Machine learning modeling of time-dependent corrosion rates of carbon steel in presence of corrosion inhibitors M Aghaaminiha, R Mehrani, M Colahan, B Brown, M Singer, S Nesic, ... Corrosion Science 193, 109904, 2021 | 42 | 2021 |
A machine learning approach to estimation of phase diagrams for three-component lipid mixtures M Aghaaminiha, SA Ghanadian, E Ahmadi, AM Farnoud Biochimica et Biophysica Acta (BBA)-Biomembranes 1862 (9), 183350, 2020 | 26 | 2020 |
Quantitative relationship between cholesterol distribution and ordering of lipids in asymmetric lipid bilayers M Aghaaminiha, AM Farnoud, S Sharma Soft Matter 17 (10), 2742-2752, 2021 | 23 | 2021 |
Forecasting ATM cash demand before and during the COVID-19 pandemic using an extensive evaluation of statistical and machine learning models A Fallahtafti, M Aghaaminiha, S Akbarghanadian, GR Weckman SN computer science 3 (2), 164, 2022 | 14 | 2022 |
Comparison of machine learning methodologies for predicting kinetics of hydrothermal carbonization of selective biomass M Aghaaminiha, R Mehrani, T Reza, S Sharma Biomass Conversion and Biorefinery 13 (11), 9855-9864, 2023 | 9 | 2023 |
Mesoscale Aggregation of Sulfur-Rich Asphaltenes: In Situ Microscopy and Coarse-Grained Molecular Simulation CB Hammond, M Aghaaminiha, S Sharma, C Shen, H Chen, L Wu Langmuir 38 (22), 6896-6910, 2022 | 3 | 2022 |
Application of Molecular Simulations and Machine Learning Methods to Study Biological and Metallic Interfaces in Aqueous Environment M Aghaaminiha Ohio University, 2021 | 2 | 2021 |
New Insights into the Formation of Aggregates of Bidisperse Nano- and Microplastics in Water Based on the Analysis of In Situ Microscopy and Molecular Simulation CB Hammond, A Faeli Qadikolae, M Aghaaminiha, S Sharma, L Wu Langmuir, 2024 | | 2024 |
Interdependence of cholesterol distribution and conformational order in lipid bilayers M Aghaaminiha, AM Farnoud, S Sharma Biointerphases 18 (3), 2023 | | 2023 |
Numerical Simulation and Sensitivity Analysis of a Membrane Bio-Reactor (MBR) process Treating Produced Water (PW) Constituents: Toluene, Naphthalene, and m-Cresol M Aghaaminiha New Mexico Institute of Mining and Technology, 2015 | | 2015 |