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Gold nanoparticles represent an important class of functional nanomaterials for optoelectronics, biomedical applications, and catalysis. Therefore, controllable synthesis of nanoparticles with specified size and shape is important. Though reduction of gold ions is quite a simple process and may be performed with many different protocols, the reproducibility of the results and transfer of protocols between independent research groups remains a challenging task. Machine learning analysis based on statistical approaches is hardly applicable to the published data, since most of the researchers report only successful syntheses. In this work, we apply uniform sampling of the reaction parameter space. The concentrations of gold precursor, reducing agent, and surfactant were varied via an improved Latin hypercube sampling, and each run was performed under in situ UV−vis control. Based on the resulting set of optical spectra, we address the relevant chemical questions about nanoparticle formation, their shape, and period of growth. Our work demonstrates a data driven approach applied to the space of reaction parameters in a limited available set of experiments.

Photocatalytic hydrogen (H2) production is a promising route for alternative energetics. Understanding structure–activity relationships is a crucial step towards the rational design of photocatalysts, which requires the application of operando spectroscopy under relevant working conditions. We performed an operando investigation on a catalytic system during the photodeposition of Pt on TiO2 and photostimulated H2 production, using simultaneous laboratory X-ray absorption spectroscopy (XAS), UV–Vis spectroscopy, and mass spectrometry. XAS showed a progressive increase in Pt fluorescence for Pt deposited on TiO2 for over an hour, which is correlated with the signal of the produced H2. The final Pt/TiO2 catalyst contained Pt(0) particles. The electronic features corresponding to the Pt4+ species in the UV–Vis spectrum of the solution disappear as soon as UV radiation is applied in the presence of formic acid, which acts as a hole scavenger, resulting in the presence of Pt(0) particles in solution.

Polylactic acid (PLA) porous composite scaffolds with three different infill patterns were subjected to compression testing. The composites were fabricated by 3D printing based on Fused Filament Fabrication (FFF) technology. Stress-strain curves were obtained which allowed to identify Young’s modulus, yield point and residual strain of samples. 3D tomography images were taken before and after deformation. Comparison between images corresponding to a particular sample were used to identify deformation and failure mechanisms.

A multichannel microfluidic cell (MFC) obtained using 3D printing for studying the structure of complex solutions by small-angle X-ray scattering (SAXS) is described. MFC was tested at the BioMUR beamline of the Kurchatov synchrotron. A comparative analysis of SAXS signal from the standard capillary and from the developed MFC was carried out, with MFC showing significant advantages. The dynamics of SAXS scattering curves for lysozyme solutions with NaCl precipitant were studied when the protein and precipitant concentrations changed. The obtained time series of data are well consistent with the known data for the lysozyme solution.

A mathematical model of maintaining the thermal conditions of microreactors used in biological, medical and other experiments that require stabilization or temperature control software is considered. Several heating modes are considered: using a liquid heating jacket, heating from below through the bottom, heating from the side using a flexible silicone heater. Simulated heat loss and dynamic modes of temperature control.

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