scholarly journals Constraints on the phase diagram of molybdenum from first-principles free-energy calculations

2012 ◽  
Vol 85 (6) ◽  
Author(s):  
C. Cazorla ◽  
D. Alfè ◽  
M. J. Gillan
Keyword(s):  
Phase Diagram ◽  
Free Energy ◽  
First Principles ◽  
Free Energy Calculations ◽  
Energy Calculations

scholarly journals Machine Learning the Metastable Phase Diagram of Materials

2021 ◽  
Author(s):  
Srilok Sriniva ◽  
Rohit Batra ◽  
Duan Luo ◽  
Troy Loeffler ◽  
Sukriti Manna ◽  
...  
Keyword(s):  
Machine Learning ◽  
Phase Diagram ◽  
Free Energy ◽  
Phase Diagrams ◽  
First Principles ◽  
Metastable Phase ◽  
Free Energy Calculations ◽  
Metastable Phases ◽  
Metastable Phase Diagram ◽  
Far From Equilibrium

Abstract A central feature of materials synthesis is the concept of phase diagrams. Phase diagrams are an invaluable tool for material synthesis and provide information on the phases of the material at any given thermodynamic condition (i.e., state variables such as pressure, temperature and composition). Conventional phase diagram generation involves experimentation to provide an initial estimate of the set of thermodynamically accessible phases and their boundaries, followed by use of phenomenological models to interpolate between the available experimental data points and extrapolate to experimentally inaccessible regions. Such an approach, combined with high throughput first-principles calculations and data-mining techniques, has led to exhaustive thermodynamic databases (e.g. compatible with the CALPHAD method), albeit focused on the reduced set of phases observed at distinct thermodynamic equilibria. In contrast, materials during their synthesis, operation, or processing, may not reach their thermodynamic equilibrium state but, instead, remain trapped in a local (metastable) free energy minimum, that may exhibit desirable properties. A phase diagram that maps these metastable phases and their thermodynamic behavior is highly desirable but currently lacking, due to the vast configurational landscape. Here, we introduce an automated workflow that integrates first-principles physics and atomistic simulations with machine learning (ML), and high-performance computing to allow rapid exploration of the metastable phases of a given elemental composition and construct "metastable" phase diagrams for materials far-from-equilibrium. Using carbon, a prototypical system with a vast number of metastable phases without parent in equilibrium, we demonstrate automated metastable phase diagram construction to map hundreds of metastable states ranging from near equilibrium to those far-from-equilibrium (400 meV/atom). Moreover, we incorporate the free energy calculations into a neural-network-based learning of the equations of state that allows for efficient construction of metastable phase diagrams. We use the metastable phase diagram and identify domains of relative stability and synthesizability of metastable materials. High temperature high pressure experiments using a diamond anvil cell on graphite sample coupled with high-resolution transmission electron microscopy (HRTEM) confirm our metastable phase predictions. The workflow presented here is general and broadly applicable to single and multi-component systems.

scholarly journals Free energy calculations for rings and chains formed by dipolar hard spheres

Soft Matter ◽  
2017 ◽  
Vol 13 (43) ◽  
pp. 7870-7878 ◽  
Author(s):  
Michela Ronti ◽  
Lorenzo Rovigatti ◽  
José M. Tavares ◽  
Alexey O. Ivanov ◽  
Sofia S. Kantorovich ◽  
...  
Keyword(s):  
Phase Diagram ◽  
Free Energy ◽  
Hard Spheres ◽  
Numerical Approach ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations

A numerical approach to calculate the free energies of DHS particles in chains and rings, exploring the unknown low-T region of the phase diagram of DHS.

Sign in / Sign up

Export Citation Format

Share Document