Materials for Energy

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Scientific Challenge leader: Francesco Buonocore

Advanced materials can contribute to the reduction in cost, increase in performance and extension of lifetime of the low-carbon energy technologies such as batteries, supercapacitors and solar cells. Thus, there is an urgent need for multi-functional and sustainable materials designed to provide a specific function in the final product. HPC can speed-up the entire process needed to identify new materials and to optimize them for the final use (Materials Roadmap). In particular, the design of advanced materials needs to consider atomic-scale chemistry and how it affects the physical properties at larger scales till the device. The Energy Materials objective in EoCoE-II will focus on three specific flagship applications in energy storage and production respectively: libNEGF (high efficiency silicon solar cells), Metalwalls (supercapacitor modelling) and KMC/DMC (organic/perovskite photovoltaics).

In order to pursue this objective, the Materials for Energy Scientific challenge is divided in three main tasks:

Shedding light on carrier dynamics at hetero-interfaces in silicon solar cells (libNEGF).

Team: Irene Aguilera, Francesco Buonocore, Massimo Celino, Edoardo Di Napoli, Pablo Luis Garcia-Muller,  Rafael Mayo-Garcia, Simone Giusepponi, Alessandro Pecchia.

This task highlights the scientific objectives and roadmap for optimizing silicon solar cells to increase in performance and extension of lifetime. Amorphous-crystalline heterointerfaces play a crucial role in the photovoltaic operation of silicon heterojunction (SHJ) technology, but the microscopic mechanisms of transport and recombination mechanisms at the interface are still poorly understood. The purpose of the present task is to understand the transport mechanisms underlying photovoltaic devices based on SHJ technology by simulating at atomistic resolution amorphouscrystalline heterointerfaces. Medium and large c-Si/a-Si:H interface models will be build up from classic molecular dynamics (MD) simulations and first-principles calculations. Ab initio electronic properties of the c-Si/a-Si:H interfaces will be calculated. Starting from the first-principles calculations, tight-binding Hamiltonians will be represented in a basis of localized Wannier functions. Next, non-equilibrium Green’s functions (NEGF) formalism will be used to analyse the effect of interfaces on the carrier transport and dynamics in silicon solar cells. Electron-photon and electronphonon scattering processes will be taken into account.

Harvesting electricity from salinity or temperature gradient (Metalwalls).

Team: Stefano Mossa, Carlo Pierleoni, Michele Ruggeri, Mathieu Salanne.

This task focuses on optimizing capacitive blue energy electrodes and thermo-electrochemical devices. Electric power production from salinity gradients harvests the free energy lost during the mixing of river with sea water in estuaries. The main technologies developed for this purpose to date exploit the electric potential differences applied across membranes, but another approach based on capacitive mixing was recently proposed. The first objective of this project will be to ascertain the best electrode structure which optimizes such a blue energy production. Thermo-electrochemical devices employ the variation of the redox potential of an active species with temperature to convert a gradient into electricity. Ionic liquids were recently proposed as optimal media for performing such an energy harvesting, and the second objective of this task will be to find compositions that will enable optimal performances. In both cases, a fundamental understanding of the cation and anion adsorption at the surface of the electrodes is essential. The challenge for this task is that simulating the interfaces requires the rigorous accounting for the interactions between the atoms of the electrodes and the adsorbed species. Due to the large size of the simulated systems for the final application, it is not possible to use electronic density functional theory (DFT) for such calculations. We therefore aim at developing new force fields for classical molecular simulations. The parameterization of these force fields can be made based on a series of electronic DFT calculations. However, it was shown recently that the commonly used exchange-correlation functionals may yield very different results for the adsorption energy of the molecules. We will overcome this problem by performing a series of Quantum Monte Carlo (QMC) reference calculations in order to benchmark them on the adsorption energies. Once the DFT functional is benchmarked on the QMC reference, a large amount of calculations will be performed to fine-tune force fields for classical molecular simulations with Metalwalls/MDFT codes. These two codes aim at simulating electrochemical systems with explicit electrodes, using either molecular dynamics or classical density functional theory to sample the configurational space of the solvent.

Organic and Perovskite solar cells (Bath-KMC/DMC).

Team: William Saunders, Alison Walker, Matthew Wolf.

This task deals with the development of a flexible and modular scheme for the multiscale modelling of electronic and ionic transport in materials for next generation photovoltaic devices. This will be built on (augmented versions of) pre-existing, MPI parallelised Python frameworks, namely Firedrake and PPMD. The scientific goals of this project, as stated in the EoCoE proposal, are:

– simulate organic photovoltaic cells of 10 nm size and study interfaces on the nm length scale to refine models of charge generation and recombination (Kinetic Monte Carlo, KMC code).

– Understand the complex processes of charge transport in a perovskite solar cell thanks to the implementation of a semiclassical approach based on solving the Boltzmann transport equation in submicron inorganic semiconductors (Device Monte Carlo, DMC code). Both KMC and DMC codes are exascale flagship codes are part of tasks in Scalable Solvers Technical Challenge of EoCoE-II.

Metalwalls is a classical molecular dynamics code aiming at simulating electrochemical cells. It treats electrode as metallic systems held at constant potential and includes polarization effects for the liquids.

libNEGF is a general library that calculates Equilibrium and Non Equilibrium Green’s Function and related quantities in open systems, within an efficient sparse iterative scheme. The code will be optimized to describe photon-carrier dynamics (generation, transport and recombination) in nanostructured regions and at complex interfaces, and used to execute advanced simulation of high-efficiency solar cell devices for different input biases.

KMC/DMC (http://people.bath.ac.uk/pysabw/). Kinetic Monte Carlo (KMC) simulates charge and energy transport in organic solar cells. Device Monte Carlo (DMC) simulates charge transport in perovskite cells. The DMC code includes the effects of mobile ion motion that affects most perovskites.

Organic and perovskite solar cells

Fast electrostatic solvers for kinetic Monte Carlo simulations

W. R. Saunders, J. Grant, E. H. Muller and I. Thompson

University of Bath

J. Comp. Phys. 410, 109379 (2020) DOI: 10.1016/j.jcp.2020.109379

Kinetic Monte Carlo (KMC) simulations of a system of (electrically) charged particles require many evaluations of the change in electrostatic energy associated with “possible” moves of individual particles, but only one such move is selected per KMC step (Fig. 1).

Schematic sketch of one KMC step
Fig. 1: Schematic sketch of one KMC step, which consists of calculation of the propensities for all possible hops (dashed arrows) and moving one particle to a new site after accepting a particular hop (solid arrows). Subsequent steps are shown as grey arrows.

We mitigate the potential explosion in the computational complexity of the problem with system size by deriving a modified version of the well-known Fast Multipole Method which exploits the fact that the change in the charge distribution is small for each possible move, leading to an algorithm which scales linearly in the number of particles per KMC step. We present an implementation of the algorithm in a performance portable high-level Python user interface which generates low-level code optimised to the system architecture, and demonstrate its parallel scalability for 1 million charges and 8192 cores (Fig. 2).

Strong (left) and weak (right) scaling experiments
Fig. 2: Strong (left) and weak (right) scaling experiments. The time per KMC step is plotted against number of compute nodes. For the strong scaling experiment the total number of charges is N = 1,000,000.

Shedding light on carrier dynamics at hetero-interfaces in silicon solar cells

Towards exascale simulations of a-Si:H/c-Si interfaces

Sebastian Achilles 1, Irene Aguilera 1, Francesco Buonocore 2, Massimo Celino 2, Pablo Luis Garcia 3, Simone Giusepponi 2, Rafael Mayo-Garcia 3, Edoardo di Napoli 1, Alessandro Pecchia 4

1) Forschungszentrum Juelich; 2) ENEA; 3) CIEMAT – Avda. Complutense, 40 – 28040 Madrid – Spain; 4) CNR-ISMN

In the silicon heterojunction solar cells, intrinsic hydrogenated amorphous silicon a-Si:H is used to passivate the crystal silicon c-Si surface to suppress the electrical losses at interfaces and to keep  ultralow contact resistivity for the selective transport of one type of carrier only. We use ReaxFF (Reactive Force Field) molecular dynamics to efficiently simulate the thermalisation, quenching, and equilibration processes involving thousands of atoms forming realistic a-Si:H/c-Si interface structures. We generated snapshots of the equilibrated c-Si/a-Si:H interface atom configurations. The ab initio characterization has been executed on selected configurations to monitor the electronic properties of the c-Si/a-Si:H interface. The evolution of the intragap states is monitored at different temperatures to study the formation of defects and the effects on the electronic properties. The analysis performed will be used to select the atomic configurations for the investigation of the interface effects on the carrier transport and dynamics in the non-equilibrium Green’s functions formalism. This all will allow to design more efficient silicon solar cells belonging to the silicon heterojunction technology.

In the figure: a) Local density of states (green isosurface) of the intragap states of a-Si:H/c-Si interface at room temperature. They correspond to defect states localized both in the bulk of a-Si and at the a-Si:H/c-Si interface. The Silicon atoms and their bonds are in orange in the c-Si side and are in yellow in the a-Si:H side, Hydrogen atoms and bonds with Silicon atoms are in blue. Bonds between c-Si and a-Si are in red. a-Si = amorphous Silicon; c-Si = crystal Silicon. b) The c-Si/a-Si:H interface and the difference at of the charge density between the total system and the c-Si and a-Si:H systems considered as isolated slabs at the end of the room temperature thermalisation. Red (blue) isosurface is positive (negative) difference of the charge density. The electron charge is accumulated along the c-Si/aSi:H interface and depleted from the nearby c-Si and a-Si:H surfaces.
 
 
  1. William Robert Saunders, James Grant, Eike Hermann Müller, Ian Thompson, Fast electrostatic solvers for kinetic Monte Carlo simulations, Journal of Computational Physics, Volume 410, 2020, 109379, ISSN 0021-9991, https://doi.org/10.1016/j.jcp.2020.109379.