Effects of a liquid-phase sodium disilicate additive on the properties of ZrO2 ceramics containing 3 mol.% of Y2O3 and 2 wt% of Al2O3 are presented, including phase composition, microstructure, shrinkage, porosity, and bending strength. The distribution of elements along grain boundaries and the composition in a selected area of a lamella were investigated by transmission electron microscopy in pure and additive-containing samples. As a result of the introduction of the additive, sintering activity of the material increased, and the sintering temperature diminished down to 1150 degrees C. Thus, dense nanocrystalline materials with a crystallite size of 50-70 nm and a bending strength of up to 450 MPa were obtained. Optimized polymer-ceramic suspensions were used to produce objects with complex geometric shapes by 3D molding technology through layer-by-layer vat polymerization. According to in vitro assays, the obtained samples are nontoxic and cytocompatible with human osteosarcoma MG-63 cells, and according to in vivo experiments, are biocompatible and showing osseointegrative properties when implanted into the rat tibia.

The specific feature of Cu(Co) solid solutions with a sub-solidus composition involves the formation of submicron-sized cobalt particles on the free surface. In this work, Cu(Co) substrates with cobalt particles on the surface were produced through the annealing of a series of copper-based cobalt solid solutions con-taining 1-3 at% Co in a hydrogen atmosphere at 1050 degrees C, leading to the formation of a family of cobalt-based submicron-sized particles with a similar orientation within one grain on the surface. The wetting and spreading of lead and copper-based liquid alloys on the surfaces of these substrates were compared to the wetting of pure copper and pure cobalt. Experiments were conducted via the high-speed video recording of droplet transfer onto the Cu, Co, and Cu(Co) substrates at 400 degrees C (melt: pure lead), at 850 degrees C (Pb + 10.3 at% Cu), and at 1070 degrees C (Cu + 2.5 at% Ag) in a vacuum. The contact angle of the Pb melt on cobalt (46 degrees) differed significantly from the contact angle on copper at 400 degrees C (32 degrees), while at 850 degrees C, the wetting for both metals was almost complete (the wetting angles for Cu and Co were 5 degrees and 7 degrees, respectively). The wetting angle for the Cu(Co) solid solution surface with cobalt particles was almost equal to that for pure copper, and the spreading rates were comparable for the two cases. The wetting of the Cu, Co, and Cu(Co) surfaces by the Cu (Ag) melt did not demonstrate any significant differences between the equilibrium contact angles (tending to zero), while the spreading rate differed only slightly. The surface area covered by the particles reached 20%, despite the presence of the particles, which exerted no impact on the contact angle, due to two possible effects: (i) the formation of an adsorbed copper layer on the surface of the cobalt phase confirmed by room-temperature Auger electron spectroscopy, and (ii) the compensation of wetting deterioration by an increase in roughness. (c) 2023 Elsevier B.V. All rights reserved.

Property prediction accuracy has long been a key parameter of machine learning in materials informatics. Accordingly, advanced models showing state-of-the-art performance turn into highly parameterized black boxes missing interpretability. Here, we present an elegant way to make their reasoning transparent. Human-readable text-based descriptions automatically generated within a suite of open-source tools are proposed as materials representation. Transformer language models pretrained on 2 million peer-reviewed articles take as input well-known terms such as chemical composition, crystal symmetry, and site geometry. Our approach outperforms crystal graph networks by classifying four out of five analyzed properties if one considers all available reference data. Moreover, fine-tuned text-based models show high accuracy in the ultra-small data limit. Explanations of their internal machinery are produced using local interpretability techniques and are faithful and consistent with domain expert rationales. This language-centric framework makes accurate property predictions accessible to people without artificial-intelligence expertise.

Immense effort has been exerted in the materials informatics community towards enhancing the accuracy of machine learning (ML) models; however, the uncertainty quantification (UQ) of state-of-the-art algorithms also demands further development. Most prominent UQ methods are model-specific or are related to the ensembles of models; therefore, there is a need to develop a universal technique that can be readily applied to a single model from a diverse set of ML algorithms. In this study, we suggest a new UQ measure known as the Δ-metric to address this issue. The presented quantitative criterion was inspired by the k-nearest neighbor approach adopted for applicability domain estimation in chemoinformatics. It surpasses several UQ methods in accurately ranking the predictive errors and could be considered a low-cost option for a more advanced deep ensemble strategy. We also evaluated the performance of the presented UQ measure on various classes of materials, ML algorithms, and types of input features, thus demonstrating its universality.

Multicomponent heterogeneous systems containing volatile amphiphiles are relevant to the fields ranging from drug delivery to atmospheric science. Research presented here discloses the individual interfacial activity and adsorption-evaporation behavior of amphiphilic aroma molecules at the liquid-vapor interface. The surface tension of solutions of nonmicellar volatile surfactants linalool and benzyl acetate, fragrances as such, was compared with that of the conventional surfactant sodium dodecyl sulfate (SDS) under equilibrium as well as under no instantaneous equilibrium, including a fast-adsorbing regime. In open systems, the increase in the surface tension on a time scale of ∼10 min is evaluated using a phenomenological model. The derived characteristic mass transfer constant is shown to be specific to both the desorption mechanism and the chemistry of the volatile amphiphile. Fast-adsorbing behavior disclosed here, as well as the synergetic effect in the mixtures with conventional micellar surfactants, justifies the advantages of volatile amphiphiles as cosurfactants in dynamic interfacial processes. The demonstrated approach to derive specific material parameters of fragrance molecules can be used for an application-targeted selection of volatile cosurfactants, e.g., in emulsification and foaming, inkjet printing, microfluidics, spraying, and coating technologies.

The misorientation of 515 grain boundaries has been determined using electron backscatter diffraction data from an 18 μm thick copper foil with columnar grain structure and a preferential {110} surface orientation. The energy of the grain boundaries was determined from the dihedral angles in the vicinity of grain boundary thermal grooves. The experimental grain boundary energy vs. misorientation angle shows deep minima for the low-angle grain boundaries and small minima corresponding to the Σ3 and Σ9 grain boundaries. Only a small fraction of the coincidence site lattice grain boundaries demonstrate an increased occurrence frequency (compared to a random orientation distribution) and low energy. In parallel, the grain boundary energy for a subset of 400 symmetrical tilt grain boundaries was calculated using molecular statics simulations. There is a good agreement between the experiment and molecular statics modeling.

The enormous structural and chemical diversity of metal-organic frameworks (MOFs) forces researchers to actively use simulation techniques as often as experiments. MOFs are widely known for their outstanding adsorption properties, so a precise description of the host-guest interactions is essential for high-throughput screening aimed at ranking the most promising candidates. However, highly accurate ab initio calculations cannot be routinely applied to model thousands of structures due to the demanding computational costs. Furthermore, methods based on force field (FF) parametrization suffer from low transferability. To resolve this accuracy-efficiency dilemma, we applied a machine learning (ML) approach: extreme gradient boosting. The trained models reproduced the atom-in-material quantities, including partial charges, polarizabilities, dispersion coefficients, quantum Drude oscillator, and electron cloud parameters, with accuracy similar to the reference data set. The aforementioned FF precursors make it possible to thoroughly describe noncovalent interactions typical for MOF-adsorbate systems: electrostatic, dispersion, polarization, and short-range repulsion. The presented approach can also readily facilitate hybrid atomistic simulation/ML workflows.

The article presents the results of 3D printing with ceramic suspensions by DLP method using inorganic dyes.

A method is proposed for the neural network based analysis of the existence and stability of grain boundary complexions formed at high-symmetry tilt boundaries Σ3 (111) and Σ5 (210) in a polycrystalline Ni(Bi) solid solution. This method is based on the use of reference interparticle interaction potentials constructed within the framework of the density functional theory in combination with the structural capabilities of an artificial two-level self-learning neural network. The absolute error in determining potential energy by the neurosystem analysis is 0.012 eV/atom. The values of the formation enthalpy of grain boundary complexions for Σ3 and Σ5 boundaries are in rather good agreement with the published results of simulating this system and experimental data.

Al-substituted hydroxyapatite (Al-HA) powders with apatite structure and particle size of 30-70 nm were obtained via precipitation method. The effect of Al content on specific surface area and morphology of powders was studied, and a formation of highly anisotropic phase due to Al doping was observed. The influence of heat treatment in 300-1400 degrees C range on the phase composition, lattice parameters, Fourier-transform infrared spectroscopy (FTIR) spectra and mass loss of powders was investigated. Introduction of Al in the hydroxyapatite (HA) lattice in the range 0.5-1.0 mol.% resulted in the improvement in thermal stability, which had not been reported previously. Incorporation of 5-10 mol.% of Al resulted in the formation of biphasic materials based on HA and whitlockite-like structure at 900 degrees C and apatite and alpha-tricalcium phosphate (alpha-TCP) phases at 1200-1400 degrees C. Introduction of 20 mol.% of Al resulted in the formation of isomorphic Al-substituted whitlockite phase Ca9Al(PO4)(7). We have estimated the onset of Ca9Al(PO4)(7) transformation into alpha-TCP phase at 1400 degrees C. (C) 2019 Published by Elsevier B.V.

High-performance modeling of interfacial phases is a challenge because of the low scalability of first-principle methods. Here we present a data-driven approach based on using the machine learning potential to address this problem. The developed model quantitatively reproduces the formation energy of Bi films on selected Ni grain boundaries. This scheme allows us to model arbitrary grain boundaries, preserving chemical accuracy of the reference method. The suitability of the interatomic potential is also confirmed by the construction of a grain boundary phase diagram. This approach opens the door for the accelerated study of the full configurational space of interfacial phases.

Nanocrystalline 3 mol% yttria-tetragonal zirconia polycrystal (3Y-TZP) ceramic powder containing 5 wt.% Al2O3 with 64 m2/g specific area was synthesized through precipitation method. Different amounts of Co (0–3 mol%) were introduced into synthesized powders, and ceramic materials were obtained by heat treatment in the air for 2 h at 1350–1550 °C. The influence of Co addition on the sintering temperature, phase composition, microstructure, mechanical and biomedical properties of the obtained composite materials, and on the resolution of the digital light processing (DLP) printed and sintered ceramic samples was investigated. The addition of a low amount of Co (0.33 mol%) allows us to decrease the sintering temperature, to improve the mechanical properties of ceramics, to preserve the nanoscale size of grains at 1350–1400 °C. The further increase of Co concentration resulted in the formation of both substitutional and interstitial sites in solid solution and appearance of CoAl2O4 confirmed by UV-visible spectroscopy, which stimulates grain growth. Due to the prevention of enlarging grains and to the formation of the dense microstructure in ceramic based on the tetragonal ZrO2 and Al2O3 with 0.33 mol% Co the bending strength of 720 ± 33 MPa was obtained after sintering at 1400 °C. The obtained materials demonstrated the absence of cytotoxicity and good cytocompatibility. The formation of blue CoAl2O4 allows us to improve the resolution of DLP based stereolithographic printed green bodies and sintered samples of the ceramics based on ZrO2-Al2O3. The developed materials and technology could be the basis for 3D manufacturing of bioceramic implants for medicine.

A molecular dynamics method developed on the basis of the classical nucleation theory for calculating the interfacial energy at melt–crystal interfaces has been extended to binary metal systems. The temperature dependence plotted for the interfacial energy of a Pb–Cu bimetallic system within a range of 1025–1125 K is in good agreement with the results of the statistical calculations performed within the framework of a simplified quasi-crystalline coherent model of the liquid phase and the interface taking into account the interatomic interactions with the closest neighbors. A similar methodology may be used to determine the interfacial energy for a wide spectrum of multicomponent metal systems, if the interparticle interaction potentials have been reliably determined for them.

Understanding of non-equilibrium processes at dynamic interfaces is indispensable for advancing design and fabrication of solid state and soft materials.The research presented here unveils specific interfacial behavior of aroma molecules and justifies their usage as multifunctional volatile surfactants. As non-conventional volatile amphiphiles we study commercially available poorly water-soluble compounds from the classes of synthetic and essential flavor oils. Their distinctive feature is high dynamic interfacial activity, so that they decrease the surface tension of aqueous solutions on a time scale of milliseconds. Another potentially useful property of such amphiphiles is their volatility, so that they notably evaporate from interfaces on a time scale of seconds. This behavior allows for control of wetting and spreading processes. A revealed synergetic interfacial behavior of mixtures of conventional and volatile surfactants is attributed to a decrease of the adsorption barrier as a result of high statistical availability of new sites at the surface upon evaporation of the volatile component. Our results offer promising advantages in manufacturing technologies which involve newly creating interfaces, such as spraying, coating technologies, ink-jet printing, microfluidics, laundry, stabilization of emulsions in cosmetic and food industry, as well as in geosciences for controlling aerosols formation.

In the present study, the capillary equilibrium along the triple junctions of grain boundaries (GB) was analyzed. The values of GB energy torque terms were estimated for an 18-μm-thick copper foil with {110} texture from the dihedral angles formed between the intersections of the GB planes and the sample surface and dihedral angles between the GB planes joined at a triple junction. The average value of the torque term was found to be greater than 15 pct of the GB energy.

Al-substituted beta-tricalcium phosphate (β-TCP) nanopowders containing 0–20mol.% of Al were obtained via precipitation method. The effect of Al content on the phase composition, lattice parameters, crystallite size, specific surface area and morphology of powders was established. Over the substitution range 0 – 1mol.% the synthesis products consist of single whitlokite-like phase. For 5 – 20mol.% two separate whitlokite-like phases were indentified: Al enriched Ca9Al(PO4)7 and β-TCP solid solution. For both phases, the general trend is a reduction of cell parameters, as well as decrease of crystalline and particle size with an increase of Al content. Powder with 20mol.% of Al consists of 84wt% of Ca9Al(PO4)7 and 16wt% of β-TCP solid solution and is formed by spherical particles with average size of 20–30nm and specific surface area of 129m2/g.