Yair Litman

Yair Litman

Research Fellow

University of Cambridge

About Yair

Yair Litman is a dedicated theoretical chemist working at the Yusuf Hamied Department of Chemistry (University of Cambridge) with a passion for solving complex problems at the interface of chemistry, physics, and materials science.

Unlike the math required to model the movement of clouds or to describe apples falling from trees, the description of nuclear motion in molecules demands a more complex treatment prescribed by the theory of quantum mechanics. For this purpose, Yair performs numerical simulations with existing and newly developed algorithms, sometimes enhanced by machine learning, trying to understand and predict the non-intuitive consequences emerging from the quantum nature of the nuclei.

His research orbits around the theoretical and methodological development of adiabatic and non-adiabatic quantum rate theories and diverse types of spectroscopies (IR, Raman, tip-enhanced Raman, sum-frequency generation, 2D-IR, and others). Yair’s primary systems of interest are organic/inorganic and aqueous interfaces.

Want to know more? Check out Yair’s CV.

Interests
  • Quantum Dynamics
  • Linear and Non-linear Vibrational Spectroscopy
  • Molecular Dynamics
  • Machine Learning applied to Physics/Chemistry
Education
  • PhD in Natural Sciences (Dr. rer. nat.)

    Fritz Haber Insititute, Berlin, Germany

  • Licenciate in Chemistry

    University of Buenos Aires, Buenos Aires, Argentina

Research Areas

Aqueous Interfaces
Where water meets the world: exploring the dynamic and complex realm of aqueous interfaces
Aqueous Interfaces
Organic/Inorganic Interfaces
Exploring the fascinating intersection where organic and inorganic worlds collide.
Organic/Inorganic Interfaces
Non-linear Vibrational Spectroscopy
Using light to reveal the mysteries of molecular motion
Non-linear Vibrational Spectroscopy
Quantum Dynamics
Understanding, predicting and manipulating nuclear quantum dynamics .
Quantum Dynamics

Recent Publications

Check Yair’s full list of publications here.

(2024). Surface stratification determines the interfacial water structure of simple electrolyte solutions. Nat. Chem..

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(2023). Fully First-Principles Surface Spectroscopy with Machine Learning. J. Phys. Chem. Lett..

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(2023). First-Principles Simulations of Tip Enhanced Raman Scattering Reveal Active Role of Substrate on High-Resolution Images. J. Phys. Chem. Lett..

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(2023). Is Unified Understanding of Vibrational Coupling of Water Possible? Hyper-Raman Measurement and Machine Learning Spectra. J. Phys. Chem. Lett..

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