E-MRS FALL MEETING 2017

Unit 3 "Effective translation strategy and

materials model creation

for Energy & Funktional Materials"

September 18. 2017

Thierry Deutsch – Director of Center for Predictive Simulation

Alternative Energies and Atomic Energy Commission (CEA)

Grenoble

EMMC-Workshop “Integration of materials modelling into business decision: Approaches, Models and Licenses”

| PAGE 2EMMC-Workshop – E-MRS Fall Meeting 2017

CREATION OF THE CENTER FOR PREDICTIVE SIMULATION

Between 3 Institutes

● Laboratory for Innovation in New Energy Technologies and

Nanomaterials (LITEN)

● Laboratory for Electronics and Information Technologies (LETI)

● Institute for Nanosciences and Cryogenics (INAC)

Demonstrators (solar energy, batteries),

Nano-Characterizations Platform

Strong industrial partnerships

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THE CENTER FOR PREDICTIVE SIMULATION

1. Integration of modelling with applied research (characterisation)

● Electronics, renewable energies (battery, photovoltaic)

● Developing vertical solutions in simulation and modelling

from first-principles to modelling of devices

2. Development of scientific softwares

BigDFT - Density Functional Theory, electronic model (EM)

Fiesta - optical spectroscopy based on many-body perturbation theory (EM)

TB_Sim - electronic transport for transistors, qubits (MM)

AlmaBTE - heat management for novel materials, multiscale model (MM)

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ALMABTE: ALL-SCALE PREDICTIVE DESIGN OF HEAT MANAGEMENT MATERIALS STRUCTURE

• Modular code fully

implemented in c++.

• Over 85000 lines of code.

• Full documentation and user

manual.

• Open source, Apache licence.

• Available online:

www.almabte.eu

• Protocols for interfacing with

Silvaco’s TCAD.

• Materials database.

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INDUSTRIAL PROBLEM: Calculating the properties of a given structure

J. Carrete, B. Vermeersch, A. Katre, A. van Roekeghem, T. Wang, G.K.H. Madsen, Natalio Mingo, Computer Physics Communications, “almaBTE: a solver of the space-time dependent Boltzmann transport equation for phonons in structured materials,” www.almabte.eu

HEAT MANAGEMENT SOLUTION : ALMABTE SOFTWARE

Homogeneous materials

With defects Nanostructures Multiscale structures

• Single crystals• Alloys

• Vacancies• Substitutionals• Interstitials• Dislocations

• Superlattices• Thin films

• 1D multilayers• 2D and 3D

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OUR CUSTOMERS ARE INDUSTRIES !

Simulation – ModellingLaboratory

Industries

Synthesis – CharacterizationLaboratory

Traditional scheme: Slow development and uptake

New scheme: Well defined questions

● One of our components is not enough for a given industrial problem!

● Use components in a workflow (models) to solve a given issue.

Need a system to elaborate and use workflows to have a given model

Efficiency of dopants, heat management, ...

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EXTMOS: MODELS FOR OLEDS

The role of EXTMOS project:

Developing workflows of simulation i.e.

realistic models to simulate OLEDS

Easy integration of our developed components

(Fiesta, BigDFT)

thanks to SimStack workflow platform (Nanomatch)

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EXTMOS: MODELS FOR OLEDS

Up to the device (Silvaco)

Parametrizer

DEPOSIT

QuantumPatch

LightForge KMC

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EXTMOS WORKFLOW

Build a full workflow: Need validation from experiences

but also from first-principle simulations!

Nature of transport: is the dopant fully ionized or not (hybridization)?

Many-body perturbation theory: heavy calculations but should be predictive!

Then validate a “cheap” model of transport in good agreement with experiences

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VALIDATION OF A MODEL

Work of Neel Institute CNRS, Grenoble, Mons University, CEA

1) Calculate the properties of dopant in environment

2) Compare with model and experiences

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WHAT IS MISSING? DATA MANAGEMENT!

(Structured) Data need some computational methods

● Data management from characterization.

● Electron microscopy: 1TBytes per experiment

● Need heavy processing of large pictures

● Storage and workflows are required (+ HPC!)

● Added value for characterisation (and modelling)

● Important for industries!

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ONE WAY: CLOUD TECHNOLOGY (NOTEBOOKS)

With the courtesy of J. Kieffer (ESRF, European Synchrotron, Grenoble)

Collecting Data

Processing

Reduce information

Apply model/simulation

Compare to other data and validate

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TOWARDS EFFICIENT TRANSLATION

● Develop scientific modules or components

● Catalogue of workflows/models

● Build strong links with the management of (experimental) data

● What about «Interoperability»?

→Tutorial based on Nanomatch solutions (Tobias Neumann)

Center of Predictive SimulationAlternative Energies and Atomic Energy CommissionGrenoble

Etablissement public à caractère industriel et commercial | RCS Paris B 775 685 019

Thank you for your attention

French Alternative Energies and Atomic Energy Commission

FROM RESEARCH TO INDUSTRY

Thank you for your attention