Quantum friction – i.e. Friction of moving matter on the quantum vacuum – has been shown theoretically to produce a braking torque on rotating nanomaterials. At SPEC, we extended this property to interacting atoms in rotation one around the other, using atomic oscillators and a semi-classical model of vacuum. Recent work showed that the extension of this property to more realistic configurations necessitates a more complete calculation of the interaction between atoms and the electromagnetic field.



The importance of electromagnetic wave propagation is well known in the long-range Casimir-Polder case, but it also affects the near field situation, where its inclusion in calculations is necessary to interpret physically the friction phenomenon and induced energy exchanges. Moreover, a fully quantum model must be developed for the rotating pair of atoms, in order to explore rigorously some properties of mixed pairs of different atoms, and other more realistic configurations.



The master’s student will take up the first step, the effect of wave propagation. This effect will be studied within the already developed semi-classical model, by using both formal calculations and numerical programs. We will be interested in both potential energy and friction force determinations. The PhD student will complete those calculations and work towards of fully quantum model. The PhD research will be directed jointly with a specialist of quantum electrodynamic calculations.

Thermoelectricity, a materials’ capability to convert heat in to electric energy has been known to exist in liquids for many decades. Unlike in solids, this conversion process liquids take several forms including the thermogalvanic reactions between the redox ions and the electrodes, the thermodiffusion of charged species and the temperature dependent formation of electrical double layer at the electrodes. The observed values of Seebeck coefficient (Se = - DV/DT, the ratio between the induced voltage (DV) and the applied temperature difference (DT)) are generally above 1 mV/K, an order of magnitude higher than those found in the solid (semiconductor) counterpart. The first working example of a liquid-based thermoelectric (TE) generator was reported in 1986 using Ferro/ferricyanide redox salts in water.



However, due to the low electrical conductivity of liquids, its conversion efficiency was very low, preventing their use in low-temperature waste-heat recovery applications. The outlook of liquid TE generators brightened in the last decade with the development of ionic liquids (ILs). ILs are molten salts that are liquid below 100 °C. Compared to classical liquids, they exhibit many favorable features such as high boiling points, low vapour pressure, high ionic conductivity and low thermal conductivity accompanied by higher Se values. More recently, an experimental study by IJCLab and SPEC revealed that the complexation of transition metal redox couples in ionic liquids can lead to enhancing their Se coefficient by more than a three-fold from -1.6 to -5.7 mV/K, one of the highest values reported in IL-based thermoelectric cells. A clear understanding and the precise control of the speciation of metal ions therefore is a gateway to the rational design of future thermoelectrochemical technology.



Based on these recent findings, we proposes to further study the coordination chemistry of transition metal redox ions in ILs and mixtures. A long-term goal associated to the present project is to demonstrate the application potential of liquid thermoelectrochemical cells based on affordable, abundant and environmentally safe materials for thermal energy harvesting as an energy efficiency tool.

The present PhD aims at developing a quantitative theory for the transport induced by baroclinic turbulence. Idealized patches of atmosphere or oceans can be studied in isolation using state-of-the-art numerical methods. The first objective is to determine the

scaling dependence of the transport on the various control parameters of the problem. Beyond the sole determination of the magnitude

of the transport, the second part of the PhD will be concerned with the three-dimensional structure of the turbulent transport : orientation and vertical dependence of the flux vector. This work will be performed in close collaboration with the CLImate Modeling Alliance (CLIMA) and the skill of the resulting parameterization in a global ocean model will be assessed in that context.

Examples of active systems, formed of units that are able to extract energy from the environment and dissipate it to self-propel, are found everywhere in nature: flocks of birds, animal swarms, suspensions of bacteria or tissues are all biological active systems. Scientists are able to build synthetic active systems using catalytic colloidal particles or micro-robots.

Active systems have theoretically fascinating properties, a fact that drove a very intense research activity lately. Future applications may encompass the engineering self-assembling materials using active units, considered as a defining agenda in the community.



Large assemblies of active units display collective phenomena that are absent in equilibrium. One of the most ubiquitous is phase separation, where even repulsive but active particles phase separate into dense and dilute phases. In some cases, this phenomena resemble to liquid-vapor phase separation of standard fluids. Due to broken time-reversibility, however, active systems can show novel forms of phase separation, comprising a state where the liquid state comprises mesoscopic vapor bubbles (thus resembling to a boiling liquid), or active foams states, where thin liquid filaments are dispersed in the vapor.

Furthermore, in most experimental realization, active systems are `wet’, meaning that particles move in a fluid which itself can mediate interactions among particles, a feature whose consequences are so far little understood theoretically.



The main open theoretical question is how to control these novel states of matter in terms of microscopically tunable parameters. The main goal of this PhD is to fill this gap. This will require both analytical and computational work done on agent based models and continuous descriptions of active systems. If successful, the work will provide a guide for experimentalists to design novel self-assembling materials using active units. Given the ubiquity of phase separation in non-equilibrium contexts, we will further explore the relevance of these results to other out-of-equilibrium systems, such as biological tissues and granular materials.

Thermoelectric (TE) materials that are capable of converting heat into electricity have been considered as one possible solution to recover the low-grade waste-heat (from industrial waste-stream, motor engines, household electronic appliances or body-heat).



At SPHYNX, we explore thermoelectric effects in an entirely different class of materials, namely, complex fluids containing electrically charged nanoparticles that serve as both heat and electricity carriers. Unlike in solid materials, there are several inter-dependent TE effects taking place in liquids, resulting in Se values that are generally an order of magnitude larger that the semiconductor counterparts. Furthermore, these fluids are composed of Earth-abundant raw materials, making them attractive for future TE-materials that are low-cost and environmentally friendly. While the precise origins of high Seebeck coefficients in these fluids are still debated, our recent results indicate the decisive role played by the physico-chemical nature of particle-liquid interface.



The goal of the PhD project is two-fold. First, we will investigate the underlying laws of physics behind the thermoelectric potential and power generation and other associated phenomena in a special type of complex fluids, namely, ferrofluids (magnetic nanofluids). The results will be compared to their thermos-diffusive properties to be obtained through research collaboration actions. Second, the project aims to develop proof-of-concept hybrid solar-collector devices that are capable of co-generating heat and electricity.



The proposed research project is primarily experimental, involving thermos-electrical, thermal and electrochemical measurements; implementation of automated data acquisition system and analysis of the resulting data obtained. The notions of thermodynamics, fluid physics and engineering (device) physics, as well as hands-on knowledge of experimental device manipulation are needed. Basic knowledge of optics and electrochemistry is a plus. For motivated students, numerical simulations using commercial CFD software can also be envisaged.

The numerical study of the impact of human activity on the climate is extremely demanding in terms of computing resources: the climate is a complex system, including a gigantic range of scales, the management of which requires petabytes of storage, and billions of hours of computation on the current super-computers.

We are therefore in a paradoxical situation where the study of the impact of greenhouse gases on the climate contributes to increasing this impact via the maintenance of storage servers, or the construction and operation of very powerful computers.



The development of sober climate models necessarily requires new approaches to calculate only the relevant scales for impact studies. It is a question of seconding or even replacing the models currently used, which are based on an empirical description, using more than 100 adjustable parameters.



We propose to compute the dynamics of intense convective events in a context of climate change via localized singular structures, which interact according to laws derived exactly from the original fluid dynamics equations. This approach without adjustable parameters allows us to gain on two levels compared to a highly resolved simulation: on the one hand, it allows to restrict very strongly the number of scales to be simulated, with a gain of 13 orders of magnitude in memory. On the other hand, it allows to gain 7 orders of magnitude in CPU time, by adopting larger time steps.

This thesis will generate a database of intense convective events, which can be used to reduce the future cost of climate models.

The quest toward high-performance materials combining lightness and mechanical strength gave rise to a flurry of activity: desire to reduce CO2 emissions and develop fuel-efficient vehicles in the transport industries for instance. A promising solution in this context is to replace solid materials by cellular materials of well-chosen architecture, manufactured via 3D printing. These novel materials of a new type, referred to as metamaterials, actually consume little material, meet the challenges of the circular economy and can finally be compacted at the end of their life.



Significant progress has been made recently: microlattices formed by hollow metal tubes arranged periodically into octahedron cells can have densities comparable to those of aerogels, but rigidities more than 1000 times higher (e.g. microlattice materials invented at Caltech, produced by Boeing [1])! The rules that dictate stiffness for such periodic architectures are now well understood: They are fixed by Maxwell’s criterion and the connectivity of the lattice (number of struts per node). Conversely, these periodic microlattices have the drawback of being mechanically anisotropic at the macroscopic scale: they are softer, more brittle, and more prone to damage, when stressed along certain preferred directions.



Inspired by the observation of natural architectural materials (bone structure, alveolar structure of bark...) we will seek to develop disordered architectures in order to obtain a new class of metamaterials/microlattices that are ultralight, mechanically resistant (to deformation and fracture), while remaining fully isotropic. We will use artificial intelligence (AI) tools to elucidate the optimization rules to follow, without presupposing them. This PhD project is mainly numerical and theoretical, but will be conducted in close collaboration with experimentalists.



The first step will be to implement an AI algorithm to predict density, elasticity, fracture resistance and compressive strength as a function of the input architecture geometry, via tools to be defined: cost function and associated weights, gradient descent for minimization, neural network, etc... The second step will be to define optimal architectures in terms of mechanical stiffness, crack resistance and compressive strength under prescribed constraints in terms of density and architecture isotropy. Finally, the architectures obtained will be qualified through fracture and compression experiments carried out on microlattice samples obtained by additive manufacturing with different materials (polymers, composites, and even ceramics or metallic alloys).



[1] T. A. Schaedler et al., Ultralight Metallic Microlattices, Science 334, 962-965 (2011)

The energy transition is underway, involving or implying major changes in energy networks as well as in the use of materials, at the local and global scales. Statistical physics has often been used to study the stability of electrical networks, and even the coupling between networks. We propose to use it here to study the evolution of networks and associated infrastructures, from the geometrical point of view and from the point of view of the spatial distribution of materials.



Can we define the characteristics of the physical network - or of the different networks - that make the transition possible?

Can we define an optimal distribution of energy storage, and according to what criteria?

What is the interaction between stocks and flows of materials: flows needed to maintain the network and the infrastructure, stocks needed for a reliable energy storage making the system robust, and sufficiently distributed to allow a relevant and efficient distribution of materials?



Based on several decades of study of the key role played by energy consumption and material transformation in the economy, and on a thorough analysis of the existing system, in terms of empirical logistical knowledge as well as statistical physics, this thesis will establish a model of the coupled energy and material networks: one of the objectives of the model will be to evaluate the different possible, probable and/or desirable evolutions, in terms of efficiency (energy and material), stability and robustness.



This thesis, at the interface between physics and economics, will be followed by an inter-institute scientific committee (DRF/Iramis, DRF/Irfu and DES/I-Tésé).