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21 - 30 of 32 results for: MATSCI

MATSCI 251: Microstructure and Mechanical Properties (MATSCI 151)

Primarily for students without a materials background. Mechanical properties and their dependence on microstructure in a range of engineering materials. Elementary deformation and fracture concepts, strengthening and toughening strategies in metals and ceramics. Topics: dislocation theory, mechanisms of hardening and toughening, fracture, fatigue, and high-temperature creep. Undergraduates register in 151 for 4 units; graduates register for 251 in 3 units.
Terms: Aut | Units: 3-4

MATSCI 299: Practical Training

Educational opportunities in high-technology research and development labs in industry. Qualified graduate students engage in internship work and integrate that work into their academic program. Following the internship, students complete a research report outlining their work activity, problems investigated, key results, and any follow-on projects they expect to perform. Student is responsible for arranging own employment. See department student services manager before enrolling.nn*If you do not see your faculty's name listed, please email msestudentservices@stanford.edu the faculty name and the quarter you plan to take the course. The system can take 24-48 update for your faculty name to appear in the list below.
Terms: Aut, Win, Spr, Sum | Units: 1 | Repeatable for credit

MATSCI 300: Ph.D. Research

Participation in a research project.
Terms: Aut, Win, Spr, Sum | Units: 1-15 | Repeatable for credit
Instructors: Appel, E. (PI) ; Baccus, S. (PI) ; Bao, Z. (PI) ; Beasley, M. (PI) ; Bent, S. (PI) ; Block, S. (PI) ; Boxer, S. (PI) ; Brongersma, M. (PI) ; Caers, J. (PI) ; Cai, W. (PI) ; Cargnello, M. (PI) ; Chang, F. (PI) ; Chaudhuri, O. (PI) ; Chidsey, C. (PI) ; Cho, K. (PI) ; Chowdhury, S. (PI) ; Chueh, W. (PI) ; Clemens, B. (PI) ; Congreve, D. (PI) ; Cui, Y. (PI) ; Dai, H. (PI) ; Dauskardt, R. (PI) ; DeSimone, J. (PI) ; Devereaux, T. (PI) ; Dionne, J. (PI) ; Dresselhaus-Marais, L. (PI) ; Dunne, M. (PI) ; Fan, J. (PI) ; Feigelson, R. (PI) ; Fisher, I. (PI) ; Frank, C. (PI) ; Goldhaber-Gordon, D. (PI) ; Goodson, K. (PI) ; Gu, W. (PI) ; Harris, J. (PI) ; Heilshorn, S. (PI) ; Heinz, T. (PI) ; Hesselink, L. (PI) ; Hong, G. (PI) ; Hwang, H. (PI) ; Jaramillo, T. (PI) ; Jornada, F. (PI) ; Kanan, M. (PI) ; Karunadasa, H. (PI) ; Keller, C. (PI) ; Lee, T. (PI) ; Lee, Y. (PI) ; Lindenberg, A. (PI) ; Liu, F. (PI) ; Mai, D. (PI) ; Mannix, A. (PI) ; Manoharan, H. (PI) ; Martinez, T. (PI) ; McGehee, M. (PI) ; McIntyre, P. (PI) ; Melosh, N. (PI) ; Mukherjee, K. (PI) ; Musgrave, C. (PI) ; Nanda, J. (PI) ; Nilsson, A. (PI) ; Nishi, Y. (PI) ; Nix, W. (PI) ; Noerskov, J. (PI) ; Onori, S. (PI) ; Palanker, D. (PI) ; Pianetta, P. (PI) ; Pinsky, P. (PI) ; Plummer, J. (PI) ; Pop, E. (PI) ; Prakash, M. (PI) ; Prinz, F. (PI) ; Qi, S. (PI) ; Qin, J. (PI) ; Salleo, A. (PI) ; Saraswat, K. (PI) ; Senesky, D. (PI) ; Sinclair, R. (PI) ; Soh, H. (PI) ; Spakowitz, A. (PI) ; Stebbins, J. (PI) ; Stohr, J. (PI) ; Suzuki, Y. (PI) ; Tang, S. (PI) ; Tarpeh, W. (PI) ; Toney, M. (PI) ; Wang, S. (PI) ; Wong, H. (PI) ; Xia, Y. (PI) ; Yang, F. (PI) ; Zhao, R. (PI) ; Zheng, X. (PI) ; Zia, R. (PI)

MATSCI 331: Computational Materials Science at the Atomic Scale

Introduction to computational materials science methods at the atomistic level, with an emphasis on quantum methods. A brief history of computational approaches is presented, with deep dives into the most impactful methods: density functional theory, tight-binding, empirical potentials, and machine learning-based property prediction. Computation of optical, electronic, phonon properties. Bulk materials, interfaces, nanostructures. Molecular dynamics. Prerequisites - undergraduate quantum mechanics. Experience writing code is preferred but not required.
Terms: Aut | Units: 3

MATSCI 333: Soft Composites and Soft Robotics (ME 303)

Fundamentals of soft materials and soft composites in the aspects of mechanical characterization, polymer physics, mechanics, finite-element-analysis of large deformation, and advanced material fabrication including different 3D printing technologies. Stimuli-responsive soft composites for soft robotics and shape-morphing structures will be introduced. Examples such as material systems that respond to magnetic field, electrical field, pneumatic pressure, light, and heat will be discussed. Prerequisites: ME80
Terms: Aut | Units: 3

MATSCI 346: Nanophotonics (EE 336)

Recent developments in micro- and nanophotonic materials and devices. Basic concepts of photonic crystals. Integrated photonic circuits. Photonic crystal fibers. Superprism effects. Optical properties of metallic nanostructures. Sub-wavelength phenomena and plasmonic excitations. Meta-materials. Prerequisite: Electromagnetic theory at the level of 242.
Terms: Aut | Units: 3

MATSCI 384: Materials Advances in Neurotechnology

The dichotomy between materials and the mind has inspired scientists to explore the wonders of the brain with novel materials-enabled neurotechnologies. The development of neurotechnologies can be dated back to the late 18th century when Galvani used an iron-and-bronze arch to stimulate the sciatic nerve and evoke motor output in a dead frog. Modern neurotechnologies capitalize on the semiconductor industry's trend towards miniaturization, reading the activity of thousands of neurons simultaneously in the brains of mice, rats, monkeys, and even humans. All these capabilities would not be possible without the advances in materials science. This course introduces the basic principles of materials design and fabrication for probing the inner workings of the brain, discusses the fundamental challenges of state-of-the-art neurotechnologies, and explores the latest breakthroughs in materials-assisted neuroengineering. The course will cover the following topics: overview of the nervous system more »
The dichotomy between materials and the mind has inspired scientists to explore the wonders of the brain with novel materials-enabled neurotechnologies. The development of neurotechnologies can be dated back to the late 18th century when Galvani used an iron-and-bronze arch to stimulate the sciatic nerve and evoke motor output in a dead frog. Modern neurotechnologies capitalize on the semiconductor industry's trend towards miniaturization, reading the activity of thousands of neurons simultaneously in the brains of mice, rats, monkeys, and even humans. All these capabilities would not be possible without the advances in materials science. This course introduces the basic principles of materials design and fabrication for probing the inner workings of the brain, discusses the fundamental challenges of state-of-the-art neurotechnologies, and explores the latest breakthroughs in materials-assisted neuroengineering. The course will cover the following topics: overview of the nervous system from an engineering perspective; mechanical and biochemical requirements of neural interfacing materials; materials for electrical, magnetic, optical, biochemical, thermal, and acoustic neural interfaces; materials as contrast agents for neuroimaging; and ethical considerations for emerging neurotechnologies. Students will acquire literacy in both materials science and neuroengineering and gain the knowledge and skills to understand and address pressing neuroscience challenges with materials advances. nnPrerequisite: undergraduate physics and chemistry; MATSCI 152, 158, 164, 190 or equivalents are recommended but not required prior to taking this course.
Terms: Aut | Units: 3

MATSCI 399: Graduate Independent Study

Under supervision of a faculty member.
Terms: Aut, Win, Spr, Sum | Units: 1-10 | Repeatable for credit

MATSCI 400: Participation in Materials Science Teaching

May be repeated for credit.
Terms: Aut, Win, Spr | Units: 1-3 | Repeatable for credit

MATSCI 405: Quantum Field Theory (QFT) for Engineering Applications (ME 403)

QFT principles for engineering applications in nano and microelectronics. Examples include quantum computing, topological quantum computing, and superconductivity. Focus on solids and quasiparticles. Relation between energy, momentum, and mass. Quantization, Klein Gordon, Dirac, Pauli, and Schrödinger equation. Introduction to topological states and the Majorana condition. Lagrange invariance and the need for gauge fields (electrodynamics).
Terms: Aut | Units: 3
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