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Updated: Sep 17, 2025

07:19
Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering
Published on: November 5, 2018
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Autonomous Small-Angle Scattering for Accelerated Soft Material Formulation Optimization
Tyler B Martin1,2, Duncan R Sutherland1, Austin McDannald3
1Materials Science & Engineering Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States.
Summary
We developed an Autonomous Formulation Lab (AFL) to speed up the creation of eco-friendly liquid formulations. Our AI-guided system efficiently explores new material combinations for better performance and sustainability.
Area of Science:
- Materials Science
- Chemical Engineering
- Artificial Intelligence
Background:
- Growing demand for sustainable and high-performance soft materials.
- Traditional formulation development is time-consuming and resource-intensive.
- Need for automated platforms to accelerate materials discovery.
Purpose of the Study:
- To introduce the Autonomous Formulation Lab (AFL) platform.
- To describe the design, tuning, and validation of an active learning agent for AFL.
- To demonstrate the platform's capability in accelerating eco-friendly formulation development.
Main Methods:
- Development of an Autonomous Formulation Lab (AFL) integrating automated sample preparation and characterization.
- Utilizing small-angle neutron and X-ray scattering for microstructure analysis.
- Employing an active learning agent, extensively tuned *in silico*, to guide experimental design.
Main Results:
- The active learning agent demonstrated efficiency and robustness against measurement variations and noise.
- Experimental validation successfully replaced a petroleum-derived component with a natural analog.
- The platform efficiently mapped formulation landscapes and identified areas for optimization.
Conclusions:
- The autonomously guided AFL platform significantly accelerates the discovery of novel liquid formulations.
- The developed active learning agent is a key component for efficient and targeted materials development.
- This technology supports the transition towards greener and more sustainable chemical products.

