Norman C Rasmussen Assistant Professor
The research focus of Mingda and his group (Quantum Measurement Group) is to design novel materials characterization methods and to augment existing characterization methods to probe key properties of quantum materials that were either considered not measurable or not readily measurable with existing technique and analysis methods.
Materials characterization is essential for materials science. The birth of a new characterization method, such as X-ray diffraction (XRD), photoemission spectroscopy (PES), or inleastic neutron scattering (INS), all comes with great discoveries. However, the finite type of probe particles (e.g., photons, electrons, or neutrons) in one or more spaces (r, k, E, t) restricts the combination of measurable correlation functions, and even so, it is not always easy to interpret the experimental data.
To tackle the challenge, we take an integrated quantum theory, machine-learning, unconventional use of spectroscopies, and new architecture design approach: Quantum theory lays the foundation on measurable correlation functions, machine-learning aids to uncover hidden properties buried in data, unconventional use of neutron, x-ray, and electron spectra empowers existing techniques to a broader scope, and an integration of all these into new architecture can enable the detection of materials’ properties that evade experimental detection.
Please visit our group website for the updated publication list
22.02 Introduction to Applied Nuclear Physics
22.12 Radiation Interactions, Control, and Measurement
22.042 Modeling with Machine Learning: Nuclear Science and Engineering Applications
22.S902 Quantum Theory of Materials Characterization