Positron Emission Particle Tracking: A comprehensive guide

Clicks: 1
ID: 311745
2022
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #597 of 631 articles by views in science and technology of advanced materials

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 631 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract

Positron Emission Particle Tracking (PEPT) is a technique which allows the three-dimensional, internal dynamics of opaque systems to be imaged with high temporal and spatial resolution. This book provides both an accessible introduction to, and a comprehensive reference guide for the PEPT technique. The work provides detailed information regarding the technique, its underpinning principles and underlying physics, the detectors, tracers and algorithms which allow it to operate, and the extensive, discipline-spanning work which has been performed using it. The text is accompanied by detailed interactive examples and working pre- and post-processing codes which the reader can use not only to gain still deeper insight into how PEPT works, but to directly perform PEPT analysis using real data provided. It is aimed at masters students, PhD students and researchers for whom PEPT may be a valuable research tool.

Key features

• First comprehensive book on the PEPT technique

• Written by well-respected experts in the field

• Provides a practical treatment of the subject matter

• Contains interactive, editable online code, produced using JupyterLab

Reference Key
persistent_1771691785_6999df092fa24 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors David Parker
Journal science and technology of advanced materials
Year 2022
DOI
10.1088/978-0-7503-3071-8
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.