Thermodynamics of Surface Defects at the Aspirin/Water Interface

We present a simulation scheme to calculate defect formation free energies at a molecular crystal/water interface based on force-field molecular dynamics (MD) simulations. To this end we adopt and modify existing approaches to calculate binding free energies of biological ligand/receptor complexes to be applicable to common surface defects, such as step edges and kink sites. We obtain statistically accurate and reliable free energy values for the aspirin/water interface, which can be applied to estimate the distribution of defects using well-established thermodynamic relations. As a show case we calculate the free energy upon dissolving molecules from kink sites at the interface. This free energy can be related to the solubility concentration and we obtain solubility values in excellent agreement with experimental results.Comment: 12 pages, 5 figure

The Case for Community Colleges: Aligning Higher Education and Workforce Needs in Massachusetts

Reviews research on the need for middle-skilled workers with at least an associate's degree, Massachusetts' community college system, promising models for aligning community college curricula with workforce needs, and challenges. Makes recommendations

Molecular Dynamics Simulations of Biological Molecules on the Natively Oxidized Titanium Surface

In order to investigate the surface properties of metals in a realistic fashion it is crucial to take into account the thin oxide layer that forms spontaneously when the surface is exposed to an oxidising environment. Starting from reference oxide layer structures obtained in extensive first-principles molecular dynamics simulations, we have developed a novel classical potential which is able to reproduce the topological binding features of the amorphous oxide network on Ti as well as the interfacial behaviour of the TiOx/water interface. By combination of this specific potential with well-established biomolecular force fields, we have performed classical simulations of small organic molecules on the oxide surface and successfully compared their results to DFT calculations. The final model is applied to elucidate the microscopic mechanisms that take place at experimentally relevant bio-interfaces. In particular, we focus on the titanium-binding peptide motif minTBP-1. By using advanced simulation techniques, such as metadynamics, replica exchange molecular dynamics, as well as steered molecular dynamics, we have quantified the adhesion strength to the oxidized titanium surface and to the oxidized silicon surface in excellent agreement with experimental results. A microscopical analysis of the simulations reveals that the stronger adhesion to titanium compared to silicon is primarily caused by differences in the interfacial water structure. Furthermore, we have employed the model to calculate the contact forces between two water-covered titania nanoparticles and compared the results to the findings from AFM experiments

Position control of an industrial robot using an optical measurement system for machining purposes

A series of mechanical properties and disturbances limit the accuracy achievable in robotic applications. External control of the end effector position is commonly known as being an appropriate mean to increase accuracy. This paper presents an approach for position control of industrial robots using the pass-through between an industrial CNC and servomotors. A CNC-controlled robot is used together with an external optical measurement system to close the feedback loop of robot end effector and robot controller in order to improve robot accuracy. For short cycle times and implementation reasons a PLC is used for signal processing and control implementation. The relevance of the approach is outlined in experiments. The robot behaviour in free space motion and in machining application is analysed with the optical measurement system and a CMM

Deliverable 2 (SustainAQ)

The European Project SustainAQ (Framework 6) aims to identify the limiting factors for the sustainable production of aquatic origin food in Eastern Europe. It focuses on the possible use of Recirculation Aquaculture Systems (RAS) as sustainable method for the production of aquatic animals as mentioned in the communication of the European Commission on Aquaculture in 2009. RASs already exist mainly in western countries and proved economically feasible. RASs allow controlling the production process including effluents, biosecurity and escapes. Eastern European countries are facing challenges related to their excessive water use waste emission, and others. Therefore, these countries are potential beneficiaries of improved sustainability through RAS use. This project intends to assess the benefits of introducing and applying RAS for Eastern European aquaculture. This project involves three Western European countries (Norway, the Netherlands and France) and six East European countries (Croatia, Turkey, Romania, Hungary, Czech Republic and Poland). Ten research institutions collaborate in different tasks (coordination, data collection, data analysis, etc.), and nine small-medium enterprises (SME) participate in data mining (Table 1). The present data is therefore based on the situation in those countries during 2006 till 2008 before the report got finally compiled in 2008/2009

Long short-term memory networks enhance rainfall-runoff modelling at the national scale of Denmark

This study explores the application of long short-term memory (LSTM) networks to simulate runoff at the national scale of Denmark using data from 301 catchments. This is the first LSTM application on Danish data. The results were benchmarked against the Danish national water resources model (DK-model), a physically based hydrological model. The median Kling-Gupta Efficiency (KGE), a common metric to assess performance of runoff predictions (optimum of 1), increased from 0.7 (DK-model) to 0.8 (LSTM) when trained against all catchments. Overall, the LSTM outperformed the DK-model in 80% of catchments. Despite the compelling KGE evaluation, the water balance closure was modelled less accurately by the LSTM. The applicability of LSTM networks for modelling ungauged catchments was assessed via a spatial split-sample experiment. A 20% spatial hold-out showed poorer performance of the LSTM with respect to the DK model. However, after pre-training, that is, weight initialisation obtained from training against simulated data from the DK-model, the performance of the LSTM was effectively improved. This formed a convincing argument supporting the knowledge-guided machine learning (ML) paradigm to integrate physically based models and ML to train robust models that generalise well

On the Phase Space of Fourth-Order Fiber-Orientation Tensors

Fiber-orientation tensors describe the relevant features of the fiber-orientation distribution compactly and are thus ubiquitous in injection-molding simulations and subsequent mechanical analyses. In engineering applications to date, the second-order fiber-orientation tensor is the basic quantity of interest, and the fourth-order fiber-orientation tensor is obtained via a closure approximation. Unfortunately, such a description limits the predictive capabilities of the modeling process significantly, because the wealth of possible fourth-order fiber-orientation tensors is not exploited by such closures, and the restriction to second-order fiber-orientation tensors implies artifacts. Closures based on the second-order fiber-orientation tensor face a fundamental problem – which fourth-order fiber-orientation tensors can be realized? In the literature, only necessary conditions for a fiber-orientation tensor to be connected to a fiber-orientation distribution are found. In this article, we show that the typically considered necessary conditions, positive semidefiniteness and a trace condition, are also sufficient for being a fourth-order fiber-orientation tensor in the physically relevant case of two and three spatial dimensions. Moreover, we show that these conditions are not sufficient in higher dimensions. The argument is based on convex duality and a celebrated theorem of D. Hilbert (1888) on the decomposability of positive and homogeneous polynomials of degree four. The result has numerous implications for modeling the flow and the resulting microstructures of fiber-reinforced composites, in particular for the effective elastic constants of such materials. Based on our findings, we show how to connect optimization problems on fourth-order fiber-orientation tensors to semi-definite programming. The proposed formulation permits to encode symmetries of the fiber-orientation tensor naturally. As an application, we look at the differences between orthotropic and general, i.e., triclinic, fiber-orientation tensors of fourth order in two and three spatial dimensions, revealing the severe limitations inherent to orthotropic closure approximations