Academic literature on the topic 'Condensed matter physics not elsewhere classified'

I present some rather selective reminiscences of my long career in physics, from my doctoral work to the present. I do not spend time on topics such as the nuclear magnetic resonance behavior of 3He, as I have reviewed the history extensively elsewhere, but rather concentrate, first, on my long-running project to make condensed matter physics relevant to questions in the foundations of quantum mechanics, and second, on various rather “quirky” problems such as an attempt to amplify the effects of the parity violation due to the weak interaction to a macroscopic level, and an unconventional proposal for the mechanism of the first-order phase transition between the A and B phases of superfluid liquid 3He.

Single variable hypergeometric functions pFq arise in connection with the power series solution of the Schrödinger equation or in the summation of perturbation expansions in quantum mechanics. For these applications, it is of interest to obtain analytic expressions, and we present the reduction of a number of cases of pFp and p+1Fp, mainly for p=2 and p=3. These and related series have additional applications in quantum and statistical physics and chemistry.

We present a brief review of a series of on-going work on bacterial phylogeny. We propose a new method to infer relatedness of prokaryotes from their complete genome data without using sequence alignment, leading to results comparable with the bacteriologist's systematics as reflected in the latest 2001 edition of Bergey's Manual of Systematic Bacteriology.1 We only touch on the mathematical aspects of the method. The biological implications of our results will be published elsewhere.

The rise of the superconducting transition temperature Tc has been reviewed in three major superconducting systems: the cuprate, the Fe -pnictide and the heavy fermion. While the first two systems display high Tc s , heavy fermion superconductors show low Tc but embody many crucial features found in the others. The prospect of future superconductors with higher Tc, preferably close to room temperature, is also discussed. Those interested in the detailed physics of high temperature superconductivity are referred to the article by E. Abrahams in the next chapter of this book and reviews published elsewhere.

Non-axisymmetric magnetic fields arising in a tokamak either by external or internal perturbations can induce complex non-ideal MHD responses in their resonant surfaces while remaining ideally evolved elsewhere. This layer response can be characterized in a linear regime by a single parameter called the inner-layer Δ, which enables outer-layer matching and the prediction of torque balance to non-linear island regimes. Here, we follow strictly one of the most comprehensive analytic treatments including two-fluid and drift MHD effects and keep the fidelity of the formulation by incorporating the numerical method based on the Riccati transformation when quantifying the inner-layer Δ. The proposed scheme reproduces not only the predicted responses in essentially all asymptotic regimes but also with continuous transitions as well as improved accuracies. In particular, the Δ variations across the inertial regimes with viscous or semi-collisional effects have been further resolved, in comparison with additional analytic solutions. The results imply greater shielding of the electromagnetic torque at the layer than what would be expected by earlier work when the viscous or semi-collisional effects can compete against the inertial effects, and also due to the intermediate regulation by kinetic Alfvén wave resonances as rotation slows down. These are important features that can alter the non-axisymmetric plasma responses including the field penetration by external fields or island seeding process in rotating tokamak plasmas.

Abstract In this study, we examined the key particles and chemical reactions that substantially influence plasma characteristics. In summarizing the chemical reaction model for the discharge process of N2–O2–H2O(g) mixed gases, 65 particle types and 673 chemical reactions were investigated. On this basis, a global model of atmospheric pressure humid air discharge plasma was developed, with a focus on the variation of charged particles densities and chemical reaction rates with time under the excitation of a 0–200 Td pulsed electric field. Particles with a density greater than 1% of the electron density were classified as key particles. For such particles, the top ranking generation or consumption reactions (i.e. where the sum of their rates was greater than 95% of the total rate of the generation or consumption reactions) were classified as key chemical reactions. On the basis of the key particles and reactions identified, a simplified global model was derived. A comparison of the global model with the simplified global model in terms of the model parameters, particle densities, reaction rates (with time), and calculation efficiencies demonstrated that both models can adequately identify the key particles and chemical reactions reflecting the chemical process of atmospheric pressure discharge plasma in humid air. Thus, by analyzing the key particles and chemical reaction pathways, the charge and substance transfer mechanism of atmospheric pressure pulse discharge plasma in humid air was revealed, and the mechanism underlying water vapor molecules’ influence on atmospheric pressure air discharge was elucidated.

We calculate the contribution of deconfined spinons to inelastic neutron scattering (INS) in the fractionalized antiferromagnet (AF*), introduced elsewhere. We find that the presence of free spin-1/2 charge-less excitations leads to a continuum INS signal above the Néel gap. This signal is found above and in addition to the usual spin-1 magnon signal, which to lowest order is the same as in the more conventional confined antiferromagnet. We calculate the relative weights of these two signals and find that the spinons contribute to the longitudinal response, where the magnon signal is absent to lowest order. Possible higher-order effects of interactions between magnons and spinons in the AF* phase are also discussed.

To understand several peculiar features of d-wave superconductors such as the cuprates, we have studied a two-dimensional tight-binding (extended Hubbard) model in which the electrons interact with a potential which is attractive at nearest neighbor distance and repulsive elsewhere. Such a model is designed to produce d-wave superconductivity. It also yields antiferromagnetism and phase separation. In the two-phase region, due to vanishing compressibility the system can be easily rendered inhomogeneous by weak perturbations. Thus inhomogeneous superconductivity is a likely consequence of d-wave pairing. In addition to inhomogeneity the model also reproduces a phase diagram strikingly similar to the one observed in the cuprates. As such it throws some light on the nature of the pseudogap state.

A nanoferrite superparamagnetic system synthesized through co-precipitation method and subsequently dispersed in a medium of de-ionized water was encapsulated with a matrix polymer under constant sonication using chemical oxidative polymerization technique. The polymer coated functional microstructure thus obtained shows enhanced magnetization as evidenced from the results reported elsewhere. The magnetic core crystal growth and anti-spin canting hypothesis were given to be the most general justification behind the unusual enhancement in magnetization and more specifically the rationale could understand recently in accordance with spin injection behavior in functional core-shell microstructures. In this paper, an attempt has been made to correlate the previous magnetization results with spin injection behavior, in conjunction with the thermo gravimetric and dielectric results.

The prediction of ground state properties of atomistic systems is of vital importance in technological advances as well as in the physical sciences. Fundamentally, these predictions are based on a quantum-mechanical description of many-electron systems. One of the hitherto most prominent theories for the treatment of such systems is density functional theory (DFT). The main reason for its success is due to its balance of acceptable accuracy with computational efficiency. By now, DFT is applied routinely to compute the properties of atomic, molecular, and solid state systems. The general approach to solve the DFT equations is to use a density-functional approximation (DFA). In Kohn-Sham (KS) DFT, DFAs are applied to the unknown exchangecorrelation (xc) energy. In orbital-free DFT on the other hand, where the total energy is minimized directly with respect to the electron density, a DFA applied to the noninteracting kinetic energy is also required. Unfortunately, central DFAs in DFT fail to qualitatively capture many important aspects of electronic systems. Two prime examples are the description of localized electrons, and the description of systems where electronic edges are present. In this thesis, I use a model system approach to construct a DFA for the electron localization function (ELF). The very same approach is also taken to study the non-interacting kinetic energy density (KED) in the slowly varying limit of inhomogeneous electron densities, where the effect of electronic edges are effectively included. Apart from the work on model systems, extensions of an exchange energy functional with an improved KS orbital description are presented: a scheme for improving its description of energetics of solids, and a comparison of its description of an essential exact exchange feature known as the derivative discontinuity with numerical data for exact exchange. An emerging alternative route towards the prediction of the properties of atomistic systems is machine learning (ML). I present a number of ML methods for the prediction of solid formation energies, with an accuracy that is on par with KS DFT calculations, and with orders-of-magnitude lower computational cost.
Att kunna förutsäga egenskaper hos atomistiska system utgör en viktigdel av vår teknologiska utveckling, samt spelar en betydande roll i defysikaliska vetenskaperna. Sådana förutsägelser bygger på en kvantmekaniskbeskrivning av mångelektronsystem. En av de mest framståendeteorierna för att behandla den här typen av system är täthetsfunktionalteorin(DFT). Den främsta orsaken till dess framgång är attden lyckas kombinera skaplig noggrannhet med en bra beräkningseffektivitet.DFT används numera rutinmässigt för att beräkna storheterhos atomer, molekyler, och fasta kroppar. Generellt sett löses ekvationerna inom DFT genom att man inför entäthetsfunktionalapproximation (DFA). I Kohn-Sham (KS) DFT, användsDFAer för att approximera utbytes-korrelationsenergin. Inom orbitalfriDFT, där målet är att direkt minimera den totala energin med avseendepå elektrontätheten, så approximerar man också den icke-interageranderörelseenergin hos elektronerna. Dessvärre så fallerar många centralaDFAer att kvalitativt beskriva många viktiga aspekter hos elektronsystem.Två viktiga exempel är beskrivningen av lokaliserade elektroner,samt beskrivningen av system där det förekommer elektronytor. I denna avhandling använder jag modellsystem för att konstruera enDFAför elektronlokaliseringsfunktionen (ELF). Samma tillvägagångssättappliceras sedan för att studera den kinetiska energitätheten i gränsen avlångsamt varierande elektrontätheter, där effekten av elektronytor effektivtinkluderas. Förutom arbetet som berör modellsystem, så presenterasen utökad variant av en utbytes-energifunktional med en förbättrad KSorbitalbeskrivning: ett schema för att förbättra dess energiegenskaperför solida material, samt en jämförelse av dess beskrivning av en viktigegenskap hos den exakta utbytesenergin, vilket utgörs av diskontinuiteteri dess derivata. Ett mera nyligen uppkommet samt alternativt sätt att kunna förutsägaegenskaper hos atomistiska system utgörs av maskinlärning (ML).Jag presenterar ett antal ML-modeller för att kunna förutsäga formeringsenergierhos fasta material med en noggrannhet som är i linje medresultat som uppnås av beräkningar med hjälp av KS DFT, och med enberäkningseffektivitet som är flera storleksordningar snabbare.

Information on the sensitivity of explosives is highly valuable, and the short time scales in which chemical reactions occur in explosives, along with the ability of microstructure to have significant effects on sensitivity, often make this information difficult and expensive to acquire and interpret. Significant changes in impact and shock sensitivity are expected as a result of inducing structural damage in an explosive sample, and thermally damaged HMX-based samples can incur a solid-solid phase transition from beta to delta with non-extreme thermal inputs. Changes in sensitivity due to this phase transition, as well as the simultaneously induced damage, and their relative influence on sensitivity, are of interest to determine experimentally.

Microorganisms and drops are ubiquitous in nature: while drops can be found in sneezes, ink-jet printers, oceans etc, microorganisms are present in our stomach, intestine, soil, oceans etc. In most situations they are present in complex conditions: drop spreading on a rigid or soft substrate, drop covered with impurities that act as surfactants, marine microbe approaching a surfactant laden drop in density stratified oceanic waters in the event of an oil spill etc. In this thesis, we extract the physics underlying the influence of two such complicated effects (surfactant redistribution and density-stratification) on the motion of drops and swimming microorganisms when they are in isolation or in the vicinity of each other. This thesis is relevant in understanding the bioremediation of oil spill by marine microbes.