Inferring phase transitions and critical exponents from limited observations with thermodynamic maps
Phase transitions are ubiquitous across life, yet hard to quantify and describe accurately. In
this work, we develop an approach for characterizing generic attributes of phase transitions …
this work, we develop an approach for characterizing generic attributes of phase transitions …
Physics-constrained multi-objective bayesian optimization to accelerate 3d printing of thermoplastics
The printing outcome of vat photopolymerization (VPP) of thermoplastics largely depends on
physicochemical properties of monomers and their compositions in resins, which also …
physicochemical properties of monomers and their compositions in resins, which also …
Roadmap on machine learning glassy dynamics
Unravelling the connections between microscopic structure, emergent physical properties
and slow dynamics has long been a challenge when studying the glass transition. The …
and slow dynamics has long been a challenge when studying the glass transition. The …
Learning glass transition temperatures via dimensionality reduction with data from computer simulations: Polymers as the pilot case
Machine learning methods provide an advanced means for understanding inherent patterns
within large and complex datasets. Here, we employ the principal component analysis …
within large and complex datasets. Here, we employ the principal component analysis …
Rapid, Accurate and Reproducible Prediction of the Glass Transition Temperature Using Ensemble-Based Molecular Dynamics Simulation
For the computational design of new polymeric materials, accurate methods for determining
the glass transition temperature (T g) are required. We apply an ensemble approach in …
the glass transition temperature (T g) are required. We apply an ensemble approach in …
A Computationally Informed Unified View on the Effect of Polarity and Sterics on the Glass Transition in Vinyl-based Polymer Melts
We unveil a unified view on the effect of side chains on the glass transition temperatures (T
g) in polymer melts by using molecular dynamics simulations, density functional theory …
g) in polymer melts by using molecular dynamics simulations, density functional theory …
[HTML][HTML] A novel approach for Tool-Narayanaswamy-Moynihan model parameter extraction using multi-scale neural model
The accurate determination of parameters in the Tool-Narayanaswamy-Moynihan (TNM)
model, which describes the viscoelastic behavior of glass-forming materials, is crucial for …
model, which describes the viscoelastic behavior of glass-forming materials, is crucial for …