This paper describes an investigation of the possible benefits from wing optimisation in improving the performance of Micro Air Vehicles (MAVs). As an example we study the Avion (3.64 kg mass, 1.60 m span), being designed at the CSIR National Aerospace Laboratories (NAL), Bengaluru. The optimisation is first carried out using the methodology described by Rakshith \emph{et al.} (using an in\textendash house software PROWING), developed for large transport aircraft, with certain modifications to adapt the code to the special features of the MAV. The chief among such features is the use of low Reynolds number aerofoils with significantly different aerodynamic characteristics on a small MAV. These characteristics are taken from test data when available, and/or estimated by the XFOIL code of Drela. A total of 8 optimisation cases are studied for the purpose, leading to 6 different options for new wing planforms (and associated twist distributions along the wing span) with an improved performance. It is found that the improvements in drag coefficient using the PROWING code are about 5%. However, by allowing the operating lift coefficient $C_L$ to float within a specified range, drag bucket characteristics of the Eppler E423 aerofoil used on Avion can be exploited to improve the endurance, which is a major performance parameter for Avion. Thus, compared to the control wing $W_0$ (with operating point at $C_L$ =0.7) used in the preliminary design, permitting a variation of $C_L$ over a range of $\pm$ 10% is shown to enhance the endurance of wing $W_4$ by 18.6%, and of wing $W_{6}$ with a permitted $C_L$ range of $\pm$ 50% by 39.2%. Apart from the philosophy of seeking optimal operating conditions for a given configuration, the advantages of optimising design parameters such as washout of a simple wing proposed in the preliminary design stage, is also demonstrated.

Results for the kinetics of vapor-liquid transitions, following temperature quenches with different densities, are presented from the molecular dynamics simulations of a Lennard-Jones system. For critical density, bicontinuous liquid and vapor domains are observed which grow with time obeying the prediction of hydrodynamic mechanism. On the other hand, for quenches with density significantly below the critical one, phase separation progresses via nucleation and growth of liquid droplets. In the latter case, Brownian diffusion and collision mechanism for the droplet growth is confirmed. We also discuss the possibility of inter-droplet interaction leading to a different amplitude in the growth law. Arguments for faster growth, observed at early time, are also provided.

We study the evolutionary dynamics of a maladapted population of self-replicating sequences on strongly correlated fitness landscapes. Each sequence is assumed to be composed of blocks of equal length and its fitness is given by a linear combination of four independent block fitnesses. A mutation affects the fitness contribution of a single block leaving the other blocks unchanged and hence inducing correlations between the parent and mutant fitness. On such strongly correlated fitness landscapes, we calculate the dynamical properties like the number of jumps in the most populated sequence and the temporal distribution of the last jump which is shown to exhibit a inverse square dependence as in evolution on uncorrelated fitness landscapes. We also obtain exact results for the distribution of records and extremes for correlated random variables.

We propose a physics-based regularization technique for function learning, inspired by statistical mechanics. By drawing an analogy between optimizing the parameters of an interpolator and minimizing the energy of a system, we introduce corrections that impose constraints on the lower-order moments of the data distribution. This minimizes the discrepancy between the discrete and continuum representations of the data, in turn allowing to access more favorable energy landscapes, thus improving the accuracy of the interpolator. Our approach improves performance in both interpolation and regression tasks, even in high-dimensional spaces. Unlike traditional methods, it does not require empirical parameter tuning, making it particularly effective for handling noisy data. We also show that thanks to its local nature, the method offers computational and memory efficiency advantages over Radial Basis Function interpolators, especially for large datasets.

A bilayer system comprising a Kondo insulator coupled to a simple metal (KI-M) is considered. Employing the framework of dynamical mean field theory, the model system is shown to exhibit a surface of quantum critical points (QCPs), that separates a Kondo screened, Fermi liquid phase from a local moment, Mott insulating phase. The quantum critical nature of these Mott transitions is characterized by the vanishing of (a) the coherence scale on the Fermi liquid side, and (b) the Mott gap on the MI side. In contrast to the usual `large to small' Fermi surface (FS) QCPs in heavy fermion systems, the bilayer KI-M system exhibits a complete FS destruction.

Perturbative schemes utilizing a spectral moment expansion are well known and extensively used for investigating the physics of model Hamiltonians and real material systems. The advantages they offer, in terms of being computationally inexpensive, with real frequency output at zero and finite temperatures, compensate for their deficiencies and offer a quick, qualitative analysis of the system behavior. In this work, we have developed a method, that can be classified as a multi-orbital iterative perturbation theory (MO-IPT) to study N-fold degenerate and non degenerate Anderson impurity models. As applications of the solver, we have combined the method with dynamical mean field theory to explore lattice models like the single orbital Hubbard model, covalent band insulator and the multi-orbital Hubbard model for density-density type interactions in different parameter regimes. The Hund's coupling effects in case of multiple orbitals is also studied. The limitations and quality of results are gauged through extensive comparison with data from the numerically exact continuous time quantum Monte Carlo method (hybridization expansion CTQMC). In general we observe that the agreement with CTQMC results gets better as we move away from particle-hole symmetry. We have integrated MO-IPT with density functional theory based electronic structure methods to study real material systems. As a test case, we have studied the classic, strongly correlated electronic material, SrVO$_3$. A comparison of density of states and photo emission spectrum (PES) with results obtained from different impurity solvers and experiments yields good agreement.

The phenomenon of Anderson localization in various disordered media has sustained significant interest over many decades. Specifically, the Anderson localization of phonons has been viewed as a potential mechanism for creating fascinating thermal transport properties in materials. However, despite extensive work, the influence of the vector nature of phonons on the Anderson localization transition has not been well explored. In order to achieve such an understanding, we extend a recently developed phonon dynamical cluster approximation (DCA) and its typical medium variant (TMDCA) to investigate spectra and localization of multi-branch phonons in the presence of pure mass disorder. We validate the new formalism against several limiting cases and exact diagonalization results. A comparison of results for the single-branch versus multi-branch case shows that the vector nature of the phonons does not affect the Anderson transition of phonons significantly. The developed multi-branch TMDCA formalism can be employed for studying phonon localization in real materials.

The entrainment of ambient fluid into a turbulent shear flow has been a topic of wide interest for several decades. To estimate the entrainment of ambient fluid into turbulent jet, it is essential to define the boundary of the jet. The question arises as to what should be the appropriate criterion to determine the edge of the turbulent jet. From the present DNS simulations, we observe that there is a need to define two boundaries for the turbulent jet, namely, the Rotational/Irrotational (R/IR) interface termed here as "Outer boundary" and the Turbulent/Non-Turbulent (T/NT) interface as "Inner boundary". The main aim of the present paper is to identify the need for defining the two boundaries for the jet. We also present some interesting observations of the jet flow, essentially on self similarity and self preservation.

With a view towards optimizing gas storage and separation in crystalline and disordered nanoporous carbon-based materials, we use ab initio density functional theory calculations to explore the effect of chemical functionalization on gas binding to exposed edges within model carbon nanostructures. We test the geometry, energetics, and charge distribution of in-plane and out-of-plane binding of CO2 and CH4 to model zigzag graphene nanoribbons edge-functionalized with COOH, OH, NH2, H2PO3, NO2, and CH3. Although different choices for the exchange-correlation functional lead to a spread of values for the binding energy, trends across the functional groups are largely preserved for each choice, as are the final orientations of the adsorbed gas molecules. We find binding of CO2 to exceed that of CH4 by roughly a factor of two. However, the two gases follow very similar trends with changes in the attached functional group, despite different molecular symmetries. Our results indicate that the presence of NH2, H2PO3, NO2, and COOH functional groups can significantly enhance gas binding with respect to a hydrogen-passivated edge, making the edges potentially viable binding sites in materials with high concentrations of edge carbons. To first order, in-plane binding strength correlates with the larger permanent and induced dipole moments on these groups. Implications for tailoring carbon structures for increased gas uptake and improved CO2/CH4 selectivity are discussed.

Perturbative schemes utilizing a spectral moment expansion are well known and extensively used for investigating the physics of model Hamiltonians and real material systems. The advantages they offer, in terms of being computationally inexpensive, with real frequency output at zero and finite temperatures, compensate for their deficiencies and offer a quick, qualitative analysis of the system behavior. In this work, we have developed a method, that can be classified as a multi-orbital iterative perturbation theory (MO-IPT) to study N-fold degenerate and non degenerate Anderson impurity models. As applications of the solver, we have combined the method with dynamical mean field theory to explore lattice models like the single orbital Hubbard model, covalent band insulator and the multi-orbital Hubbard model for density-density type interactions in different parameter regimes. The Hund's coupling effects in case of multiple orbitals is also studied. The limitations and quality of results are gauged through extensive comparison with data from the numerically exact continuous time quantum Monte Carlo method (hybridization expansion CTQMC). In general we observe that the agreement with CTQMC results gets better as we move away from particle-hole symmetry. We have integrated MO-IPT with density functional theory based electronic structure methods to study real material systems. As a test case, we have studied the classic, strongly correlated electronic material, SrVO$_3$. A comparison of density of states and photo emission spectrum (PES) with results obtained from different impurity solvers and experiments yields good agreement.

Prediction of critical temperature $(T_c)$ of a superconductor remains a significant challenge in condensed matter physics. While the BCS theory explains superconductivity in conventional superconductors, there is no framework to predict $T_c$ of unconventional, higher $T_{c}$ superconductors. Quantum Structure Diagrams (QSD) were successful in establishing structure-property relationship for superconductors, quasicrystals, and ferroelectric materials starting from chemical composition. Building on the QSD ideas, we demonstrate that the principal component analysis of superconductivity data uncovers the clustering of various classes of superconductors. We use machine learning analysis and cleaned databases of superconductors to develop predictive models of $T_c$ of a superconductor using its chemical composition. Earlier studies relied on datasets with inconsistencies, leading to suboptimal predictions. To address this, we introduce a data-cleaning workflow to enhance the statistical quality of superconducting databases by eliminating redundancies and resolving inconsistencies. With this improvised database, we apply a supervised machine learning framework and develop a Random Forest model to predict superconductivity and $T_c$ as a function of descriptors motivated from Quantum Structure Diagrams. We demonstrate that this model generalizes effectively in reasonably accurate prediction of $T_{c}$ of compounds outside the database. We further employ our model to systematically screen materials across materials databases as well as various chemically plausible combinations of elements and predict $\mathrm{Tl}_{5}\mathrm{Ba}_{6}\mathrm{Ca}_{6}\mathrm{Cu}_{9}\mathrm{O}_{29}$ to exhibit superconductivity with a $T_{c}$ $\sim$ 105 K. Being based on the descriptors used in QSD's, our model bypasses structural information and predicts $T_{c}$ merely from the chemical composition.

The glass transition is the most enduring grand-challenge problem in contemporary condensed matter physics. Here, we review the contribution of colloid experiments to our understanding of this problem. First, we briefly outline the success of colloidal systems in yielding microscopic insights into a wide range of condensed matter phenomena. In the context of the glass transition, we demonstrate their utility in revealing the nature of spatial and temporal dynamical heterogeneity. We then discuss the evidence from colloid experiments in favor of various theories of glass formation that has accumulated over the last two decades. In the next section, we expound on the recent paradigm shift in colloid experiments from an exploratory approach to a critical one aimed at distinguishing between predictions of competing frameworks. We demonstrate how this critical approach is aided by the discovery of novel dynamical crossovers within the range accessible to colloid experiments. We also highlight the impact of alternate routes to glass formation such as random pinning, trajectory space phase transitions and replica coupling on current and future research on the glass transition. We conclude our review by listing some key open challenges in glass physics such as the comparison of growing static lengthscales and the preparation of ultrastable glasses, that can be addressed using colloid experiments.

We analyse the stability of viscoelastic Dean flow (flow of an elastic fluid through a curved two-dimensional channel, driven by an azimuthal pressure gradient) in the absence of fluid inertia. This configuration is well known to exhibit a hoop-stress-driven `purely elastic' instability (referred to henceforth as the hoop-stress mode -- `HSM') on account of the base-flow streamline curvature. The objective of this study is to demonstrate the existence and importance of a distinct elastic instability in this flow configuration, which is not driven by hoop-stresses, but instead is a continuation of a novel `centre-mode' (CM) instability recently identified in rectilinear shear flows. We use both the Oldroyd-B and FENE-P models to map out parameter regimes in the $W\!i$--$\epsilon$--$\beta$ space where the aforementioned instabilities are present. Here, $W\!i$ is a suitably defined Weissenberg number that characterizes fluid elasticity, $\beta$ is the ratio of solvent to total solution viscosity, and $\epsilon$ is the ratio of the gap (channel) width to the radius of curvature. For FENE-P model, decreasing the finite extensibility parameter $L$ has opposing effects on the HSM and CM instabilities -- stabilising the former, but destabilising the latter. In the dilute solution regime ($\beta > 0.95$), and for realistic values of $L \sim O(100)$, corresponding to polymer molecular weights of $O(10^{5-6})$g/mol, the CM remains the most unstable mode for $\epsilon \leq 0.25$, rendering it potentially relevant to the onset of elastic turbulence in the flow of such polymer solutions through curved channels.

The nonequilibrium dynamic phase transition, in the kinetic Ising model in presence of an oscillating magnetic field, has been studied both by Monte Carlo simulation and by solving numerically the mean field dynamic equation of motion for the average magnetisation. In both the cases, the Debye 'relaxation' behaviour of the dynamic order parameter has been observed and the 'relaxation time' is found to diverge near the dynamic transition point. The Debye relaxation of the dynamic order parameter and the power law divergence of the relaxation time have been obtained from a very approximate solution of the mean field dynamic equation. The temperature variation of appropiately defined 'specific-heat' is studied by Monte Carlo simulation near the transition point. The specific-heat has been observed to diverge near the dynamic transition point.

Glass-forming liquids are broadly classified as being fragile or strong, depending on the deviation from Arrhenius behavior of their relaxation times. A fragile to strong crossover is observed or inferred in liquids like water and silica, and more recently also in metallic glasses and phase change alloys, leading to the expectation that such a crossover is more widely realised among glass formers. We investigate computationally the well-studied Kob-Andersen model, accessing temperatures well below the mode coupling temperature $T_{MCT}$. We find that relaxation times exhibit a crossover in dynamics around $T_{MCT}$, and discuss whether it bears characteristics of the fragile to strong crossover. Several aspects of dynamical heterogeneity exhibit behavior mirroring the dynamical crossover, whereas thermodynamic quantities do not. In particular, the Adam-Gibbs relation describing the relation between relaxation times and configurational entropy continues to hold below the dynamical crossover, when anharmonic corrections to the vibrational entropy are included.

Polymer melts with chains undergoing reversible crosslinking have distinctively favorable dynamic properties, e.g., self healing and reprocessability. In these situations there are two relevant elementary time scales: the segmental and the sticker association times. A convenient framework to model these situations is the sticky Rouse model and here we perform hybrid moleculear dynamics (MD) Monte Carlo (MC) simulations to examine its relevance. In agreement with the underpinning idea discussed above we find that reversibly crosslinked chains show two distinct modes of relaxation behavior depending on the magnitude of bond lifetimes. For bond lifetimes shorter than the chain end-to-end relaxation time, the polymers exhibit essentially Rouse like dynamics, but with an apparently increased local friction relative to the non-sticky analog. For longer bond lifetimes, the chains exhibit two modes of relaxation: the faster mode is independent of bond lifetime, but the slower mode is controlled by it. However, these slower mode results are not consistent with the predictions of the sticky Rouse model. Our Rouse mode analysis as a function of chain length, N, imply that this is likely a result of the relatively short chain length employed, but they nevertheless suggest that theories need to include these small chain effects if they are to be relevant to experimental systems with short chains following Rouse dynamics.

Earths lower mantle extending from 670 to 2,990 km deep is predominantly composed of a perovskite-type (Mg,Fe)SiO3 phase1,2. The perovskite phase undergoes a structural phase transition to a post-perovskite phase responsible for D" layer seismic discontinuity2,3 at about 2690 km depth in the lowermost region of the lower mantle. However, structural basis of other seismic discontinuities occurring in the upper region of the lower mantle (700 km to 1,200 km deep) remains unexplained4-7, as no apparent change in the crystal symmetry of the orthorhombic perovskite phase has been reported5. We present here unambiguous evidence for a non-apparent isostructural phase transition8 in the stable orthorhombic perovskite phase of CaTiO3 which may have relevance to phase transitions in the perovskite phase of (Mg,Fe)SiO3 also, as both the compounds have similar structure, tolerance factor and thermochemical properties9-11. Our results are based on the analysis of neutron powder diffraction patterns using Rietveld and mode crystallography techniques and are supported by density functional and Landau theory calculations. The present results on CaTiO3 would encourage search for isostructural phase transition in the perovskite phase of (Mg,Fe)SiO3 that may provide clue to the unexplained geophysical phenomena in the upper part of the earths lower mantle.

A modal stability analysis shows that pressure-driven pipe flow of an Oldroyd-B fluid is linearly unstable to axisymmetric perturbations, in stark contrast to its Newtonian counterpart which is linearly stable at all Reynolds numbers. The dimensionless groups that govern stability are the Reynolds number, the elasticity number, and the ratio of solvent to solution viscosity. The unstable mode has a phase speed close to the base-state maximum over the entire unstable region in the relevant parameter space, implying that the unstable mode belongs to a class of viscoelastic center modes. Unlike the Newtonian transition which is dominated by nonlinear processes, the linear instability discussed here could be very relevant to the onset of turbulence in viscoelastic pipe flows. The prediction of an instability is, in fact, consistent with several experimental studies on pipe flow of polymer solutions, ranging from previous reports of early turbulence to the more recent discovery of elasto-inertial turbulence. The instability identified in this study comprehensively dispels the prevailing notion of pipe flow of viscoelastic fluids being linearly stable in the Reynolds-Weissenberg plane, marking a possible paradigm shift in our understanding of transition in rectilinear viscoelastic shearing flows.

Nonequilibrium calculations in the presence of an electric field are usually performed in a gauge, and need to be transformed to reveal the gauge-invariant observables. In this work, we discuss the issue of gauge invariance in the context of time-resolved angle-resolved pump/probe photoemission. If the probe is applied while the pump is still on, one must ensure that the calculations of the observed photocurrent are gauge invariant. We also discuss the requirement of the photoemission signal to be positive and the relationship of this constraint to gauge invariance. We end by discussing some technical details related to the perturbative derivation of the photoemission spectra, which involve processes where the pump pulse photoexcites electrons due to nonequilibrium effects.