2023 MRS Spring Meeting & Exhibit
Symposium QM03-Symmetry-Guided Rational Design and Control of Transient and Metastable Quantum Phenomena
Recent advances in the field of quantum materials have demonstrated the fundamental importance of symmetry breaking and topological classification. Notable examples include the strongly correlated cuprates and nickelates with unidirectional orders that break the rotational symmetry, as well as the zoo of topological systems with novel boundary states that are protected by time reversal and inversion symmetries. Understanding and controlling symmetry, therefore, provide a powerful means towards rational design and realization of material properties. Over the last few years, there has been increasing excitement over transient, hidden, and metastable phases induced using external stimuli. The creation of these novel phases fundamentally involves the breaking or conservation of symmetry. This symposium will present recent progress in the prediction, modeling, detection, and control of out-of-equilibrium quantum phenomena, and highlight the role of symmetry as the guiding principle. Key focus areas include new material properties induced using optical, electric, and magnetic stimuli and new synthesis and fabrication paradigms enabled through non-equilibrium methods. The symposium will also harness the capabilities of emerging research tools, e.g. exascale modeling, artificial intelligence, ultrafast optics and X-ray free electron lasers, and advanced synthesis capabilities. The proposed symposium will drive the field forward by creating synergy across diverse and sometimes disparate communities, to realize new materials and new properties towards future quantum technologies.
Topics will include:
- Strain and pressure induced phases and phase transitions
- Interfacial and superlattice physics in heterostructures
- Moire superlattice and strain superlattice engineered phases
- Topological phenomena and Floquet states
- Driven phase transitions through symmetry changes
- Higher order symmetry breaking, metastable and hidden phases
- Ultrafast X-ray and electron studies of quantum materials
- Exascale modeling of out-of-equilibrium behaviors aided by artificial intelligence
Invited Speakers:
- Youngjun Ahn (University of Michigan, USA)
- Antia Botana (Arizona State University, USA)
- Alberto de la Torre Duran (Brown University, USA)
- Gregory Fiete (Northeastern University, USA)
- Dillon Fong (Argonne National Laboratory, USA)
- Er-Jia Guo (Institute of Physics, Chinese Academy of Sciences, China)
- Rui He (Texas Tech University, USA)
- Wanzheng Hu (Boston University, USA)
- Long Ju (Massachusetts Institute of Technology, USA)
- Roland Kawakami (The Ohio State University, USA)
- Hyunjung Kim (Sogang University, Republic of Korea)
- Anshul Kogar (University of California, Los Angeles, USA)
- David Lederman (University of California, Santa Cruz, USA)
- Nadya Mason (University of Illinois at Urbana-Champaign, USA)
- James McIver (Max Planck Institute, Germany)
- Joel Moore (University of California, Berkeley, USA)
- Keith Nelson (Massachusetts Institute of Technology, USA)
- Seongshik Oh (Rutgers University, USA)
- Chong-Yu Ruan (Michigan State University, USA)
- Justin Song (Nanyang Technological University, Singapore)
- Jörn Venderbos (Drexel University, USA)
- Yao Wang (Clemson University, USA)
- Haidan Wen (Argonne National Laboratory, USA)
- Stephen Wilson (University of California, Santa Barbara, USA)
- Liang Wu (University of Pennsylvania, USA)
- Jiaqiang Yan (Oak Ridge National Laboratory, USA)
- Ming Yi (Rice University, USA)
- Shuyun Zhou (Tsinghua University, China)
Symposium Organizers
Yue Cao
Argonne National Laboratory
Materials Science Division
USA
Matthew Brahlek
Oak Ridge National Laboratory
Materials Science and Technology
USA
Brian Skinner
The Ohio State University
Department of Physics
USA
Liuyan Zhao
University of Michigan
Department of Physics
USA
Topics
artificial intelligence
electron microprobe
laser
machine learning
quantum effects
quantum materials
spectroscopy
x-ray diffraction (XRD)
x-ray reflectivity