Gennady Gor: Teaching

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Undergraduate Courses

ChE 342: Chemical Engineering Thermodynamics II

The principles and methods developed in Chemical Engineering Thermodynamics I are extended to multicomponent systems, and used to treat phase and chemical equilibrium as well as such applications as chemical reactors and refrigeration systems. Additionally, topics which are often left uncovered in Thermo I, such as thermodynamic cycles are discussed.


Group photos of ChE 342 students with Prof. Gor at the PSEG power plant tour, illustration of the thermodynamic cycles topic. The tour was given by NJIT alum, Ms. Kanwal Rafiq, manager at the Power Plant.

The course was offered in Fall 2016, Spring 2018, Fall 2018, Spring 2019. Next time it will be offered in Fall 2019.


ChE 491: (Independent Study) Python for Chemical Engineers

Modern engineering calculations are hard to imagine without a and flexible and efficient programming language. Python is such language. While it has spread in computational science, physics communities, rare ChemEs use it. The goal of this course is to introduce undergraduate ChemE students to Python, (including NumPy, SciPy, SymPy) and demonstrate how it can be used for solving the chemical engineering problems. In additiona to undergraduate students, several graduate students joined the seminars.

Max Maximov presents at the Python seminar. Participants include not only those undergraduate students who take it for credit, but other NJIT undergraduate and graduate students.

The course was offered in Spring 2019, and taught mostly by Max Maximov, Ph.D. student in the Gor group. The plan is to develop an elective course based on that independent study.

Introductory Materials on Python Programming

Python basics

  • A hands-on introduction to Python for beginning programmers - Jessica McKellar: YouTube video (1 h 54 min)
  • Online course on python, starting from very basics codecademy (13 hours course)

Numerical and Scientific Python

  • Introduction to NumPy - SciPy 2015 Tutorial - Eric Jones: YouTube video (2 h 42 min)
  • NumPy Beginner - SciPy 2016 Tutorial - Alexandre Chabot LeClerc: YouTube video (2 h 47 min)
  • Learn Python for Science - NumPy, SciPy and Matplotlib - Shane Neeley: YouTube video (1 h 14 min)
  • Computational Physics 509 - Physics Applications of Computers -- a great course by Professor Kristjan Haule (Rutgers physics). Substantial part of this course is about using Python, NumPy, SciPy for research in computational physics. It has detailed lecture notes and a number of useful links.
  • A number of lectures and on-line trainings in Python Enthought

Graduate Courses

ChE 702: (Special Topic) Statistical Thermodynamics and Molecular Modeling

This course aimed to kill two birds with one stone: (1) to cover the basics of classical statistical mechanics and (2) explain how the most common methods of molecular modeling work. Understanding the latter is not possible without knowing the former. The course included several computational assignments. It also included a short introduction to Python 2.7, NumPy and SciPy, so that all "spoke the same language".

Today molecular simulations became a significant complement to "paper-and-pencil" theory and experimental research. Moreover, often molecular simulations can substitute experimental research being much cheaper, safer and faster. Molecular simulations are used in numerous various fields, e.g. they are applied to study problems related to drug design, protein folding and aggregation; wetting phenomena and hydration thermodynamics; nucleation and growth processes; the thermophysical properties of complex fluids, such as ionic liquids and liquid crystals; the phase behavior of polymeric, colloidal, and self-assembled systems; and the synthesis, design and characterization of advanced materials, etc.

Equilibrated configuration of Lennard-Jones atoms and corresponding radial distribution function, obtained by Monte Carlo method, implemented by students as a part of the ChE 702 course.

The course was offered in Spring 2017. It was transformed into ChE 775, which will be offered as a regular graduate elective in the Spring 2020.


ChE 775: Molecular Simulations in Chemical Engineering

The course is aimed to introduce the graduate students to the basics of molecular simulation. Two simulation techniques will be discussed in detail: Monte Carlo and molecular dynamics methods. The students will study the algorithms, and the statistical mechanics basis of these algorithms. Then they will use the popular open source codes to simulate the systems relevant for chemical engineers.

The course will be offered in Spring 2020.


ChE 791: Chemical Engineering Graduate Seminar

While being a zero-credit course, the graduate seminar is a significant part of graduate education. It brings researchers from academia, industry and governmental labs, broadening not only the vision of potential areas of research, but aslo the spectrum of career opportunities.

Gennady Gor coordinated the Seminar Series in the Fall 2017, and will be a seminar coordinator in the Fall 2019.


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