%)
Cite this
GOST |
RIS |
BibTex |
MLA
Cite this
GOST
Copy
Volgin I. V. et al. Machine Learning with Enormous “Synthetic” Data Sets: Predicting Glass Transition Temperature of Polyimides Using Graph Convolutional Neural Networks // ACS Omega. 2022. Vol. 7. No. 48. pp. 43678-43691.
GOST all authors (up to 50)
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Volgin I. V., Batyr P. A., Matseevich A. V., Dobrovskiy A. Yu., Andreeva M. V., Nazarychev V. M., Larin S. V., Goikhman M. Ya., Vizilter Y. V., Askadskii A. A., Lyulin S. V. Machine Learning with Enormous “Synthetic” Data Sets: Predicting Glass Transition Temperature of Polyimides Using Graph Convolutional Neural Networks // ACS Omega. 2022. Vol. 7. No. 48. pp. 43678-43691.
Cite this
RIS
Copy
TY - JOUR
DO - 10.1021/acsomega.2c04649
UR - https://pubs.acs.org/doi/10.1021/acsomega.2c04649
TI - Machine Learning with Enormous “Synthetic” Data Sets: Predicting Glass Transition Temperature of Polyimides Using Graph Convolutional Neural Networks
T2 - ACS Omega
AU - Volgin, Igor V
AU - Batyr, Pavel A
AU - Matseevich, Andrey V
AU - Dobrovskiy, Alexey Yu
AU - Andreeva, Maria V.
AU - Nazarychev, V M
AU - Larin, S V
AU - Goikhman, Mikhail Ya
AU - Vizilter, Yury V.
AU - Askadskii, Andrey A
AU - Lyulin, Sergey V.
PY - 2022
DA - 2022/11/17
PB - American Chemical Society (ACS)
SP - 43678-43691
IS - 48
VL - 7
PMID - 36506114
SN - 2470-1343
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2022_Volgin,
author = {Igor V Volgin and Pavel A Batyr and Andrey V Matseevich and Alexey Yu Dobrovskiy and Maria V. Andreeva and V M Nazarychev and S V Larin and Mikhail Ya Goikhman and Yury V. Vizilter and Andrey A Askadskii and Sergey V. Lyulin},
title = {Machine Learning with Enormous “Synthetic” Data Sets: Predicting Glass Transition Temperature of Polyimides Using Graph Convolutional Neural Networks},
journal = {ACS Omega},
year = {2022},
volume = {7},
publisher = {American Chemical Society (ACS)},
month = {nov},
url = {https://pubs.acs.org/doi/10.1021/acsomega.2c04649},
number = {48},
pages = {43678--43691},
doi = {10.1021/acsomega.2c04649}
}
Cite this
MLA
Copy
Volgin, Igor V., et al. “Machine Learning with Enormous “Synthetic” Data Sets: Predicting Glass Transition Temperature of Polyimides Using Graph Convolutional Neural Networks.” ACS Omega, vol. 7, no. 48, Nov. 2022, pp. 43678-43691. https://pubs.acs.org/doi/10.1021/acsomega.2c04649.