On phase separation and crystallization of Ge-rich GeSbTe alloys from atomistic simulations with a machine learning interatomic potential
Fuente:
arXiv
Saved in:
| Main Authors: | Kheir, Omar Abou El, Baratella, Dario, Bernasconi, Marco |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Unveiling the crystallization kinetics in Ge-rich Ge$_x$Te alloys by large scale simulations with a machine-learned interatomic potential
by: Baratella, Dario, et al.
Published: (2024)
by: Baratella, Dario, et al.
Published: (2024)
On the origin of in-gap states in amorphous Ge$_2$Sb$_2$Te$_5$
by: Kheir, Omar Abou El, et al.
Published: (2026)
by: Kheir, Omar Abou El, et al.
Published: (2026)
Viscosity, breakdown of Stokes-Einstein relation and dynamical heterogeneity in supercooled liquid Ge$_2$Sb$_2$Te$_5$ from simulations with a neural network potential
by: Marcorini, Simone, et al.
Published: (2025)
by: Marcorini, Simone, et al.
Published: (2025)
Unraveling the Crystallization Kinetics of the Ge$_2$Sb$_2$Te$_5$ Phase Change Compound with a Machine-Learned Interatomic Potential
by: Kheir, Omar Abou El, et al.
Published: (2023)
by: Kheir, Omar Abou El, et al.
Published: (2023)
Comparison of intermediate-range order in GeO$_2$ glass: molecular dynamics using machine-learning interatomic potential vs.\ reverse Monte Carlo fitting to experimental data
by: Matsutani, Kenta, et al.
Published: (2024)
by: Matsutani, Kenta, et al.
Published: (2024)
High-efficiency computational methodologies for electronic properties and structural characterization of Ge-Sb-Te based phase change materials
by: Xie, Shanzhong, et al.
Published: (2025)
by: Xie, Shanzhong, et al.
Published: (2025)
Constructing and evaluating machine-learned interatomic potentials for Li-based disordered rocksalts
by: Choyal, Vijay, et al.
Published: (2023)
by: Choyal, Vijay, et al.
Published: (2023)
Simulation of the crystallization kinetics of Ge$_2$Sb$_2$Te$_5$ nanoconfined in superlattice geometries for phase change memories
by: Acharya, Debdipto, et al.
Published: (2025)
by: Acharya, Debdipto, et al.
Published: (2025)
Expanding the search space of high entropy oxides and predicting synthesizability using machine learning interatomic potentials
by: Dicks, Oliver A., et al.
Published: (2025)
by: Dicks, Oliver A., et al.
Published: (2025)
Effects of colored disorder on the heat conductivity of SiGe alloys from first principles
by: Fiorentino, Alfredo, et al.
Published: (2024)
by: Fiorentino, Alfredo, et al.
Published: (2024)
Transferable potential for molecular dynamics simulations of borosilicate glasses and structural comparison of machine learning optimized parameters
by: Yang, Kai, et al.
Published: (2025)
by: Yang, Kai, et al.
Published: (2025)
Tunable Electronic Interactions and Weak Antilocalization in Bulk Ge$_2$Sb$_2$Te$_{5-5x}$Se$_{5x}$ Phase Change Materials
by: Mazzucca, Nicholas, et al.
Published: (2025)
by: Mazzucca, Nicholas, et al.
Published: (2025)
A cost-effective strategy of enhancing machine learning potentials by transfer learning from a multicomponent dataset on ænet-PyTorch
by: Aisnadaa, An Niza El, et al.
Published: (2024)
by: Aisnadaa, An Niza El, et al.
Published: (2024)
Force field optimization by end-to-end differentiable atomistic simulation
by: Gangan, Abhijeet S., et al.
Published: (2024)
by: Gangan, Abhijeet S., et al.
Published: (2024)
Revisiting the machine-learning density functional for the one-dimensional Hubbard model with random external potential
by: Salmon, Octavio D. R., et al.
Published: (2026)
by: Salmon, Octavio D. R., et al.
Published: (2026)
Thermodynamic potentials of metallic alloys in the undercooled liquid and solid glassy states
by: Makarov, A. S., et al.
Published: (2025)
by: Makarov, A. S., et al.
Published: (2025)
Equivariant graph neural network interatomic potential for Green-Kubo thermal conductivity in phase change materials
by: Lee, Sung-Ho, et al.
Published: (2023)
by: Lee, Sung-Ho, et al.
Published: (2023)
Thermal transport of glasses via machine learning driven simulations
by: Pegolo, Paolo, et al.
Published: (2024)
by: Pegolo, Paolo, et al.
Published: (2024)
Unsupervised machine learning for supercooled liquids
by: Qiu, Yunrui, et al.
Published: (2024)
by: Qiu, Yunrui, et al.
Published: (2024)
Modeling phase separation in polymer-derived silicon carbonitride ceramics through extended machine learning molecular dynamics
by: Mortier, Fabien, et al.
Published: (2026)
by: Mortier, Fabien, et al.
Published: (2026)
Spin glass behavior in amorphous CrSiTe3 alloy
by: Wang, Xiaozhe, et al.
Published: (2025)
by: Wang, Xiaozhe, et al.
Published: (2025)
Efficient training of machine learning potentials for metallic glasses: CuZrAl validation
by: Wadowski, Antoni, et al.
Published: (2024)
by: Wadowski, Antoni, et al.
Published: (2024)
Amorphization-induced topological and insulator-metal transitions in bidimensional Bi$_x$Sb$_{1-x}$ alloys
by: Uría-Álvarez, A. J., et al.
Published: (2024)
by: Uría-Álvarez, A. J., et al.
Published: (2024)
Liquid and solid layers in a thermal deep learning machine
by: Huang, Gang, et al.
Published: (2025)
by: Huang, Gang, et al.
Published: (2025)
Influence of anisotropy on the study of critical behavior of spin models by machine learning methods
by: Sukhoverkhova, Diana, et al.
Published: (2024)
by: Sukhoverkhova, Diana, et al.
Published: (2024)
AiiDA-TrainsPot: Towards automated training of neural-network interatomic potentials
by: Bidoggia, Davide, et al.
Published: (2025)
by: Bidoggia, Davide, et al.
Published: (2025)
Machine learning of phases and structures for model systems in physics
by: Bayo, Djenabou, et al.
Published: (2024)
by: Bayo, Djenabou, et al.
Published: (2024)
Magnetic doping-induced second-order and first-order topological phase transition inthe photonic alloy
by: Wu, Xianbin, et al.
Published: (2026)
by: Wu, Xianbin, et al.
Published: (2026)
Anomalous temperature dependence of the electrical resistivity in R$_3$Co$_4$Ge$_{13}$ (R = Y, Lu) single crystals
by: Dias, Juliana Gonçalves, et al.
Published: (2026)
by: Dias, Juliana Gonçalves, et al.
Published: (2026)
Structural Analysis of Amorphous GeO$_2$ under High Pressure Using Reverse Monte Carlo Simulations
by: Matsutani, Kenta, et al.
Published: (2024)
by: Matsutani, Kenta, et al.
Published: (2024)
Experimentally validated and empirically compared machine learning approach for predicting yield strength of additively manufactured multi-principal element alloys from Co-Cr-Fe-Mn-Ni system
by: Chandraker, Abhinav, et al.
Published: (2023)
by: Chandraker, Abhinav, et al.
Published: (2023)
Estimating predictability of depinning dynamics by machine learning
by: Haavisto, Valtteri, et al.
Published: (2023)
by: Haavisto, Valtteri, et al.
Published: (2023)
Million-atom simulation of the set process in phase change memories at the real device scale
by: Kheir, Omar Abou El, et al.
Published: (2025)
by: Kheir, Omar Abou El, et al.
Published: (2025)
Quantum and classical processing with photonic quantum machine learning
by: Carreño, J. C. López, et al.
Published: (2026)
by: Carreño, J. C. López, et al.
Published: (2026)
Single replica spin-glass phase detection using field variation and machine learning
by: Talebi, Ali, et al.
Published: (2024)
by: Talebi, Ali, et al.
Published: (2024)
Phase probabilities in first-order transitions using machine learning
by: Sukhoverkhova, Diana, et al.
Published: (2024)
by: Sukhoverkhova, Diana, et al.
Published: (2024)
Disordered charge density waves in the kagome metal FeGe
by: Tan, Hengxin, et al.
Published: (2024)
by: Tan, Hengxin, et al.
Published: (2024)
Absence of higher than 6-fold coordination in glassy $GeO_{2}$ up to 158 GPa revealed by X-ray absorption spectroscopy
by: Rodrigues, João Elias F. S., et al.
Published: (2025)
by: Rodrigues, João Elias F. S., et al.
Published: (2025)
First-principles study of the phase competition, mechanical and piezoelectric properties of pseudo-binary (SiC)(AlN) alloy
by: Wolf, Laszlo, et al.
Published: (2025)
by: Wolf, Laszlo, et al.
Published: (2025)
Energy landscapes of combinatorial optimization in Ising machines
by: Dobrynin, Dmitrii, et al.
Published: (2024)
by: Dobrynin, Dmitrii, et al.
Published: (2024)
Similar Items
-
Unveiling the crystallization kinetics in Ge-rich Ge$_x$Te alloys by large scale simulations with a machine-learned interatomic potential
by: Baratella, Dario, et al.
Published: (2024) -
On the origin of in-gap states in amorphous Ge$_2$Sb$_2$Te$_5$
by: Kheir, Omar Abou El, et al.
Published: (2026) -
Viscosity, breakdown of Stokes-Einstein relation and dynamical heterogeneity in supercooled liquid Ge$_2$Sb$_2$Te$_5$ from simulations with a neural network potential
by: Marcorini, Simone, et al.
Published: (2025) -
Unraveling the Crystallization Kinetics of the Ge$_2$Sb$_2$Te$_5$ Phase Change Compound with a Machine-Learned Interatomic Potential
by: Kheir, Omar Abou El, et al.
Published: (2023) -
Comparison of intermediate-range order in GeO$_2$ glass: molecular dynamics using machine-learning interatomic potential vs.\ reverse Monte Carlo fitting to experimental data
by: Matsutani, Kenta, et al.
Published: (2024)