This course focuses on the interaction of chemical engineering, biochemistry, and microbiology. Mathematical representations of microbial systems are featured among lecture topics. Kinetics of growth, death, and metabolism are also covered. Continuous fermentation, agitation, mass transfer, and scale-up in fermentation systems, and enzyme technology round out the subject material.

This subject deals primarily with kinetic and equilibrium mathematical models of biomolecular interactions, as well as the application of these quantitative analyses to biological problems across a wide range of levels of organization, from individual molecular interactions to populations of cells.

This course aims to connect the principles, concepts, and laws/postulates of classical and statistical thermodynamics to applications that require quantitative knowledge of thermodynamic properties from a macroscopic to a molecular level. It covers their basic postulates of classical thermodynamics and their application to transient open and closed systems, criteria of stability and equilibria, as well as constitutive property models of pure materials and mixtures emphasizing molecular-level effects using the formalism of statistical mechanics. Phase and chemical equilibria of multicomponent systems are covered. Applications are emphasized through extensive problem work relating to practical cases.

Students are introduced to chemical engineering and learn about its many different applications. They are provided with a basic introduction to matter and its different properties and states. An associated hands-on activity gives students a chance to test their knowledge of the states of matter and how to make observations using their five senses: touch, smell, sound, sight and taste.

Introduces the design of chemical reactors via synthesis of chemical kinetics, transport phenomena, and mass and energy balances. Topics: reaction mechanisms and chemical/biochemical pathways; transition-state theory; batch, plug flow and well-stirred reactors; heterogeneous and enzymatic catalysis; heat and mass transport in reactors, including diffusion to and within catalyst particles and cells or immobilized enzymes.

The theoretical frameworks of Hartree-Fock theory and density functional theory are presented as approximate methods to solve the many-electron problem. A variety of ways to incorporate electron correlation are discussed. The application of these techniques to calculate the reactivity and spectroscopic properties of chemical systems, in addition to the thermodynamics and kinetics of chemical processes, is emphasized. This course also focuses on cutting edge methods to sample complex hypersurfaces, for reactions in liquids, catalysts and biological systems.

Introduces principles and mathematical models of electrochemical energy conversion and storage. Students study equivalent circuits, thermodynamics, reaction kinetics, transport phenomena, electrostatics, porous media, and phase transformations. In addition, this course includes applications to batteries, fuel cells, supercapacitors, and electrokinetics.

7.02 and 7.021 require simultaneous registration. Application of experimental techniques in biochemistry, microbiology, and cell biology. Emphasizes integrating factual knowledge with understanding the design of experiments and data analysis to prepare the students for research projects. Instruction and practice in written communication provided.

This course is the scientific communications portion of course 7.02, Experimental Biology and Communication. Students develop their skills as writers of scientific research, skills that also contribute to the learning of the 7.02 course materials. Through in class and out of class writing exercises, students explore the genre of the research article and its components while developing an understanding of the materials covered in the 7.02 laboratory.

Fundamentals of thermodynamics, chemistry, flow and transport processes as applied to energy systems. Analysis of energy conversion in thermomechanical, thermochemical, electrochemical, and photoelectric processes in existing and future power and transportation systems, with emphasis on efficiency, environmental impact and performance. Systems utilizing fossil fuels, hydrogen, nuclear and renewable resources, over a range of sizes and scales are discussed. Applications include fuel reforming, hydrogen and synthetic fuel production, fuel cells and batteries, combustion, hybrids, catalysis, supercritical and combined cycles, photovoltaics, etc. Different forms of energy storage and transmission. Optimal source utilization and fuel-life cycle analysis.

This course provides a brief introduction to the field of biocatalysis in the context of process design. Fundamental topics include why and when one may choose to use biological systems for chemical conversion, considerations for using free enzymes versus whole cells, and issues related to design and development of bioconversion processes. Biological and engineering problems are discussed as well as how one may arrive at both biological and engineering solutions.

Chemical engineering problems presented and analyzed in an industrial context. Emphasis on the integration of fundamentals with material property estimation, process control, product development, and computer simulation. Integration of societal issues, such as engineering ethics, environmental and safety considerations, and impact of technology on society are addressed in the context of case studies.

Designed as a freshmen seminar course, faculty from various School of Engineering departments describe the research and educational opportunities specific to and offered by their departments. Background lectures by the 20.010J staff introduce students to the fundamental scientific basis for bioengineering. Specially produced videos provide additional background information that is supplemented with readings from newspaper and magazine articles. Bioengineering at MIT is represented by the diverse curricula offered by most Departments in the School of Engineering. This course samples the wide variety of bioengineering options for students who plan to major in one of the undergraduate Engineering degree programs. The beginning lectures describe the science basis for bioengineering with particular emphasis on molecular cell biology and systems biology. Bioengineering faculty will then describe the bioengineering options in a particular engineering course as well as the type of research conducted by faculty in the department.

This course is offered to undergraduates and introduces students to the formulation, methodology, and techniques for numerical solution of engineering problems. Topics covered include: fundamental principles of digital computing and the implications for algorithm accuracy and stability, error propagation and stability, the solution of systems of linear equations, including direct and iterative techniques, roots of equations and systems of equations, numerical interpolation, differentiation and integration, fundamentals of finite-difference solutions to ordinary differential equations, and error and convergence analysis. The subject is taught the first half of the term. This class was originally listed in Course 13 (Ocean Engineering) as 13.002J.

Introduction of engineering management. Financial principles, management of innovation, engineering project planning and control, human factors, career planning, patents and technical strategy. Case study method of instruction emphasizes participation in class discussion. Juniors, seniors, or graduate students. Engineering School-Wide Elective subject.

This course develops and applies scaling laws and the methods of continuum mechanics to biomechanical phenomena over a range of length scales. Topics include: structure of tissues and the molecular basis for macroscopic properties; chemical and electrical effects on mechanical behavior; cell mechanics, motility and adhesion; biomembranes; biomolecular mechanics and molecular motors. Experimental methods for probing structures at the tissue, cellular, and molecular levels.

Numerical methods for solving problems arising in heat and mass transfer, fluid mechanics, chemical reaction engineering, and molecular simulation. Topics: numerical linear algebra, solution of nonlinear algebraic equations and ordinary differential equations, solution of partial differential equations (e.g. Navier-Stokes), numerical methods in molecular simulation (dynamics, geometry optimization). All methods are presented within the context of chemical engineering problems. Familiarity with structured programming is assumed. This course focuses on the use of modern computational and mathematical techniques in chemical engineering. Starting from a discussion of linear systems as the basic computational unit in scientific computing, methods for solving sets of nonlinear algebraic equations, ordinary differential equations, and differential-algebraic (DAE) systems are presented. Probability theory and its use in physical modeling is covered, as is the statistical analysis of data and parameter estimation. The finite difference and finite element techniques are presented for converting the partial differential equations obtained from transport phenomena to DAE systems. The use of these techniques will be demonstrated throughout the course in the MATLAB® computing environment.

This course serves as a description and critical assessment of the major issues and stages of developing a pharmaceutical or biopharmaceutical. Topics covered include drug discovery, preclinical development, clinical investigation, manufacturing and regulatory issues considered for small and large molecules, and economic and financial considerations of the drug development process. A multidisciplinary perspective is provided by the faculty, who represent clinical, life, and management sciences. Various industry guests also participate.

Introduction to dynamic processes and the engineering tasks of process operations and control. Subject covers modeling the static and dynamic behavior of processes; control strategies; design of feedback, feedforward, and other control structures; model-based control; applications to process equipment.