As an important part of lipid metabolism the liver produces large particles called very low density lipoproteins, filled mostly with triglyceride and cholesterol esters mixture. A large percentage of the mixture composition components has a melting point above physiological temperature. Thus solid cluster formation or phase transition could be expected. Though various single-component triglyceride systems are well researched both experimentally and by various simulation techniques, to our best knowledge, tripalmitin/cholesteryl-palmitate binary mixture was not yet studied. We study tripalmitin single component system, as well as 20%-80% and 50%-50% binary mixtures of cholesteryl-palmitate and tripalmitin using molecular dynamics approach. All systems are studied at the pressure of 1 atm and the physiological temperature of 310 K, which is below the melting points of both tripalmitin and cholesteryl-palmitate. Our results show that at the time of 1000 ns, there is still no phase transition, but there is a noticeable tendency to intermolecular organizing and early signs of clustering. We check fatty acid arrangements of tripalmitin molecules in both single component system and binary mixtures with two different percentages of cholesteryl-palmitate mixed in. Our results show that the more cholesteryl-palmitate molecules are in the mixture the smaller number of tripalmitin molecules transitions to 'a fork/chair' configuration during the same calculation time. Calculated angle distributions between fatty acid chains of tripalmitin molecules confirm that. Thus, our simulation results suggest slowing down or interfering effect of cholesteryl-palmitate on the crystallizing process of the binary mixture.

We performed molecular dynamics (MD) experiments to explore dry sliding friction at the nanoscale. We used the setup comprised of a spherical particle built up of 32,000 aluminium atoms, resting on a semi-space with a free surface, modelled by a stack of merged graphene layers. We utilized LAMMPS with the COMB3 many-body potentials for the inter-atomic interactions and Langevin thermostat which kept the system at 300 K. We varied the normal load on the particle and applied different tangential force, which caused the particle sliding. Based on the simulation data, we demonstrate that the friction force F_ fr linearly depends on the sliding velocity v, that is, F_ fr=-γ v, where γ is the friction coefficient. The observed dependence is in a sharp contrast with the macroscopic Amontons-Coulomb laws, which predict the velocity independence of sliding friction. We explain such a dependence by surface fluctuations of the thermal origin, which give rise to surface corrugation hindering sliding motion. This mechanism is similar to that of the viscous friction force exerted on a body moving in viscous fluid.

Molecular dynamic (MD) simulations are applied to investigate the dependency of the kinetic friction coefficient on the temperature at the nano-scale. The system is comprised of an aluminum spherical particle consisting of 32000 atoms in an FCC lattice sliding on a stack of several layers of graphene, and the simulations have done using LAMMPS. The interaction potential is charge-optimized many-body (COMB3) potential and a Langevin thermostat keep the system at a nearly constant temperature. With an assumption of linear viscous friction, $F_{fr}= - \gamma v$, the kinetic friction coefficient $\gamma$ is derived and plotted at different temperatures in the interval of $T \in [1, 600] K$. As a result, by increasing temperature, the kinetic friction coefficient is decreased. Consequently, while the friction is assumed as a linear viscous model, the results are similar to the thermal activation in atomic-scale friction. That is, (1) by increasing sliding velocity friction force will be increased and (2) by increasing temperature, kinetic friction coefficient decreases.

Синдром Линча – один из наиболее распространённых наследственных онкологических синдромов, причиной которого являются патогенные варианты в генах MLH1, MSH2, MSH6, PMS2 или EPCAM. Наиболее часто данное заболевание проявляется карциномами толстой кишки и/или эндометрия, хотя, несколько реже, могут наблюдаться злокачественные поражения целого спектра органов. В условиях повседневной клинической практики основную массу пациентов, направляемых на диагностику синдрома Линча, составляют больные колоректальным раком, при этом их отличительными клиническими особенностями являются молодой возраст и/или наличие семейного онкологического анамнеза. Опухоли, ассоциированные с синдром Линча, характеризуются микросателлитной нестабильностью (microsatellite instability, MSI). Данный тест используется в качестве критерия отбора пациентов и может выполняться как при помощи ПЦР, так и с использованием иммуногистохимического анализа. В случае обнаружения микросателлитной нестабильности ДНК, полученная из лимфоцитов пациента, подвергается анализу нуклеотидной последовательности перечисленных выше генов. Постановка диагноза синдрома Линча позволяет значительно модифицировать тактику лечения онкологического больного. Ранняя диагностика рака у здоровых носителей патогенных вариантов в генах синдрома Линча отличается исключительной клинической эффективностью.

The increasing growth in the development of various novel nanomaterials and their biomedical applications has drawn increasing attention to their biological safety and potential health impact. The most commonly used methods for nanomaterial toxicity assessment are based on laboratory experiments. In recent years, with the aid of computer modeling and data science, several in silico methods for the cytotoxicity prediction of nanomaterials have been developed. An affordable, cost-effective numerical modeling approach thus can reduce the need for in vitro and in vivo testing and predict the properties of designed or developed nanomaterials. We propose here a new in silico method for rapid cytotoxicity assessment of two-dimensional nanomaterials of arbitrary chemical composition by using free energy analysis and molecular dynamics simulations, which can be expressed by a computational indicator of nanotoxicity (CIN2D). We applied this approach to five well-known two-dimensional nanomaterials promising for biomedical applications: graphene, graphene oxide, layered double hydroxide, aloohene, and hexagonal boron nitride nanosheets. The results corroborate the available laboratory biosafety data for these nanomaterials, supporting the applicability of the developed method for predictive nanotoxicity assessment of two-dimensional nanomaterials.

The interaction of water with confining surfaces is primarily governed by the wetting properties of the wall material—in particular, whether it is hydrophobic or hydrophilic. The hydrophobicity or hydrophilicity itself is determined primarily by the atomic structure and polarity of the surface groups. In the present work, we used molecular dynamics to study the structure and properties of nanoscale water layers confined between layered metal hydroxide surfaces with a brucite-like structure. The influence of the surface polarity of the confining material on the properties of nanoconfined water was studied in the pressure range of 0.1–10 GPa. This pressure range is relevant for many geodynamic phenomena, hydrocarbon recovery, contact spots of tribological systems, and heterogeneous materials under extreme mechanical loading. Two phase transitions were identified in water confined within 2 nm wide slit-shaped nanopores: (1) at p1 = 3.3–3.4 GPa, the liquid transforms to a solid phase with a hexagonal close-packed (HCP) crystal structure, and (2) at p2 = 6.7–7.1 GPa, a further transformation to face-centered cubic (FCC) crystals occurs. It was found that the behavior of the confined water radically changes when the partial charges (and, therefore, the surface polarity) are reduced. In this case, water transforms directly from the liquid phase to an FCC-like phase at 3.2–3.3 GPa. Numerical simulations enabled determination of the amount of hydrogen bonding and diffusivity of nanoconfined water, as well as the relationship between pressure and volumetric strain.

The impact of nanoparticles (NPs) composed of atoms with covalent bonding is investigated numerically and theoretically. We use recent models of covalent bonding of carbon atoms and elaborate a numerical model of amorphous carbon (a-C) NPs, which may be applied for modeling soot particles. We compute the elastic moduli of the a-C material which agree well with the available data. We reveal an interesting phenomenon-stress-dependent adhesion, which refers to stress-enhanced formation of covalent bonds between contacting surfaces. We observe that the effective adhesion coefficient linearly depends on the maximal stress between the surfaces and explain this dependence. We compute the normal restitution coefficient for colliding NPs and explore the dependence of the critical velocity, demarcating bouncing and aggregative collisions, on the NP radius. Using the obtained elastic and stress-dependent adhesive coefficients we develop a theory for the critical velocity. The predictions of the theory agree very well with the simulation results.

We performed large-scale numerical simulations using a composite model to investigate the infection spread in a supermarket during a pandemic. The model is composed of the social force, purchasing strategy and infection transmission models. Specifically, we quantified the infection risk for customers while in a supermarket that depended on the number of customers, the purchase strategies and the physical layout of the supermarket. The ratio of new infections compared to sales efficiency (earned profit for customer purchases) was computed as a factor of customer density and social distance. Our results indicate that the social distance between customers is the primary factor influencing infection rate. Supermarket layout and purchasing strategy do not impact social distance and hence the spread of infection. Moreover, we found only a weak dependence of sales efficiency and customer density. We believe that our study will help to establish scientifically-based safety rules that will reduce the social price of supermarket business.

Unique physical and chemical properties of bimetallic nanoparticles of immiscible metals attract the attention of researchers in various fields. Besides materials science and engineering sciences these nanoparticles (NPs) may also be of great practical importance in the biomedicine and the environmental science. Interaction of nanoparticles and nanomaterials with cell and bacterial membranes is a complex multi-factor problem, the solution of which provides an opportunity to predict some parameters of nanoparticles associated with their potential biological activity. This article is the first study of the bimetallic nanoparticles interaction with phospholipid and lipopolysaccharide (LPS) membranes using the molecular dynamics. The free energy change during the Ag-Cu nanoparticles adhesion to the biomembranes were estimated depending on the composition of the membrane and the nanoparticle. Using the force field based molecular dynamics it was shown that lipid membrane tends to wrap Ag-Cu NPs unlike LPS membrane. The presence of loose oxide film on the nanoparticle surface leads to a decrease of adhesive interaction between NP and biomembranes. Using the quantum mechanical calculation, the dependence of surface charge density of Ag-Cu NP on the nanoparticle composition were estimated. The result demonstrates the possibility of tuning the NP electrostatic properties, which, as known, determine the cellular uptake and cytotoxicity of nanomaterials. Most of the findings can be generalized to a case of bimetallic NPs of any pair of immiscible or partially miscible metals.

The design of advanced nanostructured materials with predetermined physical properties requires knowledge of the relationship between these properties and the internal structure of the material at the nanoscale, as well as the dependence of the internal structure on the production (synthesis) parameters. This work is the first report of computer-aided analysis of high pressure consolidation (cold sintering) of bimetallic nanoparticles of two immiscible (Fe and Cu) metals using the embedded atom method (EAM). A detailed study of the effect of cold sintering parameters on the internal structure and properties of bulk Fe-Cu nanocomposites was conducted within the limitations of the numerical model. The variation of estimated density and bulk porosity as a function of Fe-to-Cu ratio and consolidation pressure was found in good agreement with the experimental data. For the first time, topological analysis using Minkowski functionals was applied to characterize the internal structure of a bimetallic nanocomposite. The dependence of topological invariants on input processing parameters was described for various components and structural phases. The model presented allows formalizing the relationship between the internal structure and properties of the studied nanocomposites. Based on the obtained topological invariants and Hadwiger's theorem we propose a new tool for computer-aided design of bimetallic Fe-Cu nanocomposites.

С помощью численного моделирования исследованы некоторые закономерности взаимодействия фундаментальных мод Рэлея с заглубленными неоднородностями различных размеров и скоростных контрастов. Рассчитано поле колебаний на поверхности вблизи рассеивающих неоднородностей в зависимости от частоты. Полученные синтетические сейсмограммы использованы для моделирования предложенной ранее технологии микросейсмического зондирования – оценки решения обратной задачи строения среды с включениями на основе использования фонового микросейсмического поля и предусматривающей простую связь глубины восстанавливаемого слоя и регистрируемой частоты в спектре микросейсм с помощью численного коэффициента приблизительно равного 0.4–0.5. Результаты прямого моделирования совместно с оценкой обратной задачи подтверждают корректность технологии микросейсмического зондирования для оценки структуры среды, которая ранее базировалась исключительно на экспериментальных наблюдениях и носила феноменологический характер. Исследован ряд взаимосвязей между скоростными параметрами исходных неоднородностей и их изображениями после восстановления.

AbstractThis chapter provides a brief review of computer simulation studies on the interaction of nanomaterialswith biomembranes. The interest in this area is governed by the variety of possible biomedical applications of nanoparticles and nanomaterials as well as by the importance of understanding their possible cytotoxicity. Molecular dynamics is a flexible and versatile computer simulation tool, which allows us to research the molecular level mechanisms of nanomaterials interaction with cell or bacterial membrane, predicting in silico their behavior and estimating physicochemical properties. In particular, based on the molecular dynamics simulations, a bio-action mechanism of two-dimensional aluminum hydroxide nanostructures, termed aloohene, was discovered by the research team led by Professor S. G. Psakhie, accounting for its anticancer and antimicrobial properties. Here we review three groups of nanomaterials (NMs) based on their structure: nanoparticles (globular, non-elongated), (quasi)one-dimensional NMs (nanotube, nanofiber, nanorod) and two-dimensional NMs (nanosheet, nanolayer, nanocoated substrate). Analysis of the available in silico studies, thus can enable us a better understanding of how the geometry and surface properties of NMs govern the mechanisms of their interaction with cell or bacterial membranes.

Recent studies have shown that the use of membranes based on artificial nanoporous materials can be effective for desalination and decontamination of water, separation of ions and gases as well as for solutions to other related problems. Before the expensive stages of synthesis and experimental testing, the search of the optimal dimensions and geometry of nanopores for the water desalination membranes can be done using computer-aided design. In the present study, we propose and examine the assumption that rectangular nanopores with a high aspect ratio would demonstrate excellent properties in terms of water permeation rate and ion rejection. Using the non-equilibrium molecular dynamic simulations, the properties of promising hexagonal boron nitride (h-BN) membranes with rectangular nanopores were predicted. It has been found that not only the nanopore width but also its design (“armchair” or “zigzag”) determines the permeability and ion selectivity of the h-BN-based membrane. The results show that membranes with a zigzag-like design of nanopores of ~6.5 Å width and the armchair-like nanopores of ~7.5 Å width possess better efficiency compared with other considered geometries. Moreover, the estimated efficiency of these membranes is higher than that of any commercial membranes and many other previously studied single-layer model membranes with other designs of the nanopores.

A molecular dynamics study of the behavior of benzylpenicillin molecules in slit-shaped nanopores was carried out. A model silicon material with a pore size from 10 to 50 nm was chosen as a nanoporous structure. The interaction between benzylpenicillin molecules was described by a pair potential, built on the basis of modelling the molecule behavior by all-atom force fields. It was shown that an adsorbed layer of benzylpenicillin molecules is formed near the pore walls. With a decrease in the pore size, the maximum density of molecules in the adsorbed layer decreases, while the fraction of adsorbed molecules in the whole pore increases.