Scientific direction Development of key enabling technologies
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Variable Capacitor MEMS Devices for Boolean Logic Operation at High Temperature

Département Composants Silicium (LETI)

Laboratoire Gestion de l'Energie, Capteurs et Actionneurs

01-01-2021

PsD-DRT-21-0013

gael.pillonnet@cea.fr

Nouveaux paradigmes de calculs, circuits et technologies, dont le quantique (.pdf)

The objective is to design a new generation of MEMS to achieve a variable capacitance devices controlled through an electrostatic actuation. These devices will be integrated in logic gates structures to ensure reliable Boolean operations at high-temperature. This study is based on a complete breakthrough proposal compared to the classical transistor-based logic to distinghish the logic state even in a large thermal bath. The postdoctoral PhD student will propose, model and simulate electro-mechanical micro fabricated structures to validate the theoretical principle recently announced by some senior-scientists in our laboratory. The project involves other leading universities and it is an excellent opportunity for post doc' to be in advanced research program.

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Integration of piezoelectric-based power converters

Département Composants Silicium (LETI)

Laboratoire Gestion de l'Energie, Capteurs et Actionneurs

01-01-2021

PsD-DRT-21-0014

gael.pillonnet@cea.fr

Matériaux et procédés émergents pour les nanotechnologies et la microélectronique (.pdf)

The aim of the post-doctoral position is to integrate high-efficiency power converters based on resonating piezoelectric transducers. A large part of the work is to develop the integrated circuit to handle high switching frequency operation while maintaining an adiabatic energy transfer. Based on our recently published results [Pollet2019], the integration of the power stage and the control between phases paves the way of the miniaturization of the piezoelectric transducer using microelectronics process. The candidate will cover the sizing, IC design, electro-mechanical characterization and feedback control of miniaturized piezoelectric-based power converters.

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Operando photoelectron spectroscopy by HAXPES studies to elucidate the switching mechanisms in manganite valence-change memory (VCM) devices

Département des Plateformes Technologiques (LETI)

Laboratoire Analyses de Surfaces et Interfaces

01-02-2021

PsD-DRT-21-0018

orenault@cea.fr

Nano-caractérisation avancée (.pdf)

Manganite heterostructures show very promising resistive switching (RS) characteristics and multilevel resistance states. The benefits of operando HArd X-ray PhotoElectron Spectropscopy (HAXPES) for understanding the RS in VCM structures were demonstrated using synchrotron-radiation HAXPES [1]. HAXPES in operando mode (i.e biaising the VCM in situ during the photoemission), will be implemented to characterize the critical LSMO/electrode interface and unravel the switching mechanisms, correlating with the electrical characterizations performed at LMGP. The candidate will work mainly at the Platform For NanoCharacterization of CEA-Leti (PFNC, Minatec Campus), and within the very stimulating collaboration between two leading laboratories in their respective field: CNRS-LMGP (VCM devices) and CEA-Leti (characterization by advanced photoemission. [1] B. Meunier, E. Martinez, M. Burriel, O. Renault et al., J. Appl. Phys. 126, 225302 (2019).

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Mixed dimensional GaN/2D heterostructures for high quality GaN on silicon substrates

Département des Plateformes Technologiques (LETI)

Laboratoire des Matériaux pour la photonique

01-02-2021

PsD-DRT-21-0020

berangere.hyot@cea.fr

Matériaux et procédés émergents pour les nanotechnologies et la microélectronique (.pdf)

GaN, AlN, InN nitride semiconductor materials and associated alloys (III-N compounds) have received great interest for more than twenty years. These materials offer bandgap widths that extend from 0.7 to 6.1 eV and therefore allow the production of light emitters / detectors covering the entire visible spectrum as well as part of the ultra-violet (UV). In addition, the electronic properties of GaN position it as a strategic material in the field of power / high frequency electronics. However, today there are no large, low-cost III-N substrates that allow obtaining layers of very good crystalline quality. III-N heterostructures are produced on sapphire, silicon carbide or silicon substrates, resulting in layers exhibiting a high density of crystalline defects which impact the performance, reliability and reproducibility of the devices. There is therefore a very strong interest in having a substrate of large size, low cost and compatible with the microelectronics industry, for the growth and integration of GaN materials for opto and nanoelectronics. Thus, one of the major problems of GaN-on-silicon heteroepitaxy is the formation of a high density of dislocations at the interface between these two materials. Different strategies have recently been investigated to overcome this issue (use of a self-organized SiN mask, epitaxial lateral overgrowth, selective zone growth, nanowires, etc.). These methods, however, require a substantial increase in the number of steps in the device manufacturing process. This new complexity results in a drop in production yield and an increase in the final cost of the chips. The implementation of a simpler and faster technology would therefore be highly desirable. In this context, the mission consists in developing an innovative strategy based on the insertion of a compliant 2D layer at the Si/GaN interface. This layer should allow promoting the growth of good quality GaN materials.

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Privacy in embedding-based neural networks by means of homomorphic encryption

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire composants logiciels pour la Sûreté et la Sécurité des Systèmes

01-01-2020

PsD-DRT-20-0021

renaud.sirdey@cea.fr

Cybersécurité : hardware et software (.pdf)

AI presently emerges as the killer application of homomorphic encryption or FHE. Indeed, this kind of cryptography, which allows to perform general calculations directly over encrypted data, has the potential of bringing privacy-by-construction for either or both user or model data, depending on the application scenario. In the longer term, FHE may also help protect training data, unleashing new usages in training data sharing and collaborative AI model building. In this context, the present postdoctoral offer aims at investigating the practical relevance of homomorphic encryption in the case of a specific kind of neural networks, the so-called embedding-based networks, which, for intrinsic reasons, both are favorable to good homomorphic execution performances and enjoy a wide spectrum of applications. Thus, this postdoctorate will study the theoretical and practical aspects cropping up in several FHE integration scenarios and will also lead to prototyping work on a best-in-class open-source speech recognition system using an embedding-based network.

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Postdoctoral fellow in AI, real time signal processing and software for real time epilepsy prediction/forecasting for closed loop neuromodulation by focal Cooling.

Clinatec (LETI)

Clinatec (LETI)

01-03-2021

PsD-DRT-21-0023

napoleon.torres-martinez@cea.fr

Technologies pour la santé et l'environnement, dispositifs médicaux (.pdf)

To date seizure suppression stimulation technologies (electrical stimulation) are majorly based on seizure detection procedure. No study has provided sound evidence that prospective seizure prediction/forecasting can be used to trigger closed loop therapeutics for drug resistant epilepsy treatment. Our proposal is based on the existing motor brain-computer interface algorithms already in clinical use. They can be adapted to generate prediction/forecasting of seizures occurrence. Our working hypothesis is that treating during high-risk seizures periods and not during the actual seizure would require relatively minor doses of the therapeutical element. This will reduce the power consumption and open the door to fully implantable system. Decoding algorithms will be potentially redesigned to respond better to the epileptic seizures forecasting task. They will be compared to the state of the art CNN based approaches, and other approaches. Prediction/forecasting seizures algorithms will be evaluated in an epilepsy model established at Clinatec, using non-human primates, and the algorithms will be refined over time. Cooling the epileptic foci is an effective way to stop de seizure before generalization. This model allows us to test the efficacy of the algorithms in treating focal seizures. An assessment of hardware embedding design constraints would be conducted to facilitate next steps for the clinical device development. The project will benefit from a collaboration between Clinatec and DSYS/SSCE; and will be in line with upcoming activities of LETI's artificial intelligence platform.

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