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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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.

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Naji, M.
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Mitchell, Daniel

  • Google
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MRC Cognition and Brain Sciences Unit

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (24/24 displayed)

  • 2021A Review of Sensing Technologies for Non-Destructive Evaluation of Structural Composite Materials82citations
  • 2020The Functional Convergence and Heterogeneity of Social, Episodic, and Self-Referential Thought in the Default Mode Network77citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.22.0citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.23.3citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.22.2citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.23.1citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.23.0citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.23.2citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.19.6citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.20.1citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.20.0citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.20.3citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.21.0citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.20.2citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.19.2citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.19.0citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.18.2citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.18.0citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.19.5citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.19.3citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.17.0citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.18.1citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.18.3citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.19.4citations

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Chart of shared publication
Bucknall, David
1 / 4 shared
Blanche, Jamie
1 / 3 shared
Harper, Sam
1 / 1 shared
Baines, Lee
1 / 2 shared
Tang, Wenshuo
1 / 1 shared
Flynn, David
1 / 25 shared
Gupta, Ranjeetkumar
1 / 21 shared
Pancholi, Ketan
1 / 30 shared
Bastholm, Eric
22 / 22 shared
Ord, Stephen
22 / 24 shared
Lenc, Emil
22 / 23 shared
Van Diepen, Ger
22 / 22 shared
Whiting, Matthew
22 / 23 shared
Khoo, Jonathan
22 / 22 shared
Collins, Daniel
22 / 22 shared
Wu, Xinyu
22 / 22 shared
Marquarding, Malte
22 / 22 shared
Bannister, Keith
22 / 22 shared
Lahur, Paulus
22 / 22 shared
Maher, Tony
22 / 22 shared
Voronkov, Max
22 / 22 shared
Guzman, Juan
22 / 22 shared
Chart of publication period
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Co-Authors (by relevance)

  • Bucknall, David
  • Blanche, Jamie
  • Harper, Sam
  • Baines, Lee
  • Tang, Wenshuo
  • Flynn, David
  • Gupta, Ranjeetkumar
  • Pancholi, Ketan
  • Bastholm, Eric
  • Ord, Stephen
  • Lenc, Emil
  • Van Diepen, Ger
  • Whiting, Matthew
  • Khoo, Jonathan
  • Collins, Daniel
  • Wu, Xinyu
  • Marquarding, Malte
  • Bannister, Keith
  • Lahur, Paulus
  • Maher, Tony
  • Voronkov, Max
  • Guzman, Juan
OrganizationsLocationPeople

document

ASKAP Science Data Processor software - ASKAPsoft Version 0.18.1

  • Mitchell, Daniel
  • Bastholm, Eric
  • Ord, Stephen
  • Lenc, Emil
  • Van Diepen, Ger
  • Whiting, Matthew
  • Khoo, Jonathan
  • Collins, Daniel
  • Wu, Xinyu
  • Marquarding, Malte
  • Bannister, Keith
  • Lahur, Paulus
  • Maher, Tony
  • Voronkov, Max
  • Guzman, Juan
Abstract

ASKAPsoft, the ASKAP Science Data Processor, provides data processing functionality, including:* Calibration * Spectral line imaging * Continuum imaging * Source detection and generation of source catalogs * Transient detectionASKAPsoft is developed as a part of the CSIRO Australian Square Kilometre Array Pathfinder (ASKAP) Science Data Processor component. ASKAPsoft is a key component in the ASKAP system. It is the primary software for storing and processing raw data, and initiating the archiving of resulting science data products into the data archive (CASDA).The processing pipelines within ASKAPsoft are largely written in C++ built on top of casacore and other third party libraries. The software is designed to be parallelised, where possible, for performance.ASKAPsoft is designed to be built and executed in a standard Unix/Linux environment and core dependencies must be fulfilled by the platform. These include, but are not limited to, a C/C++/Fortran compiler, Make, Python 2.7, Java 7 and MPI. More specific dependencies are downloaded by the ASKAPsoft build system and are installed within the ASKAPsoft development tree. Specific to the Debian platform, after a standard installation of Debian Wheezy (7.x) the following packages will need to be installed with apt-get:* g++ * gfortran * openjdk-7-jdk * python-dev * flex * bison * openmpi-bin * libopenmpi-dev * libfreetype6-dev * libpng12-devMore information regarding the building, installation and running of the software can be found in the README file in the root of the file structure that forms this collection.Source code can be accessed via the links in Related Materials section.-----This patch release sees a few bug-fixes to the pipeline scripts:* When re-running the pipeline on already-processed data, where the rawinput data no longer exists in the archive directory, the pipeline waspreviously failing due to it not knowing the name of the MS or therelated metadata file. It now has the ability to readMS_INPUT_SCIENCE and MS_INPUT_1934 anddetermine the metadata file from that. It will also not try to run jobs thatdepend on the raw data.* The new imager used in spectral-line mode can now be directed tocreate a single spectral cube, even with multiple writers, via theALT_IMAGER_SINGLE_FILE andALT_IMAGER_SINGLE_FILE_CONTCUBE parameters.* There have been changes to the defaults for the number of cores forspectral imaging (from 2000 to 200) and the number of cores per nodefor continuum imaging (from 16 to 20), based on benchmarking tests.* In addition, the following bugs were fixed:- The ntasks-per-node parameter could sometimes be more than ntasks,causing a slurm failure.- The self-calibration algorithm was not retaining images from theintermediate loops.- The image-based continuum subtraction script was not finding thecorrect image cube.

Topics
  • impedance spectroscopy
  • mass spectrometry
  • atom probe tomography