Introduction

Demystifying Vacuum Metal Deposition [Archival]

Demystifying Vacuum Metal Deposition [Archival]

Overview

This course is directed to Crime Scene Investigators, Bureaus of Identification, and Forensic Science Laboratory Examiners.

The information will help departments justify the cost of a Vacuum Metal Deposition (VMD) and demonstrate to the fingerprint industry that VMD has been one of the most sensitive latent print development processes available since 1968.

A certificate of completion is available for all who register and attend this webinar.

Presenter

  • Scott Verbonus

Funding for this Forensic Technology Center of Excellence webinar has been provided by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice.

The opinions, findings, and conclusions or recommendations expressed in this webinar are those of the presenter(s) and do not necessarily reflect those of the U.S. Department of Justice.

Contact us at ForensicCOE@rti.org with any questions and subscribe to our newsletter for notifications.


Related Content

DNA Recovery After Sequential Processing of Latent Fingerprints on Black Polyethylene Plastic

Publication Journal of Forensic Sciences, February 2024  Authors Abigail S. Bathrick | Bode Technology Sarah Norsworthy | RTI International Dane T. Plaza | Bode Technology Mallory N. McCormick | United States Secret Service Donia Slack | RTI International Robert S. Ramotowski | United States Secret Service …

FLN-TWG: A Roadmap to Improve Research and Technology Transition in Forensic Science

← Back to FLN-TWG Main Page  Forensic Laboratory Needs Technology Working Group (FLN-TWG) The National Institute of Justice (NIJ), in partnership with the Forensic Technology Center of Excellence (FTCOE) at RTI International, formed the Forensic Laboratory Needs Technology Working Group…

Evaluation of Purdue University’s 3D Imaging Prototype for Footwear and Tire Impressions

Date September 2022 Overview Supported by two National Institute of Justice (NIJ) awards (2016-DN-BX-0189 and 2019-R2-CX-0069), Dr. Song Zhang and his research team at Purdue University led the development of a fully automated 3D imaging system for footwear and tire…