The document discusses the Onsager theory of semiclassical quantization of electron orbits in a magnetic field. It describes how the Bohr-Sommerfeld quantization condition leads to the quantization of the magnetic flux through an electron orbit. This quantization of flux results in discrete Landau levels with energies dependent on the quantum number and magnetic field strength. Measurements of oscillations in magnetization via the de Haas-van Alphen effect can be used to map the Fermi surface by detecting extremal orbits corresponding to peaks in the density of states.
Fermi surfaces are important for characterizing and predicting the thermal, electrical, magnetic, and optical properties of crystalline metals and semiconductors.
In this Powerpoint show, you will become familiar with Fermi Surface and The De Haas-van Alphen effect based on Ashcroft's Solid state book, Chapter 14.
II. Charge transport and nanoelectronics.
Quantum Hall Effect: 2D electron gas (2DEG) in magnetic field, Landau levels, de Haas-van Alphen and Shubnikov-de Haas Effects, integer and fractional quantum Hall effects, Spin Hall Effect.
Quantum transport: Transport regimes and mesoscopic quantum transport, Scattering theory of conductance and Landauer-Buttiker formalism, Quantum point contacts, Quantum electronics and selected examples of mesoscopic devices (quantum interference devices).
Tunneling: Scanning tunneling microscopy and spectroscopy (and wavefunction mapping in nanostructures and molecules), Nanoelectronic devices based on tunneling, Coulomb blockade, Single electron transistors, Kondo effect.
Molecular electronics: Donor-Acceptor systems, Nanoscale charge transfer, Electronic properties and transport in molecules and biomolecules; single molecule transistors.
(If visualization is slow, please try downloading the file.)
Part 1 of a tutorial given in the Brazilian Physical Society meeting, ENFMC. Abstract: Density-functional theory (DFT) was developed 50 years ago, connecting fundamental quantum methods from early days of quantum mechanics to our days of computer-powered science. Today DFT is the most widely used method in electronic structure calculations. It helps moving forward materials sciences from a single atom to nanoclusters and biomolecules, connecting solid-state, quantum chemistry, atomic and molecular physics, biophysics and beyond. In this tutorial, I will try to clarify this pathway under a historical view, presenting the DFT pillars and its building blocks, namely, the Hohenberg-Kohn theorem, the Kohn-Sham scheme, the local density approximation (LDA) and generalized gradient approximation (GGA). I would like to open the black box misconception of the method, and present a more pedagogical and solid perspective on DFT.
(If visualization is slow, please try downloading the file.)
Part 2 of a tutorial given in the Brazilian Physical Society meeting, ENFMC. Abstract: Density-functional theory (DFT) was developed 50 years ago, connecting fundamental quantum methods from early days of quantum mechanics to our days of computer-powered science. Today DFT is the most widely used method in electronic structure calculations. It helps moving forward materials sciences from a single atom to nanoclusters and biomolecules, connecting solid-state, quantum chemistry, atomic and molecular physics, biophysics and beyond. In this tutorial, I will try to clarify this pathway under a historical view, presenting the DFT pillars and its building blocks, namely, the Hohenberg-Kohn theorem, the Kohn-Sham scheme, the local density approximation (LDA) and generalized gradient approximation (GGA). I would like to open the black box misconception of the method, and present a more pedagogical and solid perspective on DFT.
Fermi surfaces are important for characterizing and predicting the thermal, electrical, magnetic, and optical properties of crystalline metals and semiconductors.
In this Powerpoint show, you will become familiar with Fermi Surface and The De Haas-van Alphen effect based on Ashcroft's Solid state book, Chapter 14.
II. Charge transport and nanoelectronics.
Quantum Hall Effect: 2D electron gas (2DEG) in magnetic field, Landau levels, de Haas-van Alphen and Shubnikov-de Haas Effects, integer and fractional quantum Hall effects, Spin Hall Effect.
Quantum transport: Transport regimes and mesoscopic quantum transport, Scattering theory of conductance and Landauer-Buttiker formalism, Quantum point contacts, Quantum electronics and selected examples of mesoscopic devices (quantum interference devices).
Tunneling: Scanning tunneling microscopy and spectroscopy (and wavefunction mapping in nanostructures and molecules), Nanoelectronic devices based on tunneling, Coulomb blockade, Single electron transistors, Kondo effect.
Molecular electronics: Donor-Acceptor systems, Nanoscale charge transfer, Electronic properties and transport in molecules and biomolecules; single molecule transistors.
(If visualization is slow, please try downloading the file.)
Part 1 of a tutorial given in the Brazilian Physical Society meeting, ENFMC. Abstract: Density-functional theory (DFT) was developed 50 years ago, connecting fundamental quantum methods from early days of quantum mechanics to our days of computer-powered science. Today DFT is the most widely used method in electronic structure calculations. It helps moving forward materials sciences from a single atom to nanoclusters and biomolecules, connecting solid-state, quantum chemistry, atomic and molecular physics, biophysics and beyond. In this tutorial, I will try to clarify this pathway under a historical view, presenting the DFT pillars and its building blocks, namely, the Hohenberg-Kohn theorem, the Kohn-Sham scheme, the local density approximation (LDA) and generalized gradient approximation (GGA). I would like to open the black box misconception of the method, and present a more pedagogical and solid perspective on DFT.
(If visualization is slow, please try downloading the file.)
Part 2 of a tutorial given in the Brazilian Physical Society meeting, ENFMC. Abstract: Density-functional theory (DFT) was developed 50 years ago, connecting fundamental quantum methods from early days of quantum mechanics to our days of computer-powered science. Today DFT is the most widely used method in electronic structure calculations. It helps moving forward materials sciences from a single atom to nanoclusters and biomolecules, connecting solid-state, quantum chemistry, atomic and molecular physics, biophysics and beyond. In this tutorial, I will try to clarify this pathway under a historical view, presenting the DFT pillars and its building blocks, namely, the Hohenberg-Kohn theorem, the Kohn-Sham scheme, the local density approximation (LDA) and generalized gradient approximation (GGA). I would like to open the black box misconception of the method, and present a more pedagogical and solid perspective on DFT.
Presentation of third- and fifth-order optical nonlinearities measurement using the D4Sigma-Z-scan Method. I present a resolution of propagation equation in general case (with third- and fifth-order nonlinearities) and a numerical inversion.
This presentation is conclude with experimental results.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
We present an ab-initio real-time based computational approach to nonlinear optical properties in Condensed Matter systems. The equation of mot ions, and in particular the coupling of the electrons with the external electric field, are derived from the Berry phase formulation of the dynamical polarization. The zero-field Hamiltonian includes crystal local field effects, the renormalization of the independent particle energy levels by correlation and excitonic effects within the screened Hartree- Fock self-energy operator. The approach is validated by calculating the second-harmonic generation of SiC and AlAs bulk semiconductors : an excellent agreement is obtained with existing ab-initio calculations from response theory in frequency domain . We finally show applications to the second-harmonic generation of CdTe the third-harmonic generation of Si.
Reference :
Real-time approach to the optical properties of solids and nanostructures : Time-dependent Bethe-alpeter equation Phys. Rev. B 84, 245110 (2011)
Nonlinear optics from ab-initio by means of the dynamical Berry-phase
C. Attaccalite and M. Gruning Phys. Rev. B 88 (23), 235113 (2013)
Presentation of third- and fifth-order optical nonlinearities measurement using the D4Sigma-Z-scan Method. I present a resolution of propagation equation in general case (with third- and fifth-order nonlinearities) and a numerical inversion.
This presentation is conclude with experimental results.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
We present an ab-initio real-time based computational approach to nonlinear optical properties in Condensed Matter systems. The equation of mot ions, and in particular the coupling of the electrons with the external electric field, are derived from the Berry phase formulation of the dynamical polarization. The zero-field Hamiltonian includes crystal local field effects, the renormalization of the independent particle energy levels by correlation and excitonic effects within the screened Hartree- Fock self-energy operator. The approach is validated by calculating the second-harmonic generation of SiC and AlAs bulk semiconductors : an excellent agreement is obtained with existing ab-initio calculations from response theory in frequency domain . We finally show applications to the second-harmonic generation of CdTe the third-harmonic generation of Si.
Reference :
Real-time approach to the optical properties of solids and nanostructures : Time-dependent Bethe-alpeter equation Phys. Rev. B 84, 245110 (2011)
Nonlinear optics from ab-initio by means of the dynamical Berry-phase
C. Attaccalite and M. Gruning Phys. Rev. B 88 (23), 235113 (2013)
Numerical studies of the radiation patterns of resistively loaded dipolesLeonid Krinitsky
The far field radiation patterns of finite-size resistively loaded horizontal electric dipoles lying on a low-loss dielectric half-space are computed. The patterns are a superposition of the solutions for transient infinitesimal dipole elements, where the transient waveform for each element is synthesized from the exact steady-state solution. The current excitation for each dipole element is a half cycle of a sine squared waveform that propagates along the line of elements at a speed that can be varied. No reflections from the antenna ends are assumed. The time duration of the current half cycle governs the full period of the dominant part of the transient radiated waveform. The amplitude of the dipole excitation current is determined by a cosine distribution that accurately simulates the resistive loading. The transient radiation patterns differ from those of a steady-state dipole mainly by being more narrow in the E-plane, as is true for a finite-size steady-state dipole radiating in air. In addition, the far field waveforms are slightly distorted in directions off vertical in the E-plane. Two-way power radiation patterns are presented for both conductive and non-conductive dielectric media in a footprint mode, i.e. the power response to an isotropic point scatterer on a subsurface flat plane. The radar footprint in a conductive dielectric shows very narrow beamwidth due to the added conductive attenuation along the longer paths off the vertical direction. Field tests in water and glacial ice and laboratory observations show good agreement with the E-plane model results but suggest that the H-plane directivity is strongly affected by the separation between transmit and receive antennas and by the range.
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.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
(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.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
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.
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Contents
Contents
Onsager theory: Semiclassical quantization of orbits in a
magnetic field
Physical meaning for the quantization of the magnetic flux
Definition of the magnetic length
Physical meaning of the Onsager relation
Extremal orbit contributing to the dHvA signal
Landau tubes with the quantum number n
Density of states using the magnetic length
Derivation of the dHvA frequency
Energy dispersion of the Landau level
Simple model to understand the dHvA effect
Derivation of the oscillatory behavior in a 2D model
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
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Onsager theory: Semiclassical quantization of orbits in a
magnetic field
Onsager theory: Semiclassical quantization of orbits in a
magnetic field
The Onsager-Lifshitz idea was based on a simple semi-classical
treatment of how electrons move in a magnetic field, using the
Bohr-Sommerfeld condition to quantized the motion. The
Lagrangian of the electron in the presence of electric and magnetic
field is given by
L =
1
2
mv2
− q(ϕ −
1
c
v.A) (1)
where m and q are the mass and charge of the particle.
Canonical momentum:
p =
∂L
∂v
= mv +
q
c
A (2)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
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Onsager theory: Semiclassical quantization of orbits in a
magnetic field
The Hamiltonian formalism uses A and ϕ and not E and B,
directly. The result is that the description of the particle depends
on the gauge chosen. We assume that the orbits in a magnetic
field are quantized by the Bohr-Sommerfeld relation
π = mv = ~k = p −
q
c
A = p +
e
c
A (5)
and I
p.dl = (n + γ)2π~ (6)
where q = −e(e > 0) is the charge of electron, n is an integer, and
γ is the phase correction: γ = 1/2 for free electron.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
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Onsager theory: Semiclassical quantization of orbits in a
magnetic field
I
p.dl =
I
~k.dl −
e
c
I
A.dl = (n + γ)2π~ (7)
Note we assume ro = 0. Then we get
I
~k.dl = −
e
c
I
rXB.dl =
e
c
B.
I
rXdl =
e
c
B.2An =
2e
c
Φ (8)
where I
(rXdl) = 2(areaenclosedwithintheorbit)n (9)
and Φ is the magnetic flux contained within the orbit in real space,
Φ = B.An.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
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Onsager theory: Semiclassical quantization of orbits in a
magnetic field
Then we have
H
(rXdl) = 2(areaenclosedwithintheorbit)n
On the other hand,
−
e
c
I
(A.dl) = −
e
c
I
(▽XA).da = −
e
c
I
(B.da) = −
e
c
Φ (10)
by the Stokes theorem. Then we have
I
(p.dl) =
2e
c
Φ −
e
c
Φ =
e
c
Φ = (n + γ)2π~ (11)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
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Onsager theory: Semiclassical quantization of orbits in a
magnetic field
It follows that the orbit of an electron is quantized in such a way
that the flux through it is
Φn(r) = (n + γ)
2π~c
e
= 2Φo(r + γ), (12)
where Φois a quantum fluxoid and is given by
Φo =
2π~c
e
=
hc
2e
= 2.0678X10−7
Gausscm2
(13)
Note that -2e corresponds to the charge of the Cooper pair
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
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Physical meaning for the quantization of the magnetic flux
Physical meaning for the quantization of the magnetic flux
According to the Onsager theory, the magnetic flux inside the orbit
of electron is quantized as
Φn(r) = BSn(r) = (n + γ)
2π~c
e
= 2Φo(r + γ) (14)
where Sn(r) is the area of the electron orbit, and n is an integer.
Using the relation k =
eB
c~
r =
1
l2
r
it is found that the area Sn(k)of the orbit of electron in the k-space
(normal to B) is related to the area Sn(r)through
Sn(k) =
1
Bl4
BSn(r) =
e2B
c2~2
Φn(r) =
2πeB
~c
(n + γ) (15)
implying that Sn(k) is also quantized for the fixed magnetic field B.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
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Definition of the magnetic length
Definition of the magnetic length
When the magnetic field B is applied to the z axis (normal to the
plane), what is the area A where the quantum flux 2Φo penetrates?
2Φo =
2π~c
e
= BSn(r) (16)
Then we get
Sn(r) =
π~c
eB
= πl2
(17)
where
l2
=
c~
eB
(18)
In other words, l is the radius of the circle inside which the
quantum fluxoid Φo passes through.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
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Physical meaning of the Onsager relation
Physical meaning of the Onsager relation
We consider the Landau tubes whose cross sections by plane
perpendicular to the direction of the magnetic field has the same
area for the n-th Landau tube,
Sn(k) =
2πeB
~c
(n +
1
2
) (19)
and are bounded by the curves of constant energy (
~2k2
z
2m
=
~2k2
//
2m
) at the height kz in the k-space. The energy at kzof
the Landau tube is given by
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
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Physical meaning of the Onsager relation
Here we show how to draw the Landau tubes:
We choose the quantum number n (the integer) such
~2k2
⊥
2m
= ~ωc(n +
1
2
) (22)
where k⊥(kn)n is the in-plane wave number.
The energy of the cylinder (so-called Landau tube) at the
point denoted by n and kz is given by
ε(n, kz) = (n +
1
2
)~ωc +
~2k2
z
2m
(23)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
17. .
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Physical meaning of the Onsager relation
The intersection of the constant-kz plane with the Fermi surface
(ε = εf) forms a cross section (circle with the radius kn). The
Landau tube can be constructed such that the top and the bottom
are parts of the cylinder as shown in Fig-4 The radius of the
Landau tube denoted by the quantum number increases with
increasing the magnetic field.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
19. .
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Physical meaning of the Onsager relation
The level density will have a sharp peak whenever ε is equal to the
energy of an extremal orbit, satisfying the quantization condition.
The reason for this is as follows. The above figures depict the
Landau tube with the same n for different B. As the magnetic field
B increases, the area of the Landau tube increases. The number of
the states D(ε)dε is proportional to the area of the portion of
Landau tube contained between the constantenergy energy
surfaces ε and ε + dε. The area of such a portion is not extremal
in (a) to (f). The area of the portion as shown in (g) becomes
extremal when there is an extremal orbit of energy ε on the
Landau tube. Evidently, the area of the portion of the tube is
enhanced as a result of the very slow energy variation of the level
along the tube near the given orbit.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
21. .
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Extremal orbit contributing to the dHvA signal
Extremal orbit contributing to the dHvA signal
From the above discussion, we notice that the extremal value of
the area of the crosssection of the Fermi surface, A(εf, kz), at the
actual Fermi level εf, at the slice kz, where kz is the component of
the wave vector along the direction of magnetic field B. The
extremal cross section is defined by
∂A(εf, kz)
∂kz
= 0 (24)
at kz = ko
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
23. .
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Landau tubes with the quantum number n
•Landau tubes with the quantum number n
Here we draw a series of Landau tubes with different quantum
number n for each fixed magnetic field B. We start with the
relation given by
E =
~2k2
z
2m
+ ~ωc(n +
1
2
) (25)
where
ωc =
eB
mc
(26)
For simplicity, we assume that~ = 1, m = 1. Then we get
E =
1
2
k2
z + ~ωc(n +
1
2
) (27)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
24. .
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Landau tubes with the quantum number n
For a fixed n (0 or positive integer) and a fixed E,
kz = ±
p
2E − ωc(2n + 1) (28)
The Landau tube consists of the cylinder with a radius
k⊥ = kn =
p
(2n + 1)ωc (29)
and the length of cylinder
|kz| ≤
p
2E − ωc(2n + 1) (30)
We choose; E = 12.ωc is changed as a parameter, where
~ = 1, m = 1. In the quantum limit, there is only one state with n
= 0 inside the Fermi surface.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
29. .
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Fundamentals of the Landau levels
Fundamentals of the Landau levels
We now consider the case when kz = 0.
Figure: This regular periodic motion introduces a new quantization of the
energy levels (Landau levels) in the (kx, ky) plane, corresponding to those
of a harmonic oscillator with frequency ωc and energy
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
30. .
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Fundamentals of the Landau levels
This regular periodic motion introduces a new quantization of the
energy levels (Landau levels) in the (kx, ky) plane, corresponding to
those of a harmonic oscillator with frequency ωc and energy
ε(n) = ~ωc(n +
1
2
) =
~2k2
⊥
2m
(31)
where k⊥ is the magnitude of the in-plane wave vector and the
quantum number n takes integer values 0, 1, 2, 3, ...ωcis the
cyclotron angular frequency and is defined by
ωc =
eB
mc
(32)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
31. .
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Fundamentals of the Landau levels
Each Landau ring is associated with an area of k space. The area
Sn is the area of the orbit n with the radius k⊥ = kn
Sn(k) = πk2
n =
2πeB
~c
(n +
1
2
) =
2π
l2
(n +
1
2
) (33)
Thus in a magnetic field the area of the orbit in k space is
quantized. Note that
l2 =
~c
eB
. l is given by
l =
256.556
p
B[T]
[µm] (34)
in the SI units.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
33. .
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Fundamentals of the Landau levels
Figure: Quantization scheme for free electrons. Electron states are
denoted by points in the k space in the absence and presence of external
magnetic field B. The states on each circle are degenerate. (a) When
B = 0, there is one state per area (
2π
L
)2
.L2
is the area of the system. (b)
When B ̸= 0, the electron energy is quantized into Landau levels. Each
circle represents a Landau level with energy En = ~ωc(n +
1
2
)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
37. .
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Density of states using the magnetic length
Now we calculate the number of states between the adjacent
energy levels εn and εn+1. Since△ε⊥ = εn+1 − εn = ~ω(which is
independent of the quantum number n. Then the number of states
is calculated as
D = D(ε⊥)△ε⊥ =
mL2
2π~2
△ε⊥ =
mL2
2π~2
~ωc
mL2
2π~2
~eB
mc
=
eBL2
2π~c
= ρB
(40)
Where ρ =
eL2
2π~c
and l2 =
c~
eB
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
38. .
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Derivation of the dHvA frequency
Derivation of the dHvA frequency
The use of the Onsager’s relation
In the dHvA we need the area of the orbit in the k-space. We
define Sn(r) as an area enclosed by the orbit in the real space (r)
and Sn(k) as an are enclosed by the orbit in the k-space. Then we
have a relation
Sn(r) = (
c~
eB
)2
Sn(k) = l4
Sn(k) (41)
and
Sn(k) = (n + γ)
2πe
~c
B (42)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
39. .
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Derivation of the dHvA frequency
In the Fermi surface experiments we may be interested in the
increment △Bfor which two successive orbits, n and n+1, have the
same area in the k-space on the Fermi surface. Suppose that S(k)
is the Fermi surface in the momentum space. Then we have
Sn(k) = Sn+1(k) = S(k) (43)
or
(n + γ)
2πe
~c
Bn = (n + 1 + γ)
2πe
~c
Bn+1 = S(k) (44)
or
S(k)
Bn
= (n + γ)
2πe
~c
,
S(k)
Bn+1
= (n + 1 + γ)
2πe
~c
(45)
or
S(k)[
1
Bn
−
1
Bn+1
] =
2πe
~c
(46)
or
△(
1
B
) =
2πe
~cS(k)
=
1
F
(47)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
40. .
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Derivation of the dHvA frequency
The dHVA frequency F is related to the area of the Fermi surface.
F =
~c
2πe
S(k) (48)
What is a typical value of△B which is experimentally observed?
△(
1
B
) =
| △ B|
B2
=
2πe
~cS(k)
(49)
For Au, S(k) = 4.8x1016cm−2 for the belly orbit of Au.
| △ B| =
2πe
~cS(k)
B2 = 0.198872[Bo(T)]2 (in units of G) where Bo is
in the units of T. When B = 5 T (which means Bo = 5), we have
| △ B| = 4.97G(= Oe).
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
41. .
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The use of Landau level
The use of Landau level
Suppose that n-th Landau level exists just below the Fermi energy.
The total number of states below the Fermi energy is
nρB =
L2
(2π)2
S(k) (50)
where S(k) is the 2D extremal cross section of the Fermi surface,
normal to B, and ρ is
ρ =
eL2
2πc~
(51)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
44. .
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Another method for the derivation: cyclotron frequency
Another method for the derivation: cyclotron frequency
Note that the formula for can also be derived from the
correspondence principle. The frequency for motion along a closed
orbit is
ωc =
eB
mcc
(56)
where mc is defined as
mc =
~2
2π
∂S
∂ε
(57)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
45. .
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Another method for the derivation: cyclotron frequency
In the semiclassical limit, one should obtain equidistant levels with
a separation △ε equal to ~ωc . Hence
△ε = ~ωc =
~eB
mcc
=
~eB
c[
~2
2π
∂S
∂ε
]
=
2πeB
c~(∂S/∂ε)
(58)
or
∂S
∂ε
=
2πeB
c~
1
~ωc
(59)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
47. .
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Energy dispersion of the Landau level
Energy dispersion of the Landau level
We consider the energy dispersion of the Landau level with the
quantum number n as a function of kz.
ε(n, kz) = (n +
1
2
)~ωc +
~2k2
z
2m
(62)
Figure: Energy dispersion of the Landau levels with n and Kz for a 3D
electron gas in the presence of a magnetic field along the z axis.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
48. .
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Simple model to understand the dHvA effect
Simple model to understand the dHvA effect
Consider the figure showing Landau levels associated with
successive values of n = 0, 1, 2, , s The upper green line represents
the Fermi level εF. The levels below εF are filled, those above are
empty. Since εFis much larger than the level-separation ~ωc , the
number n = s of occupied levels is very large. Let us assume that
the magnetic field is increased slightly. The level separation will
increase, and one of the lower levels will eventually cross the Fermi
level. The resulting distribution of levels is similar to the original
one except that the number of filled levels below εF is now
n = s − 1, instead ofn = s. Since n is large, this difference is
essentially negligible, so that one expects the new state to be
equivalent to the original one. This implies a periodic dependence
of the magnetization.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
49. .
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Simple model to understand the dHvA effect
Figure: Schematic energy diagram of a 2D free electron gas in the
absence and presence of B. At B = 0, the states below εF are occupied.
The energy levels are split into the Landau levels with (a) n = 0, 1, 2,…,
and s for a specified field and (b) n = 0, 1, 2,…, and s-1 for another
specified field. The total energy of the electrons is the same as in the
absence of a magnetic field.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
50. .
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Derivation of the oscillatory behavior in a 2D model
Derivation of the oscillatory behavior in a 2D model
The energy level of each Landau level is given by (n +
1
2
)~ωc,
where n = 0, 1, 2, ….. Each on of the Landau level is degenerate
and contains ρB states. We now consider several cases.
Then = 0, 1, 2, …, s-1 states are occupied. n = s state is empty.
εF = ~ωcs.N = ρBs (63)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
52. .
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Derivation of the oscillatory behavior in a 2D model
The total energy is constant,
U = Uo = Σs−1
n=0ρB(n +
1
2
)~ωc = ~ωcρB[
1
2
s(s − 1) +
1
2
s] = ~ωcρB
1
2
s2
=
1
2
εFN
(64)
The case where the n = s state is not filled. We now consider the
case when ~ωcdecreases. This corresponds to the decrease of B.
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
54. .
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Derivation of the oscillatory behavior in a 2D model
εf = s~ωc + ε, with0 < ε < ~ωc (65)
Figure: 0 < ε < ~ωc
The n = 0, 1, 2, …, (s-1) levels are occupied and the n = s level is
not filled. The total number of electrons is N. The energy due to
the partially occupied n = s state is (N − ρBs)~ωc(s +
1
2
). Then
the total energy is
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect
56. .
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Derivation of the oscillatory behavior in a 2D model
Here we introduceλ as λ = N − ρBs. The parameter λ satisfies the
inequality
0 < λ < ρB for
ρs
N
<
1
B
<
ρ(s + 1)
N
The parameter λ denotes the
number of electrons partially occupied in the n = s state.
The parameter ρBs is the total number of electrons occupied in
the n = 0, 1, 2,…, s-1 states for
ρs
N
<
1
B
<
ρ(s + 1)
N
. The n = 0,
1, 2, …, s states are occupied. n = s+1 state is empty.
Figure: εf = ~ωc(s + 1)
Tewodros Adaro Fermi surface and De Haas-van Alphen Effect