Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Alchemite specializes in AI-enhanced physical modeling and offers solutions that assist organizations in deriving actionable insights from both experimental and simulation data, merging machine learning techniques with physics-informed models to enhance prediction accuracy, decrease experimental expenses, and streamline product and process development. Their offerings encompass a variety of domains, including materials discovery and design, predictive modeling for performance and reliability, multiscale modeling that bridges atomic and macroscopic behavior, as well as the automation of various workflow tasks such as data integration, surrogate modeling, and model validation. Furthermore, they advocate for physics-aware neural networks and hybrid modeling strategies that adhere to fundamental scientific principles while simultaneously learning from data, leading to quicker and more precise simulations, a diminished need for costly physical testing, and better-informed decision-making processes. Intellegens' tools find applications in various fields, including the prediction of battery performance and optimization of chemical processes, showcasing their versatility and effectiveness in addressing complex challenges. By integrating advanced computational methodologies, Alchemite aims to empower organizations to innovate and achieve their goals more efficiently.

Description

ESPResSo, which stands for the Extensible Simulation Package for Research on Soft Matter, is a flexible and open-source simulation tool designed for executing and analyzing molecular dynamics and Monte Carlo simulations involving multiple particles. This package serves as a comprehensive resource for modeling a diverse range of soft matter systems, with a particular focus on coarse-grained atomistic or bead-spring models that find applications in fields such as physics, chemistry, molecular biology, and engineering processes. Users can leverage ESPResSo to simulate various phenomena, including polymers, liquid crystals, colloids, polyelectrolytes, ferrofluids, gels, biological systems, DNA structures, lipid membranes, bacterial movements, and even super-capacitors. By employing coarse-grained models, where clusters of atoms or molecules are simplified into single beads, researchers can explore significantly larger time and length scales that would be unfeasible with purely atomistic approaches. Furthermore, ESPResSo enables the execution of classical molecular dynamics simulations across multiple statistical ensembles, enhancing its versatility in scientific research. This capability allows scientists to tackle complex problems in soft matter physics more efficiently and effectively.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Python No 

Integrations

Python Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Intellegens

Founded

2017

Country

United Kingdom

Website

intellegens.com/solutions/

Vendor Details

Company Name

ESPResSo

Country

United States

Website

espressomd.org/wordpress/

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives

LIGGGHTS Reviews

LIGGGHTS

CFDEM
StarDrop Reviews

StarDrop

Optibrium
NAMD Reviews

NAMD

Theoretical and Computational Biophysics Group