Faculty Directory

Mo, Yifei

Mo, Yifei

Associate Professor
Materials Science and Engineering
Maryland Energy Innovation Institute
1137 Engineering Laboratory Building
Website(s):

EDUCATION

Postdoctoral Research Associate, Massachusetts Institute of Technology, 2010-2013

Ph.D., University of Wisconsin-Madison, 2010

 

HONORS & AWARDS

Outstanding Young Scientist Award, Maryland Academy of Sciences, 2019

3M Non-Tenured Faculty Award, 3M, 2019 

Scialog Fellow of Advanced Energy Storage, Research Corporation Foundation, 2017

Minta Martin Award, University of Maryland, 2014

 

  • Computational materials science
  • Computational materials design and materials discovery
  • Molecular dynamics simulations
  • Large-scale atomistic modeling
  • Materials for energy storage and conversion

My research aims to advance the understanding, design, and discovery of engineering materials through cutting-edge computational techniques. We target critical materials problems that impede high-impact technologies, such as energy storage, conversion, and efficiency. In our research, the computational modeling provides enhanced fundamental scientific insights, and enables the ability to rationally design new materials.

Accelerated design and discovery of novel materials through computation. Computational techniques based on first principles are capable of predicting materials properties with little or no experimental input. In our research, we leverage an array of computational techniques to design new materials with enhancement in multiple properties. With the aid of supercomputers, computational methods can significantly speed up the innovation and development of new materials. Our current efforts focus on solid-state batteries, solid oxide fuel cell, and various membrane materials.
Selected publications: Joule, 2, 2016-2046 (2018)Nature communications, 8, 15893 (2017)Advanced Energy Materials, 1702998 (2018)Advanced Science, 1600517 (2017)Physical Chemistry Chemical Physics, 17, 18035-18044 (2015)Nature Materials, 14,1026–1031(2015)Energy and Environmental Science, 6, 148-156 (2013)Chemistry of Materials, 24, 15-17 (2012)

Understanding materials and interfaces in beyond Li-ion energy storage systems. The next-generation energy storage systems may be based on novel chemistries, such as all-solid-state, Li metal, Li-sulfur, and metal-oxygen, to achieve significantly higher energy density. Materials and their interfaces in these batteries are often the key limiting factors and origins of failures. For example, the degradation at the electrolyte-electrode interfaces causes poor cyclability, low coulombic efficiency, and premature failure in these new battery systems. We use state-of-the-art computation techniques to understand the limiting factors and failure mechanisms at the interfaces, and to computationally design solutions (such as novel coating materials) for these new energy technologies.
Selected publications: Joule, 2, 2016-2046 (2018)Journal of Materials Chemistry A, 4, 3253-3266 (2016) (Front cover); Advanced Science, 1600517 (2017)ACS Applied Materials & Interfaces, 7, 23685-23693 (2015)
Experimental collaborations: Nature Materials 16, 572-579 (2017)Advanced Energy Materials, 6, 1501590 (2016)Science Advances, 3, e1601659 (2017);Journal of the American Chemical Society, 138 (37), 12258–12262 (2016)Advanced Materials (2017); Nature Communications, 7, 11441 (2016)ACS Nano, 10, 9577–9585, (2016)Nano Letter, 15, 5755–5763 (2015)

Large-scale atomistic modeling and molecular dynamics. Large-scale atomistic modeling has the unique capability to capture complex materials phenomena, ranging from interfaces, nanostructures, to non-equilibrium dynamics. However, current large-scale modeling methods based on classical force fields have limited accuracy, transferability, and predictivity, while higher level ab initio methods are often limited in system size (hundreds of atoms) and time-scale (tens of ps). We aim to bridge the gap between ab initio methods and large-scale atomistic modeling. Integrating these techniques across different length scales enable us the unique capability to study complex processes with full atomistic details.
Selected publications: Nature, 457, 1116-1119 (2009)Nature Materials, 12, 9-11 (2013)Journal of Physics D: Applied Physics, 44, 405401 (2011)Applied Physics Letters, 90, 181926 (2007)

 

 

  • ENMA 461: Thermodynamics of Materials
  • ENMA 400 / ENMA 600: Introduction to Computational Materials Science (Formerly as ENMA 489A/ENMA 698A)
  • ENMA 300 / ENME 382: Introduction to Materials and Their Applications

Dr. Mo’s publication record on [Google Scholar][Research ID][ORCID][ResearchGate]

Selected Representative Work

Publication List  
*  corresponding author; # group members in multiple-group collaboration

 

 

The Battery Revolution

Fires in cell phones, laptops, and even a jumbo jet might have one thing in common: a liquid-electrolyte lithium-ion battery.

Hu, Leite and Mo Promoted

MSE professors honored at the 2019 Engineering Assembly.

Yifei Mo receives 3M Non-Tenured Faculty Award

Mo will receive $45K to help fund his research in engineered materials design.

Powerful X-ray Beams Unlock Secrets of Nanoscale Crystal Formation

Study published in the Journal of the American Chemical Society.

Mo Research Group's Solid-State Battery Review Published in Joule

Review discusses the advantages of all-solid-state battery chemistry.

MSE Undergrad wins ARL Student Competition

Sarah Adams recognized for her nanotechnology research.

MSE Research Reveals Unique Ionic Diffusion Mechanism in Super-Ionic Conductors  

Mo, He and Zhu devise an ‘ion transport highway’ for solid-state batteries.

MSE Researchers Discover New Materials, New Research Direction for High-energy Li-metal Batteries

Yifei Mo and team push development of high-energy rechargeable lithium batteries.

MSE Researchers Publish Series Study on All-Solid-State Batteries

Yifei Mo and team seek to improve all-solid-state Li-ion batteries.

New Software Will Enhance Materials Science and Engineering’s Undergraduate Program

UMD wins one of six computational design toolkits from ASM International.

Students Use UMD Supercomputer to Design, Test Materials

New course in computational materials design bridges theory and practice.

Discover, Create, Deploy: Professors Contribute to Materials Genome Initiative

Maryland MSE professor, alumnus co-author white paper on enhancing “materials innovation infrastructure.”

Leite, Mo Join MSE Faculty

Professors specialize in physical and computational materials science for sustainable energy applications.