Volker Heine Young Investigator Award


Congratulations to Bingqing Cheng, winner of the 5th Volker Heine Young Investigator Award! Her outstanding talk made her pioneering work in the field of machine learning interatomic potentials and applications to phase diagrams accessible to a broad audience, and it reflected the breadth and impact of her contributions.

The VHYIA committee: Lucia Reining (chair), Gábor Csányi, Claudia Draxl, Feliciano Giustino, Peter Haynes, Francesco Mauri and Arash Mostofi.

Message from Volker Heine (Psi-k's first chairman)

Congratulations to all of the finalists and congratulations to all the other applicants with their research! Let us celebrate all who take part in Psi-k to keep it going, and who help fund the Award, and contribute to all the Psi-k activities without any official funding beyond STFC's administration.

Volker Heine Young Investigator Award ceremony

September 9, 2021, 14:00-17:00 CEST


  • 14:00 — Welcome and introduction

  • 14:15 — Bingqing Cheng, University of Cambridge, UK
    Predicting material properties with the help of machine learning

  • 14:45 — Johannes Flick, Flatiron Institute, NY, USA
    Strong light-matter coupling in molecular and extended systems from first principles

  • 15:15 — (break)

  • 15:30 — Federico Grasselli, EPFL, CH
    Invariance principles and topology in the ab initio charge transport of ionic fluids

  • 16:00 — Lionel Lacombe, Rutgers University, USA
    The exact factorization approach: From strongly correlated electrons to polaritonic chemistry

  • 16:30 — Tianyu Zhu, California Institute of Technology, USA
    Full Cell Quantum Embedding for Correlated Materials

  • 17:00 — End

About the Volker Heine Young Investigator Award

The Volker Heine Young Investigator Award recognizes individuals for their outstanding computational work in the areas covered by the Psi-k mission statement ("...to develop fundamental theory, algorithms, and computer codes in order to understand, predict, and design materials properties and functions"). There is one award of 2'500€ and four runner-up prizes of 500€ each.

Applicants had to be either currently enrolled in a PhD program, or be recent PhD graduates who have received their PhD certificate no earlier than September 11, 2015.


Bingqing Cheng

Computer Laboratory & Cavendish Laboratory, University of Cambridge, UK

Predicting material properties with the help of machine learning

A central goal of computational physics and chemistry is to predict material properties using first-principles methods based on quantum mechanics. However, the high computational costs of these methods typically prevent rigorous predictions of macroscopic quantities at finite temperatures, such as chemical potential, heat capacity and thermal conductivity.

In this talk, I will first discuss how to enable such predictions by combining statistical mechanics with data-driven machine learning interatomic potentials. I will give example applications on the systems of water and high-pressure hydrogen. Besides thermodynamic properties, I will also talk about how to compute the heat conductivity of liquids just from equilibrium molecular dynamics trajectories.

During the second part of the talk, I will rationalize why machine learning potentials work at all, and in particular, the locality argument.

Johannes Flick

Center for Computational Quantum Physics, Flatiron Institute, New York, USA

Strong light-matter coupling in molecular and extended systems from first principles

Recent research at the interface of material science, chemistry, and quantum optics has offered new possibilities to study light-matter interactions. Combining concepts from these fields presents an opportunity to create a predictive theoretical and computational approach that describes the correlated dynamics of electrons, nuclei, and photons on the same quantized footing.

In this talk, we discuss quantum-electrodynamical density-functional theory (QEDFT) to describe these systems, new exchange-correlation potentials and its approximations. We discuss linear-response theory for QEDFT to access excited states and the incorporation of losses. By considering electrons, nuclei and photons explicitly, we find polaritonically induced vibrational mode mixing and show how chemical reactivity is altered. Beyond molecular systems, we discuss how strong light-matter coupling makes nonlinear-phonon processes more efficient and discuss first principle methods to characterize single-photon emitters. Our work highlights the novel abilities to alter material properties and chemical reaction pathways using strong light-matter coupling.

Federico Grasselli

Lab. of Computational Science and Modelling (COSMO), École Polytechnique Fédérale de Lausanne, Switzerland

Invariance principles and topology in the ab initio charge transport of ionic fluids

According to the Green-Kubo theory of linear response [1], the electrical conductivity can be extracted from the time-correlation function of the charge flux in equilibrium molecular dynamics simulations.

I combine a recently-formulated gauge-invariance principle of transport coefficients [2] with arguments from charge-transport quantization [3] to prove that the same ab initio electrical conductivity of ionic fluids is exactly obtained if the time-dependent Born charge tensors, entering the definition of the ab initio charge flux according to the modern theory of polarization (MTP), are replaced by the time-independent integer oxidation numbers of the atoms [4]. Besides providing an alternative method to compute the ab initio electrical conductivity with no need for MTP calculations, this result offers a topology-based definition of oxidation numbers in disordered materials, as I show through numerical experiments on molten potassium chloride. I finally discuss non-stoichiometric systems, where quantized charge transport may occur without a net ionic displacement [5].

[1] M. S. Green, J. Chem. Phys. 20(8), 1281–1295 (1952)
[2] A. Marcolongo, P.Umari, and S. Baroni, Nature Physics 12, 80–84 (2016); L. Ercole, A. Marcolongo, P. Umari, and S. Baroni, J. Low Temp. Phys. 185, 79–86 (2016)
[3] D. J. Thouless, Phys. Rev. B 27, 6083 (1983)
[4] F. Grasselli and S. Baroni, Nature Physics 15, 967–972 (2019)
[5] P. Pegolo, F. Grasselli and S. Baroni, Phys. Rev. X 10, 041031 (2020)

Lionel Lacombe

Dept. of Physics and Astronomy, Rutgers, The State University of New Jersey, USA

The exact factorization approach: From strongly correlated electrons to polaritonic chemistry

The exact factorization approach has recently generated a growing interest for the description of coupled electron-nuclear dynamics and the development of mixed quantum-classical methods. However the idea of separating the wave function into subsystems can be generalized to a plethora of other systems, from N-body electronic systems to the inclusion of photonic degrees of freedom. Here, we first present an exact-factorization-based quantum electronic embedding method to calculate static properties of a many-electron system, and demonstrate its success in capturing strong electron correlation. The method is exact in principle but the practical power lies in utilizing input from a low-level calculation on the entire system in a high-level method computed on a small fragment, as in other embedding methods. In a second part, we present what insights can be obtained in polaritonic chemistry from exact factorization and discuss how it could be used to derive mixed quantum-classical schemes for coupled light-matter problems.

Tianyu Zhu

Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA

Full Cell Quantum Embedding for Correlated Materials

The quantitative prediction of quantum properties in correlated materials requires simulations without empirical truncations and parameters. We present a method to achieve this goal through a new ab initio formulation of quantum embedding. Instead of using small impurities defined in a low-energy subspace, which require complicated downfolded interactions which are often approximated, we describe the full cell dynamical mean-field theory (DMFT), where the impurities comprise all orbitals of atoms in a unit cell or supercell of the crystal. Our formulation results in large impurity problems, which we treat here with efficient quantum chemistry impurity solvers including the coupled-cluster theory and DMRG, combined with a GW treatment of long-range Coulomb interactions. We apply our approach to study correlated transition metal oxides such as nickel oxide and cuprate superconductors, and find the predicted spectral properties are in good agreement with the experiment.

Award committee

The finalists were selected by a group of Psi-k trustees: Lucia Reining (chair), Claudia Draxl, Peter Haynes and Arash Mostofi. For the final selection, the committee was extended to include Psi-k 2022 conference plenary speakers as well.

Previous awards

2010 Claudio Attaccalite, Christoph Freysoldt, Matteo Gatti, Samir Lounis, Alexandre Tkatchenko

2013 Xavier Andrade, Michele Ceriotti, Nicholas D.M. Hine, Cheol-Hwan Park, Tim Wehling

2015 Marco Bernardi, Andreas Grüneis, Fabio Caruso, Ion Errea, Johanna Fuks

2018 Jan Gerit Brandenburg, Viktor Ivády, Yaroslav Kvashnin, Reinhard J. Maurer, Bartomeu Monserrat