Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 116 for “"Force Fields"”.
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Quantum Mechanically Derived Biomolecular Force Fields
Molecular mechanics force fields are used to understand and predict a wide range of biological phenomena. However, current biomolecular force fields assume that parameters must be fit to the properties of small molecules and subsequently transferred to model large proteins. Here, we look to …
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Development of polarizable force fields for proteins
… describes the development of the polarizable force field for proteins based on classical mechanics, electronic structure theory and the combined quantum mechanical molecular mechanical method. In the first model, the classical force field is augmented with the explicit polarization energy term …
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Optimization of force fields for molecular dynamics
… are modeled with the usual functional form of a force field. We then apply the newly developed technology to study the liquid mixture of tert-butanol and water. We are able to obtain, after 4 iterations, the correct phase behavior and accurately predict the value of the Kirkwood Buff (KB) …
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Machine Learning Force Fields for Molecular Chemistry
… time scales. The traditional alternative is force fields that enable fast and accurate simulations by bypassing the treatment of the electrons and describing the system solely in terms of the atomic positions. The emergence of machine learning tools has opened up the opportunity for the …
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Machine learning force fields for elemental sulphur
… task, out of the reach of any current force fields (which are too inaccurate) or quantum mechanical methods (which are too slow and expensive). However, following the footsteps of similar work done on silicon, phosphorus and carbon, surrogate machine learning models mimicking quantum …
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Audiogravic illusion induced by acceleratory force fields
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.
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Learning symmetry-preserving interatomic force fields for atomistic simulations
Machine-Learning Interatomic Force-Fields have shown great promise in increasing time- and length-scales in atomistic simulations while retaining the high accuracy of the reference calculations that they are trained on. Most proposed models aim to learn the potential energy surface of a system of …
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Learning force fields for limb control in character animation
… physically simulated character animation. Vector fields of joint torques, defined over joint angle space, have been shown in the neuroscience literature to be able to generate simple reaching motions in two dimensions when linearly combined with time-varying weights. In this work, …
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Quartic Force Fields for Electronically Excited States of Interstellar Molecules
… to high-accuracy experimental results. Quartic force field (QFFs) methods are one of the most efficient means of generating this data and have even shown spectroscopic accuracy (±1 cm−1) for fundamental vibrational frequencies. A method for extending QFFs to variationally inaccessible …
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Machine Learning Force Fields for Modelling Reactions at Complex Interfaces
… So-called machine learning force fields (MLFFs) predict energies and forces on atomic configurations at near quantum mechanical accuracy with orders-of-magnitude reduction in computational cost. %compared to the reference method Furthermore, under the assumption of locality, …
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Modeling larger length and time scales in machine learning force fields
… is determined by the accuracy of the interatomic forces. These forces can be obtained from fast but approximate empirical force fields, or slow but accurate quantum mechanical methods. Machine learning force fields have emerged as a promising alternative, bridging this gap by approximating …
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Comparative evaluation of two carbohydrate force fields for modelling polysaccharide conformation
… GLYCAM06 and other widely used carbohydrate force fields. This thesis investigates the scope and origin of these differences. We compare Molecular Dynamics simulations of strategically selected saccharide chains, with both the GLYCAM06 and CHARMM36 carbohydrate force fields. We find …
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Contracting force fields in robot navigation and extension to other problems
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2000.
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Spectra at speed: neural force fields for IR spectroscopy in ionic liquids
… and intensities. Machine learning (ML)–based force fields offer a promising alternative, delivering both accuracy and efficiency. Yet most are trained on isolated molecules, neglecting condensed-phase effects, long-range correlations, or electronic polarization. Furthermore, accurate IR …
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Machine learning transferable physics-based force fields using graph convolutional neural networks
… cheaper functional form. Classical force field (CFF) approaches simply define the PES as a sum over independent energy contributions. Commonly included terms include bonded (pair, angle, dihedral, etc.) and non bonded (van der Waals, Coulomb, etc.) interactions, while more recent …
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Investigating the effects of different force fields on spring-based normal mode analysis
… model for proteins and an all-atom empirical force field to maintain accuracy while reducing the computing complexity by eliminating the minimization step. In the previous work on sbNMA, only the CHARMM force field was explored. In this work, we extend the analyses to AMBER, another …
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Predicting the Hydration Free Energy of Small Alkanes and Alcohols from Custom, Electronic Structure-Based Force Fields
… computations of quantum mechanical (QM) forces and classical simulations based on these forces, I investigate models to predict several properties of solutes and solutions. This dissertation is a collection of projects exemplifying methods used to gain insight into chemical systems. </p> …
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Computational analysis of Escherichia coli O25 and O25b carbohydrate antigens using the CHARMM36 and GLYCAM06 force fields
… dependent on the quality of the selected force field. Carbohydrate force fields have matured over the past few decades and CHARMM36 and GLYCAM06 are used extensively for the analysis of bacterial polysaccharides. Studies that compare results from these two widely used force fields are, …
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Semi-empirical and machine learned interatomic interaction potentials for zirconium: training, validation and application
… interaction potentials--also known as force fields--is the main factor determining the physical soundness of molecular dynamics simulations and kinetic Monte Carlo simulations. Zirconium (Zr) is widely utilized in structural components of CANDU nuclear reactors. In this thesis, …
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Force Field Development With Gomc A Fast New Monte Carlo Molecular Simulation Code
… simulation in the Gibbs ensemble is presented. Force fields developed using the code are also presented. To fit the models a quantitative fitting process is outlined using a scoring function and heat maps. The presented n-6 force fields include force fields for noble gases and branched alkanes. …
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