SuntheticsML
SuntheticsML is an easy-to-use machine learning (ML) platform that helps you develop new materials, processes, and formulations up to 10 times faster.
Leveraging a combination of chemical engineering concepts and ML predictive algorithms, we can use very few data points to accurately predict your system's behavior.
Our software can improve existing manufacturing processes, unlock unprecedented performance, and it can be further used to identify anomalies and facilitate diagnostics.
- Shorter experimental campaigns - saves money, time, energy, and materials from lower number of experiments!
- Reaction agnostic approach
- Easy visualization and exploration of complex reaction trends
-Unlocks unprecedented performance
-No expertise in ML or statistics required
- Only 5 data points required to begin analysis
SuntheticsML tool has been piloted with chemical companies and academic research groups in 10+ different research areas. Through a better understanding of reaction behavior and variable effects, users identify optimal conditions and formulations using up to 10 times less experiments than more traditional experimental campaigns or DoE.
Electrochemical Reaction Optimization
Performance Improvement: Sunthetics identified a 7% higher faradaic efficiency, optimizing flow rate, current density, and reactant concentration.
Data reduction: Sunthetics' campaign used 75% less experiments, time, and resources.
Total number of experiments required: 9
Controlling aspect ratio of crystals
Performance Improvement: Sunthetics identified a 13% better aspect ratio optimizing 5 crystallization variables
Data reduction: Sunthetics' campaign used 70% less experiments, time, and resources than the company's Design of Experiments.
Total number of experiments required: 5
Prediction of Material Properties
Performance Improvement: Sunthetics identified a 40% higher fracture toughness in polymer double networks optimizing formulation and polymerization conditions.
Data reduction: Sunthetics' campaign used 80% less experiments, time, and resources.
Total number of experiments required: 4
FAQ
- What types of reactions does the tool work with?
SuntheticsML is built to be reaction-agnostic. Our tool learns from the reaction/system at hand. Our algorithms can be used with electrochemical reactions, catalytic processes, formulation optimization, prediction of material properties, and much more. If you have a question about a particular research area, contact us!
- What type of variables does it take?
The paltform can handle any variable relevant to your system, as long as it is a variable that you can quantify.
- Do I need to know AI, programming, or statistics to use this?
No! Our tool is extremely easy to use. Users upload an excel or csv file with the data from a few experiments and our algorithms will do all the work.
- What if I do not wish to use the cloud-based software?
Our cloud-based software is designed to be an AI partner available to the researcher at all times. However, if you do not wish to use the software yourself, we can assign one of our engineers to your project. They will run all optimizations for you and assist you through the process.
- Do I need hundreds of data points to use ML?
No! Our tool is designed to leverage information from very small datasets. Users commonly start using our algorithms with only 5 data points.
- Is this the same as DoE?
SuntheticsML is based on a bayesian optimization approach that guides experimentation to reduce the number of life experiments required. Traditional DoE can have limitations when modeling complex reactions that have multiple local mimina/maxima. SuntheticsML can map complex reaction spaces more effectively than traditional DoE, achieving higher performance with less experiments.
SuntheticsML is a stand-alone tool capable of improving scientists' productivity, guiding experimentation, and achieving unprecedented efficiencies. However, users can always complement their DoE-enabled analysis with our tool to enhance the accuracy of the models and predictions.
