Nanoparticles and Nanostructured Materials
Synthesis and Research Group
Our philosophy
Exploring
Studying the relationship between «synthesis conditions and procedures - nanoparticle parameters»
There is a generally accepted rule that the prefix “nano” indicates that at least in one dimension, the object has a size smaller than 100 nm. In the case of nanoparticles, these dimensions are three, and nanoparticles possess properties that are different from those of macroscopic particles—properties that can be felt by fingers or seen under an ordinary microscope.
What is truly amazing and fascinating is that the properties of nanoparticles depend on their parameters— size, shape (sphere, cube, rod, plate, etc.), crystallite size, surface composition, and many others. By now, a number of regularities connecting the morphological parameters of the obtained nanoparticles with the synthesis conditions and procedures are already known, theoretical approaches to describing the processes of nanoparticle growth have been developed (such as nucleation theory, Ostwald ripening, or oriented attachment theory), but the ability of a synthetic chemist to choose a synthesis method, to use the technique and procedure of synthesis that allow obtaining nanoparticles with the required parameters, remains an art that is passed down from teacher to student.
At present, researchers face the task of accumulating a significant amount of experimental data, meticulously processing the results of conducted research, avoiding errors in describing the results, which will subsequently enable them to understand the hidden mechanisms of nanoparticle formation and create new materials based on them.
Studying the relationship between «composition - structure - property» in inorganic nanoparticles and materials based on them
The idea of the relationship between the structure of a substance and its properties was first articulated by M.V. Lomonosov, and to date, a vast number of works have been dedicated to studying this relationship, primarily focusing on quantitative correlations of “structure-property” in organic chemistry.
In inorganic chemistry and materials science, there exists a highly complex relationship between the composition, structure, and properties of nanoobjects and nanomaterials – even small changes in their synthesis conditions can lead to drastic changes in characteristics, resulting in a multitude of influencing factors and parameters. Moreover, the influence often exhibits a complex, nonlinear nature and is determined by a significant number of different factors. Obtaining, processing, and analysing a large amount of experimental data to isolate the contribution from each factor are our tasks, the solution of which will enable us to learn how to predict this dependence.
Understanding
Experimental investigation and theoretical description of nanoparticle growth processes
The ability to synthesize nanoparticles with specified morphological parameters still remains somewhat of an art. If a scientist has access to a large experimental dataset, it allows for the identification of nanoparticle formation patterns. However, merely identifying patterns is not enough, as it immediately raises the question – why does such a pattern exist? Explaining these patterns is a more complex task. The answer usually involves the development and creation of a model that will provide an answer to the question “What will happen if we change the initial conditions in a certain way?”. In the pre-computer era, equations were formulated based on models, which were then solved using various mathematical techniques. Today, computers have become a reliable tool in scientific research and help us to see what the model predicts without the need to find solutions to equations. Computational modeling allows us to abandon many approximations and consider mechanisms that were previously not taken into account. Building and studying models will allow us to understand the processes of nanoparticle growth, which in turn will enable synthetic chemists to successfully synthesize nanoparticles with specified properties, directing the process of their formation along one path or another.
Experimental investigation and theoretical description of interactions between nanoparticles with each other and molecules of different nature
Nanoparticles in a vacuum only exist in the imagination of theoretical physicists. In practice, synthesis always occurs, for example, in an aqueous environment. The reaction medium contains the starting reagents, and various molecules can also be added to it, which are predominantly located near the surface of the nanoparticle or attached to it, slowing down its growth or complicating its interaction with other components.
Furthermore, the surface of nanoparticles can be modified (i.e., various molecules can be attached to it) both during synthesis and after its completion. Through modification, the application area of nanoparticles significantly expands because changing the surface composition allows us to influence the behavior of objects in different environments – whether they will be evenly distributed throughout the volume or accumulate on the surface, how they will interact with components of the environment and with each other. By modifying the surface of nanoparticles, for example, we can create sorbents for a specific substance, allowing its extraction from samples of various compositions, or attach vector molecules to nanoparticles for targeted delivery to a target organ or tissue.
Understanding how exactly the interaction between the particle surface and components of the reaction medium or solution occurs can be obtained through computer calculations and modeling.
Quantum chemical calculations of the energy spectrum of solid-state materials
The unique properties of nanoparticles are largely associated with the peculiarities of their electronic structure. A nanoparticle is not an individual atom or molecule; it is already a periodic structure but not yet a macroscopic crystal.
For a nanoparticle, its surface exerts a significant influence on the properties of the periodic structure. If we consider the proportion of atoms forming the nanoparticle that are located on the surface, it becomes clear that, unlike a macroscopic crystal, these surface atoms cannot be neglected. This leads to the necessity of conducting quantum chemical calculations of the band structure and density of states for nanoparticles of different sizes or shapes, taking into account their morphological characteristics.
Such calculations provide an understanding of why nanoparticles exhibit or, conversely, lose optical, photocatalytic, photoluminescent, or other properties associated with the peculiarities of the energy spectrum.
Modelling the magnetic properties of nanoparticles with complex structures
The magnetic properties of materials are fairly well understood. However, for nanoparticles and composites based on them, magnetic properties will exhibit unique characteristics each time. Computer modeling, being a reliable tool for researchers, helps initially answer the question “what will be the magnetic properties of nanoparticles or materials if they have such parameters or such a structure”, and then move on to the more complex question “what parameters should nanoparticles have or what should be the structure of a composite material to obtain the desired magnetic properties”. Understanding the answer to the latter question will enable the creation of new materials with unique properties and high-tech devices.
Creating
Development of inorganic nanoparticles and nanomaterials with specified functional characteristics
Directed control of properties of polymer-inorganic composite nanomaterials
Directed construction of polymer-inorganic composite nanomaterials, in which the inorganic component is in a nano state, and interactions between phases occur at the nano level, has been actively developing over the past 20 years.
The peculiarity of these materials lies in the emergence of new functional and operational properties, which can be controlled by regulating the material structure through changing the parameters of the inorganic component, its spatial distribution, and the procedure for obtaining the composite.
Despite significant progress in this area, the results of which have firmly entered our daily lives, obtaining nanomaterials with specified characteristics remains a challenging task. To address this, we extensively employ computational experiments and rely on a large volume of experimental data accumulated by us.