G-type antiferromagnetism results when the spins of electrons in a material are arranged in an antiferromagnetic pattern both within planes of atoms and between neighboring planes. An analysis of SrCr2As2 using neutron diffraction and magnetic susceptibility revealed it is a G-type antiferromagnet below 590K, with chromium magnetic moments aligned along the c axis. The ordered magnetic moment was found to be 1.9μB/Cr at 12K, reduced from the localized value due to itinerant electrons from Cr-As hybridization. Even with significant antisite disorder, G-type and other antiferromagnetic phases can still be detected through their characteristic peaks in the magnetic structure factor.
Hello, I am Subhajit Pramanick. I and my classmate, Anannya Sahaw, both presented this ppt in seminar of our Institute, Indian Institute of Technology, Kharagpur. The topic of this presentation is on exchange interaction and their consequences. It includes the basic of exchange interaction, the origin of it, classification of it and their discussions etc. We hope you will all enjoy by reading this presentation. Thank you.
Hello, I am Subhajit Pramanick. I and my classmate, Anannya Sahaw, both presented this ppt in seminar of our Institute, Indian Institute of Technology, Kharagpur. The topic of this presentation is on exchange interaction and their consequences. It includes the basic of exchange interaction, the origin of it, classification of it and their discussions etc. We hope you will all enjoy by reading this presentation. Thank you.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
To find the susceptibility arising due to water in the solution of MnCl2 , ionic molecular susceptibility ,magnetic moment of the Mn++ using quinche's Method
Paramagnetism has been explained using the classical approach. Derivation of Magnetization and Susceptibility in case of paramagnetism using Langevin Theory of Paramagnetism.
I am Abdullah A. I am a Material Science Exam Helper at liveexamhelper.com. I hold a Ph.D. Degree in Material Science from University of Chicago, USA. I have been helping students with their exams for the past 14 years. You can hire me to take your exam in Material Science.
Visit liveexamhelper.com or email info@liveexamhelper.com.You can also call on +1 678 648 4277 for any assistance with the Material Science exams.
NANO106 is UCSD Department of NanoEngineering's core course on crystallography of materials taught by Prof Shyue Ping Ong. For more information, visit the course wiki at http://nano106.wikispaces.com.
To find the susceptibility arising due to water in the solution of MnCl2 , ionic molecular susceptibility ,magnetic moment of the Mn++ using quinche's Method
Paramagnetism has been explained using the classical approach. Derivation of Magnetization and Susceptibility in case of paramagnetism using Langevin Theory of Paramagnetism.
I am Abdullah A. I am a Material Science Exam Helper at liveexamhelper.com. I hold a Ph.D. Degree in Material Science from University of Chicago, USA. I have been helping students with their exams for the past 14 years. You can hire me to take your exam in Material Science.
Visit liveexamhelper.com or email info@liveexamhelper.com.You can also call on +1 678 648 4277 for any assistance with the Material Science exams.
Dynamics of Twointeracting Electronsinthree-Dimensional LatticeIOSR Journals
The physical property of strongly correlated electrons on a three-dimensional (3D) 3 x 3 x 3 cluster of the simple cubic lattice is here presented.In the work we developed the unit step Hamiltonian as a solution to the single band Hubbard Hamiltonian for the case of two electrons interaction in a finite three dimensional lattice. The approximation to the Hubbard Hamiltonian study is actually necessary because of the strong limitation and difficulty pose by the Hubbard Hamiltonian as we move away from finite - size lattices to larger N - dimensional lattices. Thus this work has provided a means of overcoming the finite - size lattice defects as we pass on to a higher dimension. We have shown in this study, that the repulsive Coulomb interaction which in part leads to the strong electronic correlations, would indicate that the two electron system prefer not to condense into s-wave superconducting singlet state (s = 0), at high positive values of the interaction strength. This study reveals that when the Coulomb interaction is zero, that is, for free electron system (non-interacting), thevariational parameters which describe the probability distribution of lattice electron system is the same. The spectra intensity for on-site electrons is zero for all values of the interaction strength
»Over the last two decades several patents and research papers have reported purported practical methods to extract useful energy from the vacuum. I describe the inventions and analyze the underlying physics. From an analysis based on first principles it is clear that most of the inventions have fundamental errors and cannot work. The basic concept of harvesting zero-point energy remains viable, and at least one patented concept might work.
The vacuum is filled with a high density of zero-point energy, in the form of modes (vibrational patterns) of electromagnetic field. Over the last eight decades it has become clear that this zero-point field (ZPF) vacuum energy is not simply a mathematical formalism, but produces demonstrable effects on physical systems. Along with that realization has come the desire to extract energy from the ZPF.
One set of methods use nonlinear elements to convert the ZPF into a usable form. A rectifier (used to convert AC to DC) is a strongly nonlinear element. One patent makes use of antennas to capture the ZPF. This energy is then rectified and used. Another set of inventions simply rectify fluctuations (noise) in electronic elements as an extraction method. Using a detailed balance argument, I show that these methods cannot work.
Another set of patents describe using a Casimir cavity to mechanically extract energy from the ZPF. A Casimir cavity consists of two closely space reflecting plates that exclude ZPF electromagnetic modes having wavelengths larger than twice the gap spacing. The result is that the imbalance in the density of the ZPF inside and outside the cavity causes the plates to be attracted to each other. This attractive potential can be used, but only once. To produce power continuously, a method must be devised to form a reciprocating Casimir engine. The patents purport to switch off the Casimir attraction while the plates are pulled apart, so that they can repeatedly accelerate together and produce power. This approach is shown to be fundamentally flawed, and cannot produce power continuously.
A recently issued patent describes a method by which vacuum energy is extracted from gas flowing through a Casimir cavity. According to stochastic electrodynamics, the electronic orbitals in atoms are supported by ambient ZPF. When the gas atoms are pumped into a Casimir cavity, where long-wavelength ZPF modes are excluded, the electrons spin down into lower orbitals, releasing energy. This energy is harvested in a local absorber. When the electrons exit the Casimir cavity, they are re-energized to their original orbitals by the ambient ZPF. The process is repeated to produce continuous power. This method does not suffer from the fundamental flaws of the other approaches, and might work.«
We present the results on electronic and semi-conducting properties of YN in
rocksalt and zinc-blende structure by using FP-LAPW method as implemented in
the Wien2k code. By performing the volume optimization method, a theoretical
lattice constant is obtained which is used for performing our calculations. Results
on density of states (DOS) and energy bands of YN are presented. It is found that
YN acts as a semi-conducting behaviour in both the NaCl and ZB structures.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
(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.
Richard's aventures in two entangled wonderlandsRichard 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.
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.
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.
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.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
3. Introduction
Interactions with neighboring atoms make the spin of electrons align in a particular fashion.
We know that “Ferromagnetism” results when the spins are arranged parallel to one another,
and “Antiferromagnetism” results when they are anti-parallel to one another.
Antiferromagnetic ordering is of three types particularly which is illustrated in the figures.
A-type:
The intra-plane coupling is ferromagnetic while inter-plane coupling is antiferromagnetic.
C-type:
The intra-plane coupling is antiferromagnetic while inter-plane coupling is ferromagnetic.
G-type:
Figure 1: Diagram showing (a) Ferromagnetism (b) Antiferromagnetism
4. Both intra-plane and inter-plane coupling are antiferromagnetic.
Overview
The “simple perovskite” transition metal oxides - the cuprates, manganites, or cobaltates,
have a rich phase diagram , with a strong dependence on the doping level. The manganites,
for instance, exhibit not just ferromagnetism (FM), but also CE-type magnetic order and A,
C, and G type antiferromagnetic (AFM) phases, depending on the hole doping level.
Figure 2: Typesof
Antiferromagnetics
5. Similarly one may also expect the double perovskites to exhibit non ferromagnetic order
upon significant electron doping. This has been seen in model Hamiltonian studies and
confirmed via ab initio calculations .The antiferromagnetic phases should occur, for example,
on sufficient electron doping of materials like Sr2FeMoO6 (SFMO) via La substitution for
Sr.
Clear experimental indication of such antiferromagnetic order is limited ,possibly because of
increase in antisite disorder with La doping on Sr2FeMoO6, although intriguing signatures of
non-ferromagnetic behaviour are seen. The phase diagram mapping out the occurrence of
antiferromagnetic phases in the clean limit in two dimensions has been established earlier .
The top panel of Figure 3 shows the three magnetic phases in a structurally ordered
background in a two dimensional double perovskite model. These occur with increasing
electron density. The moments are on the B sites. We have not shown the induced moments
on the B0 sites. At low electron density a ferromagnetic alignment of the core spins is
favoured since it leads to the maximum bandwidth. However, at sufficiently large band
filling, antiferromagnetic states with A or G type order successively become favoured, as
shown in the bottom panel of Figure 3.
Figure 3: Top panel : Three magnetic phases in the structurally ordered 2D double perovskite model.
Left- ferromagnet, center- A type antiferromagnet, right- G type antiferromagnet. Bottom panel :
Electronic density of states for the ferromagnetic,A and G type ordered phases in the structurally
ordered background.
6. While these spin configurations lead to smaller electronic bandwidth they have a higher
density of band edge states compared to the ferromagnet. In contrast to the two dimensional
case, where the effective magnetic lattice is bipartite, the three dimensional lattice has a
geometrically frustrated face centered cubic structure. This promotes various non-collinear
spiral states and “flux” like phases in addition to collinear antiferromagnetic ordered phases,
studied in detail elsewhere.
Figure 4 shows, at large Hund’s coupling, the possible magnetic phases for varying electron
density, level separation EB – EB’, and the crucial B’ -B0’ (next neighbor) hopping t’ . In
addition to FM, and collinear A and C type order, the phase diagram includes large regions of
non-collinear flux and spiral phases and windows of phase separation. Modest B’ -B’
hopping leads to significant shift in the phase boundaries, and particle-hole asymmetry.
Figure 4: Magneticground state for varying electron density, n, and effective BB0 level
separation, ∆.(a): Phase diagram with only BB’, i.e.,nearest neighbor, hopping. (b): Phase
diagram when an additional B’ -B’hopping, t’/t = −0.3,is included.The labels are: F
(ferromagnet), A (planar phase), C (line like), FL (flux) and SP (spiral). This figure does not
show the narrow windows of phase separation in the model. The phase diagrams are
generatedvia a combination of Monte Carlo and variational calculations on lattices of size
upto 20×20×20.
7. Figure 5 shows the spin configuration for A type order in three dimension. The spins are
parallel within the 111 planes (shown) and are antiparallel between neighbouring planes. The
conduction path gets divided into two sub-lattices, such that each spin channel gets to
delocalise in one sub-lattice. In one such sublattice, only one of the up or down spin electrons
can delocalise, the other remains localised.
The roles of up and down are reversed in going from one sub-lattice to other, as a result one
gets spin-degenerate localised and dispersive bands for antiferromagnetic phases. The
delocalisation is effectively two dimensional. This A type order in three dimension is
analogous to the A type antiferromagnet phase in two dimension (top panel of Figure 3), with
the ferromagnetic planes being equivalent to the ferromagnetic stripes.
In order to get to these phases we have to electron dope the system. In real material this leads
to an increase in the amount of antisite disorder. To understand this situation we have studied
the survival of electronically driven antiferromagnetism in the presence of spatially correlated
antisite disorder in a two dimensional model. We have worked in two dimensions for ease of
visualisation and to access large system size, and will comment on the three dimensional
situation at the end. We have focussed on a couple of electron densities, one each in the A
type and G type window, respectively.
Earlier studies on AFM order
Figure 5: Spin configuration for A type order. The spins are parallel within the 111
planes (shown) and are antiparallel between neighbouring planes. The
delocalisation is effectivelytwo dimensional.
8. Early studies using model Hamiltonians for double perovskites had observed the instability of
the ferromagnetic state, without exploring the competing phase that emerges. A subsequent
variational study did identify non-ferromagnetic phases.
More recent studies using both simple models and realistic DFT calculations indicate that
the ferromagnet becomes unstable to an A type phase on increasing electron density. In
Sr2−xLaxFeMoO6, for example, this is expected to happen for x & 1. The DFT studies have
employed supercells for a few commensurate doping levels. Using a three band model
Hamiltonian with parameters inferred from the DFT, the same authors have explored a more
continuous variation of La doping level and confirmed the DFT trends. The crossover to a
non-ferromagnetic ordered state is, therefore, not an artifact of a single band model or two
dimensionality that earlier studies employed.
Regarding the effect of antisite disorder on the non-ferromagnetic phases, we are aware of
only one study involving uncorrelated antisite defects. It is more focused on the doping
dependence, and explores mainly the magnetism, but the trends are consistent with what we
observe here. Samples have indeed been synthesised with large La doping on Sr2FeMoO6 .
The main observations are (i) a suppression of the low field magnetisation with increasing x
(may be related to increase in antisite defects), and (ii) signature of an antiferromagnetic
metallic ground state in heavily electron doped Sr2FeMoO6 . There is unfortunately no
detailed understanding of the impact of antisite disorder in these samples yet, or any data on
resistivity and magnetoresistance.
The phase diagram of the two dimensional model in the clean limit before considering
disorder. In the absence of antisite disorder, there are no AFM super exchange interactions in
the system, and the magnetic order is decided by minimisation of the electronic energy. For
Hund’s coupling much much greater than hopping amplitude the model supports three
collinear phases.
The FM state gives way to A type (line like) order with increasing electron density, and
finally to a G type state. These have been discussed earlier; we reproduce the magnetic
configurations in the top panel, and the electronic density of states in the bottom panel of
Figure 4. . The ferromagnetic state is preferred at low density, n, since it has the largest
bandwidth. The A type state has lower bandwidth, but with large density of states near the
band edge. The FM becomes unstable at n ∼ 0.45. The A type state is stable for n ≥ 0.58, and
between these we have a phase separation window. Similarly the A to G transition involves
phase separation window. The phase separation windows narrow with increasing T and
vanish as T → Tc.
9. The thermal transitions and the phase separation windows are shown in Figure 6. Broadly, the
task would be to extend this phase diagram to finite antisite disorder. Instead of attempting to
map out the disorder dependence at all densities we choose two representative densities, n ∼
0.65 in the A type window, and n ∼ 0.95 in the G type region, to clarify the impact of
disorder. We also explore the effect of antisite disorder on the phase separation window,
between the ferromagnet and the A type phase, since it would be encountered in any attempt
to electron dope the ferromagnet.
Disorder configurations
There are four families, with progressively increasing antisite disorder . A representative
configuration from each family is shown in the top row in Figure 7 . They have structural
order parameter S = 0.98, 0.76, 0.50, 0.08 as we move from left to right. The red and blue
colours indicate internally ordered domains but with a phase slippage between them. We plot
(ηi − 1/2)e iπ(xi+yi) . The middle row shows the A type antiferromagnetic phase on this
structural motif, while the bottom row shows the G type phase. The magnetic correlations are
characterised via the overlap factor gi = S0.Si , where S0 is the left lower corner spin in the
Figure 6 : Phase diagram for the non disordered double perovskite. We only show the
region n = [0, 1]. From n = 1 to n = 2 one populates the non-dispersive B’ level, and the
magnetic state is G type. The n = [2, 3] window is a symmetric version of the n = [1, 2]
region. The regions between the phases indicate phase separation. The results are
obtained via Monte Carlo on a 40 × 40 lattice
10. lattice. As mentioned earlier, our disorder average for magnetic and electronic properties is
performed typically over 10 configurations within each family.
AFM order with antisite disorder
In the ferromagneticcase itissimple tosee thatthe presence of antiferromagneticsuperexchange
at the antiphase boundarywouldtendtoalignspinsinoppositedirectionsacrossanantiphase
boundary.The systembreaksupintoup anddownspindomains.Suppose the upspindomains
correspondtothe correctlylocatedsitesandare the majority. The netmagnetisationisproportional
to the volume difference betweenthe correctlylocatedandmislocatedregions.If the degree of
mislocationisx,thenthe normalisedmagnetisationM= (1−x)−x = 1−2x = S.In the magnetic
structure factor D(q),the ferromagneticpeakisat a pair of wave-vectors,QF1= {0, 0} and QF2 = {π,
π}. We have set the lattice spacinga0 = 1 on the DP lattice.A pair of wave-vectorsisrequiredto
characterise anorderedstate since half the sites(the B’) are non magneticandhence zeroesof the
spinfield.Since D(QF1) issimplyM2 , the domainargument,above,yieldsD(QF1) ∼ S2 . This
dependence iswell establishedexperimentally,andalsoobserved.
G type order occurs at the combination {QG1, QG2} : {{0, π}, {π, 0}}. As before the relative
displacement of the domains can be only ˆxa0 or ˆya0.
Figure 7: Antiphase domains and corresponding antiferromagnetic phases. The top row shows the domain
pattern in the ASD background, with increasing disorder. The middle row shows the A type antiferromagnetic
phase on this structural motif, while the bottom row shows the G type phase
11. Suppose we are 73 computing the structure factor at QG1 then all domains will contribute,
but with following phase factors: zero if the domain is not mislocated (δr = 0), zero again if
the domain is ˆx displaced, and e iπ = −1 if the domain is ˆy displaced.
In two domain systems, as in the second column in Figure 7 , the mislocated domain is either
x displaced or y displaced. For copies with x displacement the contribution at QG1 will be |(1
− x) + x| ^2 = 1, while for y displacement it will be |(1 − x) + e iπx|^ 2 = (1 − 2x) ^2 = S^2 .
Averaging the structure factor over copies would lead to D(QG1) = (1/2)(1 + S 2 ).
This is roughly what we observe in our Figure 4.6 (b) at T = 0. In large systems, where there
will be many domains, we can assume that half the mislocated domains are x displaced and
half y displaced. In that case the structure factor would be D(QG1) = |(1 − x) + x/2 + e iπx/2|
^2 . Using 1 − 2x = S this leads to D(QG1) = (1/4)(1 + S) ^2 .
For S → 0 this gives 0.25, not far from ∼ 0.20 that we obtain from our configurations. This
reveals that for both A and G type order even when half the sites are mislocated, i.e., one has
maximal antisite disorder, there is a surviving peak in the structure factor. All these of course
assumed that the structural pattern had a high degree of spatial correlation so that one can
meaningfully talk of domains. We should have 1 − p 1, or structural correlation length ξ a0.
If the structures were fragmented to a random alloy then the results above would not hold.
We have checked this explicitly.
Figure 8: Magneticorder in the A type and G type phases with ASD.The results are based on Monte Carlo on 40× 40
systems, and averaged typically over 10 configurations for each value of S.
12. Conclusion
Basically what happens in G type Antiferromagnetism is that the neutron-diffraction and
magnetic susceptibility studies of polycrystalline SrCr 2As 2 reveal that this compound is an
itinerant G-type antiferromagnet below the Néel temperature T N = 590(5) K with the Cr
magnetic moments aligned along the tetragonal c axis. The system remains tetragonal to the
lowest measured temperature (~12 K). The lattice parameter ratio c/a and the magnetic
moment saturate at about the same temperature below ~200 K, indicating a possible
magnetoelastic coupling. The ordered moment μ = 1.9(1)μ B/Cr, measured at T = 12 K, is
significantly reduced compared to its localized value (4μ B/Cr) due to the itinerant character
brought about by hybridization between the Cr 3d and As 4p orbitals.
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Thank You