Magnetism, spin texture and in-gap states: Atomic specialization at the surface of oxygen-deficient SrTiO3_3

Motivated by recent spin- and angular-resolved photoemission (SARPES) measurements performed on the two-dimensional electronic states confined near the (001) surface of SrTiO$_3$ in the presence of oxygen vacancies, we explore their spin structure by means of ab initio density functional theory (DFT) calculations of slabs. Relativistic nonmagnetic DFT calculations display Rashba-like spin winding with a splitting of a few meV and when surface magnetism on the Ti ions is in- cluded, bands become spin-split with an energy difference ~100 meV at the $\Gamma$ point, consistent with SARPES findings. While magnetism tends to suppress the effects of the relativistic Rashba interaction, signatures of it are still clearly visible in terms of complex spin textures. Furthermore, we observe an atomic specialization phenomenon, namely, two types of electronic contributions: one is from Ti atoms neighboring the oxygen vacancies that acquire rather large magnetic moments and mostly create in-gap states; another comes from the partly polarized t$_{2g}$ itinerant electrons of Ti atoms lying further away from the oxygen vacancy, which form the two-dimensional electron system and are responsible for the Rashba spin winding and the spin splitting at the Fermi surface.Comment: 6 pages, 4 figures, for Suppl. Mat. please contact first autho

Hétérostructures supraconductrices et isolants topologiques

The thesis is focused on the theoretical study of the electronic properties at the surface of the transition metal oxide STO. This material is the cornerstone of oxide electronics, an emerging research area that has the goal of investigating transition metal oxides as post-silicon candidates for a future emerging new electronics. STO is in itself an astounding system; in its purest chemical composition is a good ban-insulator with a wide bandgap. Nevertheless, upon doing it with tiny amounts of other elements it transforms itself in a metal with high electron mobility. Even more remarkably, at the lowest temperatures, typically below 300mK, it goes superconductor. And adding to these properties, strain induces also ferroelectricity in this material. Over the last years, STO has also grabbed attention because of its ability of hosting two-dimensional electron gas (2DEGs) when it is interfaced with some polar oxides. Such 2DEGs exhibit fascinating properties, the most conspicuous is the coexistence of magnetism and superconductivity.The surface of STO can host 2DEGs too, without need of interfacing it to other materials; in this case the electrons participating in transport are generated by oxygen vacancies created at the surface. This is remarkable observation, as it affords a simpler structure where the 2DEGs properties can be studied. In spite of the accumulated knowledge, still a better fundamental comprehension is required of the electronic structure of the quantum wells at the surfaces oriented along the 111 direction, for which the perovskite structure is reminiscent of the celebrated honeycomb-like structure of graphene. Contrary to the latter, in which electrons are in s- and p- states, 111 quantum wells in STO would host electrons in d-bands. Higher electronic correlations are then expected, that may bring new fascinating physics.The outline of this Thesis has two main branches: first, it studies the 111-oriented STO bilayer, formed by just two unit cells; secondly it analyzes the quantum wells generated by Oxygen vacancies at the 111-surface of STO. Both subjects are approached using tight-binding models in which the Hamiltonian incorporates different terms related to on-site energies, hopping interactions or spin-orbit coupling. From these calculations, I have carried out an exhaustive analysis of the orbital character and parity properties of valence and conduction bands, as well as edge states in the 111 bilayer. Tight-binding calculations have also shed light on the orbital character, space location and extension and energy of electronic states generated by oxygen vacancies at the 001 surface of STO.La thèse porte sur l'étude théorique des propriétés électroniques à la surface de l’oxyde de métal de transition SrTiO3. Ce matériau est la pierre angulaire de l'électronique des oxydes, un nouveau domaine de recherche qui a pour but d'enquêter sur les oxydes de métaux de transition en tant que candidats post-silicium pour une émergence future de nouveaux composants électroniques. Le SrTiO3 est en soi un système étonnant : dans sa plus pure composition chimique, c’est un bon isolant avec une large bande interdite. Cependant, en le dopant avec de petites quantités d'autres éléments, il se transforme en un métal à haute mobilité d'électrons. Le SrTiO3 a également saisi l'attention en raison de sa capacité à accueillir des gaz d'électrons bidimensionnels (2DEGs) quand il est interfacé avec certains oxydes polaires. Ces 2DEGs présentent des propriétés fascinantes, la plus visible étant la coexistence du magnétisme et de la supraconductivité.La surface du SrTiO3 peut également accueillir des 2DEGs, sans avoir besoin de s'interfacer avec d'autres matériaux ; dans ce cas, les électrons participant aux transports sont générés par des lacunes d'oxygène créées à la surface. Cette observation est remarquable, car le SrTiO3 offre une structure simple où les propriétés des 2DEGs peuvent être étudiées.Cette thèse s’articule autour des deux axes. Tout d'abord, elle étudie la bicouche STO orientée 111, formée de seulement deux cellules unitaires. Deuxièmement, elle analyse les puits quantiques générés par les postes vacants de l'oxygène à la surface 111 du STO. Les deux sujets sont abordés en utilisant des modèles de liaison forte, dans lesquels le Hamiltonien incorpore différents termes liés aux énergies sur place, aux interactions de saut et au couplage spin-orbite. A partir de ces calculs, j’ai réalisé une analyse exhaustive des propriétés, du caractère et de la parité des orbitaux des bandes de valence et de conduction, ainsi que des états de bord dans la bicouche 111

Superconducting heterostructures and topological insulators

La thèse porte sur l'étude théorique des propriétés électroniques à la surface de l’oxyde de métal de transition SrTiO3. Ce matériau est la pierre angulaire de l'électronique des oxydes, un nouveau domaine de recherche qui a pour but d'enquêter sur les oxydes de métaux de transition en tant que candidats post-silicium pour une émergence future de nouveaux composants électroniques. Le SrTiO3 est en soi un système étonnant : dans sa plus pure composition chimique, c’est un bon isolant avec une large bande interdite. Cependant, en le dopant avec de petites quantités d'autres éléments, il se transforme en un métal à haute mobilité d'électrons. Le SrTiO3 a également saisi l'attention en raison de sa capacité à accueillir des gaz d'électrons bidimensionnels (2DEGs) quand il est interfacé avec certains oxydes polaires. Ces 2DEGs présentent des propriétés fascinantes, la plus visible étant la coexistence du magnétisme et de la supraconductivité.La surface du SrTiO3 peut également accueillir des 2DEGs, sans avoir besoin de s'interfacer avec d'autres matériaux ; dans ce cas, les électrons participant aux transports sont générés par des lacunes d'oxygène créées à la surface. Cette observation est remarquable, car le SrTiO3 offre une structure simple où les propriétés des 2DEGs peuvent être étudiées.Cette thèse s’articule autour des deux axes. Tout d'abord, elle étudie la bicouche STO orientée 111, formée de seulement deux cellules unitaires. Deuxièmement, elle analyse les puits quantiques générés par les postes vacants de l'oxygène à la surface 111 du STO. Les deux sujets sont abordés en utilisant des modèles de liaison forte, dans lesquels le Hamiltonien incorpore différents termes liés aux énergies sur place, aux interactions de saut et au couplage spin-orbite. A partir de ces calculs, j’ai réalisé une analyse exhaustive des propriétés, du caractère et de la parité des orbitaux des bandes de valence et de conduction, ainsi que des états de bord dans la bicouche 111.The thesis is focused on the theoretical study of the electronic properties at the surface of the transition metal oxide STO. This material is the cornerstone of oxide electronics, an emerging research area that has the goal of investigating transition metal oxides as post-silicon candidates for a future emerging new electronics. STO is in itself an astounding system; in its purest chemical composition is a good ban-insulator with a wide bandgap. Nevertheless, upon doing it with tiny amounts of other elements it transforms itself in a metal with high electron mobility. Even more remarkably, at the lowest temperatures, typically below 300mK, it goes superconductor. And adding to these properties, strain induces also ferroelectricity in this material. Over the last years, STO has also grabbed attention because of its ability of hosting two-dimensional electron gas (2DEGs) when it is interfaced with some polar oxides. Such 2DEGs exhibit fascinating properties, the most conspicuous is the coexistence of magnetism and superconductivity.The surface of STO can host 2DEGs too, without need of interfacing it to other materials; in this case the electrons participating in transport are generated by oxygen vacancies created at the surface. This is remarkable observation, as it affords a simpler structure where the 2DEGs properties can be studied. In spite of the accumulated knowledge, still a better fundamental comprehension is required of the electronic structure of the quantum wells at the surfaces oriented along the 111 direction, for which the perovskite structure is reminiscent of the celebrated honeycomb-like structure of graphene. Contrary to the latter, in which electrons are in s- and p- states, 111 quantum wells in STO would host electrons in d-bands. Higher electronic correlations are then expected, that may bring new fascinating physics.The outline of this Thesis has two main branches: first, it studies the 111-oriented STO bilayer, formed by just two unit cells; secondly it analyzes the quantum wells generated by Oxygen vacancies at the 111-surface of STO. Both subjects are approached using tight-binding models in which the Hamiltonian incorporates different terms related to on-site energies, hopping interactions or spin-orbit coupling. From these calculations, I have carried out an exhaustive analysis of the orbital character and parity properties of valence and conduction bands, as well as edge states in the 111 bilayer. Tight-binding calculations have also shed light on the orbital character, space location and extension and energy of electronic states generated by oxygen vacancies at the 001 surface of STO

Multimodal Prediction of Five-Year Breast Cancer Recurrence in Women Who Receive Neoadjuvant Chemotherapy

SIMPLE SUMMARY: An important clinical issue to consider when selecting neoadjuvant chemotherapy treatment for breast cancer is the likelihood of cancer recurrence. Accurately predicting the future outcome of the patient based on data available prior to treatment initiation could impact the treatment selection. We study a cohort of 1738 patients and explore the contribution of clinical history, immunohistochemical markers, and multiparametric magnetic resonance imaging to the prediction of post-treatment cancer recurrence. We analyzed this multimodal data using classical machine learning, image processing, and deep learning to increase the set of discriminating features. Our results demonstrate the ability to predict recurrence using each modality alone, and the possible improvement achieved by combining the modalities. We show that the models are especially accurate for differentiating specific groups of young women with poor prognoses. These methods were also used on a different dataset of 193 patients in an international challenge, where they won second place. ABSTRACT: In current clinical practice, it is difficult to predict whether a patient receiving neoadjuvant chemotherapy (NAC) for breast cancer is likely to encounter recurrence after treatment and have the cancer recur locally in the breast or in other areas of the body. We explore the use of clinical history, immunohistochemical markers, and multiparametric magnetic resonance imaging (DCE, ADC, Dixon) to predict the risk of post-treatment recurrence within five years. We performed a retrospective study on a cohort of 1738 patients from Institut Curie and analyzed the data using classical machine learning, image processing, and deep learning. Our results demonstrate the ability to predict recurrence prior to NAC treatment initiation using each modality alone, and the possible improvement achieved by combining the modalities. When evaluated on holdout data, the multimodal model achieved an AUC of 0.75 (CI: 0.70, 0.80) and 0.57 specificity at 0.90 sensitivity. We then stratified the data based on known prognostic biomarkers. We found that our models can provide accurate recurrence predictions (AUC > 0.89) for specific groups of women under 50 years old with poor prognoses. A version of our method won second place at the BMMR2 Challenge, with a very small margin from being first, and was a standout from the other challenge entries

A framework for validating AI in precision medicine: considerations from the European ITFoC consortium

International audienceBackground: Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular-omics data from clinical data warehouses and biobanks. Methods: The European "ITFoC (Information Technology for the Future Of Cancer)" consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology. Results: This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the "ITFoC Challenge". This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets. Conclusions: The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care