# Features

*all*relevant computational chemistry algorithms, from quantum to molecular and coarse-grained modeling, to informatics and thermodynamics, and all sorts of automated mappings between different levels.

A unique and compelling feature of CULGI software is the concept of scripted workflows. Workflows can be edited through either our proprietary graphical scripting editor or python.

In a typical application, a bespoke script is made by either client or us in a service contract.

Scripting is the key to success, in modeling a wide variety of systems.

#### Quantum Chemistry

We have optimized Qeq for database screening. For a given molecule of MW 500, a CULGI charge Qeq calculation would take a few seconds, a semi-empirical calculation a few minutes, and a DFT calculation a few hours or days. The parameter sets of all CULGI methods are open and can be modified as suited by the user. For example, a proprietary optimization of Qeq calculations as input to COSMO-RS calculations is entirely possible, by writing a script that loops over the CULGI database.

Through the interface to NWChem, CULGI can model the quantum behavior of solids (plane wave) and molecules. The range of Density Functional methods in NWChem is comprehensive and covers all popular functionals.

NWChem is included in the installation.

#### Molecular Dynamics

### Unity in Diversity

CULGI software is a general modeling package, and, by means of our scripting editor, can be used just as easily for providing solutions in Oil and Gas, Personal and Home Care, Chemicals, and Pharma.

#### Coarse-Grained Simulations

Coarse-grained simulation engines include Brownian and dissipative particle dynamics. Interaction models are comprehensive. They can consist of actives, charged systems, colloids, polymers, surfactants, and also reactive systems. Coarse-grained forcefields can be simple linear as in dissipative particle dynamics, or more complex ones (by using tabular input).

#### Chemical Informatics and Machine Learning

CULGI includes a range of statistical calculation methods, such as linear and non-linear regression, and genetic algorithms.

One of many ways one could extend the modeling capabilities is the interfacing of CULGI to Machine Learning software, for instance, TensorFlow (from Google). By importing both CULGI and TensorFlow in a python script, one enables the combination of state of the art physics-modeling with state of the art data-driven modeling.

#### Engineering ThermodynamicS: COSMO-RS

Using COMO-RS, the user is capable of predicting thermodynamic properties such as pK, logP and mixing Gibbs energies from the molecular composition.

COSMO-RS is particularly useful for calibration coarse-grained simulations.

Another special feature of CULGI’s COSMO-RS is that we can offer the method based on superfast empirical and semi-empirical quantum calculations.