Ultra-high Efficiency Pixelated Area Detector for Energy Resolved Nano-scale Tissue Imaging with He Ion Beam Microscopy

Period of Performance: 09/19/2017 - 03/18/2018

$227K

Phase 1 SBIR

Recipient Firm

Direct Electron, LP
San Diego, CA 92128
Principal Investigator

Abstract

PROJECT SUMMARY The Helium Ion Microscope has been developed over the last five years into a powerful tool for imaging a wide range of samples at sub-nanometer resolution. It offers unique features for biomedical research by virtue of its ability to image, without coatings, non-conductive specimens such as bio-tissues and nano-structures in cells at resolutions beyond those attainable by other techniques. The goal of this Phase I proposal is to develop a high efficiency detector capable of energy discrimination for the Helium Ion Microscope that will add efficient elemental mapping capability to this already powerful technique. The proposed detector, based on Direct Electron?s proven sensor technology, will overcome sensitivity, acquisition speed, flexibility, and cost limitations of current spectrometers. From the specific energy and spatial distribution of ions scattered in the microscope, it will be possible to determine both elemental structure and composition of the sample on the nanometer scale. This innovation will provide a new imaging tool to study causes of human diseases such as kidney stone formation, bone tissue degradation and regeneration, nanoparticle toxicity, blood vessel damage and aging, and eventually we expect it to lead to new drug discoveries and treatment. In the first phase of the project an existing Direct Electron CMOS sensor developed for high-energy electrons (100 keV to 1 MeV) will be modified to provide the necessary detection efficiency and energy resolution for ions. The modifications will include preparation of the sensor surface so that ions can interact and produce measurable signals. The sensor will be operated in a newly designed camera and tested at the state-of-the-art Helium Ion Microscope facility at Rutgers University. The multi-dimensional image data analysis process will also be further developed based on preliminary work done at DE and Rutgers.