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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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
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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (8/8 displayed)

  • 2022A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking23citations
  • 2022A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking23citations
  • 2019Understanding the Static Interfacial Polymer Layer by Exploring the Dispersion States of Nanocomposites43citations
  • 2019Understanding the Static Interfacial Polymer Layer by Exploring the Dispersion States of Nanocomposites43citations
  • 2018Characterization of the NISTmAb Reference Material using small-angle scattering and molecular simulation16citations
  • 2016Atomistic modelling of scattering data in the ollaborative Computational Project for Small Angle Scattering (CCP-SAS)76citations
  • 2016Atomistic modelling of scattering data in the ollaborative Computational Project for Small Angle Scattering (CCP-SAS)76citations
  • 2016Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)76citations

Places of action

Chart of shared publication
Irving, Thomas C.
4 / 4 shared
He, Lilin
1 / 2 shared
Sokolov, Alexei P.
1 / 12 shared
Lehmann, Michelle
2 / 2 shared
Dieudonne-George, Philippe
1 / 6 shared
Bocharova, Vera
1 / 15 shared
Saito, Tomonori
1 / 2 shared
Carroll, Bobby
2 / 13 shared
Oberdisse, Julian
2 / 100 shared
Genix, Anne-Caroline
2 / 89 shared
Dieudonné-George, Philippe
1 / 7 shared
Curtis, Joseph E.
4 / 4 shared
Castellanos, Maria Monica
1 / 2 shared
Mattison, Kevin
1 / 1 shared
Zhang, Hailiang
3 / 3 shared
Edler, Karen J.
2 / 18 shared
Chen, Jianhan
3 / 3 shared
Terrill, Nicholas J.
2 / 4 shared
Wright, David W.
2 / 2 shared
King, Stephen M.
3 / 16 shared
Perkins, Stephen J.
3 / 4 shared
Scott, David J.
2 / 3 shared
Butler, Paul D.
2 / 2 shared
Brookes, Emre H.
3 / 4 shared
Barlow, David J.
1 / 3 shared
Barlow, Dj
1 / 1 shared
Scott, Dj
1 / 2 shared
Wright, Dw
1 / 2 shared
Terrill, Nj
1 / 2 shared
Butler, Pd
1 / 1 shared
Edler, Kj
1 / 1 shared
Chart of publication period
2022
2019
2018
2016

Co-Authors (by relevance)

  • Irving, Thomas C.
  • He, Lilin
  • Sokolov, Alexei P.
  • Lehmann, Michelle
  • Dieudonne-George, Philippe
  • Bocharova, Vera
  • Saito, Tomonori
  • Carroll, Bobby
  • Oberdisse, Julian
  • Genix, Anne-Caroline
  • Dieudonné-George, Philippe
  • Curtis, Joseph E.
  • Castellanos, Maria Monica
  • Mattison, Kevin
  • Zhang, Hailiang
  • Edler, Karen J.
  • Chen, Jianhan
  • Terrill, Nicholas J.
  • Wright, David W.
  • King, Stephen M.
  • Perkins, Stephen J.
  • Scott, David J.
  • Butler, Paul D.
  • Brookes, Emre H.
  • Barlow, David J.
  • Barlow, Dj
  • Scott, Dj
  • Wright, Dw
  • Terrill, Nj
  • Butler, Pd
  • Edler, Kj
OrganizationsLocationPeople

article

Atomistic modelling of scattering data in the ollaborative Computational Project for Small Angle Scattering (CCP-SAS)

  • Zhang, Hailiang
  • Edler, Karen J.
  • Curtis, Joseph E.
  • Chen, Jianhan
  • Terrill, Nicholas J.
  • Wright, David W.
  • Irving, Thomas C.
  • King, Stephen M.
  • Krueger, Susan
  • Perkins, Stephen J.
  • Scott, David J.
  • Butler, Paul D.
  • Brookes, Emre H.
Abstract

<p>The capabilities of current computer simulations provide a unique opportunity to model small-angle scattering (SAS) data at the atomistic level, and to include other structural constraints ranging from molecular and atomistic energetics to crystallography, electron microscopy and NMR. This extends the capabilities of solution scattering and provides deeper insights into the physics and chemistry of the systems studied. Realizing this potential, however, requires integrating the experimental data with a new generation of modelling software. To achieve this, the CCP-SAS collaboration (http://www.ccpsas.org/) is developing opensource, high-throughput and user-friendly software for the atomistic and coarsegrained molecular modelling of scattering data. Robust state-of-the-art molecular simulation engines and molecular dynamics and Monte Carlo force fields provide constraints to the solution structure inferred from the small-angle scattering data, which incorporates the known physical chemistry of the system. The implementation of this software suite involves a tiered approach in which GenApp provides the deployment infrastructure for running applications on both standard and high-performance computing hardware, and SASSIE provides a workflow framework into which modules can be plugged to prepare structures, carry out simulations, calculate theoretical scattering data and compare results with experimental data. GenApp produces the accessible webbased front end termed SASSIE-web, and GenApp and SASSIE also make community SAS codes available. Applications are illustrated by case studies: (i) inter-domain flexibility in two- to six-domain proteins as exemplified by HIV-1 Gag, MASP and ubiquitin; (ii) the hinge conformation in human IgG2 and IgA1 antibodies; (iii) the complex formed between a hexameric protein Hfq and mRNA; and (iv) synthetic 'bottlebrush' polymers.</p>

Topics
  • impedance spectroscopy
  • polymer
  • simulation
  • molecular dynamics
  • electron microscopy
  • Nuclear Magnetic Resonance spectroscopy
  • bottlebrush