932 87 306
- Unit:
- SINTEF Industry
- Department:
- Biotechnology and Nanomedicine
- Office:
- Trondheim
Publications
- Utilization of machine learning on FT-ICR MS spectra for improved understanding and prediction of theproperties of hydrate-active components
- A new high pressure method for successive accumulation of hydrate active components
- Developing machine learning models for identifying chemical components from wide and short FT-ICR mass spectrometry data
- Identifying components related to hydrate formation by machine learning-based variable selection
- Combined analytical strategies for chemical and physical characterization of tar from torrefaction of olive stone
- Demonstration of a novel instrument for online monitoring of absorber emissions to air
- Microencapsulation of Peppermint Oil by Complex Coacervation and Subsequent Spray Drying Using Bovine Serum Albumin/Gum Acacia and an Oxidized Starch Crosslinker
- Towards a machine learning based produced for interpretation of mass spectra for better understanding of hydrate phenomena in oil systems
- Crude oil characterization with a new dynamic emulsion stability technique
- Successive accumulation of naturally occurring hydrate active components and the effect on the wetting properties