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E.C. Marcoulaki

Researcher at University of Piraeus

Publications -  38
Citations -  684

E.C. Marcoulaki is an academic researcher from University of Piraeus. The author has contributed to research in topics: Simulated annealing & Computer science. The author has an hindex of 13, co-authored 33 publications receiving 633 citations. Previous affiliations of E.C. Marcoulaki include National Centre of Scientific Research "Demokritos" & University of Manchester.

Papers
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Expression of Interest for a very long baseline neutrino oscillation experiment (LBNO)

A. Stahl, +223 more
TL;DR: In this paper, the authors describe the feasibility studies of a long baseline neutrino oscillation experiment (LBNO) with a new conventional neutrinos beamline facility (CN2PY).
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On the development of novel chemicals using a systematic optimisation approach. Part II. Solvent design

TL;DR: In this article, a new approach is presented for the optimal selection of solvents, using group contribution methods and a vector representation to formulate an optimisation problem with respect to desired properties for the solvent.
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On the development of novel chemicals using a systematic synthesis approach. Part I. Optimisation framework

TL;DR: This paper presents a computer-aided technology for the synthesis of molecules with optimal properties that combines stochastic optimisation and group-contribution methods to search and select chemicals of desirable performance.
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Molecular design synthesis using stochastic optimisation as a tool for scoping and screening

TL;DR: In this paper, a new approach that combines stochastic optimisation and group-contribution methods to select chemicals with optimised properties is presented, where each molecule is represented as a set of functional groups.
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Scoping and screening complex reaction networks using stochastic optimization

TL;DR: In this article, a two-level stochastic optimization approach is proposed to target the performance of chemical reactors with the use of stochastically optimized configurations. But it is not restricted by the dimensionality or the size of the problem.