Dr. Barak Hirshberg

ביה"ס לכימיה סגל אקדמי בכיר

Research

  • Machine learning and Physical Chemistry. Prediction of dynamical properties of quantum materials using neural networks: Diffusion, spectroscopy and reaction rates.
  • Developing new methods to describe quantum effects in classical simulations: Path integral molecular dynamics for indistinguishable particles.
  • Simulations of chemical processes on water surfaces with applications to atmospheric chemistry and hydrogen storage in clathrate hydrates.

Our research follows two main directions: 1. Developing simulation methods for describing chemical and physical phenomena that are inadequately described using available models. 2. Applying these new tools and others to solve fascinating problems at the interface of chemistry and physics.

The main tool is molecular dynamics (MD) simulations, a “virtual microscope” that allows following the classical dynamics of individual atoms in time and investigating chemical and physical processes for large systems (liquids and solids). However, MD simulation are inapplicable at low temperatures or for quantum materials, whose properties are determined from the quantum correlations between their constituent particles. Unfortunately, solving the quantum equations of motion is impossible for large systems.

To overcome this important problem, we develop path Integral MD simulations (PIMD) which allow describing the thermodynamic properties of quantum condensed phase systems while being computationally efficient. We aim to solve two limitations of PIMD simulations that will greatly extend their applicability:

  1. Using neural networks to obtain dynamical properties of quantum systems e.g., diffusivity, reaction rates and spectroscopy. We will apply this approach to hydrogen storage in ice-like cages (clathrate hydrates), promising renewable energy materials. Since hydrogen is the lightest element and since clathrate hydrates are formed at low temperatures, quantum effects cannot be neglected.
  2. PIMD simulations for bosons and fermions. This development would allow applications to systems of ultracold trapped atoms which exhibit fascinating phenomena, such as Bose-Einstein condensation, and can potentially be used in emerging quantum technologies. 

Education

  • Ph.D. in Chemistry, the Hebrew University, 2018

  • M.Sc. in Physical and Theoretical Chemistry, direct PhD track, the Hebrew University, 2014

  • B.Sc. in Chemistry and the Amirim Natural Sciences Program, magna cum laude, 2009

Academic Appointments

  • Senior Lecturer, School of Chemistry, Tel Aviv University, 2021-Today

  • Postdoctoral Fellow, ETH Zurich, 2018-2020

Awards and Prizes

  • Rothschild Fellow, Yad Hanadiv foundation, 2018-2019

  • Adams Fellow of the Israel Academy of Sciences and Humanities, 2015-2018

  • Israel Chemical Society Prize for an Excellent Graduate Student, 2017

  • Excellent teaching assistant based on students’ evaluations, Faculty of Science, Hebrew University of Jerusalem, 2016

  • USA-Israel Binational Science Foundation (BSF) Prof. Rahamimoff travel grants for young scientists, 2016

  • The Lise Meitner-Minerva Center Junior Award for an outstanding work in computational quantum Chemistry, 2014

  • Giora Y. Yashinski memorial award for excellent M.Sc. and Ph.D. students, 2012

  • Dean’s list, Faculty of Science, Hebrew University of Jerusalem, 2007-2008

  • Prof. P. Elving memorial award for excellence in Analytical Chemistry, 2008

  • Dean’s award, Faculty of Science, Hebrew University of Jerusalem, 2007

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