This study investigates seeding and cultivation of C2C12 myoblast cells on poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (P3HBV) films synthesized at four polymer concentrations, yielding films with progressively increasing lateral thickness and diverse surface topographies. Cell attachment was evaluated after 24 h, alongside correlations between surface topography and cellular behavior. Surface characteristics across films at each thickness were quantified using atomic force microscopy (AFM), scanning electron microscopy (SEM), advanced topological data analysis (TDA), and threshold relief analysis. C2C12 myoblast growth was imaged via fluorescence microscopy, with quantitative metrics extracted using the Cellpose Plus toolbox. Statistical modeling revealed correlations between surface features and cell morphology. SEM imaging further corroborated pore characteristics against cell growth metrics. Results demonstrate a linear relationship between surface topography and cellular responses, underscoring the critical role of substrate morphology in modulating cell behavior, where films synthesized at high polymer concentrations (5-7% w/v) exhibit enhanced cell attachment. The 85:15 P3HBV copolymer was selected for its favorable thermomechanical properties, high biocompatibility, and cost-effectiveness for large-scale biosynthesis. Our work presents a reproducible data-driven pipeline for analyzing cell-surface interactions, combining TDA and image segmentation metrics to explore the behavior of surface morphology under varying material conditions.

The present study focuses on the problem of taste recognition of coffee by the means of electrochemical imprints. Cyclic voltammetry facilities and machine learning (ML) techniques made it possible to create a combined method of discrimination of taste profile operating with such sensory categories as sweetness, bitterness, acidity as well as overall quality. The electrochemical responses of four different electrodes in nearly 200 different samples of coffee contributed to the essential databases used for training ML-models via supervised algorithms. Best performance of quality recognition was achieved with the help of LogisticRegression using a gold electrode as the sensor (F1=0.89), while acidity and sweetness were recognized in the most efficient way by boosting algorithm at the Ni and Cu sensor electrodes (F1=0.87 and F1=0.72), respectively, and XGBClassifier was the most effective algorithm to estimate bitterness at the gold electrode (F1=0.63). Gas chromatography-mass spectrometry (GC-MS) identified key volatiles, while Density functional theory (DFT)/docking simulations confirmed electrode adsorption of caffeine, acids, and furanmethanol, supporting electrochemical fingerprints as taste proxies.

The radiation sterilization of polymer-based drug solutions can change the characteristics that determine the efficiency of drug targeting, such as particle sizes in the solution and their surface potential. The effect of E-beam treatment at doses of 3 and 8 kGy in a Xe or air atmosphere on the hydrodynamic properties of dilute solutions of polyvinylpyrrolidone (PVP) conjugate with fullerene C60 and folic acid (FA-PVP-C60) was studied and compared with native PVP K30. The capillary viscometry method was used to determine the intrinsic viscosity of solutions. The particle sizes (Rh) were determined using the DLS method. The zeta potential of the particles was determined using the PALS method. The morphological features of the conjugate surface irradiated in a Xe atmosphere with a dose of 8 kGy FA-PVP-C60 were studied by AFM. The functionalization of FA-PVP-C60 and PVP during E-beam treatment was examined using UV- and FTIR-spectrometry. When the diluted solutions of FA-PVP-C60 and PVP were irradiated in air with a dose of 3 kGy, destruction of polymer chains occurred predominantly, but when the dose was increased to 8 kGy, intermolecular cross-linking occurred, leading to an increase in the characteristic viscosity and particle size in the solution. It was shown that the average particle sizes, amounting to 3 and 8 nm for PVP and 4 and 20 nm for FA-PVP-C60, did not change significantly under E-beam irradiation in a Xe atmosphere in the considered dose range. The zeta potential of the particles remained virtually unchanged for both PVP and FA-PVP-C60 under all irradiation conditions. The obtained results indicate the possibility of performing radiation sterilization of FA-PVP-C60 conjugate solutions in an inert gas atmosphere in the range of studied doses.

Here we report on the diverse self-assembly behavior of aminothiacalix[4]arene (ATCA) drop-casted or spin-coated onto a silicon substrate. The nanofilms of ATCA feature the picket-fence domains composed of rod-shaped crystals with the mean size of ca. 700 nm, as well as the ornate patterns composed of interdigitating 3.5-µm grooves and periodically alternating ridge-like framework, with the ridge diameter 90 ± 20 nm and ridge spacing of ca. 3.5 μm. DFT calculation of possible ATCA dimers revealed a favorable arrangement of ATCA monomers either in a face parallel fashion expanding into the 1D channel structure or in a face antiparallel fashion affording the 1D zigzag chain structure. UV/Vis spectroscopy and powder X-ray diffraction data provided further evidence to the existence of thermodynamically favorable π-stacked and hydrogen-bonded ATCA associates in solution and solid state.

This study introduces a novel heuristic phenomenological model for analyzing the evolution of contact areas on rough surface. Contrasting with traditional methods, it employs a cut-off threshold approach to track numerical and topological metrics across different deformation stages. The model quantifies contact area distributions, nested sub-regions, and self-affine parameters, revealing universal trends across scales spanning nanometers to kilometers. Metrics for synthetically generated isotropic surfaces with Hurst exponents H = 2.5 and 3.5 correlate closely with those from AFM and SEM experimental datasets, respectively. In addition, the model has been tested on NASA's SRTM datasets. Cross-correlation demonstrate significant similarities in numerical and topological metrics across diverse measurement techniques, surface types, and scales, highlighting the method's robustness and calibration-free scale invariance. This approach bridges gaps in multiscale tribological analysis, offering deeper insights into frictional transitions and surface interactions. Beyond tribology and materials science, this general approach enables fundamental characterization of surface morphology as such, making it applicable to diverse fields including geomorphology, biomimetics, and nanotechnology.

Synthesis and characterization process of the PHB granules and film.

The study of friction is traditionally a data-driven area with many experimental data and phenomenological models governing structure-property relationships. Triboinformatics is a new area combining Tribology with Machine Learning (ML) and Artificial Intelligence (AI) methods, which can help to establish correlations in data on friction and wear. This is particularly relevant to unstable motion, where deterministic models are difficult to build. There are several types of friction-induced instabilities including those caused by the velocity dependency of dry friction, coupling of friction with another process (wear, heat generation, etc.), the elastic Adams instabilities, and others. The onset of sliding is also an unstable process. ML/AI methods, such as Topological Data Analysis and various ML algorithms, which have been already used for various aspects of data analysis on friction, can be applied also to the frictional instabilities.

The nanoscale topographic features of surfaces, such as vertical, lateral, and multiscale structures, are essential for understanding and identifying correlations with properties in various applications. These features are critical in applications ranging from biomedical devices to electronic components, as they play a significant role in determining the functionality of these systems. Despite the capabilities of traditional surface analysis methods, which rely on standard vertical profile and area measurements, these techniques often fail to capture the subtle and specific features that differentiate between surfaces with different morphologies. To address this challenge, this paper proposes applying of a topological data analysis of atomic force microscopy data to create a unique topological signature for each surface. This approach can help us better understand complex relationships between topography and functional characteristics in various applications and enable further advanced surface comparison.

Periodic modulation of the deposition angle (PMDA) is a new method to deposit nanostructured and continuous layers with controllable periodic density fluctuation. The method is used for the magnetron sputtering of a WO3 layer for an electrochromic device (ECD). An experimental study indicates that the electrochromic coloration-bleaching rate nearly doubles and the electrochromic efficiency grows by about 25% in comparison with the traditional method. The ECD efficiency rises with the increasing degree of nanostructure ordering, surface roughness, and homogeneity of the WO3 layer. The method is promising for coating deposition techniques needed to produce versatile devices with specific requirements for ion transport in surface layers, coatings, and interfaces, such as fuel cells, batteries, and supercapacitors.

We investigate the correlation between the Voronoi entropy (VE) of ligand molecules and their affinity to receptors to test the hypothesis that less ordered ligands have higher mobility of molecular groups and therefore a higher probability of attaching to receptors. VE of 1144 ligands is calculated using SMILES-based 2D graphs representing the molecular structure. The affinity of the ligands with the SARS-CoV-2 main protease is obtained from the BindingDB Database as half-maximal inhibitory concentration (IC50) data. The VE distribution is close to the Gaussian, 0.4 ≤ Sv ≤ 1.66, and a strong correlation with IC50 is found, IC50 = -275 Sv + 613 nM, indicating the correlation between ligand complexity and affinity. On the contrary, the Shannon entropy (SE) descriptor failed to provide enough evidence to reject the null hypothesis (p-value > 0.05), indicating that the spatial arrangement of atoms is crucial for molecular mobility and binding.

The surface roughness of layer-by-layer (LbL) polyelectrolytes is studied by atomic force microscopy (AFM) and analyzed with novel methods including topological data analysis (TDA) and machine learning (ML) to correlate multiscale roughness with the number of bilayers and to recognize the types of polyelectrolytes (PEs). LbL PEs composed of one to four bilayers of (1) polyethylenimine (PEI)/poly(sodium 4-styrenesulfonate) (PSS), (2) PEI/poly(acrylic acid) (PAA), and (3) PEI/MXene rigid flakes are deposited on a smooth silicon wafer. With a growing number of bilayers, the roughness changes from a smooth surface to an equilibrium rough profile. The AFM study of the surface morphology demonstrates that surface roughness is multiscale, with smaller features imposed on larger ones. Roughness data is filtered from measurement resolution artifacts, and several methods are applied: correlation length, statistics of the distribution of extremes in trimmed images, and TDA barcodes and persistence diagrams of simplexes in 8D data space. An ML algorithm is used to determine the number of bilayers in a PE. Roughness analysis indicates a gradual transition from a smooth to a rough surface with saturation at three to four bilayers and the existence of multiscale roughness invariance.

Polished brass alloy plate samples were treated by ultrasound in an alkaline buffer at different concentrations and sonication amplitudes. Sample topography was studied by atomic force microscopy and processed by algorithms of topological data analysis. Persistence diagrams, barcodes, autocorrelation functions, and spatial distribution of heights (min-max regions) were constructed. The isotropy/anisotropy of the surface, the level of roughness, and grain size distribution were analyzed for all samples. The brass alloy samples with various grain sizes can be useful as structured coatings with controlled bactericidal effects due to the presence of copper.

Sustainable structural design, utilizing material to imitate natural biological systems, presents both promise and challenges. By avoiding interfacial problems encountered in composite counterparts, such designs offer self-adaptive materials for smart housing and green architecture, etc. In this study, we demonstrate the feasibility of large-scale self-assembly of graphene oxide (GO) flakes into anisotropic films through a simple blade coating technique. Through the application of blade coating to a highly concentrated nematic GO suspension, we successfully fabricate GO films with morphological gradient and patterning. Additionally, we propose a statistical analysis method utilizing scanning electron microscopy (SEM) images for the characterization of materials with macroscopic surface morphology. Furthermore, we explore the application of these GO films as low-dimensional soft actuators, revealing their outstanding stimuli-responsive performance and self-adaptation to environment. Such robust and flexible films can be used as integral building elements in the bioinspired design of sustainable smart housing facilitating remote robotization and sensing capabilities.

The emerging novel class of two-dimensional materials - MХenes - have attracted significant research attention. However, there are only few reports on using the most prominent member of the MXene family, Ti3 C2 Tx , as an active material for memristive devices within a polyelectrolyte matrix and its deposition on inert electrodes like ITO and Pt. In this study, we systematically investigate Ti3 C2 Tx MXenes synthesized with two classical delamination agents, such as lithium chloride and tetramethylammonium hydroxide, to identify the most suitable candidate for memristive device applications. The characteristics of memristors based on the hybrid structures consisting of MXene-polyelectrolyte multilayers, specifically polyethyleneimine (PEI) and poly(sodium 4-styrenesulfonate) (PSS) are explored. The PEI(MXene)/PSS memristor exhibits a voltage threshold (VSET/RESET ) range of 1.5-2.0 V, enabling the transition from a high-resistive state (HRS) to a low-resistive state (LRS), along with a significant current switching ratio of approximately two orders of magnitude. The observed VSET/RESET difference of approximately 4 V is further supported by density functional theory (DFT) calculated redox potential. These findings underscore the potential of polyelectrolyte-based memristors, such as the in PEI-Ti3 C2 Tx -PSS system, in facilitating the development of highly functional, self-assembled memristive devices with diverse applications.

A concept of piezo-responsive hydrogen-bonded π-π-stacked organic frameworks made from Knoevenagel-condensed vanillin–barbiturate conjugates was proposed. Replacement of the substituent at the ether oxygen atom of the vanillin moiety from methyl (compound 3a) to ethyl (compound 3b) changed the appearance of the products from rigid rods to porous structures according to optical microscopy and scanning electron microscopy (SEM), and led to a decrease in the degree of crystallinity of corresponding powders according to X-ray diffractometry (XRD). Quantum chemical calculations of possible dimer models of vanillin–barbiturate conjugates using density functional theory (DFT) revealed that π-π stacking between aryl rings of the vanillin moiety stabilized the dimer to a greater extent than hydrogen bonding between carbonyl oxygen atoms and amide hydrogen atoms. According to piezoresponse force microscopy (PFM), there was a notable decrease in the vertical piezo-coefficient upon transition from rigid rods of compound 3a to irregular-shaped aggregates of compound 3b (average values of d33 coefficient corresponded to 2.74 ± 0.54 pm/V and 0.57 ± 0.11 pm/V), which is comparable to that of lithium niobate (d33 coefficient was 7 pm/V).

AbstractUse of inorganic oxides as transport layer material is a promising way to increase the efficiency of perovskite solar cells. Results of the studies of the influence of the gas mix composition in the plasma discharge used during magnetron sputtering on the optical, electrical, and structural parameters of deposited thin nickel oxide films are reported. Addition of oxygen or nitrogen to pure argon atmosphere (up to 30 vol %) was shown to change the growth rate (1.2–2.3 nm/min), resistivity of the samples (8.5–208 Ω cm), material band gap (2.85–3.43 eV), and the spectral dependence of the extinction coefficient, while the structural and morphological parameters of synthesized thin films were not affected. The lowest extinction coefficients were found in films deposited in pure argon atmosphere, which determines the capabilities of their usage in photovoltaic converters based on perovskite compounds.

Use of inorganic oxides as transport layer material is a promising way to increase the efficiency of perovskite solar cells. Results of the studies of the influence of the gas mix composition in the plasma discharge used during magnetron sputtering on the optical, electrical, and structural parameters of deposited thin nickel oxide films are reported. Addition of oxygen or nitrogen to pure argon atmosphere (up to 30 vol %) was shown to change the growth rate (1.2–2.3 nm/min), resistivity of the samples (8.5–208 Ω cm), material band gap (2.85–3.43 eV), and the spectral dependence of the extinction coefficient, while the structural and morphological parameters of synthesized thin films were not affected. The lowest extinction coefficients were found in films deposited in pure argon atmosphere, which determines the capabilities of their usage in photovoltaic converters based on perovskite compounds.