News Picture Generic

New algorithm for non-flowable powders

April 7, 2012

Chemspeed broadens the field of application of its solid dispensing technology with a new algorithm for non-flowable powders. Chemspeed Technologies, the leader in overhead gravimetric dispensing has improved the dispensing algorithm for non-flowable powders of its Gravimetric Dispensing Unit for Powders (GDU-P). Chemspeed’s unique and patented solution for overhead gravimetric dispensing of solids, liquids, viscous or waxy materials is the only solution capable of dispensing material into reactors or vials while they are being stirred and heated / cooled. With the new algorithm, the GDU-P, is now able to dispense an even wider range of materials. It can now deal with “non-flowable” powders that were previously impossible to dispense reliably with an automated system. Customer feedback has been enthusiastic: “No other automated dispensing system could achieve the same high accuracy and precision”. Chemspeed’s customers that have maintenance contracts and the GDU-P on their platform will automatically receive the new improved algorithm with the next software release. If you have powder dispensing challenges and would like to discuss them with our workflow architects, please contact us.

Other Recent News

Discover more news articles you might be interested in

Read more about Identifying critical powder properties for high-throughput dispensing of alumina and organic templates
News Picture 1 1 V2
Jun
16

Identifying critical powder properties for high-throughput dispensing of alumina and organic templates

Screening powder properties such as flowability, compressibility, and particle geometry is crucial for controlling ceramic processing, particularly in automated workflows that demand high reproducibility. Sacrificial templating for porous ceramics is well suited to automation because it is prone to variability arising from manual handling.

Read more about Integration of Machine Learning and Automated Synthesis for Accelerated Drug and Material Research
News Picture 1 1 V2
Jun
2

Integration of Machine Learning and Automated Synthesis for Accelerated Drug and Material Research

The challenges posed by global climate change and disease risks have intensified the demand for efficient and practical materials and molecules. Traditional trial-and-error approaches are becoming increasingly inefficient and resource-intensive. The rapid advancement of artificial intelligence (AI) has opened new avenues to accelerate research and shorten development cycles.

© Chemspeed Technologies 2026