Automated Crystallization Monitoring in Material Development using Computer Vision and Neuronal Networks

Crystallization is critical in producing various substances in the food and pharmaceutical industries. The process begins with nucleation from a supersaturated solution, followed by the directed movement of solute molecules toward the newly formed nuclei. This movement is influenced by different fac...

Full description

Saved in:
Bibliographic Details
Published inChemie ingenieur technik Vol. 96; no. 8; pp. 1107 - 1115
Main Authors Burgdorf, Simon‐Johannes, Roddelkopf, Thomas, Thurow, Kerstin
Format Journal Article
LanguageEnglish
Published 01.08.2024
Subjects
Computer vision
Crystallization monitoring
Laboratory automation
Materials research
openCV
Online AccessGet full text

Cover

More Information
Summary:Crystallization is critical in producing various substances in the food and pharmaceutical industries. The process begins with nucleation from a supersaturated solution, followed by the directed movement of solute molecules toward the newly formed nuclei. This movement is influenced by different factors such as molecular attraction and thermodynamic properties, which influence the resulting crystal size and shape. This paper presents an automated monitoring approach for the growth process of crystallization from saturated solutions. To monitor such a process, a combination of artificial intelligence and computer vision is used. The approach was developed for application in material research to automate the processing of numerous samples, which would otherwise require laboratory personnel. Exploration of new functional materials has evolved from traditional methods to incorporate AI, enhancing efficiency and cost‐effectiveness. This paper introduces a method using AI and computer vision to monitor and automate crystallization processes, crucial for developing new materials.
ISSN:0009-286X
1522-2640
DOI:10.1002/cite.202300049