Driving by artificial intelligence automated laboratory at synchrotron radiation source for accelerated development of novel advanced materials and their on-the-fly characterization

Nanocatalysts for photostimulated green hydrogen production: molecular design and advanced characterization assisted by machine learning methods

Nanocomposites for X-ray photodynamic therapy of deep tumors in oncology

Establishing the relationships between the vibrational spectra of zeolites by quantum-chemical modelling and machine learning methods

Investigation of direct methane-methanol conversion mechanism over the Cu sites in Cu-exchanged zeolites

Digital model of the experimental physical environment for diagnosing nanomaterials based on synchtron radiation for training deep reinforcement learning agents

Metal-organic frameworks (MOFs) represent a new class of crystalline materials with extremely high pore volume and specific surface area. MOFs have a great variety of potential applications.

Palladium-based nanomaterials for catalytic applications. In situ, operando and time-resolved studies using synchotron-based techniques.

FitIt is a new approach to fit spectra using multidimensional interpolation approximation. FitIt allows obtaining information about the local atomic structure from XANES spectra.

Three-dimensionally confined semiconductor quantum dots with unique physical and chemical properties for application in physics, chemistry, biology and medicine

X-ray absorption spectroscopy for 3D atomic and electronic structures of materials with and without long-range order: nanoparticles, molecules, biological systems, etc.

Multiscale computer modeling of atomic structure and electronic properties of nanomaterials