Instituto Tecnológico de Aeronáutica

Abstract Semiconductors are the basis of many vital technologies such as electronics, computing, communications, optoelectronics, and sensing. Modern semiconductor technology can trace its origins to the invention of the point contact transistor in 1947. This demonstration paved the way for the development of discrete and integrated semiconductor devices and circuits that has helped to build a modern society where semiconductors are ubiquitous components of everyday life. A key property that determines the semiconductor electrical and optical properties is the bandgap. Beyond graphene, recently discovered two-dimensional (2D) materials possess semiconducting bandgaps ranging from the terahertz and mid-infrared in bilayer graphene and black phosphorus, visible in transition metal dichalcogenides, to the ultraviolet in hexagonal boron nitride. In particular, these 2D materials were demonstrated to exhibit highly tunable bandgaps, achieved via the control of layers number, heterostructuring, strain engineering, chemical doping, alloying, intercalation, substrate engineering, as well as an external electric field. We provide a review of the basic physical principles of these various techniques on the engineering of quasi-particle and optical bandgaps, their bandgap tunability, potentials and limitations in practical realization in future 2D device technologies.

Extensive systematizations of theoretical and experimental nuclear densities and of optical potential strengths extracted from heavy-ion elastic scattering data analyses at low and intermediate energies are presented. The energy dependence of the nuclear potential is accounted for within a model based on the nonlocal nature of the interaction. The systematics indicates that the heavy-ion nuclear potential can be described in a simple global way through a double-folding shape, which basically depends only on the density of nucleons of the partners in the collision. The possibility of extracting information about the nucleon-nucleon interaction from the heavy-ion potential is investigated.

Cloud research to date has lacked data on the characteristics of the production virtual machine (VM) workloads of large cloud providers. A thorough understanding of these characteristics can inform the providers' resource management systems, e.g. VM scheduler, power manager, server health manager. In this paper, we first introduce an extensive characterization of Microsoft Azure's VM workload, including distributions of the VMs' lifetime, deployment size, and resource consumption. We then show that certain VM behaviors are fairly consistent over multiple lifetimes, i.e. history is an accurate predictor of future behavior. Based on this observation, we next introduce Resource Central (RC), a system that collects VM telemetry, learns these behaviors offline, and provides predictions online to various resource managers via a general client-side library. As an example of RC's online use, we modify Azure's VM scheduler to leverage predictions in oversubscribing servers (with oversubscribable VM types), while retaining high VM performance. Using real VM traces, we then show that the prediction-informed schedules increase utilization and prevent physical resource exhaustion. We conclude that providers can exploit their workloads' characteristics and machine learning to improve resource management substantially.

Weight reduction and improved damage tolerance characteristics were the prime drivers to develop new family of materials for the aerospace/aeronautical industry. Aiming this objective, a new lightweight Fiber/Metal Laminate (FML) has been developed. The combination of metal and polymer composite laminates can create a synergistic effect on many properties. The mechanical properties of FML shows improvements over the properties of both aluminum alloys and composite materials individually. Due to their excellent properties, FML are being used as fuselage skin structures of the next generation commercial aircrafts. One of the advantages of FML when compared with conventional carbon fiber/epoxy composites is the low moisture absorption. The moisture absorption in FML composites is slower when compared with polymer composites, even under the relatively harsh conditions, due to the barrier of the aluminum outer layers. Due to this favorable atmosphere, recently big companies such as EMBRAER, Aerospatiale, Boing, Airbus, and so one, starting to work with this kind of materials as an alternative to save money and to guarantee the security of their aircrafts.

The kinetic model for change of phases developed by M. Avrami at the end of the thirties has been used to describe the temporal behavior of phase changes. Until today this model is studied and adapted to include broader hypotheses. However, the mathematical format presented by M. Avrami is difficult to be understood by beginners. The purpose of this work is to clarify the mathematical treatment of Avrami's work, going straightforward to the arguments that led to his main results.

The local-density approximation (LDA) together with the half occupation (transition state) is notoriously successful in the calculation of atomic ionization potentials. When it comes to extended systems, such as a semiconductor infinite system, it has been very difficult to find a way to half ionize because the hole tends to be infinitely extended (a Bloch wave). The answer to this problem lies in the LDA formalism itself. One proves that the half occupation is equivalent to introducing the hole self-energy (electrostatic and exchange correlation) into the Schr\"odinger equation. The argument then becomes simple: The eigenvalue minus the self-energy has to be minimized because the atom has a minimal energy. Then one simply proves that the hole is localized, not infinitely extended, because it must have maximal self-energy. Then one also arrives at an equation similar to the self-interaction correction equation, but corrected for the removal of just 1/2 electron. Applied to the calculation of band gaps and effective masses, we use the self-energy calculated in atoms and attain a precision similar to that of GW, but with the great advantage that it requires no more computational effort than standard LDA.

Four distinct meteorological regimes in the Amazon basin have been examined to distinguish the contributions from boundary layer aerosol and convective available potential energy (CAPE) to continental cloud structure and electrification. The lack of distinction in the electrical parameters (peak flash rate, lightning yield per unit rainfall) between aerosol‐rich October and aerosol‐poor November in the premonsoon regime casts doubt on a primary role for the aerosol in enhancing cloud electrification. Evidence for a substantial role for the aerosol in suppressing warm rain coalescence is identified in the most highly polluted period in early October. The electrical activity in this stage is qualitatively peculiar. During the easterly and westerly wind regimes of the wet season, the lightning yield per unit of rainfall is positively correlated with the aerosol concentration, but the electrical parameters are also correlated with CAPE, with a similar degree of scatter. Here cause and effect are difficult to establish with available observations. This ambiguity extends to the “green ocean” westerly regime, a distinctly maritime regime over a major continent with minimum aerosol concentration, minimum CAPE, and little if any lightning.

Background: The microscopic composition and properties of infinite hadronic matter at a wide range of densities and temperatures have been subjects of intense investigation for decades. The equation of state (EoS) relating pressure, energy density, and temperature at a given particle number density is essential for modeling compact astrophysical objects such as neutron stars, core-collapse supernovae, and related phenomena, including the creation of chemical elements in the universe. The EoS depends not only on the particles present in the matter, but, more importantly, also on the forces acting among them. Because a realistic and quantitative description of infinite hadronic matter and nuclei from first principles in not available at present, a large variety of phenomenological models has been developed in the past several decades, but the scarcity of experimental and observational data does not allow a unique determination of the adjustable parameters.Purpose: It is essential for further development of the field to determine the most realistic parameter sets and to use them consistently. Recently, a set of constraints on properties of nuclear matter was formed and the performance of 240 nonrelativistic Skyrme parametrizations was assessed [M. Dutra et al., Phys. Rev. C 85, 035201 (2012)] in describing nuclear matter up to about three times nuclear saturation density. In the present work we examine 263 relativistic-mean-field (RMF) models in a comparable approach. These models have been widely used because of several important aspects not always present in nonrelativistic models, such as intrinsic Lorentz covariance, automatic inclusion of spin, appropriate saturation mechanism for nuclear matter, causality, and, therefore, no problems related to superluminal speed of sound in medium.Method: Three different sets of constraints related to symmetric nuclear matter, pure neutron matter, symmetry energy, and its derivatives were used. The first set (SET1) was the same as used in assessing the Skyrme parametrizations. The second and third sets (SET2a and SET2b) were more suitable for analysis of RMF and included, up-to-date theoretical, experimental and empirical information.Results: The sets of updated constraints (SET2a and SET2b) differed somewhat in the level of restriction but still yielded only 4 and 3 approved RMF models, respectively. A similarly small number of approved Skyrme parametrizations were found in the previous study with Skyrme models. An interesting feature of our analysis has been that the results change dramatically if the constraint on the volume part of the isospin incompressibility $({K}_{\ensuremath{\tau},\mathrm{v}})$ is eliminated. In this case, we have 35 approved models in SET2a and 30 in SET2b.Conclusions: Our work provides a new insight into application of RMF models to properties of nuclear matter and brings into focus their problematic proliferation. The assessment performed in this work should be used in future applications of RMF models. Moreover, the most extensive set of refined constraints (including nuclear matter and finite-nuclei-related properties) should be used in future determinations of new parameter sets to provide models that can be used with more confidence in a wide range of applications. Pointing to reasons for the many failures, even of the frequently used models, should lead to their improvement and to the identification of possible missing physics not included in present energy density functionals.

Understanding the properties of electronically excited states is a challenging task that becomes increasingly important for numerous applications in chemistry, molecular physics, molecular biology, and materials science. A substantial impact is exerted by the fascinating progress in time-resolved spectroscopy, which leads to a strongly growing demand for theoretical methods to describe the characteristic features of excited states accurately. Whereas for electronic ground state problems of stable molecules the quantum chemical methodology is now so well developed that informed nonexperts can use it efficiently, the situation is entirely different concerning the investigation of excited states. This review is devoted to a specific class of approaches, usually denoted as multireference (MR) methods, the generality of which is needed for solving many spectroscopic or photodynamical problems. However, the understanding and proper application of these MR methods is often found to be difficult due to their complexity and their computational cost. The purpose of this review is to provide an overview of the most important facts about the different theoretical approaches available and to present by means of a collection of characteristic examples useful information, which can guide the reader in performing their own applications.

There is growing interest in biodegradable polymers (BP), in particular poly(butylene adipate‐ co ‐terephthalate) (PBAT), due to environmental problems associated with the disposal of non‐biodegradable polymers into the environment. However, high production cost and low thermo‐mechanical properties restrict the use of this sustainable material, making its biodegradability advantageous only when it is decisively required. The addition of different compositions of monomers and selective addition of natural fillers have been reported as alternatives to develop more accessible PBAT‐based bioplastics with performance that could match or even exceed that of the most widely used commodity plastics. This review explores the recent progress of the applications and biodegradation of PBAT. The addition of natural fillers and its effect on the final performance of the PBAT‐based composites is also reported with respect to improving the properties of composites. The advance of polymerization reaction engineering combined with sustainable trend offers great opportunities for innovative green chemical manufacturing. POLYM. ENG. SCI., 59:E7–E15, 2019. © 2017 Society of Plastics Engineers

Abstract. Aerosol particle number size distributions and hygroscopic properties were measured at a pasture site in the southwestern Amazon region (Rondonia). The measurements were performed 11 September-14 November 2002 as part of LBA-SMOCC (Large scale Biosphere atmosphere experiment in Amazonia - SMOke aerosols, Clouds, rainfall and Climate), and cover the later part of the dry season (with heavy biomass burning), a transition period, and the onset of the wet period. Particle number size distributions were measured with a DMPS (Differential Mobility Particle Sizer, 3-850nm) and an APS (Aerodynamic Particle Sizer), extending the distributions up to 3.3 µm in diameter. An H-TDMA (Hygroscopic Tandem Differential Mobility Analyzer) measured the hygroscopic diameter growth factors (Gf) at 90% relative humidity (RH), for particles with dry diameters (dp) between 20-440 nm, and at several occasions RH scans (30-90% RH) were performed for 165nm particles. These data provide the most extensive characterization of Amazonian biomass burning aerosol, with respect to particle number size distributions and hygroscopic properties, presented until now. The evolution of the convective boundary layer over the course of the day causes a distinct diel variation in the aerosol physical properties, which was used to get information about the properties of the aerosol at higher altitudes. The number size distributions averaged over the three defined time periods showed three modes; a nucleation mode with geometrical median diameters (GMD) of ~12 nm, an Aitken mode (GMD=61-92 nm) and an accumulation mode (GMD=128-190 nm). The two larger modes were shifted towards larger GMD with increasing influence from biomass burning. The hygroscopic growth at 90% RH revealed a somewhat external mixture with two groups of particles; here denoted nearly hydrophobic (Gf~1.09 for 100 nm particles) and moderately hygroscopic (Gf~1.26). While the hygroscopic growth factors were surprisingly similar over the periods, the number fraction of particles belonging to each hygroscopic group varied more, with the dry period aerosol being more dominated by nearly hydrophobic particles. As a result the total particle water uptake rose going into the cleaner period. The fraction of moderately hygroscopic particles was consistently larger for particles in the accumulation mode compared to the Aitken mode for all periods. Scanning the H-TDMA over RH (30-90% RH) showed no deliquescence behavior. A parameterization of both Gf(RH) and Gf(dp), is given.

Selective Laser melting (SLM) is an additive manufacturing technology that uses laser as a power source to sinter powdered metals to produce solid structures. The application of SLM permits engineers to develop and implement components with topologically optimized designs and resultant material properties in comparison to conventionally produced casting parts. Current aviation programs as ACARE 2020 (Advisory Council for Aviation Research and Innovation in the EU) and Flightpath 2050 request a reduction of fuel consumption as well as CO2 and NOx emissions in the next years. To meet these requirements there is a clear trend to produce light-weight components for engines and structural parts of aircrafts through SLM. Since SLM process is a key technology for aeronautical application, this paper focusses on the qualification of a high performance titanium alloy as well as on the investigation of optimized process parameters and positioning strategies of the structures produced in the SLM machine.

This paper presents an overview of the results from the first major mesoscale atmospheric campaign of the Large‐Scale Biosphere‐Atmosphere Experiment in Amazonia (LBA) Program. The campaign, collocated with a Tropical Rainfall Measuring Mission (TRMM) satellite validation campaigns, was conducted in southwest Rondônia in January and February 1999 during the wet season. Highlights on the interaction between clouds, rain, and the underlying landscape through biospheric processes are presented and discussed.

In this article we study the hydrostatic equilibrium configuration of neutron stars and strange stars, whose fluid pressure is computed from the equations of state $p=\omega\rho^{5/3}$ and $p=0.28(\rho-4{\cal B})$, respectively, with $\omega$ and ${\cal B}$ being constants and $\rho$ the energy density of the fluid. We start by deriving the hydrostatic equilibrium equation for the $f(R,T)$ theory of gravity, with $R$ and $T$ standing for the Ricci scalar and trace of the energy-momentum tensor, respectively. Such an equation is a generalization of the one obtained from general relativity, and the latter can be retrieved for a certain limit of the theory. For the $f(R,T)=R+2\lambda T$ functional form, with $\lambda$ being a constant, we find that some physical properties of the stars, such as pressure, energy density, mass and radius, are affected when $\lambda$ is changed. We show that for a fixed central star energy density, the mass of neutron and strange stars can increase with $\lambda$. Concerning the star radius, it increases for neutron stars and it decreases for strange stars with the increment of $\lambda$. Thus, in $f(R,T)$ theory of gravity we can push the maximum mass above the observational limits. This implies that the equation of state cannot be eliminated if the maximum mass within General Relativity lies below the limit given by observed pulsars.

With the widespread adoption of deep learning, reinforcement learning (RL) has experienced a dramatic increase in popularity, scaling to previously intractable problems, such as playing complex games from pixel observations, sustaining conversations with humans, and controlling robotic agents. However, there is still a wide range of domains inaccessible to RL due to the high cost and danger of interacting with the environment. Offline RL is a paradigm that learns exclusively from static datasets of previously collected interactions, making it feasible to extract policies from large and diverse training datasets. Effective offline RL algorithms have a much wider range of applications than online RL, being particularly appealing for real-world applications, such as education, healthcare, and robotics. In this work, we contribute with a unifying taxonomy to classify offline RL methods. Furthermore, we provide a comprehensive review of the latest algorithmic breakthroughs in the field using a unified notation as well as a review of existing benchmarks' properties and shortcomings. Additionally, we provide a figure that summarizes the performance of each method and class of methods on different dataset properties, equipping researchers with the tools to decide which type of algorithm is best suited for the problem at hand and identify which classes of algorithms look the most promising. Finally, we provide our perspective on open problems and propose future research directions for this rapidly growing field.

The very old and successful density-functional technique of half-occupation is revisited [J. C. Slater, Adv. Quant. Chem. 6, 1 (1972)]. We use it together with the modern exchange-correlation approximations to calculate atomic ionization energies and band gaps in semiconductors [L. G. Ferreira et al., Phys. Rev. B 78, 125116 (2008)]. Here we enlarge the results of the previous paper, add to its understandability, and show when the technique might fail. Even in this latter circumstance, the calculated band gaps are far better than those of simple LDA or GGA. As before, the difference between the Kohn-Sham ground state one-particle eigenvalues and the half-occupation eigenvalues is simply interpreted as the self-energy (not self-interaction) of the particle excitation. In both cases, that of atomic ionization energies and semiconductor band gaps, the technique is proven to be very worthy, because not only the results can be very precise but the calculations are fast and very simple.

Abstract We study the velocity fields of unforced, high Reynolds number, subsonic jets, issuing from round nozzles with turbulent boundary layers. The objective of the study is to educe wavepackets in such flows and to explore their relationship with the radiated sound. The velocity field is measured using a hot-wire anemometer and a stereoscopic, time-resolved PIV system. The field can be decomposed into frequency and azimuthal Fourier modes. The low-angle sound radiation is measured synchronously with a microphone ring array. Consistent with previous observations, the azimuthal wavenumber spectra of the velocity and acoustic pressure fields are distinct. The velocity spectrum of the initial mixing layer exhibits a peak at azimuthal wavenumbers $m$ ranging from 4 to 11, and the peak is found to scale with the local momentum thickness of the mixing layer. The acoustic pressure field is, on the other hand, predominantly axisymmetric, suggesting an increased relative acoustic efficiency of the axisymmetric mode of the velocity field, a characteristic that can be shown theoretically to be caused by the radial compactness of the sound source. This is confirmed by significant correlations, as high as 10 %, between the axisymmetric modes of the velocity and acoustic pressure fields, these values being significantly higher than those reported for two-point flow–acoustic correlations in subsonic jets. The axisymmetric and first helical modes of the velocity field are then compared with solutions of linear parabolized stability equations (PSE) to ascertain if these modes correspond to linear wavepackets. For all but the lowest frequencies close agreement is obtained for the spatial amplification, up to the end of the potential core. The radial shapes of the linear PSE solutions also agree with the experimental results over the same region. The results suggests that, despite the broadband character of the turbulence, the evolution of Strouhal numbers $0. 3\leq St\leq 0. 9$ and azimuthal modes 0 and 1 can be modelled as linear wavepackets, and these are associated with the sound radiated to low polar angles.

The development of microstructured fibres offers the prospect of improved fibre sensing for low refractive index materials such as liquids and gases. A number of approaches are possible. Here we present a new approach to evanescent field sensing, in which both core and cladding are microstructured. The fibre was fabricated and tested, and simulations and experimental results are shown in the visible region to demonstrate the utility of this approach for sensing.

Metamodeling for the nucleonic equation of state (EOS), inspired from a Taylor expansion around the saturation density of symmetric nuclear matter, is proposed and parameterized in terms of the empirical parameters. The present knowledge of nuclear empirical parameters is first reviewed in order to estimate their average values and associated uncertainties, and thus defining the parameter space of the metamodeling. They are divided into isoscalar and isovector types, and ordered according to their power in the density expansion. The goodness of the metamodeling is analyzed against the predictions of the original models. In addition, since no correlation among the empirical parameters is assumed a priori, all arbitrary density dependences can be explored, which might not be accessible in existing functionals. Spurious correlations due to the assumed functional form are also removed. This meta-EOS allows direct relations between the uncertainties on the empirical parameters and the density dependence of the nuclear equation of state and its derivatives, and the mapping between the two can be done with standard Bayesian techniques. A sensitivity analysis shows that the more influential empirical parameters are the isovector parameters ${L}_{\mathrm{sym}}$ and ${K}_{\mathrm{sym}}$, and that laboratory constraints at supersaturation densities are essential to reduce the present uncertainties. The present metamodeling for the EOS for nuclear matter is proposed for further applications in neutron stars and supernova matter.

Characteristics extracted from the training datasets of classification problems have proven to be effective predictors in a number of meta-analyses. Among them, measures of classification complexity can be used to estimate the difficulty in separating the data points into their expected classes. Descriptors of the spatial distribution of the data and estimates of the shape and size of the decision boundary are among the known measures for this characterization. This information can support the formulation of new data-driven pre-processing and pattern recognition techniques, which can in turn be focused on challenges highlighted by such characteristics of the problems. This article surveys and analyzes measures that can be extracted from the training datasets to characterize the complexity of the respective classification problems. Their use in recent literature is also reviewed and discussed, allowing to prospect opportunities for future work in the area. Finally, descriptions are given on an R package named Extended Complexity Library (ECoL) that implements a set of complexity measures and is made publicly available.