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In extended inflation, the inflationary era is brought to a close by the process of percolation of true vacuum bubbles produced in a first-order phase transition. This paper discusses several effects that might obtain if the universe undergoes an inflationary first-order phase transition.
Smectic liquid crystals are phases of rod shaped molecules organized into one dimensionally (1 D) periodic arrays of layers, each layer being between one and two molecular lengths thick. In the least ordered smectic phases, the smectics A and C, each layer is a two dimensional (2D) liquid. Additionally there are a variety of more ordered smectic phases having hexatic short range translational order or 2D crystalline or quasi long range translational order within the layers. The inherent fluid-layer structure and low vapor pressure of smectic liquid crystals enables the long term stabilization of freely suspended, single component, layered fluid films as thin as 30A, a single molecular layer. The layering forces the films to be an integral number of smectic layers thick, quantizing their thickness in layer units and forcing a film of a particular number of layers to be physically homogeneous with respect to its layer structure over its entire area. Optical reflectivity enables the precise determination of the number of layers. These ultrathin freely suspended liquid crystal films are structures of fundamental interest in condensed matter and fluid physics. They are the thinnest known stable fluid structures and have the largest surface-to-volume ratio of any stable fluid preparation, making them ideal for the study of the effects of reduced dimensionality on phase behavior and on fluctuation and interface phenomena. Their low vapor pressure and quantized thickness enable the effective use of microgravity to extend the study of basic capillary phenomena to ultrathin fluid films. Freely suspended films have been a wellspring of new LC physics. They have been used to provide unique experimental conditions for the study of condensed phase transitions in two dimensions. They are the only system in which the hexatic has been unambiguously identified as a phase of matter, and the only physical system in which fluctuations of a 2D XY system and Kosterlitz Thouless phase transition has been observed and 2D XY quasi long range order verified. Smectic films have enabled the precise determination of smectic layer electron density and positional fluctuation profiles and have been used to show that the interlayer interactions in antiferroelectric tilted smectics do not extend significantly beyond nearest neighbors. Freely suspended films played a pivotal role in the recent discovery of macroscopic chiral-polar ordering in fluids of achiral molecules. The interactions which are operative in liquid crystals are generally weak in comparison to those in crystalline phases, leading to the facile manipulation of the order in liquid crystals by external agents such as applied fields and surfaces. Effects arising from weak ordering are significantly enhanced in ultrathin free films and filaments, in which the intermolecular coupling is effectively further reduced by loss of neighbors. Over the past four years this research, which we now detail, has produced a host of exciting new discoveries and unexpected results, maintaining the study of freely suspended liquid crystal structures as one of most exciting and fruitful areas of complex fluid physics. In addition, a class of experiments on the behavior of 1D interfaces in 2D films have been pursued with results that point to potentially quite interesting effects in microgravity.
Temperatures of CaAl2Si2O8 (anorthite glass) shocked to pressures between 48 and 117 GPa were measured in the range from 2500 to 5600 K, using optical pyrometry techniques. The pressure dependence of the shock temperatures deviates significantly from predictions based on a single high pressure phase. At least three phase transitions, at pressures of about 55, 85, and 100 GPa and with transition energies of about 0.5 MJ/kg each (approximately 1.5 MJ/kg total) are required to explain the shock temperature data. The phase transition at 100 GPa can possibly be identified with the stishovite melting transition. Theoretical models of the time dependence of the thermal radiation from the shocked anorthite based on the geometry of the experiment and the absorptive properties of the shocked material yields good agreement with observations, indicating that it is not necessary to invoke intrinsic time dependences to explain the data in many cases.
A scalar Higgs field can be repeatedly switched on and off when it couples to a classically oscillating scalar modulus field. The modulus flips the Higgs mass term between stable and tachyonic values. We study a cosmological scenario in which such repeated phase transitions occur during inflation. An irrelevant operator coupling the Higgs field to the inflaton can then imprint the pattern of phase transitions in the correlation functions of the inflaton. Using both numerical and analytic studies, we show that the inflaton 2-point function carries characteristic imprints of the modulus oscillation and its effect on the Higgs boson. We briefly remark on the potential observability of such patterns and how they might be distinguished from other dynamics in the early universe.
P Cygni is currently in the transition phase between core hydrogen and helium burning. The behavior of the stellar envelope in this phase is strongly affected by the intermittant dominance of hydrogen shell burning. We perform detailed stellar evolution calculations of this rapid transition phase using the most recent Livermore opacities. We find that observations and stellar evolution models agree very well if the initial main-sequence mass of P Cygni was about 60 +/- 5 solar masses. Depending on the mass-loss rate, P Cygni's current mass could be as low as 50 solar masses, which is still about a factor of 2 higher than that predicted by the radiation driven wind theory. Our calculations seem to favor the Schwarzschild criterion for convection over the Ledoux criterion in conjunction with semiconvection.
Dielectrics with a high and weakly- temperature-dependent permittivity are highly desirable for the development of high performance energy storage devices. It is well known that ferroelectrics (FEs) exhibit a high permittivity that is strongly dependent on the temperature due to phase transition. In this project, the FE BaTiO3 (BTO), based ceramics are developed as ultra-capacitors by introducing defects to eliminate the phase transition and enhance the permittivity. The ceramics are fabricated using a unique process: BTO nanoparticles are coated with a nano-layer of SiO2 and, then, sintered in vacuum using SPS process. The ceramics exhibit a giant permittivity and many other unique properties.
Under the application of a sufficiently strong electric field, a suspension may undergo reversible phase transitions from a homogeneous random arrangement of particles into a variety of ordered aggregation patterns. The surprising fact about electric-field driven phase transitions is that the aggregation patterns, that are observed in very diverse systems of colloids, display a number of common structural features and modes of evolution thereby implying that a universal mechanism may exist to account for these phenomena. It is now generally believed that this mechanism emanates from the presence of the long-range anisotropic interactions between colloidal particles due to their polarization in an applied field. But, in spite of numerous applications of the electric-field-driven phenomena in biotechnology, separation, materials engineering, chemical analysis, etc. our understanding of these phenomena is far from complete. Thus, it is the purpose of the proposed research to develop a theory and then test experimentally, under normal- and low-gravity conditions, the accuracy of the theoretical predictions regarding the effect of the synergism of the interparticle electric and hydrodynamic interactions on the phase diagram of a suspension. The main results from our theoretical studies performed to-date enable one to trace how the variations of the electrical properties of the constituent materials influence the topology of the suspension phase diagram and then, by using an appropriate phase diagram, to evaluate how the electric-field-induced transformations will depend on the frequency and the strength of the applied field.
The national airspace has evolved over many years to accommodate increased traffic demand while simultaneously maintaining air travel as one of the safest forms of transportation. One of the reasons for this success is the ability of the air traffic control system and the operators to adapt and accommodate to situations that routinely disrupt normal operations. These situations may include: adverse weather, delays, early arrivals, equipment outages, and other factors that are outside the operators’ ability to control. These factors can lead to states where automation is unable to properly handle these issues, and therefore air traffic controllers and pilots have to intervene — ultimately increasing communication between operators resulting in higher workload. As controller workload increases to handle sub-optimal operating conditions, complexity increases. This is because, under these conditions humans are required to make tactical decisions in response to external factors. This results in a departure from the original strategic plan where operations would be more efficiently managed. Human operators manage airspace complexity under rigid regulations but in a constantly changing environment. The airspace is divided into sectors and the number of aircraft assigned to each controller is limited for safe handling. Some prior studies devised airspace complexity metrics in commercial aviation and related these metrics to controller workload. The upper bounds on the system load are pre-determined. Such bounds on complexity make for a safe system, but the system cannot scale and adapt to autonomous, dense, and heterogeneous traffic — including the many types of Unmanned Aerial Vehicles (UAVs) envisioned to be added to the operations. We hypothesize that, as traffic density and heterogeneity grow, and other key metrics change, there will be phase transitions at which the way traffic should be managed changes significantly. We offer a method for in-time detection of contributing factors that lead to phase transitions, characterized by increased complexity. To the best of our knowledge, there is no tool similar to ours that identifies such contributing factors or precursor patterns.
The national airspace has evolved over many years to accommodate increased traffic demand [1] while simultaneously maintaining one of the safest forms of transportation [2], [3]. One of the reasons for this success is the ability of the system and the operators to adapt and accommodate to situations that routinely disrupt optimal operations. These situations may include: adverse weather, delays, early arrivals, equipment outages, and other factors that are outside the operators ability to control. These factors can lead to states where automation is unable to properly handle these issues and therefore air traffic controllers and pilots have to intervene, ultimately increasing communication between operators resulting in higher workload. As controller workload increases to handle sub-optimal operating conditions this can be viewed as an increase in complexity. The reasoning for this is because humans are now required to make tactical decisions in response to external factors, resulting in a departure from the strategic plan where operations would be more efficiently managed. Human operators control airspace complexity under rigid regulations that are constantly changing. The airspace is divided into sectors and the number of aircraft assigned to each controller is limited for safe handling. There has been past work that devised airspace complexity metrics in commercial aviation and related these metrics to controller workload (e.g., [4],[5]). The upper bounds on the system load are pre-determined. Such bounds on complexity make for a safe system, but the system cannot scale and adapt to autonomous, dense, and heterogeneous traffic, including the many types of Unmanned Aerial Vehicles (UAVs) envisioned to be added to the operations. We hypothesize that, as traffic density and heterogeneity grow, and other key metrics change, there will be phase transitions at which the way traffic should be managed changes significantly [6]. We offer a method for in-time detection of contributing factors that lead to phase transitions, characterized by increased complexity. To the best of our knowledge, there is no tool similar to our proposed effort that identifies such contributing factors or precursor patterns. To define the scope we are proposing to measure complexity from the viewpoint of the Terminal Radar Approach Control Facilities (TRACON) controller’s perspective. In particular we are analyzing arrivals into KSFO. With safety as the top concern for airspace operators, it is important to recognize that as density and heterogeneity grow, the focus of the system will change. Times of the day when the airspace has low density and heterogeneity, the flights will follow more efficient paths where the aircraft move on established routes that are more or less directly to the destination. However, when density and heterogeneity increases, the system will begin changing focus to avoiding conflicts and collisions and route the flights in a more flexible way. Higher flexibility requires more communication and coordination between controllers and pilots which the current automation is unable to handle. This paper proposes a novel approach that monitors airspace complexity at multiple scales, uses a Machine Learning-based tool that predicts when operations will transition to a regime of greater complexity, and identifies actions that can reduce the complexity while still maintaining efficient and safe operations. We demonstrate our proposed approach using data from multiple complementary sources. This includes, but is not limited to: historical aircraft surveillance data from NASA’s Sherlock Data Warehouse [7], METAR weather data, and airport configuration data from Aviation System Performance Metrics (ASPM). The surveillance data flight paths are sampled at a variable sample rate — increasing as the aircraft approaches the airport. This is due to how Sherlock manages flight track stitching between different radar facilities which have different sampling rates. The weather and performance data are logged at defined intervals throughout the day at a courser refresh rate. In addition to the logged data and metrics, we leverage pre-defined Standard Terminal Arrival Routes (STARs) procedures to characterize the path of each flight. Each flight files for one of these routes in the flight plan well before entering the terminal airspace, and approximately follows the route until it leaves the STAR, typically on the final fix of a runway transition. However, most flights do not always fly the full STAR procedure to completion [8], but the majority do adhere to the fixes within the common route of the procedure. Our approach leverages fixes in the common route of each of the STARs to build a reference path to the airport. This allows us to characterize the flight paths in what we are defining as the “maneuvering area” (the airspace between the STAR and before the flight is lined up on the runway’s final approach) to determine how off nominal the flights are to calculate its complexity score. Determining airspace complexity is a concept that does not have a concrete answer. In designing this metric, we consider what increases the workload for the air traffic controllers. Consequently more specialized vectoring maneuvers results in higher workload. Accordingly, we start with a theory: each flight has a direct path it takes from the STAR’s common route to the final approach’s outer marker fix for the flight’s landing runway. It is important to note that the direct path is only used as a reference. If the majority of the flights have a large consistent offset as compared to other routes it does not necessarily mean that those flights have higher complexity. We are merely building a distribution based on this direct path for that particular STAR and runway pair to determine the normal mode of operations for that route. Flights that are in the upper tail of these distributions will result in higher complexity scores and flights that fly in the median will represent the normal mode of operations and therefore will have lower complexity scores. Since flights following each STAR route take different paths to the airport, we have a different distribution for each STAR route and therefore can model these distributions to compute a complexity score from their respective normalized distributions. To evaluate the effectiveness of our proposed airspace complexity metric we will compare against an established approach based on trajectory clustering [9]. This unsupervised learning technique consists of the following steps: (1) identify the general maneuvering areas (waypoints) by performing $\kappa$-means or DBSCAN clustering on locations where aircraft frequently turn based on the surveillance radar track data, (2) map flight trajectories onto sequences of waypoints, and (3) cluster the sequences based on their common subsequences. From a high-level perspective, this baseline model learns nominal operations in the airspace through the sequence of waypoints that are representative of where aircraft change direction and defines deviations from the nominal operations as “complex.” Therefore, more deviations from the nominal operations correspond to higher complexity values. For our validation, we re-implemented this technique and tune model hyper-parameters to correctly detect waypoints for the arrival traffic into the San Francisco bay area. We will compute the complexity measure over a one-year period using our proposed technique as well as the baseline. Our validation will be based on each technique’s ability to detect a set of undesirable outcomes (e.g., go-arounds, holding patterns, average time in the airspace, etc.). Since our current complexity metric is derived from the offset from the direct reference path, it’s important to understand what causes these offsets. In many of the flights with high offset distance, flights performing holding patterns and S turns can be observed. These maneuvering tactics are utilized to add distance between the aircraft and the destination runway to prevent multiple flights from having conflicting arrival times. In order to predict a rise in complexity (or the precursor to complexity), it’s necessary to be able to identify these potential conflicts (which in turn, result in higher offsets). To do this, we define a “representative flight” for each STAR route and runway pair. This flight is approximately the path the flight would take if there was a clear path with no other flights in the airspace — including the time remaining to the airport. We first identify the flights for a given STAR runway pair using the offset to the reference path distributions that fall between the 44-55 percentiles. This yields the flights that conform to the most normal mode of operation. Each of these flights is partitioned based on the percent complete from the entry point into the maneuvering areas from 0\% – 100\% complete. Then for each percent “bin”, we take the median value of the flight’s latitude/longitude coordinates, airspeed, and (non causal) time remaining to the airport to construct a lookup table for each percent complete bin on a given route. As a flight enters the maneuvering area, we can find the estimated arrival time of a flight to the airport by finding the closest point to the representative path’s percent complete bin (relative to the flight’s current position at any snapshot in the airspace) and therefore retrieve the corresponding remaining time left on the “representative path”. We assume that the flight will follow the representative path to completion when deriving these estimates. We can then compare these estimated arrival times against other flights for the same snapshot in time to identify potential conflicts. If more flights are estimated to arrive within a tolerance window than there are runways available, then we have a potential conflict. We can use this derived measure along with other factors expected to add disruption to the operation such as weather and runway configuration changes as an input to machine learning tools to detect precursors that increases in our complexity measure. This novel method will assist in uncovering insights into the contributing factors that lead to increased complexity that may allow for in-time responses to avoid reaching a high complexity state in the airspace.
The recent work with partially miscible binary liquid mixtures has established that the structure of the liquid-vapor interface can undergo a first-order phase transition from incomplete to complete wetting of the vapor as the temperature is raised. A discontinuity in the change of interfacial tension as a function of temperature at the phase transition has been predicted to occur in many systems and to play an important role in the growth of uniform composites from alloy melts at monotectic points. These measurements are the first to establish the order of the transition. Studies of capillary rise in SF6 in a unique interferometer have led to the first measurements of the thickness of wetting layers (or equivalently, multilayer adsorbed films) on a solid surface near a liquid-vapor critical point. Instabilities in wetting layers were observed. A theory for the instabilities is being developed and will be checked by both static and dynamic optical experiments. The effect of gravity on the apparent thickness of interfaces (as measured by ellipsometry) is under study.
LARC-TPI, a thermoplastic polyimide, has been studied in order to develop an understanding of its crystalline phase transition. Our experiments suggest that samples synthesized in different laboratories apparently had different degrees of imidization and their thermal behaviors differed accordingly. When the most crystalline of these polyimides was studied in some detail, we found that it melted irreversibly in that once a sample was completely melted it would not recrystallize. A polymer that did not recrystallize displayed a glass transition, which increased in temperature upon subsequent cooling and reheating. Solubility experiments indicated that heating above the crystalline melting temperature led to network formation in the polymer, a conclusion that is consistent with other behavior just mentioned. Differential calorimetric studies revealed that annealing at slow heating rates or under isothermal conditions resulted in dual melting transitions. These studies, supported by X-ray diffraction results, strongly indicate that the annealing process involves a solid-liquid-solid transformation. From an existing phenomenological model for the kinetics of phase transitions, kinetic parameters for these crystallizations have been evaluated. The Avrami exponents n increased with the annealing temperature in the protocol used in this study. Their values were about 2 or lower, thus indicating that crystallization may have followed a mechanism that included heterogeneous nucleation of a low dimensional order in which all the embryonic crystallites formed at the beginning of the process. A positive temperature coefficient for these crystallizations indicated that diffusion may have had a rate controlling influence and affected the values of n.
The type III radio bursts are the most intense radio emissions from the sun. In Figure 1, we present a typical type III burst observed by the STEREO spacecraft. Ginzburg and Zheleznyakov (1958) were the first to suggest that Langmuir waves excited by the solar flare accelerated electrons are the source of these bursts. The in situ detection of electron beams and Langmuir waves in association with type III bursts together with tracking of type III burst sources in the interplanetary medium confirmed this plasma hypothesis. However, the dynamics of type III electron beams and their interaction with the ambient plasma through the excited Langmuir waves is an unsolved problem. In order that the electron beams don't lose their energy by resonantly interacting with Langmuir waves, various nonlinear processes, such as the induced scattering of Langmuir waves off the background ions in weak turbulence regime and oscillating two-stream instability in strong turbulence regime were invoked. However, the observed electron density fluctuations do not allow Langmuir waves to grow to very high intensities as pointed out by several authors. As far as the conversion of Langmuir wave energy into electromagnetic energy is concerned, there is no consensus either for the fundamental or for the second harmonic emission. In this paper, we address these issues in terms of critical fluctuations near the boundary of the beam-plasma instability which is analogous to the anomalously growing fluctuations near the phase transition points called critical points. We show that this phenomenon can account for the survival of electron beams over large distances as well as the intensities of Langmuir waves excited during this phase transition regime are sufficient to explain the peak intensities of the fundamental as well as harmonic emissions
Bismuth tri-iodide (BiI3) have been grown by physical vapor transport (PVT), and by the Bridgman (melt) method. These crystals along with pure and stoichiometric BiI3 powder have been investigated by differential scanning calorimetry (DSC). The DSC results show that pure BiI3 powder has no phase transition and melts around 408 C. While we found no evidence for the high temperature dissociation of BiI3, the DSC measurements show that crystals grown from melt method contain a significantly large amount of Bi-rich phases than crystals grown from PVT method, as indicated by phase transition detected at 270, 285, 298 and 336 C.
Some of the cosmological consequences are discussed of a late time phase transition which produces light domain walls. The observed peculiar velocity field of the Universe and the observed isotropy of the microwave background radiation severely constrain the wall surface density in such a scenario. The most interesting consequence of such a phase transition is the possibility that the local, coherent streaming motion reported by the Seven Samurai could be explained by the repulsive effect of a relic domain wall with the Hubble volume (the Great Wall).
A universal detection system based on allosteric aptamers, signal amplification cascade, and eye-detectable phrase transition. A broadly applicable homogeneous detection system is provided. It utilizes components of the blood coagulation cascade in the presence of polystyrene microspheres (MS) as a signal amplifier. Russell's viper venom factor X activator (RVV-X) triggers the cascade, which results in an eye-visible phase transition--precipitation of MS bound to clotted fibrin. An allosteric RNA aptamer, RNA132, with affinity for RVV-X and human vascular endothelial growth factor (VEGF.sub.165) was created. RNA132 inhibits enzymatic activity of RVV-X. The effector molecule, VEGF.sub.165, reverses the inhibitory activity of RNA132 on RVV-X and restores its enzymatic activity, thus triggering the cascade and enabling the phase transition. Similar results were obtained for another allosteric aptamer modulated by a protein tyrosine phosphatase. The assay is instrumentation-free for both processing and readout.
The high pressure structural phase transition in Ge has been studied using the energy dispersive X-ray diffraction technique and a synchrotron radiation source. Ge was observed to transform to the beta-Sn tetragonal structure in agreement with the earlier results of Jamieson, but the phase transition began at 80 + or - 5 kilobars, a somewhat lower value than generally reported. These experimental diffraction results are compared with the recent self-consistent pseudopotential calculations of Yin and Cohen (1981) and with the observed transition pressure for shock wave loaded Ge.
It is shown that the presence of a phase transition early in the history of the universe, associated with spontaneous symmetry breaking (believed to take place at very high temperatures at which the various fundamental interactions unify), significantly modifies its dynamics and evolution. This is due to the energy 'pumping' during the phase transition from the vacuum to the substance, rather than the gravitating effects of the vacuum. The expansion law of the universe then differs substantially from the relation considered so far for the very early time expansion. In particular it is shown that under certain conditions this expansion law is exponential. It is further argued that under reasonable assumptions for the mass of the associated Higgs boson this expansion stage could last long enough to potentially account for the observed isotropy of the universe.
Raman spectra & photoluminescence studies in PbTiO3, have been carried out, as a function of particle size, temperature, pressure and dopants. There appears respectively a distinct temperature-induced soft mode phase transition in each sample whose Curie temperature can be determined from the mean-field theory. The detailed Curie temperature shift in the modified PbTiO3 ceramics by Ba, Sr, La and Zr, has been investigated as a function of particle size. Pressure-induced phase transitions display an obvious diffuse behavior. Room temperature photoluminescence for nanocrystalline Ba(1-x)Pb(x)TiO3 have been observed. These studies favor preparations of high efficiency PbTiO3 sensors.