Prediction of the Size Distributions of Methanol-Ethanol Clusters Detected in VUV Laser/Time-of-flight Mass Spectrometry

The size distributions and geometries of vapor clusters equilibrated with methanol−ethanol (Me−Et) liquid mixtures were recently studied by vacuum ultraviolet (VUV) laser time-of-flight (TOF) mass spectrometry and density functional theory (DFT) calculations (Liu, Y.; Consta, S.; Ogeer, F.; Shi, Y. J.; Lipson, R. H. Can. J. Chem. 2007, 85, 843−852). On the basis of the mass spectra recorded, it was concluded that the formation of neutral tetramers is particularly prominent. Here we develop grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) frameworks to compute cluster size distributions in vapor mixtures that allow a direct comparison with experimental mass spectra. Using the all-atom optimized potential for liquid simulations (OPLS-AA) force field, we systematically examined the neutral cluster size distributions as functions of pressure and temperature. These neutral cluster distributions were then used to derive ionized cluster distributions to compare directly with the experiments. The simulations suggest that supersaturation at 12 to 16 times the equilibrium vapor pressure at 298 K or supercooling at temperature 240 to 260 K at the equilibrium vapor pressure can lead to the relatively abundant tetramer population observed in the experiments. Our simulations capture the most distinct features observed in the experimental TOF mass spectra: Et3H+ at m/z = 139 in the vapor corresponding to 10:90% Me−Et liquid mixture and Me3H+ at m/z = 97 in the vapors corresponding to 50:50% and 90:10% Me−Et liquid mixtures. The hybrid GCMC scheme developed in this work extends the capability of studying the size distributions of neat clusters to mixed species and provides a useful tool for studying environmentally important systems such as atmospheric aerosols

Universal Robotic Gripper based on the Jamming of Granular Material

Gripping and holding of objects are key tasks for robotic manipulators. The development of universal grippers able to pick up unfamiliar objects of widely varying shape and surface properties remains, however, challenging. Most current designs are based on the multi-fingered hand, but this approach introduces hardware and software complexities. These include large numbers of controllable joints, the need for force sensing if objects are to be handled securely without crushing them, and the computational overhead to decide how much stress each finger should apply and where. Here we demonstrate a completely different approach to a universal gripper. Individual fingers are replaced by a single mass of granular material that, when pressed onto a target object, flows around it and conforms to its shape. Upon application of a vacuum the granular material contracts and hardens quickly to pinch and hold the object without requiring sensory feedback. We find that volume changes of less than 0.5% suffice to grip objects reliably and hold them with forces exceeding many times their weight. We show that the operating principle is the ability of granular materials to transition between an unjammed, deformable state and a jammed state with solid-like rigidity. We delineate three separate mechanisms, friction, suction and interlocking, that contribute to the gripping force. Using a simple model we relate each of them to the mechanical strength of the jammed state. This opens up new possibilities for the design of simple, yet highly adaptive systems that excel at fast gripping of complex objects.Comment: 10 pages, 7 figure

Exciton- and Light-induced Current in Molecular Nanojunctions

We consider exciton- and light-induced current in molecular nanojunctions. Using a model comprising a two two-level sites bridge connecting free electron reservoirs we show that the exciton coupling between the sites of the molecular bridge can markedly effect the source-drain current through a molecular junction. In some cases when excited and unexcited states of the sites are coupled differently to the leads, the contribution from electron-hole excitations can exceed the Landauer elastic current and dominate the observed conduction. We have proposed an optical control method using chirped pulses for enhancing charge transfer in unbiased junctions where the bridging molecule is characterized by a strong charge-transfer transition.Comment: 8 pages, 2 figures,submitted to the Canadian J. Phy

Open-Ended Evolutionary Robotics: an Information Theoretic Approach

This paper is concerned with designing self-driven fitness functions for Embedded Evolutionary Robotics. The proposed approach considers the entropy of the sensori-motor stream generated by the robot controller. This entropy is computed using unsupervised learning; its maximization, achieved by an on-board evolutionary algorithm, implements a "curiosity instinct", favouring controllers visiting many diverse sensori-motor states (sms). Further, the set of sms discovered by an individual can be transmitted to its offspring, making a cultural evolution mode possible. Cumulative entropy (computed from ancestors and current individual visits to the sms) defines another self-driven fitness; its optimization implements a "discovery instinct", as it favours controllers visiting new or rare sensori-motor states. Empirical results on the benchmark problems proposed by Lehman and Stanley (2008) comparatively demonstrate the merits of the approach

Complex networks theory for analyzing metabolic networks

One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism, while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.Comment: 13 pages, 2 figure

Deformable Model for 3D Intramodal Nonrigid Breast Image Registration with Fiducial Skin Markers

We implemented a new approach to intramodal non-rigid 3D breast image registration. Our method uses fiducial skin markers (FSM) placed on the breast surface. After determining the displacements of FSM, finite element method (FEM) is used to distribute the markers’ displacements linearly over the entire breast volume using the analogy between the orthogonal components of the displacement field and a steady state heat transfer (SSHT). It is valid because the displacement field in x, y and z direction and a SSHT problem can both be modeled using LaPlace’s equation and the displacements are analogous to temperature differences in SSHT. It can be solved via standard heat conduction FEM software with arbitrary conductivity of surface elements significantly higher than that of volume elements. After determining the displacements of the mesh nodes over the entire breast volume, moving breast volume is registered to target breast volume using an image warping algorithm. Very good quality of the registration was obtained. Following similarity measurements were estimated: Normalized Mutual Information (NMI), Normalized Correlation Coefficient (NCC) and Sum of Absolute Valued Differences (SAVD). We also compared our method with rigid registration technique

Perfect imaging: they don't do it with mirrors

Imaging with a spherical mirror in empty space is compared with the case when the mirror is filled with the medium of Maxwell's fish eye. Exact time-dependent solutions of Maxwell's equations show that perfect imaging is not achievable with an electrical ideal mirror on its own, but with Maxwell's fish eye in the regime when it implements a curved geometry for full electromagnetic waves

Soft Robotics. Bio-inspired Antagonistic Stiffening

Soft robotic structures might play a major role in the 4th industrial revolution. Researchers have demonstrated advantages of soft robotics over traditional robots made of rigid links and joints in several application areas including manufacturing, healthcare, and surgical interventions. However, soft robots have limited ability to exert larger forces and change their stiffness on demand over a wide range. Stiffness can be achieved as a result of the equilibrium of an active and a passive reaction force or of two active forces antagonistically collaborating. This paper presents a novel design paradigm for a fabric-based Variable Stiffness System including potential applications