DOCSLIB.ORG

Chemical Engineering

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Chemical Engineering INDEX j Graduate Education Advertisements Akron, University of ..........................................................274 Missouri, Columbia; University of .................................... 321 Alabama, University of .....................................................275 Missouri S&T .................................................................... 322 Alberta, University of ........................................................276 Montana State University .................................................. 371 Arizona, University of ........................................................277 Nevada, Reno; University of ............................................. 371 Arizona State University ....................................................278 New Hampshire, University of .......................................... 376 Arkansas, University of ......................................................279 New Jersey Institute of Technology .................................. 323 Auburn University ..............................................................280 New Mexico, University of ............................................... 324 Brigham Young University .................................................367 New Mexico State University ........................................... 325 British Columbia, University of .........................................281 North Carolina State University ........................................ 326 Brown University ...............................................................375 Northwestern University ................................................... 327 Bucknell..............................................................................367 Notre Dame, University of ................................................ 303 Calgary, University of ........................................................282 Ohio State University ........................................................ 328 California, Berkeley; University of ....................................283 Oklahoma, University of ................................................... 329 California, Los Angeles; University of...............................284 Oklahoma State University .............................................. 330 California, Riverside; University of ...................................285 Oregon State University .................................................... 331 California, Santa Barbara; University of ............................286 Pennsylvania, University of .............................................. 332 Carnegie Mellon University ...............................................287 Pennsylvania State University ........................................... 333 Case Western Reserve University ......................................288 Polytechnic University ...................................................... 334 Cincinnati, University of ....................................................289 Princeton University .......................................................... 335 City College of New York ..................................................290 Purdue University .............................................................. 336 Clarkson University ............................................................368 Rensselaer Polytechnic Institute ........................................ 337 Clemson University ............................................................291 Rhode Island, University of ............................................... 372 Cleveland State University .................................................375 Rice University .................................................................. 338 Colorado, University of ......................................................292 Rochester, Chemical Program; University of .................... 339 Colorado State University ..................................................293 Rochester, Energy Program; University of ........................ 340 Colorado School of Mines ..................................................294 Rose-Hulman ..................................................................... 372 Columbia University ..........................................................295 Rowan University .............................................................. 341 Connecticut, University of .................................................296 Rutgers ............................................................................... 376 Dayton, University of .........................................................376 Ryerson .............................................................................. 342 Delaware, University of .....................................................297 Sherbrooke, University of ................................................. 343 Drexel University ...............................................................298 Singapore, National University of ..................................... 344 Florida, University of .........................................................299 South Alabama, University of ........................................... 345 Florida A&M/Florida State College of Engineering ................368 South Carolina, University of ............................................ 346 Florida Institute of Technology ..........................................300 South Dakota School of Mines .......................................... 373 Georgia Institute of Technology .........................................301 State University of New York ............................................ 347 Houston, University of .......................................................302 Syracuse University ........................................................... 373 Idaho, University of ............................................................369 Tennessee, Knoxville; University of ................................. 348 Illinois, Urbana-Champaign; University of ... inside back cover Tennessee Technological University ................................. 349 Iowa, University of .............................................................304 Texas A&M University, College Station ........................... 350 Iowa State University ........................................................305 Texas A&M University, Kingsville ................................... 374 Kansas, University of .........................................................306 Texas Tech University ....................................................... 351 Kansas State University......................................................307 Toledo, University of ......................................................... 352 Kentucky, University of .....................................................308 Toronto, University of ....................................................... 353 Lamar University ................................................................369 Tufts University ................................................................. 354 Lehigh University ...............................................................309 Tulane University .............................................................. 355 Manhattan College .............................................................310 Tulsa, University of ........................................................... 356 Maryland, Baltimore County; University of ...................... 311 Vanderbilt University ........................................................ 357 Maryland, College Park; University of ..............................312 Villanova University .......................................................... 374 Massachusetts, Amherst; University of ..............................313 Virginia, University of ....................................................... 358 Massachusetts Institute of Technology ...............................314 Virginia Tech University ................................................... 359 McGill University...............................................................315 Washington, University of ................................................. 360 McMaster University ..........................................................316 Washington State University ............................................. 361 Miami University ...............................................................370 Waterloo, University of ..................................................... 362 Michigan, University of .....................................................317 West Virginia University ................................................... 363 Michigan State University ..................................................318 Western Michigan University ............................................ 375 Michigan Technological University ...................................370 Wisconsin, University of ................................................... 364 Minnesota, Minneapolis; University of ............................. 319 Worcester Polytechnic Institute ......................................... 365 Misissippi State University ............................................... 320 Yale University .................................................................. 366 Vol. 46, No. 4, Fall 2012 273 Graduate Education in Chemical and Biomolecular Engineering Teaching and research assistantships as well as industrially sponsored fellowships available. In addition to stipends, tuition and most fees are waived. • Castaneda: Electrochemistry & Corrosion, Corrosion
Load more

Recommended publications
  • Fulbright Scholars Directory
    FULBRIG HT SCHOLAR PROGRAM 2002-2003 Visiting Scholar Directory Directory of Visiting Fulbright Scholars and Occasional Lecturers V i s i t i n g F u l b r i g h t S c h o l a r P r o g r a m S t a f f To obtain U.S. contact information fo r a scholar listed in this directory, pleaseC IE S speaks ta ff member with the responsible fo r the scholar s home country. A fr ic a (S ub -S aharan ) T he M id d le E ast, N orth A frica and S outh A sia Debra Egan,Assistant Director Tracy Morrison,Senior Program Coordinator 202.686.6230 [email protected] 202.686.4013 [email protected] M ichelle Grant,Senior Program Coordinator Amy Rustic,Program Associate 202.686.4029 [email protected] 202.686.4022 [email protected] W estern H emisphere E ast A sia and the P acific Carol Robles,Senior Program Officer Susan McPeek,Senior Program Coordinator 202.686.6238 [email protected] 202.686.4020 [email protected] U.S.-Korea International Education Administrators ProgramMichelle Grant,Senior Program Coordinator 202.686.4029 [email protected] Am elia Saunders,Senior Program Associate 202.686.6233 [email protected] S pecial P rograms E urope and the N ew I ndependent S tates Micaela S. Iovine,Senior Program Officer 202.686.6253 [email protected] Sone Loh,Senior Program Coordinator New Century Scholars Program 202.686.4011 [email protected] Dana Hamilton,Senior Program Associate Erika Schmierer,Program Associate 202.686.6252 [email protected] 202.686.6255 [email protected] New Century Scholars
    [Show full text]
  • Quantum Optics with Giant Atoms – the First Five Years
    Quantum optics with giant atoms – the first five years Anton Frisk Kockum Abstract In quantum optics, it is common to assume that atoms can be approximated as point-like compared to the wavelength of the light they interact with. However, recent advances in experiments with artificial atoms built from superconducting circuits have shown that this assumption can be violated. Instead, these artificial atoms can couple to an electromagnetic field at multiple points, which are spaced wavelength distances apart. In this chapter, we present a survey of such systems, which we call giant atoms. The main novelty of giant atoms is that the multiple coupling points give rise to interference effects that are not present in quantum optics with ordinary, small atoms. We discuss both theoretical and experimental results for single and multiple giant atoms, and show how the interference effects can be used for interesting applications. We also give an outlook for this emerging field of quantum optics. Key words: Quantum optics, Giant atoms, Waveguide QED, Relaxation rate, Lamb shift, Superconducting qubits, Surface acoustic waves, Cold atoms 1 Introduction Natural atoms are so small (radius r ≈ 10−10 m) that they can be considered point- like when they interact with light at optical frequencies (wavelength λ ≈ 10−6 − 10−7 m)[1]. If the atoms are excited to high Rydberg states, they can reach larger sizes (r ≈ 10−8 − 10−7 m), but quantum-optics experiments with such atoms have them interact with microwave radiation, which has much longer wavelength (λ ≈ arXiv:1912.13012v1 [quant-ph] 30 Dec 2019 10−2 −10−1 m)[2].
    [Show full text]
  • Merging Photonics and Artificial Intelligence at the Nanoscale
    Intelligent Nanophotonics: Merging Photonics and Artificial Intelligence at the Nanoscale Kan Yao1,2, Rohit Unni2 and Yuebing Zheng1,2,* 1Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA 2Texas Materials Institute, The University of Texas at Austin, Austin, Texas 78712, USA *Corresponding author: [email protected] Abstract: Nanophotonics has been an active research field over the past two decades, triggered by the rising interests in exploring new physics and technologies with light at the nanoscale. As the demands of performance and integration level keep increasing, the design and optimization of nanophotonic devices become computationally expensive and time-inefficient. Advanced computational methods and artificial intelligence, especially its subfield of machine learning, have led to revolutionary development in many applications, such as web searches, computer vision, and speech/image recognition. The complex models and algorithms help to exploit the enormous parameter space in a highly efficient way. In this review, we summarize the recent advances on the emerging field where nanophotonics and machine learning blend. We provide an overview of different computational methods, with the focus on deep learning, for the nanophotonic inverse design. The implementation of deep neural networks with photonic platforms is also discussed. This review aims at sketching an illustration of the nanophotonic design with machine learning and giving a perspective on the future tasks. Keywords: deep learning; (nano)photonic neural networks; inverse design; optimization. 1. Introduction Nanophotonics studies light and its interactions with matters at the nanoscale [1]. Over the past decades, it has received rapidly growing interest and become an active research field that involves both fundamental studies and numerous applications [2,3].
    [Show full text]
  • Up-And-Coming Physical Concepts of Wireless Power Transfer
    Up-And-Coming Physical Concepts of Wireless Power Transfer Mingzhao Song1,2 *, Prasad Jayathurathnage3, Esmaeel Zanganeh1, Mariia Krasikova1, Pavel Smirnov1, Pavel Belov1, Polina Kapitanova1, Constantin Simovski1,3, Sergei Tretyakov3, and Alex Krasnok4 * 1School of Physics and Engineering, ITMO University, 197101, Saint Petersburg, Russia 2College of Information and Communication Engineering, Harbin Engineering University, 150001 Harbin, China 3Department of Electronics and Nanoengineering, Aalto University, P.O. Box 15500, FI-00076 Aalto, Finland 4Photonics Initiative, Advanced Science Research Center, City University of New York, NY 10031, USA *e-mail: [email protected], [email protected] Abstract The rapid development of chargeable devices has caused a great deal of interest in efficient and stable wireless power transfer (WPT) solutions. Most conventional WPT technologies exploit outdated electromagnetic field control methods proposed in the 20th century, wherein some essential parameters are sacrificed in favour of the other ones (efficiency vs. stability), making available WPT systems far from the optimal ones. Over the last few years, the development of novel approaches to electromagnetic field manipulation has enabled many up-and-coming technologies holding great promises for advanced WPT. Examples include coherent perfect absorption, exceptional points in non-Hermitian systems, non-radiating states and anapoles, advanced artificial materials and metastructures. This work overviews the recent achievements in novel physical effects and materials for advanced WPT. We provide a consistent analysis of existing technologies, their pros and cons, and attempt to envision possible perspectives. 1 Wireless power transfer (WPT), i.e., the transmission of electromagnetic energy without physical connectors such as wires or waveguides, is a rapidly developing technology increasingly being introduced into modern life, motivated by the exponential growth in demand for fast and efficient wireless charging of battery-powered devices.
    [Show full text]
  • DNA Nanotechnology Meets Nanophotonics
    DNA nanotechnology meets nanophotonics Na Liu 2nd Physics Institute, University of Stuttgart, Pfaffenwaldring 57, 70569 Stuttgart, Germany Max Planck Institute for Solid State Research, Heisenbergstrasse 1, 70569 Stuttgart, Germany Email: [email protected] Key words: DNA nanotechnology, nanophotonics, DNA origami, light matter interactions Call-out sentence: It will be very constructive, if more research funds become available to support young researchers with bold ideas and meanwhile allow for failures and contingent outcomes. The first time I heard the two terms ‘DNA nanotechnology’ and ‘nanophotonics’ mentioned together was from Paul Alivisatos, who delivered the Max Planck Lecture in Stuttgart, Germany, on a hot summer day in 2008. In his lecture, Paul showed how a plasmon ruler containing two metallic nanoparticles linked by a DNA strand could be used to monitor nanoscale distance changes and even the kinetics of single DNA hybridization events in real time, readily correlating nanoscale motion with optical feedback.1 Until this day, I still vividly remember my astonishment by the power and beauty of these two nanosciences, when rigorously combined together. In the past decades, DNA has been intensely studied and exploited in different research areas of nanoscience and nanotechnology. At first glance, DNA-based nanophotonics seems to deviate quite far from the original goal of Nadrian Seeman, the founder of DNA nanotechnology, who hoped to organize biological entities using DNA in high-resolution crystals. As a matter of fact, DNA-based nanophotonics does closely follow his central spirit. That is, apart from being a genetic material for inheritance, DNA is also an ideal material for building molecular devices.
    [Show full text]
  • Inverse Design for Silicon Photonics: from Iterative Optimization Algorithms to Deep Neural Networks
    applied sciences Review Inverse Design for Silicon Photonics: From Iterative Optimization Algorithms to Deep Neural Networks Simei Mao 1,2, Lirong Cheng 1,2 , Caiyue Zhao 1,2, Faisal Nadeem Khan 2, Qian Li 3 and H. Y. Fu 1,2,* 1 Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, China; [email protected] (S.M.); [email protected] (L.C.); [email protected] (C.Z.) 2 Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; [email protected] 3 School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China; [email protected] * Correspondence: [email protected]; Tel.: +86-755-3688-1498 Abstract: Silicon photonics is a low-cost and versatile platform for various applications. For design of silicon photonic devices, the light-material interaction within its complex subwavelength geometry is difficult to investigate analytically and therefore numerical simulations are majorly adopted. To make the design process more time-efficient and to improve the device performance to its physical limits, various methods have been proposed over the past few years to manipulate the geometries of silicon platform for specific applications. In this review paper, we summarize the design methodologies for silicon photonics including iterative optimization algorithms and deep neural networks. In case of iterative optimization methods, we discuss them in different scenarios in the sequence of increased degrees of freedom: empirical structure, QR-code like structure and irregular structure. We also review inverse design approaches assisted by deep neural networks, which generate multiple devices Citation: Mao, S.; Cheng, L.; Zhao, with similar structure much faster than iterative optimization methods and are thus suitable in C.; Khan, F.N.; Li, Q.; Fu, H.Y.
    [Show full text]
  • Wirelessly-Powered Cage Designs for Supporting Long-Term Experiments on Small Freely Behaving Animals in a Large Experimental Arena
    electronics Review Wirelessly-Powered Cage Designs for Supporting Long-Term Experiments on Small Freely Behaving Animals in a Large Experimental Arena Byunghun Lee 1 and Yaoyao Jia 2,* 1 Department of Electrical Engineering, Incheon National University, Incheon 22012, Korea; [email protected] 2 Department of Electrical and Computer Engineering, North Carolina State University, 890 Oval Dr, Raleigh, NC 27606, USA * Correspondence: [email protected]; Tel.: +1-919-515-7350 Received: 22 October 2020; Accepted: 18 November 2020; Published: 25 November 2020 Abstract: In modern implantable medical devices (IMDs), wireless power transmission (WPT) between inside and outside of the animal body is essential to power the IMD. Unlike conventional WPT, which transmits the wireless power only between fixed Tx and Rx coils, the wirelessly-powered cage system can wirelessly power the IMD implanted in a small animal subject while the animal freely moves inside the cage during the experiment. A few wirelessly-powered cage systems have been developed to either directly power the IMD or recharge batteries during the experiment. Since these systems adapted different power carrier frequencies, coil configurations, subject tracking techniques, and wireless powered area, it is important for designers to select suitable wirelessly-powered cage designs, considering the practical limitations in wirelessly powering the IMD, such as power transfer efficiency (PTE), power delivered to load (PDL), closed-loop power control (CLPC), scalability, spatial/angular misalignment, near-field data telemetry, and safety issues against various perturbations during the longitudinal animal experiment. In this article, we review the trend of state-of-the-art wirelessly-powered cage designs and practical considerations of relevant technologies for various IMD applications.
    [Show full text]
  • NANOPHOTONICS a FORWARD LOOK NANOPHOTONICS Association a FORWARD LOOK
    association NANOPHOTONICS A FORWARD LOOK NANOPHOTONICS association A FORWARD LOOK Report Editors Gonçal Badenes, ICFO Stewe Bekk, ICFO Martin Goodwin, 2020 Insights DESIGN Sergio Simón Petreñas D.L. B-29170-2012 (Printed version) B-29171-2012 (Electronic version) © 2012 NEA. The text of this publication may be reproduced provided the source is acknowledged. Reproduction for commercial use without prior permission is prohibited. PICTURES © reserved by original copyright holder. Reproduction of the artistic material contained therein is prohibited The Nanophotonics Europe Association is partially funded by the Spanish Ministry of Economy and Competitiveness through grant ACI-2009-1013 NANOPHOTONICS association A FORWARD LOOK About this Report This document is the report of the Nanophotonics Europe Association workshop held at King's College, London (UK) in July 2012. The purpose was to define a strategy for advancing research and development of nanophotonics. The views, ideas, conclusions and recommendations presented in this report are those of the workshop participants. Nanophotonics Europe Association The Nanophotonics Europe Association (NEA) is a not-for-profit organisation created to promote and advance European science and technology in the emerging area of nanophotonics. The goals of the association are fourfold: 1. To promote research in nanophotonics by coordinating the efforts of the various players involved, and, in particular, by encouraging collaboration between academic institution and industry. 2. To create a common interest group that represents member’s interests with national and transnational scientific government funding agencies, technology platforms, professional associations and the general public. 3. To integrate the resources and strategies of its members. 4. To facilitate the exchange of information, ideas and data.
    [Show full text]
  • Advanced Trends of Nanophotonics
    Part VII Advanced Trends of Nanophotonics Wei Ting Chen and Din Ping Tsai Introduction Nanophotonics is the study of the behavior of light-matter interaction at the nanometer scale. By adding the dimensions of optical devices and components to sub-wavelength scale, nanophotonics provides new opportunities for fundamen- tal science and practical applications. One of the goals of nanophotonics devel- opment is to manipulate light at the nanoscale, which may not be limited by the chemical composition of natural materials and the diffraction limit of electromag- netic wave. Nanophotonics has several advantages with such diffraction-unlimited properties for functional applications: (i) nanoscale footprints-smaller compo- nents and devices; (ii) photon-electron process in nanoscale—faster processing speed, and (iii) nanoscale confinement of optical radiation and electromagnetic fields—enhancing the light-matter interactions and dramatically reducing the optical energy consumption. The characterization of drastic optical localization within such components strongly enhances the typically weak interaction between light and matter, which increases the energy efficiency to obtain desired effects and phenomena. This chapter covers two major parts of the latest trends of nano- photonics, plasmonics, and metamaterials. Several cutting-edge approaches har- vested from the extraordinary properties of nanophotonics, which are conducted to advanced trends relate to: Micro/nano-lasers with the smallest plasmonic nano- laser, theoretical models of the micro/nano-cavity, and semiconductor micro-lasers with tuning functions on a flexible substrate (Chap. 16, 17 and 19), nanostructures light-emitting diode (LED) with better light extraction and reduced piezoelectric field induced by strain (Chap.18 , 24), one-dimensional photonic crystal nanowires with small footprints and ultrahigh Q-factors (Chap.
    [Show full text]
  • Prof. Michael Tsapatsis University of Minnesota Department of Chemical Engineering & Materials Science
    e CHEMICAL ENGINEERING Ch UC SANTA BARBARA TM CHEMICAL ENGINEERING 290 SEMINAR SERIES PRESENTS Prof. Michael Tsapatsis University of Minnesota Department of Chemical Engineering & Materials Science 4pm - Tuesday, February 9th 2016 in ENGR II room 1519 2-dimensional zeolites for catalysis and separations It is only recently that single-unit-cell thick zeolite nanosheets (2-dimensional zeolites; AIChE Journal 60(7), 2374-2381 (2014) ) with intact crystal and micropore structure were shown to be possible. The structural integrity and unprecedented purity and uniformity of these microporous nanosheets, open exciting possibilities for technological breakthroughs in molecular sieve membrane fabrication, synthesis of hierarchical catalysts and polymer-zeolite nanocomposites. Moreover, zeolite nanosheets enable for the first time zeolite pore mouth adsorption and catalysis to be studied by traditional uptake methods as well as surface science techniques. However, along with the exciting possibilities, challenges abound. For example, the in-plane dimensions of the existing nanosheets are in the sub-micrometer range limiting potential applications and processability as thin films. Moreover, the two exfoliated zeolites currently available are only a small fraction of zeolite topologies one would like to have available for a representative set. Earlier attempts to exfoliate other layered zeolites, including certain layered silicates and aluminophosphates with microporous layers, did not preserve the crystallographic order of the layers. Synthesis of high aspect ratio zeolite and other crystalline nanoporous nanosheets, methods to characterize their structure and properties, along with their processing and assembly to create membranes and catalysts will be the focus of this talk. Michael Tsapatsis joined the Department of Chemical Engineering and Materials Science at the University of Minnesota in September 2003 as a professor and he currently holds the Amundson Chair.
    [Show full text]
  • Recent Trends in Micro- and Nanophotonics: a Personal Selection
    JOURNAL OF OPTOELECTRONICS AND ADVANCED MATERIALS Vol. 13, No. 9, September 2011, p. 1055 - 1066 Recent trends in micro- and nanophotonics: A personal selection D. MIHALACHE Horia Hulubei National Institute for Physics and Nuclear Engineering, P. O. B. MG-6, 077125 Magurele, Romania I give a brief overview of some recent results in micro- and nanophotonics. Due to the vast amount of research activity in these exploding areas I only concentrate on selected recent advances in (a) silicon photonics, (b) spatial and spatiotemporal optical solitons (alias light bullets) in microwaveguide arrays and in arrays of evanescently-coupled silicon- on-insulator nanowires, (c) spatial solitons in photorefractive materials, (d) nanoplasmonics, (e) photonic crystals, (f) metamaterials for micro- and nanophotonics including optical materials with negative refractive indices, (g) terahertz radiation and its applications, and (h) solid-state single photon sources and nanometric size optical cavities for quantum information processing. (Received August 12, 2011; accepted September 15, 2011) Keywords: Microphotonics, Nanophotonics, Silicon photonics, Plasmonics, Photonic crystals, Spatial optical solitons, Light bullets, Plasmonic lattice solitons, Metamaterials, Terahertz radiation 1. Introduction for biosensing and chemical sensing applications, ability of metal nanoparticles to act as efficient pointlike sources The term “photonics” was coined in 1967 by Pierre of both light and heat, and subwavelength plasmonic Aigrain, a French scientist, who gave the following lattice solitons in arrays of metallic nanowires embedded definition: “Photonics is the science of the harnessing of in nonlinear Kerr media will be briefly discussed. light. Photonics encompasses the generation of light, the Section 4 is devoted to recent advances in the study of detection of light, the management of light through photonic crystals and metamaterial structures (including guidance, manipulation, and amplification, and most engineered media with negative refractive indices).
    [Show full text]
  • From Classical Optics to Nanophotonics
    FEATURES FROM CLASSICAL OPTICS TO NANOPHOTONICS 1 1 1 2 l François Flory , Ludovic Escoubas , Judikael¨ Le Rouzo , Gerard´ Berginc – DOI: https://doi.org/10.1051/ epn/2018503 l IM2NP – Faculte´ des Sciences et Techniques – Avenue Escadrille Normandie Niemen, Service 262 – 13397 Marseille cedex, France l THALES Optronique SA – 2 avenue Gay-Lussac – 78990 Elancourt, France Nanophotonics is a very large and rich young field experienting a very rapid development worldwide. It is based on the study of light/matter interaction at low dimension. Several books are dedicated to different aspects of nanophotonics [1]. FIG 1: long list of philosophers/scientists allowed (1000 A.D.) described light propagation, till 13th cen- (a) SEM image understanding the nature of light and of its tury Italian glassworkers made lenses that were used of Black Silicon surface obtained by interaction with matter, the development for spectacles. Kepler (1604) decribed the propagation cryogenic process. Aof optical instruments and of lasers. We of light through lenses with geometrical optics, and he (b) Cryogenic plasma can briefly cited some of them who are known to bring applied his studies to the eye. Lippershey invented the process black silicon reflectivity compared important steps in these progresses. By trying to explain telescope soon before Galileo (1609) produced his own with unprocessed vision, Greek like Euclid (300 B.C.), Hero (60 A.D.), telescope and started to study planets and moons. Snell, silicon. [10] Ptolemy (120 A. D.) and then the Arab scientist Alhazen Descartes(~1637), Newton (~1704) , Grimaldi (~1665), Huygens (~1690), Euler (1746), Gauss (~1800), Young (1803), Fraunhofer(1814), Fresnel (1819) , Abbe (1887)..
    [Show full text]