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One of the first tasks we learn as children is to grasp objects based on our tactile perception. Incorporating such skill in robots will enable multiple applications, such as increasing flexibility in industrial processes or providing assistance to people with physical disabilities. However, the difficulty lies in adapting the grasping strategies to a large variety of tasks and objects, which can often be unknown. The brute-force solution is to learn new grasps by trial and error, which is inefficient and ineffective. In contrast, Bayesian optimization applies active learning by adding information to the approximation of an optimal grasp. This paper proposes the use of Bayesian optimization techniques to safely perform robotic grasping. We analyze different grasp metrics to provide realistic grasp optimization in a real system including tactile sensors. An experimental evaluation in the robotic system shows the usefulness of the method for performing unknown object grasping even in the presence of noise and uncertainty inherent to a real-world environment.

From the implementation of the Grafcet programming language we obtain in this document the different ways of applying this method, the advantages it obtains with respect to efficiency, cost, quality and operational and time optimization. The behavior of a pump alternation process is analyzed using GRAFCET, which is easier to design, verify and implement sequential control systems. We will also have the different fields where this programming is applied., Comment: 8 PAGINAS, in Spanish language

Topological insulators (TIs) are a promising class of materials for manipulating the magnetization of an adjacent ferromagnet (FM) through the spin-orbit torque (SOT) mechanism. However, current studies combining TIs with conventional FMs present large device-to-device variations, resulting in a broad distribution of SOT magnitudes. It has been identified that the interfacial quality between the TI and the FM is of utmost importance in determining the nature and efficiency of the SOT. To optimize the SOT magnitude and enable ultra-low-power magnetization switching, an atomically smooth interface is necessary. To this end, we have developed the growth of a full van der Waals FM/TI heterostructure by molecular beam epitaxy. The compensated TI (Bi0.4Sb0.6)2Te3 and ferromagnetic Fe3GeTe2 (FGT) were chosen because of their exceptional crystalline quality, low carrier concentration in BST and relatively large Curie temperature and perpendicular magnetic anisotropy in FGT. We characterized the magnitude of the SOTs by using thorough harmonic magnetotransport measurements and showed that the magnetization of an ultrathin FGT film could be switched with a current density Jc < 10^10 A/m^2. In comparison to previous studies utilizing traditional FMs, our findings are highly reliable, displaying little to no variation between devices.

The ability to control the generation of spins in arbitrary directions is a long-sought goal in spintronics. Charge-to-spin interconversion (CSI) phenomena depend strongly on symmetry. Systems with reduced crystal symmetry allow anisotropic CSI with unconventional components, where charge and spin currents and the spin polarization are not mutually perpendicular to each other. Here, we demonstrate experimentally that the CSI in graphene-WTe2 induces spins with components in all three spatial directions. By performing multi-terminal nonlocal spin precession experiments, with specific magnetic field orientations, we discuss how to disentangle the CSI from the spin Hall and inverse spin galvanic effects.

Specular microscopy assessment of the human corneal endothelium (CE) in Fuchs' dystrophy is challenging due to the presence of dark image regions called guttae. This paper proposes a UNet-based segmentation approach that requires minimal post-processing and achieves reliable CE morphometric assessment and guttae identification across all degrees of Fuchs' dystrophy. We cast the segmentation problem as a regression task of the cell and gutta signed distance maps instead of a pixel-level classification task as typically done with UNets. Compared to the conventional UNet classification approach, the distance-map regression approach converges faster in clinically relevant parameters. It also produces morphometric parameters that agree with the manually-segmented ground-truth data, namely the average cell density difference of -41.9 cells/mm2 (95% confidence interval (CI) [-306.2, 222.5]) and the average difference of mean cell area of 14.8 um2 (95% CI [-41.9, 71.5]). These results suggest a promising alternative for CE assessment.

Customer service chatbots are conversational systems designed to provide information to customers about products/services offered by different companies. Particularly, intent recognition is one of the core components in the natural language understating capabilities of a chatbot system. Among the different intents that a chatbot is trained to recognize, there is a set of them that is universal to any customer service chatbot. Universal intents may include salutation, switch the conversation to a human agent, farewells, among others. A system to recognize those universal intents will be very helpful to optimize the training process of specific customer service chatbots. We propose the development of a universal intent recognition system, which is trained to recognize a selected group of 11 intents that are common in 28 different chatbots. The proposed system is trained considering state-of-the-art word-embedding models such as word2vec and BERT, and deep classifiers based on convolutional and recurrent neural networks. The proposed model is able to discriminate between those universal intents with a balanced accuracy up to 80.4\%. In addition, the proposed system is equally accurate to recognize intents expressed both in short and long text requests. At the same time, misclassification errors often occurs between intents with very similar semantic fields such as farewells and positive comments. The proposed system will be very helpful to optimize the training process of a customer service chatbot because some of the intents will be already available and detected by our system. At the same time, the proposed approach will be a suitable base model to train more specific chatbots by applying transfer learning strategies.

The large variety of 2D materials and their co-integration in van der Waals (vdW) heterostructures enable innovative device engineering. In addition, their atomically-thin nature promotes the design of artificial materials by proximity effects that originate from short-range interactions. Such a designer approach is particularly compelling for spintronics, which typically harnesses functionalities from thin layers of magnetic and non-magnetic materials and the interfaces between them. Here, we overview recent progress on 2D spintronics and opto-spintronics using vdW heterostructures. After an introduction to the forefront of spin transport research, we highlight the unique spin-related phenomena arising from spin-orbit and magnetic proximity effects. We further describe the ability to create multi-functional hybrid heterostructures based on vdW materials, combining spin, valley and excitonic degrees of freedom. We end with an outlook on perspectives and challenges for the design and production of ultra-compact all-2D spin devices and their potential applications in conventional and quantum technologies., Comment: Review article. 39 pages, 5 figures, 2 tables. Full-text access at the SharedIt link https://rdcu.be/cpbSv

State-of-the-art fabrication and characterization techniques have been employed to measure the thermal conductivity of suspended, single-crystalline MoS2 and MoS2/hBN heterostructures. Two-laser Raman scattering thermometry was used combined with real time measurements of the absorbed laser power, which allowed us to determine the thermal conductivities without any assumptions. Measurements on MoS2 layers with thicknesses of 5 and 14 exhibit thermal conductivity in the range between 12 and 24 Wm-1K-1. Additionally, after determining the thermal conductivity of a selected MoS2 sample, an hBN flake was transferred onto it and the effective thermal conductivity of the heterostructure was subsequently measured. Remarkably, despite that the thickness of the hBN layer was less than a third of the thickness of the MoS2 layer, the heterostructure showed an almost eight-fold increase in the thermal conductivity, being able to dissipate more than 10 times the laser power without any visible sign of damage. These results are consistent with a high thermal interface conductance between MoS2 and hBN and an efficient in-plane heat spreading driven by hBN. Indeed, we estimate G 70 MWm-2K-1 which is significantly higher than previously reported values. Our work therefore demonstrates that the insertion of hBN layers in potential MoS2 based devices holds the promise for efficient thermal management.

(Bi$_{1-x}$Sb$_x$)$_2$Te$_3$ topological insulators (TIs) are gathering increasing attention owing to their large charge-to-spin conversion efficiency and the ensuing spin-orbit torques (SOTs) that can be used to manipulate the magnetization of a ferromagnet (FM). The origin of the torques, however, remains elusive, while the implications of hybridized states and the strong material intermixing at the TI/FM interface are essentially unexplored. By combining interface chemical analysis and spin-transfer ferromagnetic resonance (ST-FMR) measurements, we demonstrate that intermixing plays a critical role in the generation of SOTs. By inserting a suitable normal metal spacer, material intermixing is reduced and the TI properties at the interface are largely improved, resulting in strong variations in the nature of the SOTs. A dramatic enhancement of a field-like torque, opposing and surpassing the Oersted-field torque, is observed, which can be attributed to the non-equilibrium spin density in Rashba-split surface bands and to the suppression of spin memory loss., Comment: This document is the unedited Author's version of a Submitted Work that was subsequently accepted for publication in Nanoletters, \copyright American Chemical Society after peer review

Spin-orbit coupling stands as a powerful tool to interconvert charge and spin currents and to manipulate the magnetization of magnetic materials through the spin torque phenomena. However, despite the diversity of existing bulk materials and the recent advent of interfacial and low-dimensional effects, control of the interconvertion at room-temperature remains elusive. Here, we unequivocally demonstrate strongly enhanced room-temperature spin-to-charge (StC) conversion in graphene driven by the proximity of a semiconducting transition metal dichalcogenide(WS2). By performing spin precession experiments in properly designed Hall bars, we separate the contributions of the spin Hall and the spin galvanic effects. Remarkably, their corresponding conversion effiencies can be tailored by electrostatic gating in magnitude and sign, peaking nearby the charge neutrality point with a magnitude that is comparable to the largest efficiencies reported to date. Such an unprecedented electric-field tunability provides a new building block for spin generation free from magnetic materials and for ultra-compact magnetic memory technologies., Comment: 13 pages, 4 figures

We determine the spin-lifetime anisotropy of spin-polarized carriers in graphene. In contrast to prior approaches, our method does not require large out-of-plane magnetic fields and thus it is reliable for both low- and high-carrier densities. We first determine the in-plane spin lifetime by conventional spin precession measurements with magnetic fields perpendicular to the graphene plane. Then, to evaluate the out-of-plane spin lifetime, we implement spin precession measurements under oblique magnetic fields that generate an out-of-plane spin population. We find that the spin-lifetime anisotropy of graphene on silicon oxide is independent of carrier density and temperature down to 150 K, and much weaker than previously reported. Indeed, within the experimental uncertainty, the spin relaxation is isotropic. Altogether with the gate dependence of the spin lifetime, this indicates that the spin relaxation is driven by magnetic impurities or random spin-orbit or gauge fields., Comment: Final version published in Nature Communications under a Creative Commons Attribution 4.0 International License

In recent years, new spin-dependent thermal effects have been discovered in ferromagnets, stimulating a growing interest in spin caloritronics, a field that exploits the interaction between spin and heat currents. Amongst the most intriguing phenomena is the spin Seebeck effect, in which a thermal gradient gives rise to spin currents that are detected through the inverse spin Hall effect. Non-magnetic materials such as graphene are also relevant for spin caloritronics, thanks to efficient spin transport, energy-dependent carrier mobility and unique density of states. Here, we propose and demonstrate that a carrier thermal gradient in a graphene lateral spin valve can lead to a large increase of the spin voltage near to the graphene charge neutrality point. Such an increase results from a thermoelectric spin voltage, which is analogous to the voltage in a thermocouple and that can be enhanced by the presence of hot carriers generated by an applied current. These results could prove crucial to drive graphene spintronic devices and, in particular, to sustain pure spin signals with thermal gradients and to tune the remote spin accumulation by varying the spin-injection bias.

Graphene has emerged as the foremost material for future two-dimensional spintronics due to its tuneable electronic properties. In graphene, spin information can be transported over long distances and, in principle, be manipulated by using magnetic correlations or large spin-orbit coupling (SOC) induced by proximity effects. In particular, a dramatic SOC enhancement has been predicted when interfacing graphene with a semiconducting transition metal dechalcogenide, such as tungsten disulphide (WS$_2$). Signatures of such an enhancement have recently been reported but the nature of the spin relaxation in these systems remains unknown. Here, we unambiguously demonstrate anisotropic spin dynamics in bilayer heterostructures comprising graphene and WS$_2$. By using out-of-plane spin precession, we show that the spin lifetime is largest when the spins point out of the graphene plane. Moreover, we observe that the spin lifetime varies over one order of magnitude depending on the spin orientation, indicating that the strong spin-valley coupling in WS$_2$ is imprinted in the bilayer and felt by the propagating spins. These findings provide a rich platform to explore coupled spin-valley phenomena and offer novel spin manipulation strategies based on spin relaxation anisotropy in two-dimensional materials.