My research spans diverse areas — from complex networks and information theory to plasma physics and computational modeling. Browse the categories below to learn about the projects and their key contributions.
Exploring dynamic networks in complex system.
Functional networks have emerged as powerful instruments to characterize the propagation of information in complex systems, with applications ranging from neuroscience to climate and air transport. In spite of their success, reliable methods for validating the resulting structures are still missing, forcing the community to resort to expert knowledge or simplified models of the system’s dynamics. We here propose the use of a real-world problem, involving the reconstruction of the structure of flights in the US air transport system from the activity of individual airports, as a way to explore the limits of such an approach. While the true connectivity is known and is, therefore, possible to provide a quantitative benchmark, this problem presents challenges commonly found in other fields, including the presence of non-stationarities and observational noise, and the limitedness of available time series. We explore the impact of elements like the specific functional metric employed, the way of detrending the time series, or the size of the reconstructed system and discuss how the conclusions here drawn could have implications for similar analyses in neuroscience.
Ocean currents exhibit strong time dependence at all scales that influences physical and biochemical dynamics. Network approaches to fluid transport permit to address explicitly how connectivity across the seascape is affected by the spatiotemporal variability of currents. However, such temporal aspect is mostly neglected, relying on a static representation of the flow. We here investigate the role of current variability on networks describing physical transport across the Mediterranean basin. We first focus on degree distributions and community structure comparing ensembles of temporal networks that explicitly resolve time dependence and their aggregated, i.e., time-averaged, counterparts. Furthermore, we explore the implications of the two approaches in a simple reaction dispersal model for a generic tracer. Our analysis evidences that aggregation induces structural network changes that cannot be easily avoided, not even introducing a pruning of the aggregated adjacency matrix. We also highlight that, depending on the time scales considered, the importance of the temporal features of the networks can vary significantly. Finally, we find that the tracer evolution obtained from a temporal dispersal kernel cannot be always approximated by aggregated adjacency matrices, in particular during transients of the dynamics.
Functional networks have become a standard tool for the analysis of complex systems, allowing the unveiling of their internal connectivity structure while only requiring the observation of the system’s constituent dynamics. To obtain reliable results, one (often overlooked) prerequisite involves the stationarity of an analyzed time series, without which spurious functional connections may emerge. Here, we show how ordinal patterns and metrics derived from them can be used to assess the effectiveness of detrending methods. We apply this approach to data representing the evolution of delays in major European and US airports, and to synthetic versions of the same, obtaining operational conclusions about how these propagate in the two systems.
Investigating complex system through the lense of the Information theory
Information theory, i.e. the mathematical analysis of information and of its processing, has become a tenet of modern science; yet, its use in real-world studies is usually hindered by its computational complexity, the lack of coherent software frameworks, and, as a consequence, low reproducibility. We here introduce infomeasure, an open-source Python package designed to provide robust tools for calculating a wide variety of information-theoretic measures, including entropies, mutual information, transfer entropy and divergences. It is designed for both discrete and continuous variables; implements state-of-the-art estimation techniques; and allows the calculation of local measure values, -values and -scores. By unifying these approaches under one consistent framework, infomeasure aims to mitigate common pitfalls, ensure reproducibility, and simplify the practical implementation of information-theoretic analyses. In this contribution, we explore the motivation and features of infomeasure; its validation, using known analytical solutions; and exemplify its utility in a case study involving the analysis of human brain time series.
Within the endeavour of understanding and tackling problems like delays and their propagation, or the optimisation of operations, air transport has customarily been studied through microscale dynamical models, describing the movements of its constituting elements according to sets of pre-hoc hypotheses and rules. The relevance of such models is nevertheless bounded by the realism and completeness of such rules. We here propose a complementary information-theoretic approach that does not rely on any pre-assumed model, but instead treats airports as information processing units. This allows to investigate the dynamics of airports in terms of information processing, whereby the relationship between the different aspects of their operations is expressed in terms of information contained, shared and transferred. Leveraging techniques from information decomposition, we describe such relationships in a large data set covering operations in Europe and US, focusing on departures and arrivals at the largest airports therein. Contrary to standard expectations, we find that departure dynamics is not a direct function of arrival one; departure delay shows a prominent dependency on the saturation of airports; and that there is a complex relationship between the way airports process information and their size, across both US and EU, with some notable exceptions. We further discuss the challenges appearing when this approach is used to assess the temporal evolution of the system, the information synergies and redundancies between different aspects of operations, and its integration with other standard models towards the evaluation of new policies and procedures.
Investigating non-equilibrium plasma properties and deposition.
The plasma-surface interaction is studied for a low temperature helium plasma jet generated at atmospheric pressure using Mueller polarimetry on an electro-optic target. The influence of the AC kHz operating frequency is examined by simultaneously obtaining images of the induced electric field and temperature of the target. The technique offers high sensitivity in the determination of the temperature variation on the level of single degrees. Simultaneously, the evolution of the electric field in the target caused by plasma-driven charge accumulation can be measured with the threshold of the order of 105 V/m. Even though a specific electro-optic crystal is used to obtain the results, they are generally applicable to dielectric targets under exposure of a plasma jet when they are of 0.5 mm thickness, have a dielectric constant greater than 4 and are at floating potential. Other techniques to examine the induced electric field in a target do not exist to the best of our knowledge, making this technique unique and necessary. The influence of the AC kHz operating frequency is important because many plasma jet designs used throughout the world operate at different frequency which changes the time between the ionization waves and hence the leftover species densities and stability of the plasma. Results for our jet show a linear operating regime between 20 and 50 kHz where the ionization waves are stable and the temperature increases linearly by 25 K. The charge deposition and induced electric fields do not increase significantly but the surface area does increase due to an extended surface propagation. Additionally, temperature mapping using a 100 μm GaAs probe of the plasma plume area has revealed a mild heat exchange causing a heating of several degrees of the helium core while the surrounding air slightly cools. This peculiarity is also observed without plasma in the gas plume.
An atmospheric pressure plasma chemical vapor deposition process designed for the site-selective deposition of organic functional materials with a sub-millimetric lateral resolution is presented in this study. Injecting methyl methacrylate vapor in plasma post-discharge allowed to synthesize plasma-polymerized methyl methacrylate (ppMMA) coatings on metallic, dielectric, and polymer substrates at close to room temperature (40°C). A circular dot, as small as 400 µm in diameter, of ppMMA is deposited and characterized by Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, and high-resolution mass spectrometry. Oligomeric species of poly-MMA up to n=18 have been detected, evidencing the particularly “soft” polymerization offered by the presented process.
An atmospheric pressure Dielectric Barrier Discharge plasma torch was used to perform selective area plasma enhanced chemical vapour deposition of four organosilicon precurors: Triethylvinylsilane (VTES), Vinyltriethoxysilane (VTEOS), Tetraethoxysilane (TEOS) and Tetraethylsilane (TES). The precursors were chosen in such a way that they differ only by the presence or absence of vinyl and/or ethoxy groups. Experimentally, major differences have been observed on the deposition speed, coating patterns and thin film composition. Precursor with vinyl group has confined deposition at the central region of plasma torch, in contrast precursor with only ethoxy groups has circular deposition in the periphery region of plasma torch, and precursors with both the vinyl and ethoxy groups has deposition at both locations. A detailed chemical analysis revealed the film composition to be silicon oxycarbide (SiOxCyH) with high content of carbon for the central region's coating whereas the peripherical coating is close to silica like (SiOx) with a minuscule carbon content. Coatings patterns and composition have been investigated in the light of gaseous flows mixing obtained from computational Fluid Dynamic (CFD) simulation. A strong correlation is evidenced for central SiOxCyH deposition of vinyl containing precursors, to the high concentration of precursor. Whereas the peripheral SiOx deposition of ethoxy containing precursors corresponds to high concentration of plasma species. Furthermore, the role of reactive plasma species on the underlying deposition mechanisms has been identified as crucial and has been purposed as the driving factor.
This paper presents a DBD system used to generate plasma at atmospheric pressure in argon environment. The discharge was produced by applying high voltage power supply (7kV) to the electrodes separated by distance of 3 mm. The lower electrode was covered by a glass plate of thickness 1.5mm which served as the dielectric barrier. Argon was supplied at a flow rate of 2liter per minute. Two types of polymer samples, PET and PP were treated for different time ranging from 5sec-1minute.Contact angle of both the samples before and after treatment were measured. In our experimental results, it has been shown that plasma treatment produces remarkable improvement in wettability. The change in surface morphology of the sample was investigated by SEM analysis. SEM images showed that roughness of the sample increases appreciably after the treatment in plasma for both the polymers. The stability of plasma modified sample was also studied by measuring the hydrophobic recovery of the sample up to several days after the treatment.
Simulating plasma gas dynamics and studying its impact in printing.
A coaxial shaped atmospheric pressure plasma torch has been used to deposit the millimetric scale plasma polymer. A detailed experiment has revealed the appearance of three different kinetic regimes with distinct coating morphology: no deposition, circular dot and circular ring formation. The ratio of precursor carrier gas flow to the plasma species carrier gas flow has been identified as crucial factor to separate the three regimes. Further experiments regarding the influence of precursor mass fraction on the dimension and deposition rates has been performed for a circular dot regime to get more insights into the coating shape, size and volume and its relation to gas flow dynamics. A side by side computational fluid dynamic simulation coupled with species transport module has been performed to understand the influence of flow dynamics on coating morphology. The appearance of recirculatory vortices in-between the nozzle and substrate and its role on confinement of precursor at specific region and mixing of plasma species to precursor has been highlighted. A good correlation in between the diameter of thus coated plasma polymer in circular dot regime and the simulated confinement zone is here reported.