The cool flame oscillation occurred around a fuel droplet pair is compared with that around a single droplet. A Variational Auto-Encoder (VAE), a kind of deep neural network, was trained by data of these oscillations. The encoder part of the VAE reduces the data into three dimensions. The data is projected to trajectories in a phase space spanned by the three latent variables from the encoder. The submanifolds, on which the trajectory for each of the single droplet and the droplet pair case were mapped, were determined in the space to sample physical states represented by the distribution of temperature and species mass fraction. The difference distributions, derived by subtracting those of the single droplet from the droplet pair’s distribution, were used to identify the physical process during the cool flame oscillations. Distributions of temperature and mass fractions are sampled at different phases of the oscillation. Similar phenomena are located close together in the phase space, while different ones are located far apart in the space. From the difference distributions, we identified both the locations and the timing at which the temperature or the mass fractions is different for the droplet pair case compared with those of the single droplet.

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This paper reports on a method to immobilize aqueous colloidal dispersions using polymer gels, which was used in the space experiment "Colloidal Clusters" project. The association structure of colloidal particles formed under microgravity conditions on the International Space Station was successfully immobilized by the gel, even after a long storage period of more than 8 months. Gelation was performed through radical polymerization under ultraviolet irradiation. The gelation technique had already been used in the JAXA 3D Photonic Crystal Project on colloidal crystallization, and we found that gelation was possible on the ISS about one month after the sample preparation. On the other hand, since the Colloidal Clusters Project assumed a long waiting time of several months or more, it was necessary to develop a gelation method that could be used over a longer period of time. Thus, we used a gel monomer (N,N-dimethylacrylamide) that is more resistant to aging. In addition, the reaction initiator and gel monomer were injected into separate bags and mixed in space. The colloidal samples could be fixed in the gel successfully and returned to the ground for analysis. We expect the present gelation technique to be useful for space experiments on various soft matter systems.

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The objective of the present study is to quantify and eliminate the error factors in the measurement of diffusion coefficients in liquid alloys by using in-situ X-ray fluorescence analysis (in-situ XRF). Averaging effect, initial mass transport, and matrix effect were investigated. The impurity diffusion coefficient of Bi in liquid Sn was measured at 573 K using a combination of the long capillary technique and in-situ XRF. The apparent diffusion coefficient was obtained as the time-series data by fitting an analytical solution of Fick’s second law to the temporal variation in Bi concentration in the capillary. In the present measurement, matrix effect did not induce a significant error in the measured diffusion coefficient. Averaging effect can be eliminated by convoluting the analytical solution with the distribution of the X-ray fluorescence intensity scanned from the rod sample. Furthermore, the initial mass transport can be eliminated by shifting the point of time origin to the latter time in the temporal variation in the measured concentration by fitting the analytical solution. By performing the above corrections, the systematic error in the measured diffusion coefficient can be reduced.

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