This document outlines a study on ion energy distribution (IED) in multi-frequency capacitively coupled plasma. It presents analytical models for IED in triple frequency discharges and examines the effects of various plasma parameters on IED through simulations. The parameters investigated include operating pressure, ion density, RF current density, low frequency, and their effects on the mid-position and width of the IED. The study shows IED can be adjusted by choosing the appropriate fundamental frequency, pressure, and ion density for applications like plasma etching and deposition.
IOSR Journal of Applied Physics (IOSR-JAP) is an open access international journal that provides rapid publication (within a month) of articles in all areas of physics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in applied physics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IOSR Journal of Applied Physics (IOSR-JAP) is an open access international journal that provides rapid publication (within a month) of articles in all areas of physics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in applied physics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Frequency, wavelength and energy characteristics of the electromagnetic spectrum. The observed EM frequency spectrum spans more than 140 octaves or ~24 order of magnitude. The calculated Planck frequency of 2.952E42 Hz appears to represent an upper frequency cutoff limit of the vacuum.
CBSE NOTES; XII PHYSICS NOTES;BOARD NOTES;ELECTROMAGNETIC WAVES NOTES; PHYSICS NOTES FROM KOTA RAJASTAHN;
NOTES FROM KOTA COACHING;PHYSICS NOTES FROM AARAV CLASSES
Physics Sample Paper with General Instruction for Class - 12Learning Three Sixty
Learning 360 brings “Physics sample paper” for CLASS – 12. This document also carries 31 questions with solution of each given question for better understanding of the students. Download for free now; http://www.learning360.net/study_hub/1090-2/
Frequency, wavelength and energy characteristics of the electromagnetic spectrum. The observed EM frequency spectrum spans more than 140 octaves or ~24 order of magnitude. The calculated Planck frequency of 2.952E42 Hz appears to represent an upper frequency cutoff limit of the vacuum.
CBSE NOTES; XII PHYSICS NOTES;BOARD NOTES;ELECTROMAGNETIC WAVES NOTES; PHYSICS NOTES FROM KOTA RAJASTAHN;
NOTES FROM KOTA COACHING;PHYSICS NOTES FROM AARAV CLASSES
Physics Sample Paper with General Instruction for Class - 12Learning Three Sixty
Learning 360 brings “Physics sample paper” for CLASS – 12. This document also carries 31 questions with solution of each given question for better understanding of the students. Download for free now; http://www.learning360.net/study_hub/1090-2/
international workshop accelerator based neutron sources for medical industrial and scientific applications torino eurosea international workshop accelerator based neutron sources for medical industrial and scientific applications torino eurosea
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
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.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
5. DEBYE SHIELDING
The free charges in a
plasma will move in
response to any electric
field in such a way to
decrease
the Effect of the
field,Quasi-Neutrality.
7. SHEATH: NON-CONDUCTING SURFACE
•The electron flux to the wall will be
greater initially.
•Causing plasma become more
positive and developing an electric
field.
• Potential falls off from the wall into
the plasma over Debye length
8. SHEATH: CONDUCTING ELECTRODE
The potential on the electrode is negative
And large, attract ions and repel e-.
Ions crosses the sheath, strike the electrode
At x=Sm.
Current density J = eniui
Potential V(x) is given by the equation
12. • The cathode region
• Secondary electron generation
• Ionization of the cathode sheath
• Ion charge exchange in the
cathode sheath Ar+ + Ar = Ar +
Ar+
• The anode region , Vdrop= 3KT/e
• The negative glow region
• Beyond the negative glow
• The positive column
DC GLOW DISCHARGE
13. DC Glow Discharge
The negative glow region along with
the cathode and associated dark space
Comprise a SELF-SUSTAINING discharge
Configuration [24]
[24] S. M. Rossnagel , Jerome J. Cuomo , William D. Westwood Bell ,Handbook of plasma processing technology Fundamentals,
Etchin Deposition and Surface Interactions;Noyes Publications, Park Ridge, New Jersey, U.S.A. ,1990.
14. WHY CCP,IED ?
• CCP widely used in etching, thin film deposition and surface
treatment
• Better control over etch rates
15. MULTIPLE FREQUENCY OPERATION
Goto et al demonstrated
Independent control of the ion density and the ion bombardment energy by selecting
appropriate excitation frequencies in a dual RF excitation system
H. H. Goto, H.-D. Lowe, and T. Ohmi, J. Vac. Sci. Technol. A, vol.10, p. 3048, 1992.
18. TRIPLE FREQUENCY CAPACITIVE DISCHARGE
Current density across the sheath [21] ,
𝐽𝑟𝑓= 𝐽1cos(ω1 𝑡)+ 𝐽2cos(ω2 𝑡)+ 𝐽3cos(ω3 𝑡)
Instantaneous electron sheath edge expressed as a step like electron density
profile
Ion motiontime independent and collision less
Sheath in triple frequency capacitive discharge [21],
𝑠(𝑡) = 𝑠 − 𝑠1 sin ω1 𝑡 − 𝑠2 sin ω2 𝑡 − 𝑠3 sin ω3 𝑡
[21] S H Lee, Pawan K Tiwari, JK Lee. Plasma Sources Sci. Technol.18 (2009) 025024 (9pp)
19. IED
For single frequency, sheath potential[45]
𝑉𝑠 𝑥, 𝑡 = 𝑉𝑠 [1 + λ sin(ω𝑡)]
𝑥
𝑑
4
3
For triple frequency RF discharge similar equation
𝑉𝑠 𝑥, 𝑡 = 𝑉𝑠[1 + λ1 sin(ω1 𝑡)][1 + λ2 sin(ω2 𝑡)][1 + λ3 sin(ω3 𝑡)]
𝑥
𝑑
4
3
Electric field in the sheath region
𝐸𝑠 𝑥 = −
4𝑒 𝑉𝑠
3𝑑
[1 + λ1 sin(ω1 𝑡)][1 + λ2 sin(ω2 𝑡)][1 + λ3 sin(ω3 𝑡)]
𝑥
𝑑
4
3
[45] W J Goedheer, Plasma Sources Sci. Technol.9 (2000) 507–516
22. After differentiating and neglecting phase angles near 180 and 0
degree we get the distribution
𝑓 𝐸 =
𝑑𝑛
𝑑𝐸
=
𝑑𝑛
𝑑𝑡1
𝑑𝑡1
𝑑𝐸
=
Г
𝑑𝐸
𝑑𝑡1
=
Г
4𝑒 𝑉𝑠
3𝑑
2𝑒 𝑉𝑠
𝑀
λ2sin(ω2 𝑡)
=
2Г
ωΔ𝐸
1
1 − 𝑐𝑜𝑠2 ω2 𝑡 1/2
So ion energy distribution of triple frequency CCP is,
𝑓 𝐸 =
2Г
ωΔ𝐸
1 −
2
Δ𝐸
2
𝐸 − 𝑒 𝑉𝑠
2
IED
1
1
23. EFFECTIVE VOLTAGE METHOD
Sheath voltage
𝑉𝑠(𝑡)
𝑉𝑠(𝑓) 𝑉𝑖(𝑓)
𝑉𝑖(𝑡) IED
Fourier Transform
Filter
Inverse Fourier Transform
𝒅𝑽𝒊
𝒅𝒕
−𝟏
Filter transfer function, ∝ 𝒇 =
𝟏
((𝒄𝒇𝝉 𝒊) 𝒑+𝟏) 𝟏/𝒑
[16] M.A. Lieberman, Nano electronics And Plasma Processing-The Next 15 Years And Beyond
24. MODEL CONSIDERATION
IED Model:
•Analytical model proposed by S H Lee, Pawan K Tiwari, JKLee [21]
•Semi Analytical model proposed by Alan C. F. Wu, M. A. Lieberman, J.
P. Verboncoeur [16]
Plasma Sheath Model:
•Collisional Triple Frequency capacitively coupled plasma sheath
modeled by M. T. Rahman, M. N. A. Dewan, M. R. H. Chowdhury [3]
REF: [21] S H Lee, Pawan K Tiwari, JK Lee. Plasma Sources Sci. Technol.18 (2009) 025024 (9pp)
[16] Alan C. F. Wu, M. A. Lieberman, and J. P. Verboncoeur. In: J. Appl. Phys. 101 (2007),p. 056105.
[65] Rahman, M.T, Dewan, M.N.A.,Plasma Science, IEEE Transactions on (Volume:42, Issue: 3 ),p 729
25. SIMULATION RESULT
LF= 1MHz
α= 15
β= 50
Jlf = 10 Am-2
n0=2x1016 m-3
P=100mTorr
Normalized IED from JK LEE model
Normalized IED from Lieberman model
0 100 200 300 400 500 600 700 800 900 1000
0
0.5
1
1.5
2
2.5
x 10
-7
Energy in eV
NormalizedIED(1/eV)
20 25 30 35 40 45 50 55 60 65
0
0.5
1
1.5
2
2.5
3
3.5
Energy in eV
NormalizedIED(1/eV)
26. EFFECT OF PRESSURE ON IED
IED distribution for triple frequency driven CCP
0 50 100 150 200 250 300 350
0
0.5
1
1.5
2
2.5
3
3.5
Energy in eV
NormalizedIED(1/eV)
p=3mtorr
p=10mtorr
p=100mtorr
LF= 1MHz
α= 15
β= 50
Jlf = 10 Am-2
n0=2x1016 m-3
27. EFFECT OF PRESSURE ON IED
Mid Position of
Energy Band
(in eV)
Width of Energy
Band
(in eV)
1 mTorr 436.8617 127.8113
10 mTorr 138.1478 71.8736
20 mTorr 97.6852 60.4382
30 mTorr 79.7597 54.6121
40 mTorr 69.0739 50.8223
50 mTorr 61.7816 48.0648
100 mTorr 43.6862 40.4175
Parameters: LF= 1MHz, α= 15, β= 50, Jlf = 10 Am-2,
n0=2x1016 m-3
28. EFFECT OF ION DENSITY ON IED
LF= 1MHz
α= 15
β= 50
Jlf = 10 Am-2
n0=nx1016 m-3
P=10mTorr
IED distribution for triple frequency driven CCP
0 50 100 150 200 250 300 350 400
0
0.5
1
1.5
2
2.5
3
Energy in eV
NormalizedIED(1/eV)
n=1
n=2
n=5
29. EFFECT OF ION DENSITY ON IED
Mid Position of
Energy Band
(in eV)
Width of Energy
Band
(in eV)
2x1016 m-3 43.6862 40.4175
20x1016 m-3 4.3686 1.2781
40x1016 m-3 2.1843 0.4519
60x1016 m-3 1.4562 0.2460
80x1016 m-3 1.0922 0.1598
100x1016 m-3 0.8737 0.1143
200x1016 m-3 0.4369 0.0404
Parameters: LF= 1MHz, α= 15, β= 50, Jlf = 10 Am-2,
p=100 mTorr
30. EFFECT OF CURRENT DENSITY ON IED
LF= 1MHz
α= 15
β= 50
n0=2x1016 m-3
P=10mTorr
IED distribution for triple frequency driven CCP
0 100 200 300 400 500 600
0
1
2
3
4
5
6
7
Energy in eV
NormalizedIED(1/eV)
J=5
J=10
J=15
31. EFFECT OF CURRENT DENSITY ON IED
Mid Position of
Energy Band
(in eV)
Width of Energy
Band
(in eV)
0.1Am-2 4.3686e-04 1.2781e-05
1 Am-2 0.1381 0.0227
10 Am-2 43.6862 40.4175
20 Am-2 247.1263 384.5181
30 Am-2 680.9999 1.4362e+03
Parameters: LF= 1MHz, α= 15, β= 50, n0=2x1016, m-3,
pressure= 100 mTorr
32. EFFECT OF LOW FREQUENCY ON IED
LF= fxMHz
α= 15
β= 50
Jlf = 10 Am-2
n0=2x1016 m-3
P=10mTorr
IED distribution for triple frequency driven CCP
20 40 60 80 100 120 140 160 180
0
5
10
15
20
25
30
35
Energy in eV
NormalizedIED(1/eV)
f=1
f=2
33. EFFECT OF LOW FREQUENCY ON IED
Mid Position of
Energy Band
(in eV)
Width of Energy
Band
(in eV)
1 MHz 43.6862 40.4175
1.5 MHz 15.8532 7.2141
2 MHz 7.7227 2.1242
3 MHz 2.8025 0.3791
4 MHz 1.3652 0.1116
Parameters: α= 15, β= 50, n0=2x1016, m-3, n0=2x1016m-3,
pressure= 100 mTorr
34. CONCLUSION
• Ion Energy Distribution (IED) in multi-frequency RF source driven
capacitively coupled plasma are determined.
•Effects of various input parameters (pressure, ion density, frequency, frequency
ratios , ion density ratio) on IED have been investigated.
35. CONCLUSION
• Position and width of IED can be adjusted with the choice of fundamental
frequency, pressure and ion density
