How to Derive Force Field Parameters by Genetic Algorithms: Modellingtripod-Mo(CO)3 Compounds as an Example

Hunger, Johannes; Beyreuther, Stefan; Hüttner, Gottfried; Allinger, K.; Radelof, Uwe; Zsolnai, László

doi:10.1002/(sici)1099-0682(199806)1998:6<693::aid-ejic693>3.0.co;2-m

Cited by 39 publications

(39 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In recent years, optimization algorithms have been proposed that seek to avoid overfitting or underfitting of the database [108,122]. Rigorous statistical methods have been applied [123], and even approaches based on neural networks [124,125] and genetic algorithms [126,127] have been proposed. A portable computer software has been developed [128] to improve the efficiency of the fitting process.…”

Section: Potential Generation Proceduresmentioning

confidence: 99%

Atomistic modeling of interfaces and their impact on microstructure and properties

2010

View full text Add to dashboard Cite

Atomic-level modeling of materials provides fundamental insights into phase stability, structure and properties of crystalline defects, and to physical mechanisms of many processes ranging from atomic diffusion to interface migration. This knowledge often serves as a guide for the development of mesoscopic and macroscopic continuum models, with input parameters provided by atomistic models. This paper gives an overview of the most recent developments in the area of atomistic modeling with emphasis on interfaces and their impact on microstructure and properties of materials. Modern computer simulation methodologies are discussed and illustrated by several applications related to thermodynamic, kinetic and mechanical properties of materials. Existing challenges and future research directions in this field are outlined.

show abstract

Section: Potential Generation Proceduresmentioning

confidence: 99%

Atomistic modeling of interfaces and their impact on microstructure and properties

2010

View full text Add to dashboard Cite

show abstract

“…When comparing these parameters between complexes 6 and 8, we can see that the substitution of the phenyl groups by the o-tolyl groups implies that Re-P bonds are somewhat lengthier and some angle bonds that contain phosphorus are slightly more opened, changes that should be attributed to higher steric hindrance of o-tolyl groups. It must be born in mind that, as far as we know, only one structure of an octahedral transition metal complex with two bis(o-tolyl)phosphine groups in cis-position has been reported [34], and in this case the ligand is a tripodal phosphine.…”

Section: Crystal Structures Of Complexes 2 6 Andmentioning

confidence: 99%

Rhenium carbonyl compounds with (diphenyl)phosphinoalkynes and a sterically hindered phosphinoalkyne

Ledesma

Álvarez‐Larena

Suades

2008

Journal of Organometallic Chemistry

View full text Add to dashboard Cite

“…Due to the large number of parameters to be optimized and the nonconvex nature of the search space, multistart techniques based on local optimization algorithms are problematic . Therefore, nondeterministic global optimization strategies, for example Genetic Algorithms (GA), have been used by several authors …”

Section: Introductionmentioning

confidence: 99%

Efficient global optimization of reactive force‐field parameters

et al. 2015

View full text Add to dashboard Cite

Reactive force fields make low-cost simulations of chemical reactions possible. However, optimizing them for a given chemical system is difficult and time-consuming. We present a high-performance implementation of global force-field parameter optimization, which delivers parameter sets of the same quality with much less effort and in far less time than before, and also offers excellent parallel scaling. We demonstrate these features with example applications targeting the ReaxFF force field. © 2015 Wiley Periodicals, Inc.

show abstract

How to Derive Force Field Parameters by Genetic Algorithms: Modellingtripod-Mo(CO)3 Compounds as an Example

Cited by 39 publications

References 22 publications

Atomistic modeling of interfaces and their impact on microstructure and properties

Atomistic modeling of interfaces and their impact on microstructure and properties

Rhenium carbonyl compounds with (diphenyl)phosphinoalkynes and a sterically hindered phosphinoalkyne

Efficient global optimization of reactive force‐field parameters

Contact Info

Product

Resources

About