Academic literature on the topic 'Computational physics|Computational chemistry'

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Journal articles on the topic "Computational physics|Computational chemistry"

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Houk, K. N., and Peng Liu. "Using Computational Chemistry to Understand & Discover Chemical Reactions." Daedalus 143, no. 4 (October 2014): 49–66. http://dx.doi.org/10.1162/daed_a_00305.

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Chemistry, the “science of matter,” is the investigation of the fabulously complex interchanges of atoms and bonds that happen constantly throughout our universe and within all living things. Computational chemistry is the computer modeling of chemistry using mathematical equations that come from physics. The field was made possible by advances in computer algorithms and computer power and continues to flourish in step with developments in those areas. Computational chemistry can be thought of as both a time-lapse video that slows down processes by a quadrillion-fold and an ultramicroscope that provides a billion-fold magnification. Computational chemists can quantitatively simulate simple chemistry, such as the chemical reactions between molecules in interstellar space. The chemistry inside a living organism is dramatically more complicated and cannot be simulated exactly, but even here computational chemistry enables understanding and leads to discovery of previously unrecognized phenomena. This essay describes how computational chemistry has evolved into a potent force for progress in chemistry in the twenty-first century.
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Schneider, Barry I. "Looking Back at 45 Years of Computational Physics and Chemistry." Computing in Science & Engineering 19, no. 5 (2017): 4–5. http://dx.doi.org/10.1109/mcse.2017.3421543.

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Alonso, Pedro, Ian P. Hamilton, and J. Vigo-Aguiar. "Mathematical and computational methods with applications in chemistry and physics." Journal of Mathematical Chemistry 48, no. 1 (February 14, 2010): 95–97. http://dx.doi.org/10.1007/s10910-010-9661-y.

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Mignon, David, Karen Druart, Eleni Michael, Vaitea Opuu, Savvas Polydorides, Francesco Villa, Thomas Gaillard, Nicolas Panel, Georgios Archontis, and Thomas Simonson. "Physics-Based Computational Protein Design: An Update." Journal of Physical Chemistry A 124, no. 51 (November 10, 2020): 10637–48. http://dx.doi.org/10.1021/acs.jpca.0c07605.

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Mazumder, Sandip. "Modeling Full-Scale Monolithic Catalytic Converters: Challenges and Possible Solutions." Journal of Heat Transfer 129, no. 4 (July 24, 2006): 526–35. http://dx.doi.org/10.1115/1.2709655.

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Modeling full-scale monolithic catalytic converters using state-of-the-art computational fluid dynamics algorithms and techniques encounters a classical multiscale problem: the channels within the monolith have length scales that are ∼1–2 mm, while the converter itself has a length scale that is ∼5–10 cm. This necessitates very fine grids to resolve all the length scales, resulting in few million computational cells. When complex heterogeneous chemistry is included, the computational problem becomes all but intractable unless massively parallel computation is employed. Two approaches to address this difficulty are reviewed, and their effectiveness demonstrated for the computation of full-scale catalytic converters with complex chemistry. The first approach is one where only the larger scales are resolved by a grid, while the physics at the smallest scale (channel scale) are modeled using subgrid scale models whose development entails detailed flux balances at the “imaginary” fluid–solid interfaces within each computational cell. The second approach makes use of the in situ adaptive tabulation algorithm, after significant reformulation of the underlying mathematics, to accelerate computation of the surface reaction boundary conditions. Preliminary results shown here for a catalytic combustion application involving 19 species and 24 reactions indicate that both methods have the potential of improving computational efficiency by several orders of magnitude.
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Fujisaki, Hiroshi. "Physics and Chemistry Based Computational Approach to Conformational Change of Biomolecules." Nihon Ika Daigaku Igakkai Zasshi 9, no. 4 (2013): 202–6. http://dx.doi.org/10.1272/manms.9.202.

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Koch, Wolfram. "Buchbesprechung: Computational Methods in Physics, Chemistry and Biology. Von Paul Harrison." Angewandte Chemie 114, no. 14 (July 15, 2002): 2726–27. http://dx.doi.org/10.1002/1521-3757(20020715)114:14<2726::aid-ange2726>3.0.co;2-8.

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Fujisaki, Hiroshi. "Physics- and Chemistry-based Computational Approaches to Ligand Binding for Proteins." Nihon Ika Daigaku Igakkai Zasshi 9, no. 2 (2013): 135–39. http://dx.doi.org/10.1272/manms.9.135.

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Oberkampf, William L., Timothy G. Trucano, and Charles Hirsch. "Verification, validation, and predictive capability in computational engineering and physics." Applied Mechanics Reviews 57, no. 5 (September 1, 2004): 345–84. http://dx.doi.org/10.1115/1.1767847.

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Developers of computer codes, analysts who use the codes, and decision makers who rely on the results of the analyses face a critical question: How should confidence in modeling and simulation be critically assessed? Verification and validation (V&V) of computational simulations are the primary methods for building and quantifying this confidence. Briefly, verification is the assessment of the accuracy of the solution to a computational model. Validation is the assessment of the accuracy of a computational simulation by comparison with experimental data. In verification, the relationship of the simulation to the real world is not an issue. In validation, the relationship between computation and the real world, ie, experimental data, is the issue. This paper presents our viewpoint of the state of the art in V&V in computational physics. (In this paper we refer to all fields of computational engineering and physics, eg, computational fluid dynamics, computational solid mechanics, structural dynamics, shock wave physics, computational chemistry, etc, as computational physics.) We describe our view of the framework in which predictive capability relies on V&V, as well as other factors that affect predictive capability. Our opinions about the research needs and management issues in V&V are very practical: What methods and techniques need to be developed and what changes in the views of management need to occur to increase the usefulness, reliability, and impact of computational physics for decision making about engineering systems? We review the state of the art in V&V over a wide range of topics, for example, prioritization of V&V activities using the Phenomena Identification and Ranking Table (PIRT), code verification, software quality assurance (SQA), numerical error estimation, hierarchical experiments for validation, characteristics of validation experiments, the need to perform nondeterministic computational simulations in comparisons with experimental data, and validation metrics. We then provide an extensive discussion of V&V research and implementation issues that we believe must be addressed for V&V to be more effective in improving confidence in computational predictive capability. Some of the research topics addressed are development of improved procedures for the use of the PIRT for prioritizing V&V activities, the method of manufactured solutions for code verification, development and use of hierarchical validation diagrams, and the construction and use of validation metrics incorporating statistical measures. Some of the implementation topics addressed are the needed management initiatives to better align and team computationalists and experimentalists in conducting validation activities, the perspective of commercial software companies, the key role of analysts and decision makers as code customers, obstacles to the improved effectiveness of V&V, effects of cost and schedule constraints on practical applications in industrial settings, and the role of engineering standards committees in documenting best practices for V&V. There are 207 references cited in this review article.
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Koch, Wolfram. "Book Review: Computational Methods in Physics, Chemistry and Biology. By Paul Harrison." Angewandte Chemie International Edition 41, no. 13 (July 3, 2002): 2416. http://dx.doi.org/10.1002/1521-3773(20020703)41:13<2416::aid-anie2416>3.0.co;2-w.

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Dissertations / Theses on the topic "Computational physics|Computational chemistry"

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Tsai, Carol Leanne. "Heuristic Algorithms for Agnostically Identifying the Globally Stable and Competitive Metastable Morphologies of Block Copolymer Melts." Thesis, University of California, Santa Barbara, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13423067.

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Block copolymers are composed of chemically distinct polymer chains that can be covalently linked in a variety of sequences and architectures. They are ubiquitous as ingredients of consumer products and also have applications in advanced plastics, drug delivery, advanced membranes, and next generation nano-lithographic patterning. The wide spectrum of possible block copolymer applications is a consequence of block copolymer self-assembly into periodic, meso-scale morphologies as a function of varying block composition and architecture in both melt and solution states, and the broad spectrum of physical properties that such mesophases afford.

Materials exploration and discovery has traditionally been pursued through an iterative process between experimental and theoretical/computational collaborations. This process is often implemented in a trial-and-error fashion, and from the computational perspective of generating phase diagrams, usually requires some existing knowledge about the competitive phases for a given system. Self-Consistent Field Theory (SCFT) simulations have proven to be both qualitatively and quantitatively accurate in the determination, or forward mapping, of block copolymer phases of a given system. However, it is possible to miss candidates. This is because SCFT simulations are highly dependent on their initial configurations, and the ability to map phase diagrams requires a priori knowledge of what the competing candidate morphologies are. The unguided search for the stable phase of a block copolymer of a given composition and architecture is a problem of global optimization. SCFT by itself is a local optimization method, so we can combine it with population-based heuristic algorithms geared at global optimization to facilitate forward mapping. In this dissertation, we discuss the development of two such methods: Genetic Algorithm + SCFT (GA-SCFT) and Particle Swarm Optimization + SCFT (PSO-SCFT). Both methods allow a population of configurations to explore the space associated with the numerous states accessible to a block copolymer of a given composition and architecture.

GA-SCFT is a real-space method in which a population of SCFT field configurations “evolves” over time. This is achieved by initializing the population randomly, allowing the configurations to relax to local basins of attraction using SCFT simulations, then selecting fit members (lower free energy structures) to recombine their fields and undergo mutations to generate a new “generation” of structures that iterate through this process. We present results from benchmark testing of this GA-SCFT technique on the canonical AB diblock copolymer melt, for which the theoretical phase diagram has long been established. The GA-SCFT algorithm successfully predicts many of the conventional mesophases from random initial conditions in large, 3-dimensional simulation cells, including hexagonally-packed cylinders, BCC-packed spheres, and lamellae, over a broad composition range and weak to moderate segregation strength. However, the GA-SCFT method is currently not effective at discovery of network phases, such as the Double-Gyroid (GYR) structure.

PSO-SCFT is a reciprocal space approach in which Fourier components of SCFT fields near the principal shell are manipulated. Effectively, PSO-SCFT facilitates the search through a space of reciprocal-space SCFT seeds which yield a variety of morphologies. Using intensive free energy as a fitness metric by which to compare these morphologies, the PSO-SCFT methodology allows us to agnostically identify low-lying competitive and stable morphologies. We present results for applying PSO-SCFT to conformationally symmetric diblock copolymers and a miktoarm star polymer, AB4, which offers a rich variety of competing sphere structures. Unlike the GA-SCFT method we previously presented, PSO-SCFT successfully predicts the double gyroid morphology in the AB-diblock. Furthermore, PSO-SCFT successfully recovers the A 15 morphology at a composition where it is expected to be stable in the miktoarm system, as well as several competitive metastable candidates, and a new sphere morphology belonging to the hexagonal space group 191, which has not been seen before in polymer systems. Thus, we believe the PSO-SCFT method provides a promising platform for screening for competitive structures in a given block copolymer system.

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Sponseller, Daniel Ray. "Molecular Dynamics Study of Polymers and Atomic Clusters." Thesis, George Mason University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10685723.

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This dissertation contains investigations based on Molecular Dynamics (MD) of a variety of systems, from small atomic clusters to polymers in solution and in their condensed phases. The overall research is divided in three parts. First, I tested a new thermostat in the literature on the thermal equilibration of a small cluster of Lennard-Jones (LJ) atoms. The proposed thermostat is a Hamiltonian thermostat based on a logarithmic oscillator with the outstanding property that the mean value of its kinetic energy is constant independent of the mass and energy. I inspected several weak-coupling interaction models between the LJ cluster and the logarithmic oscillator in 3D. In all cases I show that this coupling gives rise to a kinetic motion of the cluster center of mass without transferring kinetic energy to the interatomic vibrations. This is a failure of the published thermostat because the temperature of the cluster is mainly due to vibrations in small atomic clusters This logarithmic oscillator cannot be used to thermostat any atomic or molecular system, small or large.

The second part of the dissertation is the investigation of the inherent structure of the polymer polyethylene glycol (PEG) solvated in three different solvents: water, water with 4% ethanol, and ethyl acetate. PEG with molecular weight of 2000 Da (PEG2000) is a polymer with many applications from industrial manufacturing to medicine that in bulk is a paste. However, its structure in very dilute solutions deserved a thorough study, important for the onset of aggregation with other polymer chains. I introduced a modification to the GROMOS 54A7 force field parameters for modeling PEG2000 and ethyl acetate. Both force fields are new and have now been incorporated into the database of known residues in the molecular dynamics package Gromacs. This research required numerous high performance computing MD simulations in the ARGO cluster of GMU for systems with about 100,000 solvent molecules. My findings show that PEG2000 in water acquires a ball-like structure without encapsulating solvent molecules. In addition, no hydrogen bonds were formed. In water with 4% ethanol, PEG2000 acquires also a ball-like structure but the polymer ends fluctuate folding outward and onward, although the general shape is still a compact ball-like structure.

In contrast, PEG2000 in ethyl acetate is quite elongated, as a very flexible spaghetti that forms kinks that unfold to give rise to folds and kinks in other positions along the polymer length. The behavior resembles an ideal polymer in a &thetas; solvent. A Principal Component Analysis (PCA) of the minima composing the inherent structure evidences the presence of two distinct groups of ball-like structures of PEG2000 in water and water with 4% ethanol. These groups give a definite signature to the solvated structure of PEG2000 in these two solvents. In contrast, PCA reveals several groups of avoided states for PEG2000 in ethyl acetate that disqualify the possibility of being an ideal polymer in a &thetas; solvent.

The third part of the dissertation is a work in progress, where I investigate the condensed phase of PEG2000 and study the interface between the condensed phase and the three different solvents under study. With a strategy of combining NPT MD simulations at different temperatures and pressures, PEG 2000 condensed phase displays the experimental density within a 1% discrepancy at 300 K and 1 atm. This is a very encouraging result on this ongoing project.

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Thompson, Travis W. "Tuning the Photochemical Reactivity of Electrocyclic Reactions| A Non-adiabatic Molecular Dynamics Study." Thesis, California State University, Long Beach, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10839950.

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We use non-adiabatic ab initio molecular dynamics to study the influence of substituent side groups on the photoactive unit (Z)-hexa-1,3,5-triene (HT). The Time-Dependent Density Functional Theory Surface Hopping method (TDDFT-SH) is used to investigate the influence of substituted isopropyl and methyl groups on the excited state dynamics. The 1,4 and 2,5-substituted molecules are simulated: 2,5-dimethylhexa-1,3,5-triene (DMHT), 2-isopropyl-5-methyl-1,3,5-hexatriene (2,5-IMHT), 3,7-dimethylocta-1,3,5-triene (1,4-IMHT), and 2,5-diisopropyl-1,3,5-hexatriene (DIHT). We find that HT and 1,4-IMHT have the lowest ring-closing branching ratios of 5.3% and 1.0%, respectively. For the 2,5-substituted derivatives, the branching ratio increases with increasing size of the substituents, exhibiting yields of 9.78%, 19%, and 24% for DMHT, 2,5-IMHT, and DIHT, respectively. The reaction channels are shown to prefer certain conformation configurations at excitation, where the ring-closing reaction tends to originate from the gauche-Z-gauche (gZg) rotamer almost exclusively. In addition, there is a conformational dependency on absorption, gZg conformers have on average lower S1 ← S0 excitation energies that the other rotamers. Furthermore, we develop a method to calculate a predicted quantum yield that is in agreement with the wavelength-dependence observed in experiment for DMHT. In addition, the quantum yield method also predicts DIHT to have the highest CHD yield of 0.176 at 254 nm and 0.390 at 290 nm.

Additionally, we study the vitamin D derivative Tachysterol (Tachy) which exhibits similar photochemical properties as HT and its derivatives. We find the reaction channels of Tachy also have a conformation dependency, where the reactive products toxisterol-D1 (2.3%), previtamin D (1.4%) and cyclobutene toxisterol (0.7%) prefer cEc, cEt, and tEc configurations at excitation, leaving the tEt completely non-reactive. The rotamers similarly have a dependence on absorption as well, where the cEc configuration has the lowest energy S 1 ← S0 excitation of the rotamers. The wavelength dependence of the rotamers should lead to selective properties of these molecules at excitation. An excitation to the red-shifted side of the maximum absorption peak will on average lead to excitations of the gZg rotamers more exclusively.

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Ghosh, Raja. "Spectroscopy of Polarons in Organic Semiconductors: A New Theoretical Model." Diss., Temple University Libraries, 2019. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/574625.

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Chemistry
Ph.D.
The spectral line-shape of the mid-IR absorption spectrum provides valuable information about the "hole" polaron coherence length in doped and undoped conjugated polymer films. In poly(3-hexylthiophene) (P3HT) films the spectrum generally consists of a narrow, low-energy peak A (700-1000 $cm^{-1}$) followed by a much broader, higher-energy peak B (2500-5000 $cm^{-1}$). Using a theory based on the Holstein Hamiltonian for mobile holes in P3HT, the IR line-shape is successfully reproduced for several recently measured spectra recorded in doped and undoped films, confirming the association of an enhanced peak ratio (A/B) with extended polaron coherence. Emphasis is placed on the origin of components polarized along the intra- and inter-chain directions and their dependence on the spatial distribution of disorder as well as the position of the dopant relative to the $\pi$-stack. The model is further adapted to treat donor-acceptor copolymers where the local HOMO energy varies periodically from donor unit to acceptor unit. The calculated line shape for a diketopyrrolopyrrole-based copolymer agrees well with the recently measured spectrum.
Temple University--Theses
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Borin, Veniamin Aleksandrovich. "A Computational Study of Diiodomethane Photoisomerization." Bowling Green State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1477581227858711.

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Fransson, Thomas. "Chemical bond analysis in the ten-electron series." Thesis, Linköping University, Department of Physics, Chemistry and Biology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-19554.

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This thesis presents briefly the application of quantum mechanics on systems ofchemical interest, i.e., the field of quantum chemistry and computational chemistry.The molecules of the ten-electron series, hydrogen fluoride, water, ammonia,methane and neon, are taken as computational examples. Some applications ofquantum chemistry are then shown on these systems, with emphasis on the natureof the molecular bonds. Conceptual methods of chemistry and theoreticalchemistry for these systems are shown to be valid with some restrictions, as theseinterpretations does not represent physically measurable entities.The orbitals and orbital energies of neon is studied, the binding van der Waalsinteractionresulting in a Ne2 molecule is studied with a theoretical bond lengthof 3.23 °A and dissociation energy of 81.75 μEh. The equilibrium geometries ofFH, H2O, NH3 and CH4 are studied and the strength and character of the bondsinvolved evaluated using bond order, dipole moment, Mulliken population analysisand L¨owdin population analysis. The concept of electronegativity is studied in thecontext of electron transfer. Lastly, the barrier of inversion for NH3 is studied, withan obtained barrier height of 8.46 mEh and relatively constant electron transfer.

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Mclaughlin, Keith. "Development of Improved Models for Gas Sorption Simulation." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4916.

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Computational chemistry offers one the ability to develop a better understanding of the complex physical and chemical interactions that are fundamental to macro- and mesoscopic processes that are seen in laboratory experiments, industrial processes, and ordinary, everyday life. For many systems, the physics of interest occur at the molecular or atomistic levels, and in these cases, computational modeling and two well refined simulation techniques become invaluable: Monte Carlo (MC) and molecular dynamics (MD). In this work, two well established problems were tackled. First, models and potentials for various gas molecules were produced and refined from first principles. These models, although based on work done previously by Belof et al., are novel due to the inclusion of many-body van der Waals interactions, advanced r-12 repulsion combining rules for treating unlike intra- and intermolecular interactions, and highly-efficient treatment of induction interactions. Second, a multitude of models were developed and countless MD simulations were performed in order to describe and understand the giant frictional anisotropy of d-AlCoNi, first observed by Park et al. in 2005.
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Aeberhard, Philippe C. "Computational modelling of structure and dynamics in lightweight hydrides." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:bfaf28b1-da03-4ce9-8577-5e8c18eb05ae.

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Hydrogen storage in lightweight hydrides continues to attract significant interest as the lack of a safe and efficient storage of hydrogen remains the major technological barrier to the widespread use of hydrogen as a fuel. The metal borohydrides Ca(BH₄)₂ and LiBH₄ form the subject of this thesis; three aspects of considerable academic interest were investigated by density functional theory (DFT) and molecular dynamics (MD) modelling. (i) High-pressure crystal structures of Ca(BH₄)₂ were predicted from a structural analogy between metal borohydrides and isoelectronic metal oxides. The structural stability of hydrogen storage materials under high pressure is an important aspect, as high-pressure polymorphs may provide structures with better hydrogen desorption properties. The isoelectronic analogue of Ca(BH₄)₂ is TiO₂, and structural equivalents of Ca(BH₄)₂ in the baddeleyite, columbite and cotunnite structures of TiO₂ were found to be stable at elevated pressure. Thermodynamic stability was evaluated by computing the Gibbs energy with respect to pressure and temperature. The pressure-dependence of the Helmholtz energy was determined to described a third-order Birch-Murnaghan equation of state, and the harmonic approximation was used to compute the vibrational energy levels and the Helmholtz energy as a function of temperature. The proposed structures are consistent with reports of two hitherto unidentified high-pressure phases observed experimentally. (ii) The disordered structure of the high-temperature phase of LiBH4 was studied by ab initio molecular dynamics (MD) at temperatures ranging from 200-535 K. It was found that the model emerging from analysis of the MD simulations properly accounts for dynamical disorder and fundamentally differs from the published experimental and theoretical structures. The validity of the MD model was corroborated by comparison of calculated pair distribution functions, vibrational spectra and a crystallographic model with neutron diffraction data; good agreement was found. A reassignment of the space group from P63mc to P63/mmc is proposed based on evidence for additional symmetry from MD simulations. (iii) Finally, a new MD-based method was developed to simulate fast ionic diffusion in LiBH₄. The colour diffusion algorithm - a nonequilibrium molecular dynamics method originally developed for the study of model fluids - was adapted and applied to self-diffusion of atoms in a solid for the first time. Calculated diffusion coefficients agreed very well with published measurements, and diffusion pathways that include collective particle effects were determined directly from the simulation results, thereby opening up a promising and efficient new method for the study of phenomena such as superionic conduction.
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Troville, Jonathan. "Multiscale Modeling of Carbon Nanotube Synthesis in a Catalytic Chemical Vapor Deposition Reactor." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1495839218743389.

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Agrawal, Anupriya. "Computational Study of Vanadate and Bulk Metallic Glasses." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1345536954.

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Books on the topic "Computational physics|Computational chemistry"

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Vesely, Franz J. Computational Physics: An Introduction. Boston, MA: Springer US, 1994.

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Zalesny, Robert, Manthos G. Papadopoulos, Paul G. Mezey, and Jerzy Leszczynski, eds. Linear-Scaling Techniques in Computational Chemistry and Physics. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-2853-2.

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service), SpringerLink (Online, ed. Handbook of Computational Chemistry. Dordrecht: Springer Netherlands, 2012.

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G, Papadopoulos Manthos, Mezey Paul G, Leszczyński Jerzy, and SpringerLink (Online service), eds. Linear-Scaling Techniques in Computational Chemistry and Physics: Methods and Applications. Dordrecht: Springer Science+Business Media B.V., 2011.

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Manoj, Shukla, and SpringerLink (Online service), eds. Practical Aspects of Computational Chemistry II: An Overview of the Last Two Decades and Current Trends. Dordrecht: Springer Netherlands, 2012.

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Manoj, Shukla, and SpringerLink (Online service), eds. Practical Aspects of Computational Chemistry I: An Overview of the Last Two Decades and Current Trends. Dordrecht: Springer Netherlands, 2012.

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Sirca, Simon. Computational Methods for Physicists: Compendium for Students. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Eyert, Volker. The Augmented Spherical Wave Method: A Comprehensive Treatment. 2nd ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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T, Maitra Neepa, Nogueira Fernando M. S, Gross E. K. U, Rubio Angel, and SpringerLink (Online service), eds. Fundamentals of Time-Dependent Density Functional Theory. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Rui-Qin, Zhang, Treutlein Herbert R, and SpringerLink (Online service), eds. Quantum Simulations of Materials and Biological Systems. Dordrecht: Springer Netherlands, 2012.

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Book chapters on the topic "Computational physics|Computational chemistry"

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Koleżyński, Andrzej. "Computational Methods in Spectroscopy." In Challenges and Advances in Computational Chemistry and Physics, 1–48. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01355-4_1.

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Kusko, Rebecca, and Huixiao Hong. "Computational Toxicology Promotes Regulatory Science." In Challenges and Advances in Computational Chemistry and Physics, 1–11. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16443-0_1.

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Lupan, Alexandru, and R. Bruce King. "Computational Studies of Metallaboranes and Metallacarboranes." In Challenges and Advances in Computational Chemistry and Physics, 49–95. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22282-0_3.

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Huang, Jingsong, Jacek Jakowski, Ariana Beste, Jarod Younker, Alvaro Vazquez-Mayagoitia, Eduardo Cruz-Silva, Miguel Fuentes-Cabrera, Alejandro Lopez-Bezanilla, Vincent Meunier, and Bobby G. Sumpter. "Advancing Understanding and Design of Functional Materials Through Theoretical and Computational Chemical Physics." In Practical Aspects of Computational Chemistry II, 209–78. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-0923-2_7.

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Zhu, Yinghuai, Amartya Chakrabarti, and Narayan S. Hosmane. "Applications of Nanocatalysis in Boron Chemistry." In Challenges and Advances in Computational Chemistry and Physics, 199–217. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22282-0_8.

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Schwarz, W. H. Eugen. "An Introduction to Relativistic Quantum Chemistry." In Challenges and Advances in Computational Chemistry and Physics, 1–62. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-1-4020-9975-5_1.

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Hoffman, David K., and Donald J. Kouri. "Distributed Approximating Functionals: a Robust, New Approach to Computational Chemistry and Physics." In Lecture Notes in Chemistry, 57–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57051-3_4.

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Church, Jonathan R., Aditya G. Rao, Avishai Barnoy, Christian Wiebeler, and Igor Schapiro. "Computational Studies of Photochemistry in Phytochrome Proteins." In Challenges and Advances in Computational Chemistry and Physics, 197–226. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57721-6_4.

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Styszyński, Jacek. "Why do we Need Relativistic Computational Methods?" In Challenges and Advances in Computational Chemistry and Physics, 99–164. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-1-4020-9975-5_3.

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Ferrer, Silvia, Sergio Martí, Vicent Moliner, and Iñaki Tuñón. "Computational Modeling of Biological Systems: The LDH Story." In Challenges and Advances in Computational Chemistry and Physics, 355–74. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-3034-4_13.

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Conference papers on the topic "Computational physics|Computational chemistry"

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Sher, A., M. van Schilfgaarde, and M. A. Berding. "Review of the status of computational solid-state physics." In Physics and chemistry of mercury cadmium telluride and novel IR detector materials. AIP, 1991. http://dx.doi.org/10.1063/1.41084.

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Aerts, A., J. Lim, and A. Marino. "Modelling Coolant Chemistry in the MYRRHA Reactor with a Multi-Physics Computational Tool." In Tranactions - 2019 Winter Meeting. AMNS, 2019. http://dx.doi.org/10.13182/t30881.

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Murthy, Jayathi Y. "Computational Heat Transfer in Complex Systems: A Review of Needs and Opportunities." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-23367.

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During the few decades, computational techniques for simulating heat transfer in complex industrial systems have reached maturity. Combined with increasingly sophisticated modeling of turbulence, chemistry, radiation, phase change and other physics, powerful computational fluid dynamics (CFD) and computational heat transfer (CHT) solvers have been developed which are beginning to enter the industrial design cycle. In this paper, an overview of emerging simulation needs is first given, and currently-available CFD techniques are evaluated in light of these needs. Emerging computational methods which address some of the failings of current techniques are then reviewed. New research opportunities for computational heat transfer, such as in sub-micron and multiscale heat transport, are reviewed. As computational techniques and physical models become mature, there is increasing demand for predictive simulation, that is, simulation which is not only verified and validated, but whose uncertainty is also quantified. Current work in the area of sensitivity computation and uncertainty propagation is described.
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Paternoster, Beatrice. "Symposium "Numerical methods and computational procedures for special problems in physics and chemistry" dedicated to Prof. Liviu Ixaru to celebrate his 70th birthday." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756356.

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Krzhizhanovskaya, V. V., M. A. Zatevakhin, A. A. Ignatiev, Yu E. Gorbachev, W. J. Goedheer, and P. M. A. Sloot. "A 3D Virtual Reactor for Simulation of Silicon-Based Film Production." In ASME/JSME 2004 Pressure Vessels and Piping Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/pvp2004-3120.

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In this paper we introduce a Grid-based Virtual Reactor, a problem-solving environment that supports detailed numerical study of industrial thin film production in Plasma Enhanced Chemical Vapor Deposition (PECVD) reactors. We describe the physics and chemistry underpinning the deposition process, the numerical approach to simulate these processes on advanced computer architectures as well as the associated software environment supporting computational experiments. In the developed 3D model we took into account all relevant chemical kinetics, plasma physics and transport processes that occur in PECVD reactors. We built an efficient problem-solving environment for scientists studying PECVD processes and end-users working in chemical industry and validated the resulting Virtual Reactor against real experiments.
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Perini, Federico, Anand Krishnasamy, Youngchul Ra, and Rolf D. Reitz. "Computationally Efficient Simulation of Multi-Component Fuel Combustion Using a Sparse Analytical Jacobian Chemistry Solver and High-Dimensional Clustering." In ASME 2013 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/icef2013-19039.

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The need for more efficient and environmentally sustainable internal combustion engines is driving research towards the need to consider more realistic models for both fuel physics and chemistry. As far as compression ignition engines are concerned, phenomenological or lumped fuel models are unreliable to capture spray and combustion strategies outside of their validation domains — typically, high-pressure injection and high-temperature combustion. Furthermore, the development of variable-reactivity combustion strategies also creates the need to model comprehensively different hydrocarbon families even in single fuel surrogates. From the computational point of view, challenges to achieving practical simulation times arise from the dimensions of the reaction mechanism, that can be of hundreds species even if hydrocarbon families are lumped into representative compounds, and thus modeled with non-elementary, skeletal reaction pathways. In this case, it is also impossible to pursue further mechanism reductions to lower dimensions. CPU times for integrating chemical kinetics in internal combustion engine simulations ultimately scale with the number of cells in the grid, and with the cube number of species in the reaction mechanism. In the present work, two approaches to reduce the demands of engine simulations with detailed chemistry are presented. The first one addresses the demands due to the solution of the chemistry ODE system, and features the adoption of SpeedCHEM, a newly developed chemistry package that solves chemical kinetics using sparse analytical Jacobians. The second one aims to reduce the number of chemistry calculations by binning the CFD cells of the engine grid into a subset of clusters, where chemistry is solved and then mapped back to the original domain. In particular, a high-dimensional representation of the chemical state space is adopted for keeping track of the different fuel components, and a newly developed bounding-box-constrained k-means algorithm is used to subdivide the cells into reactively homogeneous clusters. The approaches have been tested on a number of simulations featuring multi-component diesel fuel surrogates, and different engine grids. The results show that significant CPU time reductions, of about one order of magnitude, can be achieved without loss of accuracy in both engine performance and emissions predictions, prompting for their applicability to more refined or full-sized engine grids.
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Mehrotra, Vibhor, Jonathan Berkoe, Rajesh Rawat, and Phillip J. Smith. "CFD Modeling Predictions of Near Burner Jet Region and Comparison With Sandia Flame." In ASME/JSME 2003 4th Joint Fluids Summer Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/fedsm2003-45435.

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Quantitative emissions prediction in industrial process furnaces is as difficult as it is important. A wide range of length and time scales must be bridged to capture the flow physics and chemistry of combustion and pollutant formation. This paper focuses on gathering and testing the state of the art for turbulence, mixing and reaction subgrid scale (SGS) models as they are applied to the near burner region using a commercial CFD code. The Fluent® version 5.5 computational fluid dynamics (CFD) code is used to simulate a single port, axisymmetric fuel jet of 50% (by vol.) methane and 50% hydrogen in a co-flowing air stream (Sandia flame HM1a). This configuration is chosen for its simplicity and for the wealth of experimental data available [1]. The intermediate goal is to predict temperature and species concentration accurately that may affect the prediction of NO concentrations in the flue products. Therefore, flow dynamics, heat transfer; combustion and NOx chemistry are important issues and will be analyzed in this paper.
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Hergart, Carl, and Norbert Peters. "Applying the Representative Interactive Flamelet Model to Evaluate the Potential Effect of Wall Heat Transfer on Soot Emissions in a Small-Bore DI Diesel Engine." In ASME 2001 Internal Combustion Engine Division Spring Technical Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/ices2001-118.

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Abstract Due to the wide spectrum of turbulent and chemical length- and time scales occurring in a HSDI diesel engine, capturing the correct physics and chemistry underlying combustion poses a tremendous modeling challenge. The processes related to the two-phase flow in a DI diesel engine add even more complexity to the total modeling effort. The Representative Interactive Flamelet (RIF) model has gained widespread attention owing to its ability of correctly describing ignition, combustion and pollutant formation phenomena. This is achieved by incorporating very detailed chemistry for the gas phase as well as the soot particle growth and oxidation, without imposing any significant computational penalty. The model, which is based on the laminar flamelet concept, treats a turbulent flame as an ensemble of thin, locally one-dimensional flame structures, whose chemistry is fast. A potential explanation for the significant underprediction of part load soot observed in previous studies applying the model is the neglect of wall heat losses in the flamelet chemistry model. By introducing an additional source term in the flamelet temperature equation, directly coupled to the wall heat transfer predicted by the CFD-code, flamelets exposed to walls are assigned heat losses of various magnitudes. Results using the model in three-dimensional simulations of the combustion process in a small-bore direct injection diesel engine indicate that the experimentally observed emissions of soot may have their origin in flame quenching at the relatively cold combustion chamber walls.
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Chandross, Michael. "Advances in Molecular Dynamics Simulations of Nanotribology." In STLE/ASME 2008 International Joint Tribology Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/ijtc2008-71201.

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Molecular dynamics is the simulation method that is most amenable to the length and time scales of nanotribological experiments. The ability to track the individual motion of every atom in simulations has led to a detailed understanding of the underlying physics that is difficult to extract from experiment. While significant progress has been made in simulations over the past two decades, computational issues still limit the types of problems that can be approached, and the detailed understanding that results. Here we discuss recent advances in molecular dynamics simulations that push the bounds of simulation size, velocity, and chemistry. These state of the art simulation techniques have made great strides in allowing detailed comparisons to experimental results. These advances will be placed in context by addressing the barriers that remain and where future progress lies.
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Shi, Shaoping, Christopher Guenther, and Stefano Orsino. "Numerical Study of Coal Gasification Using Eulerian-Eulerian Multiphase Model." In ASME 2007 Power Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/power2007-22144.

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Gasification converts the carbon-containing material into a synthesis gas (syngas) which can be used as a fuel to generate electricity or used as a basic chemical building block for a large number of uses in the petrochemical and refining industries. Based on the mode of conveyance of the fuel and the gasifying medium, gasification can be classified into fixed or moving bed, fluidized bed, and entrained flow reactors. Entrained flow gasifiers normally feature dilute flow with small particle size and can be successfully modeled with the Discrete Phase Method (DPM). For the other types, the Eulerian-Eulerian (E-E) or the so called two-fluid multiphase model is a more appropriate approach. The E-E model treats the solid phase as a distinct interpenetrating granular “fluid” and it is the most general-purposed multi-fluid model. This approach provides transient, three-dimensional, detailed information inside the reactor which would otherwise be unobtainable through experiments due to the large scale, high pressure and/or temperature. In this paper, a transient, three-dimensional model of the Power Systems Development Facility (PSDF) transport gasifier will be presented to illustrate how Computational Fluid Dynamics (CFD) can be used for large-scale complicated geometry with detailed physics and chemistry. In the model, eleven species are included in the gas phase while four pseudo-species are assumed in the solid phase. A total of sixteen reactions, both homogeneous (involving only gas phase species) and heterogeneous (involving species in both gas and solid phases), are used to model the coal gasification chemistry. Computational results have been validated against PSDF experimental data from lignite to bituminous coals under both air and oxygen blown conditions. The PSDF gasifier geometry was meshed with about 70,000, hexahedra-dominated cells. A total of six cases with different coal, feed gas, and/or operation conditions have been performed. The predicted and measured temperature profiles along the gasifier and gas compositions at the outlet agreed fairly well.
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Reports on the topic "Computational physics|Computational chemistry"

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Buchanan, Christopher C. A Computational Examination of Detonation Physics and Blast Chemistry. Fort Belvoir, VA: Defense Technical Information Center, August 2011. http://dx.doi.org/10.21236/ada548990.

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Buchanan, Christopher C. A Computational Examination of Detonation Physics and Blast Chemistry. Fort Belvoir, VA: Defense Technical Information Center, August 2011. http://dx.doi.org/10.21236/ada548571.

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Millis, Andrew. Many Body Methods from Chemistry to Physics: Novel Computational Techniques for Materials-Specific Modelling: A Computational Materials Science and Chemistry Network. Office of Scientific and Technical Information (OSTI), November 2016. http://dx.doi.org/10.2172/1332662.

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