Mono-chloro-substituted m-dinitrobenzene compound as cathode materials magnesium battery

The performance of mono-chloro-substituted m-dinitrobenzene compounds in magnesium battery is reported here. While the operating voltage is improved, the current efficiency is lowered by the chloro-substituents. The influence is explained taking into account inductive and mesomeric effects of the substituent

Structural and Functional Role of Proline Residues in Fibroblast Growth Factor-1

Additional file 4: Figure S2. Electrolyte leakage of MsK8 cells (A) upon inoculation with Phytophthora zoospores (zsp) or (B) treatment with zoospore exudate (ZE) measured as conductivity at various time points. Colors of the bars represent a specific species and/or strain as indicated and correspond to the colors in Fig. 2. Error bars represent standard deviation (n = 3)

Micromechanical modelling of ductile damage: from single crystals to polycrystals

Mención Internacional en el título de doctorFor more than six decades, improving the strength and ductility of industrially important materials has been in the focus of research. Besides economic reasons, safety issues have driven research and development in this field. For the purpose of safety, it is imperative to understand the failure behaviour of ductile materials, as ductile materials are commonly used in protective structures. It is well known that major failure mode for ductile materials is through void nucleation, growth and void coalescence. In structural ductile materials voids nucleate at inclusions and second-phase particles by decohesion of the particle–matrix interface or by particle cracking. The presence of voids can have drastic implications at the macroscopic level including strong material softening and incipient fracture. Significant efforts have been made over the years to describe the plastic behavior of isotropic and anisotropic ductile materials. Numerous investigations, in the last decades, have been dedicated to the study of ductile failure, leading to a deeper knowledge on the factors influencing the ductile process. This doctoral thesis contributes to the understanding of the key role played by material anisotropy and stress state on the growth of voids in single crystals, bi-crystals and polycrystals using numerical and experimental methods. Using a numerical approach, void growth and morphology evolution in fcc single crystals and bi-crystals are investigated using crystal plasticity finite element method. For that purpose, representative volume element of single crystals and bi-crystals are considered in the analysis. Fully periodic boundary conditions are prescribed in the representative volume element and macroscopic stress triaxiality and Lode parameter are kept constant during the whole deformation process. Simulations are performed to study the implications of triaxiality, Lode parameter and crystallographic orientation on slip mechanism, hardening and hence void evolution. In the bi-crystal case, a void at the grain boundary is considered in the analysis. Grain boundary is assumed initially perpendicular/coaxial with the straight sides of the cell. Three different pairs of crystal orientations characterized as hard-hard, soft-soft and soft-hard has been employed for modelling the mechanical response of the bi-crystal. The impact of void presence and its growth on the heterogeneity of lattice rotation and resulting grain fragmentation in neighbouring areas is analysed and discussed. On the other hand and using an experimental approach, void growth behaviour in pure Aluminium polycrystals with pre-drilled holes are investigated in this work. By varying the hole diameter and position of the holes, three different types of specimens are defined and considered for investigation. Using in-situ tensile test coupled with scanning electron microscope, uni axial tensile tests are performed at constant low strain rate. The specimens are analysed with the help of EBSD, DIC and high resolution SEM images. Interrelation between hole diameter, distance between holes, local orientation of the grains and grain size on void growth and final failure of the material are analysed and discussed.The research leading to the results reported in this doctoral thesis has received funding from the European Union's Horizon2020 Programme (Excellent Science, Marie Skłodowska-Curie Actions) under REA grant agreement 675602 (Project OUTCOME).Programa de Doctorado en Ingeniería Mecánica y de Organización Industrial por la Universidad Carlos III de MadridPresidente: Francisco Javier Llorca Martínez.- Secretario: Kim Lau Nielsen .- Vocal: Stanislaw Stupkiewic

Standardisation in the field of ferro alloys

Indian Standards Institution has set up a separate Sectional Committee known as Ferro Alloys Sectional Commi-ttee, SMDC 8 in late fifties due to the important role played by the Ferro Alloys in the field of steel industry and in the economy of the country. Standardisation work done by this committee so far, is outlined and some of the important standards on ferro alloys are discussed. The work done by the Methods of Sampling Sectional Committee, SMDC 4 on sampling of form alloys and by the Methods of Chemical Analysis Sectional Committee, SMDC 2 on Chemical Analysis of Ferro Alloys is also discussed. Standards prepared by the Technical Committee TC 132 of Internati-onal Organisation for Standardisation (ISO) on Ferro Alloys are also outlined in this paper

Oxidation Resistant Coatings on Microcelluar Carbon Foam using Simple Scalable Techniques

Carbon foam has many applications in the fields of thermal management, net-shape composites and electronic cooling due to its porous structure, low density, electrical and thermal conductivities. However it is prone to oxidation at high temperatures in air. Whereas some previous studies have reported oxidation protective coatings on other carbon structures such as graphite parts and fibers, there is very limited work on foam. Moreover, earlier methods have used vapor phase techniques such as Plasma Vapor Deposition (PVD) and Chemical Vapor Deposition (CVD). There is no known study involving such coatings using simple scalable liquid phase method. This thesis reports our results on such coatings obtained on carbon foam. Boron Nitride was chosen as the coating material. Several solvents and processes were investigated. Finally a two step process using PVP binder in alcohol-based solution is found to be most effective. Unlike other available methods this technique does not involve toxic precursors or by-products. This method is simple and can be obtained at atmospheric pressure. Different coating combinations using various particle sizes were applied and their surface morphologies were studied using SEM (Scanning Electron Microscopy) and FESEM (Field Emission Scanning Electron Spectroscopy). It was observed that coating formed using 1μ BN followed by 0.7μ size BN particles has the best performance so far. The surface chemistry of this coating was studied using X-ray Photo Spectroscopy (XPS) and found to be that of pure BN after heat treatment. This coating was tested on several grades of aerospace foams having different porosities and cell sizes. The testing shows that this layer enhances the oxidation resistance of all foams to a certain extent. However it is most effective on the foams that have ridged ligaments compared to those having smooth ligaments. On carbon foams having high surface roughness this layer could suppress oxidation even at 800 C and enhance the survivability by 333%. This coating approach therefore shows promise as a scalable, environmentally friendly way of inhibiting oxidation in porous carbon structures

Advancing Near Surface Soil Moisture Measurements Using Robotics, Automation, and Remote Sensing

Near-surface soil moisture, or the water content within the soil, is important for understanding the interactions between land and the atmosphere, and for monitoring plants in agricultural settings. However, soil moisture can be highly variable within the same field and varies considerably with time. The challenge involved with measuring soil moisture is that traditional techniques that rely on obtaining large samples are labor and time-intensive, especially for large fields. Developments in sensor technologies have allowed users to record the soil moisture regularly at the points where the sensors are installed. However, to understand how soil moisture changes across a field from sensors installed at single points, there needs to be a large number of sensors installed, which are not easily moved and are expensive. Remote sensing approaches that use imagery from satellites and drones have been used to develop soil moisture prediction models. Developing these models requires measurements from the field to validate them. However, collecting data from large fields on a regular basis is challenging. Also, remote sensing models using machine learning techniques tend to be “black box models”, or models that do not reveal any information about their inner workings and may not have any physical significance to soil moisture. To address the challenges presented here, a first-of-its-kind, cost-effective fully autonomous drone payload was developed to measure near-surface soil moisture. A new validation technique for the payload sensor measurements was developed that only relies on two pieces of data–depth of insertion and sensor signal–to obtain a calibrated moisture content. Finally, a soil moisture prediction model was developed using the soil line concept, which is a linear relationship between bare soil reflectance observed in two different wavebands, combined with machine learning models to add physical meaning to the models. The three techniques developed in this dissertation address the challenges in near-surface soil moisture measurements and represent significant progress toward automating critical data collection across large fields in agriculture

A Compiler-based Framework For Automatic Extraction Of Program Skeletons For Exascale Hardware/software Co-design

The design of high-performance computing architectures requires performance analysis of largescale parallel applications to derive various parameters concerning hardware design and software development. The process of performance analysis and benchmarking an application can be done in several ways with varying degrees of fidelity. One of the most cost-effective ways is to do a coarse-grained study of large-scale parallel applications through the use of program skeletons. The concept of a “program skeleton” that we discuss in this paper is an abstracted program that is derived from a larger program where source code that is determined to be irrelevant is removed for the purposes of the skeleton. In this work, we develop a semi-automatic approach for extracting program skeletons based on compiler program analysis. We demonstrate correctness of our skeleton extraction process by comparing details from communication traces, as well as show the performance speedup of using skeletons by running simulations in the SST/macro simulator. Extracting such a program skeleton from a large-scale parallel program requires a substantial amount of manual effort and often introduces human errors. We outline a semi-automatic approach for extracting program skeletons from large-scale parallel applications that reduces cost and eliminates errors inherent in manual approaches. Our skeleton generation approach is based on the use of the extensible and open-source ROSE compiler infrastructure that allows us to perform flow and dependency analysis on larger programs in order to determine what code can be removed from the program to generate a skeleton

Crack propagation in TRIP assisted steels modeled by crystal plasticity and cohesive zone method

The influence of transformation induced plasticity (TRIP) on materials mechanical behaviours, as well as failure phenomena including crack propagation and phase boundary debonding in multiphase steels (e.g. dual phase steels, TRIP steels) are studied by using an advanced crystal plasticity finite element method. We have coupled the crystal plasticity model Ma and Hartmaier (2015), which explicitly considers elastic-plastic deformation of ferrite and austenite, austenite-martensite phase, with a cohesive zone model designed for crack propagation, to study the deformations of several representative microstructural volume elements (RVE). Results shows that, the transformation induced plasticity enhances materials strength and ductility, hinders crack propagation and influences interface debonding. Furthermore, the martensitic transformation kinetics in TRIP steels was found depending on the crystallographic orientation and the stress state of a retained austenite grain. The current simulation results helps to investigate and design multiphase steels with improved mechanical properties

AN OVERVIEW OF COLORECTAL CANCER: IMPLICATION OF TWO MEDICINAL PLANTS IN THEIR TREATMENT

Nowadays, cancer is one of the most common diseases in humans. Among all types, colorectal cancer (CRC) is one of the most serious types diagnosed in men after lung and prostate cancer while in women it occupies the second position after breast cancer worldwide. The risk factors such as obesity, sedentary lifestyle, bad nutritional habits (high in fats and proteins), smoking, and progressive aging are the cause of CRC. The acquisition of abnormal mutations leads to a consisting of many different arrangements of events during the tumor development process. Over the years, different approaches have been employed, in the treatment of cancer. These include chemotherapy, radiotherapy, surgery, and immunotherapy. Chemotherapy is routinely used for cancer treatment, but the toxicity of chemotherapeutics on healthy cells of the human body is obvious. This is the reason for discovering the new, natural origin, substances with potential cytostatic effects and less toxic side effects on the healthy cells. Medicinal plants have a special place in the management of cancer. Numerous cancer research studies have been conducted using traditional medicinal plants to discover new therapeutic agents with fewer side effects. In this review, we are describing two medicinal plants such as Actiniopteris radiata (Sw.) Link (Mayurashikha) and Terminalia pallida Brandis (Tella karaka) (endemic plant) which are available immensely in Chittoor District are used till today by the traditional herbal practitioners, tribal people is near to Talakona forest and Ayurvedic people for various diseases and also for CRC

Early prediction of diabetes diagnosis using hybrid classification techniques

Diabetes can be mentioned as one of the most lethal and constant sicknesses that may cause an arise in the glucose levels. Design and development of performance efficient diagnosis tool is important and plays a vigorous role in initial prediction of disease and help medical experts to start with suitable treatment or medication. The insulin produced by pancreases in the subject’s body will be affected leading to several dysfunctionalities to various body organs such as kidney, heart eyes and nervous system with their normal functionalities. Hence, preliminary stage detection with proper care and medication could reduce the risk of these problems. In the area of medicine to discover patient’s data as well as to attain a predictive model or a set of rules, classification techniques have been continuously used. This study helped diagnose diabetes by selecting three important artificial intelligence (AI) techniques namely the optimal decision tree algorithm model, Type-2 fuzzy expert system and adaptive neuro fuzzy inference system which is modified. In the present research work, a hybrid model is proposed in order to improve the classification prediction and accuracy. The Pima Indian diabetes dataset (PIDD) from machine learning repository dataset was used to carry out validation and predication of the model accuracy