Robotic Surface Analysis Mass Spectrometry (RoSA-MS) of Three-Dimensional Objects.

Academic Article

Abstract

  • Many technologies currently exist that are capable of analyzing the surface of solid samples under ambient or vacuum conditions, but they are typically limited to smooth, planar surfaces. Those few that can be applied to nonplanar surfaces, however, require manual sampling and a high degree of human intervention. Herein, we describe a new platform, Robotic Surface Analysis Mass Spectrometry (RoSA-MS), for direct surface sampling of three-dimensional (3D) objects. In RoSA-MS, a sampling probe is attached to a robotic arm that has 360° rotation through 6 individual joints. A 3D laser scanner, also attached to the robotic arm, generates a digital map of the sample surface that is used to direct a probe to specific ( x, y, z) locations. The sampling probe consists of a spring-loaded needle that briefly contacts the object surface, collecting trace amounts of material. The probe is then directed at an open port liquid sampling interface coupled to the electrospray ion source of a mass spectrometer. Material on the probe tip is dissolved by the solvent flow in the liquid interface and mass analyzed with high mass resolution and accuracy. The surface of bulky, nonplanar objects can thus be probed to produce chemical maps at the molecular level. Applications demonstrated herein include the examination of food sample surfaces, lifestyle chemistry, and chemical reactions on curved substrates. The modular design of this system also allows for modifications to the sampling probe and the ionization source, thereby expanding the potential of RoSA-MS for a great diversity of applications.
  • Authors

  • Li, Anyin
  • Paine, Martin RL
  • Zambrzycki, Stephen
  • Stryffeler, Rachel B
  • Wu, Jason
  • Bouza, Marcos
  • Huckaby, Jake
  • Chang, Chu-Yin
  • Kumar, Manoj
  • Mukhija, Piyoosh
  • Fernández, Facundo M
  • Status

    Publication Date

  • March 20, 2018
  • Has Subject Area

    Published In

    Keywords

  • Bioengineering
  • Digital Object Identifier (doi)

    Pubmed Id

  • 29494147
  • Start Page

  • 3981
  • End Page

  • 3986
  • Volume

  • 90
  • Issue

  • 6