The relationship between fragility, configurational entropy and the potential energy landscape of glass forming liquids

Glass is a microscopically disordered, solid form of matter that results when a fluid is cooled or compressed in such a fashion that it does not crystallise. Almost all types of materials are capable of glass formation -- polymers, metal alloys, and molten salts, to name a few. Given such diversity, organising principles which systematise data concerning glass formation are invaluable. One such principle is the classification of glass formers according to their fragility\cite{fragility}. Fragility measures the rapidity with which a liquid's properties such as viscosity change as the glassy state is approached. Although the relationship between features of the energy landscape of a glass former, its configurational entropy and fragility have been analysed previously (e. g.,\cite{speedyfr}), an understanding of the origins of fragility in these features is far from being well established. Results for a model liquid, whose fragility depends on its bulk density, are presented in this letter. Analysis of the relationship between fragility and quantitative measures of the energy landscape (the complicated dependence of energy on configuration) reveal that the fragility depends on changes in the vibrational properties of individual energy basins, in addition to the total number of such basins present, and their spread in energy. A thermodynamic expression for fragility is derived, which is in quantitative agreement with {\it kinetic} fragilities obtained from the liquid's diffusivity.Comment: 8 pages, 3 figure

Energy landscape of a Lennard-Jones liquid: Statistics of stationary points

Molecular dynamics simulations are used to generate an ensemble of saddles of the potential energy of a Lennard-Jones liquid. Classifying all extrema by their potential energy u and number of unstable directions k, a well defined relation k(u) is revealed. The degree of instability of typical stationary points vanishes at a threshold potential energy, which lies above the energy of the lowest glassy minima of the system. The energies of the inherent states, as obtained by the Stillinger-Weber method, approach the threshold energy at a temperature close to the mode-coupling transition temperature Tc.Comment: 4 RevTeX pages, 6 eps figures. Revised versio

Analytical model for erosion behaviour of impacted fly-ash particles on coal-fired boiler components

Fly ash particles entrained in the flue gas from boiler furnaces in coal-fired power stations can cause serious erosive wear on steel surfaces along the flow path. Such erosion can significantly reduce the operational life of the boiler components. A mathematical model embodying the mechanisms of erosion on behaviour, has been developed to predict erosion rates of coal-fired boiler components at different temperatures.Various grades of steels used in fabrication of boiler components and published data pertaining to boiler fly ash have been used for the modelling. The model incorporates high temperature tensile properties of the target metal surface at room and elevated temperatures and has been implemented in an user-interactive in-house computer code (EROSIM–1), to predict the erosion rates of various grades of steel. Predictions have been found to be in good agreement with the published data. The model is calibrated with plant and experimental data generated from a high temperature air-jet erosion-testing facility. It is hoped that the calibrated model will be useful for erosion analysis of boiler components

An Optimized Deep Learning Based Optimization Algorithm for the Detection of Colon Cancer Using Deep Recurrent Neural Networks

Colon cancer is the second leading dreadful disease-causing death. The challenge in the colon cancer detection is the accurate identification of the lesion at the early stage such that mortality and morbidity can be reduced. In this work, a colon cancer classification method is identified out using Dragonfly-based water wave optimization (DWWO) based deep recurrent neural network. Initially, the input cancer images subjected to carry a pre-processing, in which outer artifacts are removed. The pre-processed image is forwarded for segmentation then the images are converted into segments using Generative adversarial networks (GAN). The obtained segments are forwarded for attribute selection module, where the statistical features like mean, variance, kurtosis, entropy, and textual features, like LOOP features are effectively extracted. Finally, the colon cancer classification is solved by using the deep RNN, which is trained by the proposed Dragonfly-based water wave optimization algorithm. The proposed DWWO algorithm is developed by integrating the Dragonfly algorithm and water wave optimization

Anisotropic Local Stress and Particle Hopping in a Deeply Supercooled Liquid

The origin of the microscopic motions that lead to stress relaxation in deeply supercooled liquid remains unclear. We show that in such a liquid the stress relaxation is locally anisotropic which can serve as the driving force for the hopping of the system on its free energy surface. However, not all hopping are equally effective in relaxing the local stress, suggesting that diffusion can decouple from viscosity even at local level. On the other hand, orientational relaxation is found to be always coupled to stress relaxation.Comment: 4 pages, 3 figure

Stability, Gain, and Robustness in Quantum Feedback Networks

This paper concerns the problem of stability for quantum feedback networks. We demonstrate in the context of quantum optics how stability of quantum feedback networks can be guaranteed using only simple gain inequalities for network components and algebraic relationships determined by the network. Quantum feedback networks are shown to be stable if the loop gain is less than one-this is an extension of the famous small gain theorem of classical control theory. We illustrate the simplicity and power of the small gain approach with applications to important problems of robust stability and robust stabilization.Comment: 16 page

The Glass Transition and Liquid-Gas Spinodal Boundaries of Metastable Liquids

A liquid can exist under conditions of thermodynamic stability or metastability within boundaries defined by the liquid-gas spinodal and the glass transition line. The relationship between these boundaries has been investigated previously using computer simulations, the energy landscape formalism, and simplified model calculations. We calculate these stability boundaries semi-analytically for a model glass forming liquid, employing accurate liquid state theory and a first-principles approach to the glass transition. These boundaries intersect at a finite temperature, consistent with previous simulation-based studies.Comment: Minor text revisions. Fig.s 4, 5 update

Liquid Limits: The Glass Transition and Liquid-Gas Spinodal Boundaries of Metastable Liquids

The liquid-gas spinodal and the glass transition define ultimate boundaries beyond which substances cannot exist as (stable or metastable) liquids. The relation between these limits is analyzed {\it via} computer simulations of a model liquid. The results obtained indicate that the liquid - gas spinodal and the glass transition lines intersect at a finite temperature, implying a glass - gas mechanical instability locus at low temperatures. The glass transition lines obtained by thermodynamic and dynamic criteria agree very well with each other.Comment: 5 pages, 4 figures, to appear in Phys. Rev. Let