In order to create neuromorphic computing systems (NCSs) capable of efficiently solving artificial intelligence problems, elements with short- and long-term memory effects are required. Memristors are promising candidates for the implementation of such elements since they demonstrate volatile and nonvolatile resistive switching (RS) modes. Of particular interest are structures that realize both RS modes in a single device. In this work, parylene-based nanocomposite memristors with MoO3 nanoparticles have been studied in crossbar architecture, which is convenient for NCS implementation. For these structures, a reversible temperature-induced transition between volatile and nonvolatile RS modes was found if local, controlled via the compliance current, or external temperature is fine-tuned. In addition, the crossbar structures showed high endurance to cyclic RS, ability to retain states in nonvolatile mode and multilevel nature of RS. The obtained results open the possibility of using parylene-based crossbar structures in bioinspired NCSs.

In recent years, many scientific groups have been working on hardware implementation of the artificial neural networks to approach the computational efficiency of their biological counterpart. Memristors may play the role of synapses in such networks [1]. Varieties of memristive structures and materials have already been tested in different neural network architectures, but still no memristor is considered ideal for hardware synapse implementation [1]. One of the most significant problems is the presence of inherent stochasticity distinctive for all memristive devices, which complicates the training of the neural networks [1]. Several approaches were proposed to partially mitigate this problem, e.g., a reservoir computing system (RCS) [2] and spiking neural networks (SNN) [3] as well as defect engineering for memristive characteristics improvement. In this work, we propose to combine RCS with SNN and create a bio-inspired neuromorphic system based on two types of organic memristors with specifically designed structures and advanced characteristics. The RCS consists of two main parts: the reservoir and the readout [2]. The reservoir layer extracts some representative features from the input data due to its internal nonlinear dynamics. The readout layer then uses these features to classify the input data. Typically, a conventional fully connected neural network is used as a readout layer in the RCS. The training process occurs only in the readout layer, while a reservoir is not trainable. This decrease in trainable parameters considerably reduces the memristive stochasticity impact on the training process. The use of different types of memristors for the RCS is essential. The reservoir layer should consist of memristors with short-term memory, i.e., volatile memristors. This way, memristors can process each input sample individually. Volatile polyaniline-based memristors were chosen for this layer implementation. They can operate within a biologically plausible time range, which is essential as we aim to mimic biological systems [4]. In contrast, the reservoir layer should consist of memristors with long-term memory, i.e., non-volatile memristors, because the readout layer should preserve the trained synaptic weights. Non-volatile parylene memristors with incorporated MoO3 nanoparticles were chosen for the readout layer. The reservoir computing system adopts some essential principles of brain function, as both short- and long-term memory are significant in biological systems. However, traditional neural networks are commonly used as a readout layer in the RCSs [2]. Their training requires global weight updates, making them vulnerable to memristive stochasticity. In contrast, the SNNs allow local training, e.g., using bio-inspired learning rules, which makes them more effective and robust [3]. Consequently, we presume that a fully organic RCS with an SNN readout layer is a promising hardware memristive architecture. The work consists of two parts: hardware and software. First, the polyaniline- and parylene-based memristive devices were fabricated and tested. Hardware polyaniline reservoir demonstrated an ability to extract characteristic features from the input data. Nanocomposite parylene memristors were suitable for the role of synapses in the readout layer due to the unique combination of high switching speed, high stability, low power consumption and the possibility of crossbar implementation. Next, the traditional and spiking readout layers were compared in simulation. It was shown that the SNN readout layer is more adaptive and sustainable to noise in image classification tasks as well as memristive stochasticity [5].

Poly( p -xylylene)–molybdenum oxide nanocomposite thin films of different thicknesses and inorganic filler content are synthesized by low-temperature vapor deposition polymerization. The structure of the nanocomposites and its evolution during thermal annealing is studied by wide angle X-ray scattering and X-ray absorption spectroscopy. It is found that the molybdenum oxide nanoparticles are amorphous in both the as-deposited and annealed composite films. The short-range order characteristic of orthorhombic molybdenum trioxide is preserved in the nanoparticles; however, a noticeable disordering of the structure together with a decrease in the effective oxidation state of molybdenum are revealed. Both an increase in the filler content and thermal annealing lead to a decrease in the bandgap of the composites, which is related to the increase in the nanoparticle size. It is shown that thermal annealing improves the stability of the resistive switching (RS) characteristics in memristors based on the synthesized nanocomposites, which creates an opportunity for the application of these materials as the active layer of memristive devices.

Методом полимеризации на поверхности из газовой фазы синтезированы образцы тонкопленочных композитов на основе поли-пара-ксилилена и оксида молибдена с различной толщиной и концентрацией неорганического наполнителя. Методами рентгеновского рассеяния и спектроскопии поглощения рентгеновского излучения исследована структура синтезированных композитов и ее изменение при термическом отжиге. Обнаружено, что наночастицы оксида молибдена как в исходных, так и в отожженных образцах остаются аморфными. При этом в наночастицах сохраняются элементы локального порядка, характерные для орторомбического триоксида молибдена, однако происходит заметное разупорядочение структуры с понижением эффективной степени окисления молибдена. Увеличение концентрации наполнителя и отжиг приводят к уменьшению ширины запрещенной зоны в наночастицах оксида молибдена, что, по всей видимости, связано с увеличением размера наночастиц. Показано, что отжиг приводит к улучшению стабильности характеристик резистивного переключения в мемристорах на основе синтезированных композитов, что открывает возможность использования данных материалов в качестве активного слоя мемристивных устройств.

We proposed a method of cyclic alternating-current voltammetry with track membranes (TM) filled with ion exchangers with asymmetric pores for the determination of acetylcholine chloride (ACC). We studied the electrochemical and performance characteristics of the determination of ACC using track membranes with pores filled with nanoparticles of crushed cation and anion exchangers. Acetylcholine chloride can be determined in concentrations down to 10–6 M.

The track membranes based on poly(ethylene terephthalate) activated by low-temperature plasma were modified with the use of a solution of N-isopropylacrylamide in an organic solvent. The filtration efficiency of the modified membranes was higher by a factor of 2.5 than that of the original track membrane.

The blueshift of a probe laser pulse propagating in an unsteady plasma has been experimentally detected. The possibility of using this method for the diagnostic of the dense femtosecond plasma has been demonstrated.

Microemulsion electrokinetic chromatography (MEEKC) offers a valuable tool for the rapid and highly productive determination of lipophilicity for metal-based anticancer agents. In this investigation, the MEEKC technique was applied for estimation of n-octanol-water partition coefficient (logP(oct)) of a series of antiproliferative complexes of gallium(III) and iron(III) with (4)N-substituted α-N-heterocyclic thiosemicarbazones. Analysis of relationships between the experimental logP(oct) and the retention factors of compounds showed their satisfactory consistency in the case of single metal sets, as well as for both metals. Since none of available calculation programs allows for evaluating the contribution of central metal ion into logP(oct) (i.e. ΔlogP(oct)) of complexes of different metals, this parameter was measured experimentally, by the standard 'shake-flask' method. Extension of the logP(oct) programs by adding ΔlogP(oct) data resulted in good lipophilicity predictions for the complexes of gallium(III) and iron(III) included in one regression set. Comparison of metal-thiosemicarbazonates under examination in terms of logP(oct) vs. antiproliferative activities (i.e. 50% inhibitory concentration in cancer cells) provided evidence that their cytotoxic potency is associated with the ability to cross the lipid bilayer of the cell-membrane via passive diffusion.

The process of geometrical modification of pores in poly(ethylene terephthalate) track-etched membranes (TM) by use of plasma deposition of a fluorine-containing polymer protective layer on one membrane surface and alkali etching of the other surface has been studied in order to produce membranes with improved performance characteristics. Samples of membranes with conical pores have been obtained which have better filtration efficiency compared with initial TM with cylindric pores. Plasma polymerization of 1H,1H,2H-perfluoro-1-octene at the membrane surface was used to produce the protective layer resistant to alkali solutions. The occurrence of plasma modification and changing of pore geometry have been verified by X-ray photoelectron spectroscopy and scanning electron microscopy studies. The filtration efficiency and selectivity of the modified membranes have been studied.

Reinforced track membranes are used for the first time to study element distribution between particles of various sizes and other water components. The properties of the reinforced track membranes are considered. Factors affecting the quality of water in the Volga River in the region of the water intake of the city of Dubna in the Moscow region and potable water in various districts of the city in are characterized by the fractional composition of macro- and microcomponent.