Search Results - "Sauceda, Huziel E"

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  1. 1

    Towards exact molecular dynamics simulations with machine-learned force fields by Chmiela, Stefan, Sauceda, Huziel E., Müller, Klaus-Robert, Tkatchenko, Alexandre

    Published in Nature communications (24-09-2018)
    “…Molecular dynamics (MD) simulations employing classical force fields constitute the cornerstone of contemporary atomistic modeling in chemistry, biology, and…”
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  2. 2

    SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects by Unke, Oliver T., Chmiela, Stefan, Gastegger, Michael, Schütt, Kristof T., Sauceda, Huziel E., Müller, Klaus-Robert

    Published in Nature communications (14-12-2021)
    “…Machine-learned force fields combine the accuracy of ab initio methods with the efficiency of conventional force fields. However, current machine-learned force…”
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  3. 3

    Machine learning of accurate energy-conserving molecular force fields by Chmiela, Stefan, Tkatchenko, Alexandre, Sauceda, Huziel E, Poltavsky, Igor, Schütt, Kristof T, Müller, Klaus-Robert

    Published in Science advances (01-05-2017)
    “…Using conservation of energy-a fundamental property of closed classical and quantum mechanical systems-we develop an efficient gradient-domain machine learning…”
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  4. 4

    BIGDML—Towards accurate quantum machine learning force fields for materials by Sauceda, Huziel E., Gálvez-González, Luis E., Chmiela, Stefan, Paz-Borbón, Lauro Oliver, Müller, Klaus-Robert, Tkatchenko, Alexandre

    Published in Nature communications (29-06-2022)
    “…Machine-learning force fields (MLFF) should be accurate, computationally and data efficient, and applicable to molecules, materials, and interfaces thereof…”
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  5. 5

    Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature by Sauceda, Huziel E., Vassilev-Galindo, Valentin, Chmiela, Stefan, Müller, Klaus-Robert, Tkatchenko, Alexandre

    Published in Nature communications (19-01-2021)
    “…Nuclear quantum effects (NQE) tend to generate delocalized molecular dynamics due to the inclusion of the zero point energy and its coupling with the…”
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  6. 6

    Mechanical Vibrations of Atomically Defined Metal Clusters: From Nano- to Molecular-Size Oscillators by Maioli, Paolo, Stoll, Tatjana, Sauceda, Huziel E, Valencia, Israel, Demessence, Aude, Bertorelle, Franck, Crut, Aurélien, Vallée, Fabrice, Garzón, Ignacio L, Cerullo, Giulio, Del Fatti, Natalia

    Published in Nano letters (14-11-2018)
    “…Acoustic vibrations of small nanoparticles are still ruled by continuum mechanics laws down to diameters of a few nanometers. The elastic behavior at lower…”
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  7. 7

    Intercavity polariton slows down dynamics in strongly coupled cavities by García Jomaso, Yesenia A., Vargas, Brenda, Domínguez, David Ley, Armenta-Rico, Román J., Sauceda, Huziel E., Ordoñez-Romero, César L., Lara-García, Hugo A., Camacho-Guardian, Arturo, Pirruccio, Giuseppe

    Published in Nature communications (04-04-2024)
    “…Band engineering stands as an efficient route to induce strongly correlated quantum many-body phenomena. Besides inspiring analogies among diverse physical…”
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  8. 8

    Size and Shape Dependence of the Vibrational Spectrum and Low-Temperature Specific Heat of Au Nanoparticles by Sauceda, Huziel E, Salazar, Fernando, Pérez, Luis A, Garzón, Ignacio L

    Published in Journal of physical chemistry. C (27-11-2013)
    “…The vibrational spectra of metal nanoparticles are a signature of their structures and determine the low-temperature behavior of their thermal properties. In…”
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  9. 9

    On the forbidden graphene’s ZO (out-of-plane optic) phononic band-analog vibrational modes in fullerenes by Pedroza-Montero, Jesús N., Garzón, Ignacio L., Sauceda, Huziel E.

    Published in Communications chemistry (05-07-2021)
    “…The study of nanostructures’ vibrational properties is at the core of nanoscience research. They are known to represent a fingerprint of the system as well as…”
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  10. 10

    Machine Learning Force Fields by Unke, Oliver T, Chmiela, Stefan, Sauceda, Huziel E, Gastegger, Michael, Poltavsky, Igor, Schütt, Kristof T, Tkatchenko, Alexandre, Müller, Klaus-Robert

    Published in Chemical reviews (25-08-2021)
    “…In recent years, the use of machine learning (ML) in computational chemistry has enabled numerous advances previously out of reach due to the computational…”
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  11. 11

    sGDML: Constructing accurate and data efficient molecular force fields using machine learning by Chmiela, Stefan, Sauceda, Huziel E., Poltavsky, Igor, Müller, Klaus-Robert, Tkatchenko, Alexandre

    Published in Computer physics communications (01-07-2019)
    “…We present an optimized implementation of the recently proposed symmetric gradient domain machine learning (sGDML) model. The sGDML model is able to faithfully…”
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  12. 12

    Vibrational Spectrum, Caloric Curve, Low-Temperature Heat Capacity, and Debye Temperature of Sodium Clusters: The Na139 + Case by Sauceda, Huziel E., Pelayo, J. Jesús, Salazar, Fernando, Pérez, Luis A., Garzón, Ignacio L.

    Published in Journal of physical chemistry. C (30-05-2013)
    “…The vibrational properties of atomic clusters are a fingerprint of their structures and can be used to investigate their thermodynamic behavior at low…”
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  13. 13

    Structural Determination of Metal Nanoparticles from their Vibrational (Phonon) Density of States by Sauceda, Huziel E, Garzón, Ignacio L

    Published in Journal of physical chemistry. C (21-05-2015)
    “…The vibrational (phonon) density of states of metal nanoparticles with size between 2 and 6 nm can be measured using nuclear resonant inelastic X-ray or…”
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  14. 14

    Accurate global machine learning force fields for molecules with hundreds of atoms by Chmiela, Stefan, Vassilev-Galindo, Valentin, Unke, Oliver T, Kabylda, Adil, Sauceda, Huziel E, Tkatchenko, Alexandre, Müller, Klaus-Robert

    Published in Science advances (13-01-2023)
    “…Global machine learning force fields, with the capacity to capture collective interactions in molecular systems, now scale up to a few dozen atoms due to…”
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  15. 15

    Interpolating Nonadiabatic Molecular Dynamics Hamiltonian with Bidirectional Long Short-Term Memory Networks by Wang, Bipeng, Winkler, Ludwig, Wu, Yifan, Müller, Klaus-Robert, Sauceda, Huziel E., Prezhdo, Oleg V.

    Published in The journal of physical chemistry letters (10-08-2023)
    “…Essential for understanding far-from-equilibrium processes, nonadiabatic (NA) molecular dynamics (MD) requires expensive calculations of the excitation…”
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  16. 16

    Size evolution of characteristic acoustic oscillations of fullerenes and its connection to continuum elasticity theory by Pedroza-Montero, Jesús N., Garzón, Ignacio L., Sauceda, Huziel E.

    “…We performed a theoretical investigation, based on density functional theory, on the vibrational properties of fullerenes and its dependence with size ( 20 →…”
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  17. 17

    High-fidelity molecular dynamics trajectory reconstruction with bi-directional neural networks by Winkler, Ludwig, Müller, Klaus-Robert, Sauceda, Huziel E

    Published in Machine learning: science and technology (01-06-2022)
    “…Abstract Molecular dynamics (MD) simulations are a cornerstone in science, enabling the investigation of a system’s thermodynamics all the way to analyzing…”
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  18. 18

    Vibrational Properties of Metal Nanoparticles: Atomistic Simulation and Comparison with Time-Resolved Investigation by Sauceda, Huziel E, Mongin, Denis, Maioli, Paolo, Crut, Aurélien, Pellarin, Michel, Del Fatti, Natalia, Vallée, Fabrice, Garzón, Ignacio L

    Published in Journal of physical chemistry. C (29-11-2012)
    “…Knowledge of the vibrational spectrum of metal clusters and nanoparticles is of fundamental interest since it is a signature of their morphology, and it can be…”
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  19. 19
  20. 20

    On the forbidden graphene's ZO (out-of-plane optic) phononic band-analog vibrational modes in fullerenes by Pedroza-Montero, Jesús N, Garzón, Ignacio L, Sauceda, Huziel E

    Published 10-01-2021
    “…The study of nanostructures' vibrational properties is at the core of nanoscience research, they are known to represent a fingerprint of the system as well as…”
    Get full text
    Journal Article