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Luis Briceno-Mena
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Electrochemical pumping for challenging hydrogen separations
G Venugopalan, D Bhattacharya, E Andrews, L Briceno-Mena, ...
ACS Energy Letters 7 (4), 1322-1329, 2022
342022
Machine learning for guiding high-temperature PEM fuel cells with greater power density
LA Briceno-Mena, G Venugopalan, JA Romagnoli, CG Arges
Patterns 2 (2), 2021
222021
Machine learning-based surrogate models and transfer learning for derivative free optimization of HT-PEM fuel cells
LA Briceno-Mena, CG Arges, JA Romagnoli
Computers & Chemical Engineering 171, 108159, 2023
182023
PemNet: A Transfer Learning-Based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems
LA Briceno-Mena, JA Romagnoli, CG Arges
Industrial & Engineering Chemistry Research 61 (9), 3350-3357, 2022
142022
Determining ion activity coefficients in ion-exchange membranes with machine learning and molecular dynamics simulations
HK Gallage Dona, T Olayiwola, LA Briceno-Mena, CG Arges, R Kumar, ...
Industrial & Engineering Chemistry Research 62 (24), 9533-9548, 2023
112023
Unsupervised learning: Local and global structure preservation in industrial data
EE Seghers, LA Briceno-Mena, JA Romagnoli
Computers & Chemical Engineering 178, 108378, 2023
52023
GH; Romagnoli, JA; Janik, MJ; Arges, CG Deconvoluting charge-transfer, mass transfer, and ohmic resistances in phosphonic acid− sulfonic acid ionomer binders used in …
K Arunagiri, AJW Wong, L Briceno-Mena, HM Elsayed
Energy Environ. Sci 16 (12), 5916-5932, 2023
52023
Deconvoluting charge-transfer, mass transfer, and ohmic resistances in phosphonic acid–sulfonic acid ionomer binders used in electrochemical hydrogen pumps
K Arunagiri, AJW Wong, L Briceno-Mena, HMGH Elsayed, JA Romagnoli, ...
Energy & Environmental Science 16 (12), 5916-5932, 2023
52023
Data mining and knowledge discovery in chemical processes: Effect of alternative processing techniques
LA Briceno-Mena, M Nnadili, MG Benton, JA Romagnoli
Data-Centric Engineering 3, e18, 2022
52022
Optimization of Multi-Modal Classification for Process Monitoring
Z Webb, M Nnadili, E Seghers, L Briceno-Mena, J Romagnoli
Frontiers in Chemical Engineering 4, 78, 2022
42022
A Machine Learning Approach for Device Design from Materials and Operation Data
LA Briceno-Mena, G Venugopalan, CC Arges, JA Romagnoli
Computer Aided Chemical Engineering 50, 279-285, 2021
42021
Hybrid Modeling for Electrochemical Systems
LA Briceno-Mena
22023
Synergizing data-driven and knowledge-based hybrid models for ionic separations
T Olayiwola, LA Briceno-Mena, CG Arges, JA Romagnoli
ACS ES&T Engineering 4 (12), 3032-3044, 2024
12024
Feature Embedding of Molecular Dynamics-Based Descriptors for Modeling Electrochemical Separation Processes
HKG Dona, T Olayiwola, LA Briceno-Mena, CG Arges, R Kumar, ...
Computer Aided Chemical Engineering 52, 1451-1456, 2023
12023
Introduction to Formulation Optimization
A Schmidt, L Briceno-Mena, S Rajagopalan, K Ma, B Reiner, B Braun
The Digital Transformation of Product Formulation, 207-235, 2025
2025
AI in Chemical Engineering: Unlocking the Power Within Data
JA Romagnoli, L Briceño-Mena, V Manee
CRC Press, 2024
2024
Optimization and Machine Learning in Chemical Manufacturing
L Briceno-Mena, S Iyer
2024 Spring Meeting & 20th Global Congress on Process Safety, 2024
2024
A Practitioner’s Guide to Machine Learning Applications in Chemical Engineering
L Briceno-Mena, J Romagnoli
2024 Spring Meeting & 20th Global Congress on Process Safety, 2024
2024
A microfluidic approach to study variations in Chlamydomonas reinhardtii alkaline phosphatase activity in response to phosphate availability
A Rahnama, M Vaithiyanathan, L Briceno-Mena, TM Dugas, KL Yates, ...
Analyst 149 (16), 4256-4266, 2024
2024
Automated Synthesis of Hybrid Models for Ionic Separations
T Olayiwola, L Briceno-Mena, T Kulkarni, C Arges, R Kumar, ...
2023 AIChE Annual Meeting, 2023
2023
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