Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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1.080 Topics available

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693.932 PEOPLE
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Naji, M.
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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (18/18 displayed)

  • 2021On the competition for ultimately stiff and strong architected materials53citations
  • 2018Benchmarking state-of-the-art numerical simulation techniques for analyzing large photonic crystal membrane line defect cavitiescitations
  • 2018Benchmarking state-of-the-art numerical simulation techniques for analyzing large photonic crystal membrane line defect cavitiescitations
  • 2018Benchmarking state-of-the-art optical simulation methods for analyzing large nanophotonic structurescitations
  • 2018Benchmarking state-of-the-art optical simulation methods for analyzing large nanophotonic structurescitations
  • 2018Benchmarking five numerical simulation techniques for computing resonance wavelengths and quality factors in photonic crystal membrane line defect cavities19citations
  • 2018Which Computational Methods Are Good for Analyzing Large Photonic Crystal Membrane Cavities?citations
  • 2018Which Computational Methods Are Good for Analyzing Large Photonic Crystal Membrane Cavities?citations
  • 2018Investment casting and experimental testing of heat sinks designed by topology optimization82citations
  • 2018Benchmarking five numerical simulation techniques for computing resonance wavelengths and quality factors in photonic crystal membrane line defect cavities19citations
  • 2017Comparison of Five Computational Methods for Computing Q Factors in Photonic Crystal Membrane Cavitiescitations
  • 2017Comparison of Five Computational Methods for Computing Q Factors in Photonic Crystal Membrane Cavitiescitations
  • 2017Benchmarking five computational methods for analyzing large photonic crystal membrane cavities1citations
  • 2017Benchmarking five computational methods for analyzing large photonic crystal membrane cavities1citations
  • 2015Topology Optimized Architectures with Programmable Poisson's Ratio over Large Deformations457citations
  • 2014Design of materials with prescribed nonlinear properties164citations
  • 2011Modelling of Active Semiconductor Photonic Crystal Waveguides and Robust Designs based on Topology Optimizationcitations
  • 2011Modelling of Active Semiconductor Photonic Crystal Waveguides and Robust Designs based on Topology Optimizationcitations

Places of action

Chart of shared publication
Andersen, Morten N.
1 / 1 shared
Sigmund, Ole
18 / 47 shared
Ivinskaya, Aliaksandra
12 / 18 shared
Lasson, Jakob Rosenkrantz De
6 / 9 shared
Gutsche, Philipp
12 / 14 shared
Häyrynen, Teppo
12 / 12 shared
Burger, Sven
12 / 16 shared
Gregersen, Niels
12 / 21 shared
Breinbjerg, Olav
12 / 26 shared
Frandsen, Lars Hagedorn
12 / 19 shared
Kim, Oleksiy S.
12 / 23 shared
Lavrinenko, Andrei V.
7 / 98 shared
De Lasson, Jakob Rosenkrantz
6 / 9 shared
Lavrinenko, Andrei
5 / 32 shared
Mørk, Jesper
6 / 17 shared
Moerk, Jesper
6 / 20 shared
Malureanu, Radu
2 / 51 shared
Haertel, Jan Hendrik Klaas
1 / 1 shared
Sanna, Simone
1 / 26 shared
Lei, Tian
1 / 1 shared
Lazarov, Boyan Stefanov
1 / 2 shared
Engelbrecht, Kurt
1 / 8 shared
Alexandersen, Joe
1 / 1 shared
Novitsky, Andrey
2 / 13 shared
Jensen, Jakob Søndergaard
4 / 19 shared
Clausen, Anders
1 / 2 shared
Lewis, Jennifer A.
1 / 2 shared
Ek, Sara
2 / 6 shared
Chen, Yaohui
2 / 7 shared
Chart of publication period
2021
2018
2017
2015
2014
2011

Co-Authors (by relevance)

  • Andersen, Morten N.
  • Sigmund, Ole
  • Ivinskaya, Aliaksandra
  • Lasson, Jakob Rosenkrantz De
  • Gutsche, Philipp
  • Häyrynen, Teppo
  • Burger, Sven
  • Gregersen, Niels
  • Breinbjerg, Olav
  • Frandsen, Lars Hagedorn
  • Kim, Oleksiy S.
  • Lavrinenko, Andrei V.
  • De Lasson, Jakob Rosenkrantz
  • Lavrinenko, Andrei
  • Mørk, Jesper
  • Moerk, Jesper
  • Malureanu, Radu
  • Haertel, Jan Hendrik Klaas
  • Sanna, Simone
  • Lei, Tian
  • Lazarov, Boyan Stefanov
  • Engelbrecht, Kurt
  • Alexandersen, Joe
  • Novitsky, Andrey
  • Jensen, Jakob Søndergaard
  • Clausen, Anders
  • Lewis, Jennifer A.
  • Ek, Sara
  • Chen, Yaohui
OrganizationsLocationPeople

document

Which Computational Methods Are Good for Analyzing Large Photonic Crystal Membrane Cavities?

  • Lasson, Jakob Rosenkrantz De
  • Gutsche, Philipp
  • Wang, Fengwen
  • Gregersen, Niels
  • Breinbjerg, Olav
  • Frandsen, Lars Hagedorn
  • Kim, Oleksiy S.
  • Moerk, Jesper
  • Ivinskaya, Aliaksandra
  • Malureanu, Radu
  • Häyrynen, Teppo
  • Burger, Sven
  • Sigmund, Ole
  • Lavrinenko, Andrei V.
Abstract

By introducing defects into an otherwise periodic photonic crystal lattice, high quality (Q) factor cavities may be formed. However, the size and the lack of simplifying symmetries in the photonic crystal membrane make these types of cavities exceptionally hard to analyze using numerical simulation methods. In this work, we consider<br/>two different line defect cavities and we compute their Q factors using state-of-the-art optical simulation tools. We show that certain simulation methods perform much better than others in the analysis of these challenging structures.

Topics
  • simulation
  • defect
  • crystalline lattice