Academic literature on the topic 'Ab initio prediction'

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Dissertations / Theses on the topic "Ab initio prediction"

1

Thomas, Geraint Llewllyn. "Ab initio protein fold prediction." Thesis, University of Leeds, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436019.

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2

Meyer, Irmtraud Margret. "Mathematical methods for comparative Ab initio gene prediction." Thesis, University of Cambridge, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.619669.

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3

Djurdjević, Dušan. "Ab initio protein fold prediction using evolutionary algorithms." Thesis, University of Edinburgh, 2006. http://hdl.handle.net/1842/13660.

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A comprehensive study was undertaken for <i>ab initio </i>protein fold prediction using a fully atomistic protein model and a physicochemical potential. Twenty four EA designs where initially assessed on polyalanine, a prototypical α-helical polypeptide.  Design aspects varied include the encoding alphabet, crossover operator, replacement strategy and selection strategy. By undertaking a comprehensive parameter study, the best performing designs and associated control parameter values were identified for polyalanine. The scaling between the performance and polyalinine size was also identified
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4

Wang, Guisheng. "Ab initio prediction of the mechanical properties of alloys." Doctoral thesis, KTH, Tillämpad materialfysik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169511.

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At the time of the 50th anniversary of the Kohn-Sham method, ab initio calculations based on density functional theory have formed an accurate, efficient, and reliable method to work on the properties of engineering materials. In this thesis, we use the exact muffin-tin orbitals method combined with the coherent-potential approximation to study the mechanical properties of high-technology materials. The thesis includes two parts: a study of long-range chemical order effects and a study of alloying effects on the mechanical properties of alloys. In the first part, we concentrate on the impact o
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5

Kang, ShinYoung. "Ab initio prediction of thermodynamics in alkali metal-air batteries." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/89952.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Materials Science and Engineering, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 93-100).<br>Electric vehicles ("EVs") require high-energy-density batteries with reliable cyclability and rate capability. However, the current state-of-the-art Li-ion batteries only exhibit energy densities near ~150 Wh/kg, limiting the long-range driving of EVs with one charge and hindering their wide-scale commercial adoption.1-3 Recently, non-aqueous metal-O₂ batteries have drawn attention due to
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6

Mijajlovic, Milan. "Ab initio prediction of the conformation of solvated and adsorbed proteins." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/3173.

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Proteins are among the most important groups of biomolecules, with their biological functions ranging from structural elements to signal transducers between cells. Apart from their biological role, phenomena related to protein behaviour in solutions and at solid interfaces can find a broad range of engineering applications such as in biomedical implants, scaffolds for artificial tissues, bioseparations, biomineralization and biosensors. For both biological and engineering applications, the functionality of a protein is directly related to its three-dimensional structure (i.e. conformation). Me
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7

DePristo, Mark Andrew. "Ab initio conformational sampling for protein structure determination, analysis, and prediction." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615942.

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8

Simons, Kim T. "Deciphering the protein folding code : ab initio prediction of protein structure /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/9234.

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9

Shi, Jingming. "Ab initio prediction of crystalline phases and their electronic properties : from ambient to extreme pressures." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE1110/document.

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Dans cette thèse nous utilisons des méthodes globaux de prédiction des structures cristallographiques combinés à des techniques de grande capacité de traitement de données afin de prédire la structure cristalline de différents systèmes et dans des conditions thermodynamiques variées. Nous avons réalisé des prédictions structurales utilisant l'analyse cristalline par optimisation par essaims particuliers (CALYPSO) combinés avec la Théorie Fonctionnel de la Densité (DFT) ce qui a permis de mettre en évidence la stabilité de plusieurs composés jusqu'à la inconnus dans le digramme de phases du sys
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10

McLean, Malcolm Arthur. "Potential energy functions and search routines for ab initio protein structure prediction." Thesis, University of Leeds, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.522963.

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