Abstract

Spin-echo small-angle neutron scattering (SESANS) yields structural information on length scales from 30 nanometres up till 20 micrometres. These length scales match nicely those of colloids, protein networks and fat droplets, which are present in many food materials. This makes SESANS an excellent probe to study food materials. An interesting feature of SESANS is the real space character of the raw data. Several examples of quantitative neutron scattering studies on food materials are shortly reviewed. • Spin-echo small-angle neutron scattering techniques can probe the bulk structure of food materials from a length scale of 30 nanometre up till 20 micrometre. • Spin-echo small-angle neutron scattering yields direct space results which allow for direct visual data interpretation. • Several successful spin-echo small-angle neutron scattering studies have been performed to clarify food material structures.

Highlights

  • Spin-echo small-angle neutron scattering (SESANS) yields structural information on length scales from 30 nanometres up till 20 micrometres. These length scales match nicely those of colloids, protein networks and fat droplets, which are present in many food materials

  • An interesting feature of SESANS is that the direct measurement data are in real space, which is for layman already interpretable without any strong background into scattering theory

  • In the examples given above the length scales were ranging over three orders in magnitude

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Summary

Small-angle neutron scattering

The food industry seeks methods to produce high quality food with new, often more sustainable, ingredients. To rationally redesign food processing methods structural information on all length scales is needed. Scattering yields quantitative descriptions of the structure of food that can be modelled based on input from microscopy. Neutron scattering is another natural probe to study food materials (Lopez-Rubio & Gilbert, 2009). Some review articles on (small-angle) neutron scattering studies on food materials have been published (Gilbert, 2019; Lopez-Rubio & Gilbert, 2009). The article concludes with examples on larger structures, as fat droplets, air bubbles and fibre structures

Principle of SESANS
Data analysis
Instrumentation
Comparison with SANS and USAns
Colloids
Networks
Droplets and fibres
Conclusions and outlook
Full Text
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