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Host

  • Prof. Rongpei Shi

    Harbin Institute of Technology, Shenzhen, Guangdong, China.

    Rongpei Shi is a full professor in the College of Materials at Harbin Institute of Technology Shenzhen (HITsz). He received his Ph.D. degree in Materials Science and Engineering from The Ohio State University (OSU) in 2014. Prior to joining HITsz, he was a research associate in the Department of Materials Science and Engineering at OSU from June 2014 to June 2017, and a staff scientist in the Materials Science Division at the Lawrence Livermore National Laboratory (LLNL) from July 2017 to August 2021. His research focuses on the intersection of multi-scale modeling and machine learning, and their applications in understanding composition-processing-microstructure-properties linkages in advanced metallic (Ti, Ni, Co, Cu-based) alloys for structural applications, metal additive manufacturing and energy storage materials. He has published about 80 papers (21 in Acta Materialia with 9 as a first author) in peer-reviewed journals as documented in Google Scholar Profile. He received best poster award in Gordon Research Conference-Physical Metallurgy 2013 and was named among five finalists of Aaronson Award in the International Conference on Solid-Solid Phase Transformation in Inorganic Materials for Materials for outstanding young researcher, at Whistler, Canada on 2015, publication award in physical life and science directorate at LLNL 2021.

Speaker(s)

  • Prof. Zi-Kui Liu

    The Pennsylvania State University, PA, USA.

    Dr. Zi-Kui Liu is the Dorothy Pate Enright Professor in the department of Materials Science and Engineering at The Pennsylvania State University. He obtained his BS from Central South University (China), MS from University of Science and Technology Beijing (China), PhD from Royal Institute of Technology (KTH, Sweden). He was a research associate at University of Wisconsin-Madison and a senior scientist at Questek. He has been at the Pennsylvania State University since 1999 and coined the term "Materials Genome®" in 2002. Dr. Liu's current research activities are centered on first-principles calculations, machine learning, CALPHAD modeling, statistical mechanics, irreversible thermodynamics, and their integration for understanding defects, phase stability, and phase transformations, and designing and tailoring materials chemistry, processing, and properties. He was the lead author of a textbook on Computational Thermodynamics of Materials published by Cambridge University Press.

Abstract

The core of 4th industrial revolution is the digitization of knowledge and fusion of technologies through digitization. As materials performances are dictated by their microstructures consisting of phases and their spatial arrangements, knowledge of phase stability and phase properties is the center piece of discovery and design of materials with transformative properties and is represented by thermodynamics of individual phases. The systematic digitization of thermodynamics has been occurring since the middle of the last century, represented by the CALPHAD modeling of Gibbs energy of individual phases in multicomponent systems as a function of their external and internal variables. At the same time, the first-principles calculations based on the density functional theory (DFT) has enabled the digitization of quantum mechanics. The significant interactions of CALPHAD and DFT approaches have not only enhanced each other, but also enabled us to develop the zentropy theory with a remarkable predictive capability, a set of computational tools, and their integration towards an ocean of data as an open-source ecosystem for materials science and engineering. The presenter's experience on those interactions and future perspectives will be discussed in this seminar.
• Liu et al. An integrated framework for multi-scale materials simulation and design, J. Comput-Aided Mater. Des. 11 (2004), 183–199.
• Liu, First-Principles calculations and CALPHAD modeling of thermodynamics, J. Phase Equilibria Diffus. 30 (2009), 517-534.
• Liu, Perspective on Materials Genome®. Chinese Sci. Bull. 59, 1619–1623 (2014).
• Liu, Ocean of Data: Integrating first-principles calculations and CALPHAD modeling with machine learning. J. Phase Equilibria Diffus. 39, 635–649 (2018).
• Liu, Computational thermodynamics and its applications, Acta Mater. 200 (2020), 745.
• Liu, Theory of cross phenomena and their coefficients beyond Onsager theorem, Mater. Res. Lett. 10, 393–439 (2022).

Presentation

  • Prof. Zi-Kui Liu
    Topic: Ocean of Data
  • Topic: Free discussion
  • Topic: JMI introduction
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