Materials Map

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

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

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.

×

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.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Pannier, Christopher

  • Google
  • 2
  • 5
  • 0

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2023Benchmarking the Tensile Properties of Polylactic Acid (PLA) Recycled Through Fused Granule Fabrication Additive Manufacturingcitations
  • 2023System Identification of Fused Filament Fabrication Additive Manufacturing Extrusion and Spreading Dynamicscitations

Places of action

Chart of shared publication
Mohanty, Pravansu
2 / 2 shared
Nabhani, Dawood Al
1 / 1 shared
Habbal, Osama
2 / 2 shared
Kassab, Ali
2 / 2 shared
Ayoub, Georges
2 / 15 shared
Chart of publication period
2023

Co-Authors (by relevance)

  • Mohanty, Pravansu
  • Nabhani, Dawood Al
  • Habbal, Osama
  • Kassab, Ali
  • Ayoub, Georges
OrganizationsLocationPeople

document

System Identification of Fused Filament Fabrication Additive Manufacturing Extrusion and Spreading Dynamics

  • Mohanty, Pravansu
  • Habbal, Osama
  • Kassab, Ali
  • Pannier, Christopher
  • Ayoub, Georges
Abstract

In fused filament fabrication additive manufacturing, polymer extrusion and spreading dynamics affect build quality in both surface finish and mechanical properties. The state of the art in extrusion modeling and control is identification and compensation of a fixed first order pole with a linear model of the system. However, physical nonlinearities cause deviation of this pole in practice. To advance the aim of slicing using accurate nonlinear dynamic models, this work presents a system and procedure for automated measurement of dynamic bead extrusion. The system uses a belt printer, iFactory3D One Pro, with nozzle tilted 45 degrees from the build belt, and a snapshot 3D scanner. Single layer prints in polylactic acid (PLA) are scanned and then automatically ejected. The gcode for the single bead print holds the gantry speed fixed or extrusion speed constant while the extrusion flow rate or gantry speed is varied as a step input signal in space. The experiment design matrix varied two variables: gantry speed and extrusion flow rate. Time constants are fitted to bead area signals that are extracted from the scan data to obtain nonlinear models. Depending on the experiment condition, the percent difference between the highest time constant and the lowest time constant ranged from 279% to 61%, confirming the high nonlinearity of the extrusion system in FFF 3D printers. Additionally, measurements are performed on a cartesian 3D printer with a 2D scanner to test applicability of the methods to a general audience and verify observed trends. It was observed that larger steps in extrusion velocity for a constant X-Axis velocity, yielded smaller time constants, while the same steps in velocity using a constant extrusion velocity condition with variable X-Axis velocity, yielded the opposite trend. Moreover, the time constants for a step up in extrusion velocity yielded higher overall values in time constant when compared to step down conditions.

Topics
  • impedance spectroscopy
  • surface
  • polymer
  • experiment
  • extrusion
  • additive manufacturing
  • field-flow fractionation