Opendata, web and dolomites

TEC1p SIGNED

Big-Data Analytics for the Thermal and Electrical Conductivity of Materials from First Principles

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

Project "TEC1p" data sheet

The following table provides information about the project.

Coordinator
MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV 

Organization address
address: HOFGARTENSTRASSE 8
city: Munich
postcode: 80539
website: www.mpg.de

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Total cost 2˙048˙183 €
 EC max contribution 2˙048˙183 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-ADG
 Funding Scheme ERC-ADG
 Starting year 2017
 Duration (year-month-day) from 2017-10-01   to  2022-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV DE (Munich) coordinator 2˙048˙183.00

Map

 Project objective

'Thermal conductivity (TC) is a key characteristic of many materials, particularly those used in the energy and environment sectors (thermoelectrics, thermal-barrier coatings, catalysis, etc.). However, TC is largely unknown − of the 225,000 identified inorganic semiconductor and insulator crystals, only 100 have any TC data available.

By combining a novel ab initio molecular dynamics TC theory and big-data analytics (machine learning, compressed sensing, subgroup discovery), we will generate quantitative values and understanding of TC (and electrical conductivity (EC)) for most of these 225,000 materials, as well as for materials not yet discovered.

TEC1p will develop and deploy five key approaches. Individually these are already novel for materials science, but their combination in TEC1p enables a true breakthrough. These five components are: 1) Ab initio theory of TC 3 (advanced density-functional theory, seamlessly linked to size- and time-converged statistical mechanics). 2) Ab initio theory of EC (advanced …; see #1). 3) Compressed sensing to identify a set of physical parameters that describe the TC and EC behaviour and to derive predictive equations that work for all materials.5 4) Active learning to build a systematic big-data database of materials, their TCs and ECs. 5) Subgroup discovery to recognise trends and anomalies in the big data, enhance the active learning, and elucidate the underlying physical mechanisms.

In analogy to Mendeleev’s table of the elements, we will build maps that arrange existing and predicted materials according to their TC and EC properties. The methods that we will develop and the extensive calculations that we will execute are both innovative and timely. They will greatly progress scientific knowledge of the physical properties of materials. The impact of the concepts, methodology, and results will be far reaching for materials science, novel materials discovery, engineering,'

 Publications

year authors and title journal last update
List of publications.
2019 Mie Andersen, Sergey V. Levchenko, Matthias Scheffler, Karsten Reuter
Beyond Scaling Relations for the Description of Catalytic Materials
published pages: 2752-2759, ISSN: 2155-5435, DOI: 10.1021/acscatal.8b04478
ACS Catalysis 9/4 2019-06-07

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "TEC1P" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "TEC1P" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.1.)

CRISPR2.0 (2019)

Microbial genome defence pathways: from molecular mechanisms to next-generation molecular tools

Read More  

UpTEMPO (2019)

Ultrafast tunneling microscopy by optical field control of quantum currents

Read More  

MAGIC (2020)

Architectured Soft Magnetoactive Materials: Beyond Instabilities

Read More