Characterization of pores and microfractures in tight conglomerate reservoirs

Machine learning based prediction of metal hydrides for hydrogen storage, part I: Prediction of hydrogen weight percent

Alireza Rahnama, Guilherme Zepon, Seetharaman Sridhar · International Journal of Hydrogen Energy · 2019 · 129 citations

Natural Sciences, Materials Engineering, Materials Science +15

Machine learning analysis of alloying element effects on hydrogen storage properties of AB2 metal hydrides

Suwarno Suwarno, Ghazy Dicky, Abdillah Suyuthi et al. · International Journal of Hydrogen Energy · 2022 · 110 citations

Natural Sciences, Materials Engineering, Materials Science +15

Pore Structure Characterization of the Tight Reservoir: Systematic Integration of Mercury Injection and Nuclear Magnetic Resonance

Liang Wang, Ning Zhao, Liqiang Sima et al. · Energy & Fuels · 2018 · 105 citations

Engineering, Geology, Petroleum Engineering +17

Theoretical understandings, key technologies and practices of tight conglomerate oilfield efficient development: A case study of the Mahu oilfield, Junggar Basin, NW China

Guoxin Li, Jianhua Qin, Chenggang Xian et al. · Petroleum Exploration and Development · 2020 · 96 citations · Full text

Engineering, Geological Engineering, Petroleum Engineering +14

Comparison of support vector regression and random forest algorithms for estimating the SOFC output voltage by considering hydrogen flow rates

Feride Cansu İskenderoğlu, Mustafa Kaan Baltacıoğlu, Mehmet Hakan Demir et al. · International Journal of Hydrogen Energy · 2020 · 91 citations

Computing, Chemical Engineering, Data Mining +10