Origin of the low conversion efficiency in Cu2ZnSnS4 kesterite solar cells: the actual role of cation disorder

The controversial role of cation disorder in the extraordinarily low open-circuit voltage (VOC) of Cu2ZnSnS4 (CZTS) kesterite absorber is examined through a statistical treatment of disorder within the cluster-expansion method....

Single-Ion Solvation Free Energy: A New Cluster-Continuum Approach Based on the Cluster Expansion Method

Accurate calculation of the solvation free energy of single ions remains an important goal, involving the development in the dielectric continuum solvation models, statistical mechanics with explicit solvent and hybrid...

First-Principles Atomistic Thermodynamics and Configurational Entropy

In most applications, functional materials operate at finite temperatures and are in contact with a reservoir of atoms or molecules (gas, liquid, or solid). In order to understand the properties of materials at realistic conditions, statistical effects associated with configurational sampling and particle exchange at finite temperatures must consequently be taken into account. In this contribution, we discuss the main concepts behind equilibrium statistical mechanics. We demonstrate how these concepts can be used to predict the behavior of materials at realistic temperatures and pressures within the framework of atomistic thermodynamics. We also introduce and discuss methods for calculating phase diagrams of bulk materials and surfaces as well as point defect concentrations. In particular, we describe approaches for calculating the configurational density of states, which requires the evaluation of the energies of a large number of configurations. The cluster expansion method is therefore also discussed as a numerically efficient approach for evaluating these energies.

Anion order in perovskite oxynitrides AMO2N (A = Ba, Sr, Ca; M = Ta, Nb): a first-principles based investigation

Anion order in perovskite oxynitrides is investigated by a combination of first-principles calculations, cluster expansion method and Monte Carlo simulations.