2.S990: Fashion Engineering
Lectures: Wed 1:00PM - 2:30PM (Online)
Level: Graduate (undergrads can take), 6 units: 2-0-4
Fashion is one of the biggest industries in the world, which is driving innovation in polymer science, mechanical engineering, manufacturing techniques, optical engineering, and manufacturer-consumer interactions. On the other hand, the textile industry faces numerous environmental and sustainability problems, from the massive consumption of water for cotton production, to half a million tons of microplastics and an estimated 11 million tons of textile waste landfilled annually in the US alone.
The course will outline underlying physical and engineering principles that are used in engineering and manufacturing of fibers and textiles. These include fundamentals of polymer science, mechanical, thermal, and moisture transport engineering of fibrous media, visual color science and engineering, and friction and wear of polymer and composite fibrous materials. The students will practice analyzing how the material and structure of woven, knitted, and nonwoven textiles translates into their strength, stretchability, abrasion resistance, visible color and reflectance, passive cooling or heating, and anti-microbial and self-cleaning properties.
The students will study and analyze real-life examples including different commercial and specialty textiles and will learn to use the life cycle assessment analysis to identify and prioritize the materials, processes, and designs that have the greatest potential for the reduction the environmental impact of the textile and garment production. They will also study examples of textile/garment-related patent applications and will practice drafting applications for their design ideas.
The course will include guest lectures and discussions with mentors from industry, military, and academia currently working on the development of smart fibers, fabrics and garments. Students will be offered support from the MechE Communication Lab for the final project preparation.
For the final class project, the student will either analyze and improve an existing garment/textile design or will develop a new one to address the challenges proposed by the instructor in collaboration with the textile/design industry experts.
Expected learning outcomes: After taking this subject, students should be able to:
- List common uses of fibers and textiles in wearables, architecture, and industry, and give examples
- Describe how fibers and fabrics are manufactured and the implications of using alternative materials, form factors, and structural arrangements
- Analyze function and performance and compare different types of fibers and fiber-based materials
- Understand the fundamentals of visible color formation, name and compare industrial techniques of textiles coloring and reflectance engineering
- Understand and compare different mechanisms of passive thermoregulation provided by textiles
- List and explain different textile industry standards of fibers/textiles testing
- Select a material and a fabric composition for a specific use based on the customer-provided information
- Perform lifecycle assessment analysis of different textile-based products
- Determine customer needs, brainstorm, sketch model, develop and refine designs of wearable garments and other textile-based materials
- Present data in appropriate graphical formats
- Communicate a design and its analysis (written, oral, and graphical forms)
- Basic characteristics of fibers and yarns
- Textile terminology and units
- Types and properties of ‘natural’ fibers and fabrics
- Synthetic fiber production: intro to polymer science
- Fiber extrusion techniques
- Textile pattern construction: weaving & knitting
- Color formation, different dyeing techniques, active coloring
- Heat and moisture transport engineering in textiles
- Textile industry and sustainability
- Microplastic pollution
- Smart and specialty textiles
Recommended: 2.00 Intro to Design; 2.001: Mechanics & Materials; 2.051: Intro to Heat Transfer
Evaluation: Class discussions 10%, Homework 30%, Exploratory projects & class presentations 30%, Final design project 30%
Metamaterials: fundamentals, design & applications
MIT Course Number: 2.S987
Lectures: Tue-Thu 1:00PM - 2:30PM (Online)
Instructors: Dr. Svetlana V. Boriskina & Prof. Nick Fang
Level: graduate, 12 units: 4-0-8 (undergrads are allowed to enroll)
Description: Photonic crystals, metamaterials, metasurfaces, and other types of artificial composite media can be engineered to display physical properties mimicking and often surpassing those available in natural materials. The concept of a metamaterial has been originally proposed to tailor electromagnetic and optical response of structures, and has since been extended to tailor elastic, acoustic, and thermal properties. The students will learn what new optical and thermal properties can be engineered in complex media structured on the sub-wavelength scale under different global symmetry conditions. They will also learn to connect the local field features to the global field distributions, engineer energy powerflow patterns, and manipulate the photonic density of states through bandstructure engineering.
Through historical examples, it will be revealed how an object can absorb more light than is incident on it, how evanescent waves can carry energy, whether there are such things as quasi-crystals or only quasi-scientists, and why some researchers initially had a negative reaction to the negative refraction. Through a partially-flipped classroom instructional strategy, the students will get to practice some of the new concepts via numerical modeling and visualization prior to formal learning of the fundamentals in class.
Additional Resources: Free access to the Lumerical software package will be provided to the enrolled students for the duration of the course courtesy of Lumerical. Students should bring their laptop computers to every class to fully participate. To promote understanding, the students will be running simple scripts visualizing the physical phenomena discussed in the lecture materials, starting from the very first class. Github resource will be used for sharing design ideas and scripts.
Course learning objectives and expected outcomes: The students will learn basic fundamental concepts underlying physical properties of both, natural photonic materials and metamaterials, including effective permittivity and permeability, origin of wavelength dispersion, optical losses, and optical magnetism, and the role that different types of symmetry and symmetry breaking play in defining the [meta]-material properties. They will be able to read and construct the photonic band structures of photonic metamaterials and will recognize the role the photonic band structure and dissipative losses play in sculpting the material interaction with embedded sources and propagating fields. This fundamental understanding will lay the foundation to identifying the opportunities and limitations of photonic metamaterial engineering for a variety of emerging applications and will promote understanding of similar concepts in solid state physics and mechanics. The students will learn and practice using the transfer-matrix and FDTD-based simulation tools to design, analyze, and visualize different regimes of light manipulation by metamaterials and metasurfaces.
18.02 Calculus, 8.02 Physics II or 6.013 Electromagnetics and Applications, and 18.03 Differential Equations
Recommended: 2.71/2.710 Optics, 2.096J Introduction to Numerical Simulation, 2.097J Numerical Methods for Partial Differential Equations.
Assignments: There will be 6 homeworks (30%), 6 online quizzes (15%), 1 team project (20%), and one individual final design project (35%).
Team Project deliverables: 20 minute presentation, all workgroup members must speak. During the next class, submit corrected slides
Final Project deliverables: Project proposal (1-2 pages) describing a metamaterial or a metamaterial-based device, its application/impact & design strategY + 15 minute presentation and a project report.
The final class projects will focus on studying and presenting a design of a photonic metamaterial or a metamaterial-/ composite-media based device, describing the physics behind its operation and application areas. Metamaterial examples from the literature will be provided by the instructor. Because metamaterial design often looks like an arts project, each final project should include an image, a video or [optionally] a physical model (3D printed, woven, knitted, etc) to provide a visual intro to the metamaterial of choice. Faculty will be invited to listen and comment on the projects, and the department members will be invited to vote to pick the favorite metamaterial art entry to be awarded a Science&Art prize.
PHOTONIC BIO(CHEMICAL) SENSORS
MIT Course Number: 2.S983
Instructor: Dr. Svetlana V. Boriskina
Level: Graduate, 12 units, 4-0-8 (undergrads are welcome to enroll, no prior experience in numerical modeling is required).
Schedule: Lectures: Tue & Thu 1pm-2:30pm ET, online
Bio(chemical) sensors play an outsized role in medical care, biological research, drug development, national security, and environmental monitoring, as exemplified by the current need for SARS-CoV-2 virus detection. Photonic biosensors use optical and plasmonic resonances to amplify biological signals associated with biological or chemical markers, and offer high-sensitivity detection, real-time readout, and scalable low-cost fabrication. The course will outline underlying physical and engineering principles that are used in photonic sensors to detect DNA molecules, proteins, and atmospheric/marine pollutants. These include fundamentals of light trapping and guiding, surface-polariton-mediated electromagnetic field enhancement, sensor surface functionalization, linear and non-linear light-matter interactions, refractometric sensing, fluorescence and Raman spectroscopy.
The students will study and analyze commercial photonic biosensor systems, and will design novel sensor configurations in the context of SARS-CoV-2 virus detection and microplastic pollution monitoring. The students will also learn and practice the general principles of data sampling, statistical analysis and presentation of data acquired by biosensors.
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