Enalos Read Across Platform
Zeta Potential Predictive Model Based on Image Nanodescriptors
A new predictive model has been developed within NanoCommons project with the aid of Enalos Cloud Platform to support the safety-by-design concept. More specifically a read across predictive model was developed for zeta-potential of NMs and released through the platform as an online application. Based on the NM type of core, main elongation and pH value, interested users in NM design, can import different NM datasets and study the effects of different inputs on the zeta-potential value, a decisive step during the design process of novel NMs. Users should use the Enalos NanoXtract tool (http://enaloscloud.novamechanics.com/EnalosWebApps/NanoXtract/) or an image analysis tool of their choice, to provide the requested image nanodescriptor (main elongation). The produced results include the predicted zeta-potential values for each NM sample as well as a warning on the prediction reliability according to the domain of applicability limits. The neighbours of each NM in the training set are also available through the web-service.
- Provided by: NovaMechanics Ltd.
- Type: Predictive modelling
- Applicability domain: Image nanodescriptors (main elongation), NMs core.
- Topic: Data analysis
- Contact: Antreas Afantitis
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