This PhD project, conducted on the MAPP platform (CEA-Metz), focuses on the development of additive manufacturing (3D/4D) processes for the integration of smart materials. The aim is to overcome the limitations of traditional planar electronic architectures (PCBs, wafers) integration by enabling the direct-to-shape printing of electronic functions within 3D parts performed by Fused Deposition Modeling...

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The increasing complexity of heterogeneous networks (satellite, 5G, IoT, TSN) requires an evolution in network management. Intent-Based Networking (IBN), while advanced, still faces challenges in unambiguously translating high-level intentions into technical configurations. This work proposes to overcome this limitation by leveraging Large Language Models (LLMs) as a cognitive interface for complete and reliable automation. This...

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The terahertz (THz) range (0.1–10 THz) is increasingly exploited for imaging and spectroscopy (e.g. security scanning, medical diagnostics, non-destructive testing) because many materials are transparent to THz radiation and have unique spectral signatures. However, existing sources struggle to offer both high power and wide tunability: electronic sources (diodes, QCLs) deliver milliwatts but over narrow bands,...

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Video Anomaly Detection (VAD) aims to automatically identify unusual events in video that deviate from normal patterns. Existing methods often rely on One-Class or Weakly Supervised learning: the former uses only normal data for training, while the latter leverages video-level labels. Recent advances in Vision-Language Models (VLMs) and Large Language Models (LLMs) have improved both...

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The security assessment of post-quantum cryptography, from the perspective of physical attacks, has been extensively studied in the literature, particularly with regard to the ML-KEM and ML-DSA standards, which are based on Euclidean lattices. Furthermore, in March 2025, the HQC scheme, based on error-correcting codes, was standardized as an alternative key encapsulation mechanism to ML-KEM....

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The aim of this PhD thesis is to develop new clinical assessment methods using surface haptics technologies, developed at CEA List, and machine learning algorithms for testing and monitoring tactile-motor integration. In particular, the thesis will investigate and validate the development of a multimodal analytics pipeline that converts surface haptics signals and dexterity exercises inputs...

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Block copolymers (BCP) are an industrial technology in full expansion, offering promising perspectives for material nanostructuring. These polymers, composed of chemically distinct block chains, self-assemble to form ordered structures at the nanometric scale. However, their current use is limited to specific nanostructuring per product (1 product = 1 nanostructuring), thus restricting their application potential. This...

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The proposed PhD work lies within the exploration of new supercapacitor and hybrid energy storage technologies, aiming to combine miniaturization, high power density, and CMOS process compatibility. The hosting laboratory (LTEI/DCOS/LCRE) has recognized expertise in thin-film integration and dielectric material engineering, offering unique opportunities to investigate ferroelectric (FE) and antiferroelectric (AFE) behaviors in doped hafnium...

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Complementary Field Effect Transistors (CFETs) represent a new generation of vertically stacked CMOS devices, offering a promising path to continue transistor miniaturization and to meet the requirements of high-performance computing. The objective of this PhD work is to study and optimize the strain engineering of the transistor channel in order to enhance carrier mobility and...

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The performance of micro-LEDs (µLEDs) is crucial for micro-displays, a field of expertise at the LITE laboratory within CEA-LETI. However, simulating these components is complex and computationally expensive due to the incoherent nature of light sources and the involved geometries. This limits the ability to effectively explore multi-parameter design spaces. This thesis proposes to develop...

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The laboratory, reknown for its expertise in high-resolution and high-precision magnetic measurements, has been developing and providing for several decades successive generations of optically pumped helium-4 magnetometers. These instruments serve as reference sensors aboard the ESA Swarm mission satellites launched in late 2013, and will also equip the forthcoming NanoMagSat mission, scheduled to launch from...

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Dispersion engineering (DE) refers to the control of how electromagnetic waves propagate in a structure by shaping the relationship between frequency and phase velocity. Using artificially engineered materials and surfaces, this relationship can be tailored to achieve non-conventional propagation behaviors, enabling precise control of dispersive effects in the system. In antenna design, dispersion engineering can...

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This PhD aims to design analog liquid neural networks for generative edge intelligence. Current neuromorphic architectures, although more efficient through in-memory computing, remain limited by their extreme parameter density and interconnection complexity, making their hardware implementation costly and difficult to scale. The Liquid Neural Networks (LNN), introduced by MIT at the algorithmic level, represent a...

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Quantum information technologies offers several promises in domains such as computation or secured communications. Because of their robustness against decoherence, photonic qubits are particularly interesting for quantum communications applications, even at room temperature. They also offers an alternative to other qubits technologies for quantum computing. For the large-scale deployment of those applications, it is necessary...

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The security of numerical systems relies on cryptographic chains of trust starting from the hardware up to end-user applications. The root of chain of trust is called a “root of trust” and takes the form a dedicated Integrated Circuit (IC), which stores and manipulates secrets. Thanks to countermeasures, those secrets are kept safe from extraction...

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The manufacturing of electronic equipment, and more specifically Printed Circuit Boards (PCBs), represents a significant share of the environmental impact of digital technologies, which must be minimized. Within a circular economy approach, the development of monitoring and diagnostic tools for assessing the health status of these boards could feed into the product’s digital passport and...

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Thanks to strong collaborations between teams from several research institutes and the cleanroom facilities at CEA-LETI, Grenoble has been a pioneer in the development of spin qubit devices as a platform for quantum computing. The lifetime of these spin qubits is highly sensitive to fluctuations in the qubitapos;s electrical environment, known as charge noise. Charge...

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This PhD research focuses on the integrated co-optimization of materials, fabrication processes and device architectures to enable high-performance RF transistors on advanced nanometer-scale technologies. The work aims to understand and improve key RF figures of merit—such as transit frequency, maximum oscillation frequency, noise behaviour and linearity—by establishing clear links between material choices, process innovations and...

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The blood-brain barrier (BBB) protects the brain by controlling exchanges between the blood and nervous tissue. However, current models struggle to accurately reproduce its complexity. This thesis aims at developing and evaluating a microfluidic chip of BBB model incorporating a real-time monitoring system that combines simultaneous optical and electrical measurements. The device will enable the...

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Infertility is a growing problem in all developed countries. The standard methods for the diagnostic of male infertility examine the concentration, motility and morphological anomalies of individual sperm cells. However, 40% of male infertility cases remain unexplained with the standard diagnostic tools. In this thesis, we will explore the possibility to determine the male infertility...

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The development of 4D-STEM (Scanning Transmission Electron Microscopy) has profoundly transformed transmission electron microscopy (TEM) by enabling the simultaneous recording of spatial (2D) and diffraction (2D) information at each probe position. These so-called “4D” datasets make it possible to extract a wide variety of virtual contrasts (bright-field imaging, annular dark-field imaging, ptychography, strain and orientation...

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Cortisol plays a central role in regulating the circadian cycle and in many essential physiological processes such as energy metabolism and immune response. Conventional monitoring of cortisol relies on single blood or saliva samples, which do not accurately reflect the temporal dynamics of its secretion. It is therefore necessary to develop innovative approaches that enable...

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Recently, deep learning has been successfully applied in numerous domains and is increasingly being integrated into healthcare and clinical research. The ability to combine diverse data sources such as genomics and imaging enhances medical decision-making. Access to large and heterogeneous datasets is essential for improving model quality and predictive accuracy. Federated learning is currently developed...

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Fully Homomorphic Encryption (FHE) is a technology that allows computations to be performed directly on encrypted data, meaning that we can process information without ever knowing its actual content. For example, it could enable online searches where the server never sees what you are looking for, or AI inference tasks on private data that remain...

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Retinal tears then detachment, a serious eye condition (20–25 cases per 100,000 in France each year), requires urgent surgery. Current treatments involve removing the vitreous, using gas as a tamponade agent, and sealing tears with laser. However, this method presents drawbacks, including patient restrictions (e.g., prolonged lying down) and complications (e.g., cataracts). Injectable hydrogels are...

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Phase contrast microscopy and fluorescence microscopy are the two pillars of modern biological imaging. Phase contrast reveals the morphology of the sample, while fluorescent labeling provides specificity to the process of interest. In both cases, the image is the average value of the measured signal. In this thesis, we propose to focus not on the...

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Clouds are constituted of servers interconnected via the Internet, on which systems can be implemented, making use of applications and databases deployed on the servers. Cloud-based computing is gaining in popularity, and that includes the context of critical systems. As a result, it is useful to define formal frameworks for reasoning about cloud-based systems. One...

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The culture of adherent is a promising approach for various bioproduction applications, such as drug manufacturing and delivery, regenerative medicine, and tracking of cellular differentiation. However, the analysis of single cell morphology and behavior without affecting the substrate integrity remains a major challenge. Lens-free holographic imaging is emerging as a promising solution for real-time, non-invasive...

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Biopharmaceutical production is booming and consists of using cells to produce molecules of interest. To achieve this, monitoring the culture and the state of the cells is essential. Quantitative phase imaging by holography is a label-free optical method that has already demonstrated its ability to measure the concentration and viability of cultured cells. However, implementing...

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Power converters are essential in numerous applications such as industry, photovoltaic systems, electric vehicles, and data centers. Their conventional maintenance is often based on fixed schedules, leading to premature replacement of components and significant electronic waste. This PhD project aims to develop a novel non-invasive and low-cost ultrasound-based monitoring approach to assess the state of...

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This work is part of the development of brain-machine interfaces dedicated to restoring mobility for patients with severe chronic motor disabilities. The proposed technological solutions are based on decoding brain signals acquired at the motor cortex level in order to extract movement intentions. These intentions serve as commands for motor compensation systems. Our team is...

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The inspection of wafer surfaces is critical in microelectronics to detect defects affecting chip quality. Traditional methods, based on physical models, are limited in accuracy and computational efficiency. This thesis proposes using artificial intelligence (AI) to characterize and model wafer topography, leveraging optical interferometry techniques and advanced AI models. The goal is to develop AI...

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The innovations that gave rise to industrial robots date back to the sixties and seventies. They have enabled a massive deployment of industrial robots that transformed factory floors, at least in industrial sectors such as car manufacturing and other mass production lines. However, such robots do not fit the requirements of other interesting applications that...

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To increase the performance of quantum computers, three-dimensional (3D) integration is now the key! Using technologies such as flip-chip bonding, multi-layer wiring or even through-silicon vias (TSV), 3D integration offers solutions to increase the number of qubits on a processor, reduce signal loss and cross-talk and even improve thermal management. All of these aspects are...

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This PhD proposal will develop a container orchestration scheme for real-time applications, deployed on a continuum of heterogeneous computing resources in the embedded-edge-cloud space, with a specific focus on applications that require real-time guarantees. Applications, from autonomous vehicles, environment monitoring, or industrial automation, applications traditionally require high predictability with real-time guarantees, but they increasingly ask...

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Critical systems must simultaneously meet the requirements of both Safety (preventing unintentional failures that could lead to damage) and Security (protecting against malicious attacks). Traditionally, these two areas are treated separately, whereas they are interdependent: An attack (Security) can trigger a failure (Safety), and a functional flaw can be exploited as an attack vector. MBSE...

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Thermal infrared imaging (wavelengths 8-14 µm) is a growing field, particularly in industry, transportation, and environment. It relies on a detection technology, microbolometers, for which CEA-Leti is at the forefront of the global state of the art. Integrating advanced optical functions directly onto the detectors is a very promising approach for improving performance, compactness, and...

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The goal of this PhD is to explore the potential of machine learning (ML) tools for simultaneous localization and mapping (SLAM) applications, while leveraging multipath radio signals between cooperative wireless devices. The idea is to identify characteristic features of the propagation channels observed over multiple radio links, so as to jointly determine the relative positions...

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Free-Space Optical Communications (FSO) rely on transmitting data via light between two distant points, eliminating the need for fibers or cables. This approach is particularly valuable when wired connections are impractical or prohibitively expensive. However, these links are highly susceptible to atmospheric conditions—fog, rain, dust, and thermal turbulence—which attenuate or distort the light beam, significantly...

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Recent advances in electric motors and associated power electronics have led to a significant increase in power density requirements. This increase in power density means smaller heat exchange surfaces, which amplifies the challenges associated with dissipating the heat generated by power electronics components during operation. In fact, the lack of adequate heat dissipation causes electronic...

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In the race towards building a quantum computer, there is a deep interest in fabricating devices based on the robust and scalable silicon FD-SOI technology. One example is the Josephson Field Effect Transistor (JoFET) whose operability relies on the high transparency of the interface between the superconducting source/drain regions and the semiconducting channel. Such transparency...

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This work aims to develop Advanced ultrathin cunductive layers (lt;10nm) by ALD (Atomic Layer Deposition)for électrodes use(resistivity lt;mOhm)of high density ionic capacitors fabricated on 3D complex structures (high aspect ratio 1:100). The preliminary effort will be focused on the deep analysis and the impact of interface formation between ionic layers and subseqquent electrode layers. One...

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This thesis falls within the field of cooled infrared detectors. The CEA-LETI-MINATEC Infrared Laboratory specializes in the design and manufacture of infrared camera prototypes used in defense, astronomy, environmental monitoring, and satellite meteorology. In this context of high-performance imaging, it is crucial to ensure optimal detector quality. However, manufacturing processes can introduce defects that can...

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As part of the FAMES project and the European ChipACT initiative, which aim to ensure France’s and Europe’s sovereignty and competitiveness in the field of electronic nano-components, CEA-LETI has launched the design of new FD-SOI chips. Among the various modules being developed, the fabrication of electrical contacts is one of the most critical modules in...

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The growing demand for III-V semiconductors in high-efficiency photovoltaics, quantum photonics, and advanced imaging technologies requires innovative and cost-effective fabrication methods. This PhD project focuses on developing plasma etching processes for In-based III-V semiconductors to produce high aspect ratio (HAR) structures on large wafers from 100 to 300 mm. The research addresses two key challenges:...

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Ultra-high-dose-rate FLASH radiotherapy is one of the most promising innovations of the last decade in radiation oncology. It has the potential to eradicate radioresistant tumours and reduce unwanted side effects, that in turn increases cure rates and improves patient quality of life. However, dosimetry infrastructure is lagging behind this clinical and technological advance, with current...

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Advanced nanoelectronics and quantum devices rely on ultrathin oxides and engineered interfaces whose chemical composition, stoichiometry and thickness must be controlled with sub-nanometer precision. LETI is installing the first 300-mm multi-energy XPS–HAXPES tool with angle-resolved capability, enabling quasi in situ chemical metrology from deposition to characterization. This PhD will develop quantitative, multi-energy and angle-resolved XPS/HAXPES...

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Silicon technologies occupy a central position in today’s digital landscape, both for the fabrication of semiconductor devices and for the development of advanced sensors. In 2006, the discovery of superconductivity in silicon heavily doped with boron opened a new field of research. Since then, several laboratories, including CEA, have been investigating its electronic properties and...

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Through the Carnot SpectroRF exploratory project, CEA Leti is involved in radio-frequency sensor systems based on atomic optical spectroscopy. The idea behind the development is that these systems offer exceptional detection performance. These include high sensitivity´ (~nV.cm-1.Hz-0.5), very wide bandwidths (MHz- THz), wavelength-independent size (~cm) and no coupling with the environment. These advantages surpass the...

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Switches based on phase change materials (PCM) demonstrate excellent RF performance (FOM lt;10fs) and can be co-integrated into the BEOL of CMOS processes. However, their reliability is still very little studied today. Failure modes such as heater breakage, segregation, or the appearance of cavities in the material are shown during endurance tests, but the mechanisms...

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This PhD thesis offers a unique opportunity to work at the crossroads of electromagnetics, numerical simulations, and artificial intelligence, contributing to the development of next-generation intelligent sensing and recognition systems. The intern will join the Antenna amp; Propagation Laboratory at CEA-LETI, Grenoble (France), a world-class research environment equipped with state-of-the-art tools for propagation channel characterization...

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The characterization of the security of embedded systems in quot;black boxquot; or quot;gray boxquot; against Side-Channel attacks often requires a preparatory phase of Reverse-Engineering, which can be particularly time-consuming, especially on a complex System-on-Chip that can be found in smartphones or in the automotive industry. This phase can, for example, consist of detecting a cryptographic...

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Embedded systems are increasingly used in critical infrastructures (e.g., energy production networks) and are therefore prime targets for malicious actors. The use of intrusion detection systems (IDS) that dynamically analyze the systemapos;s state is becoming necessary to detect an attack before its impacts become harmful. The IDS that interest us are based on machine learning...

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The integration of renewable energy sources (RES) has become an important issue for power converters. The increasing number of these converters and their average utilization rate allows for a rethink of energy exchange management at the system level. This leads us to the concept of an energy hub, which can interface, for example, a photovoltaic...

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The application of gamma spectrometry to radiological characterization in nuclear facility decommissioning, requires the development of specific algorithms for automatic gamma spectrum analysis. In particular, the classification of concrete waste according to its level of contamination, is a crucial issue for controlling decommissioning costs. Within CEA/List, LNHB, in collaboration with CEA/DEDIP, has been involved for...

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Scene understanding is a major challenge in computer vision, with recent approaches dominated by transformers (ViT, LLM, MLLM), which offer high performance but at a significant computational cost. This thesis proposes an innovative alternative combining lightweight convolutional neural networks (Lightweight CNN) and causal graph neural networks (Causal GNN) for efficient spatio-temporal analysis while optimizing computational...

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Wireless power transfer (WPT) technologies are rapidly expanding, particularly for wireless charging of everyday electronic devices and for powering wireless communicating sensor nodes. However, their transmission ranges remain limited, and the high operating frequencies typically used prevent energy transfer in the presence of, or through, conductive media (such as metallic barriers or seawater). This constraint...

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This PhD topic offers a unique opportunity to enhance your skills in GaN power devices and develop cutting-edge architectures. You’ll work alongside a multidisciplinary team specializing in material engineering, characterization, device simulation, and electrical measurements. If you’re eager to innovate, expand your knowledge, and tackle state-of-the-art challenges, this position is a valuable asset to your...

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Illicit uses of images dramatically rise with deepfake content manipulation or unauthorized access. Securing images from their source i.e., at the image sensor level, is key to address the challenges of this field of cybersecurity. The quot;trusted imagersquot; addresses the need to ensure image security, authentication, and encryption starting at the point of acquisition. Building...

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For next-generation microelectronics, Area Selective Deposition (ASD)is a promising approach to simplify integration schemes for the most advanced technology nodes. These ASD approaches need to be adapted according to a trio comprising the material to be deposited, the growth surface, and the inhibited surface. This PhD focuses on the area selective deposition of oxides (such...

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Direct dies-to-wafer bonding has become, in recent years, a major development axis in microelectronics and at the heart of many LETI projects, both in silicon photonics and for 3D applications involving hybrid bonding. Due to their small size, die bonding allows the study of direct bonding edge effects and the implementation of new direct bonding...

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Discover a unique phd opportunity where you will dive into the heart of innovation in memory technologies. You will develop strong expertise in areas such as electrical characterization and the understanding of degradation phenomena in chalcogenide-based memories. By joining our multidisciplinary teams, you will play a key role in studying and improving the endurance of...

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