Yefei Zhang

yif@colostate.edu

I'm currently a Senior student in Mathematics and Chemistry at Colorado State University.

My Research Interests lie in the broad area of Complex Systems and Nonlinear Dynamics. Currently, I am working on a MATLAB project about Navier–Stokes equations.

Curriculum Vitae  |  Email  |  GitHub  |  LinkedIn

"The whole universe is in a glass of wine."----Richard Feynman
Education
  • Colorado State University, Fort Collins, Colorado, USA Jan 2020 - May 2021

    Major in General Mathematics and Chemistry (GPA: 4.00/4.00)

  • East China Normal University, Shanghai, China Sep 2017 - Jul 2021

    Major in Chemistry and Elite Program (GPA: 3.32/4.00)

  • Belmont University, Nashville, Tennessee, USAAug 2019 - Dec 2019

    Partner School Exchange Student Program (GPA: 3.90/4.00)

Research Experience

Current research interests: Nonlinear Dynamics, Complex Systems, Multiscale Modeling.

Independent Studies in PDEs and Multiscale ModelingJan 2020 – Present

  • Learning the first four chapters of the book Partial Differential Equations authored by L.C. Evans and trying to complete the exercises in these chapters.
  • Reading the book Principles of Multiscale Modeling by Weinan E and Nonlinear Dynamics And Chaos by Steven Strogatz. Trying to get the basic method of studying complex systems.

    • Synthesis and Characterization of Several Terbium(III)-Based MoleculesAug 2019 – Dec 2019
    Research Student, Department of Chemistry and Physics, Belmont University Advisor:Dr. Justin Stace

  • Studied the chemical sensing properties and Synthesized some terbium-bisphenathroline complex molecules.
  • Used UV-VIS and NMR to characterize the luminescent molecules and explored their electromagnetic properties.

    • Solar-Based Photocatalytic Decomposition of Water into HydrogenJul 2019 – Aug 2019
    Summer School Student, Dalian Institute of Chemical Physics, CAS Advisor:Dr. Fuxiang Zhang

  • Read and organized some recent papers about Photocatalytic Water Splitting.
  • Learned how to design the photocatalyst and how to use the analytical instruments (XRD, SEM, TEM).

    • Synthesis and Characterization Fluorescent Probes Based on CoumarinJan 2018 – Jun 2019
    Research Student, Department of Chemistry, ECNUAdvisor:Dr. Xiaoyan Cui

  • Studied the properties of Fluorescent Probes and synthesized the silicon-based coumarin fluorescent molecule using m­bromoaniline as the precursor.
  • Calculated the hydrogen bond energy of silicon-based coumarin using M06-2X and Def2TZVP theoretical model in Gaussian software, and explained the reason for spectral changes in different polar solvents.
    • Mathematical Physics

    Physics is an experimental and theoretical science. It lies in the balance of theory being confirmed by experiment while experiment may drave theory. The realm of theoretical physics is concerned with finding mathematical theories that describe our world in ways we will (hopefully) assert via experimentation.

    Mathematical physics is a broad subject. I like to think of it as dual to theoretical physics in that a mathematical physicist expands the mathematics found in the theoretical models that physicist create. A mathematician is concerned with the rigor of the mathematics being correct, whereas a physicist cares about the model working properly. Hence, there is indeed a gap that must be filled in order for the mathematics to be well-posed.
    Partial Differential Equations

    The world around us is a complex dyamical beast. One such way of capturing the behavior of model systems is through PDEs. A motivating example is the model of heat flow on a piece of ice where heat is being pumped into the ice through its boundary. Even such a simple system can become complex. Yet, in order to be able to solve such models, we make simplifying assumptions (the cube is homogeneous in specific heat, it cannot melt, and it is nicely shaped). When we remove such restrictions, we find ourselves in the realm of numerical PDEs and computing.

    PDEs are also highly geometrical as one finds the relationships causing dynamics to be intimately connected to the structure of the domain of interest. In the previous example, we can imagine the crystaline structure of ice allows one to understand the routes that energy must flow, and it is through this geometric information that we are capturing change.
    Linear Programming

    Linear Programming is the technique of portraying complicated relationships between elements by using linear functions to find optimum points. The relationships may be more complicated than accounted for, however linear programming allows for a simplified understanding of their connections.

    Linear programming is often used when seeking the optimal solution to a problem, given a set of constraints. To find the optimum result, real-life problems are translated into mathematical models to better conceptualize linear inequalities and their constraints.
    Awards & Scholarships
    1. Dean’s List, Colorado State University 2020
    2. Global Partnership Award, Colorado State University 2020
    3. Dean’s List, Belmont University Fall 2019
    4. Exchange Partner Tuition Waiver, Belmont University Fall 2019
    5. The Elite Program Scholarship, East China Normal University 2017 & 2018 & 2019
    6. School-level Scholarship, East China Normal University (Top 10%) 2018
    7. Honorable Mention of Physics Contest, East China Normal University (Top 15%) 2018
    8. Outstanding Volunteer, East China Normal University 2018
    Teaching Experience
    1. East China normal university tutor center, Shanghai, CN Feb 2018 – Jul 2018
      Teaching Assistant in Calculus.
    2. Xiacun Primary School, Linyi, Shandong Province, CN Jan 2018 – Feb 2018
      Teaching Volunteer in Basic Chemistry and Physics Experiments.
    Miscellaneous

    I'm an amateur in cooking / running / traveling.

    Interesting Websites

    Theoretical Chemistry