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The TRGB-SBF Project team is developing an independent distance ladder using a geometrical calibration of the tip of the red giant branch (TRGB) method in elliptical galaxies that can in turn be used to set the surface brightness fluctuation (SBF) distance scale independent of Cepheid variables and Type Ia supernovae. In this paper, we use JWST TRGB distances calibrated using the megamaser galaxy NGC 4258 to determine a new Cepheid-independent SBF zero point for HST. This new calibration, along with improved optical color measurements from PanSTARRS and DECam, gives an updated value of the Hubble-Lemaitre constant $H_0 = 73.8 \pm 0.7 \pm 2.3$ km/s/Mpc that is virtually identical to the previously published result based on SBF distances calibrated using Cepheids (Blakeslee et al. 2021, arxiv:2101.02221). Future improvements in the geometrical calibration of TRGB and additions to the HST SBF survey will further reduce the random and systematic uncertainties on $H_0$ measured using the extensive HST WFC3/IR SBF dataset. JWST observations of the Coma cluster will soon establish a foundation for the SBF calibration that will extend to much larger distances than is possible with HST., Comment: 8 pages, 2 figures, submitted to ApJL

Charge-to-spin and spin-to-charge conversion mechanisms in high spin-orbit materials are the new frontier of memory devices. They operate via spin-orbit torque (SOT) switching of a magnetic electrode, driven by an applied charge current. In this work, we propose a novel memory device based on the semiconducting two-dimensional centrosymmetric transition metal dichalcogenide (TMD) MoS2, that operates as a SOT device in the writing process and a spin valve in the reading process. We demonstrate that stable voltage states at room temperature can be deterministically controlled by a switching current density as low as 3.2x10^4 A/cm^2 even in zero field. An applied field 50-100 Oe can be used as a further or alternative control parameter for the state switching. Ab initio calculations of spin Hall effect (SHE) and orbital Hall effect (OHE) indicate that the latter is the only one responsible for the generation of the SOT in the magnetic electrode. The large value of OHC in bulk MoS2 makes our device competitive in terms of energetic efficiency and could be integrated in TMD heterostructures to design memory devices with multiple magnetization states for non-Boolean computation.

Predictive modeling using structural magnetic resonance imaging (MRI) data is a prominent approach to study brain-aging. Machine learning algorithms and feature extraction methods have been employed to improve predictions and explore healthy and accelerated aging e.g. neurodegenerative and psychiatric disorders. The high-dimensional MRI data pose challenges to building generalizable and interpretable models as well as for data privacy. Common practices are resampling or averaging voxels within predefined parcels, which reduces anatomical specificity and biological interpretability as voxels within a region may differently relate to aging. Effectively, naive fusion by averaging can result in information loss and reduced accuracy. We present a conceptually novel two-level stacking ensemble (SE) approach. The first level comprises regional models for predicting individuals' age based on voxel-wise information, fused by a second-level model yielding final predictions. Eight data fusion scenarios were explored using as input Gray matter volume (GMV) estimates from four datasets covering the adult lifespan. Performance, measured using mean absolute error (MAE), R2, correlation and prediction bias, showed that SE outperformed the region-wise averages. The best performance was obtained when first-level regional predictions were obtained as out-of-sample predictions on the application site with second-level models trained on independent and site-specific data (MAE=4.75 vs baseline regional mean GMV MAE=5.68). Performance improved as more datasets were used for training. First-level predictions showed improved and more robust aging signal providing new biological insights and enhanced data privacy. Overall, the SE improves accuracy compared to the baseline while preserving or enhancing data privacy., Comment: version1

Probabilistic Ising machines (PIMs) provide a path to solving many computationally hard problems more efficiently than deterministic algorithms on von Neumann computers. Stochastic magnetic tunnel junctions (S-MTJs), which are engineered to be thermally unstable, show promise as entropy sources in PIMs. However, scaling up S-MTJ-PIMs is challenging, as it requires fine control of a small magnetic energy barrier across large numbers of devices. In addition, non-spintronic components of S-MTJ-PIMs to date have been primarily realized using general-purpose processors or field-programmable gate arrays. Reaching the ultimate performance of spintronic PIMs, however, requires co-designed application-specific integrated circuits (ASICs), combining CMOS with spintronic entropy sources. Here we demonstrate an ASIC in 130 nm foundry CMOS, which implements integer factorization as a representative hard optimization problem, using PIM-based invertible logic gates realized with 1143 probabilistic bits. The ASIC uses stochastic bit sequences read from an adjacent voltage-controlled (V-) MTJ chip. The V-MTJs are designed to be thermally stable in the absence of voltage, and generate random bits on-demand in response to 10 ns pulses using the voltage-controlled magnetic anisotropy effect. We experimentally demonstrate the chip's functionality and provide projections for designs in advanced nodes, illustrating a path to millions of probabilistic bits on a single CMOS+V-MTJ chip.

Machine learning (ML) models benefit from large datasets. Collecting data in biomedical domains is costly and challenging, hence, combining datasets has become a common practice. However, datasets obtained under different conditions could present undesired site-specific variability. Data harmonization methods aim to remove site-specific variance while retaining biologically relevant information. This study evaluates the effectiveness of popularly used ComBat-based methods for harmonizing data in scenarios where the class balance is not equal across sites. We find that these methods struggle with data leakage issues. To overcome this problem, we propose a novel approach PrettYharmonize, designed to harmonize data by pretending the target labels. We validate our approach using controlled datasets designed to benchmark the utility of harmonization. Finally, using real-world MRI and clinical data, we compare leakage-prone methods with PrettYharmonize and show that it achieves comparable performance while avoiding data leakage, particularly in site-target-dependence scenarios.

The electrically readable complex dynamics of robust and scalable magnetic tunnel junctions (MTJs) offer promising opportunities for advancing neuromorphic computing. In this work, we present an MTJ design with a free layer and two polarizers capable of computing the sigmoidal activation function and its gradient at the device level. This design enables both feedforward and backpropagation computations within a single device, extending neuromorphic computing frameworks previously explored in the literature by introducing the ability to perform backpropagation directly in hardware. Our algorithm implementation reveals two key findings: (i) the small discrepancies between the MTJ-generated curves and the exact software-generated curves have a negligible impact on the performance of the backpropagation algorithm, (ii) the device implementation is highly robust to inter-device variation and noise, and (iii) the proposed method effectively supports transfer learning and knowledge distillation. To demonstrate this, we evaluated the performance of an edge computing network using weights from a software-trained model implemented with our MTJ design. The results show a minimal loss of accuracy of only 0.1% for the Fashion MNIST dataset and 2% for the CIFAR-100 dataset compared to the original software implementation. These results highlight the potential of our MTJ design for compact, hardware-based neural networks in edge computing applications, particularly for transfer learning., Comment: 18 pages, 5 figures

The Virgo Cluster is the nearest substantial cluster of galaxies to the Milky Way and a cornerstone of the extragalactic distance scale. Here, we present JWST/NIRCam observations that simultaneously cover the cores and halos of ten galaxies in and around the Virgo Cluster and are designed to perform simultaneous measurements of the tip of the red giant branch (TRGB) and surface brightness fluctuations (SBF). Seven of the targets are within the Virgo Cluster and where we are able to resolve some of the cluster's substructure, while an additional three provide important constraints on Virgo infall. The seven galaxies within Virgo itself all have SBF measurements from the Advanced Camera for Surveys Virgo Cluster Survey (ACSVCS). After adjusting the ACSVCS measurements for the offset from our new JWST TRGB measurements, we determine a distance to the Virgo Cluster of d $=$ 16.17 $\pm$ 0.25 (stat) $\pm$ 0.47 (sys) Mpc. The work presented here is part of a larger program to develop a Population II distance scale through the TRGB and SBF that is completely independent of the prominent Cepheid + Type Ia supernova ladder. The TRGB distances to the galaxies presented here, when combined with future SBF measurements, will provide a crucial step forward for determining whether or not systematic errors can explain the well-known "Hubble tension'' or if there is significant evidence for cracks in the $\Lambda$CDM model., Comment: 18 pages, 9 figures, accepted to ApJ

Radiofrequency harvesting using ambient wireless energy could be used to reduce the carbon footprint of electronic devices. However, ambient radiofrequency energy is weak (less than -20 dBm), and thermodynamic limits and high-frequency parasitic impedance restrict the performance of state-of-the-art radiofrequency rectifiers. Nanoscale spin rectifiers based on magnetic tunnel junctions have recently demonstrated high sensitivity, but suffer from a low a.c.-to-d.c. conversion efficiency (less than 1%). Here, we report a sensitive spin rectifier rectenna that can harvest ambient radiofrequency signals between -62 and -20 dBm. We also develop an on-chip co-planar waveguide-based spin rectifier array with a large zero-bias sensitivity (around 34,500 mV/mW) and high efficiency (7.81%). Self-parametric excitation driven by voltage-controlled magnetic anisotropy is a key mechanism that contributes to the performance of the spin-rectifier array. We show that these spin rectifiers can wirelessly power a sensor at a radiofrequency power of -27 dBm.

This paper presents a review of the NTIRE 2024 challenge on night photography rendering. The goal of the challenge was to find solutions that process raw camera images taken in nighttime conditions, and thereby produce a photo-quality output images in the standard RGB (sRGB) space. Unlike the previous year's competition, the challenge images were collected with a mobile phone and the speed of algorithms was also measured alongside the quality of their output. To evaluate the results, a sufficient number of viewers were asked to assess the visual quality of the proposed solutions, considering the subjective nature of the task. There were 2 nominations: quality and efficiency. Top 5 solutions in terms of output quality were sorted by evaluation time (see Fig. 1). The top ranking participants' solutions effectively represent the state-of-the-art in nighttime photography rendering. More results can be found at https://nightimaging.org., Comment: 10 pages, 10 figures

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

Studying the dynamics of small-scale beams with attached particles is crucial for sensing applications in various fields, such as bioscience, material science, energy storage devices, and environmental monitoring. Here, a stress-driven nonlocal model is presented for the free transverse vibration of small-scale beams carrying multiple masses taking into account the eccentricity of the masses relative to the beam axis. The results show excellent agreement with the experimental and numerical data in the literature. New insights into the frequency shifts and mode shapes of the first four vibrational modes of stress-driven nonlocal beams with up to three attached particles are presented. The study investigates the inverse problem of detecting the location and mass of an attached particle based on natural frequency shifts. The knowledge acquired from the present study provides valuable guidance for the design and analysis of ultrasensitive mechanical mass sensors., Comment: 43 pages, 17 figures, Published in Thin-Walled Structures, 112005, 2024

Differences between the local value of the Hubble constant measured via the distance ladder versus the value inferred from the cosmic microwave background with the assumption of the standard $\Lambda$CDM model have reached over 5$\sigma$ significance. To determine if this discrepancy is due to new physics or more mundane systematic errors, it is essential to remove as many sources of systematic uncertainty as possible by developing high-precision distance ladders that are independent of the traditional Cepheid and Type Ia supernovae route. Here we present JWST observations of three early-type Fornax Cluster galaxies, the first of fourteen observations from a Cycle 2 JWST program. Our modest integration times allow us to measure highly precise tip of the red giant branch (TRGB) distances, and will also be used to perform measurements of Surface Brightness Fluctuations (SBF). From these three galaxies, we determine an average TRGB distance modulus to the Fornax Cluster of $\mu$ = 31.424 $\pm$ 0.077 mag, or D = 19.3 $\pm$ 0.7 Mpc. With eleven more scheduled observations in nearby elliptical galaxies, our program will allow us set the zero point of the SBF scale to better than 2$\%$ for more distant measurements, charting a path towards a high-precision measurement of $H_{0}$ that is independent of the traditional Cepheid-SN Ia distance ladder., Comment: 14 pages, 9 figures, accepted to ApJ

This paper reports on the NTIRE 2024 Quality Assessment of AI-Generated Content Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2024. This challenge is to address a major challenge in the field of image and video processing, namely, Image Quality Assessment (IQA) and Video Quality Assessment (VQA) for AI-Generated Content (AIGC). The challenge is divided into the image track and the video track. The image track uses the AIGIQA-20K, which contains 20,000 AI-Generated Images (AIGIs) generated by 15 popular generative models. The image track has a total of 318 registered participants. A total of 1,646 submissions are received in the development phase, and 221 submissions are received in the test phase. Finally, 16 participating teams submitted their models and fact sheets. The video track uses the T2VQA-DB, which contains 10,000 AI-Generated Videos (AIGVs) generated by 9 popular Text-to-Video (T2V) models. A total of 196 participants have registered in the video track. A total of 991 submissions are received in the development phase, and 185 submissions are received in the test phase. Finally, 12 participating teams submitted their models and fact sheets. Some methods have achieved better results than baseline methods, and the winning methods in both tracks have demonstrated superior prediction performance on AIGC.

The surface brightness fluctuation (SBF) method is a robust and efficient way of measuring distances to galaxies containing evolved stellar populations. Although many recent applications of the method have used space-based imaging, SBF remains a powerful technique for ground-based telescopes. Deep, wide-field imaging surveys with subarsecond seeing enable SBF measurements for numerous nearby galaxies. Using a preliminary calibration, Cantiello et al. (2018) presented SBF distances for 89 bright, mainly early-type galaxies observed in the Next Generation Virgo Cluster Survey (NGVS). Here, we present a refined calibration and SBF distances for 278 galaxies extending several magnitudes fainter than in previous work. The derived distances have uncertainties of 5-12\% depending on the properties of the individual galaxies, and our sample is more than three times larger than any previous SBF study of this region. Virgo has a famously complex structure with numerous subclusters, clouds and groups; we associate individual galaxies with the various substructures and map their three-dimensional spatial distribution. Curiously, subcluster A, centered around M87, appears to have two peaks in distance: the main peak at $\sim$16.5 Mpc and a smaller one at $\sim$19.4 Mpc. Subclusters B and C have distances of $\sim$15.8 Mpc. The W and W' groups form a filament-like structure, extending more than 15~Mpc behind the cluster with a commensurate velocity increase of $\sim$1000 \kms\ along its length. These measurements are a valuable resource for future studies of the relationship between galaxy properties and local environment within a dynamic and evolving region., Comment: 30 pages, 15 figures, Acccepted for publication on the ApJ

Networks are convenient mathematical models to represent the structure of complex systems, from cells to societies. In the past decade, multilayer network science -- the branch of the field dealing with units interacting in multiple distinct ways, simultaneously -- was demonstrated to be an effective modeling and analytical framework for a wide spectrum of empirical systems, from biopolymer networks (such as interactome and metabolomes) to neuronal networks (such as connectomes), from social networks to urban and transportation networks. In this Element, a decade after the publication of one of the most seminal papers on this topic, we review the most salient features of multilayer network science, covering both theoretical aspects and direct applications to real-world coupled/interdependent systems, from the point of view of multilayer structure, dynamics, and function. We discuss potential frontiers for this topic and the corresponding challenges in the field for the future., Comment: Published in Cambridge Elements. Cambridge University Press; 2022

We consider the Schr\"odinger operators which are constructed from the $\lambda$-opers corresponding to solutions of the $\widehat{\mathfrak{sl}}_2$ Gaudin Bethe Ansatz equations. We define and study the connection coefficients called the $Q$-functions. We conjecture that the $Q$-functions obtained from the $\lambda$-opers coincide with the $Q$-functions of the Bazhanov-Lukyanov-Zamolodchikov opers with the monster potential related to the quantum KdV flows. We give supporting evidence for this conjecture., Comment: Revised version, new section about the action of the reproduction procedures on opers and Q functions. 1 figure

The buckling instability of micro- and nanopillars can be an issue when designing intelligent miniaturized devices and characterizing composite materials reinforced with beam-like particles on the small-scale. Analytical modeling of the buckling of miniaturized pillars is especially important due to the difficulties in conducting experiments. Here, a well-posed stress-driven nonlocal model is developed, which allows the calculation of the critical loads and buckling configurations of the miniaturized pillars on an elastic foundation and with arbitrary numbers of edge cracks. The discontinuities in bending slopes and deflection at the damaged cross-sections due to the edge cracks are captured through the incorporation of both rotational and translational springs. A comprehensive analysis is conducted to investigate the instability of pillars containing a range of one to four cracks. This analysis reveals interesting effects regarding the influence of crack location, nonlocality, and elastic foundation on the initial and subsequent critical loads and associated buckling configurations. The main findings are: (i) the shielding and amplification effects related to a system of cracks become more significant as the dimensions of pillars reduce, (ii) the influence of the shear force at the damaged cross-section related to the translational spring must not be neglected when dealing with higher modes of buckling and long cracks, (iii) an elastic foundation decreases the effects of the cracks and size dependency on the buckling loads, and (iv) the effects of the edge cracks on the critical loads and buckling configurations of the miniaturized pillars are highly dependent on the boundary conditions., Comment: 29 pages, 15 figures, Published in International Journal of Damage Mechanics (2023)

This paper represents the completion of our work on the ODE/IM correspondence for the generalised quantum Drinfeld-Sokolov models. We present a unified and general mathematical theory, encompassing all particular cases that we had already addressed, and we fill important analytic and algebraic gaps in the literature on the ODE/IM correspondence. For every affine Lie algebra $\mathfrak{g}$ -- whose Langlands dual $\mathfrak{g}'$ is the untwisted affinisation of a simple Lie algebra -- we study a class of affine twisted parabolic Miura $\mathfrak{g}$-opers, introduced by Feigin, Frenkel and Hernandez. The Feigin-Frenkel-Hernandez opers are defined by fixing the singularity structure at $0$ and $\infty$, and by allowing a finite number of additional singular terms with trivial monodromy. We define the central connection matrix and Stokes matrix for these opers, and prove that the coefficients of the former satisfy the the $QQ$ system of the quantum $\mathfrak{g}'$-Drinfeld-Sokolov (or quantum $\mathfrak{g}'$-KdV) model. If $\mathfrak{g}$ is untwisted, it is known that the trivial monodromy conditions are equivalent to a complete system of algebraic equations for the additional singularities. We prove a suprising negative result in the case $\mathfrak{g}$ is twisted: in this case, the trivial monodromy conditions have no non-trivial solutions., Comment: 55 pages, 4 figures

This paper proposes new methods for set-based state estimation and active fault diagnosis (AFD) of linear descriptor systems (LDS). In contrast to intervals, ellipsoids, and zonotopes, linear static constraints on the state variables, typical of descriptor systems, can be directly incorporated in the mathematical description of constrained zonotopes (CZs). Thanks to this feature, methods using CZs could provide less conservative enclosures than zonotope methods. However, an enclosure on the states should be known for all $k \geq 0$, which is not true in the case of unstable or unobservable LDS. In this context, this paper proposes a new representation for unbounded sets, which allows to develop methods for state estimation and AFD of stable and unstable LDS. Unlike many other extensions of CZs, the proposed set inherits most of their properties, including polynomial time complexity reduction methods, while allowing to describe different classes of sets, such as strips, hyperplanes, and the entire $n$-dimensional Euclidean space. The advantages of the proposed approaches with respect to CZ methods are highlighted in numerical examples., Comment: 15 pages, 6 figures. Revised manuscript includes a new name for the set representation, revised article structure, a new numerical example, and several minor modifications. Theoretical results unchanged. arXiv admin note: text overlap with arXiv:2306.07369

Machine learning (ML) provides powerful tools for predictive modeling. ML's popularity stems from the promise of sample-level prediction with applications across a variety of fields from physics and marketing to healthcare. However, if not properly implemented and evaluated, ML pipelines may contain leakage typically resulting in overoptimistic performance estimates and failure to generalize to new data. This can have severe negative financial and societal implications. Our aim is to expand understanding associated with causes leading to leakage when designing, implementing, and evaluating ML pipelines. Illustrated by concrete examples, we provide a comprehensive overview and discussion of various types of leakage that may arise in ML pipelines., Comment: second draft

The fast-paced development of machine learning (ML) methods coupled with its increasing adoption in research poses challenges for researchers without extensive training in ML. In neuroscience, for example, ML can help understand brain-behavior relationships, diagnose diseases, and develop biomarkers using various data sources like magnetic resonance imaging and electroencephalography. The primary objective of ML is to build models that can make accurate predictions on unseen data. Researchers aim to prove the existence of such generalizable models by evaluating performance using techniques such as cross-validation (CV), which uses systematic subsampling to estimate the generalization performance. Choosing a CV scheme and evaluating an ML pipeline can be challenging and, if used improperly, can lead to overestimated results and incorrect interpretations. We created julearn, an open-source Python library, that allow researchers to design and evaluate complex ML pipelines without encountering in common pitfalls. In this manuscript, we present the rationale behind julearn's design, its core features, and showcase three examples of previously-published research projects that can be easily implemented using this novel library. Julearn aims to simplify the entry into the ML world by providing an easy-to-use environment with built in guards against some of the most common ML pitfalls. With its design, unique features and simple interface, it poses as a useful Python-based library for research projects., Comment: 13 pages, 5 figures

The interest in tellurium nanostructures is on the rise due to their outstanding physical properties including high carrier mobility, anisotropic charge conduction, photoconductivity, thermoelectricity, and piezoelectricity. Applications in related technologies require tailoring the synthesis of tellurium from its preferred vertical growth toward the lateral growth. Here, the synthesis of pillar-like and pennette-like structures of tellurium through a powder vapor deposition technique has been discussed. It has been shown that exploiting salt additives such as NaCl in vapor deposition technique can enhance tellurium pillar dimensionality toward large planar grains. Further, we report on the synthesis of hexagonal ultrathin tellurium nanoflakes, namely tellurene, from few-layer to monolayer thickness by optimizing the growth kinetics without the usage of any additives. In addition, we explore the surface quality and physical properties of as-grown two-dimensional (2D) tellurium, using a variety of characterization techniques, including Raman spectroscopy, scanning electron microscopy, atomic force microscopy, and Kelvin probe force microscopy. This study provides a pivotal scheme for enabling scalable 2D tellurium integration in numerous potential applications for electronics and optoelectronic devices., Comment: 17 pages, 13 figures

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2023. This challenge is to address a major challenge in the field of video processing, namely, video quality assessment (VQA) for enhanced videos. The challenge uses the VQA Dataset for Perceptual Video Enhancement (VDPVE), which has a total of 1211 enhanced videos, including 600 videos with color, brightness, and contrast enhancements, 310 videos with deblurring, and 301 deshaked videos. The challenge has a total of 167 registered participants. 61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions. A total of 176 submissions were submitted by 37 participating teams during the final testing phase. Finally, 19 participating teams submitted their models and fact sheets, and detailed the methods they used. Some methods have achieved better results than baseline methods, and the winning methods have demonstrated superior prediction performance.

Synthetic two-dimensional (2D) mono-elemental crystals, namely X-enes, have recently emerged as a new frontier for atomically thin nanomaterials with on-demand properties. Among X-enes, antimonene, the \b{eta}-phase allotrope of antimony, is formed by atoms arranged in buckled hexagonal rings bearing a comparatively higher environmental stability with respect to other players of this kind. However, the exploitation of monolayer or few-layer antimonene and other 2D materials in novel opto-electronic devices is still hurdled by the lack of scalable processes. Here, we demonstrated the viability of a bottom-up process for the epitaxial growth of antimonene-like nanocrystals (ANCs), based on a Metal-Organic Chemical Vapor Deposition (MOCVD) process, assisted by gold nanoparticles (Au NPs) on commensurate (111)-terminated Ge surfaces. The growth mechanism was investigated by large- and local-area microstructural analysis, revealing that the etching of germanium, catalyzed by the Au NPs, led to the ANCs growth on the exposed Ge (111) planes. As a supportive picture, ab-initio calculations rationalized this epitaxial relationship in terms of compressively strained \b{eta}-phase ANCs. Our process could pave the way to the realization of large-area antimonene layers by a deposition process compatible with the current semiconductor manufacturing technology.

Accelerometers have widespread applications and are an essential component in many areas such as automotive, consumer electronics and industrial applications. Most commercial accelerometers are based on micro-electromechanical system (MEMS) that are limited in downscaling and power consumption. Spintronics-based accelerometers have been proposed as alternatives, however, current proposals suffer from design limitations that result in reliability issues and high cost. Here we propose spintronic accelerometers with magnetic tunnel junctions (MTJs) as building block, which map accelerations into a measurable voltage across the MTJ terminals. The device exploits elastic and dipolar coupling as a sensing mechanism and the spintronic diode effect for the direct read out of the acceleration. The proposed technology represents a potentially competitive and scalable solution to current capacitive MEMS-based approaches that could lead to a step forward in many of the commercial applications., Comment: main document with 4 figures + supplemental information