Spin dynamics of current-driven single magnetic adatoms and molecules

A scanning tunneling microscope can probe the inelastic spin excitations of a single magnetic atom in a surface via spin-flip assisted tunneling in which transport electrons exchange spin and energy with the atomic spin. If the inelastic transport time, defined as the average time elapsed between two inelastic spin flip events, is shorter than the atom spin-relaxation time, the scanning tunnel microscope (STM) current can drive the spin out of equilibrium. Here we model this process using rate equations and a model Hamiltonian that describes successfully spin-flip-assisted tunneling experiments, including a single Mn atom, a Mn dimer, and Fe Phthalocyanine molecules. When the STM current is not spin polarized, the nonequilibrium spin dynamics of the magnetic atom results in nonmonotonic dI/dV curves. In the case of spin-polarized STM current, the spin orientation of the magnetic atom can be controlled parallel or antiparallel to the magnetic moment of the tip. Thus, spin-polarized STM tips can be used both to probe and to control the magnetic moment of a single atom.

Dynamic Visual Servoing With Chaos Control for Redundant Robots

This paper presents a new dynamic visual control system for redundant robots with chaos compensation. In order to implement the visual servoing system, a new architecture is proposed that improves the system maintainability and traceability. Furthermore, high performance is obtained as a result of parallel execution of the different tasks that compose the architecture. The control component of the architecture implements a new visual servoing technique for resolving the redundancy at the acceleration level in order to guarantee the correct motion of both end-effector and joints. The controller generates the required torques for the tracking of image trajectories. However, in order to guarantee the applicability of this technique, a repetitive path tracked by the robot-end must produce a periodic joint motion. A chaos controller is integrated in the visual servoing system and the correct performance is observed in low and high velocities. Furthermore, a method to adjust the chaos controller is proposed and validated using a real three-link robot.

Improving drug discovery using a neural networks based parallel scoring function

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface to find new hotspots, where ligands might potentially interact with, and which is implemented in massively parallel Graphics Processing Units, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to solve this problem, we propose a novel approach where neural networks are trained with databases of known active (drugs) and inactive compounds, and later used to improve VS predictions.

Dispersive liquid–liquid microextraction for metals enrichment: A useful strategy for improving sensitivity of laser-induced breakdown spectroscopy in liquid samples analysis

A rapid and efficient Dispersive Liquid–Liquid Microextraction (DLLME) followed by Laser-Induced Breakdown Spectroscopy detection (LIBS) was evaluated for simultaneous determination of Cr, Cu, Mn, Ni and Zn in water samples. Metals in the samples were extracted with tetrachloromethane as pyrrolidinedithiocarbamate (APDC) complexes, using vortex agitation to achieve dispersion of the extractant solvent. Several DLLME experimental factors affecting extraction efficiency were optimized with a multivariate approach. Under optimum DLLME conditions, DLLME-LIBS method was found to be of about 4.0–5.5 times more sensitive than LIBS, achieving limits of detection of about 3.7–5.6 times lower. To assess accuracy of the proposed DLLME-LIBS procedure, a certified reference material of estuarine water was analyzed.