Science highlights

Computational Materials Discovery Lab (head of Laboratory – Prof. Artem R. Oganov)

Our laboratory develops global optimization methods for the prediction of atomic structure of crystals and low-dimensional materials (surfaces, polymers, nanoclusters, etc.) and for predicting materials with desired properties. We also develop techniques for predicting mechanisms of phase transitions. Our methods are implemented in our code USPEX (http://uspex-team.org), used by numerous researchers and companies around the world. Some highlights include:

  1. Discovery of a new unique superhard material WB5 (JPCL 2018).
  2. Discovery of transparent form of sodium (Nature 2009a), discovery of the crystal structure of superhard gamma-boron (Nature 2009b).
  3. Discovery of new unexpected sodium chlorides (e.g. Na3Cl, NaCl3, etc. – Science 2013) stable under pressure.
  4. Discovery of helium chemistry under pressure – which started with our predicted compounds Na2He and Na2HeO (Nature Chemistry 2017).
  5. Prediction of novel high-temperature superconductors (JPCL 2018, Sci. Adv. 2018).
  6. Elucidation of the structure of surfaces of alpha-boron (PRL 2013), rutile TiO2 (PRL 2014), silica polymorphs (Sci. Rep. 2018).

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Multiscale Modeling Group (PI: Assistant Professor Alexander Shapeev)

The main research theme of the Multiscale Modeling Group is an application of machine learning to molecular modeling. The projects that we currently work on are:

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Organic semiconductors (PIs Profs. Andriy Zhugayevych and Sergei Tretiak)

We perform multiscale modeling of organic semiconductors for applications in optoelectronics, sensing, energy conversion and storage. Experiment is conducted in the group of Prof. Pavel Troshin. Highlights include:

  • State of the art modeling of solar cells (ARPC 2015), light emitters (ChemSci 2015), field effect transistors and photodetectors (AFM 2018), emerging biomaterials (AM 2015)
  • Structure prediction for semicrystalline polymers (JPCC 2018)
  • Development of fragmentation approaches for extended systems (ChemSci 2017)

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Theoretical chemistry and spectroscopy lab (PI: Adj. Prof. Sergei Tretiak)

We are developing modern computational methods to model optical and electronic properties, and dynamics of electronically excited states in molecular, nanoscale and semiconducting materials.  Some highlights include:

  • Coherent non-adiabatic molecular dynamics of excitons in conjugated organic chromophores (Nature Comm., 9, 2316, 2018);
  • Optical response of semiconducting carbon nanotubes (Nature Chem., 10, 1089, 2018);
  • Electronic properties mixed halide perovskites (Nature Comm., 9, 2525, 2018; Science, 360, 67, 2018);
  • Machine learning and data science complementing conventional quantum chemistry (J. Phys. Chem. Lett., 9, 4495, 2018).

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Dmitrii Aksenov

My ultimate research goal is to design new materials using computer simulation. The supreme ingredient of success is deep understanding of the material’ properties on the atomic and electronic level, which can be achieved with modelling.  My current focus is on electrode materials for metal-ion batteries – the groundwork of future energy. Among the highlights:
  •  Understanding intercalation sequence in lithium and sodium iron fluorophosphates with DFT calculations (J. Am. Chem. Soc., 2018)
  • Understanding cation migration barriers in oxide and phosphate based cathode materials with DFT calculations
  • Development of computational framework SIMAN for high-throughput DFT calculations
  • Solubility and grain boundary segregation of alloying elements in metals (Comput. Mat. Sci, 2012, 2015, 2017)
  • Radiation swelling in vanadium radiation-resistant alloys (J. Nucl. Mater. 2017 )

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Unifying Concepts in Catalysis Lab (PI: Assistant Professor Sergey V. Levchenko)

Our research focuses on first-principles modeling of complex materials (surfaces, interfaces, nano-structured systems) and phenomena (defect formation and interaction, statistical effects, dynamics, kinetics) at realistic temperature, pressure, and doping conditions in general, and heterogeneous catalysts and catalytic processes in particular. Here are some highlights:

  • Influence of ferroelectric polarization on the equilibrium stoichiometry of ferroelectric surfaces at realistic temeratures and oxygen partial pressures (Physical review letters 100, 256101 (2008))
  • Concentration of vacancies at semiconductor surfaces including charge-carrier-doping effects (Physical review letters 111, 045502 (2013))
  • Stability and metastability of clusters in a reactive atmosphere: Theoretical evidence for unexpected stoichiometries (Physical review letters 111, 135501 (2013))
  • Controlling molecular dissociation on a catalyst surrface through surface site blocking by co-adsorbates (Journal of catalysis 320, 89 (2014))
  • Developing artificial intelligence approaches to finding descriptors for rational materials design (Physical review letters 114, 105503 (2015))
  • Hybrid functionals for large periodic systems in an all-electron, numeric atom-centered basis framework (Computer Physics Communications 192, 60 (2015))
  • First-principles supercell calculations of small polarons with proper account for long-range polarization effects (New Journal of Physics 20, 033023 (2018))

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More highlights to be added…