E-LIB Suche - Ergebnisse für: Briceno-Mena, Luis A.

1

A microfluidic approach to study variations in Chlamydomona..:

Rahnama, Alireza ; Vaithiyanathan, Manibarathi ; Briceno-Mena, Luis...
The Analyst. , 2024

2

Unsupervised learning: Local and global structure preservat..:

Seghers, Estelle E. ; Briceno-Mena, Luis A. ; Romagnoli, José A.
Computers & Chemical Engineering. 178 (2023) - p. 108378 , 2023

Link: https://doi.org/10.1016/..

3

Deconvoluting charge-transfer, mass transfer, and ohmic res..:

Arunagiri, Karthik ; Wong, Andrew Jark-Wah ; Briceno-Mena, Luis...
Energy & Environmental Science. 16 (2023) 12 - p. 5916-5932 , 2023

Link: https://doi.org/10.1039/..

4

Machine learning-based surrogate models and transfer learni..:

Briceno-Mena, Luis A. ; Arges, Christopher G. ; Romagnoli, Jose A.
Computers & Chemical Engineering. 171 (2023) - p. 108159 , 2023

Link: https://doi.org/10.1016/..

5

Determining Ion Activity Coefficients in Ion-Exchange Membr..:

Gallage Dona, Hishara Keshani ; Olayiwola, Teslim ; Briceno-Mena, Luis A....
Industrial & Engineering Chemistry Research. 62 (2023) 24 - p. 9533-9548 , 2023

Link: https://doi.org/10.1021/..

6

PemNet: A Transfer Learning-Based Modeling Approach of High..:

Briceno-Mena, Luis A. ; Romagnoli, José A. ; Arges, Christopher G.
Industrial & Engineering Chemistry Research. 61 (2022) 9 - p. 3350-3357 , 2022

Link: https://doi.org/10.1021/..

7

Electrochemical Pumping for Challenging Hydrogen Separation:

Venugopalan, Gokul ; Bhattacharya, Deepra ; Andrews, Evan...
ACS Energy Letters. 7 (2022) 4 - p. 1322-1329 , 2022

Link: https://doi.org/10.1021/..

8

Data mining and knowledge discovery in chemical processes: ..:

Briceno-Mena, Luis A. ; Nnadili, Miriam ; Benton, Michael G..
Data-Centric Engineering. 3 (2022) - p. , 2022

Link: https://doi.org/10.1017/..

9

A Machine Learning Approach for Device Design from Material..:

, In: 31st European Symposium on Computer Aided Process Engineering; Computer Aided Chemical Engineering,

Briceno-Mena, Luis A. ; Venugopalan, Gokul ; Arges, Christopher C.. - p. 279-285 , 2021

Link: https://doi.org/10.1016/..

10

Machine learning for guiding high-temperature PEM fuel cell..:

Briceno-Mena, Luis A. ; Venugopalan, Gokul ; Romagnoli, José A..
Patterns. 2 (2021) 2 - p. 100187 , 2021

Link: https://doi.org/10.1016/..

11

Machine learning for guiding high-temperature PEM fuel cell..:

Briceno-Mena, Luis A ; Venugopalan, Gokul ; Romagnoli, José A.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892359/. , 2021

Link: http://www.ncbi.nlm.nih...

12

PEMNET: A Transfer Learning-based Modeling Approach of High..:

Briceno-Mena, Luis A ; Arges, Christopher G ; Romagnoli, Jose A
http://arxiv.org/abs/2105.03057. , 2021

Link: http://arxiv.org/abs/210..

13

Heterogeneous Catalytic Ozonation of Phenol over Iron-based..:

Durán Herrera, Esteban ; Briceño Mena, Luis
Revista Ingeniería. 30 (2020) 2 - p. 1-13 , 2020

Link: https://doi.org/10.15517..

14

Data mining and knowledge discovery in chemical processes: ..:

Luis A. Briceno-Mena ; Miriam Nnadili ; Michael G. Benton.
https://www.cambridge.org/core/product/identifier/S2632673622000211/type/journal_article. , 2022

Link: https://doi.org/10.1017/..

15

Machine learning for guiding high-temperature PEM fuel cell..:

Luis A. Briceno-Mena ; Gokul Venugopalan ; José A. Romagnoli.
http://www.sciencedirect.com/science/article/pii/S2666389920302579. , 2021

Link: https://doi.org/10.1016/..