Tag: Saint Petersburg Electrotechnical University ETU-LETI

An accelerometer is a device that measures acceleration. Accelerometers are used in many systems, from navigation modules of planes and submarines to smartphones and other gadgets. In the first accelerometers, acceleration was measured based on the compression of the spring with a load attached to it. The same principle of movable mass is used in modern-day accelerometers but on a smaller scale. However, many devices (such as industrial robots) require navigation systems that are not only small in size but also resistant to impact, vibration, and high acceleration. Accelerometers based on surface acoustic waves can provide accurate data even in these conditions. Surface acoustic waves spread across the surfaces of solid bodies and can be registered in piezoelectric materials (i.e. the materials that have electric fields reacting to mechanical impact). To do so, a piezoelectric membrane is connected to devices that transform mechanical waves into acoustic ones.

In modern-day accelerometers, membranes are usually made of quartz and lithium niobate. Although effective to some extent, these materials are still not the best: quartz isn’t sensitive enough, and lithium niobate becomes unstable when the temperature changes. To find an alternative solution, a team of physicists from LETI modeled the sensitive elements of accelerometers from aluminum nitride using the COMSOL Multiphysics software package. This tool allows one to set up various mechanical and electric properties of models and test them in different conditions. The team modeled round membranes surrounded by ring transducers and encased in thick aluminum nitride frames. For comparison, they also created models of similar structures from quartz and lithium niobate. The sensitive elements had 3 mm in diameter, and the membranes were only 0.22 mm in thickness.

First, the researchers tested different ways of fixing a membrane in a frame. According to the model, the best option was to use a thin layer of silicone adhesive. If a membrane is simply inserted into a frame, it can deform at fixation points under load thus reducing the sensitivity of the accelerometer. In the following tests, the team considered a model with adhesive fixtures. The researchers modeled the device’s behavior at acceleration tens, hundreds, and thousands of times higher than the standard acceleration of free fall (g=9.81 m/c2). Regardless of the acceleration value, the aluminum nitride membrane moved less than the quartz or lithium niobate one. It means that a meter with it would work more effectively. Another considerable advantage of this material was its relatively small energy loss. At the same time, the accelerometer with the membrane made of aluminum nitride was more sensitive to temperatures than the device with the quartz membrane.

“Based on the results of computer modeling, we can conclude that aluminum nitride is a promising material for acoustic accelerometer sensors, especially for measuring high levels of acceleration. Its resistance to mechanical deformation is two times higher than that of quartz which increases the sensitivity 1.5 times. Like in the case of lithium niobate, the main issue that can limit the use of aluminum nitride is its sensitivity to temperature changes,” said Sergei Shevchenko, Associate Professor of the Department of Laser Measuring and Navigation Systems at LETI.

A team of researchers from Saint Petersburg Electrotechnical University “LETI,” Peter the Great Saint Petersburg Polytechnic University, and the Technical University of Madrid tested and improved a classic approach to the research of magnetic fluids – liquid substances that get polarized in the presence of a magnetic field. The results of the work were published in the “Applied Sciences” journal.

Magnetic fluids consist of two immiscible phases: magnetic material particles (from several nanometers to several micrometers in size) and a polar or nonpolar dispersion medium. Such fluids are considered colloid systems: they don’t hinder light transmission but disperse the rays of light. Moreover, they don’t settle out because of the chaotic thermal motion of molecules. Magnetic fluids have several important properties: they are resistant to transitioning into other physical conditions, can preserve magnetization after it reaches its top level, and change their viscosity when magnetized.

Fluids like this are used in the mining industry, machine building, electronics, and medicine. For example, they can serve as lubricants and coolant materials or transfer power and energy from one mechanism to another. Different areas of application require magnetic fluids with different particle concentrations. To achieve a necessary concentration, the fluid is diluted several times. However, because of it, particles can stick together, and important properties of the fluid may be lost.

To properly prepare a diluted magnetic fluid, one needs to analyze the particle size distribution. In this process, one could use optic methods such as dynamic light scattering (DLS) — an approach based on the analysis of the time behavior of light scattering intensity on a sample. Still, the standard DLS technique does not provide data on the shape of the particles. Moreover, when the particles in diluted magnetic fluids stick together, it is impossible to study them individually.

A team of researchers including Kamil Gareev, a researcher at the Department of Micro and Nanoelectronics of ETU “LETI,” decided to use the original DLS method to study the size distribution of both individual magnetic particles and their aggregates in magnetic fluids. They synthesized magnetite–silica magnetic fluid from a water solution of iron (III) chloride and iron (II) sulfate following a method patented by LETI and studied its optical, structural, and magnetic properties.

The particle composition of the magnetic fluid was studied using microscopy, while its phase composition was analyzed based on the reflection of X-rays and electrons from the particles. To study the magnetic properties of the fluid, the team chose the method of vibrating sample magnetometry.

To analyze the shape of the particles, the team improved the DLS technique. This way, they managed to study the quantitative characteristics of magnetic material particle motion in a fluid medium for the first time. Namely, they focused on the translational and rotational diffusion coefficients of individual magnetic particles and their aggregates. The values of these parameters are determined by the rotational influences of the chaotic thermal motion of molecules and are indicative of particle sizes.

Using this data, the team calculated the geometrical parameters of nanoparticles and their aggregates and found out that the former had almost spherical shapes while the latter were more elliptical. The spherical shape of 10–20 nm large magnetic nanoparticles determined their superparamagnetic properties, i.e. the absence of the magnetic moment without an external magnetic field.

These characteristics are especially important for medicine: superparamagnetism prevents the particles from sticking to each other in the bloodstream and reduces the risk of thrombosis. Moreover, because of this property nanoparticles can be used as a magnetically controlled carrier for targeted drug delivery and as a contrasting agent in MRI.

“Using the improved DLS technique, we have studied the structural properties of magnetite–silica nanoparticles and made one more step towards introducing them into medical practice, namely MRI. Moreover, our method could be used to study nanoparticles not only in magnetic fluids but also in biological solutions,” explains Kamil Gareev, a researcher at the Department of Micro and Nanoelectronics of ETU “LETI.”

According to the team, when diluted 200 or more times, a magnetic fluid loses its stability, and its particles form aggregates around 140 nm in diameter. In the future, the researchers plan to find out at what level of dilution magnetic fluids lose their resistance to sedimentation.

Nowadays, objective analysis and interpretation of biomedical research results are largely dependent on the fast and efficient processing of biomedical images, including tomographic images, histological samples, microphotographs of tissues, bacterial colonies, and other biological structures. ETU “LETI” scientists have proposed an innovative way to quickly process micro-images to assess the effectiveness of promising wound-healing drugs.

“The fact that biomedical images are non-stationary and heterogeneous makes automatic selection and classification of objects difficult. That makes developing specialized methods for their analysis, adapted to these properties, relevant. ETU “LETI” scientists have researched in the field of visual data analysis for several years. Analysis of biomedical visual data is one of the main areas of application of the developed methods and approaches,” notes Mikhail Bogachev, Chief Researcher of the Research Center “Digital Telecommunication Technologies” at ETU “LETI.”

One of the research areas is the automated analysis of images obtained using microscopy. St. Petersburg scientists have developed a modified method for analyzing microimages of aggregated bacterial cells. In such structures, it is impossible to distinguish individual cells in the image, so to evaluate subpopulations, LETI scientists suggested using a two-step algorithm based on a combination of selection and counting of individual cells.

Researchers analyzed the shape of objects highlighted in tissue sections to reconstruct the properties of the recovered tissue based on the biomechanical model developed by experts from Kazan Federal University. The results confirmed not only the accelerated wound healing but also the more natural structure of the recovered tissue, close to normal in its biomechanical properties, due to the treatment. The research materials were presented in the International Journal of Biological Macromolecules at the end of 2020.

“The search for promising drugs is inextricably linked to an extensive screening of candidate molecules. Although modern bio- and chemoinformatics tools make it possible to pre-select the most likely candidates, the volume of experimental studies for their verification remains considerable and requires laborious and time-consuming work from experts,” ” says Mikhail Bogachev.

“The algorithms for evaluating cell subpopulations on microscopic images that we have developed allow us to reduce the expert workload and increase the objectivity of studies not only when studying Ficin, but also other promising drugs.”

The proposed algorithm is demanded among practitioners, as evidenced by several dozens of citations in biomedical publications. The current research is carried out in close collaboration with specialists from Pavlov St. Petersburg Medical University, Saint Petersburg Research Institute of Ear, Throat, Nose and Speech, Albrecht Center for Rehabilitation of People with Disabilities, and several other healthcare organizations.

Researchers from Saint Petersburg Electrotechnical University ETU “LETI” and Riga Technical University tested new technology for monitoring the state of the roadway surface. Fibre-optic strain and temperature sensors collect data on changes in the roadway structure depending on the load. This information will help design durable roads and plan their maintenance. The study was published in the Journal of Sensors.

The pavement of any road deteriorates over time. It is impossible to stop this process altogether, but it is possible, on the one hand, to choose more durable materials and, on the other hand, to repair cracks and ruts in the roadbed structure in the early stages, until the damage requires replacing the entire surface. Therefore road construction industry is always looking for effective monitoring systems along with new materials. Roads should be equipped with sensors that allow not only to detect defects timely but also estimate the load on the road section. Using this information, a maintenance team could understand the levels of pressure and vibration created by traffic in that area and reinforce the roadway surface where needed.

Dmitry Redka, Associate Professor of the Department of Photonics of ETU “LETI,” used fibre-optic sensors for asphalt pavements in a joint project with Riga Technical University. TThese devices are known for their sensitivity and can be arranged in existing fibre optic networks to remotely collect data, so they do not require an electrical power supply. The sensors are based on the so-called fibre Bragg grating. It is a short segment in an optical fibre in which the refractive index is variated using UV light. As a result, this segment always reflects radiation only in a very small spectrum and transmits the rest of the light without loss.

FBG can be constructed so that the wavelength of the reflected light depends on changes in the ambient temperature, pressure on the fibre, or other parameters. Fibre optic sensors work thanks to this effect. For example, a temperature sensor will reflect a laser signal differently at +20°C and -15°C.

Dmitry Redka, Associate Professor of the Department of Photonics of ETU “LETI,” explains: “Our experiments show that fibre optic sensors can accurately measure roadway deformations. It is necessary to monitor the temperature because, in warm weather, asphalt is more pliable, and strain values increase. Using our constant monitoring approach, one could determine when deformations exceed the limit in a section and take it into account when designing new roads and repairing existing ones.”

Researchers embedded two types of fibre-optic sensors for measuring strain and temperature in a layer of asphalt on a Latvian road during its maintenance. The sensors were placed 25-30 mm deep at two points on one side of the roadway. Because unprotected fibre-optic sensors are fragile, they were encased in composite and ceramic tubes.

To test if the system is working, researchers used a falling weight deflectometer, a device measuring the surface deflection under load. The centre of the plate, on which the load falls, was placed at different distances from and directly above the sensors. This test showed that the most accurate measurements are possible when the load is directed right on the sensors. That is why in real-life monitoring, it is essential to consider the direction of traffic. Scientists also verified that temperature plays a major role in the deformation of asphalt: all measured values were lower in fall than in warm summer.

A key part of the experiment was monitoring actual traffic. About 3.15 million cars pass through the point where the measurements were taken in a year, and over 23% of them are heavy trucks. Physicists determined which types of trucks impact the roadway the most and calculated that in 33% of cases, a passing truck deforms the asphalt by 0.3 mm per meter.

Researchers of ETU “LETI” and Aristotle University of Thessaloniki have created a new algorithm for constructing hash functions. Taking advantage of chaos theory and adaptive symmetry, the scientists made it harder to break than existing solutions. The results of the study are published in the Chaos, Solitons & Fractals journal.

A hash function is a mathematical function designed to convert some message or data, such as a password, into a bit array called a hash. This way, the system processes code that is unique to each message. It is essentially a way to verify encoded messages, impossible to decrypt unambiguously. For example, when we enter a password in a system that uses hash functions, the server receives not the text of our password itself but its bit array. If it matches the sequence on the server, then we log in to our account. The point is that if intruders intercept our message, they won’t get the plain text of our password but the bit array, which they won’t be able to decrypt correctly.

Hash functions are used in many areas: data encryption, electronic signatures, cryptocurrencies, data sorting and compression. In modern cryptography, one of the most promising areas is chaotic hash functions based on chaos theory. This theory describes the dynamics of nonlinear systems in which changes in initial conditions lead to unpredictable consequences. Such systems include mechanical devices like a double pendulum, atmospheric phenomena models, population dynamics, and even some social processes. But since we need as random a sequence of bits as possible for hashing data, the use of chaotic systems with confusion and diffusion property facilitates this process, enhancing data security. The researchers from ETU “LETI” studied existing chaotic hash functions and developed their improved version.

“Unlike other solutions based on classical chaotic maps, we used modifications with adaptive symmetry. The use of discrete maps with controlled symmetry expands the key space and, consequently, the cryptographic strength of the obtained hash functions. The symmetry of the maps becomes an additional key in their construction while having little effect on the chaotic behavior of the system,” says Alexandra Tutueva, a Ph.D. student at the Department of Computer Aided Design Systems of ETU “LETI.”

After constructing the hash function, scientists have tested it thoroughly. Like any other counterparts, it must have certain properties of cryptographic hash functions. First of all, the authors analyzed the performance – how quickly the input data (keys) is converted into a bit array and back. For comparison, they used the known standard SHA-3 (Keccak) hash function and several currently existing chaotic functions. The development of ETU “LETI” researchers showed a speed of 0.9 Gbit/s, comparable with analogues.

The function also successfully passed the birthday attack test. This method is used in cryptanalysis to break ciphers. It is based on the birthday paradox. For example, in a group of 23 people, the probability that two of them will have the same birthday is greater than the probability that each of these people will have unique birthdays. That seems counterintuitive, but the math shows otherwise. Using this paradox, attackers try to discover the same bit arrays for two different source messages. So scammers using hash functions can send one contract to sign with e-signature, but the victim will end up signing two contracts with different contents at once. However, the scientists have established that for the new function it is enough to generate messages of at least 128 bits in length to prevent the attack. This way, the probability of a bit array match is minimized.

The authors also confirmed the avalanche effect of the function. It means that changes in the original data lead to changes in hashes. The researchers created a text message and then ran it through a hash function, obtaining a specific bit array. They then changed the length and meaning of the original texts and hashed those messages. The result was completely different bit sequences, indicating that the function worked correctly.

The new chaotic hash function passed all the tests and showed its reliability and efficiency. According to scientists, it can be used in cryptography as a more secure version of data transmission. Also, the new function can be the basis for a mechanism that creates realistic models of objects of fractal structure in computer graphics and solid-state modeling – for example, for the generation of clouds and mountains, the surface of the sea, the tensions within solids, and much more.

Vessel traffic in the river and marine waters is growing, which causes the issue of control and safety of navigation. Ship collisions often result in loss of life, ship damage and costly repairs, and cause irreparable damage to the environment through oil spills. The use of ships in illegal activities, such as smuggling and sabotage, also poses a threat.

One of the main tools for ship movement monitoring is the Automatic Identification System (AIS). It provides information on the ship’s dimensions, course, and other parameters via radio channels. Besides, navigation radar systems are used for the surveillance of coastlines, ice, and other objects on the sea surface. However, they are installed mainly on large vessels.

Evgeny Vorobyov, a young scientist from ETU “LETI,” researcher of Prognoz Research Institute, suggested an effective way to detect “intruders” of water traffic. The ground-based system passive radar monitoring of vessel movements, using signals from third-party satellite-based sources (satnav systems GPS and GLONASS), will provide a radar observation virtually at any spot of the marine areas.

“The system is more economically attractive and competitive. For port cities, such a system is especially relevant, as it allows to monitor ship movement with high-rise buildings around and active development of traffic arteries. It causes no interfering with other radio equipment and doesn’t violate the sanitary standards, which is an advantage compared to active radars,” says Evgeny.

According to the developer, in Russia, there are no commercially available systems for passive radar control of ship traffic, working on reflected signals of satellite-based transmitters. The methods and principles of their creation require additional research, taking into account the specifics of signal processing of satellite radio systems.

The study will employ the developments of ETU “LETI” researchers in passive bistatic radars. A research team of the Prognoz Research Institute, together with members of the Faculty of Radio Engineering, developed such a radar, which uses signals of digital terrestrial television. One of the receivers is located on the roof of building 5 of the university. Evgeny will apply his experience in processing reflected signals of digital TV broadcasting to the development of a new system by adapting the algorithms to satellite signals.