Welcome to the QM-RCD lab!

We are a small interdisciplinary team, working on theoretical and computational methods for quantum mechanical rational compound design (QM-RCD). Our lab was established in July of 2013. Our research falls into the realm of physical chemistry, and relies on theory and computations. Due to the interdisciplinary nature of our work, we rely heavily on physics, mathematics, and computer sciences, and we are active members of the university's Competence Center of Computational Sciences. Unfortunately, we lack the capacity to carry out our own experiments. Instead we compare our computational predictions to experimental results reported in the scientific literature, or we collaborate directly with experimentalists.


  • Google collaboration: Our first draft has been posted on the arxiv: "Fast machine learning models of electronic and energetic properties consistently reach approximation errors better than DFT accuracy", arxiv.org/abs/1702.05532
  • Jan 2017: The "53rd Symposium on Theoretical Chemistry-Big Data in Chemistry: From Molecular Structure to Condensed Phase Dynamics", organized in August in Basel by the Meuwly group and us, has come online!
    For registration and further details go to www.chemie.unibas.ch/~stc2017.
  • Jan 2017: Virtual reality immersion in electron density of drug-target complex
  • Dec 2016: Chemical derivatives of Diels-Alder transition states (generated by Anders)
  • Nov 2016: Grant awarded "Big Data for Computational Chemistry: Unified machine learning and sparse grid combination technique for quantum based molecular design" (NRP 75) by SNF on collaborative project with Harbrecht group in Mathematics
  • Nov 2016: Mehdi Segidhi joined our group as a Postdoc: Welcome, Mehdi!
  • Oct 2016: Anders Christensen joined our group as a Postdoc: Welcome, Anders!
  • Oct 2016: Heini (Stefan) Heinen joined our group as a PhD student: Welcome, Heini!
  • Sep 2016: Felix Phys Rev Lett on ML energies of 2 million crystals just came out!
  • Sep 2016: Dirk Bakowies joined our group as a senior research associate: Welcome, Dirk!
  • Sep 2016: Anne-Sophie Alingue joined our group as a PhD student: Welcome, Anne-Sophie!
  • Aug 2016: Marco Di Gennaro joined our group as a Postdoc: Welcome, Marco!
  • Aug 2016: Google grant awarded for machine learning!
  • Jun 2016: Anatole accepted an offer to return to the University of Basel.
  • May 2016: Bing published some of his PhD work in Angewandte Chemie International Edition! Congratulations, Bing!
  • Apr 2016: We have been awarded an Odysseus grant from the the Flemish Science Foundation.
  • Jan 2016: Anatole has started as Associate Professor at the Lab of General Chemistry, Free University of Brussels, Belgium.
  • Nov 2015: Approved! CECAM workshop on ''Exploring Chemical Space with Machine Learning and Quantum Mechanics'' (ETHZ, May 30 - Jun 3, 2016)
  • Oct 2015: Rafael Sarmiento Perez joined our group as a Postdoc: Welcome, Rafael!
  • Sep 2015: Bing Huang joined our group as a Postdoc: Welcome, Bing!
  • Aug 2015: Our paper on ML predictions of atomic properties is out! Have a look at an atom in a molecule:

    Moving vertical red bar indicates instantaneous C-NMR shift of atom highlighted in yellow. The bar advances at a rate of 8 molecules per second, as the atom navigates through different molecular environments drawn from a data-set of over 50 k C-NMR shifts whose distribution is given on the horizontal axis.
    See here for more details: "Machine Learning for Quantum Mechanical Properties of Atoms in Molecules", M. Rupp, R. Ramakrishnan, OAvL,
    J. Phys. Chem. Lett. 6 3309 (2015). arxiv.org/abs/1505.00350
  • Apr 2015: Grant awarded for machine learning of reaction rates!
  • Mar 2015: Anatole's talk on "Machine Learning Models in Chemical Space" in February at UCLA came online .
  • Jan 2015: Zhenwei Li joined our group as a Postdoc. Welcome, Zhenwei!
  • Jan 2015: Diana Tahchieva joined our group as a PhD student. Welcome, Diana!
  • Nov 2014: Felix Faber joined our group as a PhD student. Welcome, Felix!
  • Sep 2014: Raghu won the "Best Oral Presentation Award at the Fall Meeting" of the Swiss Chemical Society. Congratulations!
  • Sep 2014: Alisa Solovyeva joined our group as a Postdoc. Welcome, Alisa!
  • Jun 2014: We are looking for PhD students, please visit the section OPENINGS for more details!
  • Jan 2014: Anatole's ZURICH.MINDS talk on The Amazingly Huge Chemical Space (given in Dec 2013) just came online.
  • Dec 2013: The Swiss National Science Foundation awarded 18M CHF to our MARVEL proposal (lead: Prof. N. Marzari at EPFL) on computational materials design.
  • Nov 2013: The U.S. Department of Energy's Office of Science awarded compute time on the BG/Q computer Mira, No 5 on November 2013 top500 list:
    125M core hours to be used for ``SiO2 Fracture: Chemomechanics with a Machine Learning Hybrid QM/MM Scheme''within our collaboration with James Kermode and Alessandro de Vita (King's College, London) at Argonne's Leadership Computing Facility.
    56M core hours for our collaboration on ``Non-Covalent Bonding in Complex Molecular Systems with Quantum Monte Carlo'' with Dario Alfe, Mike Gillan, Angelos Michaelides, Mike Towler (All University College London), Ken Jordan (University of Pittsburgh) and Alexandre Tkatchenko (Fritz-Haber Institute, Berlin). See the announcement, and the complete list of awards made.
    The goal of our work is to develop and apply algorithms meant to enable the rational design of new materials from first principles, i.e. the virtual identification of interesting materials/catalysts/molecules using ``smart'' optimizations, rather than mere trial and error. Once this is accomplished, these algorithms could be combined within new software, such as the materials project's Lithium battery explorer for designing better electrodes.

    Our work involves topics such as
  • chemical compound space
  • conceptual as well as molecular grand-canonical ensemble density functional theory
  • ligand design and intermolecular binding
  • quantum chemistry (solving approximate Schroedinger equations with density functional theory, semi-empirical methods, or post-Hartree Fock methods)
  • machine learning (supervised learnign approaches applied to important equations in chemistry)
  • statistical mechanics (using electronic, atomistic, coarse-grained & empirical force-fields and multi-scaling)
  • molecules, liquids, and solids including molecular crystals and defects
  • supercomputing
    Our calculations are mostly based on combined statistical mechanics and electronic structure theory software, such as CPMD, SeqQuest, VASP, abinit, octopus, LAMMPS, QUANTUM ESPRESSO, and others.

    If you wonder what this is all about, here's a recent Q&A session on combining machine learning with quantum chemistry to speed up the exploration of chemical compound space. You can also check out these reports in the New Scientist Feb 2012: Molecules from scratch without the fiendish physics, and on Chemistry World from the Royal Society of Chemistry, Dec 2011: Artificial intelligence for quantum chemistry.
    And here's Intel's very own Sadas giving a TED talk on ``designing new materials one atom at a time''.
    And here's Simon Elliot from Tyndall Institute talking about materials modelling for devices.
    If you you have been thinking that quantum mechanics is irrelevant, here's Walter Lewin on Heisenberg's uncertainty.
    Here's a movie , depicting the quantum nature of atomic nuclei within a simplified model of Watson-Crick's DNA base-pair (see also publication No. 23 for more information).
    And if you don't understand anything about this, rest assured, here's a link to Richard Feynman telling you that neither do we.

    Our current efforts are funded through the Swiss National Science foundation professorship program.

    Our seminar schedule (shared with Meuwly group) can be found here. The seminar schedule of the Competence Center of Computational Sciences can be found here