Research on the rapid combustion process of butane under microwave discharge

To study the combustion process of fuel in the microwave plasma torch, we designed a butane microwave plasma device exploiting a tungsten rod as an electrode. Through analysis of the image record by high-speed camera, we found that the discharge of butane microwave plasma torch is a cyclic process at atmospheric pressure at a frequency of around 100 Hz. During the discharge, the active particles continuously diffuse from the electrode to the outside like the bloom of the flower. Then, the variation of plasma torch of jet height and temperature with microwave power is obtained. In addition, we studied the effects of different butane flow rates on the plasma torch. The results illustrate that excessive butane will lead to carbon deposition on the electrode. All in all, this work provides a new understanding of the combustion of the microwave plasma torch, which is conducive to the further development of microwave plasma in the fields of waste gas treatment, fuel combustion, and plasma engine.

Correction: Guided run-and-tumble active particles: wall accumulation and preferential deposition

Correction for ‘Guided run-and-tumble active particles: wall accumulation and preferential deposition’ by Chamkor Singh, Soft Matter, 2021, 17, 8858–8866, DOI: 10.1039/D1SM00775K.

Microscopic study of ion transport in porous electrode of desalination battery based on Lattice Boltzmann method

The desalting process of desalting battery includes ion transport in pores, diffusion in active particles and electrochemical reaction at the interface between solution and active particles. In this paper, quartet...

Synchronized oscillations in swarms of nematode Turbatrix aceti

There is a recent surge of interest in the behavior of active particles that can at the same time align their direction of movement and synchronize their oscillations, known as...

Reinforcement Learning reveals fundamental limits on the mixing of active particles

The control of far-from-equilibrium physical systems, including active materials, requires advanced control strategies due to the non-linear dynamics and long-range interactions between particles, preventing explicit solutions to optimal control problems....

Arctic fog chemistry induces the unexpected growth of Aitken mode particles to CCN-active particles

<p>New particle formation (NPF) and early growth are efficient processes producing high concentrations of cloud condensation nuclei (CCNs) precursors in the Arctic marine boundary layer (AMBL). However, due to short lifetime and lack of condensable vapors, newly formed particles do often not grow beyond 50 nm and cause low CCN particle concentrations in the AMBL. Thus, even the smallest amount of Aitken mode particle growth is capable to significantly increase the CCN budget. However, the growth mechanism of Aitken-mode particles from NPF into CCN range in the Arctic is still rather unclear and was therefore investigated during the cruise campaign PASCAL in 2017.</p> <p>During PASCAL, aerosol particles measurements were performed and an unexpected rapid growth of Aitken mode particles was observed right after fog episodes. Combined field data analyses and detailed multiphase chemistry box model simulations with the CAPRAM mechanism were performed to study the underlying processes. Resulting, a new mechanism is proposed explaining how particles with d < 50 nm are able to grow into CCN size range in the Arctic without requiring high water vapor supersaturation (SS). The investigations demonstrated that the rapid post-fog particle growth of Aitken mode is related to chemical processes within the Arctic fog. The redistribution of semi-volatile acidic (e.g., methanesulfonic acid) and basic (e.g., ammonia) compounds from processed CCN-active particles to smaller CCN-inactive particles can cause a rapid particle growth of Aitken mode particles after fog evaporation enabling them to grow towards CCN size. Comparisons of the model results with Berner impactor measurements supports the proposed growth mechanism.</p> <p>Overall, this study provided new insights on how the increasing frequency of NPF and fog-related particle processing can increase in the number of CCNs and cloud droplets leading to an increased albedo of Arctic clouds and thus affect the radiative balance in the Arctic. Since fogs will occur more frequently in the Arctic as a result of climate change, this growth mechanism and a deeper knowledge on its feedbacks can be essential to understand Arctic warming.</p>

Effect of Composition and Structure of Metal Oxide Composites Nanostructured on Their Conductive and Sensory Properties

The relationship between the structure and properties of nanoscale conductometric sensors based on binary mixtures of metal oxides in the detection of reducing gases in the environment is considered. The sensory effect in such systems is determined by the chemisorption of oxygen molecules and the detected gas on the surface of metal oxide catalytically active particles, the transfer of the reaction products to electron-rich nanoparticles, and subsequent reactions. Particular attention is paid to the doping of nanoparticles of the sensitive layer. In particular, the effect of doping on the concentration of oxygen vacancies, the activity of oxygen centers, and the adsorption properties of nanoparticles is discussed. In addition, the role of heterogeneous contacts is analyzed.

Collective self-optimization of communicating active particles

The quest for how to collectively self-organize in order to maximize the survival chances of the members of a social group requires finding an optimal compromise between maximizing the well-being of an individual and that of the group. Here we develop a minimal model describing active individuals which consume or produce, and respond to a shared resource—such as the oxygen concentration for aerotactic bacteria or the temperature field for penguins—while urging for an optimal resource value. Notably, this model can be approximated by an attraction–repulsion model, but, in general, it features many-body interactions. While the former prevents some individuals from closely approaching the optimal value of the shared “resource field,” the collective many-body interactions induce aperiodic patterns, allowing the group to collectively self-optimize. Arguably, the proposed optimal field–based collective interactions represent a generic concept at the interface of active matter physics, collective behavior, and microbiological chemotaxis. This concept might serve as a useful ingredient to optimize ensembles of synthetic active agents or to help unveil aspects of the communication rules which certain social groups use to maximize their survival chances.