Hydrogel Property Prediction Platform

Predict Young's Modulus and Ionic Conductivity of hydrogels using deep learning models

This platform uses custom deep learning models trained on experimental data to predict hydrogel properties based on chemical composition.

Input Parameters

Monomer

Acrylamide (AAm)
Recommended range: 10-90

Crosslinker

Polyethylene glycol diacrylate (PEGDA)
Recommended range: 1-100

Initiator (Fixed)

Diethylamino phenyl ketone (DEAP)
Recommended range: 2 - 50

Additive

1-Ethyl-3-methylimidazolium tetrafluoroborate (EMIMBF4)
Recommended range: 0-100

Prediction Result

Young's Modulus
0.00
kPa

Input Summary

Monomer
Type: AAm
Concentration: 0 μL/mL
Crosslinker
Type: PEGDA
Concentration: 0 μL/mL
Initiator
Type: DEAP
Concentration: 0 μL/mL
Additive
Type: EMIMBF4
Concentration: 0 μL/mL