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We report on spin transport in state-of-the-art epitaxial monolayer graphene based 2D-magnetic tunnel junctions (2D-MTJs). In our measurements, supported by ab-initio calculations, the strength of interaction between ferromagnetic electrodes and graphene monolayers is shown to fundamentally control the resulting spin signal. In particular, by switching the graphene/ferromagnet interaction, spin transport reveals magneto-resistance signal MR > 80% in junctions with low resistance × area products. Descriptions based only on a simple K-point filtering picture (i.e. MR increase with the number of layers) are not sufficient to predict the behavior of our devices. We emphasize that hybridization effects need to be taken into account to fully grasp the spin properties (such as spin dependent density of states) when 2D materials are used as ultimately thin interfaces. While this is only a first demonstration, we thus introduce the fruitful potential of spin manipulation by proximity effect at the hybridized 2D material / ferromagnet interface for 2D-MTJs. 2D materials are foreseen as an opportunity to tailor spintronics devices interfaces, a.k.a spinterfaces. Here, using state-of-the-art large-scale integration in spin-valves, authors demonstrate that hybridization of graphene with a metallic spin source results in strong spin filtering effects.

Spin information processing is a possible new paradigm for post-CMOS (complementary metal-oxide semiconductor) electronics and efficient spin propagation over long distances is fundamental to this vision. However, despite several decades of intense research, a suitable platform is still wanting. We report here on highly efficient spin transport in two-terminal polarizer/analyser devices based on high-mobility epitaxial graphene grown on silicon carbide. Taking advantage of high-impedance injecting/detecting tunnel junctions, we show spin transport efficiencies up to 75%, spin signals in the mega-ohm range and spin diffusion lengths exceeding 100 μm. This enables spintronics in complex structures: devices and network architectures relying on spin information processing, well beyond present spintronics applications, can now be foreseen. A demonstration of the ability to transmit spin currents over distances of more than one hundred micrometres with an efficiency of up to 75% in graphene grown epitaxially on silicon carbide improves the prospects of graphene-based spintronic devices.

Raman thermometry is a powerful technique for sub-microscale thermal measurements on semiconductor-based devices, provided that the active region remains accessible and is not obscured by metallization. Since pure metals do not exhibit Raman scattering, traditional Raman thermometry becomes ineffective in such cases. To overcome this limitation, we propose the use of atomically thin Two-Dimensional materials as local temperature sensors. These materials generate Raman spectra at the nanoscale, enabling highly precise absolute surface temperature measurements. In this study, we investigate the feasibility and effectiveness of this approach by applying it to power devices, including a calibrated gold resistor and an SiC Junction Barrier Schottky (JBS) diode. We assess the processing challenges and measurement reliability of 2D materials for thermal characterization. To validate our findings, we complement Raman thermometry with thermoreflectance measurements, which are well suited for metallized surfaces. For example, on the serpentine resistor, Raman thermometry applied to the 2D material yielded a thermal resistance of 22.099 °C/W, while thermoreflectance on the metallic surface measured 21.898 °C/W. This close agreement suggests good thermal conductance at the metal/2D material interface. The results demonstrate the potential of integrating 2D materials as effective nanoscale temperature probes, offering new insights into thermal management strategies for advanced electronic components. Additionally, thermal simulations are conducted to further analyze the thermal response of these devices under operational conditions. Furthermore, we investigate two 2D material integration methods, transfer and direct growth, and evaluate them through measured thermal resistances for the SiC JBS diode, highlighting the influence of the deposition technique on thermal performance.

Van der Waals heterostructures are set as strong contenders for post‐CMOS quantum materials engineering. A major step for their systematic exploration and exploitation of technological component demonstrators resides in their eased large‐scale design. In this direction, the growth of artificial van der Waals 2D superlattices is presented here such as (MoS2/WS2)n, (WS2/WSe2)n, and (MoS2/WSe2)n with unit cells repetitions reaching n > 10. The fabrication of these materials is enabled by a fully automated in‐situ pulsed laser deposition (PLD) tool. This approach provides cm2 scale homogeneous superlattices with on‐demand material parameters tailoring (layer number, order, and composition). The process is rapid and simple compared to manual pickup exfoliation methods or to sequential transfers of single layers grown by techniques such as chemical vapor deposition, allowing a large repetition of the unit cells in a “mille‐feuille” cake configuration. The computational exploration of this family of superlattice materials sheds light on the potential for optoelectronic property design by shaping the band‐structure landscape while taking into account the influential effects induced by proximity. Overall, this large‐area approach is proposed as an entry point for the systematic design of complex van der Waals heterostructures. The design of artificial complex van der Waals 2D superlattices with unit cell repetitions reaching n > 10 is introduced. A fully automated, rapid, and relatively simple in situ pulsed laser deposition approach provides cm2 scale homogeneous superlattices with on‐demand material parameters tailoring (layer number, order, and composition). The potential for designing properties by shaping the band‐structure landscape is highlighted.

Non-volatile magnetic random-access memories (MRAMs), such as spin-transfer torque MRAM and next-generation spin–orbit torque MRAM, are emerging as key to enabling low-power technologies, which are expected to spread over large markets from embedded memories to the Internet of Things. Concurrently, the development and performances of devices based on two-dimensional van der Waals heterostructures bring ultracompact multilayer compounds with unprecedented material-engineering capabilities. Here we provide an overview of the current developments and challenges in regard to MRAM, and then outline the opportunities that can arise by incorporating two-dimensional material technologies. We highlight the fundamental properties of atomically smooth interfaces, the reduced material intermixing, the crystal symmetries and the proximity effects as the key drivers for possible disruptive improvements for MRAM at advanced technology nodes. Developments, challenges and opportunities in using two-dimensional materials for the next generation of non-volatile spin-based memory technologies are reviewed, and possible disruptive improvements are discussed.

Ferroic-order parameters 1 are useful as state variables in non-volatile information storage media because they show a hysteretic dependence on their electric or magnetic field. Coupling ferroics with quantum-mechanical tunnelling allows a simple and fast readout of the stored information through the influence of ferroic orders on the tunnel current. For example, data in magnetic random-access memories 2 are stored in the relative alignment of two ferromagnetic electrodes separated by a non-magnetic tunnel barrier, and data readout is accomplished by a tunnel current measurement. However, such devices based on tunnel magnetoresistance 3 typically exhibit OFF/ON ratios of less than 4, and require high powers for write operations (>1 × 10 6  A cm −2 ). Here, we report non-volatile memories with OFF/ON ratios as high as 100 and write powers as low as ∼1 × 10 4  A cm −2 at room temperature by storing data in the electric polarization direction of a ferroelectric tunnel barrier. The junctions show large, stable, reproducible and reliable tunnel electroresistance, with resistance switching occurring at the coercive voltage of ferroelectric switching. These ferroelectric devices emerge as an alternative to other resistive memories 4 , and have the advantage of not being based on voltage-induced migration of matter at the nanoscale 5 , 6 , but on a purely electronic mechanism 7 . A tunnel junction that consists of a ferroelectric barrier layer sandwiched between two electrodes can operate as a fast, low-power and non-volatile nanoscale solid-state memory.

Superconductivity can be induced in a normal material via the 'leakage' of superconducting pairs of charge carriers from an adjacent superconductor. This so-called proximity effect is markedly influenced by graphene's unique electronic structure, both in fundamental and technologically relevant ways. These include an unconventional form of the 'leakage' mechanism--the Andreev reflection--and the potential of supercurrent modulation through electrical gating. Despite the interest of high-temperature superconductors in that context, realizations have been exclusively based on low-temperature ones. Here we demonstrate a gate-tunable, high-temperature superconducting proximity effect in graphene. Notably, gating effects result from the perfect transmission of superconducting pairs across an energy barrier--a form of Klein tunnelling, up to now observed only for non-superconducting carriers--and quantum interferences controlled by graphene doping. Interestingly, we find that this type of interference becomes dominant without the need of ultraclean graphene, in stark contrast to the case of low-temperature superconductors. These results pave the way to a new class of tunable, high-temperature Josephson devices based on large-scale graphene.

Hardware spiking neural networks hold the promise of realizing artificial intelligence with high energy efficiency. In this context, solid-state and scalable memristors can be used to mimic biological neuron characteristics. However, these devices show limited neuronal behaviors and have to be integrated in more complex circuits to implement the rich dynamics of biological neurons. Here we studied a NbO x memristor neuron that is capable of emulating numerous neuronal dynamics, including tonic spiking, stochastic spiking, leaky-integrate-and-fire features, spike latency, temporal integration. The device also exhibits phasic bursting, a property that has scarcely been observed and studied in solid-state nano-neurons. We show that we can reproduce and understand this particular response through simulations using non-linear dynamics. These results show that a single NbO x device is sufficient to emulate a collection of rich neuronal dynamics that paves a path forward for realizing scalable and energy-efficient neuromorphic computing paradigms.

The crystallographic orientation of anisotropic 2D materials plays a crucial role in their physical properties and device performance. However, standard orientation techniques such as transmission electron microscopy (TEM) or X-ray diffraction (XRD) can be complex and less accessible for routine characterization. In this study, we investigate the orientation of black phosphorus (BP) from bulk crystals to thin layers using angle-resolved polarized Raman spectroscopy (ARPRS) with a single-wavelength (514 nm) Raman setup. By incorporating thickness-dependent interference effects and anisotropic optical indices, this approach provides a reliable framework for orientation determination across different BP thicknesses. The method is validated through direct orientation measurements using TEM and Electron Backscattering Diffraction (EBSD), confirming its applicability to both thick and ultrathin samples. Given its simplicity and compatibility with widely available Raman setups, this approach offers a practical solution for characterizing BP orientation without requiring advanced structural characterization techniques.

Black phosphorus (BP) stands out from other 2D materials by the wide amplitude of the band-gap energy (Delta(Eg)) that sweeps an optical window from Visible (VIS) to Infrared (IR) wavelengths, depending on the layer thickness. This singularity made the optical and excitonic properties of BP difficult to map. Specifically, the literature lacks in presenting experimental and theoretical data on the optical properties of BP on an extended thickness range. Here we report the study of an ensemble of photoluminescence spectra from 79 passivated BP flakes recorded at 4 K with thicknesses ranging from 4 nm to 700 nm, obtained by mechanical exfoliation. We observe that the exfoliation steps induce additional defects states that compete the radiative recombination from bound excitons observed in the crystal. We also show that the evolution of the photoluminescence energy versus thickness follows a quantum well confinement model appreciable from a thickness predicted and probed at 25 nm. The BP slabs placed in different 2D heterostructures show that the emission energy is not significantly modulated by the dielectric environment. Introduction Confinement effects