Research on diffractive optics

Samara National Research University (Samara University) is one of the world leaders in research of diffractive optical elements (DOEs) and image processing. Weighing only tens of grams, diffractive lens developed at Samara University can replace bulky systems of modern telephoto lenses and mirrors. Their development is a result of 40 years’ work of a Diffractive Optics and Nanophotonics school supervised by Viktor Soifer, an academician of the Russian Academy of Sciences and the President of Samara University. 

The first article by Samara University scientists confirming the possibility of using diffractive optics in imaging systems was published in May 2015. The article followed the results of the world’s largest conference on image processing, IEEE Computer Vision and Pattern Recognition. In November 2015, Toronto University (USA) and King Abdullah University of Science and Technology (Saudi Arabia) published a joint work on the issue citing the Samara University study. For the first time in the world, diffractive optics was used to produce high-resolution color images. 

To manufacture such a diffractive lens, a resist is applied to a fused quartz surface. The fused glass is a 10 micrometers thick (a human hair is 40-90 micrometers thick) photosensitive substance. A focused laser beam creates a 256-layered micro-relief on the resist. That forms an object image and computer processing of the resulting images based on deep learning neural networks compensates for the distortion. 

Optics based on diffractive lenses is already applied in a variety of areas – space, medicine, agriculture. Samara University has developed an ultralight optical system for Earth remote sensing (ERS), which will simplify and reduce the cost of designing massive constellations of nanosatellites for continuous monitoring of the Earth’s surface. The miniature devices will also be used as cameras on unmanned aerial vehicles. According to Artem Nikonorov (1), a professor at Supercomputers and Informatics Department, Samara University, it is planned to equip a fleet of nano-spacecraft with the Samara optics. The fleet will be sent to the Alpha Centauri star system as part of Breakthrough Starshot project. The project also aims to search for potentially habitable exoplanets. 

Research of DOEs allowed the Samara University scientists to design a compact hyperspectrometer. The hyperspectrometer served as a control system basis for the world’s first smart sprinkler machine. Using this system, the mobile agro-reclamation complex is able to independently analyze the soil condition, measure soil moisture and availability of necessary mineral fertilizers while driving across the field. Depending on the received data, the sprinkler regulates the irrigation intensity and fertilizer application rates. According to Roman Skidanov (2), a professor at Technical Cybernetics Department, Samara University, that can increase the agricultural crops yield by 25-30%. 

Hyperspectral DOE-based equipment can also be used in medicine. The equipment can make it possible to achieve high accuracy in non-contact diagnostics of skin neoplasms. This technology allows registering not only the object image but also its spectral data. That will significantly improve the accuracy of digital dermatoscopy carried out in clinics today. “Multivariate analysis of spectral data based on the modern statistics methods makes it possible to identify biochemical changes occuring in biological tissues during cancer development. This way we can detect the growth of neoplasms at the earliest stages,” Ivan Bratchenko (3), an associate professor at Laser and Biotechnical Systems Department, Samara University, noted. 

Science directions and leading research teams

Artem Nikonorov

Artem Nikonorov is a Doctor of Technical Sciences, a professor at Supercomputers and General Informatics Department, a leading researcher of a research and education center for Computer Research, Samara University, the head of an Intelligent Video Data Analysis Laboratory, Image Processing Systems Institute, the Russian Academy of Sciences. He graduated from Faculty of Informatics, Samara State Aerospace University (currently Samara National Research University). His main research interests are artificial intelligence and deep learning in industrial applications, machine vision, high performance computing. He is a winner of the New Space All-Russian competition of young scientist laboratories of new space technology (2016), a holder of the Russian Federation President’s grant (2017), a laureate of the Provincial Prize in Science and Technology (2018). Artem Nikonorov is also a Member of the Institute of Electrical and Electronics Engineers (IEEE) and the International Association for Pattern Recognition (IAPR). 

Roman Skidanov

Roman Skidanov is a Doctor of Physical and Mathematical Sciences, a professor at Technical Cybernetics Department, a leading researcher of a research and education center for Computer Research, Samara University. He graduated from Samara State University (currently Samara National Research University). Roman Skidanov is an author of patents for a method for controlling a micromechanical pump rotating under the action of a light beam, a method for moving micro- and nano-objects, an imaging hyperspectrometer based on a diffraction grating with a variable line height, an opto-digital system for calculating diffractive optical elements, etc.

Ivan Bratchenko

Ivan Bratchenko is an associate professor at Laser and Biotechnical Systems Department, the head of a Photonics research laboratory, a PhD in Physical and Mathematical Sciences. He graduated from Faculty of Informatics, Samara State Aerospace University (currently Samara National Research University). Ivan Bratchenko wrote his PhD thesis on analysis of multiple scattering media considering their microscopic structure, effects of fluorescence and Raman scattering in 2013. He is an author of patents for a device for diagnosing skin cancer, a laser source with a receiving channel for Raman spectroscopy of skin neoplasms, a measuring chamber of a microsystem for optical analysis of biofluid.