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Finding low energy conformations of atomic clusters using evolution strategies

https://doi.org/10.1007/bfb0040801
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/(sici)1096-987x(199706)18:8<1096::aid-jcc13>3.0.co;2-bopenalex-snapshot
Energy minimization of mixed argon-xenon microclusters using a genetic algorithm
inferredcites →https://doi.org/10.1002/andp.19273892002openalex-snapshot
Zur Quantentheorie der Molekeln
inferredcites →https://doi.org/10.1002/jcc.540140705openalex-snapshot
A critical comparison of search algorithms applied to the optimization of protein side‐chain conformations
inferredcites →https://doi.org/10.1002/jcc.540141115openalex-snapshot
Analysis of the genetic algorithm method of molecular conformation determination
inferredcites →https://doi.org/10.1002/jcc.540141117openalex-snapshot
Conformational searching methods for small molecules. II. Genetic algorithm approach
inferredcites →https://doi.org/10.1002/qua.560440214openalex-snapshot
Do intelligent configuration search techniques outperform random search for large molecules?
inferredcites →https://doi.org/10.1007/bf00175353openalex-snapshot
Basic aspects of evolution strategies
inferredcites →https://doi.org/10.1016/0009-2614(96)00629-xopenalex-snapshot
Global geometry optimization of clusters guided by N-dependent model potentials
inferredcites →https://doi.org/10.1021/j100001a004openalex-snapshot
Drift Tube Studies of Atomic Clusters
inferredcites →https://doi.org/10.1021/j100141a013openalex-snapshot
Global geometry optimization of clusters using genetic algorithms
inferredcites →https://doi.org/10.1021/jp960574jopenalex-snapshot
Molecular Clusters: Structure and Dynamics of Weakly Bound Systems
inferredcites →https://doi.org/10.1088/0305-4470/18/8/003openalex-snapshot
Computational complexity of the ground-state determination of atomic clusters
inferredcites →https://doi.org/10.1103/physrevb.31.5262openalex-snapshot
Computer simulation of local order in condensed phases of silicon
inferredcites →https://doi.org/10.1103/physrevb.41.10568openalex-snapshot
Interatomic potential for silicon clusters, crystals, and surfaces
inferredcites →https://doi.org/10.1103/physrevb.47.2329openalex-snapshot
Empirical-potential studies on the structural properties of small silicon clusters
inferredcites →https://doi.org/10.1103/physreve.51.r2769openalex-snapshot
Prediction of the lowest energy structure of clusters using a genetic algorithm
inferredcites →https://doi.org/10.1103/physrevlett.62.292openalex-snapshot
Surface and Thermodynamic Interatomic Force Fields for Silicon Clusters and Bulk Phases
inferredcites →https://doi.org/10.1103/physrevlett.75.288openalex-snapshot
Molecular Geometry Optimization with a Genetic Algorithm
inferredcites →https://doi.org/10.1103/revmodphys.61.689openalex-snapshot
The density functional formalism, its applications and prospects
inferredcites →https://doi.org/10.1126/science.235.4791.860openalex-snapshot
Covalent Group IV Atomic Clusters

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4870699openalex-extracted
Optimizing Hydraulic Fracturing in Tight Gas Reservoirs: A Comparative Analysis of AI Techniques Integrated with Reservoir Simulation
inferred← citeshttps://doi.org/10.1080/03081070701303470openalex-snapshot
An empirical study about the usefulness of evolution strategies to solve constrained optimization problems
inferred← citeshttps://doi.org/10.1109/tevc.2004.836819openalex-snapshot
A Simple Multimembered Evolution Strategy to Solve Constrained Optimization Problems
inferred← citeshttps://doi.org/10.1142/s0129183105007340openalex-snapshot
COMPARISON OF PARTICLE SWARM AND EVOLUTIONARY PROGRAMMING AS THE GLOBAL CONFORMATION OPTIMIZER OF CLUSTERS
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