arXiv subjects

V. Tonchev

Publications and source records attributed to V. Tonchev.

3 recordsLinked to original sources

arXiv2023

Modelling crystallization: When the normal growth velocity depends on the supersaturation

The crystallization proceeds by the advance of the crystal faces into the disordered phase at the expense of the supersaturation which is not sustained in our model. Using a conservation constraint for the transformation ratio and a kinetic law, we derive a general equation for the rate of transformation. It is integrated for the six combinations of the three spatial dimensions D = 1, 2, 3 and the two canonical values of the growth order (1 and 2). The same equation with growth order 1 is obtained when taking only the linear term from the Taylor's expansion around 0 transformation of the model of Johnson-Mehl-Avrami-Kolmogorov(JMAK). We verify our model by fitting it with JMAK. We start the validation of our model in 2D with published results.

cond-mat.mtrl-sci↗

arXiv2018

What One Can Learn From the Cloud Condensation Nuclei (CCN) Size Distributions as Monitored by the BEO Moussala?

In this proceeding we report initial studies into the big data set acquired by the Cloud Condensation Nuclei (CCN) counter of the Basic Environmental Observatory (BEO) Moussala over the whole 2016 year at a frequency of 1 Hz. First, we attempt to reveal correlations between the results for CCN number concentrations on the timescale of a whole year (2016) as averaged over 12 month periods with the meteorological parameters for the same period and with the same time step. Then, we zoom into these data and repeat the study on the timescale of a month for two months from 2016, January and July, with a day time step. For the same two months we show the CCN size distributions averaged over day periods. Finally, we arrive at our main result: typical, in terms of maximal and minimal number concentrations, CCN size distributions for chosen hours, one hour for each month of the year, hence 24 distributions in total. These data show a steady pattern of peaks and valleys independent of the concrete number concentration which moves up and down the number concentrations (y-axis) without significant shifts along the sizes (x-axis).

physics.ao-ph↗

arXiv2016

Step bunching and macrostep formation in 1D atomistic scale model of unstable vicinal crystal growth

We devise a new 1D atomistic scale model of vicinal growth based on Cellular Automaton. In it the step motion is realized by executing the automaton rule prescribing how adatoms incorporate into the vicinal crystal. Time increases after each rule execution and then nDS diffusional updates of the adatoms are performed. The increase of nDS switches between the diffusion-limited (DL, nDS=1) and kinetics-limited (KL, nDS >> 1) regimes of growth. We study the unstable step motion by employing two alternative sources of instability - biased diffusion and infinite inverse Ehrlich-Schwoebel barrier (iiSE). The resulting step bunches consist of steps but also of macrosteps since there is no step-step repulsion incorporated explicitly into the model. This complex pattern formation is quantified by studying the time evolution of the bunch size N and macrostep size Nm in order to find the proper parameter combinations that rescale the time and thus to obtain the full time-scaling relations including the pre-factors. For the case of biased diffusion the time-scaling exponent beta of N is 1/2 while for the case of iiSE it is 1/3. In both cases the time-scaling exponent beta_m of Nm is ~3beta/4 in the DL regime and 3beta/5 in the KL one.

cond-mat.mtrl-sci↗