Characterization Research

Robust and varied data sets are essential for model validation, machine learning,
and database population to support knowledge sharing across the glycomaterials
community.

Characterization Data Types

Molecular structure determination
- Mass spectrometry
- NMR spectroscopy
Intermolecular interaction quantification
- Biolayer interferometry (BLI)
- Surface plasmon resonance (SPR)
- Quartz crystal microbalance
Three‑dimensional shape analysis
- Computational simulation
- NMR, Raman optical activity (ROA), and vibrational circular dichroism (VCD)
Solution and rheological properties
- Viscosity and gel formation
- Persistence length
- Radius of gyration and hydrodynamic radius

Overview of glycomaterial characterization methods spanning structural, interaction, shape, and rheological measurements

Overview of experimental and computational characterization approaches used to
generate data sets for glycomaterial modeling, machine learning, and validation.