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

Highly Cited Researcher (Top 0.1%), Clarivate Web of Science, 2023

Highly Cited Researcher (Top 0.1%), Clarivate Web of Science, 2022

World’s top 2% scientists (based on 2021-single-year citation) by the Stanford University list, 2022

Junior Faculty Outstanding Research Award, A. James Clark School of Engineering, University of Maryland, 2022

Highly Cited Researcher (Top 0.1%), Clarivate Web of Science, 2021

World’s top 2% scientists (based on 2020-single-year citation) by the Stanford University list, 2021 

Outstanding Young Scientist Award, Maryland Academy of Sciences, 2019

Highly Cited Author (top 5%), Royal Society of Chemistry, 2019

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

Top Peer Reviewer in Materials Science (top 1%) and Cross-Field (top 1%), Web of Science, 2019

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















 

Editorial Board

NPJ Computational Materials

Energy Storage Materials

Advanced Theory and Simulations

Energy Materials

Journal of Materials Informatics 































































































 

  • 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: Advanced Energy Materials, 9, 1902078 (2019), 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: Angewandte Chemie Int. Ed., 59, 8039-8043 (2019), ACS Energy Letters, 4, 2444-2451 (2019), 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: Atomistic Modeling in Materials (Formerly ENMA 489A/ENMA 698A)
  • ENMA 401 / ENMA 601: Continuum Modeling of Materials (Formerly ENMA 489C/ENMA 698C)
  • ENMA 300 / ENME 382: Introduction to Materials and Their Applications
  • ENMA 688: Seminar in Materials Science and Engineering
  • ENMA 499: Senior Laboratory Project 
  • PHYS 499A: Special Problems in Physics
  • ENMA 698: Special Problems in Engineering Materials
  • ENMA 312: Experimental Methods in Materials Science (Guest Lecturer of computational methods) 



     

See full publication record on [Google Scholar][Research ID][ORCID][ResearchGate]

Selected Publications

*  corresponding author; # group members in multiple-group collaboration papers; 1 co-first authors. 

 

$2M NSF Grant to Advance Future of Semiconductors Technology and Workforce

UMD Researchers Will Work to Discover New Materials to Safeguard Nation’s Supply of Crucial Tech Hardware

Ten Maryland MSE Faculty Members Ranked in Top 2% of World Scientists

Elsevier releases updated science-wide database

Engineering a Multi-Element Atomic Arrangement

A novel disorder-to-order transition strategy for ordered nanoparticles published in Science Advances.

Nine Maryland Engineers Recognized as Being "One in 1,000"

Clark School researchers among the "who's who" of influential researchers, according to Clarivate.

UMD-Led Team Wins NSF Award for Rapid Materials Design

The collaborative team receives $1.8 million in funding to develop an integrated framework to drive the rapid design of novel materials for batteries and fuel cells.

Seven Students Win 2021 Dean's Research Awards

From fabricated human tissue to Wifi beamed from space, awards recognize cutting-edge research

CREB Kicks Off 2021 with Meeting to Discuss Future of Battery Research

The virtual meeting aimed to bolster battery technology under extreme conditions.

MSE Graduate Student Adelaide Nolan Receives MRS Award

Nolan took the "Best Student Presenter Award" at the 2020 fall meeting.

MSE Alum Awarded NSF Graduate Research Fellowship

Alexander Epstein is on track to complete his Ph.D. at UC Berkeley in 2023. 

New, superfast method for ceramic manufacturing could open door to AI-driven materials discovery

UMD engineers have reinvented a 26,000-year-old manufacturing process into an innovative approach to fabricating ceramic materials.

MSE Ranked #23 by U.S. News and World Report

UMD’s Materials Science and Engineering Department hits #23 in U.S. graduate school rankings – its highest ranking yet.

2020 Hulka/Wells Energy Fellowships Awarded

Biofuel Production and Advanced Energy Storage Projects Selected

MSE Graduate Student Racks Up Multiple Honors

Adelaide Nolan recognized by UMD, NSF and Clearwater for her contributions to energy research.

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.