470 research outputs found

    A Description of Multiscale Modeling for the Head-Disk Interface Focusing on Bottom-Level Lubricant and Carbon Overcoat Models

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    The challenges in designing future head disk interface (HDI) demand efficient theoretical modeling tools with flexibility in investigating various combinations of perfluoropolyether (PFPE) and carbon overcoat (COC) materials. For broad range of time and length scales, we developed multiscale/multiphysical modeling approach, which can bring paradigm-shifting improvements in advanced HDI design. In this paper, we introduce our multiscale modeling methodology with an effective strategic framework for the HDI system. Our multiscale methodology in this paper adopts a bottom to top approach beginning with the high-resolution modeling, which describes the intramolecular/intermolecular PFPE-COC degrees of freedom governing the functional oligomeric molecular conformations on the carbon surfaces. By introducing methodology for integrating atomistic/molecular/mesoscale levels via coarse-graining procedures, we investigated static and dynamic properties of PFPE-COC combinations with various molecular architectures. By bridging the atomistic and molecular scales, we are able to systematically incorporate first-principle physics into molecular models, thereby demonstrating a pathway for designing materials based on molecular architecture. We also discussed future materials (e.g., graphene for COC, star-like PFPEs) and systems (e.g., heat-assisted magnetic recording (HAMR)) with higher scale modeling methodology, which enables the incorporation of molecular/mesoscale information into the continuum scale models

    Accurate solution of Bayesian inverse uncertainty quantification problems combining reduced basis methods and reduction error models

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    Computational inverse problems related to partial differential equations (PDEs) often contain nuisance parameters that cannot be effectively identified but still need to be considered as part of the problem. The objective of this work is to show how to take advantage of a reduced order framework to speed up Bayesian inversion on the identifiable parameters of the system, while marginalizing away the (potentially large number of) nuisance parameters. The key ingredients are twofold. On the one hand, we rely on a reduced basis (RB) method, equipped with computable a posteriori error bounds, to speed up the solution of the forward problem. On the other hand, we develop suitable reduction error models (REMs) to quantify in an inexpensive way the error between the full-order and the reduced-order approximation of the forward problem, in order to gauge the effect of this error on the posterior distribution of the identifiable parameters. Numerical results dealing with inverse problems governed by elliptic PDEs in the case of both scalar parameters and parametric fields highlight the combined role played by RB accuracy and REM effectivity

    3-D multiobservable probabilistic inversion for the compositional and thermal structure of the lithosphere and upper mantle: III. Thermochemical tomography in the Western-Central U.S.

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    Acknowledgments We are indebted to F. Darbyshire and J. von Hunen for useful comments on earlier versions of this work. This manuscript benefited from thorough and constructive reviews by W. Levandowski and an anonymous reviewer. We also thank J. Connolly, M. Sambridge, B. Kennett, S. Lebedev, B. Shan, U. Faul, and M. Qashqai for insightful discussions about, and contributions to, some of the concepts presented in this paper. The work of J.C.A. has been supported by two Australian Research Council Discovery grants (DP120102372 and DP110104145). Seismic data are from the IRIS DMS. D.L.S. acknowledges support from NSF grant EAR-135866. This is contribution 848 from the ARC Centre of Excellence for Core to Crust Fluid Systems (http://www.ccfs.mq.edu.au) and 1106 in the GEMOC Key Centre (http://www.gemoc.mq.edu.au).Peer reviewedPublisher PD

    Implementation of an innovative teaching project in a Chemical Process Design course at the University of Cantabria, Spain

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    This paper shows the planning, the teaching activities and the evaluation of the learning and teaching process implemented in the Chemical Process Design course at the University of Cantabria, Spain. Educational methods to address the knowledge, skills and attitudes that students who complete the course are expected to acquire are proposed and discussed. Undergraduate and graduate engineers' perceptions of the methodology used are evaluated by means of a questionnaire. Results of the teaching activities and the strengths and weaknesses of the proposed case study are discussed in relation to the course characteristics. The findings of the empirical evaluation shows that the excessive time students had to dedicate to the case study project and dealing with limited information are the most negative aspects obtained, whereas an increase in the students' self-confidence and the practical application of the methodology are the most positive aspects. Finally, improvements are discussed in order to extend the application of the methodology to other courses offered as part of the chemical engineering degree.This work was partially supported with the financial help of the University of Cantabria, 1st and 2nd Teaching Innovation Programs 2011-2012, 2013-2014, Projects Innodesign 1 and 2

    Bilevel Parameter Learning for Higher-Order Total Variation Regularisation Models.

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    We consider a bilevel optimisation approach for parameter learning in higher-order total variation image reconstruction models. Apart from the least squares cost functional, naturally used in bilevel learning, we propose and analyse an alternative cost based on a Huber-regularised TV seminorm. Differentiability properties of the solution operator are verified and a first-order optimality system is derived. Based on the adjoint information, a combined quasi-Newton/semismooth Newton algorithm is proposed for the numerical solution of the bilevel problems. Numerical experiments are carried out to show the suitability of our approach and the improved performance of the new cost functional. Thanks to the bilevel optimisation framework, also a detailed comparison between TGV 2 and ICTV is carried out, showing the advantages and shortcomings of both regularisers, depending on the structure of the processed images and their noise level.King Abdullah University of Science and Technology (KAUST) (Grant ID: KUKI1-007-43), Engineering and Physical Sciences Research Council (Grant IDs: Nr. EP/J009539/1 “Sparse & Higher-order Image Restoration” and Nr. EP/M00483X/1 “Efficient computational tools for inverse imaging problems”), Escuela Politécnica Nacional de Quito (Grant ID: PIS 12-14, MATHAmSud project SOCDE “Sparse Optimal Control of Differential Equations”), Leverhulme Trust (project on “Breaking the non-convexity barrier”), SENESCYT (Ecuadorian Ministry of Higher Education, Science, Technology and Innovation) (Prometeo Fellowship)This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s10851-016-0662-

    Branch-and-lift algorithm for deterministic global optimization in nonlinear optimal control

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    This paper presents a branch-and-lift algorithm for solving optimal control problems with smooth nonlinear dynamics and potentially nonconvex objective and constraint functionals to guaranteed global optimality. This algorithm features a direct sequential method and builds upon a generic, spatial branch-and-bound algorithm. A new operation, called lifting, is introduced, which refines the control parameterization via a Gram-Schmidt orthogonalization process, while simultaneously eliminating control subregions that are either infeasible or that provably cannot contain any global optima. Conditions are given under which the image of the control parameterization error in the state space contracts exponentially as the parameterization order is increased, thereby making the lifting operation efficient. A computational technique based on ellipsoidal calculus is also developed that satisfies these conditions. The practical applicability of branch-and-lift is illustrated in a numerical example. © 2013 Springer Science+Business Media New York

    High-Utilisation Nanoplatinum Catalyst (Pt@cPIM) Obtained via Vacuum Carbonisation in a Molecularly Rigid Polymer of Intrinsic Microporosity

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    Polymers of intrinsic microporosity (PIM or here PIM-EA-TB) offer a highly rigid host environment into which hexachloroplatinate(IV) anions are readily adsorbed and vacuum carbonised (at 500 °C) to form active embedded platinum nanoparticles. This process is characterised by electron and optical microscopy, atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and electrochemical methods, which reveal that the PIM microporosity facilitates the assembly of nanoparticles of typically 1.0 to 2.5-nm diameter. It is demonstrated that the resulting carbonised “Pt@cPIM” from drop-cast films of ca. 550-nm average thickness, when prepared on tin-doped indium oxide (ITO), contain not only fully encapsulated but also fully active platinum nanoparticles in an electrically conducting hetero-carbon host. Alternatively, for thinner films (50–250 nm) prepared by spin coating, the particles become more exposed due to additional loss of the carbon host. In contrast to catalyst materials prepared by vacuum-thermolysed hexachloroplatinate(IV) precursor, the platinum nanoparticles within Pt@cPIM retain high surface area, electrochemical activity and high catalyst efficiency due to the molecular rigidity of the host. Data are presented for oxygen reduction, methanol oxidation and glucose oxidation, and in all cases, the high catalyst surface area is linked to excellent catalyst utilisation. Robust transparent platinum-coated electrodes are obtained with reactivity equivalent to bare platinum but with only 1 μg Pt cm−2 (i.e. ~100% active Pt nanoparticle surface is maintained in the carbonised microporous host). [Figure not available: see fulltext.

    Quantum mechanical studies of lincosamides

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    Lincosamides are a class of antibiotics used both in clinical and veterinary practice for a wide range of pathogens. This group of drugs inhibits the activity of the bacterial ribosome by binding to the 23S RNA of the large ribosomal subunit and blocking protein synthesis. Currently, three X-ray structures of the ribosome in complex with clindamycin are available in the Protein Data Bank, which reveal that there are two distinct conformations of the pyrrolidinyl propyl group of the bound clindamycin. In this work, we used quantum mechanical methods to investigate the probable conformations of clindamycin in order to explain the two binding modes in the ribosomal 23S RNA. We studied three lincosamide antibiotics: clindamycin, lincomycin, and pirlimycin at the B3LYP level with the 6-31G** basis set. The focus of our work was to connect the conformational landscape and electron densities of the two clindamycin conformers found experimentally with their physicochemical properties. For both functional conformers, we applied natural bond orbital (NBO) analysis and the atoms in molecules (AIM) theory, and calculated the NMR parameters. Based on the results obtained, we were able to show that the structure with the intramolecular hydrogen bond C=O…H–O is the most stable conformer of clindamycin. The charge transfer between the pyrrolidine-derivative ring and the six-atom sugar (methylthiolincosamide), which are linked via an amide bond, was found to be the dominant factor influencing the high stability of this conformer

    The modulating effect of education on semantic interference during healthy aging

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    Aging has traditionally been related to impairments in name retrieval. These impairments have usually been explained by a phonological transmission deficit hypothesis or by an inhibitory deficit hypothesis. This decline can, however, be modulated by the educational level of the sample. This study analyzed the possible role of these approaches in explaining both object and face naming impairments during aging. Older adults with low and high educational level and young adults with high educational level were asked to repeatedly name objects or famous people using the semantic-blocking paradigm. We compared naming when exemplars were presented in a semantically homogeneous or in a semantically heterogeneous context. Results revealed significantly slower rates of both face and object naming in the homogeneous context (i.e., semantic interference), with a stronger effect for face naming. Interestingly, the group of older adults with a lower educational level showed an increased semantic interference effect during face naming. These findings suggest the joint work of the two mechanisms proposed to explain age-related naming difficulties, i.e., the inhibitory deficit and the transmission deficit hypothesis. Therefore, the stronger vulnerability to semantic interference in the lower educated older adult sample would possibly point to a failure in the inhibitory mechanisms in charge of interference resolution, as proposed by the inhibitory deficit hypothesis. In addition, the fact that this interference effect was mainly restricted to face naming and not to object naming would be consistent with the increased age-related difficulties during proper name retrieval, as suggested by the transmission deficit hypothesis.This research was supported by grants PSI2013-46033-P to A.M., PSI2015-65502-C2-1-P to M.T.B., PCIN-2015-165-C02-01 to D.P., PSI2017-89324-C2-1-P to DP from the Spanish Ministry of Economy and Competitiveness (http://www.mineco.gob.es/)
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