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Matthias Scheffler

Matthias Scheffler is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Matthias Scheffler rather than just read about it. In short: Matthias Scheffler (born June 25, 1951, in Berlin) is a German theoretical physicist whose research focuses on condensed matter theory, materials science, and artificial intelligence. He is particularly known for his contributions to density-functional theory and many-electron quantum mechanics and for his development of multiscale approaches.

Matthias Scheffler — main illustration
Matthias Scheffler — illustration

Key takeaways

  • Matthias Scheffler belongs to physics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Matthias Scheffler to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Matthias Scheffler from memory before moving on to harder problems.

Reference excerpt

Matthias Scheffler (born June 25, 1951, in Berlin) is a German theoretical physicist whose research focuses on condensed matter theory, materials science, and artificial intelligence. He is particularly known for his contributions to density-functional theory and many-electron quantum mechanics and for his development of multiscale approaches. In the latter, he combines electronic-structure theory with thermodynamics and statistical mechanics, and also employs numerical methods from engineering. As summarized by his appeal "Get Real!" he introduced environmental factors (e. g. partial pressures, deposition rates, and temperature) into ab initio calculations. In recent years, he has increasingly focused on data-centric scientific concepts and methods (the 4th paradigm of materials science) and on the goal that materials-science data must become "Findable and Artificial Intelligence Ready".

Academic career Scheffler studied physics at Technische Universität (TU) Berlin. He carried out his doctoral work in the field of theoretical solid-state physics at the Fritz Haber Institute of the Max Planck Society (FHI) and received his Ph.D. from the TU Berlin in 1978. He then moved to the Physikalisch-Technische Bundesanstalt in Braunschweig, where he was employed as a research associate from 1978 to 1987. From 1979 to 1980, he was also a visiting scientist at the IBM T.J. Watson Research Center, Yorktown Heights, USA. He received his habilitation in 1984 from the TU Berlin. In 1988, he was appointed as a scientific member of the Max Planck Society and founding director of the Theory Department of the Fritz Haber Institute of the Max Planck Society in Berlin. The following year he received an honorary professorship at the TU Berlin. This was followed by further honorary professorships at Freie Universität Berlin (2006), Humboldt-Universität zu Berlin (2016), and in Hokkaido, Japan (2016). He is also Distinguished Visiting Professor of Computational Materials Science and Engineering at the University of California, Santa Barbara since 2005. Since 2020 he directs the NOMAD Laboratory at the Berlin Institute for the Foundations of Learning and Data (BIFOLD) at the Technical University of Berlin. The NOMAD Laboratory was founded in 2014 as part of the European NOMAD Center of Excellence. It was initially based at the Fritz Haber Institute of the Max Planck Society in Berlin, and later moved to the Berlin Institute for the Foundations of Learning and Data (BIFOLD).

Research focus Since the beginning of his career, Scheffler has been working on fundamental aspects of the chemical and physical properties of surfaces, interfaces, clusters, and nanostructures. Current research activities include studies of heterogeneous catalysis, thermal conductivity, electrical conductivity, thermoelectric materials, defects in semiconductors, inorganic/organic hybrid materials, and biophysics. These are studies that combine quantum mechanics, ab initio calculations of the electron structure and molecular dynamics with methods from thermodynamics, statistical mechanics, and engineering. In this way, the understanding of meso- and macroscopic phenomena can be developed or deepened under realistic conditions (T, p). Scheffler is also working on the development of theoretical models for the calculation of excited states and electron correlations. The software package FHI-aims developed for this purpose by Scheffler, together with Volker Blum and many others, was specifically designed for large-scale calculations on high-performance computers. Scheffler has investigated many different classes of materials with high application relevance (e.g. compound semiconductors, metals, oxides, two-dimensional materials, organic materials, surfaces), as well as successfully developing a wide range of phenomena with direct practical relevance (e.g. crystal structure and growth, electronic material properties, metastability of impurities in semiconductors, electrical and thermal conductivity, heterogeneous catalysis). More than 116 of his former employees now hold professorships or alike positions. Scheffler is one of the most highly cited scientists in his field.

Data science and development of the NOMAD database Since 2003, Scheffler and his group have been developing artificial intelligence methods and are increasingly engaged in scientific data-sharing activities. Worldwide, vast amounts of scientific data are generated on materials, but only a fraction of it is actually used and published. Often, data are not adequately characterized and described, and most data are not considered further because they are not useful for the ongoing, focused research project. However, they may contain valuable information for other topics ("recycle the waste!"). For computational materials science, Scheffler, together with Claudia Draxl, designed and set up a database where research data can be stored in a well-documented manner and where the research data are also available to other researchers. With the detailed description and availability of data, artificial intelligence methods can be applied and materials with novel and advantageous properties can be identified. The previously often very lengthy value creation process in the development of new materials, from basic research to market-ready product, can thus be significantly shortened.

Awards and honors 2001: Max Planck Research Award jointly awarded by the Alexander von Humboldt Foundation and the Max Planck Society 2003: Medard W. Welch Award of the AVS (association for science and technology of materials, interfaces and processing) 2004: Max Born Medal and Prize jointly awarded by the British Institute of Physics (IOP) and the German Physical Society (DPG) 2007: Honorary doctorate from the Lund University, Sweden 2010: Rudolf Jaeckel Prize of the German Vacuum Society (DVG) Since 1998: Fellow of the American Physical Society Since 2002: Member of the Berlin-Brandenburg Academy of Sciences and Humanities Since 2017: Member of the German National Academy of Sciences Leopoldina 2023: Daniel C. Tsui Lecture, IOP CAS, Beijing 2024: MBA Award of the Japan Society of Vacuum and Surface Science 2025: Zhongguancun Award for International Cooperation of the City of Beijing 2026: Lee Hsun Award, Institute of Metal Research (IMR), Chinese Academy of Sciences

References

External links NOMAD Laboratory Publications by Matthias Scheffler at google scholar

Illustrations

Matthias Scheffler illustration

Worked examples

Example 1 — a first encounter with Matthias Scheffler

Start with the simplest possible case. Write down what Matthias Scheffler claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Matthias Scheffler before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Matthias Scheffler ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Matthias Scheffler

In research
Matthias Scheffler appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Matthias Scheffler in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Matthias Scheffler is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1951 births, 20th-century German physicists, 21st-century German physicists, so understanding it makes those chapters shorter.
In everyday life
Look for Matthias Scheffler outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Matthias Scheffler in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Matthias Scheffler means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Matthias Scheffler out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Matthias Scheffler in simple terms?

Matthias Scheffler (born June 25, 1951, in Berlin) is a German theoretical physicist whose research focuses on condensed matter theory, materials science, and artificial intelligence. He is particularly known for his contributions to density-functional theory and many-electron quantum mechanics and…

Why does Matthias Scheffler matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Matthias Scheffler?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Matthias Scheffler.

Tags

  • 1951 births
  • 20th-century German physicists
  • 21st-century German physicists
  • Condensed matter physicists
  • Fellows of the American Physical Society
  • German materials scientists
  • German theoretical physicists
  • Living people
  • Max Planck Institute directors
  • Max Planck Society people
  • Members of the German National Academy of Sciences Leopoldina
  • Scientists from Berlin

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