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Title: Electronic spectra from TDDFT and machine learning in chemical space

Authors:
 [1];  [2];  [2];  [3]
  1. Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
  2. Department of Chemistry and Biochemistry, California State University, 1250 Bellflower Boulevard, Long Beach, California 90840, USA
  3. Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland, Argonne Leadership Computing Facility, Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, Illinois 60439, USA
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1229636
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
The Journal of Chemical Physics
Additional Journal Information:
Journal Name: The Journal of Chemical Physics Journal Volume: 143 Journal Issue: 8; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics
Country of Publication:
United States
Language:
English

Citation Formats

Ramakrishnan, Raghunathan, Hartmann, Mia, Tapavicza, Enrico, and von Lilienfeld, O. Anatole. Electronic spectra from TDDFT and machine learning in chemical space. United States: N. p., 2015. Web. doi:10.1063/1.4928757.
Ramakrishnan, Raghunathan, Hartmann, Mia, Tapavicza, Enrico, & von Lilienfeld, O. Anatole. Electronic spectra from TDDFT and machine learning in chemical space. United States. doi:10.1063/1.4928757.
Ramakrishnan, Raghunathan, Hartmann, Mia, Tapavicza, Enrico, and von Lilienfeld, O. Anatole. Tue . "Electronic spectra from TDDFT and machine learning in chemical space". United States. doi:10.1063/1.4928757.
@article{osti_1229636,
title = {Electronic spectra from TDDFT and machine learning in chemical space},
author = {Ramakrishnan, Raghunathan and Hartmann, Mia and Tapavicza, Enrico and von Lilienfeld, O. Anatole},
abstractNote = {},
doi = {10.1063/1.4928757},
journal = {The Journal of Chemical Physics},
number = 8,
volume = 143,
place = {United States},
year = {2015},
month = {8}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1063/1.4928757

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Cited by: 10 works
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Works referenced in this record:

Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond
journal, November 2014

  • Gasparotto, Piero; Ceriotti, Michele
  • The Journal of Chemical Physics, Vol. 141, Issue 17
  • DOI: 10.1063/1.4900655

Generalized Gradient Approximation Made Simple
journal, October 1996

  • Perdew, John P.; Burke, Kieron; Ernzerhof, Matthias
  • Physical Review Letters, Vol. 77, Issue 18, p. 3865-3868
  • DOI: 10.1103/PhysRevLett.77.3865

Photoelectrochemical cells
journal, November 2001


Machine learning for many-body physics: The case of the Anderson impurity model
journal, October 2014

  • Arsenault, Louis-François; Lopez-Bezanilla, Alejandro; von Lilienfeld, O. Anatole
  • Physical Review B, Vol. 90, Issue 15
  • DOI: 10.1103/PhysRevB.90.155136

Finding Density Functionals with Machine Learning
journal, June 2012


A Computational Investigation of Organic Dyes for Dye-Sensitized Solar Cells: Benchmark, Strategies, and Open Issues
journal, March 2010

  • Pastore, Mariachiara; Mosconi, Edoardo; De Angelis, Filippo
  • The Journal of Physical Chemistry C, Vol. 114, Issue 15
  • DOI: 10.1021/jp100713r

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space
journal, June 2015

  • Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan
  • The Journal of Physical Chemistry Letters, Vol. 6, Issue 12
  • DOI: 10.1021/acs.jpclett.5b00831

Using Molecular Similarity to Develop Reliable Models of Chemical Reactions in Complex Environments
journal, November 2009

  • Ediz, Volkan; Monda, Anthony C.; Brown, Robert P.
  • Journal of Chemical Theory and Computation, Vol. 5, Issue 12
  • DOI: 10.1021/ct9004195

Adiabatic time-dependent density functional methods for excited state properties
journal, October 2002

  • Furche, Filipp; Ahlrichs, Reinhart
  • The Journal of Chemical Physics, Vol. 117, Issue 16
  • DOI: 10.1063/1.1508368

Highly Efficient and Photostable Photosensitizer Based on BODIPY Chromophore
journal, September 2005

  • Yogo, Takatoshi; Urano, Yasuteru; Ishitsuka, Yukiko
  • Journal of the American Chemical Society, Vol. 127, Issue 35
  • DOI: 10.1021/ja0528533

The big challenges of big data
journal, June 2013


Many Molecular Properties from One Kernel in Chemical Space
journal, April 2015

  • Ramakrishnan, Raghunathan; von Lilienfeld, O. Anatole
  • CHIMIA International Journal for Chemistry, Vol. 69, Issue 4
  • DOI: 10.2533/chimia.2015.182

Double excitations within time-dependent density functional theory linear response
journal, April 2004

  • Maitra, Neepa T.; Zhang, Fan; Cave, Robert J.
  • The Journal of Chemical Physics, Vol. 120, Issue 13
  • DOI: 10.1063/1.1651060

Machine learning of molecular electronic properties in chemical compound space
journal, September 2013


Benchmarking Coupled Cluster Methods on Valence Singlet Excited States
journal, July 2014

  • Kánnár, Dániel; Szalay, Péter G.
  • Journal of Chemical Theory and Computation, Vol. 10, Issue 9
  • DOI: 10.1021/ct500495n

Optimizing transition states via kernel-based machine learning
journal, May 2012

  • Pozun, Zachary D.; Hansen, Katja; Sheppard, Daniel
  • The Journal of Chemical Physics, Vol. 136, Issue 17
  • DOI: 10.1063/1.4707167

Excited-State Dynamics of Isolated and Microsolvated Cinnamate-Based UV-B Sunscreens
journal, July 2014

  • Tan, Eric M. M.; Hilbers, Michiel; Buma, Wybren J.
  • The Journal of Physical Chemistry Letters, Vol. 5, Issue 14
  • DOI: 10.1021/jz501140b

Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties
journal, April 2015

  • von Lilienfeld, O. Anatole; Ramakrishnan, Raghunathan; Rupp, Matthias
  • International Journal of Quantum Chemistry, Vol. 115, Issue 16
  • DOI: 10.1002/qua.24912

Improvements on the direct SCF method: Improved Direct SCF Method
journal, January 1989

  • Häser, Marco; Ahlrichs, Reinhart
  • Journal of Computational Chemistry, Vol. 10, Issue 1
  • DOI: 10.1002/jcc.540100111

CC2 excitation energy calculations on large molecules using the resolution of the identity approximation
journal, January 2000

  • Hättig, Christof; Weigend, Florian
  • The Journal of Chemical Physics, Vol. 113, Issue 13
  • DOI: 10.1063/1.1290013

A new hybrid exchange–correlation functional using the Coulomb-attenuating method (CAM-B3LYP)
journal, July 2004

  • Yanai, Takeshi; Tew, David P.; Handy, Nicholas C.
  • Chemical Physics Letters, Vol. 393, Issue 1-3, p. 51-57
  • DOI: 10.1016/j.cplett.2004.06.011

Using molecular similarity to construct accurate semiempirical electronic structure theories
journal, September 2004

  • Janesko, Benjamin G.; Yaron, David
  • The Journal of Chemical Physics, Vol. 121, Issue 12
  • DOI: 10.1063/1.1785771

Oscillator Strength: How Does TDDFT Compare to EOM-CCSD?
journal, December 2010

  • Caricato, Marco; Trucks, Gary W.; Frisch, Michael J.
  • Journal of Chemical Theory and Computation, Vol. 7, Issue 2
  • DOI: 10.1021/ct100662n

Self-Consistent Equations Including Exchange and Correlation Effects
journal, November 1965


Balanced basis sets of split valence, triple zeta valence and quadruple zeta valence quality for H to Rn: Design and assessment of accuracy
journal, January 2005

  • Weigend, Florian; Ahlrichs, Reinhart
  • Physical Chemistry Chemical Physics, Vol. 7, Issue 18, p. 3297-3305
  • DOI: 10.1039/b508541a

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
journal, January 2012


Improving the performance of doped π-conjugated polymers for use in organic light-emitting diodes
journal, June 2000

  • Gross, Markus; Müller, David C.; Nothofer, Heinz-Georg
  • Nature, Vol. 405, Issue 6787
  • DOI: 10.1038/35015037

Design strategies of metal free-organic sensitizers for dye sensitized solar cells: Role of donor and acceptor monomers
journal, June 2014

  • Tseng, Chieh-Yu; Taufany, Fadlilatul; Nachimuthu, Santhanamoorthi
  • Organic Electronics, Vol. 15, Issue 6
  • DOI: 10.1016/j.orgel.2014.03.022

Excitation energies in density functional theory: An evaluation and a diagnostic test
journal, January 2008

  • Peach, Michael J. G.; Benfield, Peter; Helgaker, Trygve
  • The Journal of Chemical Physics, Vol. 128, Issue 4
  • DOI: 10.1063/1.2831900

Modeling electronic quantum transport with machine learning
journal, June 2014


Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach
journal, April 2015

  • Ramakrishnan, Raghunathan; Dral, Pavlo O.; Rupp, Matthias
  • Journal of Chemical Theory and Computation, Vol. 11, Issue 5
  • DOI: 10.1021/acs.jctc.5b00099

Energy Transfer Tunes Phosphorescent Color of Single-Dopant White OLEDs
journal, November 2011

  • Han, Juan; Chen, XueBo; Shen, Lin
  • Chemistry - A European Journal, Vol. 17, Issue 50
  • DOI: 10.1002/chem.201102702

A vision for data science
journal, January 2013


Correlated electron dynamics with time-dependent quantum Monte Carlo: Three-dimensional helium
journal, July 2011

  • Christov, Ivan P.
  • The Journal of Chemical Physics, Vol. 135, Issue 4
  • DOI: 10.1063/1.3615061

Assessing Excited State Methods by Adiabatic Excitation Energies
journal, July 2011

  • Send, Robert; Kühn, Michael; Furche, Filipp
  • Journal of Chemical Theory and Computation, Vol. 7, Issue 8
  • DOI: 10.1021/ct200272b

Assessment of the Perdew–Burke–Ernzerhof exchange-correlation functional
journal, March 1999

  • Ernzerhof, Matthias; Scuseria, Gustavo E.
  • The Journal of Chemical Physics, Vol. 110, Issue 11
  • DOI: 10.1063/1.478401

Toward reliable density functional methods without adjustable parameters: The PBE0 model
journal, April 1999

  • Adamo, Carlo; Barone, Vincenzo
  • The Journal of Chemical Physics, Vol. 110, Issue 13
  • DOI: 10.1063/1.478522

Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17
journal, November 2012

  • Ruddigkeit, Lars; van Deursen, Ruud; Blum, Lorenz C.
  • Journal of Chemical Information and Modeling, Vol. 52, Issue 11
  • DOI: 10.1021/ci300415d

Unravelling the details of vitamin D photosynthesis by non-adiabatic molecular dynamics simulations
journal, January 2011

  • Tapavicza, Enrico; Meyer, Alexander M.; Furche, Filipp
  • Physical Chemistry Chemical Physics, Vol. 13, Issue 47
  • DOI: 10.1039/c1cp21292c

Inhomogeneous Electron Gas
journal, November 1964


Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies
journal, July 2013

  • Hansen, Katja; Montavon, Grégoire; Biegler, Franziska
  • Journal of Chemical Theory and Computation, Vol. 9, Issue 8
  • DOI: 10.1021/ct400195d

Electronic spectra from TDDFT and machine learning in chemical space
journal, August 2015

  • Ramakrishnan, Raghunathan; Hartmann, Mia; Tapavicza, Enrico
  • The Journal of Chemical Physics, Vol. 143, Issue 8
  • DOI: 10.1063/1.4928757

Extensive TD-DFT Benchmark: Singlet-Excited States of Organic Molecules
journal, August 2009

  • Jacquemin, Denis; Wathelet, Valérie; Perpète, Eric A.
  • Journal of Chemical Theory and Computation, Vol. 5, Issue 9
  • DOI: 10.1021/ct900298e

First principles view on chemical compound space: Gaining rigorous atomistic control of molecular properties
journal, February 2013

  • von Lilienfeld, O. Anatole
  • International Journal of Quantum Chemistry, Vol. 113, Issue 12
  • DOI: 10.1002/qua.24375

Inverse Strategies for Molecular Design
journal, January 1996

  • Kuhn, Christoph; Beratan, David N.
  • The Journal of Physical Chemistry, Vol. 100, Issue 25
  • DOI: 10.1021/jp960518i

A Simplex Method for Function Minimization
journal, January 1965


Ultrafast Infrared Spectroscopy of Riboflavin: Dynamics, Electronic Structure, and Vibrational Mode Analysis
journal, October 2008

  • Wolf, Matthias M. N.; Schumann, Christian; Gross, Ruth
  • The Journal of Physical Chemistry B, Vol. 112, Issue 42
  • DOI: 10.1021/jp804231c

Kernel density estimation via diffusion
journal, October 2010

  • Botev, Z. I.; Grotowski, J. F.; Kroese, D. P.
  • The Annals of Statistics, Vol. 38, Issue 5
  • DOI: 10.1214/10-AOS799

Long-range charge-transfer excited states in time-dependent density functional theory require non-local exchange
journal, August 2003

  • Dreuw, Andreas; Weisman, Jennifer L.; Head-Gordon, Martin
  • The Journal of Chemical Physics, Vol. 119, Issue 6
  • DOI: 10.1063/1.1590951

Rationale for mixing exact exchange with density functional approximations
journal, December 1996

  • Perdew, John P.; Ernzerhof, Matthias; Burke, Kieron
  • The Journal of Chemical Physics, Vol. 105, Issue 22, p. 9982-9985
  • DOI: 10.1063/1.472933

Quantum chemistry structures and properties of 134 kilo molecules
journal, August 2014

  • Ramakrishnan, Raghunathan; Dral, Pavlo O.; Rupp, Matthias
  • Scientific Data, Vol. 1, Issue 1
  • DOI: 10.1038/sdata.2014.22

Relaxed active space: Fixing tailored-CC with high order coupled cluster. I
journal, December 2012

  • Melnichuk, Anna; Bartlett, Rodney J.
  • The Journal of Chemical Physics, Vol. 137, Issue 21
  • DOI: 10.1063/1.4767900