The document summarizes the betatron, a device that accelerates electrons to high energies. It works on the principle of transformer induction, where a changing magnetic field induces an electric field that accelerates electrons in a circular path. The betatron consists of an evacuated doughnut chamber with electromagnets that produce an increasing magnetic field. This causes an induced electric field to accelerate electrons injected from a cathode, keeping them moving in a constant radius orbit through magnetic force balance. The maximum energy electrons attain is directly proportional to the strongest magnetic field achieved.
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DOWNLOAD THE POWERPOINT FILE FROM HERE:
https://www.dropbox.com/s/d8zbqyvc81pgg5w/compton%20effect.pptx?dl=0
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DOWNLOAD THE POWERPOINT FILE FROM HERE:
https://www.dropbox.com/s/d8zbqyvc81pgg5w/compton%20effect.pptx?dl=0
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brief but informative knowledge about what basically LINAC is and what is the phenomenon behind this machine ... easy to understand as well as presenting during lectures and in classes . share it
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The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
1. R.SUYA PADHRA HARIDHA
ASSISTANT PROFESSOR
DEPARTMENT OF PHYSICS
A.P.C.MAHALAXMI COLLEGE FOR WOMEN
THOOTHUKUDI, TAMILNADU
Betatron
2. Betatron is a device used to accelerate electrons/beta
particles to very high energies.
It was developed by Donald William Kerst
3. Principle
It is same as that of the transformer. In transformer,
if an alternating current is passed through the
primary coil an alternating magnetic field will appear
in the coil. This field produces an induced e.m.f. in
the secondary coil. Similarly the changing magnetic
flux induces an e.m.f. tangentially along a circular
path for the electron which accelerates the electrons
to high energies. The electrons is kept accelerating in
circular path of constant radius with the help of
increasing magnetic field.
4. Construction
The Betatron consists of an evacuated doughnut
chamber in which electrons are produced by
indirectly heated cathode.
The doughnut tube is placed between two strong
electromagnet such that, when the a.c current is
passed in the electromagnets the flux increases in the
centre of doughnut (single coil).
5.
6. Working
When the electron appears at K (cathode) in
doughnut tube and the electromagnets are energized
the magnetic field increases, the increasing magnetic
field has two effects
(i) Induced e.m.f. is produced in electron orbit by
changing magnetic flux that gives an additional
energy to electron. According to Faraday’s law
induced e.m.f. E= - dφ/dt
7. (ii) A radial force (magnetic force) is produced by
action of magnetic field whose direction is
perpendicular to the electron orbit, velocity which
keeps the electron moving in circular path. The
magnetic force is balanced by centripetal force,
qvB=mv2/r
8. Induced e.m.f in the coil from Faraday’s law of electromagnetic induction
E= dφ/dt (1)
Work done on an electron in one revolution
W = e.m.f. * charge of electron
W=e * dφ/dt (2)
Work done = tangential Force ‘F’ on electron x
distance traveled in one revolution
W=F* 2πr =e * dφ/dt
F=(e/ 2πr ) * dφ/dt (3)
The electron moves in circular path. The magnetic
force is balanced by centripetal force,
evB=mv2/r
9. eBr=mv=p (4)
From Newtons second law radial force
F=dp/dt = d(mv)/dt
F= d(eBr)/dt
In order to maintain path of constant radius (r is
const.)
F=er( dB/ dt) (5)
Equating equations (3) & (5)
F=er( dB/ dt)=(e/ 2πr ) * dφ/dt
10. dφ/dt = 2πr2 (dB/ dt ) (6)
Integrating the above equation
φ = 2πr2 B (7)
The relation is known as Betatron condition.
The electron moves in circular path of constant radius,
the magnetic flux within the orbit of radius R is always
twice what it would have been if magnetic field were
uniform throughout the orbit.
11. Energy gained by electron
The particles have maximum energy when the
magnetic field is at its strongest value but the formula
used for the cyclotron will not work for Betatron
because the electron motion is relativistic.
However, if the total energy is much greater than the
rest energy then
E=pc (8)
p=E/c
mv=E/c
E= mvc (9)
12. For electron in the stable orbit,
centripetal force = magnetic force,
The momentum of the electron will
eBr=mv=p (10)
hence Energy of the electron can be given by,
E=Berc (11)