We are looking for highly motivated candidates to work on our projects

PhD positions below

contact : nick.barrett@cea.fr/lucia.perezramirez@cea.fr

Title : Advanced characterization of ferroelectric domains in hafnia-based thin films

Domain, Specialties: Material physics, surface science

Keywords: Surfaces, interfaces, imaging, microscopy, PFM, LEEM, PEEM

Location: Laboratory for the Study of NanoStructures and Surface Imaging (LENSIS) at CEA Saclay, France

Type of contract: PhD offer, expected start date October 2025

Financement: PEPR Ferrofutures & travail en synergie avec le projet Horizon EuropeFerro4EdgeAI

Description

Hafnium oxide (HfO2) has reactivated significant interest since the discovery of its ferroelectric (FE) properties in 2011 [1]. Currently, it is one of the most promising materials for emerging low-power non-volatile memory and logic, essential for in-memory computing (IMC) architectures. The working principle is simple; information is stored by leveraging the characteristic switchable spontaneous polarization of a FE layer. In hafnia, this polarization has been ascribed to the presence the metastable polar orthorhombic (o-, Pca21) crystallographic phase, which can be formed via doping, mechanical or thermal stress [2]. Hafnia-based memories are particularly appealing for very high-density mass storage (>10 Tbit/in²) because they retain their ferroelectric properties at very low layer thicknesses (< 10 nm), suitable for 3D integration and ultra-low power operation.

The complex domain structures (regions of uniform polarization) in FE materials can be controlled by tailoring their electrical or mechanical boundary conditions. The size of a domain in a hafnia FE layer is of the order of 10-15 nm, which makes their study challenging, as the resolution of most electron microscopy techniques is limited to several tenths of nm. We propose to use a systematic methodology to examine them.

The first stage involves the use piezoelectric force microscopy (PFM) to locally write and subsequently image these artificially written microscopic ferroelectric domains. The resulting phase contrast images will allow us to study the phenomena of charge injection and polarization switching with varying voltage pulse parameters (amplitude, pulse duration) (Figure 1.a).

Figure 1. Schematics of (a) PFM ferroelectric domain writing and subsequent imaging to asses domain stability; (b) LEEM-PEEM imaging for surface potential characterization

In the second stage, the PhD student will use Low-Energy Electron Microscopy (LEEM) and PhotoEmission Electron Microscopy (PEEM) to characterize the surface potential (an inherent property of the material) of the domains in different polarization states and as a function of the writing voltage. This will allow to correlate the modulation of the surface potential with the polarization and/or injected charge from the PFM writing stage. We also expect to elucidate the effects of the presence (absence) of a metallic electrode above the ferroelectric layer in modulating the electrostatic properties and hence the ferroelectric response of capacitors (Figure 1.b).

The third stage of the project comprises the study of the above-mentioned mechanisms in real time during ferroelectric switching (Figure 2.a). Both switching pulse length and voltage amplitude are expected to determine the switching speed (latency) (Figure 2.b). This requires the use of advanced time-resolved spectromicroscopy techniques, often relying on the use of synchrotron photon sources for high intensity and resolution. Time-resolved imaging using photoemission spectroscopy (XPS) with a dedicated detection system will allow full characterization of domain switch dynamics under real operating conditions (see [3]).

Besides, by integrating the obtained core-level spectra in a specific region of interest (ROI) we will be able to correlate the ferroelectric properties and domain switching with the oxygen vacancy point defect concentration deduced from the hafnium reduced fraction (Figure 2.c) (see [4,5]).

Skills: Previous experience/skills on electron spectroscopy and/or image processing is not mandatory but highly desired. Strong grounding in solid state physics is essential.

How to apply: Candidates should send a CV, cover letter and contact details for two referees to the e-mail addresses in the contact information.

Links: www.lensislab.com
           iramis.cea.fr/spec/lensis

https://www.pepr-electronique.fr/fer/

Contact

Nick BARRETT
Phone: 01 69 08 32 72
Email: nick.barrett@cea.fr

Lucia PEREZ RAMIREZ
Phone: 01 69 08 47 27
Email: lucia.perezramirez@cea.fr

References
[1] Böscke, T. S., et al (2011). Ferroelectricity in hafnium oxide thin films. Appl Phys Lett 99(10).
[2] Mikolajick, T., Schroeder, U., & Park, M. H. (2021). Special topic on ferroelectricity in hafnium oxide: Materials and devices. devices. Appl Phys Lett, 118(18).
[3] Rault, J. E., et al (2013). Time-resolved photoemission spectroscopy on a metal/ferroelectric heterostructure. Phys Rev B Condens Matter, 88(15).
[4] Barrett, N., et al (2024). Oxygen vacancy engineering in Si-doped, HfO2 ferroelectric capacitors using Ti oxygen scavenging layers. Appl Phys Lett, 125(4).
[5] Hamouda, W., et al (2020). Physical chemistry of the TiN/Hf0. 5Zr0. 5O2 interface. J Appl Phys, 127(6).

Summary:

Ferroelectric random access memories (FeRAM) based on hafnium zirconium oxide (HZO) are intrinsically ultra-low power thanks to the voltage switching mechanism, the scaling potential of HZO to below 10 nm and full CMOS compatibility. In addition, they demonstrate low latency necessary for a wide variety of edge logic and memory applications. Understanding the underlying mechanisms and kinetics of ferroelectric domains switching is essential for intelligent FeRAM design and optimal performance.

This thesis focuses on the comprehensive characterization of ferroelectric (FE) domains in ultra-thin HZO films. The student will use several surface imaging techniques (piezoelectric force microscopy, PFM, low energy electron microscopy, LEEM, and x-ray photoemission electron microscopy, PEEM) combined with advanced operando characterization methods (time-resolved detection coupled with synchrotron radiation) for this purpose. This project will mark an important progress on the fundamental research on the polarization switching mechanisms of ultra-thin hafnia-based FE layer, elucidating the specific effects of the metal electrode/FE layer interface in the electrostatic behaviour of the studied capacitors. It will ultimately allow a significant breakthrough on the industrial development of ferroelectric emerging memories, essential for large-scale artificial intelligence (AI) applications.

Résumé :

Les mémoires ferroélectriques à accès aléatoire (FeRAM en anglais) à base d'oxyde d’hafnium et de zirconium (HZO) sont intrinsèquement ultra-faibles en consommation grâce au mécanisme de changement de tension, au potentiel de mise à l'échelle du HZO en dessous de 10 nm et à la compatibilité CMOS complète. De plus, elles présentent une faible latence nécessaire à une grande variété d'applications de logique et de mémoire. La compréhension des mécanismes sous-jacents et de la cinétique du ‘switching’ des domaines ferroélectriques est essentielle pour une conception intelligente des FeRAMs avec des performances optimales.

Cette thèse porte sur la caractérisation complète des domaines ferroélectriques (FE) dans des films HZO ultra-minces. L'étudiant utilisera plusieurs techniques d'imagerie de surface (microscopie à force piézoélectrique, PFM, microscopie électronique à basse énergie, LEEM, et microscopie électronique à photoémission de rayons X, PEEM) combinées à des méthodes avancées de caractérisation operando (détection résolue dans le temps couplée au rayonnement synchrotron). Ce projet marquera une avancée importante dans la recherche fondamentale des mécanismes de basculement de polarisation des couches FE ultra-minces à base d'hafnium, en élucidant les effets spécifiques de l'interface électrode métallique/couche FE dans le comportement électrostatique des condensateurs étudiés. Il permettra à terme une avancée significative dans le développement industriel des mémoires émergentes ferroélectriques, essentielles pour les applications d'intelligence artificielle (IA) à grande échelle.