Recent Advances in Machine Learning‐Assisted Multiscale Design of Energy Materials
B Mortazavi - Advanced Energy Materials, 2024 - Wiley Online Library
This review highlights recent advances in machine learning (ML)‐assisted design of energy
materials. Initially, ML algorithms were successfully applied to screen materials databases …
materials. Initially, ML algorithms were successfully applied to screen materials databases …
Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments
Molecular dynamics (MD) simulations allow insights into complex processes, but accurate
MD simulations require costly quantum-mechanical calculations. For larger systems, efficient …
MD simulations require costly quantum-mechanical calculations. For larger systems, efficient …
On the importance of crystal structures for organic thin film transistors
Historically, knowledge of the molecular packing within the crystal structures of organic
semiconductors has been instrumental in understanding their solid-state electronic …
semiconductors has been instrumental in understanding their solid-state electronic …
The seventh blind test of crystal structure prediction: structure generation methods
A seventh blind test of crystal structure prediction was organized by the Cambridge
Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon …
Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon …
Machine learning assisted prediction of organic salt structure properties
EP Shapera, DK Bučar, RP Prasankumar… - npj Computational …, 2024 - nature.com
We demonstrate a machine learning-based approach which predicts the properties of crystal
structures following relaxation based on the unrelaxed structure. Use of crystal graph …
structures following relaxation based on the unrelaxed structure. Use of crystal graph …
Impact of heteroatoms and chemical functionalisation on crystal structure and carrier mobility of organic semiconductors
S Hutsch, F Ortmann - npj Computational Materials, 2024 - nature.com
The substitution of heteroatoms and the functionalisation of molecules are established
strategies in chemical synthesis. They target the precise tuning of the electronic properties of …
strategies in chemical synthesis. They target the precise tuning of the electronic properties of …
Pharmaceutical digital design: from chemical structure through crystal polymorph to conceptual crystallization process
CL Burcham, MF Doherty, BG Peters… - Crystal Growth & …, 2024 - ACS Publications
A workflow for the digital design of crystallization processes starting from the chemical
structure of the active pharmaceutical ingredient (API) is a multistep, multidisciplinary …
structure of the active pharmaceutical ingredient (API) is a multistep, multidisciplinary …
[HTML][HTML] The seventh blind test of crystal structure prediction: structure ranking methods
A seventh blind test of crystal structure prediction has been organized by the Cambridge
Crystallographic Data Centre. The results are presented in two parts, with this second part …
Crystallographic Data Centre. The results are presented in two parts, with this second part …
Assessing the Accuracy and Efficiency of Free Energy Differences Obtained from Reweighted Flow-Based Probabilistic Generative Models
Computing free energy differences between metastable states characterized by
nonoverlapping Boltzmann distributions is often a computationally intensive endeavor …
nonoverlapping Boltzmann distributions is often a computationally intensive endeavor …
Understanding discrepancies of wavefunction theories for large molecules
Quantum mechanical many-electron calculations can predict properties of atoms, molecules
and even complex materials. The employed computational methods play a quintessential …
and even complex materials. The employed computational methods play a quintessential …