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 …
Layer-by-layer unsupervised clustering of statistically relevant fluctuations in noisy time-series data of complex dynamical systems
Complex systems are typically characterized by intricate internal dynamics that are often
hard to elucidate. Ideally, this requires methods that allow to detect and classify in an …
hard to elucidate. Ideally, this requires methods that allow to detect and classify in an …
Dimensionality reduction of local structure in glassy binary mixtures
D Coslovich, RL Jack, J Paret - The Journal of Chemical Physics, 2022 - pubs.aip.org
We consider unsupervised learning methods for characterizing the disordered microscopic
structure of supercooled liquids and glasses. Specifically, we perform dimensionality …
structure of supercooled liquids and glasses. Specifically, we perform dimensionality …
Zundeig: The structure of the proton in liquid water from unsupervised learning
S Di Pino, ED Donkor, VM Sánchez… - The Journal of …, 2023 - ACS Publications
The structure of the excess proton in liquid water has been the subject of lively debate on
both experimental and theoretical fronts for the last century. Fluctuations of the proton are …
both experimental and theoretical fronts for the last century. Fluctuations of the proton are …
Do machine-learning atomic descriptors and order parameters tell the same story? The case of liquid water
Machine-learning (ML) has become a key workhorse in molecular simulations. Building an
ML model in this context involves encoding the information on chemical environments using …
ML model in this context involves encoding the information on chemical environments using …
DADApy: Distance-based analysis of data-manifolds in Python
DADApy is a Python software package for analyzing and characterizing high-dimensional
data manifolds. It provides methods for estimating the intrinsic dimension and the probability …
data manifolds. It provides methods for estimating the intrinsic dimension and the probability …
Molecular Understanding and Practical In Silico Catalyst Design in Computational Organocatalysis and Phase Transfer Catalysis—Challenges and Opportunities
CW Kee - Molecules, 2023 - mdpi.com
Through the lens of organocatalysis and phase transfer catalysis, we will examine the key
components to calculate or predict catalysis-performance metrics, such as turnover …
components to calculate or predict catalysis-performance metrics, such as turnover …
Detecting dynamic domains and local fluctuations in complex molecular systems via timelapse neighbors shuffling
M Crippa, A Cardellini, C Caruso… - Proceedings of the …, 2023 - National Acad Sciences
It is known that the behavior of many complex systems is controlled by local dynamic
rearrangements or fluctuations occurring within them. Complex molecular systems …
rearrangements or fluctuations occurring within them. Complex molecular systems …
The collective burst mechanism of angular jumps in liquid water
Understanding the microscopic origins of collective reorientational motions in aqueous
systems requires techniques that allow us to reach beyond our chemical imagination …
systems requires techniques that allow us to reach beyond our chemical imagination …
TimeSOAP: Tracking high-dimensional fluctuations in complex molecular systems via time variations of SOAP spectra
Many molecular systems and physical phenomena are controlled by local fluctuations and
microscopic dynamical rearrangements of the constitutive interacting units that are often …
microscopic dynamical rearrangements of the constitutive interacting units that are often …