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Artificial Intelligence
for Advanced Alloy Design
Rapid alloy composition discovery through materials property predictions and behavior modeling.
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Predictions
Our machine learning models enable us to predict a range of properties associated with any arbitrary alloy composition within seconds.
Modeling
We use state-of-the-art computational chemistry tools to accurately model the properties and behaviors associated with alloys from atomic to mesoscale.
1
CONCEPT
Derive a list of material properties based on the need of a client - generally, end-user or manufacturer.
2
PREDICTION
Generate material compositions that satisfy the objective properties through predictive algorithms.
3
MODELING
Accurately model the properties of the predicted material and further fine-tune the compositions.
4
EVALUATION
Experimental evaluation of the computational results through mechanical testing and characterization.
BMG
Our models are currently focused on Bulk Metallic Glass (BMG) or Amorphous Alloys. These materials are significantly tougher and resistant to corrosion than some of the most durable alloys known.
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Additive Manufacturing
We optimize the properties of our models for the evolving additive manufacturing landscape. Our computational chemistry models enable us to model processes such as Laser Powder Bed Fusion, Direct Energy Deposition, etc.
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Founding Team
Fazal
Chief Executive Officer
A Physics graduate with 2 years of experience in A.I. and Quantum Computing.
Gurjot
Chief Technology Officer
Ph.D. in Industrial Engineering, with a focus on using Machine Learning for Materials Science.
Abu
Chief Science Officer
2nd year of Ph.D. with focus on Concentrated Alloy Design through Computational Chemistry.
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