The latest version of J-OCTA V6.1 has been released in September 2020.
In this version, following new functions and improvements are included.

Key new functions and improvements in J-OCTA V6.1

• 1. SIESTA Modeler and FCEWS.
• SIESTA Modeler (Modeling tool for SIESTA) has been implemented, and the interface with FCEWS.
  (X(Chi) parameter estimation tool with FMO method) has been updated.
  By using SIESTA Modeler, you can calculate stable structures, elastic modulus and reaction paths and more, with Density Functional Theory (DFT).
• 2. Machine Learning QSPR
• Trained models about several material properties are added and the features of Machine Learning are improved.
• Latest feature to extract the common molecular structure has been implemented.
• Using this feature, we can extract common molecular substructures based on the range of specified physical properties.
• 3. Modeling functions
• Additional functions for scenarios are developed, which is useful to build and share the workflow to estimate material properties.
  PCFF force field is supported in the molecular modeling.
  API function for high throughput calculations without GUI has been released. This function is useful to build the material property DB for Machine Learning.
• 4. i-Rheo GT for J-OCTA
• "i-Rheo GT" proposed by Dr.M.Tassieri from The University of Glasgow has been implemented in J-OCTA.
  i-Rheo GT converts the relaxation modulus obtained by MD to complex elastic modulus.

In this seminar, we will introduce and demonstrate new features in the latest version of J-OCTA, and show you how to use J-OCTA conveniently.

Our presentation about the machine learning includes the common substructure extraction and simple inverse problems solving by the feature. Futhermore, we also show you future roadmap about the ML-QSPR, machine learning based QSPR.

We look forward to your participation.