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Hutter, Dieter

doi:10.1023/a:1005772217686

Cited by 19 publications

(1 citation statement)

References 25 publications

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“…The PBC calculations are carried out using the CPMD (Car–Parrinello molecular dynamics) program package and the plane-wave DFT method . The BLYP functional , was employed.…”

Section: Computational Detailsmentioning

confidence: 99%

Predictions of Gibbs Free Energies for the Adsorption of Polyaromatic and Nitroaromatic Environmental Contaminants on Carbonaceous Materials: Efficient Computational Approach

Scott

Gorb²,

Mobley³

et al. 2012

Langmuir

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The adsorption of benzene, polycyclic aromatic hydrocarbons (PAHs), and nitroaromatic compounds (NACs) on the carbonaceous surfaces from the gas phase and water solution was investigated. Several different levels of theory were applied, including DFT-, MP2-, and CCSD(T)-based methods, to find an approach that is computationally inexpensive and can provide accurate thermodynamic parameters for studied adsorption phenomena. The methods and techniques used (including cluster and periodic approximations) were evaluated on the basis of comparison with available experimental data. The optimized structures of calculated complexes are obtained, and the interaction energies and Gibbs free energies are predicted. Good agreement was revealed for the theoretical and experimental adsorption energies of benzene and PAHs adsorbed on the carbon surfaces. The adsorption of benzene, PAHs, and NACs on carbon is suggested to be effective from the gas phase for all studied compounds and for PAHs and NACs also from water solution at room temperature.

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“…The PBC calculations are carried out using the CPMD (Car–Parrinello molecular dynamics) program package and the plane-wave DFT method . The BLYP functional , was employed.…”

Section: Computational Detailsmentioning

confidence: 99%

Predictions of Gibbs Free Energies for the Adsorption of Polyaromatic and Nitroaromatic Environmental Contaminants on Carbonaceous Materials: Efficient Computational Approach

Scott

Gorb²,

Mobley³

et al. 2012

Langmuir

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Best-First Rippling

Johansson

Bundy

Dixon

2006

Reasoning, Action and Interaction in AI Theories and Systems

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Abstract. Rippling is a form of rewriting that guides search by only performing steps that reduce the differences between formulae. Termination is normally ensured by a defined measure that is required to decrease with each step. Because of these restrictions, rippling will fail to prove theorems about, for example, mutual recursion where steps that temporarily increase the differences are necessary. Best-first rippling is an extension to rippling where the restrictions have been recast as heuristic scores for use in best-first search. If nothing better is available, previously illegal steps can be considered, making best-first rippling more flexible than ordinary rippling. We have implemented best-first rippling in the IsaPlanner system together with a mechanism for caching proof-states that helps remove symmetries in the search space, and machinery to ensure termination based on term embeddings. Our experiments show that the implementation of best-first rippling is faster on average than IsaPlanner's version of traditional depth-first rippling, and solves a range of problems where ordinary rippling fails.

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