Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Chenru Duan"'
Publikováno v:
Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-17 (2023)
Abstract With the increasingly more important role of machine learning (ML) models in chemical research, the need for putting a level of confidence to the model predictions naturally arises. Several methods for obtaining uncertainty estimates have be
Externí odkaz:
https://doaj.org/article/ed0651e907dd46c78f2bfbd9571ea303
Autor:
Xue Zhang, Zhuo Wang, Adam Mukhtar Lawan, Jiahong Wang, Chang‐Yu Hsieh, Chenru Duan, Cheng Heng Pang, Paul. K. Chu, Xue‐Feng Yu, Haitao Zhao
Publikováno v:
InfoMat, Vol 5, Iss 6, Pp n/a-n/a (2023)
Abstract Owing to increasing global demand for carbon neutral and fossil‐free energy systems, extensive research is being conducted on efficient and inexpensive electrocatalysts for catalyzing the kinetically sluggish oxygen reduction reaction (ORR
Externí odkaz:
https://doaj.org/article/5ecb12255d00403cadd369dc756174d4
Autor:
Aditya Nandy, Gianmarco Terrones, Naveen Arunachalam, Chenru Duan, David W. Kastner, Heather J. Kulik
Publikováno v:
Scientific Data, Vol 9, Iss 1, Pp 1-11 (2022)
Measurement(s) thermal decomposition Technology Type(s) thermogravimetry
Externí odkaz:
https://doaj.org/article/40ab9ceff7b64f64872d2d95e12c2d66
Publikováno v:
ACS Central Science, Vol 6, Iss 4, Pp 513-524 (2020)
Externí odkaz:
https://doaj.org/article/27bfbb92c9784fdfb290b54bfa9bd536
Publikováno v:
Chemical Science. 14:1419-1433
Neural networks are used to predict iridium phosphor excited state properties at accuracy competitive with TDDFT, enabling high-throughput screening.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37e0bde451d62f1af90d3dd91c3f8ebf
https://doi.org/10.1039/d2sc06150c
https://doi.org/10.1039/d2sc06150c
Publikováno v:
JACS Au. 3:391-401
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05ada6d6f8a47ec5434bdaa98edd1e0a
https://doi.org/10.1021/jacsau.2c00547
https://doi.org/10.1021/jacsau.2c00547
Spin crossover (SCO) complexes, which exhibit changes in spin state in response to external stimuli, have applications in molecular electronics and are challenging materials for computational design. We curate a data set of 95 Fe(II) SCO complexes (S
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eafdb40448f62b9b9c9d7711b722a818
https://doi.org/10.26434/chemrxiv-2023-kqbhs
https://doi.org/10.26434/chemrxiv-2023-kqbhs
Publikováno v:
Annual Review of Chemical and Biomolecular Engineering. 13:405-429
Machine learning (ML) has become a part of the fabric of high-throughput screening and computational discovery of materials. Despite its increasingly central role, challenges remain in fully realizing the promise of ML. This is especially true for th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19d2c1fb15656da36f1315f8618612b1
https://doi.org/10.1146/annurev-chembioeng-092320-120230
https://doi.org/10.1146/annurev-chembioeng-092320-120230
Autor:
Mingjie Liu, Azadeh Nazemi, Michael G. Taylor, Aditya Nandy, Chenru Duan, Adam H. Steeves, Heather J. Kulik
Publikováno v:
ACS Catalysis. 12:383-396
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e26341dabf1e12178c290b44aea37f4a
https://doi.org/10.1021/acscatal.1c04624
https://doi.org/10.1021/acscatal.1c04624
Publikováno v:
Journal of chemical theory and computation.
When a many-body wave function of a system cannot be captured by a single determinant, high-level multireference (MR) methods are required to properly explain its electronic structure. MR diagnostics to estimate the magnitude of such static correlati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2bcc1b7fb8a932ace95529734e6b6523
https://pubmed.ncbi.nlm.nih.gov/36548116
https://pubmed.ncbi.nlm.nih.gov/36548116