Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Caetano R, Miranda"'
Autor:
Dirk Wallacher, Leide P. Cavalcanti, Kenneth D. Knudsen, Caetano R. Miranda, Jon Otto Fossum, Alexsandro Kirch, Josef Breu, Matthias Daab, Martin Rieß, Patrick Loch, Vegard Josvanger, Fabiano Yokaichiya, Kristoffer William Bø Hunvik, Sven Grätz
Publikováno v:
14491-14499
Langmuir
Langmuir
Due to the compact two-dimensional interlayer pore space and the high density of interlayer molecular adsorption sites, clay minerals are competitive adsorption materials for carbon dioxide capture. We demonstrate that with a decreasing interlayer su
Publikováno v:
Journal of Energy Storage. 66:107470
Publikováno v:
Surface Science. 733:122302
Publikováno v:
Surface Science. 732:122283
Autor:
Rubens Caram, Caetano R. Miranda, Camilo A.F. Salvador, Dalton Daniel de Lima, Mariana R. Dal Bo
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Among many β-metastable alloys explored for biomedical applications, alloys from the Ti-Nb-Fe-Zr system present great potential regarding cost and mechanical strength. In this article, we take a new look at the possibility of using Fe as a minor all
Discovery of Low-Modulus Ti-Nb-Zr Alloys Based on Machine Learning and First-Principles Calculations
Publikováno v:
ACS Applied Materials & Interfaces. 12:56850-56861
The discovery of low-modulus Ti alloys for biomedical applications is challenging due to a vast number of compositions and available solute contents. In this work, machine learning (ML) methods are employed for the prediction of the bulk modulus (K)
CO2 Capture by Nickel Hydroxide Interstratified in the Nanolayered Space of a Synthetic Clay Mineral
Autor:
Leide P. Cavalcanti, Kenneth D. Knudsen, Caetano R. Miranda, Svemir Rudić, Kristoffer William Bø Hunvik, Alexsandro Kirch, Josef Breu, Dirk Wallacher, Konstanse Kvalem Seljelid, Paul Monceyron Røren, Patrick Loch, Heloisa N. Bordallo, Jon Otto Fossum
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
'Journal of Physical Chemistry C ', vol: 124, pages: 26222-26231 (2020)
Hunvik, K W B, Loch, P, Cavalcanti, L P, Seljelid, K K, Roren, P M, Rudic, S, Wallacher, D, Kirch, A, Knudsen, K D, Miranda, C R, Breu, J, Bordallo, H N & Possum, J O 2020, ' CO2 Capture by Nickel Hydroxide Interstratified in the Nanolayered Space of a Synthetic Clay Mineral ', Journal of Physical Chemistry C, vol. 124, no. 48, pp. 26222-26231 . https://doi.org/10.1021/acs.jpcc.0c07206
Universidade de São Paulo (USP)
instacron:USP
'Journal of Physical Chemistry C ', vol: 124, pages: 26222-26231 (2020)
Hunvik, K W B, Loch, P, Cavalcanti, L P, Seljelid, K K, Roren, P M, Rudic, S, Wallacher, D, Kirch, A, Knudsen, K D, Miranda, C R, Breu, J, Bordallo, H N & Possum, J O 2020, ' CO2 Capture by Nickel Hydroxide Interstratified in the Nanolayered Space of a Synthetic Clay Mineral ', Journal of Physical Chemistry C, vol. 124, no. 48, pp. 26222-26231 . https://doi.org/10.1021/acs.jpcc.0c07206
Clay minerals can adsorb large amounts of CO2 and are present in anthropogenic storage sites for CO2. Nanoscale functionalization of smectite clay minerals is essential for developing technologies for carbon sequestration based on these materials and
Autor:
Caetano R. Miranda, Naiyer Razmara, Alexsandro Kirch, Julio Romano Meneghini, Vladivostok Franz Suxo Mamani
Publikováno v:
Polytechnica. 3:54-65
This review brings an overview based on recent publications of multi-scale molecular modeling studies applied to the upstream Oil & Gas segment. These works provide suitable insights on technologies of Oil & Gas interest ranging from fluid properties
A Machine Learning Model for Adsorption Energies of Chemical Species Applied to CO2 Electroreduction
Autor:
Paulo H. R. Amaral, Alvaro D. Torrez-Baptista, Dawany Dionisio, Thiago Lopes, Julio R. Meneghini, Caetano R. Miranda
Publikováno v:
Journal of The Electrochemical Society. 169:116505
Machine learning methods are applied to obtain adsorption energies of different chemical species on (100), (111), and (211) FCC surfaces of several transition metals and Pb. Based on information available in databases containing adsorption energies o
Publikováno v:
Journal of Molecular Modeling. 27
Nanofluids have received a great deal of interest in recent years because of their various unique features. According to the findings, the addition of nanotubes to the base materials can drastically alter their properties. In the present work, the vi