Posters will be presented in front of room 0.06

A1

Mai Yotsumoto

Detection of alcohols using artificial sniffing

Hiroshima University

We smell by sniffing. For mimicking the sniffing, we constructed a experimental system to pulse odor stimuli to DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphocholine) molecular layer and measured the time changes of the surface tension (γ) of phopholipid molecular layers. The alcohol (CnH2n+1OH) with n = 3, 4 increased γ while the fan was running, that with n = 8, 9 decreased γ. It is thought that the alcohols with n = 3, 4 act on the hydrophobic part of DPPC, while that with n = 8, 9 act on the hydrophilic part, inducing a different arrangement of DPPC molecules and causing the charactristic changes in γ.

A2

Karol Bukowski

Influence of micro- and mesoscale on the permeability characteristics of 3D printed porous objects

Warsaw University of Technology

The study aims to deepen the understanding of fluid behaviour within porous media by examining the influence of different porosity structures on permeability and exploring the relationship between pressure gradients and flow efficiency. Hybrid structures combining micro and mesoscales were created to assess their combined impact on fluid flow. Experimental data derived from measuring pressure gradients and flow velocities were used to calculate permeability coefficients according to the Darcy-Forchheimer law. The study introduces dimensionless flow efficiency coefficients, linking geometric characteristics of porous objects with their flow impact, revealing that hybrid structures exhibit superior flow efficiency. These findings contribute significantly to the field of porous media analysis, offering insights into optimizing industrial applications through an improved understanding of fluid flow dynamics.

B1

Ayase Kawamura

Self-propulsion of Aldehyde Droplets on Surfactant Solutions

Hiroshima University

The spontaneous motion of oil droplets in aqueous solution due to interfacial tension differences around them is well known, but reports of self-propulsion in chemically reactive droplets are rare. In this symposium, the self-propulsion of oil droplets of the aldehydes in a solution of the surfactant, sodium dodecyl sulfate, is reported. Furthermore, we show that droplets of two different aldehyde isomers move in an SDS aqueous solution with significantly different modes of motion. We discuss chemical reactions that can be introduced into these aldehyde droplet systems.

B2

Tomasz Szawełło

Reaction kinetics in a network model of dissolution-precipitation processes

University of Warsaw

In dissolution-precipitation processes, the complex interplay between chemical kinetics at pore surfaces, evolving pore geometry, and emerging flow pathways plays a crucial role. Achieving a delicate balance between transport and chemical reactions is essential for maintaining reaction progress. However, practical challenges often arise, such as the formation of passivation layers or the clogging of flow pathways by precipitates, which frequently disrupt this balance. This issue is particularly pertinent in mineral trapping of CO2, where chemical reactions coincide with an increase in solid volume. Consequently, identifying optimal injection rates becomes vital for enhancement of the process. To address these challenges, we propose a numerical framework attempting to simulate hydrochemical transformations of porous media.

In our simulations, we examine a medium infiltrated by a reactive fluid that triggers coupled dissolution/precipitation reactions at pore surfaces. We model the porous medium as a system of interconnected pipes (Budek et al. PRE, 86, 056318, 2012), with the diameter of each segment increasing in proportion to local reactant consumption. We incorporate details of chemical reactions to model reactive surface area evolution, including passivation processes on mineral surfaces. We validate the model against experimental results by Poonoosamy et al. (GCA, 270, 43, 2020) and observe the effects of solution supersaturation on spatial variations of chemical reactions.

We utilize our understanding of these processes to explore possible dissolution-precipitation regimes in search of optimal conditions for mineral replacement. We are particularly interested in regimes with oscillating permeability, previously observed in experiments by Singurindy et al. (WRR, 39, 1016, 2003). In these regimes, the reaction is self-limiting, with the precipitate clogging the pores. Nonetheless, reaction progress is maintained as the system continually creates new flow pathways. We analyze the physical nature of these oscillations and search for relationships between their amplitude and frequency and injection rates and solution supersaturation effects.

C1

Krzysztof Michałowski

Extending Channelflow: incorporating temperature effects in Poiseuille and Couette flows

Warsaw University of Technology

This work introduces a significant extension to the Channelflow library, enabling the incorporation of temperature effects in Poiseuille and Couette flows. The study addresses the critical need to understand the impact of thermal variations on hydrodynamic stability and turbulence onset in such flow configurations. Our approach centres around leveraging the Boussinesq approximation and aims at the development of a computational framework allowing for the efficient numerical exploration of thermally driven phenomena, bridging the gap between classical isothermal flow simulations and real-world scenarios where temperature variations play a crucial role.

C2

Mizuki Nakamura

Bifurcation analysis of the thermal convection pattern in two immiscible liquid layers with an undeformed interface

Chiba University

Rayleigh-Benard convection in two-layer systems with an undeformed horizontal interface can be mechanically or thermally coupled. The vertical flow directions of the two layers are opposite in mechanical coupling, while they are the same in thermal coupling. We investigate the bifurcation structure of these two convection patterns by changing the initial conditions in two-dimensional hydrodynamic simulation.

D1

Ilyas Djafer-Cherif

Machine learning for tracking bacterial colonies growth

Institute of Physical Chemistry, PAS

Timelapses of microbial colonies are essential to understand how micro-organisms interact and develop. However, we are then facing the problem of processing those massive amounts of data which cannot be performed by experimentalists in a reasonable amount of time. On the other hand standard computational methods pose other problems: segmentation relies on fluorescence imaging which is detrimental to the cells metabolism and standard tracking peforms poorly unless the framerate becomes very high. Here we seek to use machine learning to perform those tasks with a precision closer to human annotators. We also seek to use those insights from experimental data to develop computer models that can predict or help better our understanding the bacteria behaviour.

*E1

Michał Bogdan

Can topological data analysis predict the properties of porous metals?

Institute of Physical Chemistry, PAS

Metallic porous materials are used in wide-ranging practical applications, from lightweight metal structures to medical implants. However, their use in a given application depends on obtaining the desired mechanical properties, such as Young’s modulus and yield stress. Advances in 3D printing enable creating a wider choice of prescribed structures than ever before. However, to take advantage of this opportunity one must predict which structures will exhibit the desired mechanical properties. Instead of testing each candidate structure directly using the computationally expensive finite element method (FEM), our strategy rests on using FEM to create a database of sample structures that will be used to build predictive models based on variables defined by topological data analysis (TDA) whose results can be extrapolated to a wider space of possible structures.

*E2

Dawid Woś

Impact of physicochemical conditions on the morphology of mineral dendrites

University of Warsaw

Manganese dendrites, commonly observed as two-dimensional structures on rock surfaces, typically form when Mn-rich hydrothermal fluids infiltrate and interact with oxygenated fluids within the rock matrix. This interaction facilitates the precipitation of manganese oxide, leading to the development of complex dendritic structures. Despite their prevalence in two dimensions, three-dimensional manganese dendrites are infrequently reported, and their growth dynamics have not been extensively studied. This work addresses this gap by investigating the morphology of three-dimensional manganese dendrites under varying physical and chemical conditions. Utilizing a reaction-diffusion system framework, specifically through a particle attachment model for precipitate growth, this study derives a phase diagram that illustrates the influence of growth parameters on dendrite morphology. The dendritic structures obtained from the simulations exhibit characteristics, including fractal dimensions and volume fraction profiles, consistent with those observed in natural formations.