Automated and Selective Product Removal for Lab-Scale Draft Tube Baffle Crystallizer Under Vacuum Operation

Continuous product removal in lab-scale vacuum applications poses significant challenges, particularly due to the risk of clogging in the product tube caused by the small tubing diameter relative to the particle size. This contribution addresses this problem by presenting an automatic gate system specifically designed for selective product removal within a Draft Tube Baffle Crystallizer (DTBC). In order to enable selective product removal, the classification behavior of the crystals in the DTBC was evaluated in experimental studies by determining the crystal size distributions in the product removal and in the fine grain dissolution. The influence of different stirring speeds and solid contents were considered for different product removal rates. The results indicated that sufficient classification occurs at stirring speeds of 600 rpm and a crystal content of ≥3 wt%. Under these conditions, more than 75% of the crystals in the product were larger than 210 μm from a sieve size range of 45 to 500 µm. During experiments, the automatic gate system allowed for blockage-free, continuous product removal for six hours per experiment and more than thirty hours in total, proving the reliability of the system. Although designed for down-scaling of the DTBC, this system can also be applied to other continuous-flow lab-scale applications.

Authors

Institutions

Publication Details

Journal
Crystals
Published
2025-10-15
DOI
https://doi.org/10.3390/cryst15100893
Primary Topic
Crystallization and Solubility Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Automated and Selective Product Removal for Lab-Scale Draft Tube Baffle Crystallizer Under Vacuum Operation

Norbert Kockmann, M. Hubmann, Laura Marsollek, Kim Buchhorn
Crystals
Crystallization and Solubility Studies
article

Automated and Selective Product Removal for Lab-Scale Draft Tube Baffle Crystallizer Under Vacuum Operation

Norbert Kockmann, M. Hubmann, Laura Marsollek, Kim Buchhorn
article en

Abstract

Continuous product removal in lab-scale vacuum applications poses significant challenges, particularly due to the risk of clogging in the product tube caused by the small tubing diameter relative to the particle size. This contribution addresses this problem by presenting an automatic gate system specifically designed for selective product removal within a Draft Tube Baffle Crystallizer (DTBC). In order to enable selective product removal, the classification behavior of the crystals in the DTBC was evaluated in experimental studies by determining the crystal size distributions in the product removal and in the fine grain dissolution. The influence of different stirring speeds and solid contents were considered for different product removal rates. The results indicated that sufficient classification occurs at stirring speeds of 600 rpm and a crystal content of ≥3 wt%. Under these conditions, more than 75% of the crystals in the product were larger than 210 μm from a sieve size range of 45 to 500 µm. During experiments, the automatic gate system allowed for blockage-free, continuous product removal for six hours per experiment and more than thirty hours in total, proving the reliability of the system. Although designed for down-scaling of the DTBC, this system can also be applied to other continuous-flow lab-scale applications.

CrystalsVol. 15(10)
TU Dortmund University (DE)
Technische Universität Dortmund
Openalex Percentile: Top 77%
Crystallization and Solubility Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.