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Exergy model of the human heart
Exergy model of the human heart
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Exergy model of the human heart

Mady, Carlos Eduardo Keutenedjian, 1984- Universidade Estadual de Campinas (Unicamp); Universidade Estadual De Campinas

MADY, Carlos Eduardo Keutenedjian. Exergy model of the human heart. Energy. London : Elsevier, 2016.. Vol. 117 (Dec., 2016), p. 612-619. Disponível em: https://hdl.handle.net/20.500.12733/1653771. Acesso em: 14 jun. 2024.

2016

Acesso online

2
Recent advances and applications of machine learning in solid-state materials science
Recent advances and applications of machine learning in solid-state materials science
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Recent advances and applications of machine learning in solid-state materials science

Schmidt, Jonathan ; Marques, Mário R. G. ; Botti, Silvana ; Marques, Miguel A. L.

npj computational materials, 2019-08, Vol.5 (1), p.1-36, Article 83 [Periódico revisado por pares]

London: Nature Publishing Group

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Propagators for the Time-Dependent Kohn–Sham Equations: Multistep, Runge–Kutta, Exponential Runge–Kutta, and Commutator Free Magnus Methods
Propagators for the Time-Dependent Kohn–Sham Equations: Multistep, Runge–Kutta, Exponential Runge–Kutta, and Commutator Free Magnus Methods
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Propagators for the Time-Dependent Kohn–Sham Equations: Multistep, Runge–Kutta, Exponential Runge–Kutta, and Commutator Free Magnus Methods

Gómez Pueyo, Adrián ; Marques, Miguel A. L ; Rubio, Angel ; Castro, Alberto

Journal of chemical theory and computation, 2018-06, Vol.14 (6), p.3040-3052 [Periódico revisado por pares]

United States: American Chemical Society

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4
Machine Learning the Physical Nonlocal Exchange–Correlation Functional of Density-Functional Theory
Machine Learning the Physical Nonlocal Exchange–Correlation Functional of Density-Functional Theory
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Machine Learning the Physical Nonlocal Exchange–Correlation Functional of Density-Functional Theory

Schmidt, Jonathan ; Benavides-Riveros, Carlos L ; Marques, Miguel A. L

The journal of physical chemistry letters, 2019-10, Vol.10 (20), p.6425-6431 [Periódico revisado por pares]

American Chemical Society

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5
Predicting the Thermodynamic Stability of Solids Combining Density Functional Theory and Machine Learning
Predicting the Thermodynamic Stability of Solids Combining Density Functional Theory and Machine Learning
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Predicting the Thermodynamic Stability of Solids Combining Density Functional Theory and Machine Learning

Schmidt, Jonathan ; Shi, Jingming ; Borlido, Pedro ; Chen, Liming ; Botti, Silvana ; Marques, Miguel A. L

Chemistry of materials, 2017-06, Vol.29 (12), p.5090-5103 [Periódico revisado por pares]

American Chemical Society

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Benchmarking the Starting Points of the GW Approximation for Molecules
Benchmarking the Starting Points of the GW Approximation for Molecules
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Benchmarking the Starting Points of the GW Approximation for Molecules

Bruneval, Fabien ; Marques, Miguel A. L

Journal of chemical theory and computation, 2013-01, Vol.9 (1), p.324-329 [Periódico revisado por pares]

United States: American Chemical Society

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7
Neural network force fields for simple metals and semiconductors: construction and application to the calculation of phonons and melting temperatures
Neural network force fields for simple metals and semiconductors: construction and application to the calculation of phonons and melting temperatures
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Neural network force fields for simple metals and semiconductors: construction and application to the calculation of phonons and melting temperatures

Marques, Mário R G ; Wolff, Jakob ; Steigemann, Conrad ; Marques, Miguel A L

Physical chemistry chemical physics : PCCP, 2019, Vol.21 (12), p.6506-6516 [Periódico revisado por pares]

England: Royal Society of Chemistry

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Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems
Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems
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Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems

Andrade, Xavier ; Strubbe, David ; De Giovannini, Umberto ; Larsen, Ask Hjorth ; Oliveira, Micael J. T ; Alberdi-Rodriguez, Joseba ; Varas, Alejandro ; Theophilou, Iris ; Helbig, Nicole ; Verstraete, Matthieu J ; Stella, Lorenzo ; Nogueira, Fernando ; Aspuru-Guzik, Alán ; Castro, Alberto ; Marques, Miguel A. L ; Rubio, Angel

Physical chemistry chemical physics : PCCP, 2015-01, Vol.17 (47), p.31371-31396 [Periódico revisado por pares]

England: Royal Society of Chemistry

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9
Computational acceleration of prospective dopant discovery in cuprous iodide
Computational acceleration of prospective dopant discovery in cuprous iodide
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Computational acceleration of prospective dopant discovery in cuprous iodide

Grau inyt, Migl ; Botti, Silvana ; Marques, Miguel A. L ; Goedecker, Stefan ; Flores-Livas, José A

Physical chemistry chemical physics : PCCP, 2019, Vol.21 (35), p.18839-18849 [Periódico revisado por pares]

England: Royal Society of Chemistry

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Double perovskites as p-type conducting transparent semiconductors: a high-throughput search
Double perovskites as p-type conducting transparent semiconductors: a high-throughput search
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Double perovskites as p-type conducting transparent semiconductors: a high-throughput search

Wang, Hai-Chen ; Pistor, Paul ; Marques, Miguel A. L ; Botti, Silvana

Journal of materials chemistry. A, Materials for energy and sustainability, 2019, Vol.7 (24), p.1475-14711 [Periódico revisado por pares]

Cambridge: Royal Society of Chemistry

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Deste Autor:

  1. Freitas, E
  2. Freitas, D
  3. Lima, F
  4. Vendruscolo, C
  5. Totti, L

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