PSE Releases Major Update of gCRYSTAL Process Modelling Software
- Full polymorph handling brings a step change to crystallization process design
With its ability to rigorously predict particle size distributions, gCRYSTAL provides an integrated, easy-to-use, drag & drop graphical environment for R&D personnel, process engineers and scientists engaged in characterisation, design, scale-up and operation of crystallization processes.
A major addition in gCRYSTAL 4.0 is support for multiple crystal phases. This allows accurate modelling of crystallization and transformation of compounds exhibiting polymorphism, providing the ability to maximise yield with respect to the desired polymorph. In addition, the new version contains significantly enhanced parameter estimation and optimisation workflows; the ability to estimate scale-independent kinetic parameters simultaneously using experiments from different scales; various enhancements to kinetic models; new models, including a seed pot model that allows seeding at any (including multiple) points in time; and improved access to model help documentation.
gCRYSTAL 4.0 builds on gCRYSTAL’s powerful existing capabilities for batch, semi-batch and continuous crystallization process design and operational analysis, which include capabilities for estimating growth and other kinetic parameters from experimental data; multizonal modelling - utilising links with computational fluid dynamics (CFD) software - for reliable scale-up; and industry-leading optimisation facilities.
The software has been developed in conjunction with several leading companies from industries where crystallization processes - including precipitation - play an integral part, such as pharmaceuticals, fine and bulk chemicals, agrochemicals, food processing, consumer goods and minerals and mining.
Dr Sean Bermingham, VP of PSE’s Life Sciences, Consumer Products and Specialty Chemicals businesses, says “The inclusion of full polymorph handling in gCRYSTAL 4.0 brings a significant enhancement to the toolset available to engineers and scientists designing and operating crystallization processes. In addition, the significant improvements in usability of the parameter estimation capabilities streamline the all-important step of validating kinetic models with experimental data in order to provide accurate predictive models that can be used with confidence in scale-up and other critical design activities.”
Website: http://www.psenterprise.com
Contact
Process Systems Enterprise
Kate Burness
+44-20-8563-0888
k.burness@psenterprise.com
Editors: www.psenterprise.com/news/pr140320.html
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2021년 4월 28일 14:30
