Research

In-House Research Program

Scope: convergence of scalable synthesis, automated characterization, and advanced modeling to accelerate rational glycomaterial design.

Intellectual Merit: ability to rationally design glycomaterials does not currently exist.

• Innovations are required for predicting, synthesizing and characterizing carbohydrate self-assembly (relevant to aggregation, gelation, film formation, etc).

National and International Impact: discovery of completely novel materials and methods.

• Applications in areas as diverse as medicine, aerospace, renewable resources, and defense.

Iterative Approach: transdisciplinary, iterative, closed-loop approach.

• MGI approach integrates synthesis, characterization, and modeling to surmount scientific and technological barriers in glycomaterials research and innovation.

Major Goals of the In-House Program

1. Develop new chemical and enzymatic methods and protocols for the automated synthesis of glycopolymers with the guidance of advanced machine-learning techniques
2. Develop advanced automated modeling protocols that better account for the effects of molecular environment on the conformations and physical properties of glycopolymers.
3. Implement autonomous and automated computational methods for predicting and assigning the spectra (ROA, VCD, MS) of glycopolymers.
4. Develop high-throughput characterization methods for measuring the properties of glycomaterials.

MGI Approach to In-House Research

In-house research domains ( “Loops”) were created to address the Major Goals.

Loop 1: Novel Glycomaterials
(Lead: John Matson / Sanket Deshmukh)

Loop 2: Biocatalysis in Glycomaterial Creation
(Lead: Maren Roman)

Loop 3: Rational Glycomaterial Design
(Lead: Rob Woods)

Loop 4: Machine learning in Glycoscience
(Lead: Pengyu Hong)

Within each loop, the research program contains three core elements: synthesis, characterization, and theory that together synergize to advance research efficiency