Prof. Dr. Claudia Draxl Prof. Christoph T. Koch, PhD Prof. Dr. Martin Aeschlimann Dr. Martin Albrecht Prof. Dr. Silvana Botti Prof. Dr. Hans-Joachim Bungartz Prof. Dr. Heiko Weber Prof. Dr. Christof Wöll
Prof. Dr. Claudia Draxl
C=
We are looking for a project assistant to help the FAIRmat team with:
This is an E8 TV-L position, initially limited until September 2026 but with an extension being sought, with the possibility to work part-time. The full job description and instructions on how to apply are also available on our jobs page (EN) or the Humboldt University site (DE).
We are looking for a Data Steward for FAIRmat Task E2: Heterogeneous Catalysis. This role involves:
Developing web-based applications for data acquisition, storage and visualization of data in Heterogeneous Catalysis
Working at the interface between catalysis research and information technology
Mediating communication between the project partners in Task E2 and establish connections with other use cases, such as battery materials, metal organic frameworks, and optoelectronics, as wekk as with other NFDI initiatives.
Interested? You can view the full advert and apply now on our careers page.
Videos of talks from this year's FAIR-DI Conference on a FAIR Data Infrastructure for Materials Genomics are available on the conference's KouShare page under "videos". You can also find the links for specific talks on our conference program page.
The second International FAIR-DI Conference on a FAIR Data Infrastructure for Materials Genomics will take online place from July 12-15, 2022. The full program of 78 talks by experts in Data management, Experimental and computational databases, Exascale computing, High-throughput experiments and computations and Machine learning, is now available to view or download here.
Registration for the conference is free and open until June 30, 2022.
Recordings of the FAIRmat tutorial on NOMAD Oasis and FAIR data collaboration and sharing are now available on YouTube !
The YouTube playlist includes the following sessions:
All information about the tutorial including slides & the link to the YouTube playlist can be found on the tutorial event page.
The video of the talk The Next Decade of the US Materials Genome Initiative given by James A Warren at the NFDI Physical Sciences Joint Colloquium on May 5, 2022 is now available on YouTube.
Abstract: The US Materials Genome Initiative has just begun its second decade. With a goal of accelerating the discovery, design, development, and deployment of new materials into manufactured products, the MGI is focused on the creation of a materials innovation infrastructure.
My institution, the National Institute of Standards and Technology (NIST), has framed its support for the MGI around the need for a data infrastructure that enables the rapid discovery of existing data and models, the tools to assess and improve the quality of those data, and finally the development of new methods and metrologies based on that data. In partnership with agencies across the government, academia, industry, and synergistic efforts around the globe, these approaches are now yielding significant advances.
Of particular note is the potential for machine learning and artificial intelligence applications upon these troves of data, which is now being borne out, and the vast consequent opportunities for new discoveries. Additionally, and in light of the many changes in how materials R&D is done, the MGI is has just released a new strategic plan, charting a plan for the next 10 years of an evolving materials innovation infrastructure, which I will review in this lecture.
The link can also be found in our video library or along with other information about the colloquium on the event page.
The first talk of the NFDI Physical Sciences Joint Colloquium will be given by James A. Warren, Director of the NIST Materials Genome Program, on May 5, 2022.
This will be a hybrid event, taking place in Berlin-Adlershof and on Zoom.
More information and registration can be found here.
The video from Hans-Joachim Bungartz' talk An Infrastructure for the Infrastructure at the FAIR-DI - FAIRmat Colloquium on April 7, 2022 is now available on our website and on YouTube.
Videos from the tutorial on the NOMAD Artificial-Intelligence (AI) Toolkit, which took place on April 6-7, 2022, are now available on YouTube and Koushare.
More information about the event and links to all videos can also be found on the Tutorial 3 page.
At our next FAIR-DI - FAIRmat Colloquium on April 7, Hans-Joachim Bungartz will talk about Providing Infrastructure for the Infrastructure.
On April 6 & 7, our FAIRmat hands-on tutorial series continues with a tutorial on the NOMAD Artificial-Intelligence (AI) Toolkit, the platform for running (jupyter) notebooks to analyse with AI tools the data contained in the NOMAD Archive.
We will cover, in an interactive, hands-on fashion, the several aspects of the AI-toolkit: the query over the NOMAD Archive via the NOMAD API, the basic notebooks for learning AI methods, and the advanced notebooks, where the workflow of relevant publications, in which AI is applied to materials science, can be interactively reproduced and further explored. Furthermore, we will introduce the local AI-toolkit app that allows to run a local version of the notebooks, e.g., to combine own data with the NOMAD Archive data.
At the end of the first day, few tutorial notebooks will be suggested to be perused by the participants before the second day starts. In the second day, break-out rooms will be organized, and in each room one of the selected tutorial notebooks will be discussed.
More and more demand is generated by large funding agencies around the world that researchers publish their data in open-access repositories in a reusable, FAIR way. This is also supported by EU and German federal research agencies as shown by the developments of the European Open Science Cloud (EOSC), and German National Research Data Infrastructure (NFDI) projects.
Such a movement requires that the data is annotated with well defined metadata, where the naming convention also follows standards. In order to achieve this, researchers have to be able to access the measured raw data together with any results derived by subsequent data processing.
The workshop reviews the opportunities provided by the scientific community standard NeXus.
We are happy to invite you for the NFDI NeXus Workshop to discuss the use of the NeXus glossary/ontology, corresponding data format and FAIR Data management in general.
On March 9 and 10, our FAIRmat hands- on tutorial series continues with a tutorial on ELNs and FAIR data management.
This tutorial is reviewing the need of using electronic lab notebooks (ELNs) in materials science research labs, synthesis, and experimental characterisation facilities. A special emphasis is put on efficiently collecting all metadata and performing FAIR data management which not only facilitates organising the work better and making the processes in the lab more performant but also guarantees the possibility of data reuse via offering machine readability and machine interpretability.
The tutorial is also addressing the questions: Which kind of choices are available and how to set up such ELN system for a laboratory? A demonstration of such a lab setup will also be provided on the first day.
On the second day, three more presentations will guide you through the details of implementing such a setup for your own lab. For this purpose, we have chosen relevant, but simple use cases which can help you in mapping our strategies and solutions onto your institute.
Program
Mar 9, 2022:
Overview Talk
15:00 CET - John Henry Scott (NIST): Data-Centric Materials Science - The Critical Role of ELNs
16:00 CET - Mark Greiner: ELNs in FAIR data management
Hands-on Tutorial
17:00 CET - Christoph T. Koch: Demonstration of the eLabFTW and NOMAD in daily use
18:00 CET - End of the 1st day
Mar 10, 2022:
10:00 & 16:00 CET - José Márquez: Setting up eLabFTW for a simple lab
10:30 & 16:30 CET - Sherjeel Shabih: Integrating eLabFTW and NOMAD
11:15 & 17:15 CET - Markus Scheidgen: NOMAD ELN - ELN features integrated into NOMAD
12:00 & 18:00 CET- End of the 2nd day
Tutorial Chair: Sandor Brockhauser
You can find all videos and exercises of the first FAIRmat tutorial on Publishing and Exploring Data with NOMAD on our website and on our YouTube channel!
Website with exercises: https://www.fair-di.eu/fairmat-tutorials-1
YouTube playlist with videos of the overview talk by Matthias Scheffler and the hands-on tutorials by Markus Scheidgen:
On February 9, the brand new FAIRmat hands-on tutorial series begins!
Feb 9, 15:00 CET
Matthias Scheffler: Making the Data Revolution Happen – How Sharing and FAIRification Is Changing the Science Already Today
15:45-18:00 CET
Markus Scheidgen: Publishing and Exploring Data with NOMAD: How-to and Exercises
Feb 10, 10:00-12:00 and 16:00-18:00 CET
Markus Scheidgen: Questions and Answers
The tutorial series continues every second Wednesday of the month and the following Thursday.
More info here: https://www.fair-di.eu/fairmat-tutorials-home
Our FAIRmat - NFDI4Cat collaboration was accepted for publication in ACSCatalysis. You can download the preprint of "Learning design rules for selective oxidation catalysts from high-throughput experimentation and artificial intelligence" here.
L. Foppa, C. Sutton, L. M. Ghiringhelli, S. De, P. Löser, S.A. Schunk, A. Schäfer, and M. Scheffler,
Learning design rules for selective oxidation catalysts from high-throughput experimentation and artificial intelligence
Preprint Download: chemrxiv
Hands-on FAIRmat Tutorials
Every second Wednesday of the month and the following Thursday
https://www.fair-di.eu/fairmat-tutorials-home
FAIRmat introduces its efforts towards a FAIR data infrastructure for condensed-matter physics and the chemical physics of solids in its new hands-on tutorial series. We will show how FAIRmat can help research work already today and how you will get prepared for the new scientific opportunities of tomorrow.
The tutorials consist of overview talks by internationally renowned scientists and hands-on tutorials by our FAIRmat developers.
We are looking forward to seeing you there!
FAIRmat is looking for a Public Relations / Communication Expert and Assistant! Find all information here: https://nomad-lab.eu/career
Congratulations to our FAIRmat Area A Leader Claudia Felser, Director at the Max Planck Institute for Chemical Physics of Solids in Dresden. She is awarded the Max Born Prize 2022 for her seminal contributions to the fields of magnetic an chiral topology, in prediction, single crystal growth, and experimental observations.
The Max Born Prize is awarded jointly by the British Institute of Physics (IOP) and the German Physical Society (DPG) in memory of Max Born's work in Great Britain and Germany for particularly valuable and current scientific contributions to physics. It is awarded annually, alternately to a physicist living and working in Germany and Great Britain.
Read the article here: https://www.dpg-physik.de/auszeichnungen/dpg-preise-mit-anderen-organisationen/max-born-preis-und-medaille/preistraeger?set_language=en
After a great start of our colloquium series (watch the talk by Barend Mons here: https://youtu.be/N4CBAqKQmQs), our next colloquium will take place on December 2 at 10:15 CET.
Christoph T. Koch will talk about Ingredients for Effective Computer-augmented Experimental Materials Science.
We are very much looking forward to her talk since it will set the stage for fruitful discussions in many sessions. So come ready to ask questions!
https://www.fair-di.eu/fairdi-colloqium-home
Elsa Olivetti's talk about Text and Data Mining for Materials Development will be postponed to spring 2022. Originally, the talk was to take place on November 4, 2021, as part of the second FAIR-DI - FAIRmat colloquium.
The next colloquium with Christoph Koch from Humboldt-Universität zu Berlin will be held as a hybrid event on December 02 at 10:15 CET.
We are very much looking forward to his talk since it will set the stage for fruitful discussions in many sessions. So come ready to ask questions! In case you missed it, you can watch the talk by Barend Mons on How to materialise FAIR here: https://www.fair-di.eu/fairdi-colloqium-videos
After a great start of our colloquium series (watch the talk by Barend Mons here: https://youtu.be/N4CBAqKQmQs), our next colloquium will take place on November 4 at 10:15 CET.
Elsa Olivetti from the Massachusetts Institute of Technology will talk about Text and Data Mining for Materials Development.
We are very much looking forward to her talk since it will set the stage for fruitful discussions in many sessions. So come ready to ask questions!
https://www.fair-di.eu/fairdi-colloqium-home
We are excited to have leading FAIR data specialist Barend Mons as our first speaker at the FAIR-DI - FAIRmat Colloquium on October 7!
Barend Mons is the Scientific Director of the GO FAIR Foundation, President of CODATA, and key person behind the renowned paper The FAIR Guiding Principles for Scientific Data Management and Stewardship. He will talk about "How to materialise FAIR".
Registration required: https://www.fair-di.eu/fairdi-colloqium-home
FAIRmat is seeking several highly qualified and motivated colleagues to join the consortium and the dynamic NOMAD team towards shaping the future of materials science! We are looking for
Scientific Software Developers,
IT-affine Materials Scientists,
Administrative and Scientific Team Leaders,
a Scientific Project Manager,
and a Project Assistant
Apply here: https://nomad-lab.eu/career/nomad-hub
Let's build a FAIR infrastructure together!
We made it! Today, the Joint Science Conference (GWK) announced its final funding decision about the National Research Data Infrastructure Program: FAIRmat is being funded as an NFDI consortium! A total of 10 consortia were chosen this year. You can read the official press release here: https://www.gwk-bonn.de/presseaktuelles/pressemitteilungen.
This success would not have been possible without your motivation and commitment, and we would like to thank all of you very much for that! It is great to know that a large community is behind the FAIRmat idea.
We are now looking forward to getting down to work with full vigour. As a first important step, we are now in the process of expanding the FAIRmat team with experts from different fields. Please, forward these job advertisements to potential candidates and colleagues: https://nomad-lab.eu/career/nomad-hub.
Let's build up a FAIR data infrastructure together!
FAIRmat is delighted to welcome Dr. Walid Hetaba as the leader of Task B3: Core-level Spectroscopy.
Dr. Hetaba is the leader of the Electron Microscopy group in the department Heterogeneous Reactions at the Max Planck Institute for Chemical Energy Conversion (MPI CEC).
We are delighted to welcome Prof. Dr. Heiko Weber as the new leader of FAIRmat Area B: Experiment!
Prof. Dr. Weber is head of the Chair of Applied Physics at the Friedrich-Alexander-University and leader of FAIRmat Task D5: Configurable Experiment Control Systems.
On Friday Septmber 9 at 11:00 CEST, Christopher M Wolverton of Northwestern University will give the talk The Phase Diagram of All Inorganic Materials at the NFDI Physical Sciences Joint Colloquium in Berlin and online.
For full information and the registration link see the event page.
Abstract
One of the holy grails of materials science, unlocking structure-property relationships, has largely been pursued via bottom-up investigations of how the arrangement of atoms and interatomic bonding in a material determine its macroscopic behavior. Here we consider a complementary approach, a top-down study of the organizational structure of networks of materials, based on the interaction between materials themselves. We demonstrate the utility of applying network theory to materials science in two applications: First, we unravel the complete “phase stability network of all inorganic materials” as a densely-connected complex network of 21,000 thermodynamically stable compounds (nodes) interlinked by 41 million tie-lines (edges) defining their two-phase equilibria, as computed by high-throughput density functional theory. Using the connectivity of nodes in this phase stability network, we derive a rational, data-driven metric for material reactivity, the “nobility index”, and quantitatively identify the noblest materials in nature. Second, we apply network theory to the problem of synthesizability of inorganic materials, a grand challenge for accelerating their discovery using computations. We use machine-learning of our network to predict the likelihood that hypothetical, computer generated materials will be amenable to successful experimental synthesis.
The FAIRmat hands-on tutorial series will resume on October 5-6, 2022 with Tutorial 5: NOMAD Encyclopedia.
The tutorial will take place on Zoom. For a full description and registration see the tutorial page.
A tailored AI Approach for Heterogeneous Catalysis
NOMAD CoE researchers Lucas Foppa, Luca M. Ghiringhelli, Matthias Scheffler and other colleagues have developed a customized artificial intelligence approach for modeling of heterogeneous catalysis. This method takes into account the key physicochemical parameters that are correlated with catalytic performance to accelerate the discovery of improved or novel materials. The study was published in the prestigious high-ranking journal MRS Bulletin in November 2021.
Artificial-intelligence-driven discovery of catalyst “genes” with application to CO2 activation on semiconductor oxides
A. Mazheika, Y. Wang, R. Valero, F. Vines, F. Illas, L. Ghiringhelli, S. Levchenko, and M. Scheffler of the NOMAD Laboratory of the Fritz Haber Institute developed and advanced artificial intelligence methods that enable the identification of basic materials parameters that correlate with materials properties and functions of interest (here the activation of CO2).
Matthias Scheffler (NOMAD CoE coordinator) gave a plenary talk titled "Artificial Intelligence for Surface Science and Heterogeneous Catalysis: Learning Rules and Creating Maps of Materials Properties" at the ISSS9 virtual conference (Nov. 28 - Dec. 01, 2021). The meeting was organized by the Japan Society of Vacuum and Surface Science (JVSS) and highlights recent achievements in surface science and its related fields. ISSS9 was originally planned as a face-to-face conference but had to be changed to an online format due to the pandemic.
The Danish VILLUM Foundation has appointed NOMAD PI Kristian Sommer Thygesen as Villum Investigator with a grant of 30 Mio DDK (4 Mio Euro) for the project “Data-Driven Discovery of Functionalized 2D Materials”.
The web service of the NOMAD Artificial-Intelligence (AI) Toolkit has been upgraded in its functionality and its look-and-feel.
In a newly accepted Nature Perspective article Matthias Scheffler and colleagues describe the challenges of establishing a FAIR (Findable, Accessible, Interoperable, and Re- usable) data infrastructure.
The Atomic Simulation Recipes (ASR) is an open source Python framework for working with atomistic materials simulations in an efficient and sustainable way that is ideally suited for high-throughput computations. ASR contains a library of recipes, or high-level functions, that define specific atomistic simulations tasks using the Atomic Simulation Environment (ASE). The recipes can be combined into workflows that perform complex simulation tasks while keeping track of relevant metadata to ensure documentation and reproducibility of the data. The ASR also contains functionality for collecting the resulting data into databases and presenting them in a browser.
NOMAD CoE researchers from TU Wien and the Fritz Haber Institute have developed novel computer codes to enable massively parallel and highly accurate coupled cluster theory simulations of materials.
The number of serious brain disorders and deaths worldwide caused by diseases of the nervous system has risen sharply in recent decades. Despite huge advances in neuroscience over the past century, our understanding of the brain is still far from complete. To understand the causes and to aid the growing number of affected people, we need to be able to study the brain more closely. New tailored sensors measuring small electromagnetic fluctuations produced by active neurons could contribute to rapidly developing treatments for brain disorders.
Kristian Thygesen (WPs 4, 5 & 9), is part of a team at the Technical University of Denmark (DTU) that has just received an 8 million EURO (60 million DKK) grant from the Novo Nordisk Foundation. The BIO-MAG project focuses on developing new materials for highly sensitive magnetic field sensors for neuroimaging. Kristian leads the theoretical activities of the project, which is funded over six years starting January 2022.
Kristian is part of a team led by Nini Pryds (Department of Energy Conversion and Storage at DTU) that will develop 2D materials for two novel sensing technologies that can capture images of the brain at room temperature with tremendous sensitivity and spatial resolution. This will allow nervous system disorders to be detected and treated much earlier. The goal is to allow general practitioners to use the technology and perform imaging directly in their practices. The technology under development could become an alternative to expensive magnetic resonance imaging (MRI), which is usually only available in hospitals.
The goal of the Novo Nordisk Foundation Challenge Program is to support excellent researchers in addressing major societal challenges in the fields of health, sustainability or biotechnology.
The latest edition of the Adlershof Journal included an article interviewing our spokesperson Claudia Draxl about the work of FAIRmat.
You can read the article online for free or find a paper copy in one of the Adlershof Technology Center buildings.
The paper Similarity of materials and data‑quality assessment by fingerprinting by Martin Kuban, Šimon Gabaj, Wahib Aggoune, Cecilia Vona, Santiago Rigamonti and Claudia Draxl appeared in the October 2022 MRS Bulletin.
Abstract
Identifying similar materials (i.e., those sharing a certain property or feature) requires interoperable data of high quality. It also requires means to measure similarity. We demonstrate how a spectral fingerprint as a descriptor, combined with a similarity metric, can be used for establishing quantitative relationships between materials data, thereby serving multiple purposes. This concerns, for instance, the identification of materials exhibiting electronic properties similar to a chosen one. The same approach can be used for assessing uncertainty in data that potentially come from different sources. Selected examples show how to quantify differences between measured optical spectra or the impact of methodology and computational parameters on calculated properties, like the density of states or excitonic spectra. Moreover, combining the same fingerprint with a clustering approach allows us to explore materials spaces in view of finding (un)expected trends or patterns. In all cases, we provide physical reasoning behind the findings of the automatized assessment of data.
On Friday Septmber 9, Christopher M Wolverton of Northwestern University gave the talk The Phase Diagram of All Inorganic Materials at the NFDI Physical Sciences Joint Colloquium in Berlin.
The colloquium is now available to watch on our YouTube channel.
You can also read a review of the event on the MatWerk website.
Abstract
One of the holy grails of materials science, unlocking structure-property relationships, has largely been pursued via bottom-up investigations of how the arrangement of atoms and interatomic bonding in a material determine its macroscopic behavior. Here we consider a complementary approach, a top-down study of the organizational structure of networks of materials, based on the interaction between materials themselves. We demonstrate the utility of applying network theory to materials science in two applications: First, we unravel the complete “phase stability network of all inorganic materials” as a densely-connected complex network of 21,000 thermodynamically stable compounds (nodes) interlinked by 41 million tie-lines (edges) defining their two-phase equilibria, as computed by high-throughput density functional theory. Using the connectivity of nodes in this phase stability network, we derive a rational, data-driven metric for material reactivity, the “nobility index”, and quantitatively identify the noblest materials in nature. Second, we apply network theory to the problem of synthesizability of inorganic materials, a grand challenge for accelerating their discovery using computations. We use machine-learning of our network to predict the likelihood that hypothetical, computer generated materials will be amenable to successful experimental synthesis.