2 citations · 3 across the 6 of their papers we have counts for
8 papers
Mechanism of charge transfer and electrostatic field fluctuations in complex metallic alloys
Wai-Ga D. Ho, Wasim Raja Mondal, Swarnava Ghosh +6
Complex metallic alloys exhibit rich disorder-driven electronic, magnetic, and vibrational behavior arising from strong chemical disorder, leading to unconventional structure-prope…
Quantum solver for single-impurity Anderson models with particle-hole symmetry
Mariia Karabin, Tanvir Sohail, Dmytro Bykov +8
Quantum embedding methods, such as dynamical mean-field theory (DMFT), provide a powerful framework for investigating strongly correlated materials. A central computational bottlen…
Enhancing Dimensionality Prediction in Hybrid Metal Halides via Feature Engineering and Class-Imbalance Mitigation
Mariia Karabin, Isaac Armstrong, Leo Beck +5
We present a machine learning framework for predicting the structural dimensionality of hybrid metal halides (HMHs), including organic-inorganic perovskites, using a combination of…
Mechanism of charge transfer and electrostatic field fluctuations in high entropy metallic alloys
Wai-Ga D. Ho, Wasim Raja Mondal, Hanna Terletska +5
High entropy alloys present a new class of disordered metals which hold promising prospects for the next generation of materials and technology. However, much of the basic physics…
Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials
Markus Eisenbach, Mariia Karabin, Massimiliano Lupo Pasini +1
The investigation of finite temperature properties using Monte-Carlo (MC) methods requires a large number of evaluations of the system's Hamiltonian to sample the phase space neede…
Ab initio Approaches to High Entropy Alloys: A Comparison of CPA, SQS, and Supercell Methods
Mariia Karabin, Wasim Mondal, Andreas Ostlin +7
We present a comparative study of different modeling approaches to the electronic properties of the $\textrm{Hf}_{0.05}\textrm{Nb}_{0.05}\textrm{Ta}_{0.8}\textrm{Ti}_{0.05}\textrm{…
An Entropy-Maximization Approach to Automated Training Set Generation for Interatomic Potentials
Mariia Karabin, Danny Perez
Machine learning (ML)-based interatomic potentials are currently garnering a lot of attention as they strive to achieve the accuracy of electronic structure methods at the computat…
Simulated Annealing with Adaptive Cooling Rates
Mariia Karabin, Steven J. Stuart
As one of the most robust global optimization methods, simulated annealing has received considerable attention, with many variations that attempt to improve the cooling schedule. T…